xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

87f14b098265544dbf022e3f54455436deb0ad4b

24

py

Python

structures/tree/__init__.py

spencerpomme/pyalgolib

d055287caa4a779ea833c7efc305cd4f966bd841

[ "MIT" ]

null

structures/tree/__init__.py

spencerpomme/pyalgolib

d055287caa4a779ea833c7efc305cd4f966bd841

[ "MIT" ]

null

structures/tree/__init__.py

spencerpomme/pyalgolib

d055287caa4a779ea833c7efc305cd4f966bd841

[ "MIT" ]

null

# data structure module

12

23

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6.333333

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0.95

0.875

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null

0

1

0

1

0

null

0

1

0

5

e20433bc889dc0f32de713dc2c45f59d8175f0f2

481

py

Python

cachetclient/v1/__init__.py

amdemas/cachet-client

6a34ada87f99f8a3af593eefadc37a83f59827dd

[ "MIT" ]

null

cachetclient/v1/__init__.py

amdemas/cachet-client

6a34ada87f99f8a3af593eefadc37a83f59827dd

[ "MIT" ]

null

cachetclient/v1/__init__.py

amdemas/cachet-client

6a34ada87f99f8a3af593eefadc37a83f59827dd

[ "MIT" ]

null

from cachetclient.v1.client import Client # noqa from cachetclient.v1.subscribers import Subscriber # noqa from cachetclient.v1.components import Component # noqa from cachetclient.v1.component_groups import ComponentGroup # noqa from cachetclient.v1.incident_updates import IndicentUpdate # noqa from cachetclient.v1.metrics import Metric # noqa from cachetclient.v1.metric_points import MetricPoint # noqa from cachetclient.v1 import enums # noqa __version__ = '1.1.0'

40.083333

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481

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0.02619

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43.727273

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0

null

0

1

0

1

0

5

e20447ecbe22286bf4163b908e5eba34ac71394f

141

py

Python

documentation/admin.py

establishment/django-establishment

ad1d04fe9efc748e2fba5b4bc67446d2a4cf12f6

[ "CC0-1.0" ]

1

2017-04-27T19:35:42.000Z

documentation/admin.py

establishment/django-establishment

ad1d04fe9efc748e2fba5b4bc67446d2a4cf12f6

[ "CC0-1.0" ]

null

documentation/admin.py

establishment/django-establishment

ad1d04fe9efc748e2fba5b4bc67446d2a4cf12f6

[ "CC0-1.0" ]

null

from django.contrib import admin from establishment.documentation.models import DocumentationEntry admin.site.register(DocumentationEntry)

23.5

65

0.87234

15

141

8.2

0.733333

0

0.078014

141

5

66

28.2

0.946154

0

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0

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0.666667

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0.666667

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null

0

1

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1

0

1

0

5

e204c971bbb2c9c7ca0b1436805590f663181057

96

py

Python

libs/parsers/__init__.py

pullself/Compilers

590226d02e5291857cb3875bd1ed6315c37fc74e

[ "MIT" ]

null

libs/parsers/__init__.py

pullself/Compilers

590226d02e5291857cb3875bd1ed6315c37fc74e

[ "MIT" ]

null

libs/parsers/__init__.py

pullself/Compilers

590226d02e5291857cb3875bd1ed6315c37fc74e

[ "MIT" ]

null

import libs.parsers.parser import libs.parsers.constructor __all__ = ['parser', 'constructor']

19.2

35

0.78125

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96

6.454545

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0.28169

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96

4

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24

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null

1

0

1

0

null

0

1

0

5

354d0a0e8ce535bc378cbced25f44f2527b5fa3a

373

py

Python

bindings/python/capstone/__init__.py

zouguangxian/capstone

a1818520dfb37596cc5a3f19f3e04412c4c66dca

[ "BSD-3-Clause" ]

1

2021-07-06T23:36:41.000Z

bindings/python/capstone/__init__.py

zouguangxian/capstone

a1818520dfb37596cc5a3f19f3e04412c4c66dca

[ "BSD-3-Clause" ]

null

bindings/python/capstone/__init__.py

zouguangxian/capstone

a1818520dfb37596cc5a3f19f3e04412c4c66dca

[ "BSD-3-Clause" ]

null

from capstone import Cs, CsError, cs_disasm_quick, cs_version, CS_API_MAJOR, CS_API_MINOR, CS_ARCH_ARM, CS_ARCH_ARM64, CS_ARCH_MIPS, CS_ARCH_X86, CS_MODE_LITTLE_ENDIAN, CS_MODE_ARM, CS_MODE_THUMB, CS_OPT_SYNTAX, CS_OPT_SYNTAX_INTEL, CS_OPT_SYNTAX_ATT, CS_OPT_DETAIL, CS_OPT_ON, CS_OPT_OFF, CS_MODE_16, CS_MODE_32, CS_MODE_64, CS_MODE_BIG_ENDIAN, CS_MODE_MICRO, CS_MODE_N64

186.5

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0.034783

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null

0

1

0

1

0

1

0

5

359377901334427aec4295ca0684ad7dffa3d7ff

182

py

Python

server/app/api/weather/resources.py

WagnerJM/home_pod

f6a51e4956d5956a85084f637e267406f21df6df

[ "MIT" ]

null

server/app/api/weather/resources.py

WagnerJM/home_pod

f6a51e4956d5956a85084f637e267406f21df6df

[ "MIT" ]

null

server/app/api/weather/resources.py

WagnerJM/home_pod

f6a51e4956d5956a85084f637e267406f21df6df

[ "MIT" ]

null

from flask import request from flask_restful import Resource from flask_jwt_extended import get_jwt_claims, get_jwt_identity, jwt_required from app.cache import redis_client

26

78

0.840659

28

182

5.142857

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0.142857

182

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79

30.333333

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true

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null

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1

0

null

0

1

0

1

0

1

0

5

ea20af329182c07294d2c1bbed18aee79997d85a

32

py

Python

uresnet/iotools/__init__.py

NuTufts/uresnet_pytorch

3a05f2349ae1e9601d05a80384920d8a22b4bc34

[ "MIT" ]

null

uresnet/iotools/__init__.py

NuTufts/uresnet_pytorch

3a05f2349ae1e9601d05a80384920d8a22b4bc34

[ "MIT" ]

null

uresnet/iotools/__init__.py

NuTufts/uresnet_pytorch

3a05f2349ae1e9601d05a80384920d8a22b4bc34

[ "MIT" ]

null

from .iotools import io_factory

16

31

0.84375

5

32

5.2

1

0

0.125

32

1

32

0.928571

0

1

0

true

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null

0

1

0

null

0

1

0

1

0

5

ea436f37e311aec310471106ec69e43fc23e41c4

1,152

py

Python

cannlytics/lims/qc.py

mindthegrow/cannlytics

c266bc1169bef75214985901cd3165f415ad9ba7

[ "MIT" ]

7

2021-05-31T15:30:22.000Z

2022-02-05T14:12:31.000Z

cannlytics/lims/qc.py

mindthegrow/cannlytics

c266bc1169bef75214985901cd3165f415ad9ba7

[ "MIT" ]

17

2021-06-09T01:04:27.000Z

2022-03-18T14:48:12.000Z

cannlytics/lims/qc.py

mindthegrow/cannlytics

c266bc1169bef75214985901cd3165f415ad9ba7

[ "MIT" ]

5

2021-06-07T13:52:33.000Z

2021-08-04T00:09:39.000Z

""" Quality Control Tools | Cannlytics Author: Keegan Skeate <keegan@cannlytics.com> Created: 2/6/2021 Updated: 6/23/2021 License: MIT License <https://opensource.org/licenses/MIT> Perform various quality control checks and analyses to ensure that your laboratory is operating as desired. TODO: - Trend analyte results. - Create predictions of lab results given available inputs! - Statistics for internal standards. """ def backup_data(): """Backup data stored in Firestore.""" return NotImplementedError def calculate_relative_percent_diff(): """Calculate relative perecent difference between two samples.""" return NotImplementedError def plot_area_response(): """Plot area response over time for a group of samples.""" return NotImplementedError def plot_deviations(): """Plot deviations in results for a group of samples.""" return NotImplementedError def track_deviations(): """Track deviations in results for a group of samples.""" return NotImplementedError def metrc_reconciliation(): """Reconcile Metrc data with Firestore data.""" return NotImplementedError

24.510638

69

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1,152

6.138686

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0.260404

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1,152

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1

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null

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1

0

1

0

1

0

5

ea43b6473a80169e05c17d102859f981a7b958d9

76

py

Python

containershare/validator/__init__.py

vsoch/containershare-python

9db2a4d7c7fcb0c21edd5d2e2b5396d7108fe392

[ "BSD-3-Clause" ]

null

containershare/validator/__init__.py

vsoch/containershare-python

9db2a4d7c7fcb0c21edd5d2e2b5396d7108fe392

[ "BSD-3-Clause" ]

1

2018-07-30T22:11:56.000Z

containershare/validator/__init__.py

vsoch/containershare-python

9db2a4d7c7fcb0c21edd5d2e2b5396d7108fe392

[ "BSD-3-Clause" ]

null

from .library import LibraryValidator from .runtime import RuntimeValidator

25.333333

37

0.868421

8

76

8.25

0.75

0

0.105263

76

2

38

0.970588

0

1

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true

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1

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1

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1

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null

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1

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null

0

1

0

1

0

1

0

5

ea5034df827000a7c021ce8d10922be02ea67910

70

py

Python

chatrender/celery.py

The-Politico/django-politico-slackchat-renderer

adb3ed2ba5039a97ee7b021d39aa40cab11e5661

[ "MIT" ]

2

2018-07-02T16:49:35.000Z

2018-07-09T03:52:28.000Z

chatrender/celery.py

The-Politico/django-politico-slackchat-renderer

adb3ed2ba5039a97ee7b021d39aa40cab11e5661

[ "MIT" ]

42

2018-02-14T21:28:54.000Z

2022-02-10T18:30:58.000Z

chatrender/celery.py

The-Politico/django-politico-slackchat-renderer

adb3ed2ba5039a97ee7b021d39aa40cab11e5661

[ "MIT" ]

null

# flake8: noqa from chatrender.tasks.publish import publish_slackchat

23.333333

54

0.842857

9

70

6.444444

0.888889

0

0.015873

0.1

70

2

55

35

0.904762

0.171429

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

ea61b0a3ba0b11abd7ed94000c53187e3c4b4ffc

109

py

Python

viper_dev.py

safinsingh/viper

f7fa9182713c4f0fbb33c2e881f668b807fd3956

[ "MIT" ]

null

viper_dev.py

safinsingh/viper

f7fa9182713c4f0fbb33c2e881f668b807fd3956

[ "MIT" ]

null

viper_dev.py

safinsingh/viper

f7fa9182713c4f0fbb33c2e881f668b807fd3956

[ "MIT" ]

null

from viper import * import inspect def GetSource(func): lines = inspect.getsource(func) print(lines)

18.166667

35

0.724771

14

109

5.642857

0.642857

0.329114

0

0.183486

109

6

36

18.166667

0.88764

0

1

0.2

false

0

0.4

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0.6

0.2

1

0

null

1

0

1

0

null

0

1

0

1

0

5

575b35db9c979401cf63c36c72e33a04e3269d4a

69

py

Python

win/devkit/other/pymel/extras/completion/py/maya/app/sceneAssembly/__init__.py

leegoonz/Maya-devkit

b81fe799b58e854e4ef16435426d60446e975871

[ "ADSL" ]

21

2015-04-27T05:01:36.000Z

2021-11-22T13:45:14.000Z

python/maya/site-packages/pymel-1.0.5/extras/completion/py/maya/app/sceneAssembly/__init__.py

0xb1dd1e/PipelineConstructionSet

621349da1b6d1437e95d0c9e48ee9f36d59f19fd

[ "BSD-3-Clause" ]

null

python/maya/site-packages/pymel-1.0.5/extras/completion/py/maya/app/sceneAssembly/__init__.py

0xb1dd1e/PipelineConstructionSet

621349da1b6d1437e95d0c9e48ee9f36d59f19fd

[ "BSD-3-Clause" ]

9

2018-06-02T09:18:49.000Z

2021-12-20T09:24:35.000Z

from . import adskPrepareRender import maya.cmds as cmd import maya

13.8

31

0.811594

10

69

5.6

0.7

0.357143

0

0.15942

69

4

32

17.25

0.965517

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true

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1

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null

0

1

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1

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5

576cb2eea467a88f13b66f007bd906188c23f5fc

4,239

py

Python

lib/systems/chlorophyll_c2.py

pulsar-chem/BPModule

f8e64e04fdb01947708f098e833600c459c2ff0e

[ "BSD-3-Clause" ]

null

lib/systems/chlorophyll_c2.py

pulsar-chem/BPModule

f8e64e04fdb01947708f098e833600c459c2ff0e

[ "BSD-3-Clause" ]

null

lib/systems/chlorophyll_c2.py

pulsar-chem/BPModule

f8e64e04fdb01947708f098e833600c459c2ff0e

[ "BSD-3-Clause" ]

null

import pulsar as psr def load_ref_system(): """ Returns chlorophyll_c2 as found in the IQMol fragment library. All credit to https://github.com/nutjunkie/IQmol """ return psr.make_system(""" C -2.51105 2.48309 -0.00367 C -1.01315 4.06218 0.09798 C 0.16582 4.71018 0.03445 C 1.49771 4.10555 -0.16166 C 3.11156 2.64885 -0.24011 C 3.76129 1.46796 -0.14139 C 3.09159 0.16424 -0.04831 C 1.53984 -1.29933 -0.10261 C -0.91181 -1.59853 -0.35248 C -2.45607 -0.05240 -0.35298 C -3.10620 1.27291 -0.16460 N 1.75017 2.78429 -0.23961 N 1.76493 0.00621 -0.16383 N -1.13225 -0.25365 -0.35470 C -3.20202 3.66639 0.28881 C 2.68521 4.82968 -0.22081 C 3.68747 -1.09005 0.15938 C -2.24542 4.67945 0.36245 C -2.41991 6.13752 0.71407 C -3.56473 6.73948 1.06129 C 3.72098 3.91621 -0.29248 N -1.17823 2.72953 -0.07212 Mg 0.26793 1.27490 -0.35377 C 0.34760 -2.11926 -0.19964 C 2.64511 -1.99016 0.09433 C 2.31747 -3.38932 0.17127 O 3.13845 -4.27117 0.35919 C 0.80633 -3.58955 -0.01558 O -0.47000 -3.54277 1.99390 C 0.19951 -4.22772 1.23456 O 0.33390 -5.55184 1.51538 C -2.14828 -2.27838 -0.46597 C -2.34627 -3.76961 -0.59495 C -3.52338 -4.42976 -0.61516 C -3.58867 -5.90449 -0.76226 O -2.56916 -6.57072 -0.87406 O -4.79233 -6.51526 -0.77059 C -3.12715 -1.27243 -0.46107 C 0.83624 -6.50254 0.65250 C 5.12089 -1.42417 0.42504 C -4.62172 -1.44902 -0.55794 C -4.68427 3.81267 0.53984 C 2.86086 6.32939 -0.22433 C 6.20198 3.61878 -0.78465 C 5.15458 4.35926 -0.39637 H 0.16297 5.77206 0.17065 H 4.82596 1.44735 -0.07176 H -4.17158 1.24062 -0.09244 H -1.55035 6.77752 0.72933 H -4.51438 6.24702 1.11665 H -3.54680 7.79385 1.31901 H 0.60711 -4.17663 -0.93384 H -1.47776 -4.37959 -0.70310 H -4.46318 -3.92775 -0.52160 H -4.86588 -7.47619 -0.86197 H 0.78374 -7.49457 1.14518 H 1.89335 -6.30524 0.40486 H 0.22776 -6.53794 -0.27557 H 5.75783 -0.51879 0.44869 H 5.50014 -2.12026 -0.34842 H 5.18953 -1.91331 1.42119 H -5.18859 -0.50460 -0.59248 H -4.99451 -2.00986 0.32226 H -4.86783 -1.97442 -1.50531 H -5.27115 2.88458 0.45319 H -5.12053 4.53158 -0.18161 H -4.83661 4.15056 1.58664 H 1.91301 6.89359 -0.19061 H 3.38213 6.63177 -1.15809 H 3.47321 6.63697 0.64765 H 7.18160 4.08465 -0.84048 H 6.13795 2.59183 -1.09149 H 5.36680 5.40361 -0.19182 """)

52.333333

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4,239

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52.9875

0.114044

0.026185

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true

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0.012987

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0.038961

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null

0

1

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1

0

1

0

null

0

1

0

5

17c5134f523338eb38c2be750ed00943cad1dc8d

34

py

Python

matfactor/__init__.py

Joshua-Chin/matfactor

6730ca7ddb7844d9d50f7e5725f5ccdaae31721b

[ "Apache-2.0" ]

1

2018-02-13T02:55:16.000Z

matfactor/__init__.py

Joshua-Chin/matfactor

6730ca7ddb7844d9d50f7e5725f5ccdaae31721b

[ "Apache-2.0" ]

null

matfactor/__init__.py

Joshua-Chin/matfactor

6730ca7ddb7844d9d50f7e5725f5ccdaae31721b

[ "Apache-2.0" ]

null

from ._factorize import factorize

17

33

0.852941

4

34

7

0.75

0

0.117647

34

1

34

0.933333

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

17f3d9a2300741cd7506a6c4460578d98121f0a5

154

py

Python

gather/handlers/__init__.py

openghg/gather

0096cfe66b0093cdd294fa2a67c060d7fc28d2fa

[ "Apache-2.0" ]

null

gather/handlers/__init__.py

openghg/gather

0096cfe66b0093cdd294fa2a67c060d7fc28d2fa

[ "Apache-2.0" ]

null

gather/handlers/__init__.py

openghg/gather

0096cfe66b0093cdd294fa2a67c060d7fc28d2fa

[ "Apache-2.0" ]

null

from ._scrape import scrape_handler from ._binary_data import data_handler from ._crds import crds_handler __all__ = ["scrape_handler", "data_handler"]

22

44

0.811688

21

154

5.333333

0.380952

0.232143

0

0.116883

154

6

45

25.666667

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0.168831

0

1

0

false

0

0.75

0

0.75

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

aa25080d95db6003a47cb7e9144e0411c4a11460

88

py

Python

onnxmltools/convert/common/utils.py

xjarvik/onnxmltools

e4fbdc09814ceedc7655d85b6c4203ca21d8433a

[ "Apache-2.0" ]

1

2022-01-28T04:59:37.000Z

onnxmltools/convert/common/utils.py

xjarvik/onnxmltools

e4fbdc09814ceedc7655d85b6c4203ca21d8433a

[ "Apache-2.0" ]

null

onnxmltools/convert/common/utils.py

xjarvik/onnxmltools

e4fbdc09814ceedc7655d85b6c4203ca21d8433a

[ "Apache-2.0" ]

1

2021-07-05T23:51:56.000Z

# SPDX-License-Identifier: Apache-2.0 from onnxconverter_common.utils import * # noqa

22

48

0.772727

12

88

5.583333

1

0

0.025974

0.125

88

3

49

29.333333

0.844156

0.454545

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null

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0

1

0

1

0

5

aa35c651bcb63b7652b7a85574cf82938974798d

206

py

Python

src/page/page_parser.py

baallezx/collect

7156f239d133660e03bba334d716025b96d6b230

[ "MIT" ]

1

2016-02-08T10:53:48.000Z

src/page/page_parser.py

baallezx/collect

7156f239d133660e03bba334d716025b96d6b230

[ "MIT" ]

null

src/page/page_parser.py

baallezx/collect

7156f239d133660e03bba334d716025b96d6b230

[ "MIT" ]

null

# TODO: implement a page_parser that uses nlp and stats to get a good read of a file. class page_parser(object): """ a multi purpose parser that can read these file types """ def __init__(self): pass

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1

0

5

aa35ead0147cdaa5e16792a1159c28c73e8158c5

110

py

Python

crawl_and_scrap/__main__.py

byung-u/GranXiSearch

80a4a2cd19e39424013b7838aafbbbffd2a3574b

[ "MIT" ]

1

2017-06-21T10:44:27.000Z

crawl_and_scrap/__main__.py

byung-u/GranXiSearch

80a4a2cd19e39424013b7838aafbbbffd2a3574b

[ "MIT" ]

5

2017-02-05T15:20:32.000Z

2017-03-11T14:09:49.000Z

crawl_and_scrap/__main__.py

byung-u/FindTheTreasure

80a4a2cd19e39424013b7838aafbbbffd2a3574b

[ "MIT" ]

null

"""crwal_and_scrap trying to gathering news with web scrawl""" from crwal_and_scrap.main import main main()

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0

null

0

1

0

1

0

5

a4c5246b1bb457ccf2adc163a51a115f0a845803

56

py

Python

utils/test_fm.py

dilum1995/DAugmentor

6cc86dccf826415a88b8226265e16ae96b5cc05b

[ "MIT" ]

1

2020-08-02T13:06:03.000Z

utils/test_fm.py

dilum1995/DAugmentor

6cc86dccf826415a88b8226265e16ae96b5cc05b

[ "MIT" ]

null

utils/test_fm.py

dilum1995/DAugmentor

6cc86dccf826415a88b8226265e16ae96b5cc05b

[ "MIT" ]

null

from utils import constants as const print(const.PATH)

14

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1

0

1

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5

a4e00d2cb49985d38fa9a42e89c6babd42a14602

190

py

Python

ldaptor/apps/webui/i18n.py

tv42/ldaptor

3f227602c8c021b9e943136a2dc8d7db44a11e50

[ "MIT" ]

1

2015-11-25T04:01:26.000Z

ldaptor/apps/webui/i18n.py

tv42/ldaptor

3f227602c8c021b9e943136a2dc8d7db44a11e50

[ "MIT" ]

null

ldaptor/apps/webui/i18n.py

tv42/ldaptor

3f227602c8c021b9e943136a2dc8d7db44a11e50

[ "MIT" ]

2

2019-11-06T02:14:10.000Z

2022-01-10T08:34:11.000Z

from nevow.inevow import ILanguages from nevow.i18n import I18NConfig from nevow import i18n _ = i18n.Translator(domain='ldaptor-webui') def render(): return i18n.render(translator=_)

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1

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5

a4e76062bd271f3f1cc37a95b088bfcb694c00bc

217

py

Python

hs_modflow_modelinstance/admin.py

ResearchSoftwareInstitute/MyHPOM

2d48fe5ac8d21173b1685eb33059bb391fe24414

[ "BSD-3-Clause" ]

1

2018-09-17T13:07:29.000Z

hs_modflow_modelinstance/admin.py

ResearchSoftwareInstitute/MyHPOM

2d48fe5ac8d21173b1685eb33059bb391fe24414

[ "BSD-3-Clause" ]

100

2017-08-01T23:48:04.000Z

2018-04-03T13:17:27.000Z

hs_modflow_modelinstance/admin.py

ResearchSoftwareInstitute/MyHPOM

2d48fe5ac8d21173b1685eb33059bb391fe24414

[ "BSD-3-Clause" ]

2

2017-07-27T20:41:33.000Z

2017-07-27T22:40:57.000Z

from mezzanine.pages.admin import PageAdmin from django.contrib import admin from hs_modflow_modelinstance.models import MODFLOWModelInstanceResource admin.site.register(MODFLOWModelInstanceResource, PageAdmin)

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104fe95906a89882b90ee817c831630744acea53

355

py

Python

tests/test_deploy.py

NCAR/marbl-solutions

0840e2a594d49218b1510cd8cb95d9d058495a8a

[ "MIT" ]

null

tests/test_deploy.py

NCAR/marbl-solutions

0840e2a594d49218b1510cd8cb95d9d058495a8a

[ "MIT" ]

1

2022-02-11T22:53:37.000Z

tests/test_deploy.py

NCAR/marbl-solutions

0840e2a594d49218b1510cd8cb95d9d058495a8a

[ "MIT" ]

null

import solutions def test_deploy_config(): deploy_config = solutions.config.deploy_config assert deploy_config['reference_case'] == 'ref_case' assert type(deploy_config['reference_case_path']) == list assert deploy_config['reference_case_file_format'] == 'history' assert deploy_config['case_to_compare_file_format'] == 'timeseries'

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5.75

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9

72

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0

null

1

0

1

0

null

0

1

0

5

10521ee81224fcf01be655be4e17446c05559c19

148

py

Python

backend/home/models.py

crowdbotics-apps/test-29106

34df3fa66e798f61d9189fa248f21cabb9bca0e1

[ "FTL", "AML", "RSA-MD" ]

null

backend/home/models.py

crowdbotics-apps/test-29106

34df3fa66e798f61d9189fa248f21cabb9bca0e1

[ "FTL", "AML", "RSA-MD" ]

null

backend/home/models.py

crowdbotics-apps/test-29106

34df3fa66e798f61d9189fa248f21cabb9bca0e1

[ "FTL", "AML", "RSA-MD" ]

null

from django.conf import settings from django.db import models class Tasks(models.Model): "Generated Model" task_name = models.TextField()

18.5

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5.5

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1

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null

0

1

0

1

0

5

106e4b0ccf7d2a2518a1959d9ed235098c74fcea

97

py

Python

getKey.py

cychiang/spotify-lyrics

78219ea2e9c8eacda7a8cb1cecbb7ecdd39d208e

[ "Apache-2.0" ]

null

getKey.py

cychiang/spotify-lyrics

78219ea2e9c8eacda7a8cb1cecbb7ecdd39d208e

[ "Apache-2.0" ]

null

getKey.py

cychiang/spotify-lyrics

78219ea2e9c8eacda7a8cb1cecbb7ecdd39d208e

[ "Apache-2.0" ]

null

def musixmatch(): with open('musixmatch.txt', 'r') as key: return key.readline()

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null

0

1

0

1

0

5

1071d5d3c31d440ee16ee62b40826c1d771809f7

216

py

Python

regularize_charsets.py

sys-bio/temp-biomodels

596eebb590d72e74419773f4e9b829a62d7fff9a

[ "CC0-1.0" ]

null

regularize_charsets.py

sys-bio/temp-biomodels

596eebb590d72e74419773f4e9b829a62d7fff9a

[ "CC0-1.0" ]

5

2022-03-30T21:33:45.000Z

2022-03-31T20:08:15.000Z

regularize_charsets.py

sys-bio/temp-biomodels

596eebb590d72e74419773f4e9b829a62d7fff9a

[ "CC0-1.0" ]

null

from charset_normalizer import from_path, normalize results = from_path('original\BIOMD0000000424\BIOMD0000000424_url.xml') best = str(results.best()) normalize('original\BIOMD0000000424\BIOMD0000000424_url.xml')

27

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6.96

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216

7

72

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1

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1

0

1

null

0

5

10b7df52a7109b3cd059e5aa3d9c1aee9eb2218c

2,171

py

Python

tests/models/boundary/test_is_boundary_concave_to_y.py

EderVs/Voronoi-Diagrams

6e69f9b6eb516dee12d66f187cf267a7b527da5f

[ "MIT" ]

3

2021-11-12T17:43:08.000Z

2022-01-03T02:47:34.000Z

tests/models/boundary/test_is_boundary_concave_to_y.py

EderVs/Voronoi-Diagrams

6e69f9b6eb516dee12d66f187cf267a7b527da5f

[ "MIT" ]

3

2021-11-19T20:12:31.000Z

2021-11-19T20:14:39.000Z

tests/models/boundary/test_is_boundary_concave_to_y.py

EderVs/Voronoi-Diagrams

6e69f9b6eb516dee12d66f187cf267a7b527da5f

[ "MIT" ]

null

"""Test is_boundary_not_x_monotone method in WeightedPointBoundary.""" # Standard from typing import List, Any from random import randint # Models from voronoi_diagrams.models import ( WeightedSite, WeightedPointBisector, WeightedPointBoundary, ) # Math from decimal import Decimal class TestWeightedPointBoundaryIsBoundaryConcaveToY: """Test formula.""" def test_with_concave_to_y_boundary(self): """Test with a boundary that is concave to y.""" p = WeightedSite(Decimal(-20), Decimal(10), Decimal(2)) # q is the one in the top. q = WeightedSite(Decimal(-5), Decimal(10), Decimal(7)) bisector = WeightedPointBisector(sites=(p, q)) boundary_plus = WeightedPointBoundary(bisector=bisector, sign=True) boundary_minus = WeightedPointBoundary(bisector=bisector, sign=False) assert not boundary_plus.is_boundary_not_x_monotone() assert boundary_minus.is_boundary_not_x_monotone() def test_with_normal_boundary(self): """Test with a boundary that is not concave to y.""" p = WeightedSite(Decimal(-20), Decimal(10), Decimal(2)) # q is the one in the top. q = WeightedSite(Decimal(-8), Decimal(18), Decimal(7)) bisector = WeightedPointBisector(sites=(p, q)) boundary_plus = WeightedPointBoundary(bisector=bisector, sign=True) boundary_minus = WeightedPointBoundary(bisector=bisector, sign=False) assert not boundary_plus.is_boundary_not_x_monotone() assert not boundary_minus.is_boundary_not_x_monotone() def test_with_stopped_boundary(self): """Test with a boundary that is not concave to y.""" p = WeightedSite(Decimal(-20), Decimal(10), Decimal(2)) # q is the one in the top. q = WeightedSite(Decimal(-5), Decimal(15), Decimal(7)) bisector = WeightedPointBisector(sites=(p, q)) boundary_plus = WeightedPointBoundary(bisector=bisector, sign=True) boundary_minus = WeightedPointBoundary(bisector=bisector, sign=False) assert not boundary_plus.is_boundary_not_x_monotone() assert not boundary_minus.is_boundary_not_x_monotone()

41.75

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null

0

1

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null

0

5

10bd99ec8ccedb03c569281fb82814ef2e18a1af

44

py

Python

europython-2018/code/simple_bind/run.py

svenstaro/talks

0462268a8c684dde65aceb2fb98644cb655c5013

[ "MIT" ]

5

2018-07-26T10:45:41.000Z

2020-08-16T17:45:51.000Z

europython-2018/code/simple_bind/run.py

svenstaro/talks

0462268a8c684dde65aceb2fb98644cb655c5013

[ "MIT" ]

null

europython-2018/code/simple_bind/run.py

svenstaro/talks

0462268a8c684dde65aceb2fb98644cb655c5013

[ "MIT" ]

1

2020-10-02T22:09:15.000Z

from europython import hello hello("Alisa")

14.666667

28

0.795455

6

44

5.833333

0.833333

0

0.113636

44

2

29

22

0.897436

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1

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true

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null

0

1

0

1

0

5

52c38d1cc6e6ce5d847e7873d6a974fa56d65e99

163

py

Python

tests/__init__.py

RonenTRA/faster-than-requests

237a57cf2607e0694c87fea8e313461bf9a462e7

[ "MIT" ]

857

2018-11-18T17:55:01.000Z

2022-03-31T23:39:10.000Z

tests/__init__.py

RonenTRA/faster-than-requests

237a57cf2607e0694c87fea8e313461bf9a462e7

[ "MIT" ]

181

2018-12-08T18:31:05.000Z

2022-03-29T01:40:02.000Z

tests/__init__.py

RonenTRA/faster-than-requests

237a57cf2607e0694c87fea8e313461bf9a462e7

[ "MIT" ]

92

2018-11-22T03:53:31.000Z

2022-03-21T10:54:24.000Z

# Allow tests/ directory to see faster_than_requests/ package on PYTHONPATH import sys from pathlib import Path sys.path.append(str(Path(__file__).parent.parent))

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5

52d3d72868c077690bde8ce4b9a24f77c6b48f81

134

py

Python

app/blueprints/printing/__init__.py

OrigamiCranes/PrintingPortal

e25f9f683dca3a0dcf4c90ae50515d7693447cb8

[ "MIT", "Unlicense" ]

null

app/blueprints/printing/__init__.py

OrigamiCranes/PrintingPortal

e25f9f683dca3a0dcf4c90ae50515d7693447cb8

[ "MIT", "Unlicense" ]

null

app/blueprints/printing/__init__.py

OrigamiCranes/PrintingPortal

e25f9f683dca3a0dcf4c90ae50515d7693447cb8

[ "MIT", "Unlicense" ]

null

from flask import Blueprint, url_for bp = Blueprint('printing', __name__,template_folder='templates') from . import routes, forms

16.75

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0

1

0

null

0

1

0

1

0

5

5e05f2cccefdec04a8fd2cca1ee7503f900daacf

292

py

Python

app/main/views.py

chushijituan/job_analysis

a99d8f12b9dafa93de448a27d2f76ee6ddbde469

[ "MIT" ]

45

2016-07-07T08:53:04.000Z

2022-01-10T11:00:40.000Z

app/main/views.py

chushijituan/job_analysis

a99d8f12b9dafa93de448a27d2f76ee6ddbde469

[ "MIT" ]

1

2016-07-09T03:40:13.000Z

2017-02-02T06:58:27.000Z

app/main/views.py

chushijituan/job_analysis

a99d8f12b9dafa93de448a27d2f76ee6ddbde469

[ "MIT" ]

20

2016-07-08T02:18:49.000Z

2019-06-09T14:21:26.000Z

# coding: utf-8 from . import main from flask import render_template, jsonify, flash, request, current_app, url_for, Response, g, abort @main.route('/') def index(): return render_template('index.html') @main.route('/about') def about_page(): return render_template('about.html')

20.857143

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1

0

null

0

1

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1

0

5

eacf62541cfea44c5aa6f4ef694688addf50cbbc

232

py

Python

catsndogs/training.py

simonpf/catsndogs

36732a7c2c767b2bb6efa87a849598170c8026e8

[ "MIT" ]

1

2020-12-18T17:19:37.000Z

catsndogs/training.py

simonpf/catsndogs

36732a7c2c767b2bb6efa87a849598170c8026e8

[ "MIT" ]

null

catsndogs/training.py

simonpf/catsndogs

36732a7c2c767b2bb6efa87a849598170c8026e8

[ "MIT" ]

null

import os import glob from catsndogs.data import get_training_data folder = get_training_data() cats = glob.glob(os.path.join(get_training_data(), "cat", "*.jpg")) dogs = glob.glob(os.path.join(get_training_data(), "dog", "*.jpg"))

33.142857

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0.737069

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232

4.405405

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0.269939

0.368098

0.171779

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0

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6

68

38.666667

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0

null

1

0

1

0

null

0

1

0

5

d820b4f0770506dfe9510b1820590790869fb745

247

py

Python

apollo/embeds/__init__.py

rpetti/apollo

1304d8623e6dfe8c9b269b7e90611b3688c0c61e

[ "MIT" ]

null

apollo/embeds/__init__.py

rpetti/apollo

1304d8623e6dfe8c9b269b7e90611b3688c0c61e

[ "MIT" ]

null

apollo/embeds/__init__.py

rpetti/apollo

1304d8623e6dfe8c9b269b7e90611b3688c0c61e

[ "MIT" ]

null

from .about_embed import AboutEmbed from .event_embed import EventEmbed from .help_embed import HelpEmbed from .select_channel_embed import SelectChannelEmbed from .start_time_embed import StartTimeEmbed from .time_zone_embed import TimeZoneEmbed

35.285714

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247

6.30303

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0

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6

53

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0

1

0

true

0

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1

0

null

0

1

0

1

0

1

0

5

dc3a778a081bc0e908fbf22ada6b3c5f69d5f4aa

16,560

py

Python

sdk/python/pulumi_kong/_inputs.py

pulumi/pulumi-kong

775c17e4eac38934252410ed3dcdc6fc3bd40c5c

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

4

2020-02-23T10:05:20.000Z

2020-05-15T14:22:10.000Z

sdk/python/pulumi_kong/_inputs.py

pulumi/pulumi-kong

775c17e4eac38934252410ed3dcdc6fc3bd40c5c

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

41

2020-04-21T22:04:23.000Z

2022-03-31T15:29:53.000Z

sdk/python/pulumi_kong/_inputs.py

pulumi/pulumi-kong

775c17e4eac38934252410ed3dcdc6fc3bd40c5c

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

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from . import _utilities __all__ = [ 'RouteDestinationArgs', 'RouteHeaderArgs', 'RouteSourceArgs', 'UpstreamHealthchecksArgs', 'UpstreamHealthchecksActiveArgs', 'UpstreamHealthchecksActiveHealthyArgs', 'UpstreamHealthchecksActiveUnhealthyArgs', 'UpstreamHealthchecksPassiveArgs', 'UpstreamHealthchecksPassiveHealthyArgs', 'UpstreamHealthchecksPassiveUnhealthyArgs', ] @pulumi.input_type class RouteDestinationArgs: def __init__(__self__, *, ip: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None): if ip is not None: pulumi.set(__self__, "ip", ip) if port is not None: pulumi.set(__self__, "port", port) @property @pulumi.getter def ip(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "ip") @ip.setter def ip(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "ip", value) @property @pulumi.getter def port(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "port") @port.setter def port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "port", value) @pulumi.input_type class RouteHeaderArgs: def __init__(__self__, *, name: pulumi.Input[str], values: pulumi.Input[Sequence[pulumi.Input[str]]]): """ :param pulumi.Input[str] name: The name of the route """ pulumi.set(__self__, "name", name) pulumi.set(__self__, "values", values) @property @pulumi.getter def name(self) -> pulumi.Input[str]: """ The name of the route """ return pulumi.get(self, "name") @name.setter def name(self, value: pulumi.Input[str]): pulumi.set(self, "name", value) @property @pulumi.getter def values(self) -> pulumi.Input[Sequence[pulumi.Input[str]]]: return pulumi.get(self, "values") @values.setter def values(self, value: pulumi.Input[Sequence[pulumi.Input[str]]]): pulumi.set(self, "values", value) @pulumi.input_type class RouteSourceArgs: def __init__(__self__, *, ip: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None): if ip is not None: pulumi.set(__self__, "ip", ip) if port is not None: pulumi.set(__self__, "port", port) @property @pulumi.getter def ip(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "ip") @ip.setter def ip(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "ip", value) @property @pulumi.getter def port(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "port") @port.setter def port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "port", value) @pulumi.input_type class UpstreamHealthchecksArgs: def __init__(__self__, *, active: Optional[pulumi.Input['UpstreamHealthchecksActiveArgs']] = None, passive: Optional[pulumi.Input['UpstreamHealthchecksPassiveArgs']] = None): if active is not None: pulumi.set(__self__, "active", active) if passive is not None: pulumi.set(__self__, "passive", passive) @property @pulumi.getter def active(self) -> Optional[pulumi.Input['UpstreamHealthchecksActiveArgs']]: return pulumi.get(self, "active") @active.setter def active(self, value: Optional[pulumi.Input['UpstreamHealthchecksActiveArgs']]): pulumi.set(self, "active", value) @property @pulumi.getter def passive(self) -> Optional[pulumi.Input['UpstreamHealthchecksPassiveArgs']]: return pulumi.get(self, "passive") @passive.setter def passive(self, value: Optional[pulumi.Input['UpstreamHealthchecksPassiveArgs']]): pulumi.set(self, "passive", value) @pulumi.input_type class UpstreamHealthchecksActiveArgs: def __init__(__self__, *, concurrency: Optional[pulumi.Input[int]] = None, healthy: Optional[pulumi.Input['UpstreamHealthchecksActiveHealthyArgs']] = None, http_path: Optional[pulumi.Input[str]] = None, https_sni: Optional[pulumi.Input[str]] = None, https_verify_certificate: Optional[pulumi.Input[bool]] = None, timeout: Optional[pulumi.Input[int]] = None, type: Optional[pulumi.Input[str]] = None, unhealthy: Optional[pulumi.Input['UpstreamHealthchecksActiveUnhealthyArgs']] = None): if concurrency is not None: pulumi.set(__self__, "concurrency", concurrency) if healthy is not None: pulumi.set(__self__, "healthy", healthy) if http_path is not None: pulumi.set(__self__, "http_path", http_path) if https_sni is not None: pulumi.set(__self__, "https_sni", https_sni) if https_verify_certificate is not None: pulumi.set(__self__, "https_verify_certificate", https_verify_certificate) if timeout is not None: pulumi.set(__self__, "timeout", timeout) if type is not None: pulumi.set(__self__, "type", type) if unhealthy is not None: pulumi.set(__self__, "unhealthy", unhealthy) @property @pulumi.getter def concurrency(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "concurrency") @concurrency.setter def concurrency(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "concurrency", value) @property @pulumi.getter def healthy(self) -> Optional[pulumi.Input['UpstreamHealthchecksActiveHealthyArgs']]: return pulumi.get(self, "healthy") @healthy.setter def healthy(self, value: Optional[pulumi.Input['UpstreamHealthchecksActiveHealthyArgs']]): pulumi.set(self, "healthy", value) @property @pulumi.getter(name="httpPath") def http_path(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "http_path") @http_path.setter def http_path(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "http_path", value) @property @pulumi.getter(name="httpsSni") def https_sni(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "https_sni") @https_sni.setter def https_sni(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "https_sni", value) @property @pulumi.getter(name="httpsVerifyCertificate") def https_verify_certificate(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "https_verify_certificate") @https_verify_certificate.setter def https_verify_certificate(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "https_verify_certificate", value) @property @pulumi.getter def timeout(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "timeout") @timeout.setter def timeout(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "timeout", value) @property @pulumi.getter def type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "type") @type.setter def type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "type", value) @property @pulumi.getter def unhealthy(self) -> Optional[pulumi.Input['UpstreamHealthchecksActiveUnhealthyArgs']]: return pulumi.get(self, "unhealthy") @unhealthy.setter def unhealthy(self, value: Optional[pulumi.Input['UpstreamHealthchecksActiveUnhealthyArgs']]): pulumi.set(self, "unhealthy", value) @pulumi.input_type class UpstreamHealthchecksActiveHealthyArgs: def __init__(__self__, *, http_statuses: Optional[pulumi.Input[Sequence[pulumi.Input[int]]]] = None, interval: Optional[pulumi.Input[int]] = None, successes: Optional[pulumi.Input[int]] = None): if http_statuses is not None: pulumi.set(__self__, "http_statuses", http_statuses) if interval is not None: pulumi.set(__self__, "interval", interval) if successes is not None: pulumi.set(__self__, "successes", successes) @property @pulumi.getter(name="httpStatuses") def http_statuses(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[int]]]]: return pulumi.get(self, "http_statuses") @http_statuses.setter def http_statuses(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[int]]]]): pulumi.set(self, "http_statuses", value) @property @pulumi.getter def interval(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "interval") @interval.setter def interval(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "interval", value) @property @pulumi.getter def successes(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "successes") @successes.setter def successes(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "successes", value) @pulumi.input_type class UpstreamHealthchecksActiveUnhealthyArgs: def __init__(__self__, *, http_failures: Optional[pulumi.Input[int]] = None, http_statuses: Optional[pulumi.Input[Sequence[pulumi.Input[int]]]] = None, interval: Optional[pulumi.Input[int]] = None, tcp_failures: Optional[pulumi.Input[int]] = None, timeouts: Optional[pulumi.Input[int]] = None): if http_failures is not None: pulumi.set(__self__, "http_failures", http_failures) if http_statuses is not None: pulumi.set(__self__, "http_statuses", http_statuses) if interval is not None: pulumi.set(__self__, "interval", interval) if tcp_failures is not None: pulumi.set(__self__, "tcp_failures", tcp_failures) if timeouts is not None: pulumi.set(__self__, "timeouts", timeouts) @property @pulumi.getter(name="httpFailures") def http_failures(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "http_failures") @http_failures.setter def http_failures(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "http_failures", value) @property @pulumi.getter(name="httpStatuses") def http_statuses(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[int]]]]: return pulumi.get(self, "http_statuses") @http_statuses.setter def http_statuses(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[int]]]]): pulumi.set(self, "http_statuses", value) @property @pulumi.getter def interval(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "interval") @interval.setter def interval(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "interval", value) @property @pulumi.getter(name="tcpFailures") def tcp_failures(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "tcp_failures") @tcp_failures.setter def tcp_failures(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "tcp_failures", value) @property @pulumi.getter def timeouts(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "timeouts") @timeouts.setter def timeouts(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "timeouts", value) @pulumi.input_type class UpstreamHealthchecksPassiveArgs: def __init__(__self__, *, healthy: Optional[pulumi.Input['UpstreamHealthchecksPassiveHealthyArgs']] = None, type: Optional[pulumi.Input[str]] = None, unhealthy: Optional[pulumi.Input['UpstreamHealthchecksPassiveUnhealthyArgs']] = None): if healthy is not None: pulumi.set(__self__, "healthy", healthy) if type is not None: pulumi.set(__self__, "type", type) if unhealthy is not None: pulumi.set(__self__, "unhealthy", unhealthy) @property @pulumi.getter def healthy(self) -> Optional[pulumi.Input['UpstreamHealthchecksPassiveHealthyArgs']]: return pulumi.get(self, "healthy") @healthy.setter def healthy(self, value: Optional[pulumi.Input['UpstreamHealthchecksPassiveHealthyArgs']]): pulumi.set(self, "healthy", value) @property @pulumi.getter def type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "type") @type.setter def type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "type", value) @property @pulumi.getter def unhealthy(self) -> Optional[pulumi.Input['UpstreamHealthchecksPassiveUnhealthyArgs']]: return pulumi.get(self, "unhealthy") @unhealthy.setter def unhealthy(self, value: Optional[pulumi.Input['UpstreamHealthchecksPassiveUnhealthyArgs']]): pulumi.set(self, "unhealthy", value) @pulumi.input_type class UpstreamHealthchecksPassiveHealthyArgs: def __init__(__self__, *, http_statuses: Optional[pulumi.Input[Sequence[pulumi.Input[int]]]] = None, successes: Optional[pulumi.Input[int]] = None): if http_statuses is not None: pulumi.set(__self__, "http_statuses", http_statuses) if successes is not None: pulumi.set(__self__, "successes", successes) @property @pulumi.getter(name="httpStatuses") def http_statuses(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[int]]]]: return pulumi.get(self, "http_statuses") @http_statuses.setter def http_statuses(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[int]]]]): pulumi.set(self, "http_statuses", value) @property @pulumi.getter def successes(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "successes") @successes.setter def successes(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "successes", value) @pulumi.input_type class UpstreamHealthchecksPassiveUnhealthyArgs: def __init__(__self__, *, http_failures: Optional[pulumi.Input[int]] = None, http_statuses: Optional[pulumi.Input[Sequence[pulumi.Input[int]]]] = None, tcp_failures: Optional[pulumi.Input[int]] = None, timeouts: Optional[pulumi.Input[int]] = None): if http_failures is not None: pulumi.set(__self__, "http_failures", http_failures) if http_statuses is not None: pulumi.set(__self__, "http_statuses", http_statuses) if tcp_failures is not None: pulumi.set(__self__, "tcp_failures", tcp_failures) if timeouts is not None: pulumi.set(__self__, "timeouts", timeouts) @property @pulumi.getter(name="httpFailures") def http_failures(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "http_failures") @http_failures.setter def http_failures(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "http_failures", value) @property @pulumi.getter(name="httpStatuses") def http_statuses(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[int]]]]: return pulumi.get(self, "http_statuses") @http_statuses.setter def http_statuses(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[int]]]]): pulumi.set(self, "http_statuses", value) @property @pulumi.getter(name="tcpFailures") def tcp_failures(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "tcp_failures") @tcp_failures.setter def tcp_failures(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "tcp_failures", value) @property @pulumi.getter def timeouts(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "timeouts") @timeouts.setter def timeouts(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "timeouts", value)

34.936709

103

0.650906

1,830

16,560

5.707104

0.054645

0.131655

0.169188

0.088472

0.754021

0.703562

0.67388

0.65473

0.648506

0.597472

0

0.000078

0.222766

16,560

473

104

35.010571

0.811359

0.015278

0

0.701333

1

0

0.118541

0.060162

0

1

0.202667

false

0.053333

0.013333

0.085333

0.330667

0

null

0

1

0

1

0

null

0

1

0

1

0

5

f4c5360b157971c47ab67890d1de372c50e60d6a

282

py

Python

MTS/__init__.py

ohhorob/pyMTS

e7553b96e72ac6d4f91657bdb7c632aeeaba3c9b

[ "Apache-2.0" ]

1

2021-04-28T12:23:42.000Z

MTS/__init__.py

ohhorob/pyMTS

e7553b96e72ac6d4f91657bdb7c632aeeaba3c9b

[ "Apache-2.0" ]

null

MTS/__init__.py

ohhorob/pyMTS

e7553b96e72ac6d4f91657bdb7c632aeeaba3c9b

[ "Apache-2.0" ]

null

# MTS Log protocol -- http://www.innovatemotorsports.com/support/downloads/Seriallog-2.pdf # Serial: 8-N-1-19.2 kbit/sec # Packet periodicity: 81.92 milliseconds (12.2 hertz) (8 MHz / 655360) # Sample resolution: 10 bits (0..5V at 0.1% resolution) import Header from word import *

35.25

90

0.734043

46

282

4.5

0.847826

0

0.106122

0.131206

282

7

91

40.285714

0.738776

0.847518

0

1

0

true

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

5

f4e2c1950f15699ea2256ebd32a508dcb6887549

105

py

Python

test_initial.py

BickySamourai/djreact

cea500cb3dc841100cc058110d7e2c6d813ca8b8

[ "MIT" ]

1

2018-12-05T11:21:50.000Z

test_initial.py

floriansollami/djreact

cea500cb3dc841100cc058110d7e2c6d813ca8b8

[ "MIT" ]

2

2020-02-11T23:28:33.000Z

2020-06-05T19:36:41.000Z

test_initial.py

BickySamourai/djreact

cea500cb3dc841100cc058110d7e2c6d813ca8b8

[ "MIT" ]

1

2018-12-10T10:32:23.000Z

def hello(name): return 'Hello ' + 'name' def test_hello(): assert hello('name') == 'Hello name'

21

40

0.609524

14

105

4.5

0.428571

0.571429

0

0.209524

105

5

40

21

0.759036

0

0.226415

0

0.25

1

0.5

false

0

0.25

0.75

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

f4fbc7791249dd3dc8759c139bed36e338524bfa

4,198

py

Python

games_logger/games/migrations/0001_initial.py

HaeckelK/games_logger_django

0a8a51e73f56e68d2dea6252a263c408ca86071e

[ "MIT" ]

null

games_logger/games/migrations/0001_initial.py

HaeckelK/games_logger_django

0a8a51e73f56e68d2dea6252a263c408ca86071e

[ "MIT" ]

3

2021-01-10T10:45:32.000Z

2021-01-10T13:31:05.000Z

games_logger/games/migrations/0001_initial.py

HaeckelK/games_logger_django

0a8a51e73f56e68d2dea6252a263c408ca86071e

[ "MIT" ]

null

# Generated by Django 3.1.5 on 2021-01-07 21:50 import django.core.validators from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Category', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=30, unique=True)), ('description_short', models.CharField(max_length=50)), ('description_long', models.CharField(max_length=250)), ('created_on', models.DateTimeField(auto_now_add=True)), ], ), migrations.CreateModel( name='Game', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=30, unique=True)), ('created_on', models.DateTimeField(auto_now_add=True)), ('players_min', models.PositiveIntegerField(validators=[django.core.validators.MinValueValidator(1)])), ('players_max', models.PositiveIntegerField(validators=[django.core.validators.MinValueValidator(1)])), ('expands', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='games.game')), ], ), migrations.CreateModel( name='Player', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=30, unique=True)), ('created_on', models.DateTimeField(auto_now_add=True)), ], ), migrations.CreateModel( name='GenreCategory', fields=[ ('category_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='games.category')), ], bases=('games.category',), ), migrations.CreateModel( name='PlatformCategory', fields=[ ('category_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='games.category')), ], bases=('games.category',), ), migrations.CreateModel( name='TimeCategory', fields=[ ('category_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='games.category')), ], bases=('games.category',), ), migrations.CreateModel( name='Match', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('comments', models.CharField(max_length=250)), ('created_on', models.DateTimeField(auto_now_add=True)), ('game', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='games.game')), ('players', models.ManyToManyField(related_name='players', to='games.Player')), ('winners', models.ManyToManyField(related_name='winners', to='games.Player')), ], ), migrations.AddField( model_name='game', name='genre', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='games.genrecategory'), ), migrations.AddField( model_name='game', name='platform', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='games.platformcategory'), ), migrations.AddField( model_name='game', name='time', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='games.timecategory'), ), ]

45.139785

193

0.595045

414

4,198

5.891304

0.202899

0.0328

0.051661

0.081181

0.752768

0.709717

0.647396

0

0.010065

0.266317

4,198

92

194

45.630435

0.781818

0.010719

0

0.635294

1

0

0.11708

0.0053

0

1

0

false

0

0.035294

0

0.082353

0

null

0

1

0

1

0

1

0

null

0

5

762189364ae8346baa62adb5a86bb79745cc8954

83

py

Python

contrib/frontends/py/nntpchan/__init__.py

majestrate/nntpchan

f92f68c3cdce4b7ce6d4121ca4356b36ebcd933f

[ "MIT" ]

233

2015-08-06T02:51:52.000Z

2022-02-14T11:29:13.000Z

contrib/frontends/py/nntpchan/__init__.py

Revivify/nntpchan

0d555bb88a2298dae9aacf11348e34c52befa3d8

[ "MIT" ]

98

2015-09-19T22:29:00.000Z

2021-06-12T09:43:13.000Z

contrib/frontends/py/nntpchan/__init__.py

Revivify/nntpchan

0d555bb88a2298dae9aacf11348e34c52befa3d8

[ "MIT" ]

49

2015-08-06T02:51:55.000Z

2020-03-11T04:23:56.000Z

# # entry for gunicorn # from nntpchan.app import app from nntpchan import viewsp

11.857143

28

0.771084

12

83

5.333333

0.666667

0.375

0

0.180723

83

6

29

13.833333

0.941176

0.216867

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

52192abd9407b91e90fb61d5319cec65580111e5

34

py

Python

exercises/spiral-matrix/spiral_matrix.py

kishankj/python

82042de746128127502e109111e6c4e8ab002af6

[ "MIT" ]

1,177

2017-06-21T20:24:06.000Z

2022-03-29T02:30:55.000Z

exercises/spiral-matrix/spiral_matrix.py

kishankj/python

82042de746128127502e109111e6c4e8ab002af6

[ "MIT" ]

1,890

2017-06-18T20:06:10.000Z

2022-03-31T18:35:51.000Z

exercises/spiral-matrix/spiral_matrix.py

kishankj/python

82042de746128127502e109111e6c4e8ab002af6

[ "MIT" ]

1,095

2017-06-26T23:06:19.000Z

2022-03-29T03:25:38.000Z

def spiral_matrix(size): pass

11.333333

24

0.705882

5

34

4.6

1

0

0.205882

34

2

25

17

0.851852

0

1

0.5

false

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

5

5231e6bd87f94e0063595e79c3086076e75fc714

31

py

Python

src/awss3/__init__.py

ZhiruiFeng/CarsMemory

658afb98b1b8a667ae45e599ceb56f51759fdfce

[ "MIT" ]

9

2019-01-26T21:57:38.000Z

2021-08-13T11:55:56.000Z

src/awss3/__init__.py

ZhiruiFeng/CarsMemory

658afb98b1b8a667ae45e599ceb56f51759fdfce

[ "MIT" ]

6

2019-02-03T05:42:50.000Z

2021-06-01T23:24:35.000Z

src/awss3/__init__.py

ZhiruiFeng/CarsMemory

658afb98b1b8a667ae45e599ceb56f51759fdfce

[ "MIT" ]

5

2019-03-06T04:33:57.000Z

2021-05-31T17:43:57.000Z

#!/usr/bin/env python # aws s3

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6

31

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0

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22

15.5

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0

null

0

null

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true

0

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0

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0

1

0

1

0

null

0

1

0

5

52813eb5a92147299029b6f56c0318355c220c8b

131

py

Python

backend/app/admin/components/__init__.py

griviala/garpix_page

55f1d9bc6d1de29d18e15369bebcbef18811b5a4

[ "MIT" ]

null

backend/app/admin/components/__init__.py

griviala/garpix_page

55f1d9bc6d1de29d18e15369bebcbef18811b5a4

[ "MIT" ]

null

backend/app/admin/components/__init__.py

griviala/garpix_page

55f1d9bc6d1de29d18e15369bebcbef18811b5a4

[ "MIT" ]

null

from .text_component import TextComponentAdmin # noqa from .text_description_component import TextDescriptionComponentAdmin # noqa

43.666667

76

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13

131

8.615385

0.615385

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0

0.091603

131

2

77

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0.068702

0

1

0

true

0

1

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1

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0

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1

0

null

0

1

0

1

0

1

0

5

5282a5299abff7b8701b16a10c2c45a9be1078cc

27

py

Python

portal/pulsar/__init__.py

bbhunter/pulsar

1f6384482eebc71137716e27ba7a010f3aea7241

[ "Apache-2.0", "BSD-3-Clause" ]

12

2021-12-28T14:15:27.000Z

2022-03-29T00:45:00.000Z

portal/pulsar/__init__.py

bbhunter/pulsar

1f6384482eebc71137716e27ba7a010f3aea7241

[ "Apache-2.0", "BSD-3-Clause" ]

1

2022-02-09T12:47:14.000Z

portal/pulsar/__init__.py

bbhunter/pulsar

1f6384482eebc71137716e27ba7a010f3aea7241

[ "Apache-2.0", "BSD-3-Clause" ]

1

2022-01-18T03:59:11.000Z

from .celeryapp import *

6.75

24

0.703704

3

27

6.333333

1

0

0.222222

27

3

25

9

0.904762

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0

1

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1

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5

528a9e7052216cb329d6d29d4440112a9d78b9fe

146

py

Python

starter_code/api_keys.py

bjouellette/python-api-challenge

855c31769893596211ef072df8412cd47a557e19

[ "ADSL" ]

1

2022-01-27T00:04:14.000Z

starter_code/api_keys.py

bjouellette/python-api-challenge

855c31769893596211ef072df8412cd47a557e19

[ "ADSL" ]

null

starter_code/api_keys.py

bjouellette/python-api-challenge

855c31769893596211ef072df8412cd47a557e19

[ "ADSL" ]

null

# OpenWeatherMap API Key weather_api_key = "e1067d92d6b631a16363bf4db3023b19" # Google API Key g_key = "AIzaSyA4RYdQ1nxoMTIW854C7wvVJMf0Qz5qjNk"

24.333333

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0.842466

13

146

9.230769

0.615385

0.15

0

0.229008

0.10274

146

5

53

29.2

0.687023

0.253425

0

0.669811

0

1

0

false

0

1

0

null

0

1

0

1

0

1

null

0

5

bfdb50593c6e1e9d0effbbd8845a4184d945a3b0

547

py

Python

plugins/minfraud/komand_minfraud/actions/__init__.py

lukaszlaszuk/insightconnect-plugins

8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892

[ "MIT" ]

46

2019-06-05T20:47:58.000Z

2022-03-29T10:18:01.000Z

plugins/minfraud/komand_minfraud/actions/__init__.py

lukaszlaszuk/insightconnect-plugins

8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892

[ "MIT" ]

386

2019-06-07T20:20:39.000Z

2022-03-30T17:35:01.000Z

plugins/minfraud/komand_minfraud/actions/__init__.py

lukaszlaszuk/insightconnect-plugins

8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892

[ "MIT" ]

43

2019-07-09T14:13:58.000Z

2022-03-28T12:04:46.000Z

# GENERATED BY KOMAND SDK - DO NOT EDIT from .account_lookup.action import AccountLookup from .all_lookup.action import AllLookup from .billing_lookup.action import BillingLookup from .card_lookup.action import CardLookup from .cart_lookup.action import CartLookup from .device_lookup.action import DeviceLookup from .email_lookup.action import EmailLookup from .event_lookup.action import EventLookup from .order_lookup.action import OrderLookup from .payment_lookup.action import PaymentLookup from .shipping_lookup.action import ShippingLookup

42.076923

50

0.859232

73

547

6.287671

0.452055

0.287582

0.431373

0

0.096892

547

12

51

45.583333

0.92915

0.067642

0

1

0

1

0

true

0

1

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1

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1

0

1

0

null

0

1

0

1

0

5

bfe27fe9229cd07b93680b62a614ccd6ac91ab8a

208

py

Python

wmt-etl/config.py

ministryofjustice/hmpps-wmt

66a85b029e2fc2b525b299f9e2ac1803b9cf8516

[ "MIT" ]

3

2017-02-27T17:09:20.000Z

2017-03-27T08:23:50.000Z

wmt-etl/config.py

ministryofjustice/hmpps-wmt

66a85b029e2fc2b525b299f9e2ac1803b9cf8516

[ "MIT" ]

3

2017-03-03T16:08:20.000Z

2017-03-16T17:19:34.000Z

wmt-etl/config.py

ministryofjustice/noms-wmt-alpha

66a85b029e2fc2b525b299f9e2ac1803b9cf8516

[ "MIT" ]

1

2021-04-11T06:54:44.000Z

import os DB_SERVER = os.getenv('WMT_DB_SERVER', 'localhost') DB_NAME = os.getenv('WMT_DB_NAME', 'wmt_db') DB_USERNAME = os.getenv('WMT_DB_USERNAME', 'wmt') DB_PASSWORD = os.getenv('WMT_DB_PASSWORD', 'wmt')

29.714286

51

0.735577

35

208

4

0.285714

0.214286

0.314286

0.371429

0

0.091346

208

6

52

34.666667

0.740741

0

0.360577

0

1

0

false

0.2

0

0.2

0

null

1

0

1

0

null

0

1

0

5

870a1fd5ff0795c011afc5632b304b463b0623e3

131

py

Python

testapp2/admin.py

gabrielbiasi/django-improved-permissions

9cf6d0ddb8a4dcfa2e58d3adbf1357e56a64ce71

[ "MIT" ]

12

2018-03-22T00:30:32.000Z

2021-04-24T16:26:08.000Z

testapp2/admin.py

s-sys/django-improved-permissions

9cf6d0ddb8a4dcfa2e58d3adbf1357e56a64ce71

[ "MIT" ]

27

2018-03-18T00:43:37.000Z

2020-06-05T18:09:18.000Z

testapp2/admin.py

gabrielbiasi/django-improved-permissions

9cf6d0ddb8a4dcfa2e58d3adbf1357e56a64ce71

[ "MIT" ]

2

2018-03-28T17:54:43.000Z

2021-01-11T21:17:08.000Z

""" testapp2 admin configs """ from django.contrib import admin from testapp2.models import Library admin.site.register(Library)

18.714286

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0.78626

17

131

6.058824

0.647059

0

0.017391

0.122137

131

6

36

21.833333

0.878261

0.167939

0

1

0

true

0

0.666667

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0.666667

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null

0

1

0

1

0

1

0

5

87234ddbc75c00fe76141a6b66832d15ac92c6f3

2,495

py

Python

slides/figs/draw.py

hiyouga/AMP-Poster-Slides-LaTeX

c1fd40aa5ef3216f17b4d27dc6e6092e3cc52e40

[ "MIT" ]

8

2021-05-25T11:56:48.000Z

2021-12-20T07:12:01.000Z

slides/figs/draw.py

hiyouga/AMP-Poster-Slides-LaTeX

c1fd40aa5ef3216f17b4d27dc6e6092e3cc52e40

[ "MIT" ]

1

2021-05-28T15:25:37.000Z

2021-05-30T05:01:24.000Z

slides/figs/draw.py

hiyouga/AMP-Poster-Slides-LaTeX

c1fd40aa5ef3216f17b4d27dc6e6092e3cc52e40

[ "MIT" ]

2

2021-05-26T01:39:53.000Z

2021-12-20T06:36:04.000Z

import matplotlib import numpy as np import matplotlib.pyplot as plt default_params = { 'text.usetex': False, 'font.family': 'Times New Roman', 'font.serif': 'Times New Roman' } if __name__ == '__main__': plt.rcParams.update(default_params) myfont1 = matplotlib.font_manager.FontProperties(fname='C:\\times.ttf', size=14) myfont2 = matplotlib.font_manager.FontProperties(fname='C:\\times.ttf', size=12) plt.figure(figsize=(5, 3)) x = np.linspace(0.001, 5, 1000) y1 = 0.001 * x ** 2 + 0.02 * 1 / x + 0.02 y2 = 0.12 * x ** 2 + 0.04 * 1 / x + 0.06 plt.plot(x, y1, color='b', linestyle='--', label='Training error') plt.plot(x, y2, color='g', linestyle='-', label='Generalization error') cx = 0.55 cy = 0.12 * cx ** 2 + 0.04 * 1 / cx + 0.06 plt.plot([cx, cx], [-0.01, cy], color='r', linestyle=':') plt.plot([-0.01, cx], [cy, cy], color='r', linestyle=':') plt.text(cx-0.3, -0.12, 'Optimal capacity', fontproperties=myfont2) plt.arrow(1.6, 0.21, 0.0, 0.12, head_width=0.03, head_length=0.03, shape='full', fc='black', ec='black', linewidth=1) plt.arrow(1.6, 0.21, 0.0, -0.12, head_width=0.03, head_length=0.03, shape='full', fc='black', ec='black', linewidth=1) plt.text(1.65, 0.18, 'Generalization gap', fontproperties=myfont2) plt.legend(loc='upper right', prop=myfont1) plt.xticks([0]) plt.yticks([]) plt.xlabel('Capacity', fontproperties=myfont1) plt.ylabel('Error', fontproperties=myfont1) plt.xlim((-0.01, 2.5)) plt.ylim((-0.01, 1.2)) plt.savefig('gap1.pdf', format='pdf', dpi=900, bbox_inches='tight') plt.figure(figsize=(5, 3)) x = np.linspace(0.001, 5, 1000) y1 = 0.005 * x ** 2 + 0.03 * 1 / x + 0.03 y2 = 0.04 * x ** 2 + 0.05 * 1 / x + 0.03 plt.plot(x, y1, color='b', linestyle='--', label='Training error') plt.plot(x, y2, color='g', linestyle='-', label='Generalization error') cx = 0.855 cy = 0.04 * cx ** 2 + 0.05 * 1 / cx + 0.03 plt.plot([cx, cx], [-0.01, cy], color='r', linestyle=':') plt.plot([-0.01, cx], [cy, cy], color='r', linestyle=':') plt.text(cx-0.3, -0.12, 'Optimal capacity', fontproperties=myfont2) plt.legend(loc='upper right', prop=myfont1) plt.xticks([0]) plt.yticks([]) plt.xlabel('Capacity', fontproperties=myfont1) plt.ylabel('Error', fontproperties=myfont1) plt.xlim((-0.01, 2.5)) plt.ylim((-0.01, 1.2)) plt.savefig('gap2.pdf', format='pdf', dpi=900, bbox_inches='tight')

43.77193

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0.784605

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0.103922

0.182365

2,495

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123

44.553571

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0

0.528302

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0.136273

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false

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0.056604

0

0.056604

0

null

0

1

0

null

0

5

872a7c2cdb92c261fe174b94da5759ed7dfbd97f

40

py

Python

expressive_regex/exceptions.py

fsadannn/expressive_regex

3bf113e8288a0f7d756f24cf882be8709630d4d3

[ "MIT" ]

2

2020-07-31T13:49:17.000Z

2020-09-16T14:47:23.000Z

expressive_regex/exceptions.py

fsadannn/expressive_regex

3bf113e8288a0f7d756f24cf882be8709630d4d3

[ "MIT" ]

null

expressive_regex/exceptions.py

fsadannn/expressive_regex

3bf113e8288a0f7d756f24cf882be8709630d4d3

[ "MIT" ]

null

class BadStatement(Exception): pass

13.333333

30

0.75

4

40

7.5

1

0

0.175

40

2

31

20

0.909091

0

1

0

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

5

874c9017ad17aa813ad7a4b4bd54385bf7e3cba6

91

py

Python

build/lib/acousondePy/__init__.py

SvenGastauer/acousondePy

94a99dc9de35d644a35cbfa3078110a67a35212e

[ "MIT" ]

null

build/lib/acousondePy/__init__.py

SvenGastauer/acousondePy

94a99dc9de35d644a35cbfa3078110a67a35212e

[ "MIT" ]

null

build/lib/acousondePy/__init__.py

SvenGastauer/acousondePy

94a99dc9de35d644a35cbfa3078110a67a35212e

[ "MIT" ]

null

from .MTRead import MTread,spec_plot,read_multiple_MT from .main import MTreadgui,acousonde

45.5

53

0.868132

14

91

5.428571

0.785714

0

0.076923

91

2

54

45.5

0.904762

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

87567263e4472013f3e9c6f40f7e91f2cff4f5d5

40

py

Python

tipos de datos/integer1.py

gabys12/portafolio-fundamento-de-programacion

c9b47f32e885ed6ae80b14133a609798ea034e19

[ "CNRI-Python" ]

null

tipos de datos/integer1.py

gabys12/portafolio-fundamento-de-programacion

c9b47f32e885ed6ae80b14133a609798ea034e19

[ "CNRI-Python" ]

null

tipos de datos/integer1.py

gabys12/portafolio-fundamento-de-programacion

c9b47f32e885ed6ae80b14133a609798ea034e19

[ "CNRI-Python" ]

null

x = 100 y = 50 print('x=', x, 'y=', y)

8

23

0.4

9

40

1.777778

0.555556

0

0.172414

0.275

40

4

24

10

0.37931

0

0.1

0

1

0

false

0

0.333333

1

null

0

1

0

1

0

null

0

5

5e8a67301e87d6b49ee5b0aa718dbabf712a571d

245

py

Python

main.py

glhrmfrts/instr

ba08fae5149c193ada0003c0f4ca042dca84e457

[ "MIT" ]

null

main.py

glhrmfrts/instr

ba08fae5149c193ada0003c0f4ca042dca84e457

[ "MIT" ]

null

main.py

glhrmfrts/instr

ba08fae5149c193ada0003c0f4ca042dca84e457

[ "MIT" ]

null

from instr.instruments import * from instr.effects import * s = Sqr().bind(tremolo(), echo(0.4, 0.8)).loop(2, [(244, 1), (289, 1), (365, 2)]).loop(4, [(244, 0.1), (289, 0.1), (365, 0.1), (1, 0.1), (237, 0.1), (1, 0.1)]).save('tests/instr.wav')

49

183

0.555102

49

245

2.77551

0.469388

0.088235

0.044118

0.058824

0.073529

0

0.206573

0.130612

245

4

184

61.25

0.431925

0

0.061224

0

1

0

false

0

0.666667

0

0.666667

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

5

5e8def353cd8038d157012651972bf4783cd5467

77

py

Python

planar_ising/lipton_tarjan/__init__.py

ValeryTyumen/planar_ising

5a1803487e1dd59c5d5e790cc949b7234bf52ac8

[ "MIT" ]

8

2019-05-02T20:27:21.000Z

2020-11-01T20:41:38.000Z

planar_ising/lipton_tarjan/__init__.py

ValeryTyumen/planar_ising

5a1803487e1dd59c5d5e790cc949b7234bf52ac8

[ "MIT" ]

1

2019-09-03T18:15:53.000Z

2019-09-06T16:41:12.000Z

planar_ising/lipton_tarjan/__init__.py

ValeryTyumen/planar_ising

5a1803487e1dd59c5d5e790cc949b7234bf52ac8

[ "MIT" ]

3

2019-08-11T23:08:58.000Z

2022-03-19T09:09:50.000Z

from .planar_separator import PlanarSeparator from . import separation_class

25.666667

45

0.87013

9

77

7.222222

0.777778

0

0.103896

77

2

46

38.5

0.942029

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

5e9c05834cf6ad1608c5d29f26bb72785dc3ceb3

45

py

Python

pyIOS/exceptions.py

jtdub/pyIOS

1842b92068e3b0a980d53e0719efd41dbbdaf082

[ "Apache-2.0" ]

12

2016-01-09T17:47:05.000Z

2022-02-09T18:09:41.000Z

pyIOS/exceptions.py

jtdub/pyIOS

1842b92068e3b0a980d53e0719efd41dbbdaf082

[ "Apache-2.0" ]

16

2016-01-05T15:49:31.000Z

2016-08-04T20:59:15.000Z

pyIOS/exceptions.py

jtdub/pyIOS

1842b92068e3b0a980d53e0719efd41dbbdaf082

[ "Apache-2.0" ]

1

2016-04-06T16:00:32.000Z

class InvalidInputError(Exception): pass

15

35

0.777778

4

45

8.75

1

0

0.155556

45

2

36

22.5

0.921053

0

1

0

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

5

5e9cfe480f48cebb3ee33cedf5c2da8409e69016

71

py

Python

purestorage/__init__.py

sile16/rest-client

01604e00e8a64157e056fca614d320c3afd0f2d1

[ "BSD-2-Clause" ]

20

2018-10-26T01:33:15.000Z

2022-03-31T19:56:08.000Z

purestorage/__init__.py

sile16/rest-client

01604e00e8a64157e056fca614d320c3afd0f2d1

[ "BSD-2-Clause" ]

15

2018-08-09T20:42:21.000Z

2022-01-14T15:59:58.000Z

purestorage/__init__.py

sile16/rest-client

01604e00e8a64157e056fca614d320c3afd0f2d1

[ "BSD-2-Clause" ]

16

2018-10-22T18:31:42.000Z

2021-08-09T15:33:35.000Z

from .purestorage import FlashArray, PureError, PureHTTPError, VERSION

35.5

70

0.84507

7

71

8.571429

1

0

0.098592

71

1

71

0.9375

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

5eb6ed393de918f8c3120b183de9a52d1c9d90da

216

py

Python

master/scripts/paths.py

OPU-Surveillance-System/monitoring

2c2c657c74fce9a5938d986372f9077708617d9c

[ "MIT" ]

4

2020-12-24T11:51:28.000Z

2022-02-08T09:02:38.000Z

master/scripts/paths.py

OPU-Surveillance-System/monitoring

2c2c657c74fce9a5938d986372f9077708617d9c

[ "MIT" ]

1

2021-11-16T02:54:35.000Z

master/scripts/paths.py

OPU-Surveillance-System/monitoring

2c2c657c74fce9a5938d986372f9077708617d9c

[ "MIT" ]

null

""" Define the environment paths """ #Path variables TEMPLATE_PATH = "/home/scom/documents/opu_surveillance_system/monitoring/master/" STATIC_PATH = "/home/scom/documents/opu_surveillance_system/monitoring/static/"

27

81

0.805556

26

216

6.461538

0.615385

0.095238

0.142857

0.25

0.619048

0

0.069444

216

7

82

30.857143

0.835821

0.199074

0

0.763636

0

1

0

false

0

1

0

null

0

1

0

1

0

1

null

0

5

5eb703c2f5ca89811146d4e9b20de24a3405a5d5

3,181

py

Python

tests/strategies/test_local_strategy.py

gijswobben/customs

72c0d071fe35ed84eb6d6371eb651edcd13a1044

[ "MIT" ]

null

tests/strategies/test_local_strategy.py

gijswobben/customs

72c0d071fe35ed84eb6d6371eb651edcd13a1044

[ "MIT" ]

null

tests/strategies/test_local_strategy.py

gijswobben/customs

72c0d071fe35ed84eb6d6371eb651edcd13a1044

[ "MIT" ]

null

from flask.globals import request import pytest from flask import Flask from typing import Dict from customs import Customs from customs.exceptions import UnauthorizedException from customs.strategies import LocalStrategy def test_local_strategy_initialization_without_customs(): class Local(LocalStrategy): def get_or_create_user(self, user: Dict) -> Dict: return super().get_or_create_user(user) def validate_credentials(self, username: str, password: str) -> Dict: return super().validate_credentials(username, password) with pytest.warns(UserWarning): print(Customs.get_instance()) strategy = Local() assert strategy.name == "local" def test_local_strategy_initialization_with_customs(): class Local(LocalStrategy): def get_or_create_user(self, user: Dict) -> Dict: return super().get_or_create_user(user) def validate_credentials(self, username: str, password: str) -> Dict: return super().validate_credentials(username, password) # Create customs app = Flask("TESTS") app.secret_key = "630738a8-3b13-4311-8018-87554d6f7e85" Customs(app) # Create the strategy strategy = Local() assert strategy.name == "local" # Cleanup of the Customs object used for testing Customs.remove_instance() def test_local_strategy_extract_crendentials(): class Local(LocalStrategy): def get_or_create_user(self, user: Dict) -> Dict: return super().get_or_create_user(user) def validate_credentials(self, username: str, password: str) -> Dict: return super().validate_credentials(username, password) # Create customs app = Flask("TESTS") app.secret_key = "630738a8-3b13-4311-8018-87554d6f7e85" Customs(app) # Create the strategy strategy = Local() with app.test_request_context("/?test=123", json={"bla": "bla"}): credentials = strategy.extract_credentials(request) assert credentials == {} with app.test_request_context("/?username=test&password=test"): credentials = strategy.extract_credentials(request) assert "username" in credentials assert "password" in credentials # Cleanup of the Customs object used for testing Customs.remove_instance() def test_local_strategy_authenticate(): class Local(LocalStrategy): def get_or_create_user(self, user: Dict) -> Dict: return super().get_or_create_user(user) def validate_credentials(self, username: str, password: str) -> Dict: return {} # Create customs app = Flask("TESTS") app.secret_key = "630738a8-3b13-4311-8018-87554d6f7e85" Customs(app) # Create the strategy strategy = Local() with app.test_request_context("/?test=123", json={"bla": "bla"}): with pytest.raises(UnauthorizedException): user = strategy.authenticate(request) with app.test_request_context("/?username=test&password=test"): user = strategy.authenticate(request) assert user == {} # Cleanup of the Customs object used for testing Customs.remove_instance()

30.586538

77

0.688463

368

3,181

5.774457

0.17663

0.018824

0.041412

0.056471

0.787294

0.755294

0.680471

0.634353

0

0.034731

0.212512

3,181

103

78

30.883495

0.813573

0.07702

0

0.703125

0

0.081681

0.056733

0

0.09375

1

0.1875

false

0.15625

0.109375

0.125

0.484375

0.015625

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

5

5ed705bdaa66e16d951b96579ba77a4976ae6a2d

66

py

Python

pygame_ui/__init__.py

oof6969696969/pygame_ui

ca59652f30718dd8c578d994239d3a2d7aadae9c

[ "MIT" ]

null

pygame_ui/__init__.py

oof6969696969/pygame_ui

ca59652f30718dd8c578d994239d3a2d7aadae9c

[ "MIT" ]

null

pygame_ui/__init__.py

oof6969696969/pygame_ui

ca59652f30718dd8c578d994239d3a2d7aadae9c

[ "MIT" ]

null

from lib.pygame_ui import UIManager, Widgets, Shapes, load_theme

33

65

0.818182

10

66

5.2

1

0

0.121212

66

1

66

0.896552

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

0d6cfdc31d74171c37475fd7569d74d50b976420

24

py

Python

test.py

JohnnyBruh/Repository

f8bfb14737eee78fa8da400c7f6ddb21efda4baf

[ "CC0-1.0" ]

null

test.py

JohnnyBruh/Repository

f8bfb14737eee78fa8da400c7f6ddb21efda4baf

[ "CC0-1.0" ]

null

test.py

JohnnyBruh/Repository

f8bfb14737eee78fa8da400c7f6ddb21efda4baf

[ "CC0-1.0" ]

null

print("yaaaay") input()

12

16

0.666667

3

24

5.333333

1

0

0.083333

24

2

17

12

0.727273

0

0.25

0

1

0

true

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

5

0d736e7e49cff33ae106086347e250953188ade6

249

py

Python

Multiples of 3 and 5.py

ahmedharbi197/Project-Euler

596fa7622233868a08200f2d7fe3b7e83d0af41f

[ "MIT" ]

1

2019-06-10T23:10:38.000Z

Multiples of 3 and 5.py

ahmedharbi197/Project-Euler

596fa7622233868a08200f2d7fe3b7e83d0af41f

[ "MIT" ]

null

Multiples of 3 and 5.py

ahmedharbi197/Project-Euler

596fa7622233868a08200f2d7fe3b7e83d0af41f

[ "MIT" ]

null

import sys t = int(input().strip()) for a0 in range(t): n = int(input().strip()) def preSum(q): return (q*(1+q) //2 ) result = 3*preSum(int((n-1)//3)) + 5*preSum(int((n-1)//5)) - 15*preSum(int((n-1)//15)) print(int(result))

24.9

90

0.526104

45

249

2.911111

0.488889

0.206107

0.229008

0.251908

0

0.070707

0.204819

249

9

91

27.666667

0.590909

0

1

0.125

false

0

0.125

0.375

0.125

0

null

1

0

1

0

null

0

1

0

5

0d92dd46b5c6cda3a158d46142ec944eda28a213

7,986

py

Python

fairmlhealth/__fairness_metrics.py

masino-lab/fairMLHealth

943ffed5f57997401823bd2afc257f34f76ea157

[ "MIT" ]

19

2020-10-29T10:14:59.000Z

2022-03-20T06:27:35.000Z

fairmlhealth/__fairness_metrics.py

masino-lab/fairMLHealth

943ffed5f57997401823bd2afc257f34f76ea157

[ "MIT" ]

52

2020-10-14T19:21:27.000Z

2021-09-15T19:01:52.000Z

fairmlhealth/__fairness_metrics.py

masino-lab/fairMLHealth

943ffed5f57997401823bd2afc257f34f76ea157

[ "MIT" ]

9

2020-12-02T21:40:27.000Z

2021-11-01T18:09:10.000Z

""" Custom Fairness Metrics Note that ratio and difference computation is handled by AIF360's sklearn.metrics module. As of the V 0.4.0 release, these are calculated as [unprivileged/privileged] and [unprivileged - privileged], respectively """ from typing import Callable from aif360.sklearn.metrics import difference, ratio import numpy as np import pandas as pd from warnings import catch_warnings, filterwarnings from .performance_metrics import ( false_positive_rate, true_positive_rate, true_negative_rate, false_negative_rate, precision, ) def __manage_undefined_ratios(func: Callable): """ Wraps ratio functions to return NaN values instead of 0.0 in cases where the ratio is undefined """ def wrapper(*args, **kwargs): funcname = getattr(func, "__name__", "an unknown function") msg = ( "The ratio is ill-defined and being set to 0.0 because" + f" '{funcname}' for privileged samples is 0." ) with catch_warnings(record=True) as w: filterwarnings("ignore", message=msg) res = func(*args, **kwargs) if len(w) > 0: return np.nan else: return res return wrapper @__manage_undefined_ratios def ppv_ratio(y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1): """ Returns the between-group ratio of Postive Predictive Values Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values prtc_attr (str): name of the protected attribute priv_grp (int, optional): . Defaults to 1. Returns: Number """ return ratio(precision, y_true, y_pred, prot_attr=pa_name, priv_group=priv_grp) @__manage_undefined_ratios def tpr_ratio(y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1): """ Returns the between-group ratio of True Positive Rates Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values prtc_attr (str): name of the protected attribute priv_grp (int, optional): . Defaults to 1. Returns: Number """ return ratio( true_positive_rate, y_true, y_pred, prot_attr=pa_name, priv_group=priv_grp ) @__manage_undefined_ratios def fpr_ratio(y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1): """ Returns the between-group ratio of False Positive Rates Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values prtc_attr (str): name of the protected attribute priv_grp (int, optional): . Defaults to 1. Returns: Number """ return ratio( false_positive_rate, y_true, y_pred, prot_attr=pa_name, priv_group=priv_grp ) @__manage_undefined_ratios def tnr_ratio(y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1): """ Returns the between-group ratio of True Negative Rates Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values prtc_attr (str): name of the protected attribute priv_grp (int, optional): . Defaults to 1. Returns: Number """ return ratio( true_negative_rate, y_true, y_pred, prot_attr=pa_name, priv_group=priv_grp ) @__manage_undefined_ratios def fnr_ratio(y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1): """ Returns the between-group ratio of False Negative Rates Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values prtc_attr (str): name of the protected attribute priv_grp (int, optional): . Defaults to 1. Returns: Number """ return ratio( false_negative_rate, y_true, y_pred, prot_attr=pa_name, priv_group=priv_grp ) def ppv_diff(y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1): """ Returns the between-group difference of Positive Predictive Values Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values prtc_attr (str): name of the protected attribute priv_grp (int, optional): . Defaults to 1. Returns: Number """ return difference(precision, y_true, y_pred, prot_attr=pa_name, priv_group=priv_grp) def tpr_diff(y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1): """ Returns the between-group difference of True Positive Rates Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values prtc_attr (str): name of the protected attribute priv_grp (int, optional): . Defaults to 1. Returns: Number """ return difference( true_positive_rate, y_true, y_pred, prot_attr=pa_name, priv_group=priv_grp ) def fpr_diff(y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1): """ Returns the between-group difference of False Positive Rates Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values prtc_attr (str): name of the protected attribute priv_grp (int, optional): . Defaults to 1. Returns: Number """ return difference( false_positive_rate, y_true, y_pred, prot_attr=pa_name, priv_group=priv_grp ) def tnr_diff(y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1): """ Returns the between-group difference of True Negative Rates Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values prtc_attr (str): name of the protected attribute priv_grp (int, optional): . Defaults to 1. Returns: Number """ return difference( true_negative_rate, y_true, y_pred, prot_attr=pa_name, priv_group=priv_grp ) def fnr_diff(y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1): """ Returns the between-group difference of False Negative Rates Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values prtc_attr (str): name of the protected attribute priv_grp (int, optional): . Defaults to 1. Returns: Number """ return difference( false_negative_rate, y_true, y_pred, prot_attr=pa_name, priv_group=priv_grp ) """ Combined Metrics """ def eq_odds_diff(y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1): """ Returns the greatest discrepancy between the between-group FPR difference and the between-group TPR difference Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values prtc_attr (str): name of the protected attribute priv_grp (int, optional): . Defaults to 1. Returns: Number """ fprD = fpr_diff(y_true, y_pred, pa_name=pa_name, priv_grp=priv_grp) tprD = tpr_diff(y_true, y_pred, pa_name=pa_name, priv_grp=priv_grp) if abs(fprD) > abs(tprD): return fprD else: return tprD def eq_odds_ratio( y_true: pd.Series, y_pred: pd.Series, pa_name: str, priv_grp: int = 1 ): """ Returns the greatest discrepancy between the between-group FPR ratio and the between-group TPR ratio Args: y_true (pd.Series): true target values y_pred (pd.Series): predicted target values priv_grp (int, optional): . Defaults to 1. """ fprR = fpr_ratio(y_true, y_pred, pa_name=pa_name, priv_grp=priv_grp) tprR = tpr_ratio(y_true, y_pred, pa_name=pa_name, priv_grp=priv_grp) if np.isnan(fprR) or np.isnan(tprR): return np.nan elif round(abs(fprR - 1), 6) > round(abs(tprR - 1), 6): return fprR else: return tprR

29.577778

88

0.660155

1,153

7,986

4.35386

0.117086

0.076494

0.033466

0.062151

0.780478

0.772112

0.766335

0

0.007182

0.250313

7,986

269

89

29.687732

0.831301

0.464688

0

0.302326

0

0.034261

0

1

0.162791

false

0

0.069767

0

0.44186

0

null

0

1

0

null

0

5

0dc892c0ef85acbf71fdb47d9850dae8da0e6d7a

10,355

py

Python

code/services/synergy_services.py

EdsonECM17/DS_Proyecto_02_Synergy_Logistics

a6c347f99e69b926d337db82653dd16850668f4b

[ "MIT" ]

null

code/services/synergy_services.py

EdsonECM17/DS_Proyecto_02_Synergy_Logistics

a6c347f99e69b926d337db82653dd16850668f4b

[ "MIT" ]

null

code/services/synergy_services.py

EdsonECM17/DS_Proyecto_02_Synergy_Logistics

a6c347f99e69b926d337db82653dd16850668f4b

[ "MIT" ]

null

from typing import List from processing.sl_filters import SynergyLogisticsFilters class Service(SynergyLogisticsFilters): """ Clase que contine servicios para el analisis de la tabla de Synergy Logistics. """ def get_routes_list(self, direction:str or None = None) -> List: """Genera una lista con todas las rutas diferentes de la tabla. Args: direction (str or None, optional): Dirección de transacción. Defaults to None. Returns: List: Lista con rutas con formato origen-destino. """ routes_list = [] # Filter tables by direction filtered_table = self.filter_routes_df(direction=direction) # Check row by row table for index, row in filtered_table.iterrows(): # route=origin-destination route = (row['origin']+ "-" + row['destination']) if not route in routes_list: routes_list.append(route) return routes_list def get_total_elements(self, direction:str or None = None, year:int or None = None, transport_mode:str or None = None) -> int: """ Cuenta el número de transacciones en una tabla filtrada. Se pueden filtrar resultados por dirección, año y/o medio de transporte. Args: direction (str or None, optional): Dirección de transacción. Defaults to None. year (int or None, optional): Año de transacciones. Defaults to None. transport_mode (str or None, optional): Tipo de medio de transporte. Defaults to None. Returns: int: Total de casos en tabla filtrada. """ # Tabla filtrada filtered_table = self.filter_routes_df(direction=direction, start_year=year, end_year=year, transport_mode=transport_mode) # Contar filas en la tabla elements_count= len(filtered_table) return elements_count def get_route_frecuency(self, route:str, direction:str or None = None, year:int or None = None)-> int: """ Cuenta las veces que una ruta aparece en una tabla filtrada. Se pueden filtrar resultados por dirección, año y/o medio de transporte. Args: route (str): Rutas con formato origen-destino. direction (str or None, optional): Dirección de transacción. Defaults to None. year (int or None, optional): Año de transacciones. Defaults to None. Returns: int: Numero de apariciones de ruta en la tabla filtrada. """ # Obtener origen y destino para filtros origin, destination = route.split("-") # Tabla filtrada filtered_table = self.filter_routes_df(origin=origin, destination=destination, direction=direction, start_year=year, end_year=year) # Contar filas en la tabla route_frecuency = len(filtered_table) return route_frecuency def get_total_value(self, direction:str or None = None, year:int or None = None, transport_mode: str or None = None) -> int: """ Suma el valor total dentro de una tabla filtrada. Se pueden filtrar resultados por dirección, año y/o medio de transporte. Args: route (str): Rutas con formato origen-destino. direction (str or None, optional): Dirección de transacción. Defaults to None. year (int or None, optional): Año de transacciones. Defaults to None. transport_mode (str or None, optional): Tipo de medio de transporte. Defaults to None. Returns: int: suma de valor de elementos en tabla filtrada. """ filtered_table = self.filter_routes_df(direction=direction, start_year=year, end_year=year, transport_mode=transport_mode) total_value = filtered_table["total_value"].sum() return total_value def get_route_value(self, route:str, direction:str or None = None, year:int or None = None) -> int: """ Suma el valor total para una ruta especifica dentro de una tabla filtrada. Se pueden filtrar resultados por dirección, año y/o medio de transporte. Args: route (str): Rutas con formato origen-destino. direction (str or None, optional): Dirección de transacción. Defaults to None. year (int or None, optional): Año de transacciones. Defaults to None. transport_mode (str or None, optional): Tipo de medio de transporte. Defaults to None. Returns: int: suma de valor de elementos en tabla filtrada. """ origin, destination = route.split("-") filtered_table = self.filter_routes_df(origin=origin, destination=destination, direction=direction, start_year=year, end_year=year) route_value = filtered_table["total_value"].sum() return route_value def get_top_ten(self, all_cases: dict) -> dict: """De un diccionario de elementos se obtienen los 10 casos con mejores resultados. Args: all_cases (dict): Diccionario con todos los casos Returns: List: Lista con los 10 casos con mejores resultados. """ top_ten_cases = sorted(all_cases, key=all_cases.get, reverse=True)[:10] top_ten_dict = {} for case in top_ten_cases: top_ten_dict[case] = all_cases[case] return top_ten_dict def get_transport_frecuency(self, transport:str, direction:str or None = None, year:int or None = None)-> int: """ Cuenta las veces que un transporte aparece en una tabla filtrada. Se pueden filtrar resultados por dirección, año y/o medio de transporte. Args: transport (str): Tipo de medio de transporte. direction (str or None, optional): Dirección de transacción. Defaults to None. year (int or None, optional): Año de transacciones. Defaults to None. Returns: int: Numero de apariciones de transporte en la tabla filtrada. """ # Tabla filtrada filtered_table = self.filter_routes_df(transport_mode=transport, direction=direction, start_year=year, end_year=year) # Contar filas en la tabla transport_frecuency = len(filtered_table) return transport_frecuency def get_transport_value(self, transport:str, direction:str or None = None, year:int or None = None) -> int: """ Suma el valor total para un transporte especifico dentro de una tabla filtrada. Se pueden filtrar resultados por dirección, año y/o medio de transporte. Args: transport (str): Tipo de medio de transporte. direction (str or None, optional): Dirección de transacción. Defaults to None. year (int or None, optional): Año de transacciones. Defaults to None. Returns: int: suma de valor de elementos en tabla filtrada. """ filtered_table = self.filter_routes_df(transport_mode=transport, direction=direction, start_year=year, end_year=year) transport_value = filtered_table["total_value"].sum() return transport_value def get_country_frecuency(self, origin:str or None = None, destination:str or None = None, direction:str or None = None, year:int or None = None)-> int: """ Cuenta las veces que un pais aparece en una tabla filtrada. Se pueden filtrar resultados por dirección, año y/o medio de transporte. Args: origin (str or None, optional): Pais de origen. Defaults to None. destination (str or None, optional): Pais de destino. Defaults to None. direction (str or None, optional): Dirección de transacción. Defaults to None. year (int or None, optional): Año de transacciones. Defaults to None. Returns: int: Numero de apariciones de transporte en la tabla filtrada. """ # Tabla filtrada filtered_table = self.filter_routes_df(origin=origin, destination=destination, direction=direction, start_year=year, end_year=year) # Contar filas en la tabla transport_frecuency = len(filtered_table) return transport_frecuency def get_country_value(self, origin:str or None = None, destination:str or None = None, direction:str or None = None, year:int or None = None) -> int: """ Suma el valor total para un pais especifico dentro de una tabla filtrada. Se pueden filtrar resultados por dirección, año y/o medio de transporte. Args: origin (str or None, optional): Pais de origen. Defaults to None. destination (str or None, optional): Pais de destino. Defaults to None. direction (str or None, optional): Dirección de transacción. Defaults to None. year (int or None, optional): Año de transacciones. Defaults to None. Returns: int: suma de valor de elementos en tabla filtrada. """ filtered_table = self.filter_routes_df(origin=origin, destination=destination, direction=direction, start_year=year, end_year=year) transport_value = filtered_table["total_value"].sum() return transport_value def reorder_dict_max(self, data_dict: dict) -> dict: """ Ordena diccionario a partir de valores de mayor a menor. Elimita los elementos del diccionario que tengan un valor de 0. Args: data_dict (dict): Diccionario de datos desordenados. Returns: dict: Diccionario de datos filtrados. """ # Crear nuevo diccionario para almacenar datos ordenados ordered_data_dict = {} ordered_keys = sorted(data_dict, key=data_dict.get, reverse=True) for key in ordered_keys: # if value is 0, skip if data_dict[key] == 0: continue # if value > 0 else: ordered_data_dict[key]=data_dict[key] return ordered_data_dict

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218cc1a2784c43a8ecfb6c736b8023171e1890c1

149

py

Python

vb2py/PythonCard/__init__.py

ceprio/xl_vb2py

899fec0301140fd8bd313e8c80b3fa839b3f5ee4

[ "BSD-3-Clause" ]

null

vb2py/PythonCard/__init__.py

ceprio/xl_vb2py

899fec0301140fd8bd313e8c80b3fa839b3f5ee4

[ "BSD-3-Clause" ]

null

vb2py/PythonCard/__init__.py

ceprio/xl_vb2py

899fec0301140fd8bd313e8c80b3fa839b3f5ee4

[ "BSD-3-Clause" ]

null

""" Created: 2001/08/05 Purpose: Turn PythonCard into a package __version__ = "$Revision: 1.1.1.1 $" __date__ = "$Date: 2001/08/06 19:53:11 $" """

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21af95c3e6f5614235525e918b9f73b1e391d922

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py

Python

fzzzMaskBackend/users/serializers.py

FZZZMask/backend

4f987e96a5ff42d89cf536c099b944f5f7254764

[ "BSD-3-Clause" ]

null

fzzzMaskBackend/users/serializers.py

FZZZMask/backend

4f987e96a5ff42d89cf536c099b944f5f7254764

[ "BSD-3-Clause" ]

3

2020-02-11T23:24:39.000Z

2021-06-04T21:45:25.000Z

fzzzMaskBackend/users/serializers.py

FZZZMask/backend

4f987e96a5ff42d89cf536c099b944f5f7254764

[ "BSD-3-Clause" ]

null

from rest_framework import serializers

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21b4b857672198b3794c4cd67434ee8e238bf40c

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py

Python

util/prelude.py

sinsay/ds_define

0ee89edfc3ad1ed37c5b88e13936229baf50a966

[ "Apache-2.0" ]

null

util/prelude.py

sinsay/ds_define

0ee89edfc3ad1ed37c5b88e13936229baf50a966

[ "Apache-2.0" ]

null

util/prelude.py

sinsay/ds_define

0ee89edfc3ad1ed37c5b88e13936229baf50a966

[ "Apache-2.0" ]

null

from .enum import EnumBase def is_builtin_type(obj) -> bool: """ 检查 obj 是否基础类型 """ return isinstance(obj, (int, str, float, bool)) or obj is None

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21b737190d56432c7d4ca921f5d6f60d7150164a

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py

Python

batch/batch/public_gcr_images.py

MariusDanner/hail

5ca0305f8243b5888931b1afaa1fbfb617dee097

[ "MIT" ]

null

batch/batch/public_gcr_images.py

MariusDanner/hail

5ca0305f8243b5888931b1afaa1fbfb617dee097

[ "MIT" ]

null

batch/batch/public_gcr_images.py

MariusDanner/hail

5ca0305f8243b5888931b1afaa1fbfb617dee097

[ "MIT" ]

null

from typing import List def public_gcr_images(project: str) -> List[str]: # the worker cannot import batch_configuration because it does not have all the environment # variables return [f'gcr.io/{project}/{name}' for name in ('query', 'hail', 'python-dill', 'batch-worker')]

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py

Python

Other_AIMA_Scripts/planning.py

erensezener/aima-based-irl

fbbe28986cec0b5e58fef0f00338a180ed03759a

[ "MIT" ]

12

2015-06-17T05:15:40.000Z

2021-05-18T15:39:33.000Z

Other_AIMA_Scripts/planning.py

erensezener/aima-based-irl

fbbe28986cec0b5e58fef0f00338a180ed03759a

[ "MIT" ]

1

2020-03-14T08:45:49.000Z

Other_AIMA_Scripts/planning.py

erensezener/aima-based-irl

fbbe28986cec0b5e58fef0f00338a180ed03759a

[ "MIT" ]

5

2016-09-10T19:16:56.000Z

2018-10-10T05:09:03.000Z

"""Planning (Chapters 11-12) """ from __future__ import generators

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21ee59da3e9f824ace6a440137a55162daab5528

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py

Python

Timers.py

elegenstein-tgm/astrosim

1b09a32f543f5cc810621f8beaff20d57d0add22

[ "MIT" ]

null

Timers.py

elegenstein-tgm/astrosim

1b09a32f543f5cc810621f8beaff20d57d0add22

[ "MIT" ]

null

Timers.py

elegenstein-tgm/astrosim

1b09a32f543f5cc810621f8beaff20d57d0add22

[ "MIT" ]

null

class Timer: def __init__(self, duration, ticks): self.duration = duration self.ticks = ticks self.thread = None def start(self): pass # start Thread here

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1d09f4af7ac6dd139ab8ee8934a37f14f97144a4

17,847

py

Python

scripts/trajectories.py

Miedema/MCNetwork

daab1fe5880c47695c6e21124f99aa6b2589aba1

[ "Apache-2.0" ]

null

scripts/trajectories.py

Miedema/MCNetwork

daab1fe5880c47695c6e21124f99aa6b2589aba1

[ "Apache-2.0" ]

null

scripts/trajectories.py

Miedema/MCNetwork

daab1fe5880c47695c6e21124f99aa6b2589aba1

[ "Apache-2.0" ]

1

2021-10-05T14:34:30.000Z

#!/usr/bin/python3 from tools import * from sys import argv from os.path import join import h5py import matplotlib.pylab as plt from matplotlib.patches import Wedge import numpy as np if len(argv) > 1: pathToSimFolder = argv[1] else: pathToSimFolder = "../data/" parameters, electrodes = readParameters(pathToSimFolder) electrodeNumber = len(electrodes) acceptorPos = np.zeros((int(parameters["acceptorNumber"]), 2)) try: donorPos = np.zeros((int(parameters["donorNumber"]), 2)) except KeyError: donorPos = np.zeros( (int(parameters["acceptorNumber"] * parameters["compensationFactor"]), 2) ) with open(join(pathToSimFolder, "device.txt")) as deviceFile: line = next(deviceFile) line = next(deviceFile) for i in range(acceptorPos.shape[0]): acceptorPos[i] = next(deviceFile).split(" ") line = next(deviceFile) line = next(deviceFile) for i in range(donorPos.shape[0]): donorPos[i] = next(deviceFile).split(" ") # print(acceptorPos) # print(donorPos) electrodePositions = np.empty((len(electrodes), 2)) for i in range(len(electrodes)): if parameters["geometry"] == "rect": if electrodes[i][1] == 0: electrodePositions[i] = [0, electrodes[i][0] * parameters["lenY"]] if electrodes[i][1] == 1: electrodePositions[i] = [ parameters["lenX"], electrodes[i][0] * parameters["lenY"], ] if electrodes[i][1] == 2: electrodePositions[i] = [electrodes[i][0] * parameters["lenX"], 0] if electrodes[i][1] == 3: electrodePositions[i] = [ electrodes[i][0] * parameters["lenX"], parameters["lenY"], ] elif parameters["geometry"] == "circle": electrodePositions[i] = [ parameters["radius"] * np.cos(electrodes[i][0] / 360 * 2 * np.pi), parameters["radius"] * np.sin(electrodes[i][0] / 360 * 2 * np.pi), ] # print(electrodePositions) def colorMaker(x): from matplotlib import colors from scipy.interpolate import interp1d cols = ["darkred", "darkgreen"] rgbaData = np.array([colors.to_rgba(c) for c in cols]) rInterpolater = interp1d(np.linspace(0, 1, len(cols)), rgbaData[:, 0]) gInterpolater = interp1d(np.linspace(0, 1, len(cols)), rgbaData[:, 1]) bInterpolater = interp1d(np.linspace(0, 1, len(cols)), rgbaData[:, 2]) return np.array([rInterpolater(x), gInterpolater(x), bInterpolater(x), 1]) inp = ["0_0", "0_1", "1_0", "1_1"] for fileNumber in [1, 2, 3, 4]: print(inp[fileNumber - 1]) # for fileNumber in [1]: data = np.genfromtxt( join(pathToSimFolder, f"swapTrackFile{fileNumber}.txt"), delimiter=";", dtype=int, ) trajectoriesSortedByStartEnd = [ [[] for j in range(len(electrodes))] for i in range(len(electrodes)) ] trajectories = [] hops = 20000 IDs = {} hitID = 0 for i in range(hops): hoppingSite1 = data[i, 0] hoppingSite2 = data[i, 1] # print("hoppingSite1",hoppingSite1,"hoppingSite2",hoppingSite2) if hoppingSite1 in IDs: ID = IDs[hoppingSite1] del IDs[hoppingSite1] # print("found ID",ID) else: ID = hitID hitID += 1 trajectories.append([]) # print("new ID", ID) if hoppingSite2 < parameters["acceptorNumber"]: IDs[hoppingSite2] = ID trajectories[ID].append([hoppingSite1, hoppingSite2]) # sort trajectories for i in range(len(trajectories)): if trajectories[i][0][0] >= parameters["acceptorNumber"]: if trajectories[i][-1][1] >= parameters["acceptorNumber"]: trajectoriesSortedByStartEnd[ trajectories[i][0][0] - int(parameters["acceptorNumber"]) ][trajectories[i][-1][1] - int(parameters["acceptorNumber"])].append( trajectories[i] ) # print(trajectories[i][0][0], trajectories[i][-1][1]) for k in range(len(electrodes)): fig, ax = plt.subplots(1, 1, figsize=(4.980614173228346, 3.2)) electodePlotWidth = 8 for i in range(len(electrodes)): if i == parameters["outputElectrode"]: col = "blue" elif i == parameters["inputElectrode1"]: if fileNumber in [3, 4]: col = "red" else: col = "rosybrown" elif i == parameters["inputElectrode2"]: if fileNumber in [2, 4]: col = "red" else: col = "rosybrown" else: col = "green" if parameters["geometry"] == "rect": if electrodes[i][1] == 0: angle = 0 xy = ( 0 - electodePlotWidth / 2, electrodes[i][0] * parameters["lenY"] - parameters["electrodeWidth"] / 2, ) elif electrodes[i][1] == 1: angle = 0 xy = ( parameters["lenX"] - electodePlotWidth / 2, electrodes[i][0] * parameters["lenY"] - parameters["electrodeWidth"] / 2, ) elif electrodes[i][1] == 2: angle = 90 xy = ( electrodes[i][0] * parameters["lenX"] + parameters["electrodeWidth"] / 2, 0 - electodePlotWidth / 2, ) elif electrodes[i][1] == 3: angle = 90 xy = ( electrodes[i][0] * parameters["lenX"] + parameters["electrodeWidth"] / 2, parameters["lenY"] - electodePlotWidth / 2, ) ax.add_artist( plt.Rectangle( xy, electodePlotWidth, parameters["electrodeWidth"], angle=angle, fc=col, ec=col, zorder=-1, ) ) elif parameters["geometry"] == "circle": electrodeWidth = ( parameters["electrodeWidth"] / (parameters["radius"] * 2 * np.pi) * 360 ) # in degrees ax.add_artist( Wedge( (0, 0), parameters["radius"] + electodePlotWidth / 2, electrodes[i][0] - electrodeWidth / 2, electrodes[i][0] + electrodeWidth / 2, width=electodePlotWidth, fc=col, ec=col, zorder=-1, ) ) ax.scatter(acceptorPos[:, 0], acceptorPos[:, 1], c="k", marker=".", s=20) ax.scatter(donorPos[:, 0], donorPos[:, 1], c="k", marker="x", s=20) for l in range(len(electrodes)): trajectories = trajectoriesSortedByStartEnd[k][l] for i in range(len(trajectories)): for j in range(len(trajectories[i])): hoppingSite1 = trajectories[i][j][0] hoppingSite2 = trajectories[i][j][1] if hoppingSite1 >= parameters["acceptorNumber"]: x1, y1 = ( electrodePositions[ hoppingSite1 - int(parameters["acceptorNumber"]) ][0], electrodePositions[ hoppingSite1 - int(parameters["acceptorNumber"]) ][1], ) else: x1, y1 = ( acceptorPos[hoppingSite1, 0], acceptorPos[hoppingSite1, 1], ) if hoppingSite2 >= parameters["acceptorNumber"]: x2, y2 = ( electrodePositions[ hoppingSite2 - int(parameters["acceptorNumber"]) ][0], electrodePositions[ hoppingSite2 - int(parameters["acceptorNumber"]) ][1], ) else: x2, y2 = ( acceptorPos[hoppingSite2, 0], acceptorPos[hoppingSite2, 1], ) # ax.plot([x1,x2],[y1,y2],"-",alpha=0.05,color="k",linewidth=2) ax.plot( [x1, x2], [y1, y2], "-", alpha=0.05, color=color(l, len(electrodes)), linewidth=2, ) # if currentRatio>0.5: # ax.arrow((x2+x1)/2,(y2+y1)/2,(x2-x1)*0.001,(y2-y1)*0.001,color=colorMaker(abs(currentRatio-0.5)*2),ec=None,alpha=absBins[i,j],linewidth=0,head_width=(currentRatio-0.5)*20) ax.axis("off") if parameters["geometry"] == "circle": ax.add_artist( plt.Circle((0, 0), parameters["radius"], fc="none", ec="k", zorder=-2) ) elif parameters["geometry"] == "rect": ax.add_artist( plt.Rectangle( (0, 0), parameters["lenX"], parameters["lenY"], fc="none", ec="k", zorder=-2, ) ) if parameters["geometry"] == "rect": ax.set_xlim( -electodePlotWidth / 2, parameters["lenX"] + electodePlotWidth / 2 ) ax.set_ylim( -electodePlotWidth / 2, parameters["lenY"] + electodePlotWidth / 2 ) elif parameters["geometry"] == "circle": ax.set_xlim( -parameters["radius"] - electodePlotWidth, parameters["radius"] + electodePlotWidth, ) ax.set_ylim( -parameters["radius"] - electodePlotWidth, parameters["radius"] + electodePlotWidth, ) ax.set_aspect("equal") plt.savefig( join(pathToSimFolder, f"trajectory_fromEl_{k}_{inp[fileNumber-1]}.png"), bbox_inches="tight", dpi=300, ) # plt.show() plt.close(fig) for k in range(len(electrodes)): fig, ax = plt.subplots(1, 1, figsize=(4.980614173228346, 3.2)) electodePlotWidth = 8 for i in range(len(electrodes)): if i == parameters["outputElectrode"]: col = "blue" elif i == parameters["inputElectrode1"]: if fileNumber in [3, 4]: col = "red" else: col = "rosybrown" elif i == parameters["inputElectrode2"]: if fileNumber in [2, 4]: col = "red" else: col = "rosybrown" else: col = "green" if parameters["geometry"] == "rect": if electrodes[i][1] == 0: angle = 0 xy = ( 0 - electodePlotWidth / 2, electrodes[i][0] * parameters["lenY"] - parameters["electrodeWidth"] / 2, ) elif electrodes[i][1] == 1: angle = 0 xy = ( parameters["lenX"] - electodePlotWidth / 2, electrodes[i][0] * parameters["lenY"] - parameters["electrodeWidth"] / 2, ) elif electrodes[i][1] == 2: angle = 90 xy = ( electrodes[i][0] * parameters["lenX"] + parameters["electrodeWidth"] / 2, 0 - electodePlotWidth / 2, ) elif electrodes[i][1] == 3: angle = 90 xy = ( electrodes[i][0] * parameters["lenX"] + parameters["electrodeWidth"] / 2, parameters["lenY"] - electodePlotWidth / 2, ) ax.add_artist( plt.Rectangle( xy, electodePlotWidth, parameters["electrodeWidth"], angle=angle, fc=col, ec=col, zorder=-1, ) ) elif parameters["geometry"] == "circle": electrodeWidth = ( parameters["electrodeWidth"] / (parameters["radius"] * 2 * np.pi) * 360 ) # in degrees ax.add_artist( Wedge( (0, 0), parameters["radius"] + electodePlotWidth / 2, electrodes[i][0] - electrodeWidth / 2, electrodes[i][0] + electrodeWidth / 2, width=electodePlotWidth, fc=col, ec=col, zorder=-1, ) ) ax.scatter(acceptorPos[:, 0], acceptorPos[:, 1], c="k", marker=".", s=20) ax.scatter(donorPos[:, 0], donorPos[:, 1], c="k", marker="x", s=20) for l in range(len(electrodes)): trajectories = trajectoriesSortedByStartEnd[l][k] for i in range(len(trajectories)): for j in range(len(trajectories[i])): hoppingSite1 = trajectories[i][j][0] hoppingSite2 = trajectories[i][j][1] if hoppingSite1 >= parameters["acceptorNumber"]: x1, y1 = ( electrodePositions[ hoppingSite1 - int(parameters["acceptorNumber"]) ][0], electrodePositions[ hoppingSite1 - int(parameters["acceptorNumber"]) ][1], ) else: x1, y1 = ( acceptorPos[hoppingSite1, 0], acceptorPos[hoppingSite1, 1], ) if hoppingSite2 >= parameters["acceptorNumber"]: x2, y2 = ( electrodePositions[ hoppingSite2 - int(parameters["acceptorNumber"]) ][0], electrodePositions[ hoppingSite2 - int(parameters["acceptorNumber"]) ][1], ) else: x2, y2 = ( acceptorPos[hoppingSite2, 0], acceptorPos[hoppingSite2, 1], ) # ax.plot([x1,x2],[y1,y2],"-",alpha=0.05,color="k",linewidth=2) ax.plot( [x1, x2], [y1, y2], "-", alpha=0.05, color=color(l, len(electrodes)), linewidth=2, ) # if currentRatio>0.5: # ax.arrow((x2+x1)/2,(y2+y1)/2,(x2-x1)*0.001,(y2-y1)*0.001,color=colorMaker(abs(currentRatio-0.5)*2),ec=None,alpha=absBins[i,j],linewidth=0,head_width=(currentRatio-0.5)*20) ax.axis("off") if parameters["geometry"] == "circle": ax.add_artist( plt.Circle((0, 0), parameters["radius"], fc="none", ec="k", zorder=-2) ) elif parameters["geometry"] == "rect": ax.add_artist( plt.Rectangle( (0, 0), parameters["lenX"], parameters["lenY"], fc="none", ec="k", zorder=-2, ) ) if parameters["geometry"] == "rect": ax.set_xlim( -electodePlotWidth / 2, parameters["lenX"] + electodePlotWidth / 2 ) ax.set_ylim( -electodePlotWidth / 2, parameters["lenY"] + electodePlotWidth / 2 ) elif parameters["geometry"] == "circle": ax.set_xlim( -parameters["radius"] - electodePlotWidth, parameters["radius"] + electodePlotWidth, ) ax.set_ylim( -parameters["radius"] - electodePlotWidth, parameters["radius"] + electodePlotWidth, ) ax.set_aspect("equal") plt.savefig( join(pathToSimFolder, f"trajectory_toEl_{k}_{inp[fileNumber-1]}.png"), bbox_inches="tight", dpi=300, ) # plt.show() plt.close(fig)

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df102fd4bc161dbff752d14a5d6d5415a2686808

78

py

Python

test/test.py

hcamacho4200/dev_opts_training

6ce91cbeb30af7eae29c084f6180d53f64f5e9b0

[ "Apache-2.0" ]

1

2021-10-03T22:23:06.000Z

test/test.py

hcamacho4200/dev_opts_training

6ce91cbeb30af7eae29c084f6180d53f64f5e9b0

[ "Apache-2.0" ]

null

test/test.py

hcamacho4200/dev_opts_training

6ce91cbeb30af7eae29c084f6180d53f64f5e9b0

[ "Apache-2.0" ]

1

2021-12-11T19:24:59.000Z

def test_test(): """A generic test :return: """ assert True

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10d394809031c831a797106d7da931ca1931a5d8

89

py

Python

Contest/ABC017/b/main.py

mpses/AtCoder

9c101fcc0a1394754fcf2385af54b05c30a5ae2a

[ "CC0-1.0" ]

null

Contest/ABC017/b/main.py

mpses/AtCoder

9c101fcc0a1394754fcf2385af54b05c30a5ae2a

[ "CC0-1.0" ]

null

Contest/ABC017/b/main.py

mpses/AtCoder

9c101fcc0a1394754fcf2385af54b05c30a5ae2a

[ "CC0-1.0" ]

null

#!/usr/bin/env python3 import re print(re.sub("ch|o|k|u", "", input()) and "NO" or "YES")

29.666667

56

0.606742

18

89

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0.944444

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0.012658

0.11236

89

3

56

29.666667

0.670886

0.235955

0

0.191176

0

1

0

true

0

0.5

0

0.5

1

0

null

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1

0

null

0

1

0

1

0

1

0

5

10dcd63f6971079940c1323786fecd18f6fad2b3

162

py

Python

pythonperlin/__init__.py

timpyrkov/pyperlin

c79080657aa79df1abc83e481d2b09cac5edbff7

[ "MIT" ]

null

pythonperlin/__init__.py

timpyrkov/pyperlin

c79080657aa79df1abc83e481d2b09cac5edbff7

[ "MIT" ]

null

pythonperlin/__init__.py

timpyrkov/pyperlin

c79080657aa79df1abc83e481d2b09cac5edbff7

[ "MIT" ]

null

# -*- coding: utf-8 -*- from pythonperlin.perlin import perlin from pkg_resources import get_distribution __version__ = get_distribution('pythonperlin').version

27

54

0.796296

19

162

6.421053

0.631579

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0.006897

0.104938

162

6

54

27

0.834483

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0.666667

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1

0

1

0

null

0

1

0

1

0

5

10e230dff4f183cac0ecd093228e7522ab70f334

26

py

Python

25_Assigment_Operator/main.py

jmmedel/Python-Tutorials-

243ae9a6b51a4fce03dd90c02da13b859cbfbe5f

[ "MIT" ]

null

25_Assigment_Operator/main.py

jmmedel/Python-Tutorials-

243ae9a6b51a4fce03dd90c02da13b859cbfbe5f

[ "MIT" ]

null

25_Assigment_Operator/main.py

jmmedel/Python-Tutorials-

243ae9a6b51a4fce03dd90c02da13b859cbfbe5f

[ "MIT" ]

null

x = 5 x |= 3 print(x)

3.25

8

0.384615

6

26

1.666667

0.666667

0

0.133333

0.423077

26

7

9

3.714286

0.533333

0

1

0

false

0

0.333333

1

null

0

1

0

1

0

null

0

5

10eff1d39f6acd5ae6fc306444aa467930b6a9d1

1,624

py

Python

ozpcenter/models/import_task_result.py

emosher/ozp-backend

d31d00bb8a28a8d0c999813f616b398f41516244

[ "Apache-2.0" ]

1

2018-10-05T17:03:01.000Z

ozpcenter/models/import_task_result.py

emosher/ozp-backend

d31d00bb8a28a8d0c999813f616b398f41516244

[ "Apache-2.0" ]

1

2017-01-06T19:20:32.000Z

ozpcenter/models/import_task_result.py

emosher/ozp-backend

d31d00bb8a28a8d0c999813f616b398f41516244

[ "Apache-2.0" ]

7

2016-12-16T15:42:05.000Z

2020-09-05T01:11:27.000Z

from django.db import models from ozpcenter.utils import get_now_utc from .import_task import ImportTask class ImportTaskResultManager(models.Manager): def get_queryset(self): return super().get_queryset() def find_all(self): return self.all() def find_by_id(self, id): return self.get(id=id) def find_all_by_import_task(self, import_task_pk): return self.filter(import_task=import_task_pk) def create_result(self, import_task_id, result, message): result = self.create(import_task_id=import_task_id, result=result, message=message) ImportTask.objects.filter(id=import_task_id).update(last_run_result=result.id) return result class ImportTaskResult(models.Model): """ Import Task Result Represents the results of an import task that has been run previously """ class Meta: db_table = 'import_task_result' objects = ImportTaskResultManager() RESULT_PASS = 'Pass' RESULT_FAIL = 'Fail' RESULT_CHOICES = ( (RESULT_PASS, 'Pass'), (RESULT_FAIL, 'Fail'), ) import_task = models.ForeignKey(ImportTask, related_name="results") run_date = models.DateTimeField(default=get_now_utc) result = models.CharField(max_length=4, choices=RESULT_CHOICES) message = models.CharField(max_length=4000, null=False) def __repr__(self): return '{0!s} | Date: {1!s} | Result: {2!s}'.format(self.import_task, self.run_date, self.result) def __str__(self): return '{0!s} | Date: {1!s} | Result: {2!s}'.format(self.import_task, self.run_date, self.result)

28.491228

105

0.690887

219

1,624

4.86758

0.315068

0.140713

0.052533

0.033771

0.178236

0.125704

0

0.008455

0.198892

1,624

56

106

29

0.810915

0.054803

0

0.058824

0

0.058824

0.073267

0

1

0.205882

false

0.058824

0.441176

0.176471

1.176471

0

null

0

null

0

1

0

1

0

5

80178d726d35bfda33f77aca84b7fdccd2b6d2ea

253

py

Python

src/fl_simulation/server/aggregation/__init__.py

microsoft/fl-simulation

d177d329c82559c7efe82deae8dea8f9baa49495

[ "MIT" ]

5

2021-12-14T02:21:53.000Z

2021-12-26T07:45:13.000Z

src/fl_simulation/server/aggregation/__init__.py

microsoft/fl-simulation

d177d329c82559c7efe82deae8dea8f9baa49495

[ "MIT" ]

1

2022-01-04T04:51:20.000Z

src/fl_simulation/server/aggregation/__init__.py

microsoft/fl-simulation

d177d329c82559c7efe82deae8dea8f9baa49495

[ "MIT" ]

null

"""Utilities and implementation for model aggregation on the central server.""" from .aggregator import * from .fedavg import * from .fedprox import * from .scaffold import * from .aggregator_with_dropouts import * from .multi_model_aggregator import *

31.625

79

0.790514

32

253

6.125

0.59375

0.255102

0

0.134387

253

8

80

31.625

0.894977

0.288538

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

5

339ebff6a47b6fc0d76354525972cdafcdf197e6

216

py

Python

osvolbackup/verbose.py

CCSGroupInternational/osvolbackup

d0d93812a729acdb6c961c6bdd1cc2cb5c9c87f5

[ "Apache-2.0" ]

1

2019-02-27T12:59:49.000Z

osvolbackup/verbose.py

CCSGroupInternational/osvolbackup

d0d93812a729acdb6c961c6bdd1cc2cb5c9c87f5

[ "Apache-2.0" ]

4

2019-03-07T09:31:51.000Z

2019-03-12T15:19:40.000Z

osvolbackup/verbose.py

CCSGroupInternational/osvolbackup

d0d93812a729acdb6c961c6bdd1cc2cb5c9c87f5

[ "Apache-2.0" ]

null

from __future__ import print_function from os import getenv from datetime import datetime def vprint(*a, **k): if not getenv('VERBOSE'): return print(datetime.now(), ' ', end='') print(*a, **k)

19.636364

38

0.643519

29

216

4.62069

0.62069

0.029851

0

0.217593

216

10

39

21.6

0.792899

0

0.037037

0

1

0.125

true

0

0.375

0

0.625

0.5

1

0

null

0

null

0

1

0

1

0

1

0

5

33e70135430c756b9a90a2e67be6abde70c17fb4

100

py

Python

paraVerComoFuncionaAlgumasCoisas/sqlite3/fazendoTeste/teste.py

jonasht/pythonEstudos

5e7d28e7bd82b9d1b08e795867fdbaa743f4b747

[ "MIT" ]

null

paraVerComoFuncionaAlgumasCoisas/sqlite3/fazendoTeste/teste.py

jonasht/pythonEstudos

5e7d28e7bd82b9d1b08e795867fdbaa743f4b747

[ "MIT" ]

null

paraVerComoFuncionaAlgumasCoisas/sqlite3/fazendoTeste/teste.py

jonasht/pythonEstudos

5e7d28e7bd82b9d1b08e795867fdbaa743f4b747

[ "MIT" ]

null

import PegandoVariavel as v print(v.get_Pessoas()) print() for d in v.get_Pessoas(): print(d)

12.5

27

0.7

17

100

4

0.588235

0.117647

0.323529

0.470588

0

0.17

100

8

28

12.5

0.819277

0

1

0

false

0

0.2

0

0.2

0.6

1

0

null

0

1

0

1

0

null

0

1

0

5

33ed53521c15ad28a778f2b1528538b64f181026

32

py

Python

week01/test_f.py

wasit7/cn350

a84a6ed04ada532e0a12c69d705cf3c15d7e0240

[ "MIT" ]

null

week01/test_f.py

wasit7/cn350

a84a6ed04ada532e0a12c69d705cf3c15d7e0240

[ "MIT" ]

null

week01/test_f.py

wasit7/cn350

a84a6ed04ada532e0a12c69d705cf3c15d7e0240

[ "MIT" ]

null

n=1 def f(x): print(n) f(0)

6.4

12

0.46875

9

32

1.666667

0.777778

0

0.086957

0.28125

32

5

13

6.4

0.565217

0

1

0.25

false

0

0.25

1

null

0

1

0

null

0

1

0

5

1d0fdb41642d7e059e2af9967d0a5707e8be001c

1,829

py

Python

StationeryBG.py

CharlesW1970/Handright

cda9400232e1815f7137ab3bd86ded8e307f35c7

[ "BSD-3-Clause" ]

1

2020-10-14T06:05:35.000Z

StationeryBG.py

CharlesW1970/Handright

cda9400232e1815f7137ab3bd86ded8e307f35c7

[ "BSD-3-Clause" ]

null

StationeryBG.py

CharlesW1970/Handright

cda9400232e1815f7137ab3bd86ded8e307f35c7

[ "BSD-3-Clause" ]

null

# coding: utf-8 from PIL import Image, ImageFont from handright import Template, handwrite text = """ 这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。这是一段自动生成的笔迹，这是一段自动生成的笔迹。 """ imagex = Image.open("./pic/stationeryBackground.jpg") width, height = imagex.size imagex = imagex.resize((width * 2, height * 2), resample=Image.LANCZOS) template = Template(background=imagex, font_size=140, font=ImageFont.truetype("./fonts/whx_2nd.ttf"), line_spacing=220, fill=0, # 字体“颜色” left_margin=380, top_margin=370, right_margin=340, bottom_margin=340, word_spacing=12, line_spacing_sigma=7, # 行间距随机扰动 font_size_sigma=3, # 字体大小随机扰动 word_spacing_sigma=6, # 字间距随机扰动 end_chars=", 。", # 防止特定字符因排版算法的自动换行而出现在行首 perturb_x_sigma=2, # 笔画横向偏移随机扰动 perturb_y_sigma=2, # 笔画纵向偏移随机扰动 perturb_theta_sigma=0.05, # 笔画旋转偏移随机扰动 ) images = handwrite(text, template) for i, im in enumerate(images): assert isinstance(im, Image.Image) im.show() im.save("./output/{}.png".format(i))

43.547619

172

0.783488

198

1,829

7.136364

0.414141

1.07431

1.58811

2.086341

0.54494

0

0.020233

0.108256

1,829

42

173

43.547619

0.845494

0.055221

0

0.142857

0

0.142857

0.543655

0.506403

0

0.028571

0

null

0

0.057143

null

0

null

1

0

1

null

0

1

0

5

1d5874fe18b2e75012e32310519149b4c42547fe

81

py

Python

app_folder/schemas/api.py

Nuznhy/day-f-hack

9f3dbcd73e73ea4e7807e5197bf0b0ded76bc9f3

[ "MIT" ]

2

2021-10-02T12:12:57.000Z

2021-11-16T11:36:15.000Z

app_folder/schemas/api.py

Nuznhy/day-f-hack

9f3dbcd73e73ea4e7807e5197bf0b0ded76bc9f3

[ "MIT" ]

null

app_folder/schemas/api.py

Nuznhy/day-f-hack

9f3dbcd73e73ea4e7807e5197bf0b0ded76bc9f3

[ "MIT" ]

null

from pydantic import BaseModel class ReadyResponse(BaseModel): status: str

13.5

31

0.777778

9

81

7

0.888889

0

0.17284

81

5

32

16.2

0.940299

0

1

0

true

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

1d72d39d1134cd19db279903a576512ac8b9b659

139

py

Python

vedasal/criteria/losses/builder.py

Kuro96/vedasal

3c5588bf12059af5bd7bc779fd5f9dc0b2901cb2

[ "Apache-2.0" ]

2

2020-11-06T06:39:04.000Z

2020-11-11T03:39:22.000Z

vedasal/criteria/losses/builder.py

Kuro96/vedasal

3c5588bf12059af5bd7bc779fd5f9dc0b2901cb2

[ "Apache-2.0" ]

null

vedasal/criteria/losses/builder.py

Kuro96/vedasal

3c5588bf12059af5bd7bc779fd5f9dc0b2901cb2

[ "Apache-2.0" ]

null

from vedacore.misc import registry, build_from_cfg def build_loss(cfg): loss = build_from_cfg(cfg, registry, 'loss') return loss

19.857143

50

0.741007

21

139

4.666667

0.47619

0.183673

0.244898

0

0.172662

139

6

51

23.166667

0.852174

0

0.028777

0

1

0.25

false

0

0.25

0

0.75

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

d535465b4cadf1f4ee90d4f52f137ea35dc5bc11

56

py

Python

dominion/cards/__init__.py

billletson/dominion

ad430e20aa1615758091df1ca39a5fc7313e921e

[ "MIT" ]

null

dominion/cards/__init__.py

billletson/dominion

ad430e20aa1615758091df1ca39a5fc7313e921e

[ "MIT" ]

null

dominion/cards/__init__.py

billletson/dominion

ad430e20aa1615758091df1ca39a5fc7313e921e

[ "MIT" ]

null

from .constants import * from .actions import ACTIONS

18.666667

29

0.767857

7

56

6.142857

0.571429

0

0.178571

56

2

30

28

0.934783

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

d53f7a92ad96592864829c170139b3f620bcb9e7

109

py

Python

aiohttp_devtools/start/__init__.py

antonmyronyuk/aiohttp-devtools

be06d295a8911a43f7ad582a88a3d64d6482b6e8

[ "MIT" ]

2

2018-11-13T06:34:17.000Z

2019-01-08T14:33:09.000Z

aiohttp_devtools/start/__init__.py

theruziev/aiohttp-devtools

8ab8a621964c8af0021c62e7971eea8c04f534e8

[ "MIT" ]

1

2021-02-27T14:13:58.000Z

aiohttp_devtools/start/__init__.py

theruziev/aiohttp-devtools

8ab8a621964c8af0021c62e7971eea8c04f534e8

[ "MIT" ]

null

# flake8: noqa from .main import DatabaseChoice, ExampleChoice, SessionChoices, StartProject, TemplateChoice

36.333333

93

0.834862

10

109

9.1

1

0

0.010204

0.100917

109

2

94

54.5

0.918367

0.110092

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

d54e3560503b5dd94b9ef2b1f63b8e1ccc96eeee

164

py

Python

allauth/socialaccount/providers/stripe/urls.py

mina-gaid/scp

38e1cd303d4728a987df117f666ce194e241ed1a

[ "MIT" ]

1

2018-04-06T21:36:59.000Z

allauth/socialaccount/providers/stripe/urls.py

mina-gaid/scp

38e1cd303d4728a987df117f666ce194e241ed1a

[ "MIT" ]

6

2020-06-05T18:44:19.000Z

2022-01-13T00:48:56.000Z

allauth/socialaccount/providers/stripe/urls.py

mina-gaid/scp

38e1cd303d4728a987df117f666ce194e241ed1a

[ "MIT" ]

1

2022-02-01T17:19:28.000Z

from allauth.socialaccount.providers.oauth2.urls import default_urlpatterns from .provider import StripeProvider urlpatterns = default_urlpatterns(StripeProvider)

32.8

75

0.878049

17

164

8.352941

0.647059

0.253521

0

0.006579

0.073171

164

4

76

41

0.927632

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

d56af4bb09c9819923a740a48a9336b6c5056a35

42

py

Python

python_module/sirius/utils/exceptions.py

mtaillefumier/SIRIUS

50ec1c202c019113c5660f1966b170dec9dfd4d4

[ "BSD-2-Clause" ]

77

2016-03-18T08:38:30.000Z

2022-03-11T14:06:25.000Z

python_module/sirius/utils/exceptions.py

simonpintarelli/SIRIUS

f4b5c4810af2a3ea1e67992d65750535227da84b

[ "BSD-2-Clause" ]

240

2016-04-12T16:39:11.000Z

2022-03-31T08:46:12.000Z

python_module/sirius/utils/exceptions.py

simonpintarelli/SIRIUS

f4b5c4810af2a3ea1e67992d65750535227da84b

[ "BSD-2-Clause" ]

43

2016-03-18T17:45:07.000Z

2022-02-28T05:27:59.000Z

class NotEnoughBands(Exception): pass

14

32

0.761905

4

42

8

1

0

0.166667

42

2

33

21

0.914286

0

1

0

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

5

63740319cbdd9993b7493ee891f9371a9c6e02c1

256

py

Python

components/collector/src/source_collectors/sonarqube/duplicated_lines.py

kargaranamir/quality-time

1c427c61bee9d31c3526f0a01be2218a7e167c23

[ "Apache-2.0" ]

33

2016-01-20T07:35:48.000Z

2022-03-14T09:20:51.000Z

components/collector/src/source_collectors/sonarqube/duplicated_lines.py

kargaranamir/quality-time

1c427c61bee9d31c3526f0a01be2218a7e167c23

[ "Apache-2.0" ]

2,410

2016-01-22T18:13:01.000Z

2022-03-31T16:57:34.000Z

components/collector/src/source_collectors/sonarqube/duplicated_lines.py

kargaranamir/quality-time

1c427c61bee9d31c3526f0a01be2218a7e167c23

[ "Apache-2.0" ]

21

2016-01-16T11:49:23.000Z

2022-01-14T21:53:22.000Z

"""SonarQube duplicated lines collector.""" from .base import SonarQubeMetricsBaseClass class SonarQubeDuplicatedLines(SonarQubeMetricsBaseClass): """SonarQube duplicated lines collector.""" valueKey = "duplicated_lines" totalKey = "lines"

23.272727

58

0.765625

20

256

9.75

0.6

0.230769

0.246154

0.338462

0

0.140625

256

10

59

25.6

0.886364

0.292969

0

0.123529

0

1

0

false

0

0.25

0

1

0

1

0

null

1

0

null

0

1

0

5

6386ae51574c0702fa4ae47e2c3e29449d380984

71

py

Python

utils_demo/percentage_format.py

IBM/nesa-demo

4e87217f44ff66414f78df6962ee8633d89f0cf5

[ "MIT" ]

2

2021-12-16T13:16:56.000Z

2022-01-19T14:23:18.000Z

utils_demo/percentage_format.py

SocioProphet/nesa-demo

4e87217f44ff66414f78df6962ee8633d89f0cf5

[ "MIT" ]

null

utils_demo/percentage_format.py

SocioProphet/nesa-demo

4e87217f44ff66414f78df6962ee8633d89f0cf5

[ "MIT" ]

1

2022-03-07T19:57:59.000Z

def percentage_format(x: float) -> str: return f"{(x * 100):.1f}%"

23.666667

39

0.591549

11

71

3.727273

0.909091

0

0.068966

0.183099

71

2

40

35.5

0.637931

0

0.225352

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

639892302eb62bb4521dec46165a447fd1bb4884

370

py

Python

bitmovin_api_sdk/account/organizations/groups/__init__.py

jaythecaesarean/bitmovin-api-sdk-python

48166511fcb9082041c552ace55a9b66cc59b794

[ "MIT" ]

11

2019-07-03T10:41:16.000Z

2022-02-25T21:48:06.000Z

bitmovin_api_sdk/account/organizations/groups/__init__.py

jaythecaesarean/bitmovin-api-sdk-python

48166511fcb9082041c552ace55a9b66cc59b794

[ "MIT" ]

8

2019-11-23T00:01:25.000Z

2021-04-29T12:30:31.000Z

bitmovin_api_sdk/account/organizations/groups/__init__.py

jaythecaesarean/bitmovin-api-sdk-python

48166511fcb9082041c552ace55a9b66cc59b794

[ "MIT" ]

13

2020-01-02T14:58:18.000Z

2022-03-26T12:10:30.000Z

from bitmovin_api_sdk.account.organizations.groups.groups_api import GroupsApi from bitmovin_api_sdk.account.organizations.groups.tenants.tenants_api import TenantsApi from bitmovin_api_sdk.account.organizations.groups.invitations.invitations_api import InvitationsApi from bitmovin_api_sdk.account.organizations.groups.permissions.permissions_api import PermissionsApi

74

100

0.905405

47

370

6.87234

0.319149

0.148607

0.185759

0.22291

0.544892

0

0.043243

370

4

101

92.5

0.912429

0

1

0

true

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

63c88a948245c1382a743f6e1329878390cf91ac

51,310

py

Python

gazoo_device/tests/unit_tests/utility_tests/adb_utils_test.py

dedsec-9/gazoo-device

5ed2867c258da80e53b6aae07ec7a65efe473a28

[ "Apache-2.0" ]

null

gazoo_device/tests/unit_tests/utility_tests/adb_utils_test.py

dedsec-9/gazoo-device

5ed2867c258da80e53b6aae07ec7a65efe473a28

[ "Apache-2.0" ]

null

gazoo_device/tests/unit_tests/utility_tests/adb_utils_test.py

dedsec-9/gazoo-device

5ed2867c258da80e53b6aae07ec7a65efe473a28

[ "Apache-2.0" ]

null

# Copyright 2021 Google LLC # # 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. """This test script performs unit tests on functions in the adb_utils module.""" import grp import json import os import subprocess from unittest import mock from gazoo_device import config from gazoo_device import errors from gazoo_device.tests.unit_tests.utils import unit_test_case from gazoo_device.utility import adb_utils from gazoo_device.utility import host_utils ADB_CMD_PATH = "/usr/bin/adb" FAKE_ADB_DEVICES_OUTPUT = ("List of devices attached\n" "04576e89\tdevice\n" "04576ee5\tsideload\n" "04576eaz\toffline\n" "123.45.67.89:5555\tdevice\n" "123.45.67.90:5555\tsideload\n" "123.45.67.91:5555\toffline\n\n") ADB_DEVICES = ["04576e89", "123.45.67.89"] SIDELOAD_DEVICES = ["04576ee5", "123.45.67.90:5555"] FAKE_ADB_REBOOT = "" FAKE_ADB_ROOT = "" FAKE_SHELL = "abc\n123\n" FASTBOOT_CMD_PATH = "/usr/bin/fastboot" FASTBOOT_CMD = os.path.basename(FASTBOOT_CMD_PATH) FASTBOOT_DEVICES = ["04576e89", "06011HFDD0165R", "04576ee5"] FAKE_FASTBOOT = ("04576e89 fastboot\n" "06011HFDD0165R Android Fastboot\n" "04576ee5 fastboot\n\n") FAKE_FASTBOOT_REBOOT = ("Rebooting...\n\n" "Finished. Total time: 0.157s\n") DEVICE_NAME = "somedevice" DEVICE_ADB_SERIAL = "aabbccdd" DEVICE_FASTBOOT_SERIAL = "aabbccdd" TEST_GROUP_ENTRY = ("plugdev", None, 46, None) TEST_GOOD_GROUP_LIST = [42, 46] TEST_USER_UID = 1000 TEST_USER_NAME = "test_user" class AdbUtilsTests(unit_test_case.UnitTestCase): """ADB utility tests.""" @mock.patch.object(host_utils, "has_command", return_value=False) def test_010_adb_utils_get_fastboot_path_raises_error(self, mock_get_command_path): """Verify get_fastboot_path raises error if get_command_path fails.""" with self.assertRaises(RuntimeError): adb_utils.get_fastboot_path() mock_get_command_path.assert_called() @mock.patch.object( host_utils, "get_command_path", return_value=FASTBOOT_CMD_PATH) def test_011_adb_utils_get_fastboot_path_calls_get_command_path( self, mock_get_command_path): """Verify get_fastboot_path calls get_command_path.""" self.assertEqual(FASTBOOT_CMD_PATH, adb_utils.get_fastboot_path()) mock_get_command_path.assert_called() @mock.patch.object( subprocess, "check_output", return_value=FAKE_FASTBOOT.encode("utf-8", errors="replace")) @mock.patch.object( adb_utils, "get_fastboot_path", return_value=FASTBOOT_CMD_PATH) def test_020_adb_utils_get_fastboot_devices_calls_get_fastboot_path( self, mock_get_fastboot_path, mock_subprocess): """Verify get_fastboot_devices calls get_fastboot_path.""" self.assertEqual(FASTBOOT_DEVICES, adb_utils.get_fastboot_devices()) mock_get_fastboot_path.assert_called() mock_subprocess.assert_called() @mock.patch.object(host_utils, "has_command", return_value=False) def test_021_adb_utils_get_fastboot_devices_bad_fastboot_path( self, mock_has_command): """Verify get_fastboot_devices skips get_fastboot_path.""" devices = adb_utils.get_fastboot_devices(fastboot_path="bogus/path") self.assertEqual(devices, []) mock_has_command.assert_called() @mock.patch.object( subprocess, "check_output", side_effect=subprocess.CalledProcessError(-1, ["fastboot", "devices"])) @mock.patch.object( adb_utils, "get_fastboot_path", return_value=FASTBOOT_CMD_PATH) def test_022_adb_utils_get_fastboot_devices_subprocess_errors( self, mock_get_fastboot_path, mock_subprocess): """Verify get_fastboot_devices handles subprocess errors internally.""" self.assertEqual([], adb_utils.get_fastboot_devices()) mock_get_fastboot_path.assert_called() mock_subprocess.assert_called() @mock.patch.object(os.path, "exists", return_value=True) def test_023_adb_utils_get_fastboot_path_uses_correct_path(self, mock_exists): """Verify get_fastboot_devices skips get_fastboot_path.""" path = adb_utils.get_fastboot_path(fastboot_path="genuine/path") self.assertEqual(path, "genuine/path") @mock.patch.object( adb_utils, "get_fastboot_devices", return_value=FASTBOOT_DEVICES) def test_030_adb_utils_is_fastboot_mode_true(self, mock_get_fastboot_devices): """Verify is_fastboot_mode returns True.""" adb_serial = "04576e89" self.assertTrue(adb_utils.is_fastboot_mode(adb_serial)) mock_get_fastboot_devices.assert_called() @mock.patch.object( adb_utils, "get_fastboot_devices", return_value=FASTBOOT_DEVICES) def test_031_adb_utils_is_fastboot_mode_false(self, mock_get_fastboot_devices): """Verify is_fastboot_mode returns False.""" adb_serial = "bogus" self.assertFalse(adb_utils.is_fastboot_mode(adb_serial)) mock_get_fastboot_devices.assert_called() @mock.patch.object( adb_utils, "get_sideload_devices", return_value=SIDELOAD_DEVICES) def test_032_adb_utils_is_sideload_mode_true(self, mock_get_sideload_devices): """Verify is_sideload_mode on True.""" adb_serial = SIDELOAD_DEVICES[0] self.assertTrue(adb_utils.is_sideload_mode(adb_serial)) mock_get_sideload_devices.assert_called_once() @mock.patch.object( adb_utils, "get_sideload_devices", return_value=SIDELOAD_DEVICES) def test_033_adb_utils_is_sideload_mode_false(self, mock_get_sideload_devices): """Verify is_sideload_mode on False.""" adb_serial = "bogus" self.assertFalse(adb_utils.is_sideload_mode(adb_serial)) mock_get_sideload_devices.assert_called_once() @mock.patch.object( subprocess, "check_output", return_value=FASTBOOT_CMD_PATH.encode("utf-8", errors="replace")) @mock.patch.object(grp, "getgrnam", return_value=TEST_GROUP_ENTRY) @mock.patch.object(os, "getgroups", return_value=TEST_GOOD_GROUP_LIST) @mock.patch.object(os, "getuid", return_value=TEST_USER_UID) @mock.patch.object(os, "getlogin", return_value=TEST_USER_NAME) def test_040_adb_utils_verify_user_has_fastboot(self, mock_getlogin, mock_getuid, mock_getgroups, mock_getgrnam, mock_check_output): """Verify that verify_usr_has_fastboot works correctly.""" try: adb_utils.verify_user_has_fastboot(DEVICE_NAME) mock_check_output.assert_called() except subprocess.CalledProcessError as err: self.fail("verify_user_has_fastboot() raised error: {!r}".format(err)) @mock.patch.object( subprocess, "check_output", side_effect=subprocess.CalledProcessError(1, ["which", FASTBOOT_CMD])) def test_041_adb_utils_verify_user_has_fastboot_no_fastboot( self, mock_check_output): """Verify that verify_user_has_fastboot raises if fastboot not present.""" with self.assertRaises(errors.DeviceError): adb_utils.verify_user_has_fastboot(DEVICE_NAME) mock_check_output.assert_called() @mock.patch.object(host_utils, "get_command_path", return_value=ADB_CMD_PATH) def test_050_adb_utils_get_adb_path_no_config_file(self, mock_get_command_path): """Verify get_adb_path handles open errors internally.""" config_file = os.path.join(self.artifacts_directory, self._testMethodName + ".json") with mock.patch.dict(config.__dict__, {"DEFAULT_GDM_CONFIG_FILE": config_file}): self.assertEqual(ADB_CMD_PATH, adb_utils.get_adb_path()) mock_get_command_path.assert_called() @mock.patch.object(host_utils, "get_command_path", return_value=ADB_CMD_PATH) @mock.patch.object(json, "load", side_effect=ValueError) def test_051_adb_utils_get_adb_path_bad_config_data(self, mock_json_load, mock_get_command_path): """Verify get_adb_path handles json.load errors internally.""" config_file = os.path.join(self.artifacts_directory, self._testMethodName + ".json") with open(config_file, "w") as gdm_config: gdm_config.write("{}") with mock.patch.dict(config.__dict__, {"DEFAULT_GDM_CONFIG_FILE": config_file}): self.assertEqual(ADB_CMD_PATH, adb_utils.get_adb_path()) mock_json_load.assert_called() mock_get_command_path.assert_called() @mock.patch.object(host_utils, "get_command_path", return_value=ADB_CMD_PATH) def test_052_adb_utils_get_adb_path_no_adb_path_in_config( self, mock_get_command_path): """Verify get_adb_path handles missing adb_path key errors internally.""" config_file = os.path.join(self.artifacts_directory, self._testMethodName + ".json") with open(config_file, "w") as gdm_config: gdm_config.write("{}") with mock.patch.dict(config.__dict__, {"DEFAULT_GDM_CONFIG_FILE": config_file}): self.assertEqual(ADB_CMD_PATH, adb_utils.get_adb_path()) mock_get_command_path.assert_called() @mock.patch.object(host_utils, "has_command", return_value=False) def test_053_adb_utils_get_adb_path_bad_adb_path_raises_error( self, mock_has_command): """Verify get_adb_path bad adb_path raises error.""" config_file = os.path.join(self.artifacts_directory, self._testMethodName + ".json") with open(config_file, "w") as gdm_config: gdm_config.write("{\"") gdm_config.write(config.ADB_BIN_PATH_CONFIG) gdm_config.write("\":") gdm_config.write("\"/some/bad/path\"}") with mock.patch.dict(config.__dict__, {"DEFAULT_GDM_CONFIG_FILE": config_file}): with self.assertRaises(RuntimeError): adb_utils.get_adb_path() @mock.patch.object(os.path, "exists", return_value=True) def test_054_adb_utils_get_fadb_path_uses_correct_path(self, mock_exists): """Verify get_adb_path defaults to path passed in.""" path = adb_utils.get_adb_path(adb_path="genuine/path") self.assertEqual(path, "genuine/path") @mock.patch.object( adb_utils, "_adb_command", return_value=FAKE_ADB_DEVICES_OUTPUT) def test_060_adb_utils_get_adb_devices_calls_get_adb_path( self, mock_adb_command): """Verify get_adb_devices calls _adb_command.""" self.assertEqual(ADB_DEVICES, adb_utils.get_adb_devices()) mock_adb_command.assert_called() @mock.patch.object(host_utils, "has_command", return_value=False) @mock.patch.object(os.path, "exists", return_value=False) def test_061_adb_utils_get_adb_devices_returns_list_when_no_adb( self, mock_exists, mock_has_command): """Verify get_adb_devices calls _adb_command.""" self.assertEqual([], adb_utils.get_adb_devices()) @mock.patch.object( adb_utils, "_adb_command", return_value=FAKE_ADB_DEVICES_OUTPUT) def test_062_adb_utils_get_sideload_devices_on_success( self, mock_adb_command): """Verify get_sideload_devices returns devices on success.""" self.assertEqual(SIDELOAD_DEVICES, adb_utils.get_sideload_devices()) mock_adb_command.assert_called_once_with("devices", adb_path=None) @mock.patch.object(adb_utils, "_adb_command", side_effect=RuntimeError()) def test_063_adb_utils_get_sideload_devices_on_failure( self, mock_adb_command): """Verify get_sideload_devices returns empty list on failure.""" self.assertEqual([], adb_utils.get_sideload_devices()) mock_adb_command.assert_called_once_with("devices", adb_path=None) @mock.patch.object(adb_utils, "get_adb_devices", return_value=ADB_DEVICES) def test_070_adb_utils_is_adb_mode_returns_true(self, mock_get_adb_devices): """Verify is_adb_mode calls get_adb_devices.""" adb_serial = "04576e89" self.assertTrue(adb_utils.is_adb_mode(adb_serial)) mock_get_adb_devices.assert_called() @mock.patch.object(adb_utils, "get_adb_devices", return_value=ADB_DEVICES) def test_071_adb_utils_is_adb_mode_returns_false(self, mock_get_adb_devices): """Verify is_adb_mode calls get_adb_devices.""" adb_serial = "bogus" self.assertFalse(adb_utils.is_adb_mode(adb_serial)) mock_get_adb_devices.assert_called() @mock.patch.object(adb_utils, "is_fastboot_mode", return_value=False) @mock.patch.object(adb_utils, "is_adb_mode", return_value=True) def test_080_adb_utils_is_device_online_yes_no(self, mock_is_adb_mode, mock_is_fastboot_mode): """Verify is_device_online calls is_adb_mode and not is_fastboot_mode.""" self.assertTrue(adb_utils.is_device_online(DEVICE_ADB_SERIAL)) mock_is_adb_mode.assert_called() mock_is_fastboot_mode.assert_not_called() @mock.patch.object(adb_utils, "is_fastboot_mode", return_value=True) @mock.patch.object(adb_utils, "is_adb_mode", return_value=False) def test_081_adb_utils_is_device_online_no_yes(self, mock_is_adb_mode, mock_is_fastboot_mode): """Verify is_device_online calls is_adb_mode and is_fastboot_mode.""" self.assertTrue(adb_utils.is_device_online(DEVICE_ADB_SERIAL)) mock_is_adb_mode.assert_called() mock_is_fastboot_mode.assert_called() @mock.patch.object(adb_utils, "is_fastboot_mode", return_value=False) @mock.patch.object(adb_utils, "is_adb_mode", return_value=False) def test_082_adb_utils_is_device_online_no_no(self, mock_is_adb_mode, mock_is_fastboot_mode): """Verify is_device_online calls is_adb_mode and is_fastboot_mode.""" self.assertFalse(adb_utils.is_device_online(DEVICE_ADB_SERIAL)) mock_is_adb_mode.assert_called() mock_is_fastboot_mode.assert_called() @mock.patch.object(adb_utils, "is_fastboot_mode", return_value=True) @mock.patch.object(adb_utils, "is_adb_mode", return_value=True) def test_083_adb_utils_is_device_online_yes_yes(self, mock_is_adb_mode, mock_is_fastboot_mode): """Verify is_device_online calls is_adb_mode and not is_fastboot_mode.""" self.assertTrue(adb_utils.is_device_online(DEVICE_ADB_SERIAL)) mock_is_adb_mode.assert_called() mock_is_fastboot_mode.assert_not_called() @mock.patch.object(adb_utils, "get_adb_path", return_value=ADB_CMD_PATH) def test_100_adb_utils_adb_command_without_adb_serial(self, mock_get_adb_path): """Verify _adb_command without adb_serial.""" command = "fake_command" command_output = "fake output\n" mock_popen = mock.MagicMock(spec=subprocess.Popen, returncode=0) mock_popen.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_popen): output = adb_utils._adb_command(command) self.assertEqual(command_output, output) mock_get_adb_path.assert_called() @mock.patch.object(adb_utils, "get_adb_path", return_value=ADB_CMD_PATH) def test_101_adb_utils_adb_command_with_string_command( self, mock_get_adb_path): """Verify _adb_command with string command.""" command = "fake_command" command_output = "fake output\n" mock_popen = mock.MagicMock(spec=subprocess.Popen, returncode=0) mock_popen.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_popen): output = adb_utils._adb_command(command, DEVICE_ADB_SERIAL) self.assertEqual(command_output, output) mock_get_adb_path.assert_called() @mock.patch.object(adb_utils, "get_adb_path", return_value=ADB_CMD_PATH) def test_102_adb_utils_adb_command_with_string_command( self, mock_get_adb_path): """Verify _adb_command with unicode command.""" command = u"fake_command" command_output = "fake output\n" mock_popen = mock.MagicMock(spec=subprocess.Popen, returncode=0) mock_popen.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_popen): output = adb_utils._adb_command(command, DEVICE_ADB_SERIAL) self.assertEqual(command_output, output) mock_get_adb_path.assert_called() @mock.patch.object(adb_utils, "get_adb_path", return_value=ADB_CMD_PATH) def test_103_adb_utils_adb_command_with_list_command(self, mock_get_adb_path): """Verify _adb_command with command list.""" command = ["fake_command", "arg1"] command_output = "fake output\n" mock_popen = mock.MagicMock(spec=subprocess.Popen, returncode=0) mock_popen.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_popen): output = adb_utils._adb_command(command, DEVICE_ADB_SERIAL) self.assertEqual(command_output, output) mock_get_adb_path.assert_called() @mock.patch.object(adb_utils, "get_adb_path", return_value=ADB_CMD_PATH) def test_104_adb_utils_adb_command_with_tuple_command(self, mock_get_adb_path): """Verify _adb_command with tuple list.""" command = ("fake_command", "arg1") command_output = "fake output\n" mock_popen = mock.MagicMock(spec=subprocess.Popen, returncode=0) mock_popen.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_popen): output = adb_utils._adb_command(command, DEVICE_ADB_SERIAL) self.assertEqual(command_output, output) mock_get_adb_path.assert_called() @mock.patch.object(os.path, "exists", return_value=False) @mock.patch.object(host_utils, "has_command", return_value=False) def test_105_adb_utils_adb_command_bad_adb_path(self, mock_has_command, mock_os_path_exists): """Verify _adb_command skips get_adb_path raises error on bad path.""" with self.assertRaises(RuntimeError): adb_utils._adb_command( "fake_command", DEVICE_ADB_SERIAL, adb_path="bogus/path") mock_os_path_exists.assert_called() mock_has_command.assert_called() @mock.patch.object(adb_utils, "get_adb_path", return_value=ADB_CMD_PATH) def test_106_adb_utils_adb_command_include_return_code( self, mock_get_adb_path): """Verify _adb_command include_return_code returns tuple.""" command = "fake_command" command_output = "fake output\n" command_return_code = 1 mock_popen = mock.MagicMock( spec=subprocess.Popen, returncode=command_return_code) mock_popen.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_popen): output, return_code = adb_utils._adb_command( command, DEVICE_ADB_SERIAL, include_return_code=True) self.assertEqual(command_output, output) self.assertEqual(command_return_code, return_code) mock_get_adb_path.assert_called() @mock.patch.object(adb_utils, "get_adb_path", return_value=ADB_CMD_PATH) def test_107_adb_utils_adb_command_with_offline(self, mock_get_adb_path): """Verify _adb_command succeeds if output includes "offline".""" command = "fake_command" mock_popen = mock.MagicMock(spec=subprocess.Popen, returncode=0) mock_popen.communicate.return_value = ( FAKE_ADB_DEVICES_OUTPUT.encode("utf-8"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_popen): output = adb_utils._adb_command(command) self.assertEqual(FAKE_ADB_DEVICES_OUTPUT, output) mock_get_adb_path.assert_called() @mock.patch.object(adb_utils, "_adb_command", return_value="Success\n") @mock.patch.object(os.path, "exists", return_value=True) def test_119_adb_utils_install_package_on_device_success( self, mock_path_exists, mock_adb_command): """Verify install_package_on_device on success.""" fake_package_path = "/tmp/xxx.apk" adb_utils.install_package_on_device( fake_package_path, adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) mock_path_exists.assert_called_once_with(fake_package_path) mock_adb_command.assert_called_once_with(("install", fake_package_path), adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) @mock.patch.object(adb_utils, "_adb_command", return_value="Success\n") @mock.patch.object(os.path, "exists", return_value=True) def test_120_adb_utils_install_package_on_device_with_flags_success( self, mock_path_exists, mock_adb_command): """Verify install_package_on_device with flags on success.""" fake_package_path = "/tmp/xxx.apk" adb_utils.install_package_on_device( fake_package_path, adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH, allow_downgrade=True, allow_test_apk=True, reinstall=True, all_permissions=True) mock_path_exists.assert_called_once_with(fake_package_path) mock_adb_command.assert_called_once_with( ("install", "-d", "-g", "-r", "-t", fake_package_path), adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) @mock.patch.object(adb_utils, "_adb_command") @mock.patch.object(os.path, "exists") def test_121_adb_utils_install_package_on_device_exception( self, mock_path_exists, mock_adb_command): """Verify install_package_on_device raise exception.""" # Note: # install_package_on_device() raises exception when: # 1) package_path is not a file. # 2) 'Success\n' is not found in command response. fake_package_path = "/tmp/xxx.apk" # 1) package path not a file mock_path_exists.return_value = False with self.assertRaises(ValueError): adb_utils.install_package_on_device( fake_package_path, adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) mock_path_exists.assert_called_with(fake_package_path) # 2) 'Success\n' is not in command response mock_path_exists.return_value = True mock_adb_command.return_value = "" with self.assertRaises(errors.DeviceError): adb_utils.install_package_on_device( fake_package_path, adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) mock_adb_command.assert_called_with(("install", fake_package_path), adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) @mock.patch.object(adb_utils, "_adb_command", return_value="Success\n") def test_122_adb_utils_uninstall_package_on_device_success( self, mock_adb_command): """Verify uninstall_package_on_device on success.""" fake_package_name = "com.google.fakepackage" adb_utils.uninstall_package_on_device( fake_package_name, adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) mock_adb_command.assert_called_once_with(("uninstall", fake_package_name), adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) @mock.patch.object(adb_utils, "_adb_command", return_value="") def test_123_adb_utils_uninstall_package_on_device_exception( self, mock_adb_command): """Verify uninstall_package_on_device raise exception.""" fake_package_name = "com.google.fakepackage" with self.assertRaises(errors.DeviceError): adb_utils.uninstall_package_on_device( fake_package_name, adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) mock_adb_command.assert_called_once_with(("uninstall", fake_package_name), adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) @mock.patch.object(adb_utils, "_adb_command", return_value=FAKE_SHELL) @mock.patch.object(os.path, "isfile", return_value=True) def test_124_adb_utils_sideload_package_on_success(self, mock_os_path_isfile, mock_adb_command): """Verify sideload_pacakge calls _adb_command.""" package_path = "/tmp/abc" self.assertEqual( adb_utils.sideload_package(package_path, DEVICE_ADB_SERIAL), FAKE_SHELL) mock_os_path_isfile.assert_called_once_with(package_path) mock_adb_command.assert_called_once_with(("sideload", package_path), adb_serial=DEVICE_ADB_SERIAL, adb_path=None) @mock.patch.object(adb_utils, "_adb_command", return_value=FAKE_SHELL) @mock.patch.object(os.path, "isfile", return_value=False) def test_125_adb_utils_sideload_package_on_exception(self, mock_os_path_isfile, mock_adb_command): """Verify sideload_pacakge raises exception when package_path invalid.""" package_path = "/tmp/abc" with self.assertRaises(RuntimeError): adb_utils.sideload_package(package_path, DEVICE_ADB_SERIAL) mock_os_path_isfile.assert_called_once_with(package_path) mock_adb_command.assert_not_called() @mock.patch.object(adb_utils, "_adb_command", return_value=FAKE_ADB_REBOOT) def test_140_adb_utils_enter_fastboot_calls_get_adb_path( self, mock_adb_command): """Verify enter_fastboot calls get_adb_path.""" self.assertEqual(FAKE_ADB_REBOOT, adb_utils.enter_fastboot(DEVICE_ADB_SERIAL)) mock_adb_command.assert_called() @mock.patch.object(adb_utils, "_adb_command", return_value=FAKE_ADB_REBOOT) def test_141_adb_utils_enter_sideload(self, mock_adb_command): """Verify enter_sideload calls _adb_command.""" # Note: # Verify both 1) sideload auto reboot and 2) no auto reboot. # With auto_reboot: False self.assertEqual( FAKE_ADB_REBOOT, adb_utils.enter_sideload(DEVICE_ADB_SERIAL, auto_reboot=False)) mock_adb_command.assert_called_with(("reboot", "sideload"), adb_serial=DEVICE_ADB_SERIAL, adb_path=None) # With auto_reboot: True self.assertEqual( FAKE_ADB_REBOOT, adb_utils.enter_sideload(DEVICE_ADB_SERIAL, auto_reboot=True)) mock_adb_command.assert_called_with(("reboot", "sideload-auto-reboot"), adb_serial=DEVICE_ADB_SERIAL, adb_path=None) @mock.patch.object( subprocess, "check_output", return_value=FAKE_FASTBOOT_REBOOT.encode("utf-8", errors="replace")) @mock.patch.object(os.path, "exists", return_value=True) @mock.patch.object( adb_utils, "get_fastboot_path", return_value=FASTBOOT_CMD_PATH) def test_150_adb_utils_exit_fastboot_calls_get_fastboot_path( self, mock_get_fastboot_path, mock_os_path_exists, mock_subprocess): """Verify exit_fastboot calls get_fastboot_path.""" self.assertEqual(FAKE_FASTBOOT_REBOOT, adb_utils.exit_fastboot(DEVICE_ADB_SERIAL)) mock_get_fastboot_path.assert_called() mock_os_path_exists.assert_called() mock_subprocess.assert_called() @mock.patch.object(os.path, "exists", return_value=False) @mock.patch.object(adb_utils, "get_fastboot_path") def test_151_adb_utils_exit_fastboot_bad_fastboot_path( self, mock_get_fastboot_path, mock_os_path_exists): """Verify exit_fastboot skips get_fastboot_path.""" with self.assertRaises(RuntimeError): adb_utils.exit_fastboot(DEVICE_ADB_SERIAL, fastboot_path="bogus/path") mock_get_fastboot_path.assert_not_called() mock_os_path_exists.assert_called() @mock.patch.object( subprocess, "check_output", side_effect=subprocess.CalledProcessError( -1, ["timeout", "10.0", "fastboot", "reboot"])) @mock.patch.object( adb_utils, "get_fastboot_path", return_value=FASTBOOT_CMD_PATH) @mock.patch.object(os.path, "exists", return_value=True) def test_152_adb_utils_exit_fastboot_bad_request(self, mock_get_fastboot_path, mock_os_path_exists, mock_check_output): """Verify exit_fastboot returns None.""" result = adb_utils.exit_fastboot(DEVICE_ADB_SERIAL) self.assertIsNone(result) mock_get_fastboot_path.assert_called() mock_os_path_exists.assert_called() mock_check_output.assert_called() @mock.patch.object(adb_utils, "_adb_command", return_value=FAKE_ADB_REBOOT) def test_160_adb_utils_reboot_device_calls_get_adb_path( self, mock_adb_command): """Verify reboot_device calls get_adb_path.""" self.assertEqual(FAKE_ADB_REBOOT, adb_utils.reboot_device(DEVICE_ADB_SERIAL)) mock_adb_command.assert_called() @mock.patch.object(adb_utils, "_adb_command", return_value=FAKE_ADB_ROOT) def test_170_adb_utils_root_device_calls_get_adb_path(self, mock_adb_command): """Verify root_device calls get_adb_path.""" self.assertEqual(FAKE_ADB_ROOT, adb_utils.root_device(DEVICE_ADB_SERIAL)) mock_adb_command.assert_called() @mock.patch.object( adb_utils, "_adb_command", return_value=("pull output\n", 0)) def test_180_adb_utils_pull_from_device_with_single_file( self, mock_adb_command): """Verify pull_file for a single source file.""" sources = "/some/device/path/to/file" adb_utils.pull_from_device(DEVICE_ADB_SERIAL, sources) mock_adb_command.assert_called() @mock.patch.object( adb_utils, "_adb_command", return_value=("pull output\n", 0)) def test_181_adb_utils_pull_from_device_with_multiple_files( self, mock_adb_command): """Verify pull_from_device calls get_adb_path.""" sources = ["/some/device/path/to/file", "/some/device/path/to/other_file"] adb_utils.pull_from_device(DEVICE_ADB_SERIAL, sources) mock_adb_command.assert_called() @mock.patch.object( adb_utils, "_adb_command", return_value=("pull output\n", 1)) def test_182_adb_utils_pull_from_device_bad_returncode( self, mock_adb_command): """Verify pull_from_device raises if ADB command fails.""" sources = "/some/device/path/to/file" with self.assertRaises(RuntimeError): adb_utils.pull_from_device(DEVICE_ADB_SERIAL, sources) mock_adb_command.assert_called() @mock.patch.object(adb_utils, "_adb_command") @mock.patch.object(os.path, "exists", return_value=False) def test_183_adb_utils_pull_from_device_bad_destination_path( self, mock_os_path_exists, mock_adb_command): """Verify pull_from_device provided bad destination path.""" sources = "/some/device/path/to/file" destination_path = "/bogus/path" with self.assertRaises(ValueError): adb_utils.pull_from_device( DEVICE_ADB_SERIAL, sources, destination_path=destination_path) mock_os_path_exists.assert_called() mock_adb_command.assert_not_called() @mock.patch.object( adb_utils, "_adb_command", return_value=("push output\n", 0)) @mock.patch.object(os.path, "exists", return_value=True) def test_190_adb_utils_push_to_device_with_single_file( self, mock_os_path_exists, mock_adb_command): """Verify push_to_device sends a single file.""" sources = "/fake/local/path" destination_path = "/fake/device/path" adb_utils.push_to_device(DEVICE_ADB_SERIAL, sources, destination_path) mock_os_path_exists.assert_called() mock_adb_command.assert_called() @mock.patch.object( adb_utils, "_adb_command", return_value=("push output\n", 0)) @mock.patch.object(os.path, "exists", return_value=True) def test_191_adb_utils_push_to_device_with_multiple_files( self, mock_os_path_exists, mock_adb_command): """Verify push_to_device sends multiple files.""" sources = ["/fake/local/path/to/file1", "/fake/local/path/to/file2"] destination_path = "/fake/device/path" adb_utils.push_to_device(DEVICE_ADB_SERIAL, sources, destination_path) mock_os_path_exists.assert_called() mock_adb_command.assert_called() @mock.patch.object(os.path, "exists", return_value=False) def test_192_adb_utils_push_to_device_fails_single_file( self, mock_os_path_exists): """Verify push_to_device fails single file path check.""" sources = "/bogus/local/file" destination_path = "/fake/device/path" with self.assertRaises(ValueError): adb_utils.push_to_device(DEVICE_ADB_SERIAL, sources, destination_path) mock_os_path_exists.assert_called() @mock.patch.object(os.path, "exists", side_effect=[True, False]) def test_193_adb_utils_push_to_device_fails_multiple_files( self, mock_os_path_exists): """Verify push_to_device fails multiple files path check.""" sources = ["/fake/local/path/to/file1", "/fake/local/path/to/file2"] destination_path = "/fake/device/path" with self.assertRaises(ValueError): adb_utils.push_to_device(DEVICE_ADB_SERIAL, sources, destination_path) mock_os_path_exists.assert_called() @mock.patch.object( adb_utils, "_adb_command", return_value=("push output\n", 1)) @mock.patch.object(os.path, "exists", return_value=True) def test_194_adb_utils_push_to_device_bad_returncode(self, mock_os_path_exists, mock_adb_command): """Verify push_file subprocess.communicate returns non-zero returncode.""" sources = "/fake/local/path" destination_path = "/fake/device/path" with self.assertRaises(RuntimeError): adb_utils.push_to_device(DEVICE_ADB_SERIAL, sources, destination_path) mock_os_path_exists.assert_called() mock_adb_command.assert_called() @mock.patch.object(adb_utils, "_adb_command", return_value="fake\n") def test_200_adb_shell(self, mock_adb_command): """Verifies shell works as expected.""" self.assertEqual("fake\n", adb_utils.shell("12345", 'echo "fake"')) mock_adb_command.assert_called_once_with( ["shell", 'echo "fake"'], "12345", adb_path=None, retries=mock.ANY, timeout=None, include_return_code=False) @mock.patch.object(adb_utils, "_adb_command", return_value=("fake\n", 0)) def test_201_adb_shell_include_return_code(self, mock_adb_command): """Verifies shell include return code will return output and code tuple.""" output, return_code = adb_utils.shell( "12345", 'echo "fake"', include_return_code=True) self.assertEqual("fake\n", output) self.assertEqual(0, return_code) mock_adb_command.assert_called_once_with( ["shell", 'echo "fake"'], "12345", adb_path=None, retries=mock.ANY, timeout=None, include_return_code=True) @mock.patch.object( adb_utils, "get_fastboot_path", return_value="/fake/path/to/fastboot") @mock.patch.object(os.path, "exists", return_value=False) def test_300_adb_utils_fastboot_command_without_fastboot_path( self, mock_exists, mock_get_fastboot_path): """Verify get_fastboot_path called when fastboot_path is not given.""" with self.assertRaises(RuntimeError): adb_utils._fastboot_command("fake command") mock_get_fastboot_path.assert_called_once() mock_exists.assert_called() @mock.patch.object( adb_utils, "get_fastboot_path", return_value="/fake/path/to/fastboot") @mock.patch.object(os.path, "exists", return_value=False) def test_301_adb_utils_fastboot_command_with_bad_fastboot_path( self, mock_exists, mock_get_fastboot_path): """Verify _fastboot_command raise error when given a bad fastboot_path.""" with self.assertRaises(RuntimeError): adb_utils._fastboot_command( "fake_command", fastboot_path="/fake/path/to/fastboot") mock_get_fastboot_path.assert_not_called() mock_exists.assert_called() @mock.patch.object(os.path, "exists", return_value=True) def test_302_adb_utils_fastboot_command_without_fastboot_serial( self, mock_exists): """Verify _fastboot_command without fastboot_serial.""" fastboot_executable = "fastboot" command = "fake_command" command_output = "fake_command_output" mock_proc = mock.MagicMock(spec=subprocess.Popen) mock_proc.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_proc): output = adb_utils._fastboot_command( command, fastboot_path=fastboot_executable) self.assertEqual(output, command_output) mock_exists.assert_called() @mock.patch.object(os.path, "exists", return_value=True) @mock.patch.object( adb_utils, "get_fastboot_path", return_value=FASTBOOT_CMD_PATH) def test_303_adb_utils_fastboot_command_with_string_command( self, mock_get_fastboot_path, mock_exists): """Verify _fastboot_command with string command.""" command = "fake_command" command_output = "fake command output" mock_proc = mock.MagicMock(spec=subprocess.Popen) mock_proc.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_proc): output = adb_utils._fastboot_command(command, DEVICE_FASTBOOT_SERIAL) self.assertEqual(command_output, output) mock_get_fastboot_path.assert_called() mock_exists.assert_called() @mock.patch.object(os.path, "exists", return_value=True) @mock.patch.object( adb_utils, "get_fastboot_path", return_value=FASTBOOT_CMD_PATH) def test_304_adb_utils_fastboot_command_with_string_command_unicode( self, mock_get_fastboot_path, mock_exists): """Verify _fastboot_command with unicode string command.""" command = u"fake_command" command_output = "fake command output" mock_proc = mock.MagicMock(spec=subprocess.Popen) mock_proc.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_proc): output = adb_utils._fastboot_command(command, DEVICE_FASTBOOT_SERIAL) self.assertEqual(command_output, output) mock_get_fastboot_path.assert_called() mock_exists.assert_called() @mock.patch.object(os.path, "exists", return_value=True) @mock.patch.object( adb_utils, "get_fastboot_path", return_value=FASTBOOT_CMD_PATH) def test_305_adb_utils_fastboot_command_with_list_command( self, mock_get_fastboot_path, mock_exists): """Verify _fastboot_command with command list.""" command = ["fake_command", "arg1"] command_output = "fake output" mock_proc = mock.MagicMock(spec=subprocess.Popen, returncode=0) mock_proc.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_proc): output = adb_utils._fastboot_command(command, DEVICE_FASTBOOT_SERIAL) self.assertEqual(command_output, output) mock_get_fastboot_path.assert_called() mock_exists.assert_called() @mock.patch.object(os.path, "exists", return_value=True) @mock.patch.object( adb_utils, "get_fastboot_path", return_value=FASTBOOT_CMD_PATH) def test_306_adb_utils_fastboot_command_with_tuple_command( self, mock_get_fastboot_path, mock_exists): """Verify _fastboot_command with command tuple.""" command = ("fake_command", "arg1") command_output = "fake output" mock_proc = mock.MagicMock(spec=subprocess.Popen, returncode=0) mock_proc.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_proc): output = adb_utils._fastboot_command(command, DEVICE_FASTBOOT_SERIAL) self.assertEqual(command_output, output) mock_get_fastboot_path.assert_called() mock_exists.assert_called() @mock.patch.object(os.path, "exists", return_value=True) @mock.patch.object( adb_utils, "get_fastboot_path", return_value=FASTBOOT_CMD_PATH) def test_307_adb_utils_fastboot_command_include_return_code( self, mock_get_fastboot_path, mock_exists): """Verify _fastboot_command include_return_code works.""" command = "fake_command" command_output = "fake output" command_return_code = 1 mock_proc = mock.MagicMock( spec=subprocess.Popen, returncode=command_return_code) mock_proc.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_proc): output, return_code = adb_utils._fastboot_command( command, DEVICE_FASTBOOT_SERIAL, include_return_code=True) self.assertEqual(command_output, output) self.assertEqual(command_return_code, return_code) mock_get_fastboot_path.assert_called() mock_exists.assert_called() @mock.patch.object(adb_utils, "_fastboot_command") def test_308_adb_utils_fastboot_unlock_device(self, mock_fastboot_command): """Verify fastbook_unlock_device calls _fastboot_command correctly.""" fastboot_serial = "fake_fastboot_serial" fastboot_path = FASTBOOT_CMD_PATH fastboot_timeout = 30.0 adb_utils.fastboot_unlock_device( fastboot_serial, fastboot_path=fastboot_path, timeout=fastboot_timeout) mock_fastboot_command.assert_called() mock_fastboot_command.assert_called_with(("flashing", "unlock"), fastboot_serial=fastboot_serial, fastboot_path=fastboot_path, timeout=fastboot_timeout) @mock.patch.object(adb_utils, "_fastboot_command") def test_309_adb_utils_fastboot_lock_device(self, mock_fastboot_command): """Verify fastbook_lock_device calls _fastboot_command correctly.""" fastboot_serial = "fake_fastboot_serial" fastboot_path = FASTBOOT_CMD_PATH fastboot_timeout = 30.0 adb_utils.fastboot_lock_device( fastboot_serial, fastboot_path=fastboot_path, timeout=fastboot_timeout) mock_fastboot_command.assert_called() mock_fastboot_command.assert_called_with(("flashing", "lock"), fastboot_serial=fastboot_serial, fastboot_path=fastboot_path, timeout=fastboot_timeout) @mock.patch.object(adb_utils, "_fastboot_command") def test_310_adb_utils_fastboot_wipe_userdata(self, mock_fastboot_command): """Verify fastboot_wipe_userdata calls _fastboot_command correctly.""" fastboot_serial = "fake_fastboot_serial" fastboot_path = FASTBOOT_CMD_PATH fastboot_timeout = 30.0 adb_utils.fastboot_wipe_userdata( fastboot_serial, fastboot_path=fastboot_path, timeout=fastboot_timeout) mock_fastboot_command.assert_called() mock_fastboot_command.assert_called_with( "-w", fastboot_serial=fastboot_serial, fastboot_path=fastboot_path, timeout=fastboot_timeout) @mock.patch.object( adb_utils, "_adb_command", return_value="connected to aabbccdd") def test_311_adb_connect(self, mock_adb_command): """Verify adb connect method.""" adb_utils.connect(DEVICE_ADB_SERIAL) @mock.patch.object( adb_utils, "_adb_command", return_value="unable to connect") def test_312_adb_connect_failure_to_connect(self, mock_adb_command): """Verify adb connect method.""" with self.assertRaises(errors.DeviceError): adb_utils.connect(DEVICE_ADB_SERIAL) @mock.patch.object(adb_utils, "get_adb_path", return_value=ADB_CMD_PATH) def test_313_adb_command_terminate(self, mock_get_adb_path): """Verify adb connect method.""" command = "fake_command" command_output = "fake output\n" mock_proc = mock.MagicMock(spec=subprocess.Popen, returncode=0) mock_proc.communicate.side_effect = subprocess.TimeoutExpired( cmd=command, timeout=1) mock_proc.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_proc): with mock.patch.object(mock_proc, "terminate") as mock_terminate: with self.assertRaises(subprocess.TimeoutExpired): adb_utils.shell(DEVICE_ADB_SERIAL, command, timeout=1) mock_terminate.assert_called_once() @mock.patch.object(adb_utils, "get_adb_path", return_value=ADB_CMD_PATH) def test_314_adb_shell_retry_failed(self, mock_adb_command): """Verify shell works as expected.""" command_output = "error: closed" mock_proc = mock.MagicMock(spec=subprocess.Popen, returncode=0) mock_proc.communicate.return_value = (command_output.encode( "utf-8", errors="replace"), None) with mock.patch.object(subprocess, "Popen", return_value=mock_proc): with self.assertRaises(errors.DeviceError): adb_utils.shell('echo "fake"', "12345") @mock.patch.object(adb_utils, "_adb_command", return_value=("Output", 0)) def test_320_adb_utils_add_port_forwarding_success(self, mock_adb_command): """Verifies add_port_forwarding on success.""" output = adb_utils.add_port_forwarding(host_port=123, device_port=456, adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) mock_adb_command.assert_called_once_with( ("forward", "tcp:123", "tcp:456"), adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH, include_return_code=True) self.assertEqual(output, "Output") @mock.patch.object(adb_utils, "_adb_command", return_value=("Error", 1)) def test_321_adb_utils_add_port_forwarding_exception(self, mock_adb_command): """Verifies add_port_forwarding raises exception.""" with self.assertRaises(RuntimeError): adb_utils.add_port_forwarding(host_port=123, device_port=456, adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) mock_adb_command.assert_called_once_with( ("forward", "tcp:123", "tcp:456"), adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH, include_return_code=True) @mock.patch.object(adb_utils, "_adb_command", return_value=("Output", 0)) def test_325_adb_utils_remove_port_forwarding_success(self, mock_adb_command): """Verifies remove_port_forwarding on success.""" output = adb_utils.remove_port_forwarding(host_port=123, adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) mock_adb_command.assert_called_once_with( ("forward", "--remove", "tcp:123"), adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH, include_return_code=True) self.assertEqual(output, "Output") @mock.patch.object(adb_utils, "_adb_command", return_value=("Error", 1)) def test_326_adb_utils_remove_port_forwarding_exception(self, mock_adb_command): """Verifies remove_port_forwarding on raise exception.""" with self.assertRaises(RuntimeError): adb_utils.remove_port_forwarding(host_port=123, adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH) mock_adb_command.assert_called_once_with( ("forward", "--remove", "tcp:123"), adb_serial=DEVICE_ADB_SERIAL, adb_path=ADB_CMD_PATH, include_return_code=True) @mock.patch.object(adb_utils, "_fastboot_command") def test_330_adb_utils_fastboot_check_is_unlocked(self, mock_fastboot_command): """Verifies fastboot_check_is_unlocked function return correct result.""" fastboot_serial = "fake_fastboot_serial" unlocked_output = "unlocked: yes" locked_output = "unlocked: no" mock_fastboot_command.return_value = unlocked_output unlocked_expected = adb_utils.fastboot_check_is_unlocked( fastboot_serial=fastboot_serial) mock_fastboot_command.return_value = locked_output locked_expected = adb_utils.fastboot_check_is_unlocked( fastboot_serial=fastboot_serial) self.assertTrue(unlocked_expected) self.assertFalse(locked_expected) @mock.patch.object(adb_utils, "_fastboot_command") def test_331_adb_utils_fastboot_check_is_unlocked_exception( self, mock_fastboot_command): """Verifies fastboot_check_is_unlocked function raises with bad output.""" fastboot_serial = "fake_fastboot_serial" unknown_output = "something went wrong" mock_fastboot_command.return_value = unknown_output with self.assertRaises(RuntimeError): adb_utils.fastboot_check_is_unlocked(fastboot_serial=fastboot_serial) @mock.patch.object( adb_utils, "_adb_command", return_value=("bugreport output\n", 0)) def test_340_adb_utils_bugreport(self, mock_adb_command): """Verifies bugreport.""" adb_utils.bugreport(DEVICE_ADB_SERIAL) mock_adb_command.assert_called() @mock.patch.object( adb_utils, "_adb_command", return_value=("bugreport output\n", 1)) def test_341_adb_utils_bugreport_bad_returncode( self, mock_adb_command): """Verifies bugreport raises if ADB command fails.""" with self.assertRaises(RuntimeError): adb_utils.bugreport(DEVICE_ADB_SERIAL) mock_adb_command.assert_called() @mock.patch.object(adb_utils, "_adb_command") @mock.patch.object(os.path, "exists", return_value=False) def test_342_adb_utils_pull_from_device_bad_destination_path( self, mock_os_path_exists, mock_adb_command): """Verifies bugreport provided bad destination path.""" destination_path = "/bogus/path" with self.assertRaises(ValueError): adb_utils.bugreport(DEVICE_ADB_SERIAL, destination_path=destination_path) mock_os_path_exists.assert_called() mock_adb_command.assert_not_called() if __name__ == "__main__": unit_test_case.main()

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0.061641

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0

null

0

1

0

1

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null

0

5

63cb3e72171de82701ab61371e19e92285bb291d

8,866

py

Python

gbdtmo/gbdtmo.py

samanemami/GBDTMO

33ee163d5db4dd71dae620c8e1f8295ed33c0a24

[ "MIT" ]

2

2021-09-15T16:18:15.000Z

2022-01-12T10:35:18.000Z

gbdtmo/gbdtmo.py

samanemami/GBDTMO

33ee163d5db4dd71dae620c8e1f8295ed33c0a24

[ "MIT" ]

null

gbdtmo/gbdtmo.py

samanemami/GBDTMO

33ee163d5db4dd71dae620c8e1f8295ed33c0a24

[ "MIT" ]

null

import numpy as np import numpy.ctypeslib as npct import ctypes from .histogram import get_bins_maps from .lib_utils import * class BoostUtils: def __init__(self, lib): self.lib = lib self._boostnode = None def _set_gh(self, g, h): self.lib.SetGH(self._boostnode, g, h) def _set_bin(self, bins): num, value = [], [] for i, _ in enumerate(bins): num.append(len(_)) num = np.array(num, np.uint16) value = np.concatenate(bins, axis=0) self.lib.SetBin(self._boostnode, num, value) def _set_label(self, x: np.array, is_train: bool): if x.dtype == np.float64: if x.ndim == 1: self.lib.SetLabelDouble.argtypes = [ctypes.c_void_p, array_1d_double, ctypes.c_bool] elif x.ndim == 2: self.lib.SetLabelDouble.argtypes = [ctypes.c_void_p, array_2d_double, ctypes.c_bool] else: assert False, "label must be 1D or 2D array" self.lib.SetLabelDouble(self._boostnode, x, is_train) elif x.dtype == np.int32: if x.ndim == 1: self.lib.SetLabelInt.argtypes = [ctypes.c_void_p, array_1d_int, ctypes.c_bool] elif x.ndim == 2: self.lib.SetLabelInt.argtypes = [ctypes.c_void_p, array_2d_int, ctypes.c_bool] else: assert False, "label must be 1D or 2D array" self.lib.SetLabelInt(self._boostnode, x, is_train) else: assert False, "dtype of label must be float64 or int32" def boost(self): self.lib.Boost(self._boostnode) def dump(self, path): self.lib.Dump(self._boostnode, path) def load(self, path): self.lib.Load(self._boostnode, path) def train(self, num): self.lib.Train(self._boostnode, num) class GBDTSingle(BoostUtils): def __init__(self, lib, out_dim=1, params={}): super(BoostUtils, self).__init__() BoostUtils.__init__(self, lib) self.out_dim = out_dim self.params = default_params() self.params.update(params) self.__dict__.update(self.params) def set_booster(self, inp_dim): self._boostnode = self.lib.SingleNew(inp_dim, self.params['loss'], self.params['max_depth'], self.params['max_leaves'], self.params['seed'], self.params['min_samples'], self.params['num_threads'], self.params['lr'], self.params['reg_l1'], self.params['reg_l2'], self.params['gamma'], self.params['base_score'], self.params['early_stop'], self.params['verbose'], self.params['hist_cache']) def set_data(self, train_set: tuple = None, eval_set: tuple = None): if train_set is not None: self.data, self.label = train_set self.set_booster(self.data.shape[-1]) self.bins, self.maps = get_bins_maps(self.data, self.max_bins, self.num_threads) self._set_bin(self.bins) self.maps = np.ascontiguousarray(self.maps.transpose()) self.preds_train = np.full(len(self.data) * self.out_dim, self.base_score, dtype='float64') self.lib.SetData.argtypes = [ctypes.c_void_p, array_2d_uint16, array_2d_double, array_1d_double, ctypes.c_int, ctypes.c_bool] self.lib.SetData(self._boostnode, self.maps, self.data, self.preds_train, len(self.data), True) if self.label is not None: self._set_label(self.label, True) if eval_set is not None: self.data_eval, self.label_eval = eval_set self.preds_eval = np.full(len(self.data_eval) * self.out_dim, self.base_score, dtype='float64') maps = np.zeros((1, 1), 'uint16') self.lib.SetData(self._boostnode, maps, self.data_eval, self.preds_eval, len(self.data_eval), False) if self.label_eval is not None: self._set_label(self.label_eval, False) def train_multi(self, num): ''' only used for multi-classification ''' assert self.out_dim>1, "out_dim must bigger than 1" self.lib.TrainMulti(self._boostnode, num, self.out_dim) def predict(self, x, num_trees=0): preds = np.full(len(x) * self.out_dim, self.base_score, dtype='float64') if self.out_dim == 1: self.lib.Predict.argtypes = [ctypes.c_void_p, array_2d_double, array_1d_double, ctypes.c_int, ctypes.c_int] self.lib.Predict(self._boostnode, x, preds, len(x), num_trees) return preds else: self.lib.PredictMulti(self._boostnode, x, preds, len(x), self.out_dim, num_trees) preds = np.reshape(preds, (self.out_dim, len(x))) return np.transpose(preds) def reset(self): self.lib.Reset(self._boostnode) class GBDTMulti(BoostUtils): def __init__(self, lib, out_dim=1, params={}): super(BoostUtils, self).__init__() BoostUtils.__init__(self, lib) self.out_dim = out_dim self.params = default_params() self.params.update(params) self.__dict__.update(self.params) def set_booster(self, inp_dim, out_dim): self._boostnode = self.lib.MultiNew(inp_dim, self.out_dim, self.params['topk'], self.params['loss'], self.params['max_depth'], self.params['max_leaves'], self.params['seed'], self.params['min_samples'], self.params['num_threads'], self.params['lr'], self.params['reg_l1'], self.params['reg_l2'], self.params['gamma'], self.params['base_score'], self.params['early_stop'], self.params['one_side'], self.params['verbose'], self.params['hist_cache']) def set_data(self, train_set: tuple = None, eval_set: tuple = None): if train_set is not None: self.data, self.label = train_set self.set_booster(self.data.shape[-1], self.out_dim) self.bins, self.maps = get_bins_maps(self.data, self.max_bins, self.num_threads) self._set_bin(self.bins) self.maps = np.ascontiguousarray(self.maps.transpose()) self.preds_train = np.full((len(self.data), self.out_dim), self.base_score, dtype='float64') self.lib.SetData.argtypes = [ctypes.c_void_p, array_2d_uint16, array_2d_double, array_2d_double, ctypes.c_int, ctypes.c_bool] self.lib.SetData(self._boostnode, self.maps, self.data, self.preds_train, len(self.data), True) if self.label is not None: self._set_label(self.label, True) if eval_set is not None: self.data_eval, self.label_eval = eval_set self.preds_eval = np.full((len(self.data_eval), self.out_dim), self.base_score, dtype='float64') maps = np.zeros((1, 1), 'uint16') self.lib.SetData(self._boostnode, maps, self.data_eval, self.preds_eval, len(self.data_eval), False) if self.label_eval is not None: self._set_label(self.label_eval, False) def predict(self, x, num_trees=0): preds = np.full((len(x), self.out_dim), self.base_score, dtype='float64') self.lib.Predict.argtypes = [ctypes.c_void_p, array_2d_double, array_2d_double, ctypes.c_int, ctypes.c_int] self.lib.Predict(self._boostnode, x, preds, len(x), num_trees) return preds

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0.131148

0.082702

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0.034918

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8,866

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0

null

0

1

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null

0

5

63d0e3d64e13f20d2c0c373757cdad7580a1300b

4,300

py

Python

src/utils/plots.py

Light4Code/tensorflow-research

392c2d7bc376f491fec68d479b130f883d6d028d

[ "MIT" ]

5

2020-02-29T16:28:55.000Z

2021-11-24T07:47:36.000Z

src/utils/plots.py

Light4Code/tensorflow-research

392c2d7bc376f491fec68d479b130f883d6d028d

[ "MIT" ]

3

2020-11-13T18:41:57.000Z

2022-02-10T01:37:51.000Z

src/utils/plots.py

Light4Code/tensorflow-research

392c2d7bc376f491fec68d479b130f883d6d028d

[ "MIT" ]

4

2020-03-24T10:50:17.000Z

2020-06-02T13:07:28.000Z

import matplotlib.pyplot as plt import numpy as np import numpy.ma as ma import utils.image_util as iu from utils.custom_types import Vector def plot_history(loss, acc, val_loss, val_acc): plt.figure(figsize=(20, 10)) plt.subplot(2, 1, 1) plt.title("Loss") plt.grid() plt.plot(loss) plt.plot(val_loss) plt.xlabel("Epoch") plt.ylabel("Loss") plt.legend(["Train", "Test"], loc="upper left") plt.subplot(2, 1, 2) plt.title("Accuracy") plt.grid() plt.plot(acc) plt.plot(val_acc) plt.xlabel("Epoch") plt.ylabel("Accuracy") plt.legend(["Train", "Test"], loc="upper left") plt.show() def plot_difference( predictions, test_images, input_shape: Vector, threshold: float = 0.0 ): plt.figure(figsize=(20, 10)) pred_count = len(predictions) plt_shape = (input_shape[0], input_shape[1]) plt_cmap = "gray" if input_shape[2] > 1: plt_shape = ( input_shape[0], input_shape[1], input_shape[2], ) index = 1 plt_index = 0 for test_image in test_images: original_image = test_image.reshape(plt_shape) pred_image = predictions[plt_index].reshape(plt_shape) diff, se = iu.create_diff(original_image, pred_image, threshold) mask = ma.masked_where(diff == False, diff) plt.subplot(pred_count, 4, index) plt.title("Original") plt.imshow(original_image, interpolation="none", cmap=plt_cmap) index += 1 plt.subplot(pred_count, 4, index) plt.title("Prediction") plt.imshow(pred_image, interpolation="none", cmap=plt_cmap) index += 1 plt.subplot(pred_count, 4, index) plt.title("Diff (SE: {0})".format(round(se, 2))) plt.imshow(diff, interpolation="none", cmap=plt_cmap) index += 1 plt.subplot(pred_count, 4, index) plt.title("Overlay") plt.imshow(original_image, interpolation="none", cmap=plt_cmap) plt.imshow(mask, cmap="jet", interpolation="none", alpha=0.7) index += 1 plt_index += 1 plt.show() def plot_prediction( predictions, test_images, input_shape: Vector, threshold: float = 0.4 ): plt.figure(figsize=(20, 10)) pred_count = len(predictions) plt_shape = (input_shape[0], input_shape[1]) plt_cmap = "gray" if input_shape[2] > 1: plt_shape = ( input_shape[0], input_shape[1], input_shape[2], ) index = 1 plt_index = 0 for test_image in test_images: original_image = test_image.reshape(plt_shape) pred_image = predictions[plt_index].reshape(plt_shape) mask = ma.masked_where(pred_image < threshold, pred_image) plt.subplot(pred_count, 3, index) plt.title("Original") plt.imshow(original_image, interpolation="none", cmap=plt_cmap) index += 1 plt.subplot(pred_count, 3, index) plt.title("Prediction") plt.imshow(pred_image, interpolation="none", cmap=plt_cmap) index += 1 plt.subplot(pred_count, 3, index) plt.title("Overlay") plt.imshow(original_image, interpolation="none", cmap=plt_cmap) plt.imshow(mask, cmap="jet", interpolation="none", alpha=0.7) index += 1 plt_index += 1 plt.show() def plot_classification(predictions, test_images, input_shape: Vector, classes: [], threshold: float = 0.4): plt.figure(figsize=(20, 10)) pred_count = len(predictions) plt_shape = (input_shape[0], input_shape[1]) plt_cmap = "gray" if input_shape[2] > 1: plt_shape = ( input_shape[0], input_shape[1], input_shape[2], ) index = 1 plt_index = 0 for test_image in test_images: original_image = test_image.reshape(plt_shape) pred = predictions[plt_index] c_idx = np.argmax(pred) plt.subplot(pred_count, 1, index) value = pred[c_idx] if (value >= threshold): plt.title("{0} ({1})".format(classes[c_idx], value)) else: plt.title("{0} ({1})".format("Unknown", value)) plt.imshow(original_image, interpolation="none", cmap=plt_cmap) index += 1 plt_index += 1 plt.show()

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0

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0.258372

4,300

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0

1

0

1

0

1

0

null

0

5

63d33b671fe35061f0300b274a32b66e28d0a7ac

80

py

Python

pypi_starter/__init__.py

wuhaifengdhu/pypi-starter

3ccb80dd9490f9d65b986350d82f9a20743af17f

[ "Apache-2.0" ]

null

pypi_starter/__init__.py

wuhaifengdhu/pypi-starter

3ccb80dd9490f9d65b986350d82f9a20743af17f

[ "Apache-2.0" ]

null

pypi_starter/__init__.py

wuhaifengdhu/pypi-starter

3ccb80dd9490f9d65b986350d82f9a20743af17f

[ "Apache-2.0" ]

null

""" Your application """ from submodule.main import * from main import *

11.428571

29

0.65

9

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5.777778

0.666667

0.384615

0

0.2375

80

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true

0

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1

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1

0

null

0

1

0

1

0

5

8921c8342da583a53fe7e6baf0b2a3160c459d31

52

py

Python

examples/fore.py

LyQuid12/colorgb

78addcf85f0e750ca45a7955e5008f7a8a946281

[ "MIT" ]

1

2022-01-26T10:26:24.000Z

examples/fore.py

LyQuid12/colorgb

78addcf85f0e750ca45a7955e5008f7a8a946281

[ "MIT" ]

null

examples/fore.py

LyQuid12/colorgb

78addcf85f0e750ca45a7955e5008f7a8a946281

[ "MIT" ]

null

import colorgb print(colorgb.fore("Hi!", "green"))

13

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1

0

1

0

1

0

5

892b0a91946a1df7a1b4680a474c70df84c8c932

857

py

Python

tests/v2/test_team_response_attributes.py

anbnyc/datadog-api-client-python

162bd0c6f2523a809aec08a3197e85dc74b78c21

[ "Apache-2.0" ]

null

tests/v2/test_team_response_attributes.py

anbnyc/datadog-api-client-python

162bd0c6f2523a809aec08a3197e85dc74b78c21

[ "Apache-2.0" ]

null

tests/v2/test_team_response_attributes.py

anbnyc/datadog-api-client-python

162bd0c6f2523a809aec08a3197e85dc74b78c21

[ "Apache-2.0" ]

null

# coding: utf-8 # Unless explicitly stated otherwise all files in this repository are licensed under the Apache-2.0 License. # This product includes software developed at Datadog (https://www.datadoghq.com/). # Copyright 2019-Present Datadog, Inc. import sys import unittest import datadog_api_client.v2 from datadog_api_client.v2.model.team_response_attributes import TeamResponseAttributes class TestTeamResponseAttributes(unittest.TestCase): """TeamResponseAttributes unit test stubs""" def setUp(self): pass def tearDown(self): pass def testTeamResponseAttributes(self): """Test TeamResponseAttributes""" # FIXME: construct object with mandatory attributes with example values # model = TeamResponseAttributes() # noqa: E501 pass if __name__ == '__main__': unittest.main()

25.969697

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857

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857

32

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0

1

0

1

0

1

0

5

895c1ad530c40f1c5d1fb2b8ed674dd74150a4b7

49

py

Python

urduhack/utils/tests/test_text.py

fahdrazavi/urduhack

a2370b0d8c1ee3f260ff90ca5056f45ed9b73ee8

[ "MIT" ]

null

urduhack/utils/tests/test_text.py

fahdrazavi/urduhack

a2370b0d8c1ee3f260ff90ca5056f45ed9b73ee8

[ "MIT" ]

null

urduhack/utils/tests/test_text.py

fahdrazavi/urduhack

a2370b0d8c1ee3f260ff90ca5056f45ed9b73ee8

[ "MIT" ]

null

# coding: utf8 """Test cases for text.py file"""

16.333333

33

0.653061

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49

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1

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0.02439

0.163265

49

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24.5

0.756098

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null

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null

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null

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null

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null

0

1

0

1

0

null

0

1

0

5

895ceb1226f1223073e975c0eb48dfda8072b8fb

2,136

py

Python

performance_test/testcase.py

DeqingQu/CacheControlHelper

d9425ff08253f10ef1028b724418c705f8d58bf5

[ "MIT" ]

null

performance_test/testcase.py

DeqingQu/CacheControlHelper

d9425ff08253f10ef1028b724418c705f8d58bf5

[ "MIT" ]

null

performance_test/testcase.py

DeqingQu/CacheControlHelper

d9425ff08253f10ef1028b724418c705f8d58bf5

[ "MIT" ]

null

from cache_control_helper import CacheControlHelper import time import sys import requests import requests_cache requests_cache.install_cache('performance_test') def get_request(url): requests = CacheControlHelper() try: res = requests.get(url, timeout=120) except requests.exceptions.Timeout: print(url, file=sys.stderr) print('Timeout for URL: ' + url, file=sys.stderr) return None except KeyboardInterrupt: sys.exit(0) except BaseException as e: print(url, file=sys.stderr) print('%s received for URL: %s' % (e, url), file=sys.stderr) return None status_code = res.status_code if status_code != 200: print(url, file=sys.stderr) print('Status code ' + str(status_code) + ' for url: ' + url, file=sys.stderr) return None return res.json() def get_request_cache(url): try: res = requests.get(url, timeout=120) except requests.exceptions.Timeout: print(url, file=sys.stderr) print('Timeout for URL: ' + url, file=sys.stderr) return None except KeyboardInterrupt: sys.exit(0) except BaseException as e: print(url, file=sys.stderr) print('%s received for URL: %s' % (e, url), file=sys.stderr) return None status_code = res.status_code if status_code != 200: print(url, file=sys.stderr) print('Status code ' + str(status_code) + ' for url: ' + url, file=sys.stderr) return None return res.json() if __name__ == '__main__': # using CacheControl # base_url = 'http://localhost:3000/test/' # t = time.time() # for i in range(100000): # r = get_request(base_url + str(i)) # if i % 1000 == 0: # print(r) # # print(time.time() - t) # print(time.time() - t) # using requests-cache base_url = 'http://localhost:3000/test/' t = time.time() for i in range(10000): r = get_request_cache(base_url + str(i)) if i % 1000 == 0: print(r) # print(time.time() - t) print(time.time() - t)

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2,136

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null

0

1

0

null

0

5

89b8b74f1ee518f5d1b44c2b1c318c3869dd4dbd

192

py

Python

tracedump/pwn_wrapper.py

Mic92/tracedumpd

a84eac58106f1f1d7a82f5dee2a327861e763e4e

[ "MIT" ]

1

2021-03-22T18:04:53.000Z

tracedump/pwn_wrapper.py

Mic92/tracedump

a84eac58106f1f1d7a82f5dee2a327861e763e4e

[ "MIT" ]

null

tracedump/pwn_wrapper.py

Mic92/tracedump

a84eac58106f1f1d7a82f5dee2a327861e763e4e

[ "MIT" ]

null

import os # stop pwnlib from doing fancy things os.environ["PWNLIB_NOTERM"] = "1" from pwnlib.elf.corefile import Coredump, Mapping # noqa: E402 from pwnlib.elf.elf import ELF # noqa: E402

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192

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null

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null

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1

0

1

0

1

0

5

982a5a6c85f4198d136ac06c6691b36716f7b587

940

py

Python

sdks/python/test/test_ReleaseUpdateError.py

Brantone/appcenter-sdks

eeb063ecf79908b6e341fb00196d2cd9dc8f3262

[ "MIT" ]

null

sdks/python/test/test_ReleaseUpdateError.py

Brantone/appcenter-sdks

eeb063ecf79908b6e341fb00196d2cd9dc8f3262

[ "MIT" ]

6

2019-10-23T06:38:53.000Z

2022-01-22T07:57:58.000Z

sdks/python/test/test_ReleaseUpdateError.py

Brantone/appcenter-sdks

eeb063ecf79908b6e341fb00196d2cd9dc8f3262

[ "MIT" ]

2

2019-10-23T06:31:05.000Z

2021-08-21T17:32:47.000Z

# coding: utf-8 """ App Center Client Microsoft Visual Studio App Center API # noqa: E501 OpenAPI spec version: preview Contact: benedetto.abbenanti@gmail.com Project Repository: https://github.com/b3nab/appcenter-sdks """ from __future__ import absolute_import import unittest import appcenter_sdk from ReleaseUpdateError.clsReleaseUpdateError import ReleaseUpdateError # noqa: E501 from appcenter_sdk.rest import ApiException class TestReleaseUpdateError(unittest.TestCase): """ReleaseUpdateError unit test stubs""" def setUp(self): pass def tearDown(self): pass def testReleaseUpdateError(self): """Test ReleaseUpdateError""" # FIXME: construct object with mandatory attributes with example values # model = appcenter_sdk.models.clsReleaseUpdateError.ReleaseUpdateError() # noqa: E501 pass if __name__ == '__main__': unittest.main()

23.5

95

0.723404

98

940

6.77551

0.632653

0.036145

0.078313

0

0.014628

0.2

940

39

96

24.102564

0.868351

0.469149

0

0.214286

0

0.017505

0

0.025641

0

1

0.214286

false

0.214286

0.357143

0

0.642857

0

null

0

null

0

1

0

1

0

1

0

1

0

5

983a2aeb9ad32099cd6f39c374a89a7d58015b41

1,535

py

Python

campbellsoup/utilities_test.py

NBOCampbellToets/CampbellSoup

45478c3e5e0362d01af8898078c6621f7b11c191

[ "PostgreSQL" ]

null

campbellsoup/utilities_test.py

NBOCampbellToets/CampbellSoup

45478c3e5e0362d01af8898078c6621f7b11c191

[ "PostgreSQL" ]

45

2016-11-21T16:01:44.000Z

2018-05-25T13:35:01.000Z

campbellsoup/utilities_test.py

NBOCampbellToets/CampbellSoup

45478c3e5e0362d01af8898078c6621f7b11c191

[ "PostgreSQL" ]

1

2019-02-27T08:04:55.000Z

# (c) 2016 Julian Gonggrijp from .utilities import * def test_un_camelcase(): assert un_camelcase('CampbellSoupX') == 'campbell_soup_x' assert un_camelcase('NBOCampbellToets') == 'n_b_o_campbell_toets' def test_append_to(): __all__ = [] class Example(object): pass @append_to(__all__) class Illustration(object): pass @append_to(__all__) def foo(): pass def bar(): pass assert __all__ == ['Illustration', 'foo'] def test_maybe(): tester = { 'banana': [ 0, 'x', [1, 2, 3], { 'deep_banana': {'value': 'deeper_banana'}, } ], 'orange': [], } assert len(maybe(tester, 'banana')) == 4 assert maybe(tester, 'banana', 0) == 0 assert maybe(tester, 'banana', 1) == 'x' assert maybe(tester, 'banana', 1, 0) == 'x' assert maybe(tester, 'banana', 1, 1) == None assert maybe(tester, 'banana', 2) == [1, 2, 3] assert maybe(tester, 'banana', 2, 2) == 3 assert maybe(tester, 'banana', 2, 3) == None assert maybe(tester, 'banana', 3, 'deep_banana', 'value') == 'deeper_banana' assert maybe(tester, 'banana', 3, 'deep_banana', 'other') == None assert maybe(tester, 'banana', 4) == None assert maybe(tester, 'orange') == [] assert maybe(tester, 'orange', 3) == None assert maybe(tester, 'orange', 3, fallback='') == '' assert maybe(tester, 'kiwi') == None assert maybe(tester, 'kiwi', fallback=10) == 10

28.425926

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0.558306

179

1,535

4.586592

0.273743

0.227771

0.310597

0.280146

0.511571

0.261876

0.146163

0

0.030466

0.272964

1,535

53

81

28.962264

0.705197

0.016287

0

0.133333

0

0.172414

0

0.422222

1

0.111111

false

0.088889

0.022222

0

0.177778

0

null

1

0

null

0

1

0

1

0

5

986a40624bae1a159be9cd68b43440b563e81ee0

208

py

Python

test.py

Timokasse/rediscache

e5bef0da973bdf53efaaea99b0ed9b41bb331ade

[ "Apache-2.0" ]

null

test.py

Timokasse/rediscache

e5bef0da973bdf53efaaea99b0ed9b41bb331ade

[ "Apache-2.0" ]

null

test.py

Timokasse/rediscache

e5bef0da973bdf53efaaea99b0ed9b41bb331ade

[ "Apache-2.0" ]

null

#!/usr/bin/env python from time import sleep from rediscache import rediscache import time, redis @rediscache(1, 2) def getTestValue(): return (5, 'toto') if __name__ == '__main__': myfunction()

13.866667

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27

208

5.074074

0.777778

0.233577

0

0.017647

0.182692

208

14

34

14.857143

0.788235

0.096154

0

0.064171

0

1

0.125

true

0

0.375

0.125

0.625

0

1

0

null

1

0

null

0

1

0

1

0

5

98b33ea8451d3967d4ce2088f2eba80859167c6d

44,549

py

Python

tests/test_dataset_tensor_backend.py

evendrow/deepsnap

8d5762bf4a2ef6910ad602895685cac892207ba8

[ "MIT" ]

null

tests/test_dataset_tensor_backend.py

evendrow/deepsnap

8d5762bf4a2ef6910ad602895685cac892207ba8

[ "MIT" ]

null

tests/test_dataset_tensor_backend.py

evendrow/deepsnap

8d5762bf4a2ef6910ad602895685cac892207ba8

[ "MIT" ]

null

import copy import random import torch import unittest from torch_geometric.datasets import TUDataset, Planetoid from copy import deepcopy from deepsnap.graph import Graph from deepsnap.hetero_graph import HeteroGraph from deepsnap.dataset import GraphDataset, Generator, EnsembleGenerator from tests.utils import ( pyg_to_dicts, simple_networkx_graph, simple_networkx_small_graph, simple_networkx_graph_alphabet, simple_networkx_multigraph, generate_dense_hete_dataset, generate_simple_small_hete_graph, gen_graph ) class TestDatasetTensorBackend(unittest.TestCase): def test_dataset_basic(self): _, x, y, edge_x, edge_y, edge_index, graph_x, graph_y = ( simple_networkx_graph() ) G = Graph( node_feature=x, node_label=y, edge_index=edge_index, edge_feature=edge_x, edge_label=edge_y, graph_feature=graph_x, graph_label=graph_y, directed=True ) H = deepcopy(G) dataset = GraphDataset([G, H]) self.assertEqual(len(dataset), 2) def test_dataset_property(self): _, x, y, edge_x, edge_y, edge_index, graph_x, graph_y = ( simple_networkx_graph() ) G = Graph( node_feature=x, node_label=y, edge_index=edge_index, edge_feature=edge_x, edge_label=edge_y, graph_feature=graph_x, graph_label=graph_y, directed=True ) H = deepcopy(G) H.graph_label = torch.tensor([1]) graphs = [G, H] dataset = GraphDataset(graphs) self.assertEqual(dataset.num_node_labels, 5) self.assertEqual(dataset.num_node_features, 2) self.assertEqual(dataset.num_edge_labels, 4) self.assertEqual(dataset.num_edge_features, 2) self.assertEqual(dataset.num_graph_labels, 1) self.assertEqual(dataset.num_graph_features, 2) self.assertEqual(dataset.num_labels, 5) # node task dataset = GraphDataset(graphs, task="edge") self.assertEqual(dataset.num_labels, 4) dataset = GraphDataset(graphs, task="link_pred") self.assertEqual(dataset.num_labels, 5) dataset = GraphDataset(graphs, task="graph") self.assertEqual(dataset.num_labels, 1) def test_dataset_hetero_graph_split(self): G = generate_dense_hete_dataset() hete = HeteroGraph(G) hete = HeteroGraph( node_feature=hete.node_feature, node_label=hete.node_label, edge_feature=hete.edge_feature, edge_label=hete.edge_label, edge_index=hete.edge_index, directed=True ) # node dataset = GraphDataset([hete], task="node") split_res = dataset.split() for node_type in hete.node_label_index: num_nodes = int(len(hete.node_label_index[node_type])) node_0 = int(num_nodes * 0.8) node_1 = int(num_nodes * 0.1) node_2 = num_nodes - node_0 - node_1 self.assertEqual( len(split_res[0][0].node_label_index[node_type]), node_0, ) self.assertEqual( len(split_res[1][0].node_label_index[node_type]), node_1, ) self.assertEqual( len(split_res[2][0].node_label_index[node_type]), node_2, ) # node with specified split type dataset = GraphDataset([hete], task="node") node_split_types = ["n1"] split_res = dataset.split(split_types=node_split_types) for node_type in hete.node_label_index: if node_type in node_split_types: num_nodes = int(len(hete.node_label_index[node_type])) node_0 = int(num_nodes * 0.8) node_1 = int(num_nodes * 0.1) node_2 = num_nodes - node_0 - node_1 self.assertEqual( len(split_res[0][0].node_label_index[node_type]), node_0, ) self.assertEqual( len(split_res[1][0].node_label_index[node_type]), node_1, ) self.assertEqual( len(split_res[2][0].node_label_index[node_type]), node_2, ) else: num_nodes = int(len(hete.node_label_index[node_type])) self.assertEqual( len(split_res[0][0].node_label_index[node_type]), num_nodes, ) self.assertEqual( len(split_res[1][0].node_label_index[node_type]), num_nodes, ) self.assertEqual( len(split_res[2][0].node_label_index[node_type]), num_nodes, ) # node with specified split type (string mode) dataset = GraphDataset([hete], task="node") node_split_types = "n1" split_res = dataset.split(split_types=node_split_types) for node_type in hete.node_label_index: if node_type in node_split_types: num_nodes = int(len(hete.node_label_index[node_type])) node_0 = int(num_nodes * 0.8) node_1 = int(num_nodes * 0.1) node_2 = num_nodes - node_0 - node_1 self.assertEqual( len(split_res[0][0].node_label_index[node_type]), node_0, ) self.assertEqual( len(split_res[1][0].node_label_index[node_type]), node_1, ) self.assertEqual( len(split_res[2][0].node_label_index[node_type]), node_2, ) else: num_nodes = int(len(hete.node_label_index[node_type])) self.assertEqual( len(split_res[0][0].node_label_index[node_type]), num_nodes, ) self.assertEqual( len(split_res[1][0].node_label_index[node_type]), num_nodes, ) self.assertEqual( len(split_res[2][0].node_label_index[node_type]), num_nodes, ) # edge dataset = GraphDataset([hete], task="edge") split_res = dataset.split() for edge_type in hete.edge_label_index: num_edges = hete.edge_label_index[edge_type].shape[1] edge_0 = int(num_edges * 0.8) edge_1 = int(num_edges * 0.1) edge_2 = num_edges - edge_0 - edge_1 self.assertEqual( split_res[0][0].edge_label_index[edge_type].shape[1], edge_0, ) self.assertEqual( split_res[1][0].edge_label_index[edge_type].shape[1], edge_1, ) self.assertEqual( split_res[2][0].edge_label_index[edge_type].shape[1], edge_2, ) # edge with specified split type dataset = GraphDataset([hete], task="edge") edge_split_types = [("n1", "e1", "n1"), ("n1", "e2", "n2")] split_res = dataset.split(split_types=edge_split_types) for edge_type in hete.edge_label_index: if edge_type in edge_split_types: num_edges = hete.edge_label_index[edge_type].shape[1] edge_0 = int(num_edges * 0.8) edge_1 = int(num_edges * 0.1) edge_2 = num_edges - edge_0 - edge_1 self.assertEqual( split_res[0][0].edge_label_index[edge_type].shape[1], edge_0, ) self.assertEqual( split_res[1][0].edge_label_index[edge_type].shape[1], edge_1, ) self.assertEqual( split_res[2][0].edge_label_index[edge_type].shape[1], edge_2, ) else: num_edges = hete.edge_label_index[edge_type].shape[1] self.assertEqual( split_res[0][0].edge_label_index[edge_type].shape[1], num_edges, ) self.assertEqual( split_res[1][0].edge_label_index[edge_type].shape[1], num_edges, ) self.assertEqual( split_res[2][0].edge_label_index[edge_type].shape[1], num_edges, ) # link_pred dataset = GraphDataset([hete], task="link_pred") split_res = dataset.split(transductive=True) for edge_type in hete.edge_label_index: num_edges = hete.edge_label_index[edge_type].shape[1] edge_0 = 2 * int(0.8 * num_edges) edge_1 = 2 * int(0.1 * num_edges) edge_2 = 2 * ( num_edges - int(0.8 * num_edges) - int(0.1 * num_edges) ) self.assertEqual( split_res[0][0].edge_label_index[edge_type].shape[1], edge_0 ) self.assertEqual( split_res[1][0].edge_label_index[edge_type].shape[1], edge_1 ) self.assertEqual( split_res[2][0].edge_label_index[edge_type].shape[1], edge_2 ) # link_pred with specified split type dataset = GraphDataset([hete], task="link_pred") link_split_types = [("n1", "e1", "n1"), ("n1", "e2", "n2")] split_res = dataset.split( transductive=True, split_types=link_split_types ) for edge_type in hete.edge_label_index: if edge_type in link_split_types: num_edges = hete.edge_label_index[edge_type].shape[1] edge_0 = 2 * int(0.8 * num_edges) edge_1 = 2 * int(0.1 * num_edges) edge_2 = 2 * ( num_edges - int(0.8 * num_edges) - int(0.1 * num_edges) ) self.assertEqual( split_res[0][0].edge_label_index[edge_type].shape[1], edge_0 ) self.assertEqual( split_res[1][0].edge_label_index[edge_type].shape[1], edge_1 ) self.assertEqual( split_res[2][0].edge_label_index[edge_type].shape[1], edge_2 ) else: num_edges = hete.edge_label_index[edge_type].shape[1] self.assertEqual( split_res[0][0].edge_label_index[edge_type].shape[1], num_edges ) self.assertEqual( split_res[1][0].edge_label_index[edge_type].shape[1], num_edges ) self.assertEqual( split_res[2][0].edge_label_index[edge_type].shape[1], num_edges ) # link_pred + disjoint dataset = GraphDataset( [hete], task="link_pred", edge_train_mode="disjoint", edge_message_ratio=0.5, ) split_res = dataset.split( transductive=True, split_ratio=[0.6, 0.2, 0.2], ) for edge_type in hete.edge_label_index: num_edges = hete.edge_label_index[edge_type].shape[1] edge_0 = int(0.6 * num_edges) edge_0 = 2 * (edge_0 - int(0.5 * edge_0)) edge_1 = 2 * int(0.2 * num_edges) edge_2 = 2 * ( num_edges - int(0.6 * num_edges) - int(0.2 * num_edges) ) self.assertEqual( split_res[0][0].edge_label_index[edge_type].shape[1], edge_0, ) self.assertEqual( split_res[1][0].edge_label_index[edge_type].shape[1], edge_1, ) self.assertEqual( split_res[2][0].edge_label_index[edge_type].shape[1], edge_2, ) # link pred with edge_split_mode set to "exact" dataset = GraphDataset( [hete], task="link_pred", edge_split_mode="approximate" ) split_res = dataset.split(transductive=True) hete_link_train_edge_num = 0 hete_link_test_edge_num = 0 hete_link_val_edge_num = 0 num_edges = 0 for edge_type in hete.edge_label_index: num_edges += hete.edge_label_index[edge_type].shape[1] if edge_type in split_res[0][0].edge_label_index: hete_link_train_edge_num += ( split_res[0][0].edge_label_index[edge_type].shape[1] ) if edge_type in split_res[1][0].edge_label_index: hete_link_test_edge_num += ( split_res[1][0].edge_label_index[edge_type].shape[1] ) if edge_type in split_res[2][0].edge_label_index: hete_link_val_edge_num += ( split_res[2][0].edge_label_index[edge_type].shape[1] ) # num_edges_reduced = num_edges - 3 edge_0 = 2 * int(0.8 * num_edges) edge_1 = 2 * int(0.1 * num_edges) edge_2 = 2 * ( num_edges - int(0.8 * num_edges) - int(0.1 * num_edges) ) self.assertEqual( hete_link_train_edge_num, edge_0 ) self.assertEqual( hete_link_test_edge_num, edge_1 ) self.assertEqual( hete_link_val_edge_num, edge_2 ) # link pred with specified types and edge_split_mode set to "exact" dataset = GraphDataset( [hete], task="link_pred", edge_split_mode="approximate", ) link_split_types = [("n1", "e1", "n1"), ("n1", "e2", "n2")] split_res = dataset.split( transductive=True, split_types=link_split_types, ) hete_link_train_edge_num = 0 hete_link_test_edge_num = 0 hete_link_val_edge_num = 0 num_split_type_edges = 0 num_non_split_type_edges = 0 for edge_type in hete.edge_label_index: if edge_type in link_split_types: num_split_type_edges += ( hete.edge_label_index[edge_type].shape[1] ) else: num_non_split_type_edges += ( hete.edge_label_index[edge_type].shape[1] ) if edge_type in split_res[0][0].edge_label_index: hete_link_train_edge_num += ( split_res[0][0].edge_label_index[edge_type].shape[1] ) if edge_type in split_res[1][0].edge_label_index: hete_link_test_edge_num += ( split_res[1][0].edge_label_index[edge_type].shape[1] ) if edge_type in split_res[2][0].edge_label_index: hete_link_val_edge_num += ( split_res[2][0].edge_label_index[edge_type].shape[1] ) # num_edges_reduced = num_split_type_edges - 3 num_edges = num_split_type_edges edge_0 = 2 * int(0.8 * num_edges) + num_non_split_type_edges edge_1 = 2 * int(0.1 * num_edges) + num_non_split_type_edges edge_2 = 2 * ( num_edges - int(0.8 * num_edges) - int(0.1 * num_edges) ) + num_non_split_type_edges self.assertEqual(hete_link_train_edge_num, edge_0) self.assertEqual(hete_link_test_edge_num, edge_1) self.assertEqual(hete_link_val_edge_num, edge_2) def test_dataset_split(self): # inductively split with graph task pyg_dataset = TUDataset("./enzymes", "ENZYMES") ds = pyg_to_dicts(pyg_dataset) graphs = [Graph(**item) for item in ds] dataset = GraphDataset(graphs, task="graph") split_res = dataset.split(transductive=False) num_graphs = len(dataset) num_train = int(0.8 * num_graphs) num_val = int(0.1 * num_graphs) num_test = num_graphs - num_train - num_val self.assertEqual(num_train, len(split_res[0])) self.assertEqual(num_val, len(split_res[1])) self.assertEqual(num_test, len(split_res[2])) # inductively split with link_pred task # and default (`all`) edge_train_mode pyg_dataset = TUDataset("./enzymes", "ENZYMES") ds = pyg_to_dicts(pyg_dataset) graphs = [Graph(**item) for item in ds] dataset = GraphDataset(graphs, task="link_pred") split_res = dataset.split(transductive=False) num_graphs = len(dataset) num_train = int(0.8 * num_graphs) num_val = int(0.1 * num_graphs) num_test = num_graphs - num_train - num_val self.assertEqual(num_train, len(split_res[0])) self.assertEqual(num_val, len(split_res[1])) self.assertEqual(num_test, len(split_res[2])) # inductively split with link_pred task and `disjoint` edge_train_mode pyg_dataset = TUDataset("./enzymes", "ENZYMES") ds = pyg_to_dicts(pyg_dataset) graphs = [Graph(**item) for item in ds] dataset = GraphDataset( graphs, task="link_pred", edge_train_mode="disjoint", ) split_res = dataset.split(transductive=False) num_graphs = len(dataset) num_train = int(0.8 * num_graphs) num_val = int(0.1 * num_graphs) num_test = num_graphs - num_train - num_val self.assertEqual(num_train, len(split_res[0])) self.assertEqual(num_val, len(split_res[1])) self.assertEqual(num_test, len(split_res[2])) # transductively split with node task pyg_dataset = Planetoid("./cora", "Cora") ds = pyg_to_dicts(pyg_dataset, task="cora") graphs = [Graph(**item) for item in ds] dataset = GraphDataset(graphs, task="node") num_nodes = dataset.num_nodes[0] num_edges = dataset.num_edges[0] node_0 = int(0.8 * num_nodes) node_1 = int(0.1 * num_nodes) node_2 = num_nodes - node_0 - node_1 split_res = dataset.split() self.assertEqual( len(split_res[0][0].node_label_index), node_0 ) self.assertEqual( len(split_res[1][0].node_label_index), node_1 ) self.assertEqual( len(split_res[2][0].node_label_index), node_2 ) # transductively split with link_pred task # and default (`all`) edge_train_mode dataset = GraphDataset(graphs, task="link_pred") edge_0 = 2 * 2 * int(0.8 * num_edges) edge_1 = 2 * 2 * int(0.1 * num_edges) edge_2 = 2 * 2 * ( num_edges - int(0.8 * num_edges) - int(0.1 * num_edges) ) split_res = dataset.split() self.assertEqual( split_res[0][0].edge_label_index.shape[1], edge_0 ) self.assertEqual( split_res[1][0].edge_label_index.shape[1], edge_1 ) self.assertEqual( split_res[2][0].edge_label_index.shape[1], edge_2 ) # transductively split with link_pred task, `split` edge_train_mode # and 0.5 edge_message_ratio dataset = GraphDataset( graphs, task="link_pred", edge_train_mode="disjoint", edge_message_ratio=0.5, ) split_res = dataset.split() edge_0 = 2 * int(0.8 * num_edges) edge_0 = 2 * (edge_0 - int(0.5 * edge_0)) edge_1 = 2 * 2 * int(0.1 * num_edges) edge_2 = 2 * 2 * ( num_edges - int(0.8 * num_edges) - int(0.1 * num_edges) ) self.assertEqual( split_res[0][0].edge_label_index.shape[1], edge_0, ) self.assertEqual(split_res[1][0].edge_label_index.shape[1], edge_1) self.assertEqual(split_res[2][0].edge_label_index.shape[1], edge_2) # transductively split with link_pred task # and specified edge_negative_sampling_ratio dataset = GraphDataset( graphs, task="link_pred", edge_negative_sampling_ratio=2 ) split_res = dataset.split() edge_0 = (2 + 1) * (2 * int(0.8 * num_edges)) edge_1 = (2 + 1) * (2 * int(0.1 * num_edges)) edge_2 = (2 + 1) * ( 2 * (num_edges - int(0.8 * num_edges) - int(0.1 * num_edges)) ) self.assertEqual(split_res[0][0].edge_label_index.shape[1], edge_0) self.assertEqual(split_res[1][0].edge_label_index.shape[1], edge_1) self.assertEqual(split_res[2][0].edge_label_index.shape[1], edge_2) def test_dataset_split_custom(self): # transductive split with node task (self defined dataset) G, x, y, edge_x, edge_y, edge_index, graph_x, graph_y = ( simple_networkx_graph() ) Graph.add_edge_attr(G, "edge_feature", edge_x) Graph.add_edge_attr(G, "edge_label", edge_y) Graph.add_node_attr(G, "node_feature", x) Graph.add_node_attr(G, "node_label", y) Graph.add_graph_attr(G, "graph_feature", graph_x) Graph.add_graph_attr(G, "graph_label", graph_y) num_nodes = len(list(G.nodes)) nodes_train = torch.tensor(list(G.nodes)[: int(0.3 * num_nodes)]) nodes_val = torch.tensor( list(G.nodes)[int(0.3 * num_nodes): int(0.6 * num_nodes)] ) nodes_test = torch.tensor(list(G.nodes)[int(0.6 * num_nodes):]) graph_train = Graph( node_feature=x, node_label=y, edge_index=edge_index, node_label_index=nodes_train, directed=True ) graph_val = Graph( node_feature=x, node_label=y, edge_index=edge_index, node_label_index=nodes_val, directed=True ) graph_test = Graph( node_feature=x, node_label=y, edge_index=edge_index, node_label_index=nodes_test, directed=True ) graphs_train = [graph_train] graphs_val = [graph_val] graphs_test = [graph_test] dataset_train, dataset_val, dataset_test = ( GraphDataset(graphs_train, task='node'), GraphDataset(graphs_val, task='node'), GraphDataset(graphs_test, task='node') ) self.assertEqual( dataset_train[0].node_label_index.tolist(), list(range(int(0.3 * num_nodes))) ) self.assertEqual( dataset_val[0].node_label_index.tolist(), list(range(int(0.3 * num_nodes), int(0.6 * num_nodes))) ) self.assertEqual( dataset_test[0].node_label_index.tolist(), list(range(int(0.6 * num_nodes), num_nodes)) ) # transductive split with link_pred task (train/val split) edges = list(G.edges) num_edges = len(edges) edges_train = edges[: int(0.7 * num_edges)] edges_val = edges[int(0.7 * num_edges):] link_size_list = [len(edges_train), len(edges_val)] # generate pseudo pos and neg edges, they may overlap here train_pos = torch.LongTensor(edges_train).permute(1, 0) val_pos = torch.LongTensor(edges_val).permute(1, 0) val_neg = torch.randint(high=10, size=val_pos.shape, dtype=torch.int64) val_neg_double = torch.cat((val_neg, val_neg), dim=1) num_train = len(edges_train) num_val = len(edges_val) graph_train = Graph( node_feature=x, edge_index=edge_index, edge_feature=edge_x, directed=True, edge_label_index=train_pos ) graph_val = Graph( node_feature=x, edge_index=edge_index, edge_feature=edge_x, directed=True, edge_label_index=val_pos, negative_edge=val_neg_double ) graphs_train = [graph_train] graphs_val = [graph_val] dataset_train, dataset_val = ( GraphDataset( graphs_train, task='link_pred', resample_negatives=True ), GraphDataset( graphs_val, task='link_pred', edge_negative_sampling_ratio=2 ) ) self.assertEqual( dataset_train[0].edge_label_index.shape[1], 2 * link_size_list[0] ) self.assertEqual( dataset_train[0].edge_label.shape[0], 2 * link_size_list[0] ) self.assertEqual( dataset_val[0].edge_label_index.shape[1], val_pos.shape[1] + val_neg_double.shape[1] ) self.assertEqual( dataset_val[0].edge_label.shape[0], val_pos.shape[1] + val_neg_double.shape[1] ) self.assertTrue( torch.equal( dataset_train[0].edge_label_index[:, :num_train], train_pos ) ) self.assertTrue( torch.equal( dataset_val[0].edge_label_index[:, :num_val], val_pos ) ) self.assertTrue( torch.equal( dataset_val[0].edge_label_index[:, num_val:], val_neg_double ) ) dataset_train.resample_negatives = False self.assertTrue( torch.equal( dataset_train[0].edge_label_index, dataset_train[0].edge_label_index ) ) # transductive split with link_pred task with edge label edge_label_train = torch.LongTensor([1, 2, 3, 2, 1, 1, 2, 3, 2, 0, 0]) edge_label_val = torch.LongTensor([1, 2, 3, 2, 1, 0]) graph_train = Graph( node_feature=x, edge_index=edge_index, directed=True, edge_label_index=train_pos, edge_label=edge_label_train ) graph_val = Graph( node_feature=x, edge_index=edge_index, directed=True, edge_label_index=val_pos, negative_edge=val_neg, edge_label=edge_label_val ) graphs_train = [graph_train] graphs_val = [graph_val] dataset_train, dataset_val = ( GraphDataset(graphs_train, task='link_pred'), GraphDataset(graphs_val, task='link_pred') ) self.assertTrue( torch.equal( dataset_train[0].edge_label_index, dataset_train[0].edge_label_index ) ) self.assertTrue( torch.equal( dataset_train[0].edge_label[:num_train], edge_label_train ) ) self.assertTrue( torch.equal( dataset_val[0].edge_label[:num_val], edge_label_val ) ) # Multiple graph tensor backend link prediction (inductive) pyg_dataset = Planetoid('./cora', 'Cora') x = pyg_dataset[0].x y = pyg_dataset[0].y edge_index = pyg_dataset[0].edge_index row, col = edge_index mask = row < col row, col = row[mask], col[mask] edge_index = torch.stack([row, col], dim=0) edge_index = torch.cat( [edge_index, torch.flip(edge_index, [0])], dim=1 ) graphs = [ Graph( node_feature=x, node_label=y, edge_index=edge_index, directed=False ) ] graphs = [copy.deepcopy(graphs[0]) for _ in range(10)] edge_label_index = graphs[0].edge_label_index dataset = GraphDataset( graphs, task='link_pred', edge_message_ratio=0.6, edge_train_mode="all" ) datasets = {} datasets['train'], datasets['val'], datasets['test'] = dataset.split( transductive=False, split_ratio=[0.85, 0.05, 0.1] ) edge_label_index_split = ( datasets['train'][0].edge_label_index[ :, 0:edge_label_index.shape[1] ] ) self.assertTrue( torch.equal( edge_label_index, edge_label_index_split ) ) # transductive split with node task (pytorch geometric dataset) pyg_dataset = Planetoid("./cora", "Cora") ds = pyg_to_dicts(pyg_dataset, task="cora") graphs = [Graph(**item) for item in ds] split_ratio = [0.3, 0.3, 0.4] node_size_list = [0 for i in range(len(split_ratio))] for graph in graphs: custom_splits = [[] for i in range(len(split_ratio))] split_offset = 0 num_nodes = graph.num_nodes shuffled_node_indices = torch.randperm(graph.num_nodes) for i, split_ratio_i in enumerate(split_ratio): if i != len(split_ratio) - 1: num_split_i = int(split_ratio_i * num_nodes) nodes_split_i = ( shuffled_node_indices[ split_offset: split_offset + num_split_i ] ) split_offset += num_split_i else: nodes_split_i = shuffled_node_indices[split_offset:] custom_splits[i] = nodes_split_i node_size_list[i] += len(nodes_split_i) graph.custom = { "general_splits": custom_splits } node_feature = graphs[0].node_feature edge_index = graphs[0].edge_index directed = graphs[0].directed graph_train = Graph( node_feature=node_feature, edge_index=edge_index, directed=directed, node_label_index=graphs[0].custom["general_splits"][0] ) graph_val = Graph( node_feature=node_feature, edge_index=edge_index, directed=directed, node_label_index=graphs[0].custom["general_splits"][1] ) graph_test = Graph( node_feature=node_feature, edge_index=edge_index, directed=directed, node_label_index=graphs[0].custom["general_splits"][2] ) train_dataset = GraphDataset([graph_train], task="node") val_dataset = GraphDataset([graph_val], task="node") test_dataset = GraphDataset([graph_test], task="node") self.assertEqual( len(train_dataset[0].node_label_index), node_size_list[0] ) self.assertEqual( len(val_dataset[0].node_label_index), node_size_list[1] ) self.assertEqual( len(test_dataset[0].node_label_index), node_size_list[2] ) # transductive split with edge task pyg_dataset = Planetoid("./cora", "Cora") graphs_g = GraphDataset.pyg_to_graphs(pyg_dataset) ds = pyg_to_dicts(pyg_dataset, task="cora") graphs = [Graph(**item) for item in ds] split_ratio = [0.3, 0.3, 0.4] edge_size_list = [0 for i in range(len(split_ratio))] for i, graph in enumerate(graphs): custom_splits = [[] for i in range(len(split_ratio))] split_offset = 0 edges = list(graphs_g[i].G.edges) num_edges = graph.num_edges random.shuffle(edges) for i, split_ratio_i in enumerate(split_ratio): if i != len(split_ratio) - 1: num_split_i = int(split_ratio_i * num_edges) edges_split_i = ( edges[split_offset: split_offset + num_split_i] ) split_offset += num_split_i else: edges_split_i = edges[split_offset:] custom_splits[i] = edges_split_i edge_size_list[i] += len(edges_split_i) graph.custom = { "general_splits": custom_splits } node_feature = graphs[0].node_feature edge_index = graphs[0].edge_index directed = graphs[0].directed train_index = torch.tensor( graphs[0].custom["general_splits"][0] ).permute(1, 0) train_index = torch.cat((train_index, train_index), dim=1) val_index = torch.tensor( graphs[0].custom["general_splits"][1] ).permute(1, 0) val_index = torch.cat((val_index, val_index), dim=1) test_index = torch.tensor( graphs[0].custom["general_splits"][2] ).permute(1, 0) test_index = torch.cat((test_index, test_index), dim=1) graph_train = Graph( node_feature=node_feature, edge_index=edge_index, directed=directed, edge_label_index=train_index ) graph_val = Graph( node_feature=node_feature, edge_index=edge_index, directed=directed, edge_label_index=val_index ) graph_test = Graph( node_feature=node_feature, edge_index=edge_index, directed=directed, edge_label_index=test_index ) train_dataset = GraphDataset([graph_train], task="edge") val_dataset = GraphDataset([graph_val], task="edge") test_dataset = GraphDataset([graph_test], task="edge") self.assertEqual( train_dataset[0].edge_label_index.shape[1], 2 * edge_size_list[0] ) self.assertEqual( val_dataset[0].edge_label_index.shape[1], 2 * edge_size_list[1] ) self.assertEqual( test_dataset[0].edge_label_index.shape[1], 2 * edge_size_list[2] ) # inductive split with graph task pyg_dataset = TUDataset("./enzymes", "ENZYMES") ds = pyg_to_dicts(pyg_dataset) graphs = [Graph(**item) for item in ds] num_graphs = len(graphs) split_ratio = [0.3, 0.3, 0.4] graph_size_list = [] split_offset = 0 custom_split_graphs = [] for i, split_ratio_i in enumerate(split_ratio): if i != len(split_ratio) - 1: num_split_i = int(split_ratio_i * num_graphs) custom_split_graphs.append( graphs[split_offset: split_offset + num_split_i] ) split_offset += num_split_i graph_size_list.append(num_split_i) else: custom_split_graphs.append(graphs[split_offset:]) graph_size_list.append(len(graphs[split_offset:])) dataset = GraphDataset( graphs, task="graph", custom_split_graphs=custom_split_graphs ) split_res = dataset.split(transductive=False) self.assertEqual(graph_size_list[0], len(split_res[0])) self.assertEqual(graph_size_list[1], len(split_res[1])) self.assertEqual(graph_size_list[2], len(split_res[2])) def test_filter(self): pyg_dataset = TUDataset("./enzymes", "ENZYMES") ds = pyg_to_dicts(pyg_dataset) graphs = [Graph(**item) for item in ds] dataset = GraphDataset(graphs, task="graph") thresh = 90 orig_dataset_size = len(dataset) num_graphs_large = 0 for graph in dataset: if graph.num_nodes >= thresh: num_graphs_large += 1 dataset = dataset.filter( lambda graph: graph.num_nodes < thresh, deep_copy=False ) filtered_dataset_size = len(dataset) self.assertEqual( orig_dataset_size - filtered_dataset_size, num_graphs_large, ) def test_resample_disjoint_heterogeneous(self): G = generate_dense_hete_dataset() hete = HeteroGraph(G) hete = HeteroGraph( node_feature=hete.node_feature, node_label=hete.node_label, edge_feature=hete.edge_feature, edge_label=hete.edge_label, edge_index=hete.edge_index, directed=True ) graphs = [hete] dataset = GraphDataset( graphs, task="link_pred", edge_train_mode="disjoint", edge_message_ratio=0.8, resample_disjoint=True, resample_disjoint_period=1 ) dataset_train, _, _ = dataset.split(split_ratio=[0.5, 0.2, 0.3]) graph_train_first = dataset_train[0] graph_train_second = dataset_train[0] for message_type in graph_train_first.edge_index: self.assertEqual( graph_train_first.edge_label_index[message_type].shape[1], graph_train_second.edge_label_index[message_type].shape[1] ) self.assertEqual( graph_train_first.edge_label[message_type].shape, graph_train_second.edge_label[message_type].shape ) def test_resample_disjoint(self): pyg_dataset = Planetoid("./cora", "Cora") graphs = GraphDataset.pyg_to_graphs(pyg_dataset) graph = graphs[0] graph = Graph( node_label=graph.node_label, node_feature=graph.node_feature, edge_index=graph.edge_index, edge_feature=graph.edge_feature, directed=False ) graphs = [graph] dataset = GraphDataset( graphs, task="link_pred", edge_train_mode="disjoint", edge_message_ratio=0.8, resample_disjoint=True, resample_disjoint_period=1 ) dataset_train, _, _ = dataset.split(split_ratio=[0.5, 0.2, 0.3]) graph_train_first = dataset_train[0] graph_train_second = dataset_train[0] self.assertEqual( graph_train_first.edge_label_index.shape[1], graph_train_second.edge_label_index.shape[1] ) self.assertTrue( torch.equal( graph_train_first.edge_label, graph_train_second.edge_label ) ) def test_secure_split_heterogeneous(self): G = generate_simple_small_hete_graph() graph = HeteroGraph(G) graph = HeteroGraph( node_label=graph.node_label, edge_index=graph.edge_index, edge_label=graph.edge_label, directed=True ) graphs = [graph] # node task dataset = GraphDataset(graphs, task="node") split_res = dataset.split() for node_type in graph.node_label_index: num_nodes = graph.node_label_index[node_type].shape[0] num_nodes_reduced = num_nodes - 3 node_0 = 1 + int(num_nodes_reduced * 0.8) node_1 = 1 + int(num_nodes_reduced * 0.1) node_2 = num_nodes - node_0 - node_1 node_size = [node_0, node_1, node_2] for i in range(3): self.assertEqual( split_res[i][0].node_label_index[node_type].shape[0], node_size[i] ) self.assertEqual( split_res[i][0].node_label[node_type].shape[0], node_size[i] ) # edge task dataset = GraphDataset(graphs, task="edge") split_res = dataset.split() for message_type in graph.edge_label_index: num_edges = graph.edge_label_index[message_type].shape[1] num_edges_reduced = num_edges - 3 edge_0 = 1 + int(num_edges_reduced * 0.8) edge_1 = 1 + int(num_edges_reduced * 0.1) edge_2 = num_edges - edge_0 - edge_1 edge_size = [edge_0, edge_1, edge_2] for i in range(3): self.assertEqual( split_res[i][0].edge_label_index[message_type].shape[1], edge_size[i] ) self.assertEqual( split_res[i][0].edge_label[message_type].shape[0], edge_size[i] ) # link_pred task dataset = GraphDataset(graphs, task="link_pred") split_res = dataset.split() for message_type in graph.edge_label_index: num_edges = graph.edge_label_index[message_type].shape[1] num_edges_reduced = num_edges - 3 edge_0 = 2 * (1 + int(num_edges_reduced * 0.8)) edge_1 = 2 * (1 + int(num_edges_reduced * 0.1)) edge_2 = 2 * num_edges - edge_0 - edge_1 edge_size = [edge_0, edge_1, edge_2] for i in range(3): self.assertEqual( split_res[i][0].edge_label_index[message_type].shape[1], edge_size[i] ) self.assertEqual( split_res[i][0].edge_label[message_type].shape[0], edge_size[i] ) def test_secure_split(self): G = simple_networkx_small_graph() graph = Graph(G) graph = Graph( node_label=graph.node_label, edge_index=graph.edge_index, edge_label=graph.edge_label, directed=True ) graphs = [graph] # node task dataset = GraphDataset(graphs, task="node") num_nodes = dataset.num_nodes[0] num_nodes_reduced = num_nodes - 3 node_0 = 1 + int(0.8 * num_nodes_reduced) node_1 = 1 + int(0.1 * num_nodes_reduced) node_2 = num_nodes - node_0 - node_1 node_size = [node_0, node_1, node_2] split_res = dataset.split() for i in range(3): self.assertEqual( split_res[i][0].node_label_index.shape[0], node_size[i] ) self.assertEqual( split_res[i][0].node_label.shape[0], node_size[i] ) # edge task dataset = GraphDataset(graphs, task="edge") num_edges = dataset.num_edges[0] num_edges_reduced = num_edges - 3 edge_0 = 1 + int(0.8 * num_edges_reduced) edge_1 = 1 + int(0.1 * num_edges_reduced) edge_2 = num_edges - edge_0 - edge_1 edge_size = [edge_0, edge_1, edge_2] split_res = dataset.split() for i in range(3): self.assertEqual( split_res[i][0].edge_label_index.shape[1], edge_size[i] ) self.assertEqual( split_res[i][0].edge_label.shape[0], edge_size[i] ) # link_pred task dataset = GraphDataset(graphs, task="link_pred") num_edges = dataset.num_edges[0] num_edges_reduced = num_edges - 3 edge_0 = 2 * (1 + int(0.8 * num_edges_reduced)) edge_1 = 2 * (1 + int(0.1 * num_edges_reduced)) edge_2 = 2 * num_edges - edge_0 - edge_1 edge_size = [edge_0, edge_1, edge_2] split_res = dataset.split() for i in range(3): self.assertEqual( split_res[i][0].edge_label_index.shape[1], edge_size[i] ) self.assertEqual( split_res[i][0].edge_label.shape[0], edge_size[i] ) # graph task graphs = [deepcopy(graph) for _ in range(5)] dataset = GraphDataset(graphs, task="link_pred") num_graphs = len(dataset) num_graphs_reduced = num_graphs - 3 num_train = 1 + int(num_graphs_reduced * 0.8) num_val = 1 + int(num_graphs_reduced * 0.1) num_test = num_graphs - num_train - num_val split_res = dataset.split(transductive=False) self.assertEqual(num_train, len(split_res[0])) self.assertEqual(num_val, len(split_res[1])) self.assertEqual(num_test, len(split_res[2])) if __name__ == "__main__": unittest.main()

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py

Python

code/textProcessing.py

corollari/BaaCL

3ebe9ba7c3859243351fe1b12d4eb114bb51b441

[ "Unlicense" ]

1

2019-03-06T19:43:46.000Z

code/textProcessing.py

corollari/BaaL

3ebe9ba7c3859243351fe1b12d4eb114bb51b441

[ "Unlicense" ]

null

code/textProcessing.py

corollari/BaaL

3ebe9ba7c3859243351fe1b12d4eb114bb51b441

[ "Unlicense" ]

null

def preprocess(text): text=text.replace('\n', '\n\r') return text def getLetter(): return open("./input/letter.txt", "r").read()

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