xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

a8a98856c914486131c71af74b19873a5711b4de

198

py

Python

Python_Orientacao_Objeto/teste2.py

carlosrjhoe/Python

2df531b23ebbabc40539b09bb2bbdbe1ed1c2164

[ "MIT" ]

null

Python_Orientacao_Objeto/teste2.py

carlosrjhoe/Python

2df531b23ebbabc40539b09bb2bbdbe1ed1c2164

[ "MIT" ]

null

Python_Orientacao_Objeto/teste2.py

carlosrjhoe/Python

2df531b23ebbabc40539b09bb2bbdbe1ed1c2164

[ "MIT" ]

null

def soma(x,y): return print(x + y) def sub(x,y): return print(x - y) def mult(x,y): return print(x * y) def div(x,y): return print(x / y) soma(3,8) sub(10,5) mult(3,9) div(15,7)

11.647059

23

0.555556

44

198

2.5

0.363636

0.145455

0.290909

0.472727

0.627273

0.490909

0

0.066667

0.242424

198

17

24

11.647059

0.666667

0

1

0.333333

false

0

0.333333

0.666667

0.333333

0

null

0

1

0

null

0

1

0

1

0

5

a8ad80bc38cd16df91c7f7717982ec487fa5e8c1

126

py

Python

preprocessing_danych/dataset_config.py

MaciejKonieczka/gazspot-prediction

55177d7b7ae39a01a2820cd79f0e74897418e522

[ "MIT" ]

null

preprocessing_danych/dataset_config.py

MaciejKonieczka/gazspot-prediction

55177d7b7ae39a01a2820cd79f0e74897418e522

[ "MIT" ]

null

preprocessing_danych/dataset_config.py

MaciejKonieczka/gazspot-prediction

55177d7b7ae39a01a2820cd79f0e74897418e522

[ "MIT" ]

null

test_index = ("2019-05-01", "2020-04-30") train_index = ("2016-01-02", "2019-04-30") val_index = ("2018-10-01", "2019-04-30")

31.5

42

0.619048

24

126

3.125

0.583333

0.16

0.213333

0

0.421053

0.095238

126

3

43

42

0.236842

0

0.47619

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

1

0

null

0

5

765e377ff705e12f7620a2be9a2df5b9f1f29c8c

138

py

Python

apps/misc/context_processors.py

Thom03/edms-django

ad686a815d612f55921d6893093690311eeb831f

[ "MIT" ]

70

2019-05-26T11:48:32.000Z

2022-02-16T21:33:58.000Z

apps/misc/context_processors.py

CalebeGeazi/CoinBox

351611745d496d3cd3d871f96eb705250b5ec03f

[ "MIT" ]

7

2019-10-18T20:20:04.000Z

2021-04-21T15:25:15.000Z

apps/misc/context_processors.py

CalebeGeazi/CoinBox

351611745d496d3cd3d871f96eb705250b5ec03f

[ "MIT" ]

26

2019-07-07T17:06:00.000Z

2022-01-20T06:40:39.000Z

from django.utils.translation import get_language def django_settings(request): return { "LANGUAGE": get_language(), }

15.333333

49

0.688406

15

138

6.133333

0.733333

0.23913

0

0.217391

138

8

50

17.25

0.851852

0

0.057971

0

1

0.2

false

0

0.2

0.6

0

1

0

null

1

0

1

0

null

0

1

0

5

7668a391529415983ac3244d55ce03076f5a3acc

146

py

Python

starter_code/api_keys.py

tstenner1/python-api-challenge

dfc0642da6831d80664514d0705865f01e5c6c5a

[ "ADSL" ]

null

starter_code/api_keys.py

tstenner1/python-api-challenge

dfc0642da6831d80664514d0705865f01e5c6c5a

[ "ADSL" ]

null

starter_code/api_keys.py

tstenner1/python-api-challenge

dfc0642da6831d80664514d0705865f01e5c6c5a

[ "ADSL" ]

null

# OpenWeatherMap API Key weather_api_key = "f4695ec49ac558195fc591f0d450c34c" # Google API Key g_key = "AIzaSyAyIq5hhFN-Y0M16Ltie3YuwpDiKWx8tCk"

24.333333

52

0.835616

14

146

8.5

0.642857

0.151261

0

0.206107

0.10274

146

5

53

29.2

0.70229

0.253425

0

0.669811

0

1

0

false

0

1

0

null

0

1

0

1

0

1

null

0

5

76a110e79c22c20d6fd80a6e38e2b2d759f2b55b

480

py

Python

holobot/sdk/exceptions/argument_error.py

rexor12/holobot

89b7b416403d13ccfeee117ef942426b08d3651d

[ "MIT" ]

1

2021-05-24T00:17:46.000Z

holobot/sdk/exceptions/argument_error.py

rexor12/holobot

89b7b416403d13ccfeee117ef942426b08d3651d

[ "MIT" ]

41

2021-03-24T22:50:09.000Z

2021-12-17T12:15:13.000Z

holobot/sdk/exceptions/argument_error.py

rexor12/holobot

89b7b416403d13ccfeee117ef942426b08d3651d

[ "MIT" ]

null

class ArgumentError(Exception): def __init__(self, argument_name: str, *args) -> None: super().__init__(*args) self.argument_name = argument_name @property def argument_name(self) -> str: return self.__argument_name @argument_name.setter def argument_name(self, value: str) -> None: self.__argument_name = value def __str__(self) -> str: return f"{super().__str__()}\nArgument name: {self.argument_name}"

30

74

0.645833

56

480

5.017857

0.321429

0.384342

0.284698

0.170819

0.199288

0

0.235417

480

15

75

32

0.765668

0

0.116667

0.060417

0

1

0.333333

false

0

0.166667

0.583333

0

null

1

0

null

0

1

0

1

0

5

76c82645a89d088d85f5022f67a7ad6314a2c8d3

245

py

Python

api-test-code/credentials.py

srijansingh53/hatErase

eab4873efee4803a0c641777bce5bd63fb4fcc2f

[ "MIT" ]

1

2020-06-26T07:24:03.000Z

api-test-code/credentials.py

srijansingh53/hatErase

eab4873efee4803a0c641777bce5bd63fb4fcc2f

[ "MIT" ]

null

api-test-code/credentials.py

srijansingh53/hatErase

eab4873efee4803a0c641777bce5bd63fb4fcc2f

[ "MIT" ]

null

consumer_key = 'F1BCRW0AXUlr0wjLE8L6Znm8a' consumer_secret = 'HqRCnviPD8TmI05TSL47CA9eL6niFYtRu35CIP6J2F0fhjL9zz' access_token = '1163025465423982592-WrNzWHSUZykiwRmYbexhkUa5BGudYZ' access_secret = 'bZ0mWxWgFMClId9OoauDLQgT9IlwojmFS65OuGsy0E9QQ'

61.25

70

0.902041

13

245

16.692308

0.769231

0

0.196581

0.044898

245

4

71

61.25

0.730769

0

0.691057

0

1

0

false

0

1

0

1

null

0

1

0

1

null

0

5

76ce8679092b6c88a9cd642b89726a44b635faef

86

py

Python

test/lib-clay/externals/abi/newtypes/run.py

jb55/clay

db0bd2702ab0b6e48965cd85f8859bbd5f60e48e

[ "BSD-2-Clause" ]

185

2015-01-04T09:33:17.000Z

2022-03-18T04:53:38.000Z

test/externals/abi/complex/run.py

aep/clay

92224d71c9d64a32d70a289593c13da7f970ec35

[ "BSD-2-Clause" ]

7

2015-03-22T06:13:42.000Z

2015-12-28T19:07:24.000Z

test/externals/abi/complex/run.py

aep/clay

92224d71c9d64a32d70a289593c13da7f970ec35

[ "BSD-2-Clause" ]

20

2015-01-09T22:24:46.000Z

2022-03-18T04:54:59.000Z

import sys sys.path.append('..') import external_test external_test.runExternalTest()

17.2

31

0.802326

11

86

6.090909

0.636364

0.358209

0

0.069767

86

4

32

21.5

0.8375

0

0.023256

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

4f3d60508b961f3b5da0a3e216be2a3ee247021d

198

py

Python

Server/Python/src/dbs/dao/MySQL/DataTier/List.py

vkuznet/DBS

14df8bbe8ee8f874fe423399b18afef911fe78c7

[ "Apache-2.0" ]

8

2015-08-14T04:01:32.000Z

2021-06-03T00:56:42.000Z

Server/Python/src/dbs/dao/MySQL/DataTier/List.py

yuyiguo/DBS

14df8bbe8ee8f874fe423399b18afef911fe78c7

[ "Apache-2.0" ]

162

2015-01-07T21:34:47.000Z

2021-10-13T09:42:41.000Z

Server/Python/src/dbs/dao/MySQL/DataTier/List.py

yuyiguo/DBS

14df8bbe8ee8f874fe423399b18afef911fe78c7

[ "Apache-2.0" ]

16

2015-01-22T15:27:29.000Z

2021-04-28T09:23:28.000Z

#!/usr/bin/env python """ This module provides DataTier.List data access object. """ from dbs.dao.Oracle.DataTier.List import List as OraDataTierList class List(OraDataTierList): pass

19.8

64

0.727273

26

198

5.538462

0.807692

0.166667

0

0.171717

198

9

65

22

0.878049

0.378788

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

5

4f4c95f74358defd6290b5df4ac0fc0d0ae3c8b4

867

py

Python

src/pandas_profiling_study/report/structure/variables/__init__.py

lucasiscoviciMoon/pandas-profiling-study

142d3b0f5e3139cdb531819f637a407682fa5684

[ "MIT" ]

null

src/pandas_profiling_study/report/structure/variables/__init__.py

lucasiscoviciMoon/pandas-profiling-study

142d3b0f5e3139cdb531819f637a407682fa5684

[ "MIT" ]

null

src/pandas_profiling_study/report/structure/variables/__init__.py

lucasiscoviciMoon/pandas-profiling-study

142d3b0f5e3139cdb531819f637a407682fa5684

[ "MIT" ]

1

2020-04-25T15:20:39.000Z

from ....report.structure.variables.render_boolean import render_boolean from ....report.structure.variables.render_categorical import ( render_categorical, ) from ....report.structure.variables.render_common import render_common from ....report.structure.variables.render_complex import render_complex from ....report.structure.variables.render_count import render_count from ....report.structure.variables.render_date import render_date from ....report.structure.variables.render_path import render_path from ....report.structure.variables.render_path_image import ( render_path_image, ) from ....report.structure.variables.render_real import render_real from ....report.structure.variables.render_url import render_url from ....report.structure.variables.render_generic import render_generic from ....report.structure.variables.render_int import render_int

54.1875

72

0.828143

110

867

6.290909

0.163636

0.17341

0.32948

0.485549

0.601156

0.109827

0

0.068051

867

16

73

54.1875

0.856436

0

1

0

true

0

0.75

0

0.75

0

null

0

1

0

null

0

1

0

1

0

1

0

5

4f912920b3cf2a5552ceadf14640e9d27357ffce

65

py

Python

test/Task/ImageSequence/__init__.py

paulondc/chilopoda

046dbb0c1b4ff20ea5f2e1679f8d89f3089b6aa4

[ "MIT" ]

2

2019-09-24T18:56:27.000Z

2021-02-07T04:58:49.000Z

test/Task/ImageSequence/__init__.py

paulondc/kombi

046dbb0c1b4ff20ea5f2e1679f8d89f3089b6aa4

[ "MIT" ]

20

2019-02-16T04:21:13.000Z

2019-03-09T21:21:21.000Z

test/Task/ImageSequence/__init__.py

paulondc/kombi

046dbb0c1b4ff20ea5f2e1679f8d89f3089b6aa4

[ "MIT" ]

3

2019-11-15T05:16:32.000Z

2021-09-28T21:28:29.000Z

from .SequenceThumbnailTaskTest import SequenceThumbnailTaskTest

32.5

64

0.923077

4

65

15

0.75

0

0.061538

65

1

65

0.983607

0

1

0

true

0

1

0

1

0

1

0

1

null

0

1

0

null

0

1

0

1

0

5

96e7d1ddaf507ff49c193f3c3f481b154f3b0eda

13,122

py

Python

test/jpypetest/test_jchar.py

baztian/jpype

034d44e6c719995c25e9cd61348ebc1860030a9b

[ "Apache-2.0" ]

null

test/jpypetest/test_jchar.py

baztian/jpype

034d44e6c719995c25e9cd61348ebc1860030a9b

[ "Apache-2.0" ]

null

test/jpypetest/test_jchar.py

baztian/jpype

034d44e6c719995c25e9cd61348ebc1860030a9b

[ "Apache-2.0" ]

null

import _jpype import jpype import common from jpype.types import * class JChar2TestCase(common.JPypeTestCase): def setUp(self): common.JPypeTestCase.setUp(self) def testCharRange(self): self.assertEqual(ord(str(jpype.JChar(65))), 65) self.assertEqual(ord(str(jpype.JChar(512))), 512) @common.requireInstrumentation def testJPChar_new(self): _jpype.fault("PyJPChar_new") with self.assertRaisesRegex(SystemError, "fault"): JChar("a") _jpype.fault("PyJPModule_getContext") with self.assertRaisesRegex(SystemError, "fault"): JChar("a") JChar("a") @common.requireInstrumentation def testJPChar_str(self): jc = JChar("a") _jpype.fault("PyJPChar_str") with self.assertRaisesRegex(SystemError, "fault"): str(jc) @common.requireInstrumentation def testJCharGetJavaConversion(self): _jpype.fault("JPCharType::findJavaConversion") with self.assertRaisesRegex(SystemError, "fault"): JChar._canConvertToJava(object()) @common.requireInstrumentation def testJPJavaFrameCharArray(self): ja = JArray(JChar)(5) _jpype.fault("JPJavaFrame::NewCharArray") with self.assertRaisesRegex(SystemError, "fault"): JArray(JChar)(1) _jpype.fault("JPJavaFrame::SetCharArrayRegion") with self.assertRaisesRegex(SystemError, "fault"): ja[0] = 0 _jpype.fault("JPJavaFrame::GetCharArrayRegion") with self.assertRaisesRegex(SystemError, "fault"): print(ja[0]) _jpype.fault("JPJavaFrame::GetCharArrayElements") # Special case, only BufferError is allowed from getBuffer with self.assertRaises(BufferError): memoryview(ja[0:3]) _jpype.fault("JPJavaFrame::ReleaseCharArrayElements") with self.assertRaisesRegex(SystemError, "fault"): ja[0:3] = bytes([1, 2, 3]) # Not sure why this one changed. _jpype.fault("JPJavaFrame::ReleaseCharArrayElements") with self.assertRaisesRegex(SystemError, "fault"): jpype.JObject(ja[::2], jpype.JObject) _jpype.fault("JPJavaFrame::ReleaseCharArrayElements") def f(): # Special case no fault is allowed memoryview(ja[0:3]) f() ja = JArray(JChar)(5) # lgtm [py/similar-function] _jpype.fault("JPCharType::setArrayRange") with self.assertRaisesRegex(SystemError, "fault"): ja[1:3] = [0, 0] def testFromObject(self): ja = JArray(JChar)(5) with self.assertRaises(TypeError): ja[1] = object() jf = JClass("jpype.common.Fixture") with self.assertRaises(TypeError): jf.static_char_field = object() with self.assertRaises(TypeError): jf().char_field = object() def testCharArrayAsString(self): t = JClass("jpype.array.TestArray")() v = t.getCharArray() self.assertEqual(str(v), 'avcd') def testArrayConversionChar(self): t = JClass("jpype.array.TestArray")() v = t.getCharArray() self.assertEqual(str(v[:]), 'avcd') def testArrayEqualsChar(self): contents = "abc" array = jpype.JArray(jpype.JChar)(contents) array2 = jpype.JArray(jpype.JChar)(contents) self.assertEqual(array, array) self.assertNotEqual(array, array2) self.assertEqual(array, "abc") def testArrayHash(self): ja = JArray(JByte)([1, 2, 3]) self.assertIsInstance(hash(ja), int) def testNone(self): self.assertEqual(JChar._canConvertToJava(None), "none") class JCharTestCase(common.JPypeTestCase): def setUp(self): common.JPypeTestCase.setUp(self) self.nc = JChar('B') def testStr(self): self.assertEqual(type(str(self.nc)), str) self.assertEqual(str(self.nc), 'B') def testRepr(self): self.assertEqual(type(repr(self.nc)), str) self.assertEqual(repr(self.nc), "'B'") def testOrd(self): self.assertEqual(ord(self.nc), 66) def testInt(self): self.assertEqual(int(self.nc), 66) def testFloat(self): self.assertEqual(float(self.nc), 66.0) def testSub(self): self.assertEqual(len(self.nc), 1) def testHash(self): self.assertEqual(hash(self.nc), hash('B')) def testAdd(self): self.assertEqual(self.nc + 1, 67) self.assertIsInstance(self.nc + 1, int) self.assertEqual(self.nc + 1.1, 67.1) self.assertIsInstance(self.nc + 1.1, float) def testSub(self): self.assertEqual(self.nc - 1, 65) self.assertIsInstance(self.nc - 1, int) self.assertEqual(self.nc - 1.1, 64.9) self.assertIsInstance(self.nc - 1.1, float) def testMult(self): self.assertEqual(self.nc * 2, 132) self.assertIsInstance(self.nc * 2, int) self.assertEqual(self.nc * 0.25, 16.5) self.assertIsInstance(self.nc * 2.0, float) def testRshift(self): self.assertEqual(self.nc >> 1, 33) self.assertIsInstance(self.nc >> 2, int) def testLshift(self): self.assertEqual(self.nc << 1, 132) self.assertIsInstance(self.nc << 2, int) def testAnd(self): self.assertEqual(self.nc & 244, 66 & 244) self.assertIsInstance(self.nc & 2, int) def testOr(self): self.assertEqual(self.nc | 40, 66 | 40) self.assertIsInstance(self.nc | 2, int) def testXor(self): self.assertEqual(self.nc ^ 1, 66 ^ 1) self.assertIsInstance(self.nc ^ 1, int) def testPass(self): fixture = jpype.JClass('jpype.common.Fixture')() self.assertEqual(type(fixture.callChar(self.nc)), JChar) self.assertEqual(type(fixture.callObject(self.nc)), jpype.java.lang.Character) def check(self, u, v0, v1, v2): self.assertEqual(v1, u) self.assertEqual(u, v1) self.assertNotEqual(v0, u) self.assertNotEqual(u, v0) self.assertNotEqual(v2, u) self.assertNotEqual(u, v2) self.assertTrue(u > v0) self.assertFalse(u > v2) self.assertTrue(u < v2) self.assertFalse(u < v0) self.assertTrue(v0 < u) self.assertFalse(v2 < u) self.assertTrue(v2 > u) self.assertFalse(v0 > u) self.assertTrue(u >= v1) self.assertFalse(u >= v2) self.assertTrue(v1 <= u) self.assertFalse(v2 <= u) def testCompareInt(self): self.check(self.nc, 65, 66, 67) def testCompareFloat(self): self.check(self.nc, 65.0, 66.0, 67.0) def testCompareJInt(self): self.check(self.nc, JInt(65), JInt(66), JInt(67)) def testCompareJFloat(self): self.check(self.nc, JFloat(65.0), JFloat(66.0), JFloat(67.0)) class JCharBoxedTestCase(common.JPypeTestCase): def setUp(self): common.JPypeTestCase.setUp(self) self.nc = jpype.java.lang.Character('B') def testStr(self): self.assertEqual(type(str(self.nc)), str) self.assertEqual(str(self.nc), 'B') def testRepr(self): self.assertEqual(type(repr(self.nc)), str) self.assertEqual(repr(self.nc), "'B'") def testOrd(self): self.assertEqual(ord(self.nc), 66) def testInt(self): self.assertEqual(int(self.nc), 66) def testFloat(self): self.assertEqual(float(self.nc), 66.0) def testSub(self): self.assertEqual(len(self.nc), 1) def testHash(self): self.assertEqual(hash(self.nc), hash('B')) def testAdd(self): self.assertEqual(self.nc + 1, 67) self.assertIsInstance(self.nc + 1, int) self.assertEqual(self.nc + 1.1, 67.1) self.assertIsInstance(self.nc + 1.1, float) def testSub(self): self.assertEqual(self.nc - 1, 65) self.assertIsInstance(self.nc - 1, int) self.assertEqual(self.nc - 1.1, 64.9) self.assertIsInstance(self.nc - 1.1, float) def testMult(self): self.assertEqual(self.nc * 2, 132) self.assertIsInstance(self.nc * 2, int) self.assertEqual(self.nc * 0.25, 16.5) self.assertIsInstance(self.nc * 2.0, float) def testRshift(self): self.assertEqual(self.nc >> 1, 33) self.assertIsInstance(self.nc >> 2, int) def testLshift(self): self.assertEqual(self.nc << 1, 132) self.assertIsInstance(self.nc << 2, int) def testAnd(self): self.assertEqual(self.nc & 244, 66 & 244) self.assertIsInstance(self.nc & 2, int) def testOr(self): self.assertEqual(self.nc | 40, 66 | 40) self.assertIsInstance(self.nc | 2, int) def testXor(self): self.assertEqual(self.nc ^ 1, 66 ^ 1) self.assertIsInstance(self.nc ^ 1, int) def testFloorDiv(self): self.assertEqual(self.nc // 3, 66 // 3) self.assertEqual(3 // self.nc, 3 // 66) def testDivMod(self): self.assertEqual(divmod(self.nc, 3), divmod(66, 3)) self.assertEqual(divmod(3, self.nc), divmod(3, 66)) def testInv(self): self.assertEqual(~self.nc, ~66) def testPos(self): self.assertEqual(+self.nc, +66) def testPass(self): fixture = jpype.JClass('jpype.common.Fixture')() self.assertEqual(type(fixture.callObject(self.nc)), type(self.nc)) def check(self, u, v0, v1, v2): self.assertEqual(v1, u) self.assertEqual(u, v1) self.assertNotEqual(v0, u) self.assertNotEqual(u, v0) self.assertNotEqual(v2, u) self.assertNotEqual(u, v2) self.assertTrue(u > v0) self.assertFalse(u > v2) self.assertTrue(u < v2) self.assertFalse(u < v0) self.assertTrue(v0 < u) self.assertFalse(v2 < u) self.assertTrue(v2 > u) self.assertFalse(v0 > u) self.assertTrue(u >= v1) self.assertFalse(u >= v2) self.assertTrue(v1 <= u) self.assertFalse(v2 <= u) def testCompareInt(self): self.check(self.nc, 65, 66, 67) def testCompareFloat(self): self.check(self.nc, 65.0, 66.0, 67.0) def testCompareJInt(self): self.check(self.nc, JInt(65), JInt(66), JInt(67)) def testCompareJFloat(self): self.check(self.nc, JFloat(65.0), JFloat(66.0), JFloat(67.0)) class JCharBoxedNullTestCase(common.JPypeTestCase): def setUp(self): common.JPypeTestCase.setUp(self) self.nc = jpype.JObject(None, jpype.java.lang.Character) def testStr(self): self.assertEqual(type(str(self.nc)), str) self.assertEqual(str(self.nc), 'None') def testRepr(self): self.assertEqual(type(repr(self.nc)), str) self.assertEqual(repr(self.nc), 'None') def testInt(self): with self.assertRaises(TypeError): int(self.nc) def testFloat(self): with self.assertRaises(TypeError): float(self.nc) def testSub(self): with self.assertRaises(TypeError): len(self.nc) def testHash(self): self.assertEqual(hash(self.nc), hash(None)) def testAdd(self): with self.assertRaises(TypeError): self.nc + 1 with self.assertRaises(TypeError): 1 + self.nc def testSub(self): with self.assertRaises(TypeError): self.nc - 1 with self.assertRaises(TypeError): 1 - self.nc def testMult(self): with self.assertRaises(TypeError): self.nc * 1 with self.assertRaises(TypeError): 1 * self.nc def testRshift(self): with self.assertRaises(TypeError): self.nc >> 1 with self.assertRaises(TypeError): 1 >> self.nc def testLshift(self): with self.assertRaises(TypeError): self.nc << 1 with self.assertRaises(TypeError): 1 << self.nc def testAnd(self): with self.assertRaises(TypeError): self.nc & 1 with self.assertRaises(TypeError): 1 & self.nc def testOr(self): with self.assertRaises(TypeError): self.nc | 1 with self.assertRaises(TypeError): 1 | self.nc def testXor(self): with self.assertRaises(TypeError): self.nc ^ 1 with self.assertRaises(TypeError): 1 ^ self.nc def testFloorDiv(self): with self.assertRaises(TypeError): self.nc // 1 with self.assertRaises(TypeError): 1 // self.nc def testDivMod(self): with self.assertRaises(TypeError): divmod(self.nc, 1) with self.assertRaises(TypeError): divmod(1, self.nc) def testInv(self): with self.assertRaises(TypeError): ~self.nc def testPos(self): with self.assertRaises(TypeError): +self.nc def testPass(self): fixture = jpype.JClass('jpype.common.Fixture')() self.assertEqual(fixture.callObject(self.nc), None)

30.658879

86

0.601357

1,556

13,122

5.056555

0.102185

0.086934

0.094179

0.103203

0.77059

0.715048

0.6909

0.653787

0.643493

0.601423

0

0.033796

0.264899

13,122

427

87

30.730679

0.781879

0.011203

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0.710914

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0.04202

0.026908

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0.474926

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0.238938

false

0.00885

0.011799

0

0.262537

0.00295

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null

0

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1

0

1

0

null

0

1

0

1

0

5

8c05b81bf47ea60ca797bd79f44d7a048d6eca52

223

py

Python

examples/load_from_file/main.py

viniciuschiele/configd

f9b405cd2254f79152a13e57e2be907550ef83ed

[ "MIT" ]

3

2017-03-17T15:44:26.000Z

2021-08-31T02:45:52.000Z

examples/load_from_file/main.py

viniciuschiele/configd

f9b405cd2254f79152a13e57e2be907550ef83ed

[ "MIT" ]

1

2017-07-28T23:20:15.000Z

2017-07-29T11:13:49.000Z

examples/load_from_file/main.py

viniciuschiele/configd

f9b405cd2254f79152a13e57e2be907550ef83ed

[ "MIT" ]

2

2021-06-26T20:57:24.000Z

2021-11-21T19:29:39.000Z

from central.config.file import FileConfig config = FileConfig('config.json') config.load() print(config.get('timeout')) print(config.get('database')) print(config.get('database.host')) print(config.get('database.port'))

22.3

42

0.753363

30

223

5.6

0.466667

0.261905

0.333333

0.392857

0

0.06278

223

9

43

24.777778

0.803828

0

0.233184

0

1

0

false

0

0.142857

0

0.142857

0.571429

0

null

1

0

1

0

null

0

1

0

5

8c49e119bd276ab8615c3a7f51eff37f3b42ea1c

100

py

Python

eval/scripts/__init__.py

mbatchkarov/dc_evaluation

83fad49d597952957420b23c0d39c264c581e750

[ "BSD-3-Clause" ]

null

eval/scripts/__init__.py

mbatchkarov/dc_evaluation

83fad49d597952957420b23c0d39c264c581e750

[ "BSD-3-Clause" ]

null

eval/scripts/__init__.py

mbatchkarov/dc_evaluation

83fad49d597952957420b23c0d39c264c581e750

[ "BSD-3-Clause" ]

null

__author__ = 'mmb28' import sys sys.path.append('.') sys.path.append('..') sys.path.append('../..')

16.666667

24

0.63

13

100

4.538462

0.461538

0.355932

0.661017

0.542373

0.661017

0

0.021739

0.08

100

6

24

16.666667

0.619565

0

0.128713

0

1

0

false

0

0.2

0

0.2

0

1

0

null

1

0

1

0

null

0

5

4fdfd1c4ab06f23890420a493923d2a14bf8dc09

102

py

Python

kattis/I've Been Everywhere, Man.py

jaredliw/python-question-bank

9c8c246623d8d171f875700b57772df0afcbdcdf

[ "MIT" ]

1

2021-04-08T07:49:15.000Z

kattis/I've Been Everywhere, Man.py

jaredliw/leetcode-solutions

9c8c246623d8d171f875700b57772df0afcbdcdf

[ "MIT" ]

null

kattis/I've Been Everywhere, Man.py

jaredliw/leetcode-solutions

9c8c246623d8d171f875700b57772df0afcbdcdf

[ "MIT" ]

1

2022-01-23T02:12:24.000Z

# CPU: 0.09 s for _ in range(int(input())): print(len(set(input() for _ in range(int(input())))))

25.5

57

0.598039

18

102

3.277778

0.666667

0.169492

0.338983

0.440678

0.610169

0

0.035294

0.166667

102

3

58

34

0.658824

0.107843

0

1

0

false

0

0.5

1

0

null

0

1

0

1

0

null

0

1

0

5

8b09fd065dd599f9c34e182351ff1d15e47dc20c

117

py

Python

alumni/admin.py

ayushganguli1769/DevelopmentRobotix

1692c104a6f220aa1238840b791aa857a6cc7765

[ "Apache-2.0" ]

null

alumni/admin.py

ayushganguli1769/DevelopmentRobotix

1692c104a6f220aa1238840b791aa857a6cc7765

[ "Apache-2.0" ]

7

2020-02-12T02:54:35.000Z

2022-03-12T00:06:26.000Z

alumni/admin.py

ayushganguli1769/DevelopmentRobotix

1692c104a6f220aa1238840b791aa857a6cc7765

[ "Apache-2.0" ]

6

2020-02-10T16:37:38.000Z

2021-01-28T13:39:46.000Z

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

23.4

32

0.811966

17

117

5.588235

0.647059

0

0.119658

117

4

33

29.25

0.92233

0.222222

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

8b2dde35e62db95e506b03f874b47c0094c23c3a

40

py

Python

cygraphblas/lib/monoid/ss.py

eriknw/cygraphblas

81ae37591ec38aa698d5f37716464a6c366076f9

[ "Apache-2.0" ]

3

2020-09-03T21:47:25.000Z

2021-08-06T20:24:19.000Z

cygraphblas/lib/monoid/ss.py

eriknw/cygraphblas

81ae37591ec38aa698d5f37716464a6c366076f9

[ "Apache-2.0" ]

null

cygraphblas/lib/monoid/ss.py

eriknw/cygraphblas

81ae37591ec38aa698d5f37716464a6c366076f9

[ "Apache-2.0" ]

2

2020-09-03T21:47:52.000Z

2021-08-06T20:24:20.000Z

from cygraphblas_ss.lib.monoid import *

20

39

0.825

6

40

5.333333

1

0

0.1

40

1

40

0.888889

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

8c7091d977c72cdc7883602372339dbcde6de489

256

py

Python

lib/extensions/navigation_buttons_delayed_popup/startup.py

neurodiverseEsoteric/nimbus

a79a37d6001d84116831c9f3f99f5d9acfa7fd19

[ "CC-BY-3.0" ]

3

2015-11-04T10:48:12.000Z

2020-07-12T06:46:27.000Z

lib/extensions/navigation_buttons_delayed_popup/startup.py

esotericDisciple/nimbus

a79a37d6001d84116831c9f3f99f5d9acfa7fd19

[ "CC-BY-3.0" ]

null

lib/extensions/navigation_buttons_delayed_popup/startup.py

esotericDisciple/nimbus

a79a37d6001d84116831c9f3f99f5d9acfa7fd19

[ "CC-BY-3.0" ]

1

2021-05-05T13:56:49.000Z

self.toolBar.widgetForAction(self.backAction).setPopupMode(QToolButton.DelayedPopup) self.toolBar.widgetForAction(self.forwardAction).setPopupMode(QToolButton.DelayedPopup) self.toolBar.widgetForAction(self.upAction).setPopupMode(QToolButton.DelayedPopup)

64

87

0.882813

24

256

9.416667

0.375

0.146018

0.345133

0.39823

0.575221

0

0.011719

256

3

88

85.333333

0.893281

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

5

8c7623c8e92992a9d432cf1310ca2b7d13d8b1c3

1,355

py

Python

code/chapter_04/listing_04_11.py

guinslym/python_earth_science_book

f4dd0115dbbce140c6713989f630a71238daa72c

[ "MIT" ]

80

2021-04-19T10:03:57.000Z

2022-03-30T15:34:47.000Z

code/chapter_04/listing_04_11.py

guinslym/python_earth_science_book

f4dd0115dbbce140c6713989f630a71238daa72c

[ "MIT" ]

null

code/chapter_04/listing_04_11.py

guinslym/python_earth_science_book

f4dd0115dbbce140c6713989f630a71238daa72c

[ "MIT" ]

23

2021-04-25T03:50:07.000Z

2022-03-22T03:06:19.000Z

# Introductory examples name = 'Maurizio' surname = 'Petrelli' print('-------------------------------------------------') print('My name is {}'.format(name)) print('-------------------------------------------------') print('My name is {} and my surname is {}'.format(name, surname)) print('-------------------------------------------------') # Decimal Number formatting PI = 3.14159265358979323846 print('----------------------------------------------------') print("The 2 digit Archimedes' constant is equal to {:.2f}".format(PI)) print("The 3 digit Archimedes' constant is equal to {:.3f}".format(PI)) print("The 4 digit Archimedes' constant is equal to {:.4f}".format(PI)) print("The 5 digit Archimedes' constant is equal to {:.5f}".format(PI)) print('----------------------------------------------------') '''Results ------------------------------------------------- My name is Maurizio ------------------------------------------------- My name is Maurizio and my surname is Petrelli ------------------------------------------------- ---------------------------------------------------- The 2 digit Archimedes' constant is equal to 3.14 The 3 digit Archimedes' constant is equal to 3.142 The 4 digit Archimedes' constant is equal to 3.1416 The 5 digit Archimedes' constant is equal to 3.14159 ---------------------------------------------------- '''

43.709677

71

0.451661

136

1,355

4.5

0.257353

0.196078

0.300654

0.326797

0.535948

0.477124

0.470588

0

0.041565

0.094465

1,355

30

72

45.166667

0.457213

0.034686

0

0.357143

0

0.67979

0.329396

0

1

0

false

0

0.785714

0

null

0

1

0

1

0

1

0

null

0

1

0

5

8c84673cd4c815a8dd356f023b667ff78319d314

868

py

Python

job-orchestrator/tests/transformers/test_model_paths.py

anaai/anaai

fa49ba107e7c6d32aef46796452308334517a224

[ "MIT" ]

31

2022-01-26T21:47:31.000Z

2022-03-21T12:22:39.000Z

job-orchestrator/tests/transformers/test_model_paths.py

anaai/anaai

fa49ba107e7c6d32aef46796452308334517a224

[ "MIT" ]

3

2022-01-24T11:16:05.000Z

2022-01-28T15:11:19.000Z

job-orchestrator/tests/transformers/test_model_paths.py

anaai/anaai

fa49ba107e7c6d32aef46796452308334517a224

[ "MIT" ]

2

2022-02-08T12:07:55.000Z

2022-02-08T19:45:40.000Z

from transformers import model_paths def test_candy_model(): assert model_paths.CANDY_FAST_NEURAL_TRANSFER_MODEL == "models/candy.t7" def test_feathers_model(): assert model_paths.FEATHERS_FAST_NEURAL_TRANSFER_MODEL == "models/feathers.t7" def test_mosaic_model(): assert model_paths.MOSAIC_FAST_NEURAL_TRANSFER_MODEL == "models/mosaic.t7" def test_the_scream_model(): assert model_paths.THE_SCREAM_FAST_NEURAL_TRANSFER_MODEL == "models/the_scream.t7" def test_udnie_model(): assert model_paths.UDNIE_FAST_NEURAL_TRANSFER_MODEL == "models/udnie.t7" def test_celeba_distill_model(): assert model_paths.CELEBA_DISTILL_ANIME_GAN == "models/celeba_distill.pt" def test_face_paint_model(): assert model_paths.FACE_PAINT_ANIME_GAN == "models/face_paint_512_v2.pt" def test_paprika_model(): assert model_paths.PAPRIKA_ANIME_GAN == "models/paprika.pt"

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py

Python

helpers/__init__.py

sspbft/odin

30681d314748523cfbade15fc365510c78bbc711

[ "MIT" ]

null

helpers/__init__.py

sspbft/odin

30681d314748523cfbade15fc365510c78bbc711

[ "MIT" ]

null

helpers/__init__.py

sspbft/odin

30681d314748523cfbade15fc365510c78bbc711

[ "MIT" ]

null

"""Package containing various helpers."""

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py

Python

autograd/__init__.py

mattjj/autograd_tutorial

c32947fbd7f130d791ab1e277a0feed05cb3da5f

[ "MIT" ]

704

2018-01-30T16:41:47.000Z

2022-03-23T02:03:08.000Z

autograd/__init__.py

mattjj/autograd_tutorial

c32947fbd7f130d791ab1e277a0feed05cb3da5f

[ "MIT" ]

6

2018-01-30T20:43:49.000Z

2020-04-27T13:27:08.000Z

autograd/__init__.py

mattjj/autograd_tutorial

c32947fbd7f130d791ab1e277a0feed05cb3da5f

[ "MIT" ]

88

2018-02-03T16:36:54.000Z

2022-02-09T04:21:30.000Z

from .differential_operators import make_vjp, grad

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py

Python

bmcs_beam/mxn/scripts/__init__.py

bmcs-group/bmcs_beam

b53967d0d0461657ec914a3256ec40f9dcff80d5

[ "MIT" ]

1

2021-05-07T11:10:27.000Z

bmcs_beam/mxn/scripts/__init__.py

bmcs-group/bmcs_beam

b53967d0d0461657ec914a3256ec40f9dcff80d5

[ "MIT" ]

null

bmcs_beam/mxn/scripts/__init__.py

bmcs-group/bmcs_beam

b53967d0d0461657ec914a3256ec40f9dcff80d5

[ "MIT" ]

null

''' Created on Dec 18, 2016 @author: rch '''

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16,225

py

Python

sdk/python/pulumi_azure/waf/policy.py

pulumi-bot/pulumi-azure

64d5c30a77b3f4de117068add359ef85293cef8e

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

null

sdk/python/pulumi_azure/waf/policy.py

pulumi-bot/pulumi-azure

64d5c30a77b3f4de117068add359ef85293cef8e

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

null

sdk/python/pulumi_azure/waf/policy.py

pulumi-bot/pulumi-azure

64d5c30a77b3f4de117068add359ef85293cef8e

[ "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 json import warnings import pulumi import pulumi.runtime from typing import Union from .. import utilities, tables class Policy(pulumi.CustomResource): custom_rules: pulumi.Output[list] """ One or more `custom_rules` blocks as defined below. * `action` (`str`) - Type of action. * `matchConditions` (`list`) - One or more `match_conditions` blocks as defined below. * `matchValues` (`list`) - A list of match values. * `matchVariables` (`list`) - One or more `match_variables` blocks as defined below. * `selector` (`str`) - Describes field of the matchVariable collection * `variableName` (`str`) - The name of the Match Variable * `negationCondition` (`bool`) - Describes if this is negate condition or not * `operator` (`str`) - Describes operator to be matched. * `name` (`str`) - Gets name of the resource that is unique within a policy. This name can be used to access the resource. * `priority` (`float`) - Describes priority of the rule. Rules with a lower value will be evaluated before rules with a higher value. * `ruleType` (`str`) - Describes the type of rule. """ location: pulumi.Output[str] """ Resource location. Changing this forces a new resource to be created. """ managed_rules: pulumi.Output[dict] """ A `managed_rules` blocks as defined below. * `exclusions` (`list`) - One or more `exclusion` block defined below. * `matchVariable` (`str`) * `selector` (`str`) - Describes field of the matchVariable collection. * `selectorMatchOperator` (`str`) - Describes operator to be matched. Possible values: `Contains`, `EndsWith`, `Equals`, `EqualsAny`, `StartsWith`. * `managedRuleSets` (`list`) - One or more `managed_rule_set` block defined below. * `ruleGroupOverrides` (`list`) - One or more `rule_group_override` block defined below. * `disabledRules` (`list`) - One or more Rule ID's * `ruleGroupName` (`str`) - The name of the Rule Group * `type` (`str`) - The rule set type. * `version` (`str`) - The rule set version. """ name: pulumi.Output[str] """ The name of the policy. Changing this forces a new resource to be created. """ policy_settings: pulumi.Output[dict] """ A `policy_settings` block as defined below. * `enabled` (`bool`) - Describes if the policy is in enabled state or disabled state Defaults to `Enabled`. * `mode` (`str`) - Describes if it is in detection mode or prevention mode at the policy level Defaults to `Prevention`. """ resource_group_name: pulumi.Output[str] """ The name of the resource group. Changing this forces a new resource to be created. """ tags: pulumi.Output[dict] """ A mapping of tags to assign to the Web Application Firewall Policy. """ def __init__(__self__, resource_name, opts=None, custom_rules=None, location=None, managed_rules=None, name=None, policy_settings=None, resource_group_name=None, tags=None, __props__=None, __name__=None, __opts__=None): """ Manages a Azure Web Application Firewall Policy instance. ## Example Usage ```python import pulumi import pulumi_azure as azure example_resource_group = azure.core.ResourceGroup("exampleResourceGroup", location="West US 2") example_policy = azure.waf.Policy("examplePolicy", resource_group_name=example_resource_group.name, location=example_resource_group.location, custom_rules=[ { "name": "Rule1", "priority": 1, "ruleType": "MatchRule", "match_conditions": [{ "match_variables": [{ "variableName": "RemoteAddr", }], "operator": "IPMatch", "negationCondition": False, "matchValues": [ "192.168.1.0/24", "10.0.0.0/24", ], }], "action": "Block", }, { "name": "Rule2", "priority": 2, "ruleType": "MatchRule", "match_conditions": [ { "match_variables": [{ "variableName": "RemoteAddr", }], "operator": "IPMatch", "negationCondition": False, "matchValues": ["192.168.1.0/24"], }, { "match_variables": [{ "variableName": "RequestHeaders", "selector": "UserAgent", }], "operator": "Contains", "negationCondition": False, "matchValues": ["Windows"], }, ], "action": "Block", }, ], policy_settings={ "enabled": True, "mode": "Prevention", }, managed_rules={ "exclusion": [ { "matchVariable": "RequestHeaderNames", "selector": "x-company-secret-header", "selectorMatchOperator": "Equals", }, { "matchVariable": "RequestCookieNames", "selector": "too-tasty", "selectorMatchOperator": "EndsWith", }, ], "managed_rule_set": [{ "type": "OWASP", "version": "3.1", "rule_group_override": [{ "ruleGroupName": "REQUEST-920-PROTOCOL-ENFORCEMENT", "disabledRules": [ "920300", "920440", ], }], }], }) ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[list] custom_rules: One or more `custom_rules` blocks as defined below. :param pulumi.Input[str] location: Resource location. Changing this forces a new resource to be created. :param pulumi.Input[dict] managed_rules: A `managed_rules` blocks as defined below. :param pulumi.Input[str] name: The name of the policy. Changing this forces a new resource to be created. :param pulumi.Input[dict] policy_settings: A `policy_settings` block as defined below. :param pulumi.Input[str] resource_group_name: The name of the resource group. Changing this forces a new resource to be created. :param pulumi.Input[dict] tags: A mapping of tags to assign to the Web Application Firewall Policy. The **custom_rules** object supports the following: * `action` (`pulumi.Input[str]`) - Type of action. * `matchConditions` (`pulumi.Input[list]`) - One or more `match_conditions` blocks as defined below. * `matchValues` (`pulumi.Input[list]`) - A list of match values. * `matchVariables` (`pulumi.Input[list]`) - One or more `match_variables` blocks as defined below. * `selector` (`pulumi.Input[str]`) - Describes field of the matchVariable collection * `variableName` (`pulumi.Input[str]`) - The name of the Match Variable * `negationCondition` (`pulumi.Input[bool]`) - Describes if this is negate condition or not * `operator` (`pulumi.Input[str]`) - Describes operator to be matched. * `name` (`pulumi.Input[str]`) - Gets name of the resource that is unique within a policy. This name can be used to access the resource. * `priority` (`pulumi.Input[float]`) - Describes priority of the rule. Rules with a lower value will be evaluated before rules with a higher value. * `ruleType` (`pulumi.Input[str]`) - Describes the type of rule. The **managed_rules** object supports the following: * `exclusions` (`pulumi.Input[list]`) - One or more `exclusion` block defined below. * `matchVariable` (`pulumi.Input[str]`) * `selector` (`pulumi.Input[str]`) - Describes field of the matchVariable collection. * `selectorMatchOperator` (`pulumi.Input[str]`) - Describes operator to be matched. Possible values: `Contains`, `EndsWith`, `Equals`, `EqualsAny`, `StartsWith`. * `managedRuleSets` (`pulumi.Input[list]`) - One or more `managed_rule_set` block defined below. * `ruleGroupOverrides` (`pulumi.Input[list]`) - One or more `rule_group_override` block defined below. * `disabledRules` (`pulumi.Input[list]`) - One or more Rule ID's * `ruleGroupName` (`pulumi.Input[str]`) - The name of the Rule Group * `type` (`pulumi.Input[str]`) - The rule set type. * `version` (`pulumi.Input[str]`) - The rule set version. The **policy_settings** object supports the following: * `enabled` (`pulumi.Input[bool]`) - Describes if the policy is in enabled state or disabled state Defaults to `Enabled`. * `mode` (`pulumi.Input[str]`) - Describes if it is in detection mode or prevention mode at the policy level Defaults to `Prevention`. """ if __name__ is not None: warnings.warn("explicit use of __name__ is deprecated", DeprecationWarning) resource_name = __name__ if __opts__ is not None: warnings.warn("explicit use of __opts__ is deprecated, use 'opts' instead", DeprecationWarning) opts = __opts__ if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = dict() __props__['custom_rules'] = custom_rules __props__['location'] = location if managed_rules is None: raise TypeError("Missing required property 'managed_rules'") __props__['managed_rules'] = managed_rules __props__['name'] = name __props__['policy_settings'] = policy_settings if resource_group_name is None: raise TypeError("Missing required property 'resource_group_name'") __props__['resource_group_name'] = resource_group_name __props__['tags'] = tags super(Policy, __self__).__init__( 'azure:waf/policy:Policy', resource_name, __props__, opts) @staticmethod def get(resource_name, id, opts=None, custom_rules=None, location=None, managed_rules=None, name=None, policy_settings=None, resource_group_name=None, tags=None): """ Get an existing Policy resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param str id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[list] custom_rules: One or more `custom_rules` blocks as defined below. :param pulumi.Input[str] location: Resource location. Changing this forces a new resource to be created. :param pulumi.Input[dict] managed_rules: A `managed_rules` blocks as defined below. :param pulumi.Input[str] name: The name of the policy. Changing this forces a new resource to be created. :param pulumi.Input[dict] policy_settings: A `policy_settings` block as defined below. :param pulumi.Input[str] resource_group_name: The name of the resource group. Changing this forces a new resource to be created. :param pulumi.Input[dict] tags: A mapping of tags to assign to the Web Application Firewall Policy. The **custom_rules** object supports the following: * `action` (`pulumi.Input[str]`) - Type of action. * `matchConditions` (`pulumi.Input[list]`) - One or more `match_conditions` blocks as defined below. * `matchValues` (`pulumi.Input[list]`) - A list of match values. * `matchVariables` (`pulumi.Input[list]`) - One or more `match_variables` blocks as defined below. * `selector` (`pulumi.Input[str]`) - Describes field of the matchVariable collection * `variableName` (`pulumi.Input[str]`) - The name of the Match Variable * `negationCondition` (`pulumi.Input[bool]`) - Describes if this is negate condition or not * `operator` (`pulumi.Input[str]`) - Describes operator to be matched. * `name` (`pulumi.Input[str]`) - Gets name of the resource that is unique within a policy. This name can be used to access the resource. * `priority` (`pulumi.Input[float]`) - Describes priority of the rule. Rules with a lower value will be evaluated before rules with a higher value. * `ruleType` (`pulumi.Input[str]`) - Describes the type of rule. The **managed_rules** object supports the following: * `exclusions` (`pulumi.Input[list]`) - One or more `exclusion` block defined below. * `matchVariable` (`pulumi.Input[str]`) * `selector` (`pulumi.Input[str]`) - Describes field of the matchVariable collection. * `selectorMatchOperator` (`pulumi.Input[str]`) - Describes operator to be matched. Possible values: `Contains`, `EndsWith`, `Equals`, `EqualsAny`, `StartsWith`. * `managedRuleSets` (`pulumi.Input[list]`) - One or more `managed_rule_set` block defined below. * `ruleGroupOverrides` (`pulumi.Input[list]`) - One or more `rule_group_override` block defined below. * `disabledRules` (`pulumi.Input[list]`) - One or more Rule ID's * `ruleGroupName` (`pulumi.Input[str]`) - The name of the Rule Group * `type` (`pulumi.Input[str]`) - The rule set type. * `version` (`pulumi.Input[str]`) - The rule set version. The **policy_settings** object supports the following: * `enabled` (`pulumi.Input[bool]`) - Describes if the policy is in enabled state or disabled state Defaults to `Enabled`. * `mode` (`pulumi.Input[str]`) - Describes if it is in detection mode or prevention mode at the policy level Defaults to `Prevention`. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = dict() __props__["custom_rules"] = custom_rules __props__["location"] = location __props__["managed_rules"] = managed_rules __props__["name"] = name __props__["policy_settings"] = policy_settings __props__["resource_group_name"] = resource_group_name __props__["tags"] = tags return Policy(resource_name, opts=opts, __props__=__props__) def translate_output_property(self, prop): return tables._CAMEL_TO_SNAKE_CASE_TABLE.get(prop) or prop def translate_input_property(self, prop): return tables._SNAKE_TO_CAMEL_CASE_TABLE.get(prop) or prop

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5080d44c3782fcef3563b3dbf70986c2e7c13739

283

py

Python

test_mersenne.py

Crulzor/algorithms-python-intro-ex

b3c10eff978a2f0f20e41c6d5aba24746ec07076

[ "Apache-2.0" ]

null

test_mersenne.py

Crulzor/algorithms-python-intro-ex

b3c10eff978a2f0f20e41c6d5aba24746ec07076

[ "Apache-2.0" ]

null

test_mersenne.py

Crulzor/algorithms-python-intro-ex

b3c10eff978a2f0f20e41c6d5aba24746ec07076

[ "Apache-2.0" ]

null

from mersenne import generatePotentialMP, isPrime def test_generatePotentialMP(): assert(generatePotentialMP(2) == 3) assert(generatePotentialMP(1) ==1) def test_isPrime(): assert(isPrime(7)) assert(isPrime(2)) assert(isPrime(3)) assert(isPrime(4) == False)

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50bd37ee8461876376290a970632ede83e07fe93

183

py

Python

set.py

git4satya/koleksyon

966f3f6ea16a9c5c0bb12d2aec52c5c89e42090c

[ "MIT" ]

null

set.py

git4satya/koleksyon

966f3f6ea16a9c5c0bb12d2aec52c5c89e42090c

[ "MIT" ]

null

set.py

git4satya/koleksyon

966f3f6ea16a9c5c0bb12d2aec52c5c89e42090c

[ "MIT" ]

null

from setuptools import setup, find_packages from distutils.core import setup from Cython.Build import cythonize setup(name="mcmc", ext_modules=cythonize("./src/koleksyon/mcmc.pyx"))

30.5

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50f6582522a07cfc18e387853c08f5bffb83bbd5

120

py

Python

src/som/vm/current.py

SOM-st/PySOM

65ef72f44252439b724a7429408dac7f8d1b1d98

[ "MIT" ]

22

2015-10-29T05:11:06.000Z

2022-03-01T11:18:45.000Z

src/som/vm/current.py

smarr/PySOM

65ef72f44252439b724a7429408dac7f8d1b1d98

[ "MIT" ]

16

2021-03-07T22:09:33.000Z

2021-08-24T12:36:15.000Z

src/som/vm/current.py

SOM-st/PySOM

65ef72f44252439b724a7429408dac7f8d1b1d98

[ "MIT" ]

5

2015-01-02T03:51:29.000Z

2020-10-02T07:05:46.000Z

def _init(): from som.vm.universe import create_universe return create_universe() current_universe = _init()

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0faef4c43d66c9f68163503158caeb67ad86c96d

386

py

Python

planner/progression/__init__.py

cyclone923/pyplanners

e2fe156ff00d0914cfb4f20afed158706f4d5d28

[ "MIT" ]

null

planner/progression/__init__.py

cyclone923/pyplanners

e2fe156ff00d0914cfb4f20afed158706f4d5d28

[ "MIT" ]

null

planner/progression/__init__.py

cyclone923/pyplanners

e2fe156ff00d0914cfb4f20afed158706f4d5d28

[ "MIT" ]

null

from .hill_climbing import hill_climbing_search, strategies from .best_first import path_cost_fn, greedy_cost_fn, weighted_cost_fn, macro_greedy_cost_fn, \ a_star_search, best_first_search, deferred_best_first_search, macro_deferred_best_first_search, semideferred_best_first_search from .simple import dfs, bfs, srandom_walk, srrt from .recurrent import rdfs, rbfs, random_walk, rrt

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0fc20baeb9198c74f7c0542feb89fb8850d4a334

401

py

Python

vkwave/vkscript/__init__.py

krasnovmv/vkwave

e0db86cc16f97797765aadfb811ec87ff7945b1f

[ "MIT" ]

222

2020-03-30T18:09:20.000Z

2022-03-27T18:25:04.000Z

vkwave/vkscript/__init__.py

krasnovmv/vkwave

e0db86cc16f97797765aadfb811ec87ff7945b1f

[ "MIT" ]

62

2020-03-30T18:31:25.000Z

2021-12-21T17:00:44.000Z

vkwave/vkscript/__init__.py

krasnovmv/vkwave

e0db86cc16f97797765aadfb811ec87ff7945b1f

[ "MIT" ]

91

2020-03-30T18:34:49.000Z

2022-03-23T12:58:49.000Z

import vkwave.vkscript.handlers.assignments import vkwave.vkscript.handlers.blocks import vkwave.vkscript.handlers.calls import vkwave.vkscript.handlers.expressions import vkwave.vkscript.handlers.statements import vkwave.vkscript.handlers.types from .converter import VKScriptConverter from .execute import Execute from .execute import execute __all__ = ("execute", "Execute", "VKScriptConverter")

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null

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5

e8709f79e317a9c7cd2146a4a0c28214ab5b7958

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py

Python

tccli/services/wss/v20180426/__init__.py

zyh911/tencentcloud-cli

dfc5dbd660d4c60d265921c4edc630091478fc41

[ "Apache-2.0" ]

null

tccli/services/wss/v20180426/__init__.py

zyh911/tencentcloud-cli

dfc5dbd660d4c60d265921c4edc630091478fc41

[ "Apache-2.0" ]

null

tccli/services/wss/v20180426/__init__.py

zyh911/tencentcloud-cli

dfc5dbd660d4c60d265921c4edc630091478fc41

[ "Apache-2.0" ]

null

version = "2018-04-26"

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e87e61caeabea7a4911a24a31a3d383ae4ecb968

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py

Python

Server/myLibrary/admin.py

sepehrNorouzi/SemUniLib

dffeeb769ce5da4fb45a83d1792ec24adbb866e9

[ "MIT" ]

null

Server/myLibrary/admin.py

sepehrNorouzi/SemUniLib

dffeeb769ce5da4fb45a83d1792ec24adbb866e9

[ "MIT" ]

null

Server/myLibrary/admin.py

sepehrNorouzi/SemUniLib

dffeeb769ce5da4fb45a83d1792ec24adbb866e9

[ "MIT" ]

null

from django.contrib import admin from .models import Book, Favorite admin.site.register(Book) admin.site.register(Favorite)

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e89384cd4e1e1e1278f38d2fac8d56157408b3f2

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py

Python

src/bert_summarizer/data/__init__.py

k-tahiro/bert-summarizer

03a09676130e4706b42ba6ab53c545fd10b84bce

[ "MIT" ]

8

2020-10-05T02:34:40.000Z

2021-11-29T01:38:41.000Z

src/bert_summarizer/data/__init__.py

k-tahiro/bert-summarizer

03a09676130e4706b42ba6ab53c545fd10b84bce

[ "MIT" ]

5

2021-04-01T07:15:26.000Z

2022-03-15T02:48:18.000Z

src/bert_summarizer/data/__init__.py

k-tahiro/bert-summarizer

03a09676130e4706b42ba6ab53c545fd10b84bce

[ "MIT" ]

2

2021-09-30T09:10:55.000Z

2022-01-29T03:05:46.000Z

from .data_collator import ( DataCollatorWithPaddingWithAdditionalFeatures, EncoderDecoderDataCollatorWithPadding, ) from .datasets import *

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5

e8cf1815da91e995a850a952f368039cd746e5df

89

py

Python

src/UQpy/surrogates/kriging/correlation_models/baseclass/__init__.py

SURGroup/UncertaintyQuantification

a94c8db47d07134ea2b3b0a3ca53ca818532c3e6

[ "MIT" ]

null

src/UQpy/surrogates/kriging/correlation_models/baseclass/__init__.py

SURGroup/UncertaintyQuantification

a94c8db47d07134ea2b3b0a3ca53ca818532c3e6

[ "MIT" ]

null

src/UQpy/surrogates/kriging/correlation_models/baseclass/__init__.py

SURGroup/UncertaintyQuantification

a94c8db47d07134ea2b3b0a3ca53ca818532c3e6

[ "MIT" ]

null

from UQpy.surrogates.kriging.correlation_models.baseclass.Correlation import Correlation

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5

e8d1a1267a50a6e4e81cbb82affa3e724bd9c390

841

py

Python

src/losses.py

saman-codes/dldojo

9fd828f1902ba3d46e9bb5f554ef37d07335b29e

[ "MIT" ]

null

src/losses.py

saman-codes/dldojo

9fd828f1902ba3d46e9bb5f554ef37d07335b29e

[ "MIT" ]

null

src/losses.py

saman-codes/dldojo

9fd828f1902ba3d46e9bb5f554ef37d07335b29e

[ "MIT" ]

null

import numpy as np class Loss(): def output_gradient(self): return class MSE(Loss): def __call__(self, predicted, labels): return 0.5 * np.square(predicted - labels) def output_gradient(self, predicted, labels): return predicted - labels class BinaryCrossEntropy(Loss): def __call__(self, predicted, labels): return - np.nan_to_num((labels*np.log(predicted) + (1-labels)*np.log(1-predicted))) def output_gradient(self, predicted, labels): return np.nan_to_num(-(labels/predicted) + (1-labels)/(1-predicted)) class CategoricalCrossEntropy(Loss): def __call__(self, predicted, labels): return -np.nan_to_num(np.sum(labels*np.log(predicted), axis=0, keepdims=True)) def output_gradient(self, predicted, labels): return -np.nan_to_num(labels/predicted)

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null

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5

2ce777497859d2197b79ee44dcd351d14e88fcd2

172

py

Python

scripts/item/consume_2434951.py

Snewmy/swordie

ae01ed4ec0eb20a18730e8cd209eea0b84a8dd17

[ "MIT" ]

null

scripts/item/consume_2434951.py

Snewmy/swordie

ae01ed4ec0eb20a18730e8cd209eea0b84a8dd17

[ "MIT" ]

null

scripts/item/consume_2434951.py

Snewmy/swordie

ae01ed4ec0eb20a18730e8cd209eea0b84a8dd17

[ "MIT" ]

null

# Soft-serve Damage Skin success = sm.addDamageSkin(2434951) if success: sm.chat("The Soft-serve Damage Skin has been added to your account's damage skin collection.")

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null

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5

2cf7ede7519b76677c68ab0cf790c978c3c5cc8f

203

py

Python

genda/formats/__init__.py

jeffhsu3/genda

5adbb5b5620c592849fa4a61126b934e1857cd77

[ "BSD-3-Clause" ]

5

2016-01-12T15:12:18.000Z

2022-02-10T21:57:39.000Z

genda/formats/__init__.py

jeffhsu3/genda

5adbb5b5620c592849fa4a61126b934e1857cd77

[ "BSD-3-Clause" ]

5

2015-01-20T04:22:50.000Z

2018-10-02T19:39:12.000Z

genda/formats/__init__.py

jeffhsu3/genda

5adbb5b5620c592849fa4a61126b934e1857cd77

[ "BSD-3-Clause" ]

1

2022-03-04T06:49:39.000Z

""" Formats submodule contains classes and functions to parse various formats into pandas dataframes as well as lookup utilities to various formats """ from .gene_utils import * from .panVCF import VCF

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1

0

5

2cffde54fce64df2346d3c12e08ed04887efeb6d

129

py

Python

build/ARM/arch/arm/ArmSemihosting.py

zhoushuxin/impl_of_HPCA2018

594d807fb0c0712bb7766122c4efe3321d012687

[ "BSD-3-Clause" ]

5

2019-12-12T16:26:09.000Z

2022-03-17T03:23:33.000Z

build/ARM/arch/arm/ArmSemihosting.py

zhoushuxin/impl_of_HPCA2018

594d807fb0c0712bb7766122c4efe3321d012687

[ "BSD-3-Clause" ]

null

build/ARM/arch/arm/ArmSemihosting.py

zhoushuxin/impl_of_HPCA2018

594d807fb0c0712bb7766122c4efe3321d012687

[ "BSD-3-Clause" ]

null

version https://git-lfs.github.com/spec/v1 oid sha256:60c08155c02f8c1321979a81a67a2ef5a0bc292b2d26a9e5be7e6e1cb484e248 size 2756

32.25

75

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1

0

1

0

null

1

0

1

0

5

d74be0e6efcefb06e3529cae5316490cf81fffce

130

py

Python

fmojinja/awk/__main__.py

Taro-Imahiro/fmojinja

5b2c4100e25bd198b1cf8ed44b37b1c4bb93d2ee

[ "MIT" ]

null

fmojinja/awk/__main__.py

Taro-Imahiro/fmojinja

5b2c4100e25bd198b1cf8ed44b37b1c4bb93d2ee

[ "MIT" ]

13

2021-07-06T07:03:58.000Z

2021-11-22T15:25:22.000Z

fmojinja/awk/__main__.py

Taro-Imahiro/fmojinja

5b2c4100e25bd198b1cf8ed44b37b1c4bb93d2ee

[ "MIT" ]

3

2021-06-26T19:40:34.000Z

2021-09-15T04:24:21.000Z

from ..mixin import SubCommands from .pdb_reformer import PdbReformer SubCommands.main_proc({ "pdb_reformer": PdbReformer })

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null

0

1

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1

0

5

d782321c51f6868ecf0aeda657d36d93a32a2794

18,087

py

Python

tests/engine/test_error_handling.py

vanguard/sql_translate

28ae149e54a300c3337b538691be80d878a7dbf2

[ "Apache-2.0" ]

3

2021-03-19T21:39:29.000Z

2021-03-26T14:00:24.000Z

tests/engine/test_error_handling.py

vanguard/sql_translate

28ae149e54a300c3337b538691be80d878a7dbf2

[ "Apache-2.0" ]

1

2021-07-07T11:45:04.000Z

tests/engine/test_error_handling.py

vanguard/sql_translate

28ae149e54a300c3337b538691be80d878a7dbf2

[ "Apache-2.0" ]

null

import unittest import pytest import sqlparse from sql_translate.engine import error_handling from typing import Dict, List import re E = error_handling._ErrorHandler() # Just for coverage @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("select cast(a as integer)", "line 1:8: Cannot cast timestamp to integer (1)", "select to_unixtime(a)"), ("select cast(a as integer) as a", "line 1:8: Cannot cast timestamp to integer (1)", "select to_unixtime(a) AS a") ]) def test_cast_timestamp_to_epoch(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._cast_timestamp_to_epoch] assert ErrorHandlerHiveToPresto._cast_timestamp_to_epoch(statement, re.search(pattern[0], error_message)) == expected @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("select 1 in (select '1')", "line 1:10: value and result of subquery must be of the same type for IN expression: integer vs varchar (1)", "select cast(1 AS varchar) in (select '1')") ]) def test_cast_in_subquery(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._cast_in_subquery] assert ErrorHandlerHiveToPresto._cast_in_subquery(statement, re.search(pattern[0], error_message)) == expected @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("select coalesce('1', 1)", "line 1:22: All COALESCE operands must be the same type: varchar (1)", "select coalesce('1', cast(1 AS varchar))") ]) def test_coalesce_statements(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._coalesce_statements] assert ErrorHandlerHiveToPresto._coalesce_statements(statement, re.search(pattern[0], error_message)) == expected @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("select case when true then 'a' else 1 end", "line 1:37: All CASE results must be the same type: varchar (1)", "select case when true then 'a' else cast(1 AS varchar) end") ]) def test_case_statements(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._case_statements] assert ErrorHandlerHiveToPresto._case_statements(statement, re.search(pattern[0], error_message)) == expected @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("select a \nfrom cte\nwhere a in ( \n 1, 2, 3)", "line 4:2: IN value and list items must be the same type: bigint (1)", "select a \nfrom cte\nwhere cast(a AS bigint) in ( \n 1, 2, 3)"), ("select a \nfrom cte\nwhere a in (1.1, 2.3, 3.1)", "line 3:13: IN value and list items must be the same type: float (1)", "select a \nfrom cte\nwhere cast(a AS double) in (1.1, 2.3, 3.1)"), ("select a \nfrom cte\nwhere a in ('1', '2', '3')", "line 3:13: IN value and list items must be the same type: varchar (1)", "select a \nfrom cte\nwhere cast(a AS varchar) in ('1', '2', '3')"), ("select a \nfrom cte\nwhere a in ('1')", "line 3:13: IN value and list items must be the same type: varchar (1)", "select a \nfrom cte\nwhere cast(a AS varchar) in ('1')") ]) def test_cast_in(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._cast_in] assert ErrorHandlerHiveToPresto._cast_in(statement, re.search(pattern[0], error_message)) == expected @pytest.mark.parametrize(['statement', 'error_message'], [ ("select a \nfrom cte\nwhere a in ( \n 1, '2', 3)", "line 4:2: IN value and list items must be the same type: bigint (1)") ]) def test_cast_in_ValueError(statement: str, error_message: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._cast_in] with pytest.raises(ValueError): ErrorHandlerHiveToPresto._cast_in(statement, re.search(pattern[0], error_message)) @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("select cast(a as integer) from cte", "line 1:8: Cannot cast char(10) to integer (1)", "select cast(trim(cast(a AS varchar)) AS integer) from cte"), ("select a from cte", "line 1:8: Cannot cast bigint to integer (1)", "select a from cte") ]) def test_cannot_cast_to_type(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._cannot_cast_to_type] assert ErrorHandlerHiveToPresto._cannot_cast_to_type(statement, re.search(pattern[0], error_message)) == expected @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("select a from cte where b between c and d", "line 1:27: Cannot check if varchar is BETWEEN varchar and date (1)", "select a from cte where b between c and cast(d AS varchar)"), ("select a from cte where b between c and d", "line 1:27: Cannot check if double is BETWEEN double and date (1)", "select a from cte where cast(b AS varchar) between cast(c AS varchar) and cast(d AS varchar)") ]) def test_between(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._between] assert ErrorHandlerHiveToPresto._between(statement, re.search(pattern[0], error_message)) == expected @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("select a from db.vcte", # Table name start with v --> try with "t" as this could be a view "Table 'db.vcte' not found (1)", "select a from db.tcte"), ("select a from db.cte", "Table 'db.cte' not found (1)", "select a from db.cte_presto") # Table name does not start with v ]) def test_table_not_found(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._table_not_found] assert ErrorHandlerHiveToPresto._table_not_found(statement, re.search(pattern[0], error_message)) == expected @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("select concat(1, '1') from b inner join c\n ON a.my_col=b.another_col\nwhere d=e", "line 1:8: Unexpected parameters (bigint, varchar) for function concat (1)", "select concat(cast(1 AS varchar), cast('1' AS varchar)) from b inner join c\n ON a.my_col=b.another_col\nwhere d=e"), ("select concat(max(1), '1') from b inner join c\n ON a.my_col=b.another_col\nwhere d=e", "line 1:8: Unexpected parameters (bigint, varchar) for function concat (1)", "select concat(cast(max(1) AS varchar), cast('1' AS varchar)) from b inner join c\n ON a.my_col=b.another_col\nwhere d=e") ]) def test_unexpected_parameters(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._unexpected_parameters] assert ErrorHandlerHiveToPresto._unexpected_parameters(statement, re.search(pattern[0], error_message)) == expected @pytest.mark.parametrize(['statement', 'error_message'], [ ("select something(1, '1') from b inner join c\n ON a.my_col=b.another_col\nwhere d=e", "line 1:8: Unexpected parameters (bigint, varchar) for function something (1)"), ("select concat(a - b, a or b) from b inner join c\n ON a.my_col=b.another_col\nwhere d=e", "line 1:8: Unexpected parameters (bigint, varchar) for function concat (1)") ]) def test_unexpected_parameters_NotImplementedError(statement: str, error_message: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._unexpected_parameters] with pytest.raises(NotImplementedError): ErrorHandlerHiveToPresto._unexpected_parameters(statement, re.search(pattern[0], error_message)) @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("select 'a' =1", "line 1:12: '=' cannot be applied to varchar, bigint (1)", "select 'a' =cast(1 AS varchar)"), ("select 'a' >1", "line 1:12: '>' cannot be applied to varchar, bigint (1)", "select 'a' >cast(1 AS varchar)"), ("select 'a' <1", "line 1:12: '<' cannot be applied to varchar, bigint (1)", "select 'a' <cast(1 AS varchar)"), ("select 'a' >=1", "line 1:12: '>=' cannot be applied to varchar, bigint (1)", "select 'a' >=cast(1 AS varchar)"), ("select 'a' <=1", "line 1:12: '<=' cannot be applied to varchar, bigint (1)", "select 'a' <=cast(1 AS varchar)"), ("select 'a' !=1", "line 1:12: '!=' cannot be applied to varchar, bigint (1)", "select 'a' !=cast(1 AS varchar)"), ("select a from b inner join c\n ON a.my_col=b.another_col\nwhere d=e", "line 2:18: '=' cannot be applied to bigint, varchar (1)", "select a from b inner join c\n ON cast(a.my_col AS varchar)=b.another_col\nwhere d=e"), ("select a from b inner join c\n ON a.my_col=b.another_col\nwhere d=e", "line 2:18: '=' cannot be applied to date, timestamp (1)", "select a from b inner join c\n ON cast(a.my_col AS varchar)=cast(b.another_col AS varchar)\nwhere d=e"), ("select a\nfrom b\nwhere cast(event_date AS varchar)>='2021-01-21' AND event_date<='2021-01-23'", "line 3:63: '<=' cannot be applied to date, varchar(10) (1)", "select a\nfrom b\nwhere cast(event_date AS varchar)>='2021-01-21' AND cast(event_date AS varchar)<='2021-01-23'") ]) def test_cast_both_sides(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._cast_both_sides] assert ErrorHandlerHiveToPresto._cast_both_sides(statement, re.search(pattern[0], error_message)) == expected @pytest.mark.parametrize(['statement', 'table_properties', 'expected'], [ ("with cte AS (select b from cte2) select b from cte", {"columns": {"b": "bigint"}}, "with cte AS (select b from cte2) SELECT\nb\nfrom cte"), # No wildcard ("with cte AS (select b from cte2) select count(*) as b from cte", {"columns": {"b": "bigint"}}, "with cte AS (select b from cte2) SELECT\ncount(*) AS b\nfrom cte"), # No wildcard ("with cte AS (select b from cte2) select * from cte", {"columns": {"c": "bigint", "d": "bigint", "e": "bigint", "a": "bigint"}}, "with cte AS (select b from cte2) SELECT\nc,\nd,\ne,\na\nfrom cte"), # select * ("with cte AS (select b from cte2) select a.*, c as d from cte", # Wildcard then regular column {"columns": {"b": "bigint", "d": "varchar"}}, "with cte AS (select b from cte2) SELECT\nb,\nc AS d\nfrom cte"), ("with cte AS (select b from cte2) select c as d, * from cte", # regular column then wildcard {"columns": {"b": "bigint", "d": "varchar"}}, "with cte AS (select b from cte2) SELECT\nc AS d,\nb\nfrom cte"), ("with cte AS (select b, c from cte2) select foo(a) as d, *, cte.a, `hey yo` from cte", # Wildcard in the middle bringing 2+ columns in {"columns": {"a": "bigint", "c": "varchar", "some thing": "varchar", "d": "varchar", "hey yo": "varchar"}}, "with cte AS (select b, c from cte2) SELECT\nfoo(a) AS d,\nc,\n`some thing`,\ncte.a,\n`hey yo`\nfrom cte") # Final column order is not sorted by * replacement is ]) def test_expand_wildcards(statement: str, table_properties: Dict[str, str], expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() assert ErrorHandlerHiveToPresto._expand_wildcards(statement, table_properties) == expected @pytest.mark.parametrize(['statement', 'table_properties'], [ ("with cte AS (select b from cte2) select *, cte.* from cte", {"columns": {"b": "bigint"}}) # Double wildcard ]) def test_expand_wildcards_ValueError(statement: str, table_properties: Dict[str, str]) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() with pytest.raises(ValueError): ErrorHandlerHiveToPresto._expand_wildcards(statement, table_properties) @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("""with abc AS ( SELECT b FROM c GROUP BY b) SELECT d, e, f, g, CURRENT_DATE AS hhh FROM abc a LEFT JOIN def b ON a.b = b.b""", "Mismatch at column 2: 'e' is of type bigint but expression is of type double (1)", """with abc AS ( SELECT b FROM c GROUP BY b) SELECT d, cast(e AS bigint) AS e, f, g, CURRENT_DATE AS hhh FROM abc a LEFT JOIN def b ON a.b = b.b""" ), ("select name.my_col a from b inner join c\n ON name.my_col=b.another_col\nwhere d=e", "Mismatch at column 1: 'my_col' is of type char(1) but expression is of type smallint (1)", "SELECT\ncast(cast(name.my_col AS varchar) AS char(1)) AS a\nfrom b inner join c\n ON name.my_col=b.another_col\nwhere d=e"), ("select name.my_col a from b inner join c\n ON name.my_col=b.another_col\nwhere d=e", "Mismatch at column 1: 'my_col' is of type varchar but expression is of type char(1) (1)", "SELECT\ncast(name.my_col AS varchar) AS a\nfrom b inner join c\n ON name.my_col=b.another_col\nwhere d=e"), ("select name.my_col from b inner join c\n ON name.my_col=b.another_col\nwhere d=e", "Mismatch at column 1: 'my_col' is of type varchar but expression is of type char(1) (1)", "SELECT\ncast(name.my_col AS varchar) AS my_col\nfrom b inner join c\n ON name.my_col=b.another_col\nwhere d=e"), ("with abc as (select name.my_col from b inner join c\n ON name.my_col=b.another_col\nwhere d=e) select j.my_col, k.my_col from abc", "Mismatch at column 2: 'my_col' is of type varchar but expression is of type char(1) (1)", "with abc as (select name.my_col from b inner join c\n ON name.my_col=b.another_col\nwhere d=e) SELECT\nj.my_col,\ncast(k.my_col AS varchar) AS my_col\nfrom abc"), ("with abc as (select name.my_col from b inner join c\n ON name.my_col=b.another_col\nwhere d=e) select my_col, case when a=1 then 'Y' else 'N' end from abc", "Mismatch at column 2: 'unknown_col' is of type varchar but expression is of type char(1) (1)", "with abc as (select name.my_col from b inner join c\n ON name.my_col=b.another_col\nwhere d=e) SELECT\nmy_col,\ncast(case when a=1 then 'Y' else 'N' end AS varchar) AS unknown_col\nfrom abc"), ("with abc as (select name.my_col from b inner join c\n ON name.my_col=b.another_col\nwhere d=e) select my_col, concat('a', max('b')) as c, k.my_col from abc", "Mismatch at column 2: 'c' is of type varchar but expression is of type bigint (1)", "with abc as (select name.my_col from b inner join c\n ON name.my_col=b.another_col\nwhere d=e) SELECT\nmy_col,\ncast(concat('a', max('b')) AS varchar) AS c,\nk.my_col\nfrom abc"), ("select name.my_col, cte.my_col from name inner join cte\n ON name.my_col=cte.my_col\nwhere d=e", "Mismatch at column 1: 'my_col' is of type char(1) but expression is of type smallint (1)", "SELECT\ncast(cast(name.my_col AS varchar) AS char(1)) AS my_col,\ncte.my_col\nfrom name inner join cte\n ON name.my_col=cte.my_col\nwhere d=e") ]) def test_column_type_mismatch(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() pattern = [k for k, v in ErrorHandlerHiveToPresto.known_issues.items() if v == ErrorHandlerHiveToPresto._column_type_mismatch] assert ErrorHandlerHiveToPresto._column_type_mismatch(statement, re.search(pattern[0], error_message), temp_tgt_table_properties={"columns": {}}) == expected @pytest.mark.parametrize(['statement', 'error_message', 'expected'], [ ("select cast(a AS bigint) from cte", "line 1:8: Cannot cast timestamp to bigint (1)", "select to_unixtime(a) from cte") ]) def test_handle_errors(statement: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() assert ErrorHandlerHiveToPresto.handle_errors(statement, statement, error_message) == (expected, expected) @pytest.mark.parametrize(['statement', 'original_sql', 'error_message', 'expected'], [ ("select a, cast(a AS bigint) from cte", "select {a}, cast(a AS bigint) from cte", "line 1:11: Cannot cast timestamp to bigint (1)", "select a, to_unixtime(a) from cte") ]) def test_handle_errors_Exception(statement: str, original_sql: str, error_message: str, expected: str) -> None: ErrorHandlerHiveToPresto = error_handling.ErrorHandlerHiveToPresto() assert ErrorHandlerHiveToPresto.handle_errors(statement, original_sql, error_message) == (expected, "")

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ElyasSantana/example-api

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helloworld/api/v1.py

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from fastapi import APIRouter router_helloworld = APIRouter() @router_helloworld.get("/") def get_helloworld(): return {"Hello": "World"}

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tests/__init__.py

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tests/__init__.py

antoinebourayne/sd2c

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tests/__init__.py

antoinebourayne/sd2c

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[ "Apache-2.0" ]

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# -*- coding: utf-8 -*- """ Ceci est un module avec les tests unitaires et les tests d'intégrations. """

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src/Intel_Project (1).py

Lance-Dsilva/Intel-Image-Classification-Using-CNN-91-Accuracy-

e5b729dddaa3671337c6c5019b69fc6ca2c868c0

[ "Unlicense" ]

null

src/Intel_Project (1).py

Lance-Dsilva/Intel-Image-Classification-Using-CNN-91-Accuracy-

e5b729dddaa3671337c6c5019b69fc6ca2c868c0

[ "Unlicense" ]

null

src/Intel_Project (1).py

Lance-Dsilva/Intel-Image-Classification-Using-CNN-91-Accuracy-

e5b729dddaa3671337c6c5019b69fc6ca2c868c0

[ "Unlicense" ]

null

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class="blob-code blob-code-inner js-file-line"><span class=pl-c># # Convolutional Neural Network</span></td> </tr> <tr> <td id="L5" class="blob-num js-line-number" data-line-number="5"></td> <td id="LC5" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L6" class="blob-num js-line-number" data-line-number="6"></td> <td id="LC6" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Installing the libraries</span></td> </tr> <tr> <td id="L7" class="blob-num js-line-number" data-line-number="7"></td> <td id="LC7" class="blob-code blob-code-inner js-file-line">!p<span class=pl-s1>ip</span> <span class=pl-s1>install</span> <span class=pl-s1>tensorflow</span>!p<span class=pl-s1>ip</span> <span class=pl-s1>install</span> <span class=pl-s1>keras</span></td> </tr> <tr> <td id="L8" class="blob-num js-line-number" data-line-number="8"></td> <td id="LC8" class="blob-code blob-code-inner js-file-line">!p<span class=pl-s1>ip</span> <span class=pl-s1>install</span> <span class=pl-s1>opencv</span><span class=pl-c1>-</span><span class=pl-s1>python</span></td> </tr> <tr> <td id="L9" class="blob-num js-line-number" data-line-number="9"></td> <td id="LC9" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ## Importing The Libraries</span></td> </tr> <tr> <td id="L10" class="blob-num js-line-number" data-line-number="10"></td> <td id="LC10" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L11" class="blob-num js-line-number" data-line-number="11"></td> <td id="LC11" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[213]:</span></td> </tr> <tr> <td id="L12" class="blob-num js-line-number" data-line-number="12"></td> <td id="LC12" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L13" class="blob-num js-line-number" data-line-number="13"></td> <td id="LC13" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L14" class="blob-num js-line-number" data-line-number="14"></td> <td id="LC14" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>tensorflow</span> <span class=pl-k>as</span> <span class=pl-s1>tf</span></td> </tr> <tr> <td id="L15" class="blob-num js-line-number" data-line-number="15"></td> <td id="LC15" class="blob-code blob-code-inner js-file-line"><span class=pl-k>from</span> <span class=pl-s1>keras</span>.<span class=pl-s1>preprocessing</span>.<span class=pl-s1>image</span> <span class=pl-k>import</span> <span class=pl-v>ImageDataGenerator</span></td> </tr> <tr> <td id="L16" class="blob-num js-line-number" data-line-number="16"></td> <td id="LC16" class="blob-code blob-code-inner js-file-line"><span class=pl-k>from</span> <span class=pl-s1>keras</span>.<span class=pl-s1>preprocessing</span> <span class=pl-k>import</span> <span class=pl-s1>image</span> <span class=pl-k>as</span> <span class=pl-s1>img</span></td> </tr> <tr> <td id="L17" class="blob-num js-line-number" data-line-number="17"></td> <td id="LC17" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>pandas</span> <span class=pl-k>as</span> <span class=pl-s1>pd</span></td> </tr> <tr> <td id="L18" class="blob-num js-line-number" data-line-number="18"></td> <td id="LC18" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>matplotlib</span>.<span class=pl-s1>pyplot</span> <span class=pl-k>as</span> <span class=pl-s1>plt</span></td> </tr> <tr> <td id="L19" class="blob-num js-line-number" data-line-number="19"></td> <td id="LC19" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>numpy</span> <span class=pl-k>as</span> <span class=pl-s1>np</span></td> </tr> <tr> <td id="L20" class="blob-num js-line-number" data-line-number="20"></td> <td id="LC20" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>tensorflow</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>layers</span> <span class=pl-k>as</span> <span class=pl-v>Layers</span></td> </tr> <tr> <td id="L21" class="blob-num js-line-number" data-line-number="21"></td> <td id="LC21" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>tensorflow</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>activations</span> <span class=pl-k>as</span> <span class=pl-v>Actications</span></td> </tr> <tr> <td id="L22" class="blob-num js-line-number" data-line-number="22"></td> <td id="LC22" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>tensorflow</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>models</span> <span class=pl-k>as</span> <span class=pl-v>Models</span></td> </tr> <tr> <td id="L23" class="blob-num js-line-number" data-line-number="23"></td> <td id="LC23" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>tensorflow</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>optimizers</span> <span class=pl-k>as</span> <span class=pl-v>Optimizer</span></td> </tr> <tr> <td id="L24" class="blob-num js-line-number" data-line-number="24"></td> <td id="LC24" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>tensorflow</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>metrics</span> <span class=pl-k>as</span> <span class=pl-v>Metrics</span></td> </tr> <tr> <td id="L25" class="blob-num js-line-number" data-line-number="25"></td> <td id="LC25" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>tensorflow</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>utils</span> <span class=pl-k>as</span> <span class=pl-v>Utils</span></td> </tr> <tr> <td id="L26" class="blob-num js-line-number" data-line-number="26"></td> <td id="LC26" class="blob-code blob-code-inner js-file-line"><span class=pl-k>from</span> <span class=pl-s1>keras</span>.<span class=pl-s1>utils</span>.<span class=pl-s1>vis_utils</span> <span class=pl-k>import</span> <span class=pl-s1>model_to_dot</span></td> </tr> <tr> <td id="L27" class="blob-num js-line-number" data-line-number="27"></td> <td id="LC27" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>os</span></td> </tr> <tr> <td id="L28" class="blob-num js-line-number" data-line-number="28"></td> <td id="LC28" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>matplotlib</span>.<span class=pl-s1>pyplot</span> <span class=pl-k>as</span> <span class=pl-s1>plot</span></td> </tr> <tr> <td id="L29" class="blob-num js-line-number" data-line-number="29"></td> <td id="LC29" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>cv2</span></td> </tr> <tr> <td id="L30" class="blob-num js-line-number" data-line-number="30"></td> <td id="LC30" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>numpy</span> <span class=pl-k>as</span> <span class=pl-s1>np</span></td> </tr> <tr> <td id="L31" class="blob-num js-line-number" data-line-number="31"></td> <td id="LC31" class="blob-code blob-code-inner js-file-line"><span class=pl-k>from</span> <span class=pl-s1>sklearn</span>.<span class=pl-s1>utils</span> <span class=pl-k>import</span> <span class=pl-s1>shuffle</span></td> </tr> <tr> <td id="L32" class="blob-num js-line-number" data-line-number="32"></td> <td id="LC32" class="blob-code blob-code-inner js-file-line"><span class=pl-k>from</span> <span class=pl-s1>sklearn</span>.<span class=pl-s1>metrics</span> <span class=pl-k>import</span> <span class=pl-s1>confusion_matrix</span> <span class=pl-k>as</span> <span class=pl-v>CM</span></td> </tr> <tr> <td id="L33" class="blob-num js-line-number" data-line-number="33"></td> <td id="LC33" class="blob-code blob-code-inner js-file-line"><span class=pl-k>from</span> <span class=pl-s1>random</span> <span class=pl-k>import</span> <span class=pl-s1>randint</span></td> </tr> <tr> <td id="L34" class="blob-num js-line-number" data-line-number="34"></td> <td id="LC34" class="blob-code blob-code-inner js-file-line"><span class=pl-k>from</span> <span class=pl-v>IPython</span>.<span class=pl-s1>display</span> <span class=pl-k>import</span> <span class=pl-v>SVG</span></td> </tr> <tr> <td id="L35" class="blob-num js-line-number" data-line-number="35"></td> <td id="LC35" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>matplotlib</span>.<span class=pl-s1>gridspec</span> <span class=pl-k>as</span> <span class=pl-s1>gridspec</span></td> </tr> <tr> <td id="L36" class="blob-num js-line-number" data-line-number="36"></td> <td id="LC36" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L37" class="blob-num js-line-number" data-line-number="37"></td> <td id="LC37" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L38" class="blob-num js-line-number" data-line-number="38"></td> <td id="LC38" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[184]:</span></td> </tr> <tr> <td id="L39" class="blob-num js-line-number" data-line-number="39"></td> <td id="LC39" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L40" class="blob-num js-line-number" data-line-number="40"></td> <td id="LC40" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L41" class="blob-num js-line-number" data-line-number="41"></td> <td id="LC41" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>tf</span>.<span class=pl-s1>__version__</span></td> </tr> <tr> <td id="L42" class="blob-num js-line-number" data-line-number="42"></td> <td id="LC42" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L43" class="blob-num js-line-number" data-line-number="43"></td> <td id="LC43" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L44" class="blob-num js-line-number" data-line-number="44"></td> <td id="LC44" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[185]:</span></td> </tr> <tr> <td id="L45" class="blob-num js-line-number" data-line-number="45"></td> <td id="LC45" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L46" class="blob-num js-line-number" data-line-number="46"></td> <td id="LC46" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L47" class="blob-num js-line-number" data-line-number="47"></td> <td id="LC47" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>cv2</span>.<span class=pl-s1>__version__</span></td> </tr> <tr> <td id="L48" class="blob-num js-line-number" data-line-number="48"></td> <td id="LC48" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L49" class="blob-num js-line-number" data-line-number="49"></td> <td id="LC49" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L50" class="blob-num js-line-number" data-line-number="50"></td> <td id="LC50" class="blob-code blob-code-inner js-file-line"><span class=pl-c># # Analising the Data</span></td> </tr> <tr> <td id="L51" class="blob-num js-line-number" data-line-number="51"></td> <td id="LC51" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L52" class="blob-num js-line-number" data-line-number="52"></td> <td id="LC52" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[214]:</span></td> </tr> <tr> <td id="L53" class="blob-num js-line-number" data-line-number="53"></td> <td id="LC53" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L54" class="blob-num js-line-number" data-line-number="54"></td> <td id="LC54" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L55" class="blob-num js-line-number" data-line-number="55"></td> <td id="LC55" class="blob-code blob-code-inner js-file-line"><span class=pl-v>X</span> <span class=pl-c1>=</span> []</td> </tr> <tr> <td id="L56" class="blob-num js-line-number" data-line-number="56"></td> <td id="LC56" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>y</span> <span class=pl-c1>=</span> []</td> </tr> <tr> <td id="L57" class="blob-num js-line-number" data-line-number="57"></td> <td id="LC57" class="blob-code blob-code-inner js-file-line"><span class=pl-v>IMG_SIZE</span> <span class=pl-c1>=</span> <span class=pl-c1>150</span></td> </tr> <tr> <td id="L58" class="blob-num js-line-number" data-line-number="58"></td> <td id="LC58" class="blob-code blob-code-inner js-file-line"><span class=pl-v>DIR</span> <span class=pl-c1>=</span> <span class=pl-s>"111880_269359_bundle_archive/seg_train/seg_train"</span></td> </tr> <tr> <td id="L59" class="blob-num js-line-number" data-line-number="59"></td> <td id="LC59" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>folders</span> <span class=pl-c1>=</span> <span class=pl-s1>os</span>.<span class=pl-en>listdir</span>(<span class=pl-v>DIR</span>)</td> </tr> <tr> <td id="L60" class="blob-num js-line-number" data-line-number="60"></td> <td id="LC60" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>folders</span></td> </tr> <tr> <td id="L61" class="blob-num js-line-number" data-line-number="61"></td> <td id="LC61" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L62" class="blob-num js-line-number" data-line-number="62"></td> <td id="LC62" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L63" class="blob-num js-line-number" data-line-number="63"></td> <td id="LC63" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[216]:</span></td> </tr> <tr> <td id="L64" class="blob-num js-line-number" data-line-number="64"></td> <td id="LC64" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L65" class="blob-num js-line-number" data-line-number="65"></td> <td id="LC65" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L66" class="blob-num js-line-number" data-line-number="66"></td> <td id="LC66" class="blob-code blob-code-inner js-file-line"><span class=pl-k>for</span> <span class=pl-s1>i</span>, <span class=pl-s1>file</span> <span class=pl-c1>in</span> <span class=pl-en>enumerate</span>(<span class=pl-s1>folders</span>):</td> </tr> <tr> <td id="L67" class="blob-num js-line-number" data-line-number="67"></td> <td id="LC67" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>filename</span> <span class=pl-c1>=</span> <span class=pl-s1>os</span>.<span class=pl-s1>path</span>.<span class=pl-en>join</span>(<span class=pl-v>DIR</span>, <span class=pl-s1>file</span>)</td> </tr> <tr> <td id="L68" class="blob-num js-line-number" data-line-number="68"></td> <td id="LC68" class="blob-code blob-code-inner js-file-line"> <span class=pl-en>print</span>(<span class=pl-s>"Folder {} started"</span>.<span class=pl-en>format</span>(<span class=pl-s1>file</span>))</td> </tr> <tr> <td id="L69" class="blob-num js-line-number" data-line-number="69"></td> <td id="LC69" class="blob-code blob-code-inner js-file-line"> <span class=pl-k>try</span>:</td> </tr> <tr> <td id="L70" class="blob-num js-line-number" data-line-number="70"></td> <td id="LC70" class="blob-code blob-code-inner js-file-line"> <span class=pl-k>for</span> <span class=pl-s1>img</span> <span class=pl-c1>in</span> <span class=pl-s1>os</span>.<span class=pl-en>listdir</span>(<span class=pl-s1>filename</span>):</td> </tr> <tr> <td id="L71" class="blob-num js-line-number" data-line-number="71"></td> <td id="LC71" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>path</span> <span class=pl-c1>=</span> <span class=pl-s1>os</span>.<span class=pl-s1>path</span>.<span class=pl-en>join</span>(<span class=pl-s1>filename</span>, <span class=pl-s1>img</span>)</td> </tr> <tr> <td id="L72" class="blob-num js-line-number" data-line-number="72"></td> <td id="LC72" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>img</span> <span class=pl-c1>=</span> <span class=pl-s1>cv2</span>.<span class=pl-en>imread</span>(<span class=pl-s1>path</span>,<span class=pl-s1>cv2</span>.<span class=pl-v>IMREAD_COLOR</span>)</td> </tr> <tr> <td id="L73" class="blob-num js-line-number" data-line-number="73"></td> <td id="LC73" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>img</span> <span class=pl-c1>=</span> <span class=pl-s1>cv2</span>.<span class=pl-en>resize</span>(<span class=pl-s1>img</span>, (<span class=pl-v>IMG_SIZE</span>,<span class=pl-v>IMG_SIZE</span>))</td> </tr> <tr> <td id="L74" class="blob-num js-line-number" data-line-number="74"></td> <td id="LC74" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L75" class="blob-num js-line-number" data-line-number="75"></td> <td id="LC75" class="blob-code blob-code-inner js-file-line"> <span class=pl-v>X</span>.<span class=pl-en>append</span>(<span class=pl-s1>np</span>.<span class=pl-en>array</span>(<span class=pl-s1>img</span>))</td> </tr> <tr> <td id="L76" class="blob-num js-line-number" data-line-number="76"></td> <td id="LC76" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>y</span>.<span class=pl-en>append</span>(<span class=pl-s1>i</span>)</td> </tr> <tr> <td id="L77" class="blob-num js-line-number" data-line-number="77"></td> <td id="LC77" class="blob-code blob-code-inner js-file-line"> <span class=pl-k>except</span>:</td> </tr> <tr> <td id="L78" class="blob-num js-line-number" data-line-number="78"></td> <td id="LC78" class="blob-code blob-code-inner js-file-line"> <span class=pl-en>print</span>(<span class=pl-s>"File {} not read"</span>.<span class=pl-en>format</span>(<span class=pl-s1>path</span>))</td> </tr> <tr> <td id="L79" class="blob-num js-line-number" data-line-number="79"></td> <td id="LC79" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L80" class="blob-num js-line-number" data-line-number="80"></td> <td id="LC80" class="blob-code blob-code-inner js-file-line"> <span class=pl-en>print</span>(<span class=pl-s>"Folder {} done"</span>.<span class=pl-en>format</span>(<span class=pl-s1>file</span>))</td> </tr> <tr> <td id="L81" class="blob-num js-line-number" data-line-number="81"></td> <td id="LC81" class="blob-code blob-code-inner js-file-line"> <span class=pl-en>print</span>(<span class=pl-s>"The folder {} is labeled as {}"</span>.<span class=pl-en>format</span>(<span class=pl-s1>file</span>, <span class=pl-s1>i</span>))</td> </tr> <tr> <td id="L82" class="blob-num js-line-number" data-line-number="82"></td> <td id="LC82" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L83" class="blob-num js-line-number" data-line-number="83"></td> <td id="LC83" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L84" class="blob-num js-line-number" data-line-number="84"></td> <td id="LC84" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[217]:</span></td> </tr> <tr> <td id="L85" class="blob-num js-line-number" data-line-number="85"></td> <td id="LC85" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L86" class="blob-num js-line-number" data-line-number="86"></td> <td id="LC86" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L87" class="blob-num js-line-number" data-line-number="87"></td> <td id="LC87" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>np</span>.<span class=pl-en>unique</span>(<span class=pl-s1>y</span>, <span class=pl-s1>return_counts</span><span class=pl-c1>=</span><span class=pl-c1>True</span>)</td> </tr> <tr> <td id="L88" class="blob-num js-line-number" data-line-number="88"></td> <td id="LC88" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L89" class="blob-num js-line-number" data-line-number="89"></td> <td id="LC89" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L90" class="blob-num js-line-number" data-line-number="90"></td> <td id="LC90" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Making the functions to get the training and validation set from the Images</span></td> </tr> <tr> <td id="L91" class="blob-num js-line-number" data-line-number="91"></td> <td id="LC91" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L92" class="blob-num js-line-number" data-line-number="92"></td> <td id="LC92" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[223]:</span></td> </tr> <tr> <td id="L93" class="blob-num js-line-number" data-line-number="93"></td> <td id="LC93" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L94" class="blob-num js-line-number" data-line-number="94"></td> <td id="LC94" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L95" class="blob-num js-line-number" data-line-number="95"></td> <td id="LC95" class="blob-code blob-code-inner js-file-line"><span class=pl-k>from</span> <span class=pl-s1>tqdm</span> <span class=pl-k>import</span> <span class=pl-s1>tqdm</span></td> </tr> <tr> <td id="L96" class="blob-num js-line-number" data-line-number="96"></td> <td id="LC96" class="blob-code blob-code-inner js-file-line"><span class=pl-v>X</span><span class=pl-c1>=</span>[]</td> </tr> <tr> <td id="L97" class="blob-num js-line-number" data-line-number="97"></td> <td id="LC97" class="blob-code blob-code-inner js-file-line"><span class=pl-v>Z</span><span class=pl-c1>=</span>[]</td> </tr> <tr> <td id="L98" class="blob-num js-line-number" data-line-number="98"></td> <td id="LC98" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L99" class="blob-num js-line-number" data-line-number="99"></td> <td id="LC99" class="blob-code blob-code-inner js-file-line"><span class=pl-v>IMG_SIZE</span><span class=pl-c1>=</span><span class=pl-c1>150</span></td> </tr> <tr> <td id="L100" class="blob-num js-line-number" data-line-number="100"></td> <td id="LC100" class="blob-code blob-code-inner js-file-line"><span class=pl-v>IMAGE_BUILDINGS_DIR</span><span class=pl-c1>=</span><span class=pl-s>'111880_269359_bundle_archive/seg_train/seg_train/buildings'</span></td> </tr> <tr> <td id="L101" class="blob-num js-line-number" data-line-number="101"></td> <td id="LC101" class="blob-code blob-code-inner js-file-line"><span class=pl-v>IMAGE_FOREST_DIR</span><span class=pl-c1>=</span><span class=pl-s>'111880_269359_bundle_archive/seg_train/seg_train/forest'</span></td> </tr> <tr> <td id="L102" class="blob-num js-line-number" data-line-number="102"></td> <td id="LC102" class="blob-code blob-code-inner js-file-line"><span class=pl-v>IMAGE_GLACIER_DIR</span><span class=pl-c1>=</span><span class=pl-s>'111880_269359_bundle_archive/seg_train/seg_train/glacier'</span></td> </tr> <tr> <td id="L103" class="blob-num js-line-number" data-line-number="103"></td> <td id="LC103" class="blob-code blob-code-inner js-file-line"><span class=pl-v>IMAGE_MOUNTAIN_DIR</span><span class=pl-c1>=</span><span class=pl-s>'111880_269359_bundle_archive/seg_train/seg_train/mountain'</span></td> </tr> <tr> <td id="L104" class="blob-num js-line-number" data-line-number="104"></td> <td id="LC104" class="blob-code blob-code-inner js-file-line"><span class=pl-v>IMAGE_SEA_DIR</span><span class=pl-c1>=</span><span class=pl-s>'111880_269359_bundle_archive/seg_train/seg_train/sea'</span></td> </tr> <tr> <td id="L105" class="blob-num js-line-number" data-line-number="105"></td> <td id="LC105" class="blob-code blob-code-inner js-file-line"><span class=pl-v>IMAGE_STREET_DIR</span><span class=pl-c1>=</span><span class=pl-s>'111880_269359_bundle_archive/seg_train/seg_train/street'</span></td> </tr> <tr> <td id="L106" class="blob-num js-line-number" data-line-number="106"></td> <td id="LC106" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L107" class="blob-num js-line-number" data-line-number="107"></td> <td id="LC107" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L108" class="blob-num js-line-number" data-line-number="108"></td> <td id="LC108" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[224]:</span></td> </tr> <tr> <td id="L109" class="blob-num js-line-number" data-line-number="109"></td> <td id="LC109" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L110" class="blob-num js-line-number" data-line-number="110"></td> <td id="LC110" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L111" class="blob-num js-line-number" data-line-number="111"></td> <td id="LC111" class="blob-code blob-code-inner js-file-line"><span class=pl-k>def</span> <span class=pl-en>assign_label</span>(<span class=pl-s1>img</span>,<span class=pl-s1>image_type</span>):</td> </tr> <tr> <td id="L112" class="blob-num js-line-number" data-line-number="112"></td> <td id="LC112" class="blob-code blob-code-inner js-file-line"> <span class=pl-k>return</span> <span class=pl-s1>image_type</span></td> </tr> <tr> <td id="L113" class="blob-num js-line-number" data-line-number="113"></td> <td id="LC113" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L114" class="blob-num js-line-number" data-line-number="114"></td> <td id="LC114" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L115" class="blob-num js-line-number" data-line-number="115"></td> <td id="LC115" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[255]:</span></td> </tr> <tr> <td id="L116" class="blob-num js-line-number" data-line-number="116"></td> <td id="LC116" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L117" class="blob-num js-line-number" data-line-number="117"></td> <td id="LC117" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L118" class="blob-num js-line-number" data-line-number="118"></td> <td id="LC118" class="blob-code blob-code-inner js-file-line"><span class=pl-k>def</span> <span class=pl-en>make_train_data</span>(<span class=pl-s1>image_type</span>,<span class=pl-v>DIR</span>):</td> </tr> <tr> <td id="L119" class="blob-num js-line-number" data-line-number="119"></td> <td id="LC119" class="blob-code blob-code-inner js-file-line"> <span class=pl-k>for</span> <span class=pl-s1>img</span> <span class=pl-c1>in</span> <span class=pl-en>tqdm</span>(<span class=pl-s1>os</span>.<span class=pl-en>listdir</span>(<span class=pl-v>DIR</span>)):</td> </tr> <tr> <td id="L120" class="blob-num js-line-number" data-line-number="120"></td> <td id="LC120" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>label</span><span class=pl-c1>=</span><span class=pl-en>assign_label</span>(<span class=pl-s1>img</span>,<span class=pl-s1>image_type</span>)</td> </tr> <tr> <td id="L121" class="blob-num js-line-number" data-line-number="121"></td> <td id="LC121" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>path</span> <span class=pl-c1>=</span> <span class=pl-s1>os</span>.<span class=pl-s1>path</span>.<span class=pl-en>join</span>(<span class=pl-v>DIR</span>,<span class=pl-s1>img</span>)</td> </tr> <tr> <td id="L122" class="blob-num js-line-number" data-line-number="122"></td> <td id="LC122" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>img</span> <span class=pl-c1>=</span> <span class=pl-s1>cv2</span>.<span class=pl-en>imread</span>(<span class=pl-s1>path</span>,<span class=pl-s1>cv2</span>.<span class=pl-v>IMREAD_COLOR</span>)</td> </tr> <tr> <td id="L123" class="blob-num js-line-number" data-line-number="123"></td> <td id="LC123" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>img</span> <span class=pl-c1>=</span> <span class=pl-s1>cv2</span>.<span class=pl-en>resize</span>(<span class=pl-s1>img</span>, (<span class=pl-v>IMG_SIZE</span>,<span class=pl-v>IMG_SIZE</span>))</td> </tr> <tr> <td id="L124" class="blob-num js-line-number" data-line-number="124"></td> <td id="LC124" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L125" class="blob-num js-line-number" data-line-number="125"></td> <td id="LC125" class="blob-code blob-code-inner js-file-line"> <span class=pl-v>X</span>.<span class=pl-en>append</span>(<span class=pl-s1>np</span>.<span class=pl-en>array</span>(<span class=pl-s1>img</span>))</td> </tr> <tr> <td id="L126" class="blob-num js-line-number" data-line-number="126"></td> <td id="LC126" class="blob-code blob-code-inner js-file-line"> <span class=pl-v>Z</span>.<span class=pl-en>append</span>(<span class=pl-s1>__builtins__</span>.<span class=pl-en>str</span>(<span class=pl-s1>label</span>))</td> </tr> <tr> <td id="L127" class="blob-num js-line-number" data-line-number="127"></td> <td id="LC127" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L128" class="blob-num js-line-number" data-line-number="128"></td> <td id="LC128" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L129" class="blob-num js-line-number" data-line-number="129"></td> <td id="LC129" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[256]:</span></td> </tr> <tr> <td id="L130" class="blob-num js-line-number" data-line-number="130"></td> <td id="LC130" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L131" class="blob-num js-line-number" data-line-number="131"></td> <td id="LC131" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L132" class="blob-num js-line-number" data-line-number="132"></td> <td id="LC132" class="blob-code blob-code-inner js-file-line"><span class=pl-en>make_train_data</span>(<span class=pl-s>'Buildings'</span>,<span class=pl-v>IMAGE_BUILDINGS_DIR</span>)</td> </tr> <tr> <td id="L133" class="blob-num js-line-number" data-line-number="133"></td> <td id="LC133" class="blob-code blob-code-inner js-file-line"><span class=pl-en>print</span>(<span class=pl-en>len</span>(<span class=pl-v>X</span>))</td> </tr> <tr> <td id="L134" class="blob-num js-line-number" data-line-number="134"></td> <td id="LC134" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L135" class="blob-num js-line-number" data-line-number="135"></td> <td id="LC135" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L136" class="blob-num js-line-number" data-line-number="136"></td> <td id="LC136" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[257]:</span></td> </tr> <tr> <td id="L137" class="blob-num js-line-number" data-line-number="137"></td> <td id="LC137" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L138" class="blob-num js-line-number" data-line-number="138"></td> <td id="LC138" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L139" class="blob-num js-line-number" data-line-number="139"></td> <td id="LC139" class="blob-code blob-code-inner js-file-line"><span class=pl-en>make_train_data</span>(<span class=pl-s>'Forest'</span>,<span class=pl-v>IMAGE_FOREST_DIR</span>)</td> </tr> <tr> <td id="L140" class="blob-num js-line-number" data-line-number="140"></td> <td id="LC140" class="blob-code blob-code-inner js-file-line"><span class=pl-en>print</span>(<span class=pl-en>len</span>(<span class=pl-v>X</span>))</td> </tr> <tr> <td id="L141" class="blob-num js-line-number" data-line-number="141"></td> <td id="LC141" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L142" class="blob-num js-line-number" data-line-number="142"></td> <td id="LC142" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L143" class="blob-num js-line-number" data-line-number="143"></td> <td id="LC143" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[258]:</span></td> </tr> <tr> <td id="L144" class="blob-num js-line-number" data-line-number="144"></td> <td id="LC144" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L145" class="blob-num js-line-number" data-line-number="145"></td> <td id="LC145" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L146" class="blob-num js-line-number" data-line-number="146"></td> <td id="LC146" class="blob-code blob-code-inner js-file-line"><span class=pl-en>make_train_data</span>(<span class=pl-s>'Glacier'</span>,<span class=pl-v>IMAGE_GLACIER_DIR</span>)</td> </tr> <tr> <td id="L147" class="blob-num js-line-number" data-line-number="147"></td> <td id="LC147" class="blob-code blob-code-inner js-file-line"><span class=pl-en>print</span>(<span class=pl-en>len</span>(<span class=pl-v>X</span>))</td> </tr> <tr> <td id="L148" class="blob-num js-line-number" data-line-number="148"></td> <td id="LC148" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L149" class="blob-num js-line-number" data-line-number="149"></td> <td id="LC149" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L150" class="blob-num js-line-number" data-line-number="150"></td> <td id="LC150" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[259]:</span></td> </tr> <tr> <td id="L151" class="blob-num js-line-number" data-line-number="151"></td> <td id="LC151" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L152" class="blob-num js-line-number" data-line-number="152"></td> <td id="LC152" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L153" class="blob-num js-line-number" data-line-number="153"></td> <td id="LC153" class="blob-code blob-code-inner js-file-line"><span class=pl-en>make_train_data</span>(<span class=pl-s>'Mountain'</span>,<span class=pl-v>IMAGE_MOUNTAIN_DIR</span>)</td> </tr> <tr> <td id="L154" class="blob-num js-line-number" data-line-number="154"></td> <td id="LC154" class="blob-code blob-code-inner js-file-line"><span class=pl-en>print</span>(<span class=pl-en>len</span>(<span class=pl-v>X</span>))</td> </tr> <tr> <td id="L155" class="blob-num js-line-number" data-line-number="155"></td> <td id="LC155" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L156" class="blob-num js-line-number" data-line-number="156"></td> <td id="LC156" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L157" class="blob-num js-line-number" data-line-number="157"></td> <td id="LC157" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[260]:</span></td> </tr> <tr> <td id="L158" class="blob-num js-line-number" data-line-number="158"></td> <td id="LC158" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L159" class="blob-num js-line-number" data-line-number="159"></td> <td id="LC159" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L160" class="blob-num js-line-number" data-line-number="160"></td> <td id="LC160" class="blob-code blob-code-inner js-file-line"><span class=pl-en>make_train_data</span>(<span class=pl-s>'Sea'</span>,<span class=pl-v>IMAGE_SEA_DIR</span>)</td> </tr> <tr> <td id="L161" class="blob-num js-line-number" data-line-number="161"></td> <td id="LC161" class="blob-code blob-code-inner js-file-line"><span class=pl-en>print</span>(<span class=pl-en>len</span>(<span class=pl-v>X</span>))</td> </tr> <tr> <td id="L162" class="blob-num js-line-number" data-line-number="162"></td> <td id="LC162" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L163" class="blob-num js-line-number" data-line-number="163"></td> <td id="LC163" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L164" class="blob-num js-line-number" data-line-number="164"></td> <td id="LC164" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[261]:</span></td> </tr> <tr> <td id="L165" class="blob-num js-line-number" data-line-number="165"></td> <td id="LC165" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L166" class="blob-num js-line-number" data-line-number="166"></td> <td id="LC166" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L167" class="blob-num js-line-number" data-line-number="167"></td> <td id="LC167" class="blob-code blob-code-inner js-file-line"><span class=pl-en>make_train_data</span>(<span class=pl-s>'Street'</span>,<span class=pl-v>IMAGE_STREET_DIR</span>)</td> </tr> <tr> <td id="L168" class="blob-num js-line-number" data-line-number="168"></td> <td id="LC168" class="blob-code blob-code-inner js-file-line"><span class=pl-en>print</span>(<span class=pl-en>len</span>(<span class=pl-v>X</span>))</td> </tr> <tr> <td id="L169" class="blob-num js-line-number" data-line-number="169"></td> <td id="LC169" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L170" class="blob-num js-line-number" data-line-number="170"></td> <td id="LC170" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L171" class="blob-num js-line-number" data-line-number="171"></td> <td id="LC171" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[262]:</span></td> </tr> <tr> <td id="L172" class="blob-num js-line-number" data-line-number="172"></td> <td id="LC172" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L173" class="blob-num js-line-number" data-line-number="173"></td> <td id="LC173" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L174" class="blob-num js-line-number" data-line-number="174"></td> <td id="LC174" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L175" class="blob-num js-line-number" data-line-number="175"></td> <td id="LC175" class="blob-code blob-code-inner js-file-line"><span class=pl-k>from</span> <span class=pl-v>IPython</span>.<span class=pl-s1>display</span> <span class=pl-k>import</span> <span class=pl-s1>display</span></td> </tr> <tr> <td id="L176" class="blob-num js-line-number" data-line-number="176"></td> <td id="LC176" class="blob-code blob-code-inner js-file-line"><span class=pl-k>from</span> <span class=pl-v>PIL</span> <span class=pl-k>import</span> <span class=pl-v>Image</span> </td> </tr> <tr> <td id="L177" class="blob-num js-line-number" data-line-number="177"></td> <td id="LC177" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>labels</span> <span class=pl-c1>=</span> []</td> </tr> <tr> <td id="L178" class="blob-num js-line-number" data-line-number="178"></td> <td id="LC178" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>dic</span> <span class=pl-c1>=</span> <span class=pl-en>dict</span>()</td> </tr> <tr> <td id="L179" class="blob-num js-line-number" data-line-number="179"></td> <td id="LC179" class="blob-code blob-code-inner js-file-line"><span class=pl-k>for</span> <span class=pl-s1>i</span> <span class=pl-c1>in</span> <span class=pl-en>range</span>(<span class=pl-c1>0</span>,<span class=pl-c1>6</span>):</td> </tr> <tr> <td id="L180" class="blob-num js-line-number" data-line-number="180"></td> <td id="LC180" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>str</span> <span class=pl-c1>=</span> <span class=pl-s>'111880_269359_bundle_archive\seg_train\seg_train<span class=pl-cce>\\</span>'</span><span class=pl-c1>+</span><span class=pl-s1>dirs</span>[<span class=pl-s1>i</span>]</td> </tr> <tr> <td id="L181" class="blob-num js-line-number" data-line-number="181"></td> <td id="LC181" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>count</span> <span class=pl-c1>=</span> <span class=pl-c1>0</span></td> </tr> <tr> <td id="L182" class="blob-num js-line-number" data-line-number="182"></td> <td id="LC182" class="blob-code blob-code-inner js-file-line"> <span class=pl-k>for</span> <span class=pl-s1>j</span> <span class=pl-c1>in</span> <span class=pl-s1>os</span>.<span class=pl-en>listdir</span>(<span class=pl-s1>str</span>):</td> </tr> <tr> <td id="L183" class="blob-num js-line-number" data-line-number="183"></td> <td id="LC183" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>str2</span> <span class=pl-c1>=</span> <span class=pl-s1>str</span><span class=pl-c1>+</span><span class=pl-s>"<span class=pl-cce>\\</span>"</span><span class=pl-c1>+</span><span class=pl-s1>j</span></td> </tr> <tr> <td id="L184" class="blob-num js-line-number" data-line-number="184"></td> <td id="LC184" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>im</span> <span class=pl-c1>=</span> <span class=pl-v>Image</span>.<span class=pl-en>open</span>(<span class=pl-s1>str2</span>)</td> </tr> <tr> <td id="L185" class="blob-num js-line-number" data-line-number="185"></td> <td id="LC185" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>count</span> <span class=pl-c1>+=</span> <span class=pl-c1>1</span></td> </tr> <tr> <td id="L186" class="blob-num js-line-number" data-line-number="186"></td> <td id="LC186" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>labels</span>.<span class=pl-en>append</span>(<span class=pl-s1>j</span>)</td> </tr> <tr> <td id="L187" class="blob-num js-line-number" data-line-number="187"></td> <td id="LC187" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>dic</span>[<span class=pl-s1>dirs</span>[<span class=pl-s1>i</span>]] <span class=pl-c1>=</span> <span class=pl-s1>count</span></td> </tr> <tr> <td id="L188" class="blob-num js-line-number" data-line-number="188"></td> <td id="LC188" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L189" class="blob-num js-line-number" data-line-number="189"></td> <td id="LC189" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L190" class="blob-num js-line-number" data-line-number="190"></td> <td id="LC190" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[263]:</span></td> </tr> <tr> <td id="L191" class="blob-num js-line-number" data-line-number="191"></td> <td id="LC191" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L192" class="blob-num js-line-number" data-line-number="192"></td> <td id="LC192" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L193" class="blob-num js-line-number" data-line-number="193"></td> <td id="LC193" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>labels1</span> <span class=pl-c1>=</span> []</td> </tr> <tr> <td id="L194" class="blob-num js-line-number" data-line-number="194"></td> <td id="LC194" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>dic1</span> <span class=pl-c1>=</span> <span class=pl-en>dict</span>()</td> </tr> <tr> <td id="L195" class="blob-num js-line-number" data-line-number="195"></td> <td id="LC195" class="blob-code blob-code-inner js-file-line"><span class=pl-v>IMAGE_SIZE</span> <span class=pl-c1>=</span> (<span class=pl-c1>64</span>,<span class=pl-c1>64</span>)</td> </tr> <tr> <td id="L196" class="blob-num js-line-number" data-line-number="196"></td> <td id="LC196" class="blob-code blob-code-inner js-file-line"><span class=pl-k>for</span> <span class=pl-s1>i</span> <span class=pl-c1>in</span> <span class=pl-en>range</span>(<span class=pl-c1>0</span>,<span class=pl-c1>6</span>):</td> </tr> <tr> <td id="L197" class="blob-num js-line-number" data-line-number="197"></td> <td id="LC197" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>str</span> <span class=pl-c1>=</span> <span class=pl-s>'111880_269359_bundle_archive\seg_test\seg_test<span class=pl-cce>\\</span>'</span><span class=pl-c1>+</span><span class=pl-s1>dirs</span>[<span class=pl-s1>i</span>]</td> </tr> <tr> <td id="L198" class="blob-num js-line-number" data-line-number="198"></td> <td id="LC198" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>count</span> <span class=pl-c1>=</span> <span class=pl-c1>0</span></td> </tr> <tr> <td id="L199" class="blob-num js-line-number" data-line-number="199"></td> <td id="LC199" class="blob-code blob-code-inner js-file-line"> <span class=pl-k>for</span> <span class=pl-s1>j</span> <span class=pl-c1>in</span> <span class=pl-s1>os</span>.<span class=pl-en>listdir</span>(<span class=pl-s1>str</span>):</td> </tr> <tr> <td id="L200" class="blob-num js-line-number" data-line-number="200"></td> <td id="LC200" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>str2</span> <span class=pl-c1>=</span> <span class=pl-s1>str</span><span class=pl-c1>+</span><span class=pl-s>"<span class=pl-cce>\\</span>"</span><span class=pl-c1>+</span><span class=pl-s1>j</span></td> </tr> <tr> <td id="L201" class="blob-num js-line-number" data-line-number="201"></td> <td id="LC201" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>im</span> <span class=pl-c1>=</span> <span class=pl-v>Image</span>.<span class=pl-en>open</span>(<span class=pl-s1>str2</span>)</td> </tr> <tr> <td id="L202" class="blob-num js-line-number" data-line-number="202"></td> <td id="LC202" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>count</span> <span class=pl-c1>+=</span> <span class=pl-c1>1</span></td> </tr> <tr> <td id="L203" class="blob-num js-line-number" data-line-number="203"></td> <td id="LC203" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>labels1</span>.<span class=pl-en>append</span>(<span class=pl-s1>j</span>)</td> </tr> <tr> <td id="L204" class="blob-num js-line-number" data-line-number="204"></td> <td id="LC204" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>dic1</span>[<span class=pl-s1>dirs</span>[<span class=pl-s1>i</span>]] <span class=pl-c1>=</span> <span class=pl-s1>count</span></td> </tr> <tr> <td id="L205" class="blob-num js-line-number" data-line-number="205"></td> <td id="LC205" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L206" class="blob-num js-line-number" data-line-number="206"></td> <td id="LC206" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L207" class="blob-num js-line-number" data-line-number="207"></td> <td id="LC207" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[264]:</span></td> </tr> <tr> <td id="L208" class="blob-num js-line-number" data-line-number="208"></td> <td id="LC208" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L209" class="blob-num js-line-number" data-line-number="209"></td> <td id="LC209" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L210" class="blob-num js-line-number" data-line-number="210"></td> <td id="LC210" class="blob-code blob-code-inner js-file-line"><span class=pl-en>print</span> (<span class=pl-s>"Number of training examples: {}"</span>.<span class=pl-en>format</span>(<span class=pl-en>len</span>(<span class=pl-s1>labels</span>)))</td> </tr> <tr> <td id="L211" class="blob-num js-line-number" data-line-number="211"></td> <td id="LC211" class="blob-code blob-code-inner js-file-line"><span class=pl-en>print</span> (<span class=pl-s>"Number of testing examples: {}"</span>.<span class=pl-en>format</span>(<span class=pl-en>len</span>(<span class=pl-s1>labels1</span>)))</td> </tr> <tr> <td id="L212" class="blob-num js-line-number" data-line-number="212"></td> <td id="LC212" class="blob-code blob-code-inner js-file-line"><span class=pl-en>print</span> (<span class=pl-s>"Each image is of size: {}"</span>.<span class=pl-en>format</span>(<span class=pl-v>IMAGE_SIZE</span>))</td> </tr> <tr> <td id="L213" class="blob-num js-line-number" data-line-number="213"></td> <td id="LC213" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L214" class="blob-num js-line-number" data-line-number="214"></td> <td id="LC214" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L215" class="blob-num js-line-number" data-line-number="215"></td> <td id="LC215" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[265]:</span></td> </tr> <tr> <td id="L216" class="blob-num js-line-number" data-line-number="216"></td> <td id="LC216" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L217" class="blob-num js-line-number" data-line-number="217"></td> <td id="LC217" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L218" class="blob-num js-line-number" data-line-number="218"></td> <td id="LC218" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>lis1</span> <span class=pl-c1>=</span> []</td> </tr> <tr> <td id="L219" class="blob-num js-line-number" data-line-number="219"></td> <td id="LC219" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>lis2</span> <span class=pl-c1>=</span> []</td> </tr> <tr> <td id="L220" class="blob-num js-line-number" data-line-number="220"></td> <td id="LC220" class="blob-code blob-code-inner js-file-line"><span class=pl-k>for</span> <span class=pl-s1>key</span>,<span class=pl-s1>val</span> <span class=pl-c1>in</span> <span class=pl-s1>dic</span>.<span class=pl-en>items</span>():</td> </tr> <tr> <td id="L221" class="blob-num js-line-number" data-line-number="221"></td> <td id="LC221" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>lis1</span>.<span class=pl-en>append</span>(<span class=pl-s1>val</span>)</td> </tr> <tr> <td id="L222" class="blob-num js-line-number" data-line-number="222"></td> <td id="LC222" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>lis2</span>.<span class=pl-en>append</span>(<span class=pl-s1>key</span>)</td> </tr> <tr> <td id="L223" class="blob-num js-line-number" data-line-number="223"></td> <td id="LC223" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L224" class="blob-num js-line-number" data-line-number="224"></td> <td id="LC224" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L225" class="blob-num js-line-number" data-line-number="225"></td> <td id="LC225" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[266]:</span></td> </tr> <tr> <td id="L226" class="blob-num js-line-number" data-line-number="226"></td> <td id="LC226" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L227" class="blob-num js-line-number" data-line-number="227"></td> <td id="LC227" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L228" class="blob-num js-line-number" data-line-number="228"></td> <td id="LC228" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>lis11</span> <span class=pl-c1>=</span> []</td> </tr> <tr> <td id="L229" class="blob-num js-line-number" data-line-number="229"></td> <td id="LC229" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>lis22</span> <span class=pl-c1>=</span> []</td> </tr> <tr> <td id="L230" class="blob-num js-line-number" data-line-number="230"></td> <td id="LC230" class="blob-code blob-code-inner js-file-line"><span class=pl-k>for</span> <span class=pl-s1>key</span>,<span class=pl-s1>val</span> <span class=pl-c1>in</span> <span class=pl-s1>dic1</span>.<span class=pl-en>items</span>():</td> </tr> <tr> <td id="L231" class="blob-num js-line-number" data-line-number="231"></td> <td id="LC231" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>lis11</span>.<span class=pl-en>append</span>(<span class=pl-s1>val</span>)</td> </tr> <tr> <td id="L232" class="blob-num js-line-number" data-line-number="232"></td> <td id="LC232" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>lis22</span>.<span class=pl-en>append</span>(<span class=pl-s1>key</span>)</td> </tr> <tr> <td id="L233" class="blob-num js-line-number" data-line-number="233"></td> <td id="LC233" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L234" class="blob-num js-line-number" data-line-number="234"></td> <td id="LC234" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L235" class="blob-num js-line-number" data-line-number="235"></td> <td id="LC235" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[267]:</span></td> </tr> <tr> <td id="L236" class="blob-num js-line-number" data-line-number="236"></td> <td id="LC236" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L237" class="blob-num js-line-number" data-line-number="237"></td> <td id="LC237" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L238" class="blob-num js-line-number" data-line-number="238"></td> <td id="LC238" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>data</span> <span class=pl-c1>=</span> {<span class=pl-s>'Name'</span>:<span class=pl-s1>lis2</span>, <span class=pl-s>'train'</span>:<span class=pl-s1>lis1</span>,<span class=pl-s>'test'</span>:<span class=pl-s1>lis11</span>}</td> </tr> <tr> <td id="L239" class="blob-num js-line-number" data-line-number="239"></td> <td id="LC239" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>data</span></td> </tr> <tr> <td id="L240" class="blob-num js-line-number" data-line-number="240"></td> <td id="LC240" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L241" class="blob-num js-line-number" data-line-number="241"></td> <td id="LC241" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L242" class="blob-num js-line-number" data-line-number="242"></td> <td id="LC242" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[268]:</span></td> </tr> <tr> <td id="L243" class="blob-num js-line-number" data-line-number="243"></td> <td id="LC243" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L244" class="blob-num js-line-number" data-line-number="244"></td> <td id="LC244" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L245" class="blob-num js-line-number" data-line-number="245"></td> <td id="LC245" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>pandas</span> <span class=pl-k>as</span> <span class=pl-s1>pd</span></td> </tr> <tr> <td id="L246" class="blob-num js-line-number" data-line-number="246"></td> <td id="LC246" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>df</span> <span class=pl-c1>=</span> <span class=pl-s1>pd</span>.<span class=pl-v>DataFrame</span>(<span class=pl-s1>data</span>)</td> </tr> <tr> <td id="L247" class="blob-num js-line-number" data-line-number="247"></td> <td id="LC247" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>df</span></td> </tr> <tr> <td id="L248" class="blob-num js-line-number" data-line-number="248"></td> <td id="LC248" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L249" class="blob-num js-line-number" data-line-number="249"></td> <td id="LC249" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L250" class="blob-num js-line-number" data-line-number="250"></td> <td id="LC250" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ## 2.2 ) Visualizing some Random Images</span></td> </tr> <tr> <td id="L251" class="blob-num js-line-number" data-line-number="251"></td> <td id="LC251" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L252" class="blob-num js-line-number" data-line-number="252"></td> <td id="LC252" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[269]:</span></td> </tr> <tr> <td id="L253" class="blob-num js-line-number" data-line-number="253"></td> <td id="LC253" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L254" class="blob-num js-line-number" data-line-number="254"></td> <td id="LC254" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L255" class="blob-num js-line-number" data-line-number="255"></td> <td id="LC255" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>ax</span> <span class=pl-c1>=</span> <span class=pl-s1>df</span>.<span class=pl-s1>plot</span>.<span class=pl-en>bar</span>(<span class=pl-s1>x</span><span class=pl-c1>=</span><span class=pl-s>'Name'</span>, <span class=pl-s1>y</span><span class=pl-c1>=</span>[<span class=pl-s>'train'</span>,<span class=pl-s>'test'</span>], <span class=pl-s1>rot</span><span class=pl-c1>=</span><span class=pl-c1>0</span>)</td> </tr> <tr> <td id="L256" class="blob-num js-line-number" data-line-number="256"></td> <td id="LC256" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>title</span>(<span class=pl-s>'Training sets Input'</span>)</td> </tr> <tr> <td id="L257" class="blob-num js-line-number" data-line-number="257"></td> <td id="LC257" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L258" class="blob-num js-line-number" data-line-number="258"></td> <td id="LC258" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L259" class="blob-num js-line-number" data-line-number="259"></td> <td id="LC259" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[270]:</span></td> </tr> <tr> <td id="L260" class="blob-num js-line-number" data-line-number="260"></td> <td id="LC260" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L261" class="blob-num js-line-number" data-line-number="261"></td> <td id="LC261" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L262" class="blob-num js-line-number" data-line-number="262"></td> <td id="LC262" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>pie</span>(<span class=pl-s1>lis1</span>,</td> </tr> <tr> <td id="L263" class="blob-num js-line-number" data-line-number="263"></td> <td id="LC263" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>explode</span><span class=pl-c1>=</span>(<span class=pl-c1>0</span>, <span class=pl-c1>0</span>, <span class=pl-c1>0</span>, <span class=pl-c1>0</span>, <span class=pl-c1>0</span>, <span class=pl-c1>0</span>) , </td> </tr> <tr> <td id="L264" class="blob-num js-line-number" data-line-number="264"></td> <td id="LC264" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>labels</span><span class=pl-c1>=</span><span class=pl-s1>lis2</span>,</td> </tr> <tr> <td id="L265" class="blob-num js-line-number" data-line-number="265"></td> <td id="LC265" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>autopct</span><span class=pl-c1>=</span><span class=pl-s>'%1.1f%%'</span>)</td> </tr> <tr> <td id="L266" class="blob-num js-line-number" data-line-number="266"></td> <td id="LC266" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>axis</span>(<span class=pl-s>'equal'</span>)</td> </tr> <tr> <td id="L267" class="blob-num js-line-number" data-line-number="267"></td> <td id="LC267" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>title</span>(<span class=pl-s>'Proportion of each observed category'</span>)</td> </tr> <tr> <td id="L268" class="blob-num js-line-number" data-line-number="268"></td> <td id="LC268" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>show</span>()</td> </tr> <tr> <td id="L269" class="blob-num js-line-number" data-line-number="269"></td> <td id="LC269" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L270" class="blob-num js-line-number" data-line-number="270"></td> <td id="LC270" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L271" class="blob-num js-line-number" data-line-number="271"></td> <td id="LC271" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[271]:</span></td> </tr> <tr> <td id="L272" class="blob-num js-line-number" data-line-number="272"></td> <td id="LC272" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L273" class="blob-num js-line-number" data-line-number="273"></td> <td id="LC273" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L274" class="blob-num js-line-number" data-line-number="274"></td> <td id="LC274" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>random</span> <span class=pl-k>as</span> <span class=pl-s1>rn</span></td> </tr> <tr> <td id="L275" class="blob-num js-line-number" data-line-number="275"></td> <td id="LC275" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>fig</span>,<span class=pl-s1>ax</span><span class=pl-c1>=</span><span class=pl-s1>plt</span>.<span class=pl-en>subplots</span>(<span class=pl-c1>5</span>,<span class=pl-c1>3</span>)</td> </tr> <tr> <td id="L276" class="blob-num js-line-number" data-line-number="276"></td> <td id="LC276" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>fig</span>.<span class=pl-en>set_size_inches</span>(<span class=pl-c1>15</span>,<span class=pl-c1>15</span>)</td> </tr> <tr> <td id="L277" class="blob-num js-line-number" data-line-number="277"></td> <td id="LC277" class="blob-code blob-code-inner js-file-line"><span class=pl-k>for</span> <span class=pl-s1>i</span> <span class=pl-c1>in</span> <span class=pl-en>range</span>(<span class=pl-c1>5</span>):</td> </tr> <tr> <td id="L278" class="blob-num js-line-number" data-line-number="278"></td> <td id="LC278" class="blob-code blob-code-inner js-file-line"> <span class=pl-k>for</span> <span class=pl-s1>j</span> <span class=pl-c1>in</span> <span class=pl-en>range</span> (<span class=pl-c1>3</span>):</td> </tr> <tr> <td id="L279" class="blob-num js-line-number" data-line-number="279"></td> <td id="LC279" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>l</span><span class=pl-c1>=</span><span class=pl-s1>rn</span>.<span class=pl-en>randint</span>(<span class=pl-c1>0</span>,<span class=pl-en>len</span>(<span class=pl-v>Z</span>))</td> </tr> <tr> <td id="L280" class="blob-num js-line-number" data-line-number="280"></td> <td id="LC280" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>ax</span>[<span class=pl-s1>i</span>,<span class=pl-s1>j</span>].<span class=pl-en>imshow</span>(<span class=pl-v>X</span>[<span class=pl-s1>l</span>])</td> </tr> <tr> <td id="L281" class="blob-num js-line-number" data-line-number="281"></td> <td id="LC281" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>ax</span>[<span class=pl-s1>i</span>,<span class=pl-s1>j</span>].<span class=pl-en>set_title</span>(<span class=pl-s>'Intel_Image: '</span><span class=pl-c1>+</span><span class=pl-v>Z</span>[<span class=pl-s1>l</span>])</td> </tr> <tr> <td id="L282" class="blob-num js-line-number" data-line-number="282"></td> <td id="LC282" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L283" class="blob-num js-line-number" data-line-number="283"></td> <td id="LC283" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>tight_layout</span>()</td> </tr> <tr> <td id="L284" class="blob-num js-line-number" data-line-number="284"></td> <td id="LC284" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L285" class="blob-num js-line-number" data-line-number="285"></td> <td id="LC285" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L286" class="blob-num js-line-number" data-line-number="286"></td> <td id="LC286" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Preprocessing the Training set</span></td> </tr> <tr> <td id="L287" class="blob-num js-line-number" data-line-number="287"></td> <td id="LC287" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L288" class="blob-num js-line-number" data-line-number="288"></td> <td id="LC288" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[272]:</span></td> </tr> <tr> <td id="L289" class="blob-num js-line-number" data-line-number="289"></td> <td id="LC289" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L290" class="blob-num js-line-number" data-line-number="290"></td> <td id="LC290" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L291" class="blob-num js-line-number" data-line-number="291"></td> <td id="LC291" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>train_datagen</span> <span class=pl-c1>=</span> <span class=pl-v>ImageDataGenerator</span>(<span class=pl-s1>rescale</span> <span class=pl-c1>=</span> <span class=pl-c1>1.</span><span class=pl-c1>/</span><span class=pl-c1>255</span>,</td> </tr> <tr> <td id="L292" class="blob-num js-line-number" data-line-number="292"></td> <td id="LC292" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>shear_range</span> <span class=pl-c1>=</span> <span class=pl-c1>0.2</span>,</td> </tr> <tr> <td id="L293" class="blob-num js-line-number" data-line-number="293"></td> <td id="LC293" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>zoom_range</span> <span class=pl-c1>=</span> <span class=pl-c1>0.2</span>,</td> </tr> <tr> <td id="L294" class="blob-num js-line-number" data-line-number="294"></td> <td id="LC294" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>horizontal_flip</span> <span class=pl-c1>=</span> <span class=pl-c1>True</span>)</td> </tr> <tr> <td id="L295" class="blob-num js-line-number" data-line-number="295"></td> <td id="LC295" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>seg_train</span> <span class=pl-c1>=</span> <span class=pl-s1>train_datagen</span>.<span class=pl-en>flow_from_directory</span>(<span class=pl-s>'111880_269359_bundle_archive/seg_train/seg_train'</span>,</td> </tr> <tr> <td id="L296" class="blob-num js-line-number" data-line-number="296"></td> <td id="LC296" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>target_size</span> <span class=pl-c1>=</span> (<span class=pl-c1>64</span>, <span class=pl-c1>64</span>),</td> </tr> <tr> <td id="L297" class="blob-num js-line-number" data-line-number="297"></td> <td id="LC297" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>batch_size</span> <span class=pl-c1>=</span> <span class=pl-c1>32</span>,</td> </tr> <tr> <td id="L298" class="blob-num js-line-number" data-line-number="298"></td> <td id="LC298" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>class_mode</span> <span class=pl-c1>=</span> <span class=pl-s>'categorical'</span>)</td> </tr> <tr> <td id="L299" class="blob-num js-line-number" data-line-number="299"></td> <td id="LC299" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L300" class="blob-num js-line-number" data-line-number="300"></td> <td id="LC300" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L301" class="blob-num js-line-number" data-line-number="301"></td> <td id="LC301" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Preprocessing the Test set</span></td> </tr> <tr> <td id="L302" class="blob-num js-line-number" data-line-number="302"></td> <td id="LC302" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L303" class="blob-num js-line-number" data-line-number="303"></td> <td id="LC303" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[273]:</span></td> </tr> <tr> <td id="L304" class="blob-num js-line-number" data-line-number="304"></td> <td id="LC304" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L305" class="blob-num js-line-number" data-line-number="305"></td> <td id="LC305" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L306" class="blob-num js-line-number" data-line-number="306"></td> <td id="LC306" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>test_datagen</span> <span class=pl-c1>=</span> <span class=pl-v>ImageDataGenerator</span>(<span class=pl-s1>rescale</span> <span class=pl-c1>=</span> <span class=pl-c1>1.</span><span class=pl-c1>/</span><span class=pl-c1>255</span>)</td> </tr> <tr> <td id="L307" class="blob-num js-line-number" data-line-number="307"></td> <td id="LC307" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>seg_test</span> <span class=pl-c1>=</span> <span class=pl-s1>test_datagen</span>.<span class=pl-en>flow_from_directory</span>(<span class=pl-s>'111880_269359_bundle_archive/seg_test/seg_test'</span>,</td> </tr> <tr> <td id="L308" class="blob-num js-line-number" data-line-number="308"></td> <td id="LC308" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>target_size</span> <span class=pl-c1>=</span> (<span class=pl-c1>64</span>, <span class=pl-c1>64</span>),</td> </tr> <tr> <td id="L309" class="blob-num js-line-number" data-line-number="309"></td> <td id="LC309" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>batch_size</span> <span class=pl-c1>=</span> <span class=pl-c1>32</span>,</td> </tr> <tr> <td id="L310" class="blob-num js-line-number" data-line-number="310"></td> <td id="LC310" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>class_mode</span> <span class=pl-c1>=</span> <span class=pl-s>'categorical'</span>)</td> </tr> <tr> <td id="L311" class="blob-num js-line-number" data-line-number="311"></td> <td id="LC311" class="blob-code blob-code-inner js-file-line"><span class=pl-v>IMAGE_SIZE</span> <span class=pl-c1>=</span> (<span class=pl-c1>64</span>,<span class=pl-c1>64</span>)</td> </tr> <tr> <td id="L312" class="blob-num js-line-number" data-line-number="312"></td> <td id="LC312" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L313" class="blob-num js-line-number" data-line-number="313"></td> <td id="LC313" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L314" class="blob-num js-line-number" data-line-number="314"></td> <td id="LC314" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ## Part 2 - Building the CNN</span></td> </tr> <tr> <td id="L315" class="blob-num js-line-number" data-line-number="315"></td> <td id="LC315" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L316" class="blob-num js-line-number" data-line-number="316"></td> <td id="LC316" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Initialising the CNN</span></td> </tr> <tr> <td id="L317" class="blob-num js-line-number" data-line-number="317"></td> <td id="LC317" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L318" class="blob-num js-line-number" data-line-number="318"></td> <td id="LC318" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[281]:</span></td> </tr> <tr> <td id="L319" class="blob-num js-line-number" data-line-number="319"></td> <td id="LC319" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L320" class="blob-num js-line-number" data-line-number="320"></td> <td id="LC320" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L321" class="blob-num js-line-number" data-line-number="321"></td> <td id="LC321" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>cnn</span> <span class=pl-c1>=</span> <span class=pl-s1>tf</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>models</span>.<span class=pl-v>Sequential</span>()</td> </tr> <tr> <td id="L322" class="blob-num js-line-number" data-line-number="322"></td> <td id="LC322" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L323" class="blob-num js-line-number" data-line-number="323"></td> <td id="LC323" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L324" class="blob-num js-line-number" data-line-number="324"></td> <td id="LC324" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Step 1 - Convolution</span></td> </tr> <tr> <td id="L325" class="blob-num js-line-number" data-line-number="325"></td> <td id="LC325" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L326" class="blob-num js-line-number" data-line-number="326"></td> <td id="LC326" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[282]:</span></td> </tr> <tr> <td id="L327" class="blob-num js-line-number" data-line-number="327"></td> <td id="LC327" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L328" class="blob-num js-line-number" data-line-number="328"></td> <td id="LC328" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L329" class="blob-num js-line-number" data-line-number="329"></td> <td id="LC329" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>cnn</span>.<span class=pl-en>add</span>(<span class=pl-s1>tf</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>layers</span>.<span class=pl-v>Conv2D</span>(<span class=pl-s1>filters</span><span class=pl-c1>=</span><span class=pl-c1>32</span>, <span class=pl-s1>kernel_size</span><span class=pl-c1>=</span><span class=pl-c1>3</span>, <span class=pl-s1>activation</span><span class=pl-c1>=</span><span class=pl-s>'relu'</span>, <span class=pl-s1>input_shape</span><span class=pl-c1>=</span>[<span class=pl-c1>64</span>, <span class=pl-c1>64</span>, <span class=pl-c1>3</span>]))</td> </tr> <tr> <td id="L330" class="blob-num js-line-number" data-line-number="330"></td> <td id="LC330" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L331" class="blob-num js-line-number" data-line-number="331"></td> <td id="LC331" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L332" class="blob-num js-line-number" data-line-number="332"></td> <td id="LC332" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Step 2 - Pooling</span></td> </tr> <tr> <td id="L333" class="blob-num js-line-number" data-line-number="333"></td> <td id="LC333" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L334" class="blob-num js-line-number" data-line-number="334"></td> <td id="LC334" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[283]:</span></td> </tr> <tr> <td id="L335" class="blob-num js-line-number" data-line-number="335"></td> <td id="LC335" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L336" class="blob-num js-line-number" data-line-number="336"></td> <td id="LC336" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L337" class="blob-num js-line-number" data-line-number="337"></td> <td id="LC337" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>cnn</span>.<span class=pl-en>add</span>(<span class=pl-s1>tf</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>layers</span>.<span class=pl-v>MaxPool2D</span>(<span class=pl-s1>pool_size</span><span class=pl-c1>=</span><span class=pl-c1>2</span>, <span class=pl-s1>strides</span><span class=pl-c1>=</span><span class=pl-c1>2</span>))</td> </tr> <tr> <td id="L338" class="blob-num js-line-number" data-line-number="338"></td> <td id="LC338" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L339" class="blob-num js-line-number" data-line-number="339"></td> <td id="LC339" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L340" class="blob-num js-line-number" data-line-number="340"></td> <td id="LC340" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Adding a second convolutional layer</span></td> </tr> <tr> <td id="L341" class="blob-num js-line-number" data-line-number="341"></td> <td id="LC341" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L342" class="blob-num js-line-number" data-line-number="342"></td> <td id="LC342" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[284]:</span></td> </tr> <tr> <td id="L343" class="blob-num js-line-number" data-line-number="343"></td> <td id="LC343" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L344" class="blob-num js-line-number" data-line-number="344"></td> <td id="LC344" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L345" class="blob-num js-line-number" data-line-number="345"></td> <td id="LC345" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>cnn</span>.<span class=pl-en>add</span>(<span class=pl-s1>tf</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>layers</span>.<span class=pl-v>Conv2D</span>(<span class=pl-s1>filters</span><span class=pl-c1>=</span><span class=pl-c1>32</span>, <span class=pl-s1>kernel_size</span><span class=pl-c1>=</span><span class=pl-c1>3</span>, <span class=pl-s1>activation</span><span class=pl-c1>=</span><span class=pl-s>'relu'</span>))</td> </tr> <tr> <td id="L346" class="blob-num js-line-number" data-line-number="346"></td> <td id="LC346" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>cnn</span>.<span class=pl-en>add</span>(<span class=pl-s1>tf</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>layers</span>.<span class=pl-v>MaxPool2D</span>(<span class=pl-s1>pool_size</span><span class=pl-c1>=</span><span class=pl-c1>2</span>, <span class=pl-s1>strides</span><span class=pl-c1>=</span><span class=pl-c1>2</span>))</td> </tr> <tr> <td id="L347" class="blob-num js-line-number" data-line-number="347"></td> <td id="LC347" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L348" class="blob-num js-line-number" data-line-number="348"></td> <td id="LC348" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L349" class="blob-num js-line-number" data-line-number="349"></td> <td id="LC349" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Step 3 - Flattening</span></td> </tr> <tr> <td id="L350" class="blob-num js-line-number" data-line-number="350"></td> <td id="LC350" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L351" class="blob-num js-line-number" data-line-number="351"></td> <td id="LC351" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[285]:</span></td> </tr> <tr> <td id="L352" class="blob-num js-line-number" data-line-number="352"></td> <td id="LC352" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L353" class="blob-num js-line-number" data-line-number="353"></td> <td id="LC353" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L354" class="blob-num js-line-number" data-line-number="354"></td> <td id="LC354" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>cnn</span>.<span class=pl-en>add</span>(<span class=pl-s1>tf</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>layers</span>.<span class=pl-v>Flatten</span>())</td> </tr> <tr> <td id="L355" class="blob-num js-line-number" data-line-number="355"></td> <td id="LC355" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L356" class="blob-num js-line-number" data-line-number="356"></td> <td id="LC356" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L357" class="blob-num js-line-number" data-line-number="357"></td> <td id="LC357" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Step 4 - Full Connection</span></td> </tr> <tr> <td id="L358" class="blob-num js-line-number" data-line-number="358"></td> <td id="LC358" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L359" class="blob-num js-line-number" data-line-number="359"></td> <td id="LC359" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[286]:</span></td> </tr> <tr> <td id="L360" class="blob-num js-line-number" data-line-number="360"></td> <td id="LC360" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L361" class="blob-num js-line-number" data-line-number="361"></td> <td id="LC361" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L362" class="blob-num js-line-number" data-line-number="362"></td> <td id="LC362" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>cnn</span>.<span class=pl-en>add</span>(<span class=pl-s1>tf</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>layers</span>.<span class=pl-v>Dense</span>(<span class=pl-s1>units</span><span class=pl-c1>=</span><span class=pl-c1>128</span>, <span class=pl-s1>activation</span><span class=pl-c1>=</span><span class=pl-s>'relu'</span>))</td> </tr> <tr> <td id="L363" class="blob-num js-line-number" data-line-number="363"></td> <td id="LC363" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L364" class="blob-num js-line-number" data-line-number="364"></td> <td id="LC364" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L365" class="blob-num js-line-number" data-line-number="365"></td> <td id="LC365" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Step 5 - Output Layer</span></td> </tr> <tr> <td id="L366" class="blob-num js-line-number" data-line-number="366"></td> <td id="LC366" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L367" class="blob-num js-line-number" data-line-number="367"></td> <td id="LC367" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[287]:</span></td> </tr> <tr> <td id="L368" class="blob-num js-line-number" data-line-number="368"></td> <td id="LC368" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L369" class="blob-num js-line-number" data-line-number="369"></td> <td id="LC369" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L370" class="blob-num js-line-number" data-line-number="370"></td> <td id="LC370" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>cnn</span>.<span class=pl-en>add</span>(<span class=pl-s1>tf</span>.<span class=pl-s1>keras</span>.<span class=pl-s1>layers</span>.<span class=pl-v>Dense</span>(<span class=pl-s1>units</span><span class=pl-c1>=</span><span class=pl-c1>6</span>, <span class=pl-s1>activation</span><span class=pl-c1>=</span><span class=pl-s>'softmax'</span>))</td> </tr> <tr> <td id="L371" class="blob-num js-line-number" data-line-number="371"></td> <td id="LC371" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L372" class="blob-num js-line-number" data-line-number="372"></td> <td id="LC372" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L373" class="blob-num js-line-number" data-line-number="373"></td> <td id="LC373" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[288]:</span></td> </tr> <tr> <td id="L374" class="blob-num js-line-number" data-line-number="374"></td> <td id="LC374" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L375" class="blob-num js-line-number" data-line-number="375"></td> <td id="LC375" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L376" class="blob-num js-line-number" data-line-number="376"></td> <td id="LC376" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>cnn</span>.<span class=pl-en>summary</span>()</td> </tr> <tr> <td id="L377" class="blob-num js-line-number" data-line-number="377"></td> <td id="LC377" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L378" class="blob-num js-line-number" data-line-number="378"></td> <td id="LC378" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L379" class="blob-num js-line-number" data-line-number="379"></td> <td id="LC379" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ## Part 3 - Training the CNN</span></td> </tr> <tr> <td id="L380" class="blob-num js-line-number" data-line-number="380"></td> <td id="LC380" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L381" class="blob-num js-line-number" data-line-number="381"></td> <td id="LC381" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Compiling the CNN</span></td> </tr> <tr> <td id="L382" class="blob-num js-line-number" data-line-number="382"></td> <td id="LC382" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L383" class="blob-num js-line-number" data-line-number="383"></td> <td id="LC383" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[289]:</span></td> </tr> <tr> <td id="L384" class="blob-num js-line-number" data-line-number="384"></td> <td id="LC384" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L385" class="blob-num js-line-number" data-line-number="385"></td> <td id="LC385" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L386" class="blob-num js-line-number" data-line-number="386"></td> <td id="LC386" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>cnn</span>.<span class=pl-en>compile</span>(<span class=pl-s1>optimizer</span> <span class=pl-c1>=</span> <span class=pl-s>'adam'</span>, <span class=pl-s1>loss</span> <span class=pl-c1>=</span> <span class=pl-s>'categorical_crossentropy'</span>, <span class=pl-s1>metrics</span> <span class=pl-c1>=</span> [<span class=pl-s>'accuracy'</span>])</td> </tr> <tr> <td id="L387" class="blob-num js-line-number" data-line-number="387"></td> <td id="LC387" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L388" class="blob-num js-line-number" data-line-number="388"></td> <td id="LC388" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L389" class="blob-num js-line-number" data-line-number="389"></td> <td id="LC389" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ### Training the CNN on the Training set and evaluating it on the Test set</span></td> </tr> <tr> <td id="L390" class="blob-num js-line-number" data-line-number="390"></td> <td id="LC390" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L391" class="blob-num js-line-number" data-line-number="391"></td> <td id="LC391" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[290]:</span></td> </tr> <tr> <td id="L392" class="blob-num js-line-number" data-line-number="392"></td> <td id="LC392" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L393" class="blob-num js-line-number" data-line-number="393"></td> <td id="LC393" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L394" class="blob-num js-line-number" data-line-number="394"></td> <td id="LC394" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>trained</span><span class=pl-c1>=</span> <span class=pl-s1>cnn</span>.<span class=pl-en>fit</span>(<span class=pl-s1>x</span> <span class=pl-c1>=</span> <span class=pl-s1>seg_train</span>, <span class=pl-s1>validation_data</span> <span class=pl-c1>=</span> <span class=pl-s1>seg_test</span>, <span class=pl-s1>epochs</span> <span class=pl-c1>=</span> <span class=pl-c1>25</span>)</td> </tr> <tr> <td id="L395" class="blob-num js-line-number" data-line-number="395"></td> <td id="LC395" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L396" class="blob-num js-line-number" data-line-number="396"></td> <td id="LC396" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L397" class="blob-num js-line-number" data-line-number="397"></td> <td id="LC397" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ## Evaluating the Model Performance</span></td> </tr> <tr> <td id="L398" class="blob-num js-line-number" data-line-number="398"></td> <td id="LC398" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L399" class="blob-num js-line-number" data-line-number="399"></td> <td id="LC399" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[291]:</span></td> </tr> <tr> <td id="L400" class="blob-num js-line-number" data-line-number="400"></td> <td id="LC400" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L401" class="blob-num js-line-number" data-line-number="401"></td> <td id="LC401" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L402" class="blob-num js-line-number" data-line-number="402"></td> <td id="LC402" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>plot</span>(<span class=pl-s1>trained</span>.<span class=pl-s1>history</span>[<span class=pl-s>'loss'</span>])</td> </tr> <tr> <td id="L403" class="blob-num js-line-number" data-line-number="403"></td> <td id="LC403" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>plot</span>(<span class=pl-s1>trained</span>.<span class=pl-s1>history</span>[<span class=pl-s>'val_loss'</span>])</td> </tr> <tr> <td id="L404" class="blob-num js-line-number" data-line-number="404"></td> <td id="LC404" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>title</span>(<span class=pl-s>'Model Loss'</span>)</td> </tr> <tr> <td id="L405" class="blob-num js-line-number" data-line-number="405"></td> <td id="LC405" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>ylabel</span>(<span class=pl-s>'Loss'</span>)</td> </tr> <tr> <td id="L406" class="blob-num js-line-number" data-line-number="406"></td> <td id="LC406" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>xlabel</span>(<span class=pl-s>'Epochs'</span>)</td> </tr> <tr> <td id="L407" class="blob-num js-line-number" data-line-number="407"></td> <td id="LC407" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>legend</span>([<span class=pl-s>'train'</span>, <span class=pl-s>'test'</span>])</td> </tr> <tr> <td id="L408" class="blob-num js-line-number" data-line-number="408"></td> <td id="LC408" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>show</span>()</td> </tr> <tr> <td id="L409" class="blob-num js-line-number" data-line-number="409"></td> <td id="LC409" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L410" class="blob-num js-line-number" data-line-number="410"></td> <td id="LC410" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L411" class="blob-num js-line-number" data-line-number="411"></td> <td id="LC411" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[292]:</span></td> </tr> <tr> <td id="L412" class="blob-num js-line-number" data-line-number="412"></td> <td id="LC412" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L413" class="blob-num js-line-number" data-line-number="413"></td> <td id="LC413" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L414" class="blob-num js-line-number" data-line-number="414"></td> <td id="LC414" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>plot</span>(<span class=pl-s1>trained</span>.<span class=pl-s1>history</span>[<span class=pl-s>'accuracy'</span>])</td> </tr> <tr> <td id="L415" class="blob-num js-line-number" data-line-number="415"></td> <td id="LC415" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>plot</span>(<span class=pl-s1>trained</span>.<span class=pl-s1>history</span>[<span class=pl-s>'val_accuracy'</span>])</td> </tr> <tr> <td id="L416" class="blob-num js-line-number" data-line-number="416"></td> <td id="LC416" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>title</span>(<span class=pl-s>'Model Accuracy'</span>)</td> </tr> <tr> <td id="L417" class="blob-num js-line-number" data-line-number="417"></td> <td id="LC417" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>ylabel</span>(<span class=pl-s>'Accuracy'</span>)</td> </tr> <tr> <td id="L418" class="blob-num js-line-number" data-line-number="418"></td> <td id="LC418" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>xlabel</span>(<span class=pl-s>'Epochs'</span>)</td> </tr> <tr> <td id="L419" class="blob-num js-line-number" data-line-number="419"></td> <td id="LC419" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>legend</span>([<span class=pl-s>'train'</span>, <span class=pl-s>'test'</span>])</td> </tr> <tr> <td id="L420" class="blob-num js-line-number" data-line-number="420"></td> <td id="LC420" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>plt</span>.<span class=pl-en>show</span>()</td> </tr> <tr> <td id="L421" class="blob-num js-line-number" data-line-number="421"></td> <td id="LC421" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L422" class="blob-num js-line-number" data-line-number="422"></td> <td id="LC422" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L423" class="blob-num js-line-number" data-line-number="423"></td> <td id="LC423" class="blob-code blob-code-inner js-file-line"><span class=pl-c># ## Visualizing Predictons on the Validation Set</span></td> </tr> <tr> <td id="L424" class="blob-num js-line-number" data-line-number="424"></td> <td id="LC424" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L425" class="blob-num js-line-number" data-line-number="425"></td> <td id="LC425" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[298]:</span></td> </tr> <tr> <td id="L426" class="blob-num js-line-number" data-line-number="426"></td> <td id="LC426" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L427" class="blob-num js-line-number" data-line-number="427"></td> <td id="LC427" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L428" class="blob-num js-line-number" data-line-number="428"></td> <td id="LC428" class="blob-code blob-code-inner js-file-line"><span class=pl-k>import</span> <span class=pl-s1>numpy</span> <span class=pl-k>as</span> <span class=pl-s1>np</span></td> </tr> <tr> <td id="L429" class="blob-num js-line-number" data-line-number="429"></td> <td id="LC429" class="blob-code blob-code-inner js-file-line"><span class=pl-k>from</span> <span class=pl-s1>keras</span>.<span class=pl-s1>preprocessing</span> <span class=pl-k>import</span> <span class=pl-s1>image</span></td> </tr> <tr> <td id="L430" class="blob-num js-line-number" data-line-number="430"></td> <td id="LC430" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>test_image1</span> <span class=pl-c1>=</span> <span class=pl-s1>image</span>.<span class=pl-en>load_img</span>(<span class=pl-s>'111880_269359_bundle_archive/seg_pred/seg_pred/5.jpg'</span>, <span class=pl-s1>target_size</span> <span class=pl-c1>=</span> (<span class=pl-c1>64</span>, <span class=pl-c1>64</span>))</td> </tr> <tr> <td id="L431" class="blob-num js-line-number" data-line-number="431"></td> <td id="LC431" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>test_image</span> <span class=pl-c1>=</span> <span class=pl-s1>image</span>.<span class=pl-en>img_to_array</span>(<span class=pl-s1>test_image1</span>)</td> </tr> <tr> <td id="L432" class="blob-num js-line-number" data-line-number="432"></td> <td id="LC432" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>test_image</span> <span class=pl-c1>=</span> <span class=pl-s1>np</span>.<span class=pl-en>expand_dims</span>(<span class=pl-s1>test_image</span>, <span class=pl-s1>axis</span> <span class=pl-c1>=</span> <span class=pl-c1>0</span>)</td> </tr> <tr> <td id="L433" class="blob-num js-line-number" data-line-number="433"></td> <td id="LC433" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>result</span> <span class=pl-c1>=</span> <span class=pl-s1>cnn</span>.<span class=pl-en>predict</span>(<span class=pl-s1>test_image</span>)</td> </tr> <tr> <td id="L434" class="blob-num js-line-number" data-line-number="434"></td> <td id="LC434" class="blob-code blob-code-inner js-file-line"><span class=pl-k>if</span> <span class=pl-s1>result</span>[<span class=pl-c1>0</span>][<span class=pl-c1>0</span>] <span class=pl-c1>==</span> <span class=pl-c1>1</span>:</td> </tr> <tr> <td id="L435" class="blob-num js-line-number" data-line-number="435"></td> <td id="LC435" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>prediction</span> <span class=pl-c1>=</span> <span class=pl-s>'Building'</span></td> </tr> <tr> <td id="L436" class="blob-num js-line-number" data-line-number="436"></td> <td id="LC436" class="blob-code blob-code-inner js-file-line"><span class=pl-k>elif</span> <span class=pl-s1>result</span>[<span class=pl-c1>0</span>][<span class=pl-c1>1</span>] <span class=pl-c1>==</span> <span class=pl-c1>1</span>:</td> </tr> <tr> <td id="L437" class="blob-num js-line-number" data-line-number="437"></td> <td id="LC437" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>prediction</span> <span class=pl-c1>=</span> <span class=pl-s>'Forest'</span></td> </tr> <tr> <td id="L438" class="blob-num js-line-number" data-line-number="438"></td> <td id="LC438" class="blob-code blob-code-inner js-file-line"><span class=pl-k>elif</span> <span class=pl-s1>result</span>[<span class=pl-c1>0</span>][<span class=pl-c1>2</span>] <span class=pl-c1>==</span> <span class=pl-c1>1</span>:</td> </tr> <tr> <td id="L439" class="blob-num js-line-number" data-line-number="439"></td> <td id="LC439" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>prediction</span> <span class=pl-c1>=</span> <span class=pl-s>'Glacier'</span></td> </tr> <tr> <td id="L440" class="blob-num js-line-number" data-line-number="440"></td> <td id="LC440" class="blob-code blob-code-inner js-file-line"><span class=pl-k>elif</span> <span class=pl-s1>result</span>[<span class=pl-c1>0</span>][<span class=pl-c1>3</span>] <span class=pl-c1>==</span> <span class=pl-c1>1</span>:</td> </tr> <tr> <td id="L441" class="blob-num js-line-number" data-line-number="441"></td> <td id="LC441" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>prediction</span> <span class=pl-c1>=</span> <span class=pl-s>'Mountain'</span></td> </tr> <tr> <td id="L442" class="blob-num js-line-number" data-line-number="442"></td> <td id="LC442" class="blob-code blob-code-inner js-file-line"><span class=pl-k>elif</span> <span class=pl-s1>result</span>[<span class=pl-c1>0</span>][<span class=pl-c1>4</span>] <span class=pl-c1>==</span> <span class=pl-c1>1</span>:</td> </tr> <tr> <td id="L443" class="blob-num js-line-number" data-line-number="443"></td> <td id="LC443" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>prediction</span> <span class=pl-c1>=</span> <span class=pl-s>'Sea'</span></td> </tr> <tr> <td id="L444" class="blob-num js-line-number" data-line-number="444"></td> <td id="LC444" class="blob-code blob-code-inner js-file-line"><span class=pl-k>elif</span> <span class=pl-s1>result</span>[<span class=pl-c1>0</span>][<span class=pl-c1>5</span>] <span class=pl-c1>==</span> <span class=pl-c1>1</span>:</td> </tr> <tr> <td id="L445" class="blob-num js-line-number" data-line-number="445"></td> <td id="LC445" class="blob-code blob-code-inner js-file-line"> <span class=pl-s1>prediction</span> <span class=pl-c1>=</span> <span class=pl-s>'Street'</span></td> </tr> <tr> <td id="L446" class="blob-num js-line-number" data-line-number="446"></td> <td id="LC446" class="blob-code blob-code-inner js-file-line"><span class=pl-k>else</span>:</td> </tr> <tr> <td id="L447" class="blob-num js-line-number" data-line-number="447"></td> <td id="LC447" class="blob-code blob-code-inner js-file-line"> <span class=pl-en>print</span>(<span class=pl-s>"Error"</span>)</td> </tr> <tr> <td id="L448" class="blob-num js-line-number" data-line-number="448"></td> <td id="LC448" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L449" class="blob-num js-line-number" data-line-number="449"></td> <td id="LC449" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L450" class="blob-num js-line-number" data-line-number="450"></td> <td id="LC450" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[297]:</span></td> </tr> <tr> <td id="L451" class="blob-num js-line-number" data-line-number="451"></td> <td id="LC451" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L452" class="blob-num js-line-number" data-line-number="452"></td> <td id="LC452" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L453" class="blob-num js-line-number" data-line-number="453"></td> <td id="LC453" class="blob-code blob-code-inner js-file-line"><span class=pl-s1>result</span></td> </tr> <tr> <td id="L454" class="blob-num js-line-number" data-line-number="454"></td> <td id="LC454" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L455" class="blob-num js-line-number" data-line-number="455"></td> <td id="LC455" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L456" class="blob-num js-line-number" data-line-number="456"></td> <td id="LC456" class="blob-code blob-code-inner js-file-line"><span class=pl-c># In[299]:</span></td> </tr> <tr> <td id="L457" class="blob-num js-line-number" data-line-number="457"></td> <td id="LC457" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L458" class="blob-num js-line-number" data-line-number="458"></td> <td id="LC458" class="blob-code blob-code-inner js-file-line"> </td> </tr> <tr> <td id="L459" class="blob-num js-line-number" data-line-number="459"></td> <td id="LC459" class="blob-code blob-code-inner js-file-line"><span class=pl-en>print</span>(<span class=pl-s1>prediction</span>)</td> </tr> 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5

ad3e9b467042b664880d401cd499df829e241e47

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Python

ballpark/cashflows/admin.py

keyvanm/ballpark

90ca6ac355319f159fa0836f30df487ee8e72ddd

[ "MIT" ]

null

ballpark/cashflows/admin.py

keyvanm/ballpark

90ca6ac355319f159fa0836f30df487ee8e72ddd

[ "MIT" ]

null

ballpark/cashflows/admin.py

keyvanm/ballpark

90ca6ac355319f159fa0836f30df487ee8e72ddd

[ "MIT" ]

null

from django.contrib import admin from .models import * # Register your models here. admin.site.register(GenericOnetimeIncome) admin.site.register(GenericRecurringIncome) admin.site.register(GenericOnetimeExpense) admin.site.register(GenericRecurringExpense)

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py

Python

research/steve/toy_demo.py

jdavidagudelo/tensorflow-models

6f019beec73b01861363bf717706e27f4210b979

[ "Apache-2.0" ]

1

2021-05-17T01:42:29.000Z

research/steve/toy_demo.py

jdavidagudelo/tensorflow-models

6f019beec73b01861363bf717706e27f4210b979

[ "Apache-2.0" ]

null

research/steve/toy_demo.py

jdavidagudelo/tensorflow-models

6f019beec73b01861363bf717706e27f4210b979

[ "Apache-2.0" ]

null

from __future__ import division from __future__ import print_function from builtins import range from past.utils import old_div # Copyright 2018 The TensorFlow Authors All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== import numpy as np import scipy import matplotlib.pyplot as plt import seaborn as sns ### Hyperparameters NONTERMINAL_STATE_COUNT = 100 NOISE_AMOUNT = 0.1 TRAIN_STEPS = 10000 Q_ENSEMBLE_SIZE = 8 MODEL_ENSEMBLE_SIZE = 8 HORIZON = 5 TRIAL_N = 10 ### Helper functions initial_state = 0 terminal_state = NONTERMINAL_STATE_COUNT + 1 nonterminal_state_count = NONTERMINAL_STATE_COUNT state_count = NONTERMINAL_STATE_COUNT + 1 final_reward = NONTERMINAL_STATE_COUNT colors = sns.color_palette('husl', 4) plt.rcParams["figure.figsize"] = (6, 5) def step(state): if state == terminal_state: next_state = terminal_state else: next_state = state + 1 if state == terminal_state: reward = 0 elif state + 1 == terminal_state: reward = final_reward else: reward = -1 return next_state, reward def noisy_step(state): if state == terminal_state: next_state = terminal_state elif np.random.random([]) < NOISE_AMOUNT: next_state = np.random.randint(0, state_count) else: next_state = state + 1 if state == terminal_state: reward = 0 elif state + 1 == terminal_state: reward = final_reward else: reward = -1 return next_state, reward def get_error(Q): losses = np.square(np.arange(state_count) - Q[:-1]) return np.mean(losses) def downsample(array, factor): pad_size = np.ceil(old_div(float(array.size), factor)) * factor - array.size array_padded = np.append(array, np.zeros([pad_size.astype(np.int64)]) * np.NaN) return scipy.nanmean(array_padded.reshape(-1, factor), axis=1) ###################### ### Main experiments ###################### # Basic Q if True: print("Running basic Q-learning.") trial_results = [] for run_i in range(TRIAL_N): print("Trial %d" % run_i) Q = np.random.randint(0, state_count, [state_count + 1]).astype(np.float64) Q[state_count] = 0 losses = [] for step_i in range(TRAIN_STEPS): state = np.random.randint(0, state_count) next_state, reward = step(state) Q[state] = reward + Q[next_state] losses.append(get_error(Q)) trial_results.append(losses) print("...complete.\n") result = np.stack(trial_results, axis=1) means = np.mean(result, axis=1) stdevs = np.std(result, axis=1) plt.plot(means, label="Basic Q-learning", color=colors[0]) plt.fill_between(np.arange(TRAIN_STEPS), means - stdevs, means + stdevs, alpha=.2, color=colors[0]) with open('Toy-v1/baseline.csv', 'w') as f: data = [] for frame_i in range(result.shape[0]): for loss in result[frame_i]: data.append("%f,%f,%f,%f" % (frame_i, frame_i, frame_i, loss)) f.write("\n".join(data)) # Ensemble Q if True: print("Running ensemble Q-learning.") trial_results = [] for run_i in range(TRIAL_N): print("Trial %d" % run_i) Q = np.random.randint(0, state_count, [Q_ENSEMBLE_SIZE, state_count + 1]).astype(np.float64) Q[:, state_count] = 0 losses = [] for step_i in range(TRAIN_STEPS): for q_ensemble_i in range(Q_ENSEMBLE_SIZE): state = np.random.randint(0, state_count) next_state, reward = step(state) Q[q_ensemble_i, state] = reward + np.mean(Q[:, next_state]) losses.append(get_error(np.mean(Q, axis=0))) trial_results.append(losses) print("...complete.\n") result = np.stack(trial_results, axis=1) means = np.mean(result, axis=1) stdevs = np.std(result, axis=1) plt.plot(means, label="Ensemble Q-learning", color=colors[1]) plt.fill_between(np.arange(TRAIN_STEPS), means - stdevs, means + stdevs, alpha=.2, color=colors[1]) # Ensemble MVE-Oracle if True: print("Running ensemble oracle MVE.") trial_results = [] for run_i in range(TRIAL_N): print("Trial %d" % run_i) Q = np.random.randint(0, state_count, [Q_ENSEMBLE_SIZE, state_count + 1]).astype(np.float64) Q[:, state_count] = 0 losses = [] for step_i in range(TRAIN_STEPS): for q_ensemble_i in range(Q_ENSEMBLE_SIZE): state = np.random.randint(0, state_count) next_state, reward = step(state) # MVE rollout target = reward for _ in range(HORIZON): next_state, reward = step(next_state) target += reward target += np.mean(Q[:, next_state]) Q[q_ensemble_i, state] = target losses.append(get_error(np.mean(Q, axis=0))) trial_results.append(losses) print("...complete.\n") result = np.stack(trial_results, axis=1) means = np.mean(result, axis=1) stdevs = np.std(result, axis=1) plt.plot(means, label="MVE-oracle", color=colors[2]) plt.fill_between(np.arange(TRAIN_STEPS), means - stdevs, means + stdevs, alpha=.2, color=colors[2]) with open('Toy-v1/mve_oracle.csv', 'w') as f: data = [] for frame_i in range(result.shape[0]): for loss in result[frame_i]: data.append("%f,%f,%f,%f" % (frame_i, frame_i, frame_i, loss)) f.write("\n".join(data)) # Ensemble MVE-Noisy if True: print("Running ensemble noisy MVE.") trial_results = [] for run_i in range(TRIAL_N): print("Trial %d" % run_i) Q = np.random.randint(0, state_count, [Q_ENSEMBLE_SIZE, state_count + 1]).astype(np.float64) Q[:, state_count] = 0 losses = [] for step_i in range(TRAIN_STEPS): for q_ensemble_i in range(Q_ENSEMBLE_SIZE): state = np.random.randint(0, state_count) next_state, reward = step(state) # MVE rollout targets = [] first_next_state, first_reward = next_state, reward for model_ensemble_i in range(MODEL_ENSEMBLE_SIZE): next_state, reward = first_next_state, first_reward target = reward for _ in range(HORIZON): next_state, reward = noisy_step(next_state) target += reward target += np.mean(Q[:, next_state]) targets.append(target) Q[q_ensemble_i, state] = np.mean(targets) losses.append(get_error(np.mean(Q, axis=0))) trial_results.append(losses) print("...complete.\n") result = np.stack(trial_results, axis=1) means = np.mean(result, axis=1) stdevs = np.std(result, axis=1) plt.plot(means, label="MVE-noisy", color=colors[2], linestyle='dotted') plt.fill_between(np.arange(TRAIN_STEPS), means - stdevs, means + stdevs, alpha=.2, color=colors[2]) with open('Toy-v1/mve_noisy.csv', 'w') as f: data = [] for frame_i in range(result.shape[0]): for loss in result[frame_i]: data.append("%f,%f,%f,%f" % (frame_i, frame_i, frame_i, loss)) f.write("\n".join(data)) # STEVE-Oracle if True: print("Running ensemble oracle STEVE.") trial_results = [] oracle_q_estimate_errors = [] oracle_mve_estimate_errors = [] oracle_steve_estimate_errors = [] oracle_opt_estimate_errors = [] for run_i in range(TRIAL_N): print("Trial %d" % run_i) Q = np.random.randint(0, state_count, [Q_ENSEMBLE_SIZE, state_count + 1]).astype(np.float64) Q[:, state_count] = 0 losses = [] q_estimate_errors = [] mve_estimate_errors = [] steve_estimate_errors = [] opt_estimate_errors = [] steve_beat_freq = [] for step_i in range(TRAIN_STEPS): _q_estimate_errors = [] _mve_estimate_errors = [] _steve_estimate_errors = [] _opt_estimate_errors = [] _steve_beat_freq = [] for q_ensemble_i in range(Q_ENSEMBLE_SIZE): state = np.random.randint(0, state_count) next_state, reward = step(state) # STEVE rollout Q_est_mat = np.zeros([HORIZON + 1, Q_ENSEMBLE_SIZE]) reward_est_mat = np.zeros([HORIZON + 1, 1]) first_next_state, first_reward = next_state, reward next_state, reward = first_next_state, first_reward Q_est_mat[0, :] = Q[:, next_state] reward_est_mat[0, 0] = reward for timestep_i in range(1, HORIZON + 1): next_state, reward = step(next_state) Q_est_mat[timestep_i, :] = Q[:, next_state] reward_est_mat[timestep_i, 0] = reward all_targets = Q_est_mat + np.cumsum(reward_est_mat, axis=0) # STEVE weight calculation estimates = np.mean(all_targets, axis=1) confidences = old_div(1., (np.var(all_targets, axis=1) + 1e-8)) coefficients = old_div(confidences, np.sum(confidences)) target = np.sum(estimates * coefficients) Q[q_ensemble_i, state] = target true_target = state + 1. if state != terminal_state else 0. _q_estimate_errors.append(np.square(estimates[0] - true_target)) _mve_estimate_errors.append(np.square(estimates[-1] - true_target)) _steve_estimate_errors.append(np.square(np.sum(estimates * coefficients) - true_target)) _opt_estimate_errors.append(np.min(np.square(estimates - true_target))) losses.append(get_error(np.mean(Q, axis=0))) q_estimate_errors.append(np.mean(_q_estimate_errors)) mve_estimate_errors.append(np.mean(_mve_estimate_errors)) steve_estimate_errors.append(np.mean(_steve_estimate_errors)) opt_estimate_errors.append(np.mean(_opt_estimate_errors)) trial_results.append(losses) oracle_q_estimate_errors.append(q_estimate_errors) oracle_mve_estimate_errors.append(mve_estimate_errors) oracle_steve_estimate_errors.append(steve_estimate_errors) oracle_opt_estimate_errors.append(opt_estimate_errors) print("...complete.\n") result = np.stack(trial_results, axis=1) means = np.mean(result, axis=1) stdevs = np.std(result, axis=1) plt.plot(means, label="STEVE-oracle", color=colors[3]) plt.fill_between(np.arange(TRAIN_STEPS), means - stdevs, means + stdevs, alpha=.2, color=colors[3]) with open('Toy-v1/steve_oracle.csv', 'w') as f: data = [] for frame_i in range(result.shape[0]): for loss in result[frame_i]: data.append("%f,%f,%f,%f" % (frame_i, frame_i, frame_i, loss)) f.write("\n".join(data)) # STEVE-Noisy if True: print("Running ensemble noisy STEVE.") trial_results = [] noisy_q_estimate_errors = [] noisy_mve_estimate_errors = [] noisy_steve_estimate_errors = [] noisy_opt_estimate_errors = [] noisy_steve_beat_freq = [] for run_i in range(TRIAL_N): print("Trial %d" % run_i) Q = np.random.randint(0, state_count, [Q_ENSEMBLE_SIZE, state_count + 1]).astype(np.float64) Q[:, state_count] = 0 losses = [] q_estimate_errors = [] mve_estimate_errors = [] steve_estimate_errors = [] opt_estimate_errors = [] steve_beat_freq = [] for step_i in range(TRAIN_STEPS): _q_estimate_errors = [] _mve_estimate_errors = [] _steve_estimate_errors = [] _opt_estimate_errors = [] _steve_beat_freq = [] for q_ensemble_i in range(Q_ENSEMBLE_SIZE): state = np.random.randint(0, state_count) next_state, reward = step(state) # STEVE rollout Q_est_mat = np.zeros([HORIZON + 1, MODEL_ENSEMBLE_SIZE, Q_ENSEMBLE_SIZE]) reward_est_mat = np.zeros([HORIZON + 1, MODEL_ENSEMBLE_SIZE, 1]) first_next_state, first_reward = next_state, reward for model_ensemble_i in range(MODEL_ENSEMBLE_SIZE): next_state, reward = first_next_state, first_reward Q_est_mat[0, model_ensemble_i, :] = Q[:, next_state] reward_est_mat[0, model_ensemble_i, 0] = reward for timestep_i in range(1, HORIZON + 1): next_state, reward = noisy_step(next_state) Q_est_mat[timestep_i, model_ensemble_i, :] = Q[:, next_state] reward_est_mat[timestep_i, model_ensemble_i, 0] = reward all_targets = Q_est_mat + np.cumsum(reward_est_mat, axis=0) # STEVE weight calculation all_targets = np.reshape(all_targets, [HORIZON + 1, MODEL_ENSEMBLE_SIZE * Q_ENSEMBLE_SIZE]) estimates = np.mean(all_targets, axis=1) confidences = old_div(1., (np.var(all_targets, axis=1) + 1e-8)) coefficients = old_div(confidences, np.sum(confidences)) target = np.sum(estimates * coefficients) # target = estimates[0] Q[q_ensemble_i, state] = target true_target = state + 1. if state != terminal_state else 0. _q_estimate_errors.append(np.square(estimates[0] - true_target)) _mve_estimate_errors.append(np.square(estimates[-1] - true_target)) _steve_estimate_errors.append(np.square(np.sum(estimates * coefficients) - true_target)) _opt_estimate_errors.append(np.min(np.square(estimates - true_target))) _steve_beat_freq.append(float(np.square(estimates[0] - true_target) > np.square(target - true_target))) losses.append(get_error(np.mean(Q, axis=0))) q_estimate_errors.append(np.mean(_q_estimate_errors)) mve_estimate_errors.append(np.mean(_mve_estimate_errors)) steve_estimate_errors.append(np.mean(_steve_estimate_errors)) opt_estimate_errors.append(np.mean(_opt_estimate_errors)) steve_beat_freq.append(np.mean(_steve_beat_freq)) trial_results.append(losses) noisy_q_estimate_errors.append(q_estimate_errors) noisy_mve_estimate_errors.append(mve_estimate_errors) noisy_steve_estimate_errors.append(steve_estimate_errors) noisy_opt_estimate_errors.append(opt_estimate_errors) noisy_steve_beat_freq.append(steve_beat_freq) print("...complete.\n") result = np.stack(trial_results, axis=1) means = np.mean(result, axis=1) stdevs = np.std(result, axis=1) plt.plot(means, label="STEVE-noisy", color=colors[3], linestyle='dotted') plt.fill_between(np.arange(TRAIN_STEPS), means - stdevs, means + stdevs, alpha=.2, color=colors[3]) with open('Toy-v1/steve_noisy.csv', 'w') as f: data = [] for frame_i in range(result.shape[0]): for loss in result[frame_i]: data.append("%f,%f,%f,%f" % (frame_i, frame_i, frame_i, loss)) f.write("\n".join(data)) # ### Display results # plt.title("Comparison of convergence rates") # plt.legend() # plt.savefig("comparison.pdf") # plt.show() # # ### Display secondary results - error comparison # DOWNSAMPLE = 50 # colors = sns.color_palette('husl', 8) # for i, (error_curve, label) in enumerate([ # (oracle_q_estimate_errors, "Oracle Q error"), # (oracle_mve_estimate_errors, "Oracle MVE error"), # (oracle_steve_estimate_errors, "Oracle STEVE error"), # # (oracle_opt_estimate_errors, "Oracle minimum single-estimate error"), # ]): # result = np.stack(error_curve, axis=1) # means = downsample(np.mean(result, axis=1), DOWNSAMPLE) # stdevs = downsample(np.std(result, axis=1), DOWNSAMPLE) # plt.plot(means, label=label, color=colors[i]) # plt.fill_between(np.arange(means.shape[0]), means - stdevs, means + stdevs, alpha=.2, color=colors[i]) # # plt.title("Comparison of errors for oracle dynamics") # plt.legend() # plt.show() # # for i, (error_curve, label) in enumerate([ # (noisy_q_estimate_errors, "Noisy Q error"), # (noisy_mve_estimate_errors, "Noisy MVE error"), # (noisy_steve_estimate_errors, "Noisy STEVE error"), # # (noisy_opt_estimate_errors, "Noisy minimum single-estimate error"), # # (trial_steve_beat_freq, "STEVE beat freq"), # ]): # result = np.stack(error_curve, axis=1) # means = downsample(np.mean(result, axis=1), DOWNSAMPLE) # stdevs = downsample(np.std(result, axis=1), DOWNSAMPLE) # plt.plot(means, label=label, color=colors[i]) # plt.fill_between(np.arange(means.shape[0]), means - stdevs, means + stdevs, alpha=.2, color=colors[i]) # # plt.title("Comparison of errors for noisy dynamics") # plt.legend() # plt.show()

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py

Python

tests/unchained/conftest.py

uolot/py-yaml-fixtures

0b165d91578420cd4cb0b2fc245ae0e39578ede5

[ "MIT" ]

13

2018-08-14T12:28:54.000Z

2022-02-08T04:25:47.000Z

tests/unchained/conftest.py

uolot/py-yaml-fixtures

0b165d91578420cd4cb0b2fc245ae0e39578ede5

[ "MIT" ]

5

2019-02-23T04:01:48.000Z

2021-04-08T17:37:40.000Z

tests/unchained/conftest.py

uolot/py-yaml-fixtures

0b165d91578420cd4cb0b2fc245ae0e39578ede5

[ "MIT" ]

5

2018-09-04T03:28:46.000Z

2021-04-09T11:46:03.000Z

from flask_unchained.bundles.sqlalchemy.pytest import *

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py

Python

hello_world.py

hmallen/mrhawaii

4b973c185e9acf030342435204480467d189f013

[ "MIT" ]

null

hello_world.py

hmallen/mrhawaii

4b973c185e9acf030342435204480467d189f013

[ "MIT" ]

1

2020-07-30T01:46:09.000Z

hello_world.py

hmallen/mrhawaii

4b973c185e9acf030342435204480467d189f013

[ "MIT" ]

null

# Hello world program to demonstrate running PYthon files print('Hello, world!') print('I live on a volcano!')

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py

Python

lib/JumpScale/lib/ms1/__init__.py

rudecs/jumpscale_core7

30c03f26f1cdad3edbb9d79d50fbada8acc974f5

[ "Apache-2.0" ]

null

lib/JumpScale/lib/ms1/__init__.py

rudecs/jumpscale_core7

30c03f26f1cdad3edbb9d79d50fbada8acc974f5

[ "Apache-2.0" ]

4

2016-08-25T12:08:39.000Z

2018-04-12T12:36:01.000Z

lib/JumpScale/lib/ms1/__init__.py

rudecs/jumpscale_core7

30c03f26f1cdad3edbb9d79d50fbada8acc974f5

[ "Apache-2.0" ]

3

2016-03-08T07:49:34.000Z

2018-10-19T13:56:43.000Z

from JumpScale import j def cb(): from .ms1 import MS1Factory return MS1Factory() j.base.loader.makeAvailable(j, 'tools') j.tools._register('ms1', cb)

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py

Python

Tools/MagicPanels/panelMoveXp.py

dprojects/Woodworking

24420b248e3343a387ae1328fc6dcbf97e433242

[ "MIT" ]

6

2022-02-25T19:11:40.000Z

2022-03-24T22:03:47.000Z

Tools/MagicPanels/panelMoveXp.py

dprojects/Woodworking

24420b248e3343a387ae1328fc6dcbf97e433242

[ "MIT" ]

1

2022-03-13T09:35:22.000Z

2022-03-13T13:30:36.000Z

Tools/MagicPanels/panelMoveXp.py

dprojects/Woodworking

24420b248e3343a387ae1328fc6dcbf97e433242

[ "MIT" ]

3

2022-02-26T15:01:08.000Z

2022-03-20T21:30:04.000Z

import MagicPanels MagicPanels.panelMove("Xp")

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py

Python

findtime/utils.py

MattCCS/FindTime

8c38965661444d342a28eadc0cdedaf70e9f9279

[ "MIT" ]

null

findtime/utils.py

MattCCS/FindTime

8c38965661444d342a28eadc0cdedaf70e9f9279

[ "MIT" ]

null

findtime/utils.py

MattCCS/FindTime

8c38965661444d342a28eadc0cdedaf70e9f9279

[ "MIT" ]

null

def day_of_year(dt): return dt.timetuple().tm_yday

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282

py

Python

codility/python/fib.py

guvkon/aoc-2021

15c8d387f5bf218790d461d32dd948d6c667be6c

[ "MIT" ]

null

codility/python/fib.py

guvkon/aoc-2021

15c8d387f5bf218790d461d32dd948d6c667be6c

[ "MIT" ]

null

codility/python/fib.py

guvkon/aoc-2021

15c8d387f5bf218790d461d32dd948d6c667be6c

[ "MIT" ]

null

import math def fib(n): fib = [0] * (n + 1) fib[1] = 1 for i in range(2, n + 1): fib[i] = fib[i - 1] + fib[i - 2] return fib[n] def fib_formula(n): return int((math.pow((1 + math.sqrt(5)) / 2, n) - math.pow((1 - math.sqrt(5)) / 2, n)) / math.sqrt(5))

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62

py

Python

gsee/__init__.py

scene-connect/gsee

f5515fb2a20af9278e7ca11312388717760a8225

[ "BSD-3-Clause" ]

null

gsee/__init__.py

scene-connect/gsee

f5515fb2a20af9278e7ca11312388717760a8225

[ "BSD-3-Clause" ]

5

2022-03-11T10:52:24.000Z

2022-03-11T14:09:09.000Z

gsee/__init__.py

scene-connect/gsee

f5515fb2a20af9278e7ca11312388717760a8225

[ "BSD-3-Clause" ]

null

__all__ = ["brl_model", "pv"] from gsee import brl_model, pv

15.5

30

0.693548

10

62

3.7

0.7

0.432432

0.540541

0

0.16129

62

3

31

20.666667

0.711538

0

0.177419

0

1

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false

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

7e72844189e895886424dc16300b05e203165f43

46

py

Python

elevadorJahNoUltimoAndarException.py

IpRocha1/dsoo_exercicio_6

69ece39b2189b3a17a9185dca8a6d17acb6b5aa5

[ "MIT" ]

null

elevadorJahNoUltimoAndarException.py

IpRocha1/dsoo_exercicio_6

69ece39b2189b3a17a9185dca8a6d17acb6b5aa5

[ "MIT" ]

null

elevadorJahNoUltimoAndarException.py

IpRocha1/dsoo_exercicio_6

69ece39b2189b3a17a9185dca8a6d17acb6b5aa5

[ "MIT" ]

null

class ElevadorJahNoUltimoAndarException( ...

15.333333

44

0.826087

2

46

19

1

0

0.086957

46

2

45

23

0.904762

0

null

0

null

0

1

null

0

1

0

null

0

1

0

5

0e224344c163f81deb574207f38b8233548b28f8

119

bzl

Python

test/com/facebook/buck/parser/testdata/disable_implicit_native_rules/skylark/implicit_in_extension_bzl/extension.bzl

Unknoob/buck

2dfc734354b326f2f66896dde7746a11965d5a13

[ "Apache-2.0" ]

8,027

2015-01-02T05:31:44.000Z

2022-03-31T07:08:09.000Z

test/com/facebook/buck/parser/testdata/disable_implicit_native_rules/skylark/implicit_in_extension_bzl/extension.bzl

Unknoob/buck

2dfc734354b326f2f66896dde7746a11965d5a13

[ "Apache-2.0" ]

2,355

2015-01-01T15:30:53.000Z

2022-03-30T20:21:16.000Z

test/com/facebook/buck/parser/testdata/disable_implicit_native_rules/skylark/implicit_in_extension_bzl/extension.bzl

Unknoob/buck

2dfc734354b326f2f66896dde7746a11965d5a13

[ "Apache-2.0" ]

1,280

2015-01-09T03:29:04.000Z

2022-03-30T15:14:14.000Z

""" Example module """ def java_maker(*args, **kwargs): """ Make you a java """ java_library(*args, **kwargs)

19.833333

33

0.588235

15

119

4.533333

0.733333

0.294118

0

0.201681

119

5

34

23.8

0.715789

0.260504

0

1

0.5

true

0

0.5

0

1

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null

1

0

1

0

null

0

1

0

5

0e4ecce9b8ee44d7a2ecb07d04597a919fe2daa5

146

py

Python

euler_01.py

zhou-le/euler

78033a10bc186fbd2a004760966e15724b0a98f9

[ "Apache-2.0" ]

2

2018-12-24T15:36:00.000Z

2021-06-07T09:35:59.000Z

euler_01.py

zhou-le/Euler

78033a10bc186fbd2a004760966e15724b0a98f9

[ "Apache-2.0" ]

null

euler_01.py

zhou-le/Euler

78033a10bc186fbd2a004760966e15724b0a98f9

[ "Apache-2.0" ]

null

#coding: utf-8 #date: 2018/7/30 19:07 #author: zhou_le # 求1000以下3和5的倍数之和 print(sum([i for i in range(1000) if i % 3 == 0 or i % 5 == 0]))

20.857143

64

0.59589

29

146

2.965517

0.862069

0

0.232143

0.232877

146

7

64

20.857143

0.535714

0.452055

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

0e5a60a46aeb18c5fcebbf2deb1ab0ad21f787d1

24

py

Python

asn1tools/version.py

eerimoq/asn1tools

93e5fc2922c191e4a593507d4bc8847341fc9f40

[ "MIT" ]

198

2017-08-04T21:49:15.000Z

2022-03-26T10:11:21.000Z

asn1tools/version.py

eerimoq/asn1tools

93e5fc2922c191e4a593507d4bc8847341fc9f40

[ "MIT" ]

144

2017-09-29T12:06:51.000Z

2022-03-29T13:04:44.000Z

asn1tools/version.py

eerimoq/asn1tools

93e5fc2922c191e4a593507d4bc8847341fc9f40

[ "MIT" ]

73

2017-10-09T13:33:28.000Z

2022-03-11T01:35:22.000Z

__version__ = '0.159.0'

12

23

0.666667

4

24

3

0.75

0

0.238095

0.125

24

1

24

0.333333

0

0.291667

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

5

0e67c3d1189cc9a2fa0ae70c15b2f561c7bd2b47

404

py

Python

Semester2/bottles.py

ConstantineLinardakis/Programming1Portfolio

9062590de87e495ecf19b759a5d7a132a6982e3b

[ "MIT" ]

1

2020-11-23T19:02:21.000Z

Semester2/bottles.py

ConstantineLinardakis/Programming1Portfolio

9062590de87e495ecf19b759a5d7a132a6982e3b

[ "MIT" ]

null

Semester2/bottles.py

ConstantineLinardakis/Programming1Portfolio

9062590de87e495ecf19b759a5d7a132a6982e3b

[ "MIT" ]

null

#loop bottles = 99 while (bottles > 0): if (bottles > 1): print bottles, "bottles of root beer on the wall", bottles, "bottles of root beer" print "Take one down pass it around,", bottles, "bottles of root beer on the wall" else: print bottles, "bottles of root beer on the wall", bottles, "bottle of root beer" bottles = bottles - 1

21.263158

90

0.591584

56

404

4.267857

0.392857

0.292887

0.209205

0.334728

0.585774

0.514644

0.376569

0

0.018315

0.324257

404

19

91

21.263158

0.857143

0.009901

0

0.41

0

null

0.125

0

null

0.375

0

null

1

0

null

0

1

0

1

0

5

0ea7201b51048203ec576eca4a186c7f31e54813

169

py

Python

practice/bitwise_operations/ex2.py

recursivelycurious/wordnik-repl

9d9e96a8ebc79b95f135d5bc871602b65d2d2b79

[ "MIT" ]

346

2016-02-22T20:21:10.000Z

2022-01-27T20:55:53.000Z

Language Skills/Python/Unit 10/2-Introduction to Bitwise Operators/Binary representation/2-Lesson I0_ The Base 2 Number System_.py

vpstudios/Codecademy-Exercise-Answers

ebd0ee8197a8001465636f52c69592ea6745aa0c

[ "MIT" ]

55

2016-04-07T13:58:44.000Z

2020-06-25T12:20:24.000Z

Language Skills/Python/Unit 10/2-Introduction to Bitwise Operators/Binary representation/2-Lesson I0_ The Base 2 Number System_.py

vpstudios/Codecademy-Exercise-Answers

ebd0ee8197a8001465636f52c69592ea6745aa0c

[ "MIT" ]

477

2016-02-21T06:17:02.000Z

2021-12-22T10:08:01.000Z

print 0b1, #1 print 0b10, #2 print 0b11, #3 print 0b100, #4 print 0b101, #5 print 0b110, #6 print 0b111 #7 print "******" print 0b1 + 0b11 print 0b11 * 0b11

15.363636

17

0.609467

28

169

3.678571

0.535714

0.15534

0

0.333333

0.254438

169

10

18

16.9

0.484127

0.04142

0

0.03871

0

null

0

null

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

7ed68a92c00d63af048a398460040921d4a594c2

152

py

Python

src/xbrief/deco/__init__.py

pydget/xbrief

9e91927a98754b0fca1fa55eae9a785b15e963f9

[ "MIT" ]

null

src/xbrief/deco/__init__.py

pydget/xbrief

9e91927a98754b0fca1fa55eae9a785b15e963f9

[ "MIT" ]

null

src/xbrief/deco/__init__.py

pydget/xbrief

9e91927a98754b0fca1fa55eae9a785b15e963f9

[ "MIT" ]

null

from .deco_entries import deco_dict, deco_entries from .deco_matrix import deco_matrix from .deco_node import deco from .deco_vector import deco_vector

30.4

49

0.855263

25

152

4.88

0.32

0.262295

0

0.111842

152

4

50

38

0.903704

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

7edcf59eb18eef02bdb316448f6adea4f05d6570

130

py

Python

pymoo/operators/mutation/nom.py

jarreguit/pymoo

0496a3c6765826148d8bab21650736760517dd25

[ "Apache-2.0" ]

762

2018-06-05T20:56:09.000Z

2021-09-14T09:09:42.000Z

pymoo/operators/mutation/nom.py

jarreguit/pymoo

0496a3c6765826148d8bab21650736760517dd25

[ "Apache-2.0" ]

176

2018-09-05T18:37:05.000Z

2021-09-14T01:18:43.000Z

pymoo/operators/mutation/nom.py

jarreguit/pymoo

0496a3c6765826148d8bab21650736760517dd25

[ "Apache-2.0" ]

160

2018-08-05T05:31:20.000Z

2021-09-14T09:09:45.000Z

from pymoo.core.mutation import Mutation class NoMutation(Mutation): def _do(self, problem, X, **kwargs): return X

16.25

40

0.684615

17

130

5.176471

0.823529

0

0.215385

130

7

41

18.571429

0.862745

0

1

0.25

false

0

0.25

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

7ee00fb2a41f748e6f16cd24d5dbedd13ee2a74c

155

py

Python

portfolio/portfolio_site/models/__init__.py

nguyentrisinh/portfolio

83b13f8ffaafae76f3a9597b2b8b428da188a555

[ "MIT" ]

null

portfolio/portfolio_site/models/__init__.py

nguyentrisinh/portfolio

83b13f8ffaafae76f3a9597b2b8b428da188a555

[ "MIT" ]

null

portfolio/portfolio_site/models/__init__.py

nguyentrisinh/portfolio

83b13f8ffaafae76f3a9597b2b8b428da188a555

[ "MIT" ]

null

from .contact import Contact from .project import Project from .link import Link from .category import Category from .project_image import ProjectImage

31

39

0.819355

21

155

6

0.380952

0.174603

0

0.148387

155

5

39

31

0.954545

0

1

0

true

0

1

0

1

0

1

0

null

0

1

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null

0

1

0

1

0

1

0

5

7d47e3a2c72557ea55cdd53dea81dcefd1f28f34

181

py

Python

Lib/fontTools/ttLib/tables/T_S_I_B_.py

twardoch/fonttools-py27

75b852d3f59fc0d03c6e78581530597d4c6368a1

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

240

2021-01-11T14:49:24.000Z

2022-03-29T22:33:49.000Z

Lib/fontTools/ttLib/tables/T_S_I_B_.py

twardoch/fonttools-py27

75b852d3f59fc0d03c6e78581530597d4c6368a1

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

77

2021-01-12T20:23:30.000Z

2022-03-28T12:14:34.000Z

Lib/fontTools/ttLib/tables/T_S_I_B_.py

twardoch/fonttools-py27

75b852d3f59fc0d03c6e78581530597d4c6368a1

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

28

2021-01-17T05:44:11.000Z

2022-01-11T19:58:46.000Z

from __future__ import print_function, division, absolute_import from fontTools.misc.py23 import * from .T_S_I_V_ import table_T_S_I_V_ class table_T_S_I_B_(table_T_S_I_V_): pass

25.857143

64

0.845304

36

181

3.555556

0.5

0.0625

0.09375

0.140625

0

0.012346

0.104972

181

6

65

30.166667

0.777778

0

1

0

true

0.2

0.6

0

0.8

0.2

0

null

0

1

0

null

0

1

0

1

0

5

adee84920a6fd9a1311346aec3afbb03a615787d

1,237

py

Python

sdk/python/pulumi_azure_native/automation/v20200113preview/__init__.py

sebtelko/pulumi-azure-native

711ec021b5c73da05611c56c8a35adb0ce3244e4

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/automation/v20200113preview/__init__.py

sebtelko/pulumi-azure-native

711ec021b5c73da05611c56c8a35adb0ce3244e4

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/automation/v20200113preview/__init__.py

sebtelko/pulumi-azure-native

711ec021b5c73da05611c56c8a35adb0ce3244e4

[ "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** from ... import _utilities import typing # Export this package's modules as members: from ._enums import * from .automation_account import * from .certificate import * from .connection import * from .connection_type import * from .credential import * from .dsc_node_configuration import * from .get_automation_account import * from .get_certificate import * from .get_connection import * from .get_connection_type import * from .get_credential import * from .get_dsc_node_configuration import * from .get_job_schedule import * from .get_module import * from .get_private_endpoint_connection import * from .get_python2_package import * from .get_schedule import * from .get_source_control import * from .get_variable import * from .get_watcher import * from .job_schedule import * from .list_key_by_automation_account import * from .module import * from .private_endpoint_connection import * from .python2_package import * from .schedule import * from .source_control import * from .variable import * from .watcher import * from ._inputs import * from . import outputs

30.925

80

0.78658

172

1,237

5.430233

0.348837

0.331906

0.194861

0.086724

0.14561

0.070664

0

0.002822

0.140663

1,237

39

81

31.717949

0.875823

0.164107

0

1

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

bc2367f7ad3d249653384c57887795fc9732fb47

136

py

Python

models/__init__.py

dudtjakdl/OpenNMT-Korean-To-English

32fcdb860906f40f84375ec17a23ae32cb90baa0

[ "Apache-2.0" ]

1,491

2017-06-30T16:15:40.000Z

2022-03-22T02:05:16.000Z

models/__init__.py

dudtjakdl/OpenNMT-Korean-To-English

32fcdb860906f40f84375ec17a23ae32cb90baa0

[ "Apache-2.0" ]

128

2017-07-07T21:41:03.000Z

2021-06-30T13:18:23.000Z

models/__init__.py

dudtjakdl/OpenNMT-Korean-To-English

32fcdb860906f40f84375ec17a23ae32cb90baa0

[ "Apache-2.0" ]

434

2017-07-08T12:35:15.000Z

2022-03-25T06:28:13.000Z

from .EncoderRNN import EncoderRNN from .DecoderRNN import DecoderRNN from .TopKDecoder import TopKDecoder from .seq2seq import Seq2seq

27.2

36

0.852941

16

136

7.25

0.375

0

0.016667

0.117647

136

4

37

34

0.95

0

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true

0

1

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null

0

1

0

1

0

1

0

5

bc3c7092993eb4e13af6dd3b1e0b4b31e2777061

18,700

py

Python

Environment.py

mxrcfdez/TrafficLightsAutomation

fe5b3c1cebe585e4f9a3fb2d2a7653f4ac2edb8a

[ "Apache-2.0" ]

null

Environment.py

mxrcfdez/TrafficLightsAutomation

fe5b3c1cebe585e4f9a3fb2d2a7653f4ac2edb8a

[ "Apache-2.0" ]

null

Environment.py

mxrcfdez/TrafficLightsAutomation

fe5b3c1cebe585e4f9a3fb2d2a7653f4ac2edb8a

[ "Apache-2.0" ]

null

import gym from gym import spaces import numpy as np import learning_data from Simulation import Simulation def get_value_or_delimiter(value, delimiter): return min(delimiter[1], max(delimiter[0], value)) class Environment(gym.Env): def __init__(self, simulation, training): super(Environment, self).__init__() self.simulation = simulation self.training = training self.action_space = spaces.Discrete(2) observation_space_dictionary = dict() observation_space_dictionary['lights_settings'] = spaces.Box(low=0, high=1, shape=(1,), dtype=np.uint8) observation_space_dictionary['intersection_cars'] = spaces.Box(low=0, high=1000, shape=(2,), dtype=np.uint8) observation_space_dictionary['input_cars'] = spaces.Box(low=0, high=1000, shape=(2,), dtype=np.uint8) observation_space_dictionary['output_cars'] = spaces.Box(low=0, high=1000, shape=(2,), dtype=np.uint8) self.observation_space = spaces.Dict(observation_space_dictionary) def reset(self, reset_simulation=True): print('\033[94m' + 'resetting environment...' + '\033[0;0m') if reset_simulation: self.simulation = Simulation(self.simulation.traffic_volume, self.simulation.rows, self.simulation.cols, self.simulation.road_length, self.simulation.simulation_time) observation = self.simulation.get_observation() learning_data.previous_observation = observation return observation def step(self, action): if self.training: previous_observation = learning_data.previous_observation done = self.simulation.advance_step(action) current_observation = self.simulation.get_observation() learning_data.previous_observation = current_observation reward = self.definitive2x2(previous_observation, action) else: done = self.simulation.advance_step(action) current_observation = self.simulation.get_observation() reward = 0 return current_observation, reward, done, {} def render(self, mode='human', close=False): pass def reward_function_1(self, previous_observation, current_observation): previous_horizontal_waiting_time = 0 previous_vertical_waiting_time = 0 current_horizontal_waiting_time = 0 current_vertical_waiting_time = 0 for intersection in range(self.simulation.rows * self.simulation.cols): for car in range(self.simulation.road_length): if previous_observation['horizontal_waiting_time'][intersection][car] != -1: previous_horizontal_waiting_time += previous_observation['horizontal_waiting_time'][intersection][car] if previous_observation['vertical_waiting_time'][intersection][car] != -1: previous_vertical_waiting_time += previous_observation['vertical_waiting_time'][intersection][car] if current_observation['horizontal_waiting_time'][intersection][car] != -1: current_horizontal_waiting_time += current_observation['horizontal_waiting_time'][intersection][car] if current_observation['vertical_waiting_time'][intersection][car] != -1: current_vertical_waiting_time += current_observation['vertical_waiting_time'][intersection][car] previous_waiting_time = previous_horizontal_waiting_time + previous_vertical_waiting_time current_waiting_time = current_horizontal_waiting_time + current_vertical_waiting_time return previous_waiting_time - current_waiting_time def reward_function_2(self, previous_observation, action): reward = 0 num_of_intersections = self.simulation.rows * self.simulation.cols for intersection in range(num_of_intersections): # If the vertical lights turn green if previous_observation['lights_settings'][intersection] == 1 and action[intersection] >= 0.5: reward = reward + previous_observation['vertical_num_of_cars_waiting'][intersection] - previous_observation['horizontal_num_of_cars_waiting'][intersection] # If the horizontal lights turn green elif previous_observation['lights_settings'][intersection] == 0 and action[intersection] >= 0.5: reward = reward + previous_observation['horizontal_num_of_cars_waiting'][intersection] - previous_observation['vertical_num_of_cars_waiting'][intersection] return reward def reward_function_3(self, previous_observation, action): reward = 0 num_of_intersections = self.simulation.rows * self.simulation.cols for intersection in range(num_of_intersections): # If the vertical lights turn green if previous_observation['lights_settings'][intersection] >= 1 and action[intersection] >= 0.5: for car in range(self.simulation.road_length): if previous_observation['vertical_waiting_time'][intersection][car] != -1: reward += previous_observation['vertical_waiting_time'][intersection][car] if previous_observation['horizontal_waiting_time'][intersection][car] != -1: reward -= previous_observation['horizontal_waiting_time'][intersection][car] # If the horizontal lights turn green if previous_observation['lights_settings'][intersection] == 0 and action[intersection] >= 0.5: for car in range(self.simulation.road_length): if previous_observation['horizontal_waiting_time'][intersection][car] != -1: reward += previous_observation['horizontal_waiting_time'][intersection][car] if previous_observation['vertical_waiting_time'][intersection][car] != -1: reward -= previous_observation['vertical_waiting_time'][intersection][car] return reward def reward_function_4(self, previous_observation, action): reward = 0 num_of_intersections = self.simulation.rows * self.simulation.cols for intersection in range(num_of_intersections): # If the vertical lights turn green if previous_observation['lights_settings'][intersection] == 1 and action[intersection] == 1: if previous_observation['vertical_waiting_time'][intersection][0] != -1: reward += previous_observation['vertical_waiting_time'][intersection][0] if previous_observation['horizontal_waiting_time'][intersection][0] != -1: reward -= previous_observation['horizontal_waiting_time'][intersection][0] # If the horizontal lights turn green if previous_observation['lights_settings'][intersection] == 0 and action[intersection] == 1: if previous_observation['horizontal_waiting_time'][intersection][0] != -1: reward += previous_observation['horizontal_waiting_time'][intersection][0] if previous_observation['vertical_waiting_time'][intersection][0] != -1: reward -= previous_observation['vertical_waiting_time'][intersection][0] return reward def reward_function_6(self, current_observation): return - current_observation['average_waiting_time'][0] def reward_function_7(self, previous_observation, action): reward = 0 if action < self.simulation.rows * self.simulation.cols: if previous_observation['ready_to_switch'][action] == 0: reward -= 1 return reward def reward_function_8(self, previous_observation, action): reward = 0 if action < self.simulation.rows * self.simulation.cols: if previous_observation['lights_settings'][action] == 1: reward += (previous_observation['vertical_num_of_cars_waiting'][action] - previous_observation['horizontal_num_of_cars_waiting'][action]) / self.simulation.road_length else: reward += (previous_observation['horizontal_num_of_cars_waiting'][action] - previous_observation['vertical_num_of_cars_waiting'][action]) / self.simulation.road_length if previous_observation['ready_to_switch'][action] == 0: reward -= 1 return reward def reward_function_9(self, previous_observation, action): reward = -4 if action < self.simulation.rows * self.simulation.cols: if previous_observation['lights_settings'][action] == 1: reward += previous_observation['vertical_num_of_cars_waiting'][action] - previous_observation['horizontal_num_of_cars_waiting'][action] else: reward += previous_observation['horizontal_num_of_cars_waiting'][action] - previous_observation['vertical_num_of_cars_waiting'][action] return reward def reward_function_10(self, previous_observation, action): if action < self.simulation.rows * self.simulation.cols: # print('vertical cars: ' + str(previous_observation['vertical_num_of_cars'][action]), 'horizontal cars: ' + str(previous_observation['horizontal_num_of_cars'][action])) # reward = -10 if previous_observation['ready_to_switch'][action] == 0 else 0 reward = - self.simulation.road_length / 2 if previous_observation['lights_settings'][action] == 1: reward += min(previous_observation['vertical_num_of_cars'][action] - previous_observation['horizontal_num_of_cars'][action], self.simulation.road_length) else: reward += min(previous_observation['horizontal_num_of_cars'][action] - previous_observation['vertical_num_of_cars'][action], self.simulation.road_length) else: reward = 0 not_action = action - self.simulation.rows * self.simulation.cols if previous_observation['lights_settings'][not_action] == 1: reward += max(previous_observation['horizontal_num_of_cars'][not_action] - previous_observation['vertical_num_of_cars'][not_action], - self.simulation.road_length) else: reward += max(previous_observation['vertical_num_of_cars'][not_action] - previous_observation['horizontal_num_of_cars'][not_action], - self.simulation.road_length) # print('action: ' + str(action) + ', reward: ' + str(reward)) return reward def reward_function_11(self, prev_obs, action): reward = 0 if action == 1: reward = - self.simulation.road_length if prev_obs['lights_settings'][0] == 1: reward += get_value_or_delimiter(value=prev_obs['num_of_cars'][0][0] - prev_obs['num_of_cars'][0][1], delimiter=[-self.simulation.road_length, self.simulation.road_length]) # reward += get_value_or_delimiter(value=prev_obs['num_of_cars'][0][0] - prev_obs['num_of_cars'][1][0], delimiter=[-self.simulation.road_length, self.simulation.road_length]) # reward += get_value_or_delimiter(value=- prev_obs['num_of_cars'][0][1] + self.simulation.road_length, delimiter=[-self.simulation.road_length, 0]) else: reward += get_value_or_delimiter(value=prev_obs['num_of_cars'][0][1] - prev_obs['num_of_cars'][0][0], delimiter=[-self.simulation.road_length, self.simulation.road_length]) # reward += get_value_or_delimiter(value=prev_obs['num_of_cars'][0][1] - prev_obs['num_of_cars'][1][1], delimiter=[-self.simulation.road_length, self.simulation.road_length]) # reward += get_value_or_delimiter(value=- prev_obs['num_of_cars'][0][0] + self.simulation.road_length, delimiter=[-self.simulation.road_length, 0]) else: if prev_obs['lights_settings'][0] == 0: reward += get_value_or_delimiter(value=prev_obs['num_of_cars'][0][0] - prev_obs['num_of_cars'][0][1], delimiter=[-self.simulation.road_length, self.simulation.road_length]) # reward += get_value_or_delimiter(value=prev_obs['num_of_cars'][0][0] - prev_obs['num_of_cars'][1][0], delimiter=[-self.simulation.road_length, self.simulation.road_length]) # reward += get_value_or_delimiter(value=- prev_obs['num_of_cars'][0][0] + self.simulation.road_length, delimiter=[-self.simulation.road_length, 0]) else: reward += get_value_or_delimiter(value=prev_obs['num_of_cars'][0][1] - prev_obs['num_of_cars'][0][0], delimiter=[-self.simulation.road_length, self.simulation.road_length]) # reward += get_value_or_delimiter(value=prev_obs['num_of_cars'][0][1] - prev_obs['num_of_cars'][1][1], delimiter=[-self.simulation.road_length, self.simulation.road_length]) # reward += get_value_or_delimiter(value=- prev_obs['num_of_cars'][0][1] + self.simulation.road_length, delimiter=[-self.simulation.road_length, 0]) # print('action: ' + str(action) + ', reward: ' + str(reward)) # print('vertical cars: ' + str(prev_obs['num_of_cars'][0][0]), 'horizontal cars: ' + str(prev_obs['num_of_cars'][0][1]) + '\n') return reward def reward_function_12(self, prev_obs, action): reward = 0 if prev_obs['ready_to_switch'] == 0: if action == 1: reward = -10 else: if action == 1: if prev_obs['lights_settings'][0] == 1: reward += 1 if prev_obs['num_of_cars'][0][0] > 8 and prev_obs['num_of_cars'][0][1] < 2 else 0 # reward += 1 if prev_obs['num_of_cars'][1][0] < 2 else 0 else: reward += 1 if prev_obs['num_of_cars'][0][1] > 8 and prev_obs['num_of_cars'][0][0] < 2 else 0 # reward += 1 if prev_obs['num_of_cars'][2][1] < 2 else 0 else: if prev_obs['lights_settings'][0] == 0: reward += 1 if prev_obs['num_of_cars'][0][0] > 8 else 0 else: reward += 1 if prev_obs['num_of_cars'][0][1] > 8 else 0 # if self.simulation.intersection_to_process == 2: # print('action: ' + str(action) + ', reward: ' + str(reward)) # print('vertical cars: ' + str(prev_obs['num_of_cars'][0][0]), 'horizontal cars: ' + str(prev_obs['num_of_cars'][0][1]) + '\n') return reward def definitive2x2(self, prev_obs, action): reward = 0 vertical_load = prev_obs['intersection_cars'][0] # + prev_obs['input_cars'][0] horizontal_load = prev_obs['intersection_cars'][1] # + prev_obs['input_cars'][1] if prev_obs['lights_settings'][0] == 0: if horizontal_load > 2 * vertical_load: if action == 1: reward = 1 else: reward = -1 elif vertical_load > 2 * horizontal_load: if action == 1: reward = -1 else: reward = 1 elif action == 1: reward = -1 if prev_obs['lights_settings'][0] == 1: if horizontal_load > 2 * vertical_load: if action == 1: reward = -1 else: reward = 1 elif vertical_load > 2 * horizontal_load: if action == 1: reward = 1 else: reward = -1 elif action == 1: reward = -1 if self.simulation.intersection_to_process == 20: print('The vertical load is: ' + str(vertical_load)) print('The horizontal load is: ' + str(horizontal_load)) print('The green light is: ' + str('VERTICAL' if prev_obs['lights_settings'][0] == 0 else 'HORIZONTAL')) print('The action is: ' + str('MAINTAIN' if action == 0 else 'CHANGE')) print('The reward is: ' + str(reward)) print('\n') return reward def definitive3x3(self, prev_obs, action): reward = 0 vertical_load = prev_obs['intersection_cars'][0] horizontal_load = prev_obs['intersection_cars'][1] vertical_output_load = prev_obs['output_cars'][0] horizontal_output_load = prev_obs['output_cars'][1] if prev_obs['lights_settings'][0] == 0: if horizontal_load - vertical_load > 6: reward = 1 if action == 1 else -1 elif vertical_load - horizontal_load > 4: reward = -1 if action == 1 else 1 elif vertical_output_load - horizontal_output_load > 6: reward = 1 if action == 1 else -1 elif horizontal_output_load - vertical_output_load > 4: reward = -1 if action == 1 else 1 elif vertical_load > 5 and horizontal_load > 5 and vertical_output_load - horizontal_output_load > 3: reward = 1 if action == 1 else -1 elif vertical_output_load == 10: reward = 1 if action == 1 else -1 elif action == 1: reward = -1 if prev_obs['lights_settings'][0] == 1: if vertical_load - horizontal_load > 6: reward = 1 if action == 1 else -1 elif horizontal_load - vertical_load > 4: reward = -1 if action == 1 else 1 elif horizontal_output_load - vertical_output_load > 6: reward = 1 if action == 1 else -1 elif vertical_output_load - horizontal_output_load > 4: reward = -1 if action == 1 else 1 elif horizontal_load > 5 and vertical_load > 5 and horizontal_output_load - vertical_output_load > 3: reward = 1 if action == 1 else -1 elif horizontal_output_load == 10: reward = 1 if action == 1 else -1 elif action == 1: reward = -1 print('The intersection is: ' + str(self.simulation.intersection_to_process)) print('The vertical load is: ' + str(vertical_load)) print('The horizontal load is: ' + str(horizontal_load)) print('The vertical output load is: ' + str(vertical_output_load)) print('The horizontal output load is: ' + str(horizontal_output_load)) print('The green light is: ' + str('VERTICAL' if prev_obs['lights_settings'][0] == 0 else 'HORIZONTAL')) print('The action is: ' + str('MAINTAIN' if action == 0 else 'CHANGE')) print('The reward is: ' + str(reward)) print('\n') return reward

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70b086468733c1b6ce77c49c47bc0d4d8412c1dd

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py

Python

enthought/mayavi/components/implicit_plane.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

3

2016-12-09T06:05:18.000Z

2018-03-01T13:00:29.000Z

enthought/mayavi/components/implicit_plane.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

1

2020-12-02T00:51:32.000Z

2020-12-02T08:48:55.000Z

enthought/mayavi/components/implicit_plane.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

null

# proxy module from __future__ import absolute_import from mayavi.components.implicit_plane import *

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py

Python

backend/src/analytics/admin.py

codingforentrepreneurs/Geolocator-2

d4c2410301aa2497816e7ed2ec1890bc9be2e8fd

[ "MIT" ]

34

2017-04-27T20:22:08.000Z

2021-11-08T13:01:43.000Z

backend/src/analytics/admin.py

hercules261188/Geolocator-2

d4c2410301aa2497816e7ed2ec1890bc9be2e8fd

[ "MIT" ]

null

backend/src/analytics/admin.py

hercules261188/Geolocator-2

d4c2410301aa2497816e7ed2ec1890bc9be2e8fd

[ "MIT" ]

34

2017-05-18T23:23:01.000Z

2022-03-02T21:08:54.000Z

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

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0

5

cb0840d5bc91aaecbc980279a62bae916478d2ee

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py

Python

conference/forms/__init__.py

zevaverbach/epcon

8352c030ee0d4197f559cdb58a54ee45c7a4471a

[ "BSD-2-Clause" ]

null

conference/forms/__init__.py

zevaverbach/epcon

8352c030ee0d4197f559cdb58a54ee45c7a4471a

[ "BSD-2-Clause" ]

null

conference/forms/__init__.py

zevaverbach/epcon

8352c030ee0d4197f559cdb58a54ee45c7a4471a

[ "BSD-2-Clause" ]

null

from .forms import * # noqa from .talks import * # noqa

19.333333

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null

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5

cb779cc66f314d2d2731877166e373742311a2fe

428

py

Python

editor/importme.py

Amazeryogo/surf-exel

0d6a43a7ba2b059f61405db846e546308a035733

[ "MIT" ]

3

2020-08-12T05:59:47.000Z

2020-11-08T00:01:04.000Z

editor/importme.py

Amazeryogo/surf-exel

0d6a43a7ba2b059f61405db846e546308a035733

[ "MIT" ]

8

2020-08-19T06:24:06.000Z

2020-10-27T04:37:46.000Z

editor/importme.py

Amazeryogo/surf-exel

0d6a43a7ba2b059f61405db846e546308a035733

[ "MIT" ]

1

2020-10-25T13:35:17.000Z

from Tkinter import * from Tkinter import filedialog, simpledialog from Tkinter import messagebox from editor.settings import backgroundcolor as bc from editor.settings import forgroundcolor as fc from editor.settings import back as b from editor.settings import fore as f from editor.settings import size from editor.settings import font as fontx from gtts import gTTS import playsound import os # Imported everything here

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null

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0

1

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5

cb84957ad1b624b8b574c38b8823c92d6f5be898

96

py

Python

werewolf/models/__init__.py

LucienZhang/werewolf-back

289468c3589a7ad101358175e26401ba6b3b4f16

[ "MIT" ]

null

werewolf/models/__init__.py

LucienZhang/werewolf-back

289468c3589a7ad101358175e26401ba6b3b4f16

[ "MIT" ]

null

werewolf/models/__init__.py

LucienZhang/werewolf-back

289468c3589a7ad101358175e26401ba6b3b4f16

[ "MIT" ]

null

from .base import Base from .user import User from .game import Game from .role import Role

19.2

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1

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1

0

5

cbbbcdd9a359c2d8bfbdd28aa61f833e1d9364df

362

py

Python

tests/__init__.py

zhester/jdi

18d43331f15776a5ef94342ac85a24a083a3c7d7

[ "BSD-2-Clause" ]

null

tests/__init__.py

zhester/jdi

18d43331f15776a5ef94342ac85a24a083a3c7d7

[ "BSD-2-Clause" ]

null

tests/__init__.py

zhester/jdi

18d43331f15776a5ef94342ac85a24a083a3c7d7

[ "BSD-2-Clause" ]

null

#============================================================================= # # JDI Unit Tests # #============================================================================= """ JDI Unit Tests ============== Run all unit tests from project's root directory. python -m unittest discover python3 -m unittest discover """ __version__ = '0.0.0'

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cbce8d593e80431df2ec54039449d1df714915f5

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py

Python

src/Python/flask/app.py

mwaseem75/iris-python-template

c8d75e22a6eee33e796d28f5508fd656a6ea58d6

[ "MIT" ]

null

src/Python/flask/app.py

mwaseem75/iris-python-template

c8d75e22a6eee33e796d28f5508fd656a6ea58d6

[ "MIT" ]

null

src/Python/flask/app.py

mwaseem75/iris-python-template

c8d75e22a6eee33e796d28f5508fd656a6ea58d6

[ "MIT" ]

1

2022-02-21T05:14:48.000Z

from flask import Flask, jsonify, Response, request, make_response, render_template from definitions.passenger import Passenger import json,util,io,random import iris from matplotlib.backends.backend_agg import FigureCanvasAgg from matplotlib.backends.backend_svg import FigureCanvasSVG from matplotlib.figure import Figure app = Flask(__name__) app.secret_key = "abc222" # ---------------------------------------------------------------- ### CRUD FOR TITANIC_TABLE.PASSENGER # ---------------------------------------------------------------- @app.route("/") def index(): content = util.get_dashboard_stats() return render_template('index.html', content = content) @app.route("/processes") def processes(): iris.cls("Embedded.Utils").SetNameSpace("USER") statement = iris.sql.exec(util.get_sql_stat("processes")) df = statement.dataframe() my_data=json.loads(df.to_json(orient="split"))["data"] my_cols=[{"title": str(col)} for col in json.loads(df.to_json(orient="split"))["columns"]] ftitle = "Processes" fheading = "Currently runnung processes" content = util.get_sidebar_stats() return render_template('tablesdata.html', ftitle = ftitle, fheading = fheading, my_data = my_data, my_cols = my_cols, content = content) @app.route("/messages") def messages(): iris.cls("Embedded.Utils").SetNameSpace("USER") statement = iris.sql.exec(util.get_sql_stat("messages")) df = statement.dataframe() my_data=json.loads(df.to_json(orient="split"))["data"] my_cols=[{"title": str(col)} for col in json.loads(df.to_json(orient="split"))["columns"]] ftitle = "Messages" fheading = "Production Messages" content = util.get_sidebar_stats() return render_template('tablesdata.html', ftitle = ftitle, fheading = fheading, my_data = my_data, my_cols = my_cols, content = content) @app.route("/securityusers") def securityusers(): iris.cls("Embedded.Utils").SetNameSpace("%SYS") statement = iris.sql.exec(util.get_sql_stat("securityusers")) df = statement.dataframe() my_data=json.loads(df.to_json(orient="split"))["data"] my_cols=[{"title": str(col)} for col in json.loads(df.to_json(orient="split"))["columns"]] ftitle = "Users" fheading = "Security Users" content = util.get_sidebar_stats() return render_template('tablesdata.html', ftitle = ftitle, fheading = fheading, my_data = my_data, my_cols = my_cols, content = content) @app.route("/securityapps") def securityapps(): iris.cls("Embedded.Utils").SetNameSpace("%SYS") statement = iris.sql.exec(util.get_sql_stat("securityapps")) df = statement.dataframe() my_data=json.loads(df.to_json(orient="split"))["data"] my_cols=[{"title": str(col)} for col in json.loads(df.to_json(orient="split"))["columns"]] ftitle = "Applications" fheading = "Created Applications" content = util.get_sidebar_stats() return render_template('tablesdata.html', ftitle = ftitle, fheading = fheading, my_data = my_data, my_cols = my_cols, content = content) @app.route("/elassert") def elassert(): iris.cls("Embedded.Utils").SetNameSpace("USER") statement = iris.sql.exec(util.get_sql_stat("elassert")) df = statement.dataframe() my_data=json.loads(df.to_json(orient="split"))["data"] my_cols=[{"title": str(col)} for col in json.loads(df.to_json(orient="split"))["columns"]] ftitle = "Assert" fheading = "Event Log Assert" content = util.get_sidebar_stats() return render_template('tablesdata.html', ftitle = ftitle, fheading = fheading, my_data = my_data, my_cols = my_cols, content = content) @app.route("/elerror") def elerror(): iris.cls("Embedded.Utils").SetNameSpace("USER") statement = iris.sql.exec(util.get_sql_stat("elerror")) df = statement.dataframe() my_data=json.loads(df.to_json(orient="split"))["data"] my_cols=[{"title": str(col)} for col in json.loads(df.to_json(orient="split"))["columns"]] ftitle = "Error" fheading = "Event Log Error" content = util.get_sidebar_stats() return render_template('tablesdata.html', ftitle = ftitle, fheading = fheading, my_data = my_data, my_cols = my_cols, content = content) @app.route("/elwarning") def elwarning(): statement = iris.sql.exec(util.get_sql_stat("elwarning")) df = statement.dataframe() my_data=json.loads(df.to_json(orient="split"))["data"] my_cols=[{"title": str(col)} for col in json.loads(df.to_json(orient="split"))["columns"]] ftitle = "Warning" fheading = "Event Log Warning" content = util.get_sidebar_stats() return render_template('tablesdata.html', ftitle = ftitle, fheading = fheading, my_data = my_data, my_cols = my_cols, content = content) @app.route("/elinfo") def elinfo(): statement = iris.sql.exec(util.get_sql_stat("elinfo")) df = statement.dataframe() my_data=json.loads(df.to_json(orient="split"))["data"] my_cols=[{"title": str(col)} for col in json.loads(df.to_json(orient="split"))["columns"]] ftitle = "Info" fheading = "Event Log Info" content = util.get_sidebar_stats() return render_template('tablesdata.html', ftitle = ftitle, fheading = fheading, my_data = my_data, my_cols = my_cols, content = content) @app.route("/eltrace") def eltrace(): statement = iris.sql.exec(util.get_sql_stat("eltrace")) df = statement.dataframe() my_data=json.loads(df.to_json(orient="split"))["data"] my_cols=[{"title": str(col)} for col in json.loads(df.to_json(orient="split"))["columns"]] ftitle = "Trace" fheading = "Event Log Trace" content = util.get_sidebar_stats() return render_template('tablesdata.html', ftitle = ftitle, fheading = fheading, my_data = my_data, my_cols = my_cols, content = content) @app.route("/elevent") def elevent(): statement = iris.sql.exec(util.get_sql_stat("elalert")) df = statement.dataframe() my_data=json.loads(df.to_json(orient="split"))["data"] my_cols=[{"title": str(col)} for col in json.loads(df.to_json(orient="split"))["columns"]] ftitle = "Alert" fheading = "Event Log Alert" content = util.get_sidebar_stats() return render_template('tablesdata.html', ftitle = ftitle, fheading = fheading, my_data = my_data, my_cols = my_cols, content = content) # GET all passengers @app.route("/api/passengers") def getAllPassengers(): payload = {} payload['passengers'] = [] tp = {} name = request.args.get('name') currPage = request.args.get('currPage') pageSize = request.args.get('pageSize') if name is not None: # If search by name query = "SELECT ID FROM Titanic_Table.Passenger WHERE name %STARTSWITH ?" rs = iris.sql.exec(query, name) for i in rs: # We create an iris object tp = iris.ref(1) # We get the json in a string iris.cls("Titanic.Table.Passenger")._OpenId(i[0])._JSONExportToString(tp) # We normalize the string to get it in python tp = iris.cls("%String").Normalize(tp) # We load the string in a dict tp = json.loads(tp) # We add the id tp['passengerId'] = i[0] payload['passengers'].append(tp) else: currPage = int(currPage) if currPage is not None else 1 pageSize = int(pageSize) if pageSize is not None else 10 tFrom = ((currPage -1 ) * pageSize)+1 tTo = tFrom + (pageSize-1) query = """ SELECT * FROM ( SELECT ID, ROW_NUMBER() OVER (ORDER By ID ASC) rn FROM Titanic_Table.Passenger ) tmp WHERE rn between {} and {} ORDER By ID ASC """.format(tFrom,tTo) rs = iris.sql.exec(query) for i in rs: # We create an iris object tp = iris.ref(1) # We get the json in a string iris.cls("Titanic.Table.Passenger")._OpenId(i[0])._JSONExportToString(tp) # We normalize the string to get it in python tp = iris.cls("%String").Normalize(tp) # We load the string in a dict tp = json.loads(tp) # We add the id tp['passengerId'] = i[0] payload['passengers'].append(tp) # Getting the total number of passengers rs = iris.sql.exec("SELECT COUNT(*) FROM Titanic_Table.Passenger") payload['total'] = rs.__next__()[0] payload['query'] = query return jsonify(payload) # POST a new passenger @app.route("/api/passengers", methods=["POST"]) def createPassenger(): # Retreiving the data in request body passenger = request.get_json() query = "INSERT INTO Titanic_Table.Passenger (survived, pclass, name, sex, age, sibSp, parCh, ticket, fare, cabin, embarked) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)" # Getting the new ID of the passenger newId = int(iris.sql.exec("SELECT MAX(ID) FROM Titanic_Table.Passenger").__next__()[0]) + 1 try: iris.sql.exec(query, passenger['survived'], passenger['pclass'], passenger['name'], passenger['sex'], passenger['age'], passenger['sibSp'], passenger['parCh'], passenger['ticket'], passenger['fare'], passenger['cabin'], passenger['embarked']) except: return make_response( 'Bad Request', 400 ) payload = { 'query': query, 'passengerId': newId } return jsonify(payload) # GET passenger with id @app.route("/api/passengers/<int:id>", methods=["GET"]) def getPassenger(id): payload = {} query = "SELECT * FROM Titanic_Table.Passenger WHERE ID = ?" rs = iris.sql.exec(query, str(id)) try : passenger = Passenger(rs.__next__()).__dict__ except: return make_response( 'Not Found', 204 ) payload['passenger'] = passenger payload['query'] = query return jsonify(payload) # PUT to update passenger with id @app.route("/api/passengers/<int:id>", methods=["PUT"]) def updatePassenger(id): # First, checking to see if the passenger exists query = "SELECT ID FROM Titanic_Table.Passenger WHERE ID = ?" rs = iris.sql.exec(query, str(id)) try : rs.__next__() except: return make_response( 'Not Found', 204 ) # Updating passenger = request.get_json() query = "UPDATE Titanic_Table.Passenger SET survived = ?, pclass = ?, name = ?, sex = ?, age = ?, sibSp = ?, parCh = ?, ticket = ?, fare = ?, cabin = ?, embarked = ? WHERE ID = ?" try: iris.sql.exec(query, passenger['survived'], passenger['pclass'], passenger['name'], passenger['sex'], passenger['age'], passenger['sibSp'], passenger['parCh'], passenger['ticket'], passenger['fare'], passenger['cabin'], passenger['embarked'], id) except: return make_response( 'Bad Request', 400 ) payload = { 'query': query, } return jsonify(payload) # DELETE passenger with id @app.route("/api/passengers/<int:id>", methods=["DELETE"]) def deletePassenger(id): payload = {} query = "DELETE FROM Titanic_Table.Passenger WHERE ID = ?" try: iris.sql.exec(query, str(id)) except: return make_response( 'Not Found', 204 ) payload['query'] = query return jsonify(payload) def getP(): payload = {} payload['passengers'] = [] tp = {} name = request.args.get('name') currPage = request.args.get('currPage') pageSize = request.args.get('pageSize') currPage = int(currPage) if currPage is not None else 1 pageSize = int(pageSize) if pageSize is not None else 10 tFrom = ((currPage -1 ) * pageSize)+1 tTo = tFrom + (pageSize-1) query = """ SELECT * FROM ( SELECT ID, ROW_NUMBER() OVER (ORDER By ID ASC) rn FROM Titanic_Table.Passenger ) tmp WHERE rn between {} and {} ORDER By ID ASC """.format(tFrom,tTo) rs = iris.sql.exec(query) for i in rs: # We create an iris object tp = iris.ref(1) # We get the json in a string iris.cls("Titanic.Table.Passenger")._OpenId(i[0])._JSONExportToString(tp) # We normalize the string to get it in python tp = iris.cls("%String").Normalize(tp) # We load the string in a dict tp = json.loads(tp) # We add the id tp['passengerId'] = i[0] payload['passengers'].append(tp) # Getting the total number of passengers rs = iris.sql.exec("SELECT COUNT(*) FROM Titanic_Table.Passenger") payload['total'] = rs.__next__()[0] payload['query'] = query return jsonify(payload) @app.route("/matplot") def matplot(): """ Returns html with the img tag for your plot. """ content = util.get_sidebar_stats() num_x_points = int(request.args.get("num_x_points", 50)) return render_template('matplot.html', content = content, num_x_points = num_x_points) @app.route("/matplot-as-image-<int:num_x_points>.png") def plot_png(num_x_points=50): """ renders the plot on the fly. """ fig = Figure() axis = fig.add_subplot(1, 1, 1) x_points = range(num_x_points) axis.plot(x_points, [random.randint(1, 30) for x in x_points]) output = io.BytesIO() FigureCanvasAgg(fig).print_png(output) return Response(output.getvalue(), mimetype="image/png") # ---------------------------------------------------------------- ### MAIN PROGRAM # ---------------------------------------------------------------- if __name__ == '__main__': app.run('0.0.0.0', port = "8080", debug=True)

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5

1dbddad7e6aa4ab9f3b4b98398e41967db617fa0

2,989

py

Python

database/models.py

zdresearch/Nettacker

6d1653df01fee06ac6906a3cb1beebed39c166ef

[ "Apache-2.0" ]

884

2020-09-26T01:12:09.000Z

2022-03-31T07:39:23.000Z

database/models.py

GeauxWeisbeck4/Nettacker

0d6a907f4528b42ff6460c8a1e58f73ae768b38e

[ "Apache-2.0" ]

185

2018-04-18T12:16:27.000Z

2020-09-25T10:37:23.000Z

database/models.py

GeauxWeisbeck4/Nettacker

0d6a907f4528b42ff6460c8a1e58f73ae768b38e

[ "Apache-2.0" ]

236

2020-09-26T22:19:29.000Z

2022-03-30T08:21:28.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import (Column, Integer, Text, DateTime) Base = declarative_base() class Report(Base): """ This class defines the table schema of the reports table. Any changes to the reports table need to be done here. """ __tablename__ = 'reports' id = Column(Integer, primary_key=True, autoincrement=True) date = Column(DateTime) scan_unique_id = Column(Text) report_path_filename = Column(Text) options = Column(Text) def __repr__(self): """ returns a printable representation of the object of the class Report """ return "<Report(id={0}, scan_unique_id={1}, date={2}, report_path_filename={3})>".format( self.id, self.scan_unique_id, self.date, self.report_path_filename ) class TempEvents(Base): """ This class defines the table schema of the reports table. Any changes to the reports table need to be done here. """ __tablename__ = 'temp_events' id = Column(Integer, primary_key=True, autoincrement=True) date = Column(DateTime) target = Column(Text) module_name = Column(Text) scan_unique_id = Column(Text) event_name = Column(Text) port = Column(Text) event = Column(Text) data = Column(Text) def __repr__(self): """ returns a printable representation of the object of the class Report """ return ''' <scan_events(id={0}, target={1}, date={2}, module_name={3}, scan_unqiue_id={4}, port={5}, event={6}, data={7})> '''.format( self.id, self.target, self.date, self.module_name, self.scan_unique_id, self.port, self.event, self.data ) class HostsLog(Base): """ This class defines the table schema of the hosts_log table. Any changes to the reports hosts_log need to be done here. """ __tablename__ = 'scan_events' id = Column(Integer, primary_key=True, autoincrement=True) date = Column(DateTime) target = Column(Text) module_name = Column(Text) scan_unique_id = Column(Text) port = Column(Text) event = Column(Text) json_event = Column(Text) def __repr__(self): """ returns a printable representation of the object of the class HostsLog """ return ''' <scan_events(id={0}, target={1}, date={2}, module_name={3}, scan_unqiue_id={4}, port={5}, event={6}, json_event={7})> '''.format( self.id, self.target, self.date, self.module_name, self.scan_unique_id, self.port, self.event, self.json_event )

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17,756

py

Python

baselines/deepq/assembly/data/plot_result.py

DengYuelin/baselines-assembly

d40171845349395f0ed389d725873b389b08f94f

[ "MIT" ]

1

2022-03-23T02:35:05.000Z

baselines/deepq/assembly/data/plot_result.py

DengYuelin/baselines-assembly

d40171845349395f0ed389d725873b389b08f94f

[ "MIT" ]

null

baselines/deepq/assembly/data/plot_result.py

DengYuelin/baselines-assembly

d40171845349395f0ed389d725873b389b08f94f

[ "MIT" ]

3

2018-12-20T10:10:57.000Z

2020-08-07T10:12:57.000Z

# -*- coding: utf-8 -*- """ # @Time : 24/10/18 2:40 PM # @Author : ZHIMIN HOU # @FileName: plot_result.py # @Software: PyCharm # @Github ： https://github.com/hzm2016 """ import collections import matplotlib.pyplot as plt import numpy as np import pickle import copy as cp from baselines.deepq.assembly.src.value_functions import * """=================================Plot result=====================================""" # YLABEL = ['$F_x(N)$', '$F_y(N)$', '$F_z(N)$', '$M_x(Nm)$', '$M_y(Nm)$', '$M_z(Nm)$'] YLABEL = ['$F_x$(N)', '$F_y$(N)', '$F_z$(N)', '$M_x$(Nm)', '$M_y$(Nm)', '$M_z$(Nm)'] Title = ["X axis force", "Y axis force", "Z axis force", "X axis moment", "Y axis moment", "Z axis moment"] High = np.array([40, 40, 0, 5, 5, 5, 542, -36, 188, 5, 5, 5]) Low = np.array([-40, -40, -40, -5, -5, -5, 538, -42, 192, -5, -5, -5]) scale = np.array([40, 40, 40, 5, 5, 5]) """=================================================================================""" plt.rcParams['font.sans-serif']=['SimHei'] plt.rcParams['axes.unicode_minus']=False def plot(result_path): plt.figure(figsize=(15, 15), dpi=100) plt.title('Search Result') prediction_result = np.load(result_path) for i in range(len(prediction_result)): for j in range(6): line = prediction_result[:, j] # plt.subplot(2, 3, j+1) plt.plot(line) plt.ylabel(YLABEL[j]) plt.xlabel('steps') plt.legend(YLABEL) plt.show() def plot_force_and_moment(path_2, path_3): V_force = np.load(path_2) V_state = np.load(path_3) plt.figure(figsize=(15, 10), dpi=100) plt.title("Search Result of Force", fontsize=20) plt.plot(V_force[:100]) plt.xlabel("Steps", fontsize=20) plt.ylabel("F(N)", fontsize=20) plt.legend(labels=['Fx', 'Fy', 'Fz', 'Mx', 'My', 'Mz'], loc='best', fontsize=20) plt.xticks(fontsize=15) plt.yticks(fontsize=15) plt.figure(figsize=(15, 10), dpi=100) plt.title("Search Result of State", fontsize=20) plt.plot(V_state[:100] - [539.88427, -38.68679, 190.03184, 179.88444, 1.30539, 0.21414]) plt.xlabel("Steps", fontsize=20) plt.ylabel("Coordinate", fontsize=20) plt.legend(labels=['x', 'y', 'z', 'rx', 'ry', 'rz'], loc='best', fontsize=20) plt.xticks(fontsize=15) plt.yticks(fontsize=15) plt.show() def plot_reward(reward_path): reward = np.load(reward_path) print(reward[0]) plt.figure(figsize=(15, 15), dpi=100) plt.title('Episode Reward') plt.plot(np.arange(len(reward) - 1), np.array(reward[1:])) plt.ylabel('Episode Reward') plt.xlabel('Episodes') plt.show() def plot_raw_data(path_1): data = np.load(path_1) force_m = np.zeros((len(data), 12)) plt.figure(figsize=(20, 20), dpi=100) plt.tight_layout(pad=3, w_pad=0.5, h_pad=1.0) plt.subplots_adjust(left=0.065, bottom=0.1, right=0.995, top=0.9, wspace=0.2, hspace=0.2) plt.title("True Data") for j in range(len(data)): force_m[j] = data[j, 0] k = -1 for i in range(len(data)): if data[i, 1] == 0: print("===========================================") line = force_m[k+1:i+1] print(line) k = i for j in range(6): plt.subplot(2, 3, j + 1) plt.plot(line[:, j]) # plt.plot(line[:, 0]) if j == 1: plt.ylabel(YLABEL[j], fontsize=17.5) plt.xlabel('steps', fontsize=20) plt.xticks(fontsize=15) plt.yticks(fontsize=15) else: plt.ylabel(YLABEL[j], fontsize=20) plt.xlabel('steps', fontsize=20) plt.xticks(fontsize=15) plt.yticks(fontsize=15) i += 1 def plot_continuous_data(path): raw_data = np.load(path) plt.figure(figsize=(20, 15)) plt.title('Episode Reward') plt.tight_layout(pad=3, w_pad=0.5, h_pad=1.0) plt.subplots_adjust(left=0.1, bottom=0.15, right=0.98, top=0.9, wspace=0.23, hspace=0.22) # plt.subplots_adjust(left=0.065, bottom=0.1, right=0.995, top=0.9, wspace=0.2, hspace=0.2) data = np.zeros((len(raw_data), 12)) for j in range(len(raw_data)): data[j] = raw_data[j, 0] for j in range(6): plt.subplot(2, 3, j + 1) plt.plot(data[:, j]*scale[j], linewidth=2.5) # plt.ylabel(YLABEL[j], fontsize=18) if j>2: plt.xlabel('steps', fontsize=30) plt.title(YLABEL[j], fontsize=30) plt.xticks(fontsize=25) plt.yticks(fontsize=25) # plt.subplots_adjust(left=0.1, bottom=0.1, right=0.9, top=0.9, wspace=0.4, hspace=0.2) plt.savefig('raw_data.pdf') plt.show() def compute_true_return(path): raw_data = np.load(path) # print(raw_data) clock = 0 G = 0. past_gammas = [] past_cumulants = [] all_G = [] for i in range(len(raw_data)): observation, action, done, action_probability = raw_data[i] if done == False: gamma = 0.99 else: gamma = 0. past_gammas.append(gamma) past_cumulants.append(1) if done == False: clock += 1 G = 0 all_G.append(cp.deepcopy(G)) else: print('clock', clock) for j in reversed(range(0, clock + 1)): G *= past_gammas[j] G += past_cumulants[j] all_G.append(cp.deepcopy(G)) clock = 0 past_cumulants = [] past_gammas = [] print(len(raw_data)) plt.figure(figsize=(20, 15)) plt.plot(all_G[300:400]) plt.show() return all_G # Plot the true prediction and true value def plot_different_gamma_data(path): f = open(path, 'rb') titles = ['$\gamma = 0.4$', '$\gamma = 0.8$', '$\gamma = 0.96$', '$\gamma =1.0$'] # true_data = compute_true_return('prediction_result_different_gamma.npy') # f = open('../data/learning_result_policy', 'rb') # plot_value_functions = ['Move down Fy', 'Move down Fx', 'Move down Fz', 'Move down Mx', 'Move down My', 'Move down Mz'] plot_value_functions = ['Move down step', 'Move down step 2', 'Move down step 3', 'Move down step 4'] # plot_value_functions = ['Move down Fx', 'Move down Fx 1', 'Move down Fx 2', 'Move down Fx 3'] raw_data = pickle.load(f) plt.figure(figsize=(20, 15)) plt.tight_layout(pad=3, w_pad=1., h_pad=0.5) plt.subplots_adjust(left=0.1, bottom=0.15, right=0.98, top=0.9, wspace=0.23, hspace=0.23) # legend = sorted([key for key in plot_value_functions.keys()]) # print(legend) # print(value_functions.keys()) for j, key in enumerate(plot_value_functions): plt.subplot(2, 2, j + 1) # print(list(raw_data[('GTD(1)', 'Hindsight Error')][key])) # plt.plot(np.array(raw_data[('GTD(1)', 'Hindsight Error')][key])[:], linewidth=2.5) # plt.plot(true_data[300:]) plt.plot(np.array(raw_data[('GTD(0)', 'UDE')][key])[600:], linewidth=2.75) # print('true value', np.array(raw_data[('GTD(0)', 'UDE')][key])[300:400]) # plt.plot(np.array(raw_data[('GTD(0)', 'TD Error')][key])[600:], linewidth=2.5) # print('old prediction', np.array(raw_data[('GTD(0)', 'TD Error')][key])[300:400]) plt.plot(np.array(raw_data[('GTD(0)', 'Prediction')][key])[600:], linewidth=2.75) # plt.plot(np.array(raw_data[('GTD(1)', 'Prediction')][key])[300:] - np.array(raw_data[('GTD(1)', 'Hindsight Error')][key])[300:], linewidth=2.5) # plt.legend('True value', 'Prediction value') plt.title(titles[j], fontsize=30) if j > 1: plt.xlabel('steps', fontsize=30) plt.ylabel('Number of steps', fontsize=30) plt.xticks(fontsize=25) plt.yticks(fontsize=25) # plt.savefig('different_gamma.pdf') plt.show() # Plot the true prediction and true value def chinese_plot_different_gamma_data(path): f = open(path, 'rb') titles = ['$\gamma = 0.4$', '$\gamma = 0.8$', '$\gamma = 0.96$', '$\gamma =1.0$'] # true_data = compute_true_return('prediction_result_different_gamma.npy') # f = open('../data/learning_result_policy', 'rb') # plot_value_functions = ['Move down Fy', 'Move down Fx', 'Move down Fz', 'Move down Mx', 'Move down My', 'Move down Mz'] plot_value_functions = ['Move down step', 'Move down step 2', 'Move down step 3', 'Move down step 4'] # plot_value_functions = ['Move down Fx', 'Move down Fx 1', 'Move down Fx 2', 'Move down Fx 3'] raw_data = pickle.load(f) plt.figure(figsize=(20, 12), dpi=1000) plt.tight_layout(pad=3, w_pad=1., h_pad=0.5) plt.subplots_adjust(left=0.08, bottom=0.12, right=0.98, top=0.95, wspace=0.23, hspace=0.33) # legend = sorted([key for key in plot_value_functions.keys()]) # print(legend) # print(value_functions.keys()) for j, key in enumerate(plot_value_functions): plt.subplot(2, 2, j + 1) # print(list(raw_data[('GTD(1)', 'Hindsight Error')][key])) # plt.plot(np.array(raw_data[('GTD(1)', 'Hindsight Error')][key])[:], linewidth=2.5) # plt.plot(true_data[300:]) plt.plot(np.array(raw_data[('GTD(0)', 'UDE')][key])[600:], linewidth=2.75) # print('true value', np.array(raw_data[('GTD(0)', 'UDE')][key])[300:400]) # plt.plot(np.array(raw_data[('GTD(0)', 'TD Error')][key])[600:], linewidth=2.5) # print('old prediction', np.array(raw_data[('GTD(0)', 'TD Error')][key])[300:400]) plt.plot(np.array(raw_data[('GTD(0)', 'Prediction')][key])[600:], linewidth=2.75) # plt.plot(np.array(raw_data[('GTD(1)', 'Prediction')][key])[300:] - np.array(raw_data[('GTD(1)', 'Hindsight Error')][key])[300:], linewidth=2.5) # plt.legend('True value', 'Prediction value') plt.title(titles[j], fontsize=36) if j > 1: plt.xlabel('搜索步数', fontsize=36) plt.ylabel('预测周期', fontsize=36) plt.xticks([0, 50, 100, 150, 200], fontsize=36) plt.yticks(fontsize=36) plt.savefig('./figure/pdf/chinese_different_gamma.pdf') # plt.show() def chinese_plot_compare_raw_data(path1, path2): raw_data = np.load(path1) raw_data_1 = np.load(path2) plt.figure(figsize=(20, 12), dpi=1000) plt.title('Episode Reward') plt.tight_layout(pad=3, w_pad=0.5, h_pad=1.0) plt.subplots_adjust(left=0.08, bottom=0.08, right=0.98, top=0.95, wspace=0.33, hspace=0.15) data = np.zeros((len(raw_data), 12)) for j in range(len(raw_data)): data[j] = raw_data[j, 0] data_1 = np.zeros((len(raw_data_1), 12)) for j in range(len(raw_data_1)): data_1[j] = raw_data_1[j, 0] for j in range(6): plt.subplot(2, 3, j + 1) plt.plot(data[:100, j], linewidth=2.5, color='r', linestyle='--') plt.plot(data_1[:100, j], linewidth=2.5, color='b') # plt.ylabel(YLABEL[j], fontsize=18) if j>2: plt.xlabel('搜索步数', fontsize=38) plt.title(YLABEL[j], fontsize=38) plt.xticks(fontsize=38) plt.yticks(fontsize=38) # plt.subplots_adjust(left=0.1, bottom=0.1, right=0.9, top=0.9, wspace=0.4, hspace=0.2) plt.savefig('./figure/pdf/chinese_raw_data.pdf') # plt.show() # Plot the true prediction and true value def chinese_plot_different_policy_data(path, name): f = open(path, 'rb') # true_data = compute_true_return('prediction_result_different_gamma.npy') # f = open('../data/learning_result_policy', 'rb') plot_value_functions = ['Move down Fx', 'Move down Fy', 'Move down Fz', 'Move down Mx', 'Move down My', 'Move down Mz'] # plot_value_functions = ['Move down step', 'Move down step 2', 'Move down step 3', 'Move down step 4'] # plot_value_functions = ['Move down Fx', 'Move down Fx 1', 'Move down Fx 2', 'Move down Fx 3'] raw_data = pickle.load(f) plt.figure(figsize=(20, 12), dpi=1000) plt.title('Episode Reward') plt.tight_layout(pad=3, w_pad=0.5, h_pad=1.0) plt.subplots_adjust(left=0.1, bottom=0.1, right=0.98, top=0.95, wspace=0.33, hspace=0.25) # plt.subplots_adjust(left=0.1, bottom=0.12, right=0.98, top=0.94, wspace=0.23, hspace=0.33) # legend = sorted([key for key in plot_value_functions.keys()]) # print(legend) # print(value_functions.keys()) for j, key in enumerate(plot_value_functions): plt.subplot(2, 3, j + 1) # print(list(raw_data[('GTD(1)', 'Hindsight Error')][key])) # plt.plot(np.array(raw_data[('GTD(1)', 'Hindsight Error')][key])[400:]*scale[j], linewidth=2.5) # plt.plot(true_data[300:]) plt.plot(np.array(raw_data[('GTD(1)', 'UDE')][key])[1000:]*scale[j], linewidth=2.5) # print('true value', np.array(raw_data[('GTD(0)', 'UDE')][key])[300:400]) # plt.plot(np.array(raw_data[('GTD(0)', 'TD Error')][key])[600:], linewidth=2.5, color='r') # print('old prediction', np.array(raw_data[('GTD(0)', 'TD Error')][key])[300:400]) plt.plot(np.array(raw_data[('GTD(1)', 'Prediction')][key])[1000:]*scale[j], linewidth=2.5) # plt.plot(np.array(raw_data[('GTD(1)', 'Prediction')][key])[300:] - np.array(raw_data[('GTD(1)', 'Hindsight Error')][key])[300:], linewidth=2.5) # plt.legend('True value', 'Prediction value') plt.title(YLABEL[j], fontsize=38) if j > 2: plt.xlabel('搜索步数', fontsize=38) plt.xticks([0, 50, 100, 150, 200], fontsize=38) plt.yticks(fontsize=38) plt.savefig('./figure/pdf/chinese_' + name +'.pdf') # plt.show() # Plot the true prediction and true value def plot_different_policy_data(path): f = open(path, 'rb') # true_data = compute_true_return('prediction_result_different_gamma.npy') # f = open('../data/learning_result_policy', 'rb') plot_value_functions = ['Move down Fx', 'Move down Fy', 'Move down Fz', 'Move down Mx', 'Move down My', 'Move down Mz'] # plot_value_functions = ['Move down step', 'Move down step 2', 'Move down step 3', 'Move down step 4'] # plot_value_functions = ['Move down Fx', 'Move down Fx 1', 'Move down Fx 2', 'Move down Fx 3'] raw_data = pickle.load(f) plt.figure(figsize=(20, 12), dpi=1000) plt.title('Episode Reward') plt.tight_layout(pad=3, w_pad=1.0, h_pad=1.0) plt.subplots_adjust(left=0.1, bottom=0.15, right=0.98, top=0.9, wspace=0.23, hspace=0.23) # legend = sorted([key for key in plot_value_functions.keys()]) # print(legend) # print(value_functions.keys()) for j, key in enumerate(plot_value_functions): plt.subplot(2, 3, j + 1) # print(list(raw_data[('GTD(1)', 'Hindsight Error')][key])) # plt.plot(np.array(raw_data[('GTD(1)', 'Hindsight Error')][key])[400:]*scale[j], linewidth=2.5) # plt.plot(true_data[300:]) plt.plot(np.array(raw_data[('GTD(1)', 'UDE')][key])[1000:]*scale[j], linewidth=2.5) # print('true value', np.array(raw_data[('GTD(0)', 'UDE')][key])[300:400]) # plt.plot(np.array(raw_data[('GTD(0)', 'TD Error')][key])[600:], linewidth=2.5, color='r') # print('old prediction', np.array(raw_data[('GTD(0)', 'TD Error')][key])[300:400]) plt.plot(np.array(raw_data[('GTD(1)', 'Prediction')][key])[1000:]*scale[j], linewidth=2.5) # plt.plot(np.array(raw_data[('GTD(1)', 'Prediction')][key])[300:] - np.array(raw_data[('GTD(1)', 'Hindsight Error')][key])[300:], linewidth=2.5) # plt.legend('True value', 'Prediction value') plt.title(YLABEL[j], fontsize=30) if j > 2: plt.xlabel('steps', fontsize=30) plt.xticks([0, 50, 100, 150, 200], fontsize=25) plt.yticks(fontsize=25) plt.savefig('./figure/pdf/chinese_different_policies_b.pdf') # plt.show() if __name__ == "__main__": # force = np.load('./search_force.npy') # state = np.load('./search_state.npy') # print(np.max(force, axis=0)) # print(np.min(force, axis=0)) # print(np.max(state, axis=0)) # print(np.min(state, axis=0)) # plot('./search_state.npy') # plot('./search_force.npy') # plot_reward('./episode_rewards.npy') # data = np.load('prediction_result.npy') # print(data[:, 2]) # plot_continuous_data('prediction_result_different_gamma_six_force.npy') # f = open('../data/learning_result', 'rb') # y = pickle.load(f) # data = y[('GTD(1)', 'Hindsight Error')]['Move down Fz'] # print(data) # plt.figure(figsize=(15, 15), dpi=100) # plt.title('Search Result') # # plt.plot(data) # plt.ylabel(YLABEL[0]) # plt.xlabel('steps') # plt.legend(YLABEL) # plt.show() # compute_true_return('prediction_result_different_gamma.npy') # plot_true_data('learning_result_six_force_gamma_0.9') # plot_true_data('learning_result_different_gamma') # plot_different_gamma_data('learning_result_different_policy') """=============================== plot different policy ===================================== """ # plot_different_policy_data('learning_result_six_force_gamma_0.9') # chinese_plot_different_policy_data('learning_result_six_force_gamma_0.9') # plot_different_policy_data('learning_result_different_policy_new_3') chinese_plot_different_policy_data('learning_result_different_policy_new_3', 'off_policy_3') # chinese_plot_different_policy_data('learning_result_different_policy') # chinese_plot_different_policy_data('learning_result_different_policy') """=============================== plot different gamma ======================================== """ # plot_different_gamma_data('learning_result_different_gamma_new') # chinese_plot_different_gamma_data('learning_result_different_gamma_new')

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backend/models/__init__.py

hajajmaor/e_commerce_website

c3cb4b7acb4447231358ee153128dab1ef7096f5

[ "MIT" ]

null

backend/models/__init__.py

hajajmaor/e_commerce_website

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backend/models/__init__.py

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src/torchphysics/utils/data/__init__.py

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2022-03-26T09:05:12.000Z

src/torchphysics/utils/data/__init__.py

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2022-03-10T08:04:49.000Z

src/torchphysics/utils/data/__init__.py

DKreuter/torchphysics

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from .dataloader import PointsDataset, PointsDataLoader

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Python

.kodi/addons/plugin.audio.radioreference/__init__.py

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.kodi/addons/plugin.audio.radioreference/__init__.py

C6SUMMER/allinclusive-kodi-pi

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null

.kodi/addons/plugin.audio.radioreference/__init__.py

C6SUMMER/allinclusive-kodi-pi

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# -*- coding: utf-8 -*- #------------------------------------------------------------ # broadcastify #------------------------------------------------------------

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johnsca/charm-helpers

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tests/__init__.py

johnsca/charm-helpers

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tests/__init__.py

johnsca/charm-helpers

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import sys import mock sys.modules['yum'] = mock.MagicMock()

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5

69b8ea15180398bc6ee7cd290eed58c81d9257b6

27,827

py

Python

services/ui_backend_service/tests/integration_tests/tasks_test.py

runsascoded/metaflow-service

ac7770dfeae17fd060129d408fa3bb472fc00b86

[ "Apache-2.0" ]

103

2019-12-04T04:41:08.000Z

2022-03-29T16:20:45.000Z

services/ui_backend_service/tests/integration_tests/tasks_test.py

runsascoded/metaflow-service

ac7770dfeae17fd060129d408fa3bb472fc00b86

[ "Apache-2.0" ]

42

2019-12-16T23:15:44.000Z

2022-02-18T17:33:32.000Z

services/ui_backend_service/tests/integration_tests/tasks_test.py

valayDave/metaflow-service

65e19aef268e9e707522ee0695fd4ebaee42aa69

[ "Apache-2.0" ]

36

2019-12-12T17:46:46.000Z

2022-01-21T04:53:24.000Z

import pytest import time from .utils import ( init_app, init_db, clean_db, add_flow, add_run, add_step, add_task, add_artifact, _test_list_resources, _test_single_resource, add_metadata, get_heartbeat_ts ) pytestmark = [pytest.mark.integration_tests] # Fixtures begin @pytest.fixture def cli(loop, aiohttp_client): return init_app(loop, aiohttp_client) @pytest.fixture async def db(cli): async_db = await init_db(cli) yield async_db await clean_db(async_db) # Fixtures end async def test_list_tasks(cli, db): _flow = (await add_flow(db, flow_id="HelloFlow")).body _run = (await add_run(db, flow_id=_flow.get("flow_id"))).body _step = (await add_step(db, flow_id=_run.get("flow_id"), step_name="step", run_number=_run.get("run_number"), run_id=_run.get("run_id"))).body await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/tasks".format(**_step), 200, []) await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks".format(**_step), 200, []) _task = await create_task(db, step=_step) _task['duration'] = None _task['status'] = 'pending' await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/tasks".format(**_task), 200, [_task]) await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks".format(**_task), 200, [_task]) async def test_list_tasks_non_numerical(cli, db): _flow = (await add_flow(db, flow_id="HelloFlow")).body _run = (await add_run(db, flow_id=_flow.get("flow_id"))).body _step = (await add_step(db, flow_id=_run.get("flow_id"), step_name="step", run_number=_run.get("run_number"), run_id=_run.get("run_id"))).body await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/tasks".format(**_step), 200, []) await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks".format(**_step), 200, []) _task = await create_task(db, step=_step, task_name="bar") _, data = await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/tasks".format(**_task), 200, None) _, data = await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks".format(**_task), 200, None) assert len(data) == 1 assert data[0]['task_name'] == 'bar' assert data[0]['task_id'] != 'bar' async def test_single_task(cli, db): await _test_single_resource(cli, db, "/flows/HelloFlow/runs/404/steps/none/tasks/5", 404, {}) _task = await create_task(db) _task['duration'] = None _task['status'] = 'pending' await _test_single_resource(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}".format(**_task), 200, _task) async def test_single_task_non_numerical(cli, db): _task = await create_task(db, task_name="bar") _, data = await _test_single_resource(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/bar".format(**_task), 200, None) assert data['task_name'] == 'bar' assert data['task_id'] != 'bar' async def test_list_old_metadata_task_attempts(cli, db): # Test tasks with old (missing attempt) metadata _task = await create_task(db) _task['duration'] = None _task['status'] = 'pending' await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) _artifact_first = await create_ok_artifact_for_task(db, _task) _artifact_second = await create_ok_artifact_for_task(db, _task, attempt=1) _task['status'] = 'unknown' _task['task_ok'] = 'location' _task_first_attempt = dict(_task) _task_second_attempt = dict(_task) _task_first_attempt['attempt_id'] = 0 _task_first_attempt['finished_at'] = _artifact_first['ts_epoch'] _task_first_attempt['duration'] = _artifact_first['ts_epoch'] - \ _task_first_attempt['ts_epoch'] _task_second_attempt['attempt_id'] = 1 _task_second_attempt['finished_at'] = _artifact_second['ts_epoch'] _task_second_attempt['duration'] = _artifact_second['ts_epoch'] - \ _task_second_attempt['ts_epoch'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks?task_id={task_id}".format(**_task), 200, [_task_second_attempt, _task_first_attempt]) await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task_second_attempt, _task_first_attempt]) async def test_old_metadata_task_with_multiple_attempts(cli, db): # Test tasks with old (missing attempt) metadata _task = await create_task(db) _task['duration'] = None _task['status'] = 'pending' await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) _artifact_first = await create_ok_artifact_for_task(db, _task) _artifact_second = await create_ok_artifact_for_task(db, _task, attempt=1) _task['status'] = 'unknown' _task['task_ok'] = 'location' _task['attempt_id'] = 1 _task['finished_at'] = _artifact_second['ts_epoch'] _task['duration'] = _artifact_second['ts_epoch'] - \ _task['ts_epoch'] await _test_single_resource(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}".format(**_task), 200, _task) async def test_task_with_attempt_metadata(cli, db): _task = await create_task(db) _task['duration'] = None _task['status'] = 'pending' await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) _attempt_first = await create_task_attempt_metadata(db, _task) _artifact_first = await create_ok_artifact_for_task(db, _task) _task['started_at'] = _attempt_first['ts_epoch'] _task['finished_at'] = _artifact_first['ts_epoch'] _task['duration'] = _task['finished_at'] - _task['started_at'] _task['status'] = 'unknown' _task['task_ok'] = 'location' await _test_single_resource(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}".format(**_task), 200, _task) _attempt_done_first = await create_task_attempt_done_metadata(db, _task) _task['status'] = 'unknown' _task['finished_at'] = _attempt_done_first['ts_epoch'] _task['duration'] = _attempt_done_first['ts_epoch'] - _task['started_at'] await _test_single_resource(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}".format(**_task), 200, _task) _attempt_ok_first = await create_task_attempt_ok_metadata(db, _task, 0, True) # status 'completed' _task['status'] = 'completed' _task['finished_at'] = _attempt_ok_first['ts_epoch'] _task['duration'] = _attempt_ok_first['ts_epoch'] - _task['started_at'] _task['task_ok'] = None # intended behavior, status refinement location field should remain empty when metadata exists. await _test_single_resource(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}".format(**_task), 200, _task) async def test_task_failed_status_with_heartbeat(cli, db): _task = await create_task(db, last_heartbeat_ts=1, status="failed") _task['finished_at'] = 1000 # should be last heartbeat in this case, due to every other timestamp missing. _task['duration'] = _task['last_heartbeat_ts'] * 1000 - _task['ts_epoch'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) async def test_task_running_status_with_heartbeat(cli, db): hb_freeze = get_heartbeat_ts() _task = await create_task(db, last_heartbeat_ts=hb_freeze) _task['finished_at'] = None # should not have a finished at for running tasks. _task['duration'] = hb_freeze * 1000 - _task['ts_epoch'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) async def test_list_task_attempts(cli, db): _task = await create_task(db) _task['duration'] = None _task['status'] = 'pending' await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) _attempt_first = await create_task_attempt_metadata(db, _task) _artifact_first = await create_ok_artifact_for_task(db, _task) _attempt_done_first = await create_task_attempt_done_metadata(db, _task) _attempt_second = await create_task_attempt_metadata(db, _task, attempt=1) _artifact_second = await create_ok_artifact_for_task(db, _task, attempt=1) _task_first_attempt = dict(_task) _task_second_attempt = dict(_task) _task_first_attempt['attempt_id'] = 0 _task_first_attempt['status'] = 'unknown' _task_first_attempt['task_ok'] = 'location' _task_first_attempt['started_at'] = _attempt_first['ts_epoch'] _task_first_attempt['finished_at'] = _attempt_done_first['ts_epoch'] _task_first_attempt['duration'] = _task_first_attempt['finished_at'] \ - _task_first_attempt['started_at'] # Second attempt counts as completed as well due to the _task_ok existing. _task_second_attempt['attempt_id'] = 1 _task_second_attempt['status'] = 'unknown' _task_second_attempt['task_ok'] = 'location' _task_second_attempt['started_at'] = _attempt_second['ts_epoch'] _task_second_attempt['finished_at'] = _artifact_second['ts_epoch'] _task_second_attempt['duration'] = _task_second_attempt['finished_at'] \ - _task_second_attempt['started_at'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks?task_id={task_id}".format(**_task), 200, [_task_second_attempt, _task_first_attempt]) await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task_second_attempt, _task_first_attempt]) async def test_task_with_attempt_ok_completed(cli, db): _task = await create_task(db) _attempt_first = await create_task_attempt_metadata(db, _task) _artifact_first = await create_ok_artifact_for_task(db, _task) _attempt_ok = await create_task_attempt_ok_metadata(db, _task, 0, True) # status = 'completed' _task['started_at'] = _attempt_first['ts_epoch'] _task['finished_at'] = _attempt_ok['ts_epoch'] _task['duration'] = _attempt_ok['ts_epoch'] - _task['started_at'] _task['status'] = 'completed' await _test_single_resource(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}".format(**_task), 200, _task) async def test_task_with_attempt_ok_failed(cli, db): _task = await create_task(db) _attempt_first = await create_task_attempt_metadata(db, _task) _artifact_first = await create_ok_artifact_for_task(db, _task) _task['started_at'] = _attempt_first['ts_epoch'] _task['finished_at'] = _artifact_first['ts_epoch'] _task['duration'] = _task['finished_at'] - _task['started_at'] _task['status'] = 'failed' _attempt_ok = await create_task_attempt_ok_metadata(db, _task, 0, False) # status = 'failed' _task['finished_at'] = _attempt_ok['ts_epoch'] _task['duration'] = _attempt_ok['ts_epoch'] - _task['started_at'] await _test_single_resource(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}".format(**_task), 200, _task) async def test_list_task_multiple_attempts_failure(cli, db): _task = await create_task(db) _attempt_first = await create_task_attempt_metadata(db, _task) _artifact_first = await create_ok_artifact_for_task(db, _task) _attempt_done_first = await create_task_attempt_done_metadata(db, _task) _attempt_second = await create_task_attempt_metadata(db, _task, attempt=1) _artifact_second = await create_ok_artifact_for_task(db, _task, attempt=1) # Mark first attempt as 'failure' and second as 'completed' _attempt_ok_first = await create_task_attempt_ok_metadata(db, _task, 0, False) # status = 'failed' _attempt_ok_second = await create_task_attempt_ok_metadata(db, _task, 1, True) # status = 'completed' _task_first_attempt = dict(_task) _task_second_attempt = dict(_task) _task_first_attempt['attempt_id'] = 0 _task_first_attempt['status'] = 'failed' _task_first_attempt['started_at'] = _attempt_first['ts_epoch'] _task_first_attempt['finished_at'] = _attempt_done_first['ts_epoch'] _task_first_attempt['duration'] = _task_first_attempt['finished_at'] \ - _task_first_attempt['started_at'] _task_first_attempt['finished_at'] = _attempt_ok_first['ts_epoch'] _task_first_attempt['duration'] = _attempt_ok_first['ts_epoch'] - _task_first_attempt['started_at'] # Second attempt counts as completed as well due to the _task_ok existing. _task_second_attempt['attempt_id'] = 1 _task_second_attempt['status'] = 'completed' _task_second_attempt['started_at'] = _attempt_second['ts_epoch'] _task_second_attempt['finished_at'] = _artifact_second['ts_epoch'] _task_second_attempt['duration'] = _task_second_attempt['finished_at'] \ - _task_second_attempt['started_at'] _task_second_attempt['finished_at'] = _attempt_ok_second['ts_epoch'] _task_second_attempt['duration'] = _attempt_ok_second['ts_epoch'] - _task_second_attempt['started_at'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks?task_id={task_id}".format(**_task), 200, [_task_second_attempt, _task_first_attempt]) await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task_second_attempt, _task_first_attempt]) async def test_task_attempts_with_attempt_metadata(cli, db): _task = await create_task(db) _task['duration'] = None _task['status'] = 'pending' await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) _attempt_first = await create_task_attempt_metadata(db, _task) _artifact_first = await create_ok_artifact_for_task(db, _task) _attempt_done_first = await create_task_attempt_done_metadata(db, _task) # attempt metadata is written but no artifacts exist yet. # Queries should return a second attempt at this point already! _attempt_second = await create_task_attempt_metadata(db, _task, attempt=1) _task_first_attempt = dict(_task) _task_second_attempt = dict(_task) _task_first_attempt['attempt_id'] = 0 _task_first_attempt['task_ok'] = 'location' # should have location for status artifact _task_first_attempt['status'] = 'unknown' # 'unknown' because we cannot determine correct status from DB as attempt_ok is missing _task_first_attempt['started_at'] = _attempt_first['ts_epoch'] _task_first_attempt['finished_at'] = _attempt_done_first['ts_epoch'] _task_first_attempt['duration'] = _task_first_attempt['finished_at'] \ - _task_first_attempt['started_at'] _task_second_attempt['attempt_id'] = 1 _task_second_attempt['status'] = 'running' _task_second_attempt['started_at'] = _attempt_second['ts_epoch'] _task_second_attempt['duration'] = int(round(time.time() * 1000)) - _task_second_attempt['started_at'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks?task_id={task_id}".format(**_task), 200, [_task_second_attempt, _task_first_attempt], approx_keys=["duration"]) await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task_second_attempt, _task_first_attempt], approx_keys=["duration"]) # Write attempt_ok data for first attempt to check for status changes. _first_attempt_ok = await create_task_attempt_ok_metadata(db, _task, 0, False) # NOTE: in current implementation, attempt_ok overrides attempt-done as a more accurate timestamp for finished_at. _task_first_attempt['finished_at'] = _first_attempt_ok['ts_epoch'] _task_first_attempt['duration'] = _task_first_attempt['finished_at'] \ - _task_first_attempt['started_at'] _task_first_attempt['task_ok'] = None # should have no task_ok location, as status can be determined from db. _task_first_attempt['status'] = 'failed' # 'failed' because now we have attempt_ok false in db. await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks?task_id={task_id}".format(**_task), 200, [_task_second_attempt, _task_first_attempt], approx_keys=["duration"]) await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task_second_attempt, _task_first_attempt], approx_keys=["duration"]) async def test_task_attempt_statuses_with_attempt_ok_failed(cli, db): _task = await create_task(db) _task['duration'] = None _task['status'] = 'pending' await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) _attempt_first = await create_task_attempt_metadata(db, _task) _artifact_first = await create_ok_artifact_for_task(db, _task) _attempt_done_first = await create_task_attempt_done_metadata(db, _task) _attempt_ok_first = await create_task_attempt_ok_metadata(db, _task, 0, False) # status = 'failed' _attempt_second = await create_task_attempt_metadata(db, _task, attempt=1) _attempt_done_second = await create_task_attempt_done_metadata(db, _task, attempt=1) _attempt_ok_second = await create_task_attempt_ok_metadata(db, _task, 1, True) # status = 'completed' _task_first_attempt = dict(_task) _task_second_attempt = dict(_task) # NOTE: In the current implementation attempt_ok overrides attempt-done ts_epoch as the finished_at # as a more accurate timestamp for when a task finished. _task_first_attempt['attempt_id'] = 0 _task_first_attempt['status'] = 'failed' _task_first_attempt['started_at'] = _attempt_first['ts_epoch'] _task_first_attempt['finished_at'] = _attempt_ok_first['ts_epoch'] _task_first_attempt['duration'] = _task_first_attempt['finished_at'] \ - _task_first_attempt['started_at'] _task_second_attempt['attempt_id'] = 1 _task_second_attempt['status'] = 'completed' _task_second_attempt['started_at'] = _attempt_second['ts_epoch'] _task_second_attempt['finished_at'] = _attempt_ok_second['ts_epoch'] _task_second_attempt['duration'] = _task_second_attempt['finished_at'] \ - _task_second_attempt['started_at'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks?task_id={task_id}".format(**_task), 200, [_task_second_attempt, _task_first_attempt]) await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task_second_attempt, _task_first_attempt]) # Test cases from the google docs table. # status 'completed' tests # # STATUS: attempt_ok in task metadata for the attempt is set to True # STARTED_AT: created_at property for attempt attribute for the attempt in task metadata # FINISHED_AT: created_at property for attempt_ok attribute for the attempt in task metadata # NOTE: for a more accurate finished_at timestamp, use the greatest timestamp out of task_ok / attempt_ok / attempt-done # as this is the latest write_timestamp for the task async def test_task_attempt_status_completed(cli, db): _task = await create_task(db) _task['duration'] = None _task['status'] = 'pending' await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) _attempt = await create_task_attempt_metadata(db, _task, 0) _attempt_ok = await create_task_attempt_ok_metadata(db, _task, 0, True) _attempt_done = await create_task_attempt_done_metadata(db, _task, 0) _task['status'] = 'completed' _task['started_at'] = _attempt['ts_epoch'] _task['finished_at'] = _attempt_done['ts_epoch'] _task['duration'] = _task['finished_at'] - _task['started_at'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) # status 'running' tests # # STATUS 'running': # Has all of # Has a start time (NOTE: this requires 'attempt' metadata to be present) # attempt_ok does not exist in the task metadata # Has logged a heartbeat in the last x minutes (NOTE: we actually rely on heartbeat for running status.) # No subsequent attempt exists # STARTED_AT: created_at property for attempt attribute for the attempt in task metadata # FINISHED_AT: does not apply (NULL) async def test_task_attempt_status_running(cli, db): _task = await create_task(db, last_heartbeat_ts=get_heartbeat_ts()) # default status: 'running' _task['duration'] = _task['last_heartbeat_ts'] * 1000 - _task['ts_epoch'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) _attempt = await create_task_attempt_metadata(db, _task, 0) _task['started_at'] = _attempt['ts_epoch'] _task['finished_at'] = None _task['duration'] = _task['last_heartbeat_ts'] * 1000 - _task['started_at'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) # status 'failed' tests # # STATUS: # Either of # attempt_ok in task metadata for the attempt is set to False # No heartbeat has been logged for the task in the last x minutes and no new attempt has started # A newer attempt exists # STARTED_AT: created_at property for attempt attribute for the attempt in task metadata # FINISHED_AT: # Either of (in priority) # created_at property for attempt_ok attribute for the attempt in task metadata # The timestamp in the heartbeat column for the task if no subsequent attempt is detected # If a subsequent attempt exists, use the start time of the subsequent attempt async def test_task_attempt_status_failed_with_existing_subsequent_attempt(cli, db): _task = await create_task(db, last_heartbeat_ts=get_heartbeat_ts()) _task['duration'] = _task['last_heartbeat_ts'] * 1000 - _task['ts_epoch'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_task]) _first_attempt = dict(_task) _second_attempt = dict(_task) # we explicitly leave out attempt completion metadata for attempt 0 to test that it fails correctly # when attempt 1 exists. # ATTEMPT-0 _first_attempt_meta = await create_task_attempt_metadata(db, _task, 0) _first_attempt['started_at'] = _first_attempt_meta['ts_epoch'] _first_attempt['duration'] = _first_attempt['last_heartbeat_ts'] * 1000 - _first_attempt['started_at'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_first_attempt]) # ATTEMPT-1 _second_attempt_meta = await create_task_attempt_metadata(db, _task, 1) _second_attempt['attempt_id'] = 1 _second_attempt['started_at'] = _second_attempt_meta['ts_epoch'] _second_attempt['duration'] = _second_attempt['last_heartbeat_ts'] * 1000 - _second_attempt['started_at'] # first attempt should be failed due to second attempt existing. # finished_at timestamp should be the started_at of the second attempt due to it existing. _first_attempt['status'] = 'failed' _first_attempt['finished_at'] = _second_attempt['started_at'] _first_attempt['duration'] = _first_attempt['finished_at'] - _first_attempt['started_at'] await _test_list_resources(cli, db, "/flows/{flow_id}/runs/{run_number}/steps/{step_name}/tasks/{task_id}/attempts".format(**_task), 200, [_second_attempt, _first_attempt]) # Resource Helpers / factories async def create_ok_artifact_for_task(db, task, attempt=0): "Creates and returns a _task_ok artifact for a task" _task = (await add_artifact( db, flow_id=task.get("flow_id"), run_number=task.get("run_number"), run_id=task.get("run_id"), step_name=task.get("step_name"), task_id=task.get("task_id"), task_name=task.get("task_name"), artifact={ "name": "_task_ok", "location": "location", "ds_type": "ds_type", "sha": "sha", "type": "type", "content_type": "content_type", "attempt_id": attempt }) ).body return _task async def create_task(db, step=None, status="running", task_id=None, task_name=None, last_heartbeat_ts=None): "Creates and returns a task with specific status. Optionally creates the task for a specific step if provided." if not step: _flow = (await add_flow(db, flow_id="HelloFlow")).body _run = (await add_run(db, flow_id=_flow.get("flow_id"))).body step = (await add_step( db, flow_id=_run.get("flow_id"), run_number=_run.get("run_number"), step_name="step") ).body _task = (await add_task( db, flow_id=step.get("flow_id"), run_number=step.get("run_number"), step_name=step.get("step_name"), task_id=task_id, task_name=task_name, last_heartbeat_ts=last_heartbeat_ts) ).body _task['status'] = status return _task async def create_metadata_for_task(db, task, metadata={}, tags=None): "Creates a metadata record for a task" _meta = (await add_metadata(db, flow_id=task.get("flow_id"), run_number=task.get("run_number"), run_id=task.get("run_id"), step_name=task.get("step_name"), task_id=task.get("task_id"), task_name=task.get("task_name"), tags=tags, metadata=metadata) ).body return _meta async def create_task_attempt_metadata(db, task, attempt=0): "Create 'attempt' metadata for a task" return await create_metadata_for_task( db, task, metadata={ "type": "attempt", "field_name": "attempt", "value": str(attempt) } ) async def create_task_attempt_done_metadata(db, task, attempt: int = 0): "Create 'attempt-done' metadata for a task" return await create_metadata_for_task( db, task, metadata={ "type": "attempt-done", "field_name": "attempt-done", "value": str(attempt) } ) async def create_task_attempt_ok_metadata(db, task, attempt_id: int, attempt_ok: bool = False): "Create 'attempt_ok' metadata for a task" return await create_metadata_for_task( db, task, tags=["attempt_id:{attempt_id}".format(attempt_id=attempt_id)], metadata={ "type": "internal_attempt_status", "field_name": "attempt_ok", "value": str(attempt_ok) } )

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69c0d64af0daa3c05b8a8e97e012bb20be7a3134

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py

Python

study/python-brasil/exercises/sequential-structure/sequential-structure - 006.py

gustavomarquezinho/python

e36779aa5c4bfaf88c587f05db5bd447fd41e4a2

[ "MIT" ]

null

study/python-brasil/exercises/sequential-structure/sequential-structure - 006.py

gustavomarquezinho/python

e36779aa5c4bfaf88c587f05db5bd447fd41e4a2

[ "MIT" ]

null

study/python-brasil/exercises/sequential-structure/sequential-structure - 006.py

gustavomarquezinho/python

e36779aa5c4bfaf88c587f05db5bd447fd41e4a2

[ "MIT" ]

null

# 006 - Faça um programa que peça o raio de um círculo, calcule e mostre sua área. print(f'Área: {3.14 * pow(float(input("Raio círculo: ")), 2)}')

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69d7a315854c9efb1fc746e30bff79237346d088

381

py

Python

corehq/apps/fixtures/exceptions.py

SEL-Columbia/commcare-hq

992ee34a679c37f063f86200e6df5a197d5e3ff6

[ "BSD-3-Clause" ]

1

2015-02-10T23:26:39.000Z

corehq/apps/fixtures/exceptions.py

SEL-Columbia/commcare-hq

992ee34a679c37f063f86200e6df5a197d5e3ff6

[ "BSD-3-Clause" ]

null

corehq/apps/fixtures/exceptions.py

SEL-Columbia/commcare-hq

992ee34a679c37f063f86200e6df5a197d5e3ff6

[ "BSD-3-Clause" ]

null

class FixtureException(Exception): pass class FixtureUploadError(FixtureException): pass class DuplicateFixtureTagException(FixtureUploadError): pass class ExcelMalformatException(FixtureUploadError): pass class FixtureAPIException(Exception): pass class FixtureTypeCheckError(Exception): pass class FixtureVersionError(Exception): pass

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388c4200cdb6866a189312d1ba76f6d3bb459c3a

758

py

Python

pyorient/ogm/commands.py

spy7/pyorient

ac2547287f9299f4eec350666da3b19797872f20

[ "Apache-2.0" ]

142

2015-01-12T06:34:59.000Z

2022-01-19T10:34:30.000Z

pyorient/ogm/commands.py

spy7/pyorient

ac2547287f9299f4eec350666da3b19797872f20

[ "Apache-2.0" ]

238

2015-01-04T21:05:41.000Z

2021-04-12T17:45:53.000Z

pyorient/ogm/commands.py

spy7/pyorient

ac2547287f9299f4eec350666da3b19797872f20

[ "Apache-2.0" ]

107

2015-01-03T03:33:17.000Z

2021-12-07T16:48:48.000Z

from ..utils import to_str class VertexCommand(object): def __init__(self, command_text): self.command_text = command_text def __str__(self): return to_str(self.__unicode__()) def __unicode__(self): return u'{}'.format(self.command_text) class CreateEdgeCommand(object): def __init__(self, command_text): self.command_text = command_text self.retries = None def __str__(self): return to_str(self.__unicode__()) def __unicode__(self): if self.retries: return u'{} RETRY {}'.format(self.command_text, self.retries) else: return u'{}'.format(self.command_text) def retry(self, retries): self.retries = retries return self

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5

38b594515a9bd74963aec29f7d6581b2994b7f2f

155

py

Python

controle/admin.py

jeremyrodrigues/auto-ambient-music

a8f622334f921741e0011ef305ac8e991f361d35

[ "MIT" ]

null

controle/admin.py

jeremyrodrigues/auto-ambient-music

a8f622334f921741e0011ef305ac8e991f361d35

[ "MIT" ]

null

controle/admin.py

jeremyrodrigues/auto-ambient-music

a8f622334f921741e0011ef305ac8e991f361d35

[ "MIT" ]

null

from django.contrib import admin from controle.models import Time, Music # Register your models here. admin.site.register(Time) admin.site.register(Music)

25.833333

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null

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38bb581927bfd74653d9371508053b5cbf15396a

28

py

Python

textbot/action.py

sparwow/textbot

cad7ad310da8af9c826e4c52f1a8f27ae90c1462

[ "MIT" ]

null

textbot/action.py

sparwow/textbot

cad7ad310da8af9c826e4c52f1a8f27ae90c1462

[ "MIT" ]

null

textbot/action.py

sparwow/textbot

cad7ad310da8af9c826e4c52f1a8f27ae90c1462

[ "MIT" ]

null

class EmailAction: pass

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2a4a2838e188c76f4a2cd11bbdf6a1bfab7e4da2

101

py

Python

python/lookout/__init__.py

meyskens/lookout-sdk

805d0d61ca97120a257283780790ff2458a6ef29

[ "Apache-2.0" ]

5

2018-12-17T11:22:31.000Z

2019-03-14T02:50:43.000Z

python/lookout/__init__.py

meyskens/lookout-sdk

805d0d61ca97120a257283780790ff2458a6ef29

[ "Apache-2.0" ]

64

2018-08-31T10:41:36.000Z

2019-12-14T15:01:13.000Z

python/lookout/__init__.py

meyskens/lookout-sdk

805d0d61ca97120a257283780790ff2458a6ef29

[ "Apache-2.0" ]

16

2018-08-30T20:33:55.000Z

2021-08-09T05:37:06.000Z

"""Lookout - Assisted Code Review""" import pkg_resources pkg_resources.declare_namespace(__name__)

20.2

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2a522cf24383152e1f43899c4fe827f5c6c726b0

6,738

py

Python

mayan/apps/documents/tests/test_links.py

bonitobonita24/Mayan-EDMS

7845fe0e1e83c81f5d227a16116397a3d3883b85

[ "Apache-2.0" ]

343

2015-01-05T14:19:35.000Z

2018-12-10T19:07:48.000Z

mayan/apps/documents/tests/test_links.py

bonitobonita24/Mayan-EDMS

7845fe0e1e83c81f5d227a16116397a3d3883b85

[ "Apache-2.0" ]

191

2015-01-03T00:48:19.000Z

2018-11-30T09:10:25.000Z

mayan/apps/documents/tests/test_links.py

bonitobonita24/Mayan-EDMS

7845fe0e1e83c81f5d227a16116397a3d3883b85

[ "Apache-2.0" ]

114

2015-01-08T20:21:05.000Z

2018-12-10T19:07:53.000Z

from django.urls import reverse from ..links.document_file_links import ( link_document_file_delete, link_document_file_download_quick ) from ..links.favorite_links import ( link_document_favorites_add, link_document_favorites_remove ) from ..links.trashed_document_links import link_document_restore from ..models import TrashedDocument from ..permissions import ( permission_document_file_delete, permission_document_file_download, permission_document_view, permission_trashed_document_restore ) from .base import GenericDocumentViewTestCase from .mixins.favorite_document_mixins import FavoriteDocumentTestMixin class FavoriteDocumentLinkTestCase( FavoriteDocumentTestMixin, GenericDocumentViewTestCase ): def test_favorite_document_add_link_no_permission(self): self._create_test_document_stub() self.add_test_view(test_object=self.test_document) context = self.get_test_view() resolved_link = link_document_favorites_add.resolve(context=context) self.assertEqual(resolved_link, None) def test_favorite_document_add_link_with_access(self): self._create_test_document_stub() self.grant_access( obj=self.test_document_stub, permission=permission_document_view ) self.add_test_view(test_object=self.test_document) context = self.get_test_view() resolved_link = link_document_favorites_add.resolve(context=context) self.assertNotEqual(resolved_link, None) def test_favorite_document_add_link_external_user_with_access(self): self._create_test_user() self._create_test_document_stub() self.grant_access( obj=self.test_document_stub, permission=permission_document_view ) self._test_document_favorite_add(user=self.test_user) self.add_test_view(test_object=self.test_document) context = self.get_test_view() resolved_link = link_document_favorites_add.resolve(context=context) self.assertNotEqual(resolved_link, None) def test_favorite_document_remove_link_no_permission(self): self._create_test_document_stub() self._test_document_favorite_add() self.add_test_view(test_object=self.test_document) context = self.get_test_view() resolved_link = link_document_favorites_remove.resolve(context=context) self.assertEqual(resolved_link, None) def test_favorite_document_remove_link_with_access(self): self._create_test_document_stub() self.grant_access( obj=self.test_document_stub, permission=permission_document_view ) self._test_document_favorite_add() self.add_test_view(test_object=self.test_document) context = self.get_test_view() resolved_link = link_document_favorites_remove.resolve(context=context) self.assertNotEqual(resolved_link, None) def test_favorite_document_remove_link_external_user_with_access(self): self._create_test_user() self._create_test_document_stub() self.grant_access( obj=self.test_document_stub, permission=permission_document_view ) self._test_document_favorite_add(user=self.test_user) self.add_test_view(test_object=self.test_document) context = self.get_test_view() resolved_link = link_document_favorites_remove.resolve(context=context) self.assertEqual(resolved_link, None) class DocumentsLinksTestCase(GenericDocumentViewTestCase): def test_document_file_delete_link_no_permission(self): self._upload_test_document_file() self.assertTrue(self.test_document.files.count(), 2) self.add_test_view(test_object=self.test_document.files.first()) context = self.get_test_view() resolved_link = link_document_file_delete.resolve(context=context) self.assertEqual(resolved_link, None) def test_document_file_delete_link_with_permission(self): self._upload_test_document_file() self.assertTrue(self.test_document.files.count(), 2) self.grant_access( obj=self.test_document, permission=permission_document_file_delete ) self.add_test_view(test_object=self.test_document.files.first()) context = self.get_test_view() resolved_link = link_document_file_delete.resolve(context=context) self.assertNotEqual(resolved_link, None) self.assertEqual( resolved_link.url, reverse( viewname=link_document_file_delete.view, args=(self.test_document.files.first().pk,) ) ) def test_document_file_download_link_no_permission(self): self.add_test_view(test_object=self.test_document.file_latest) context = self.get_test_view() resolved_link = link_document_file_download_quick.resolve(context=context) self.assertEqual(resolved_link, None) def test_document_file_download_link_with_permission(self): self.grant_access( obj=self.test_document, permission=permission_document_file_download ) self.add_test_view(test_object=self.test_document.file_latest) context = self.get_test_view() resolved_link = link_document_file_download_quick.resolve(context=context) self.assertNotEqual(resolved_link, None) self.assertEqual( resolved_link.url, reverse( viewname=link_document_file_download_quick.view, args=(self.test_document.file_latest.pk,) ) ) class TrashedDocumentsLinksTestCase(GenericDocumentViewTestCase): def setUp(self): super().setUp() self.test_document.delete() self.test_trashed_document = TrashedDocument.objects.get( pk=self.test_document.pk ) self.add_test_view(test_object=self.test_trashed_document) self.context = self.get_test_view() def test_trashed_document_restore_link_no_permission(self): resolved_link = link_document_restore.resolve(context=self.context) self.assertEqual(resolved_link, None) def test_trashed_document_restore_link_with_permission(self): self.grant_access( obj=self.test_document, permission=permission_trashed_document_restore ) resolved_link = link_document_restore.resolve(context=self.context) self.assertNotEqual(resolved_link, None) self.assertEqual( resolved_link.url, reverse( viewname=link_document_restore.view, args=(self.test_trashed_document.pk,) ) )

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aa51ffea60a8f3722501b0b1a0f4252d675d1628

1,481

py

Python

airbyte-integrations/connectors/source-chargebee/unit_tests/conftest.py

onaio/airbyte

38302e82a25f1b66742c3febfbff0668556920f2

[ "MIT" ]

22

2020-08-27T00:47:20.000Z

2020-09-17T15:39:39.000Z

airbyte-integrations/connectors/source-chargebee/unit_tests/conftest.py

onaio/airbyte

38302e82a25f1b66742c3febfbff0668556920f2

[ "MIT" ]

116

2020-08-27T01:11:27.000Z

2020-09-19T02:47:52.000Z

airbyte-integrations/connectors/source-chargebee/unit_tests/conftest.py

onaio/airbyte

38302e82a25f1b66742c3febfbff0668556920f2

[ "MIT" ]

1

2020-09-15T06:10:01.000Z

# # Copyright (c) 2022 Airbyte, Inc., all rights reserved. # import json import os from pytest import fixture def load_file(fn): return open(os.path.join("unit_tests", "responses", fn)).read() @fixture def test_config_v1(): return {"site": "airbyte-test", "site_api_key": "site_api_key", "start_date": "2021-05-22T06:57:44Z", "product_catalog": "1.0"} @fixture def test_config_v2(): return {"site": "airbyte-test", "site_api_key": "site_api_key", "start_date": "2021-05-22T06:57:44Z", "product_catalog": "2.0"} @fixture def addons_response(): return json.loads(load_file("addons.json")) @fixture def plans_response(): return json.loads(load_file("plans.json")) @fixture def coupons_response(): return json.loads(load_file("coupons.json")) @fixture def customers_response(): return json.loads(load_file("customers.json")) @fixture def invoices_response(): return json.loads(load_file("invoices.json")) @fixture def orders_response(): return json.loads(load_file("orders.json")) @fixture def events_response(): return json.loads(load_file("events.json")) @fixture def subscriptions_response(): return json.loads(load_file("subscriptions.json")) @fixture def items_response(): return json.loads(load_file("items.json")) @fixture def item_prices_response(): return json.loads(load_file("item_prices.json")) @fixture def attached_items_response(): return json.loads(load_file("attached_items.json"))

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5

aa60b0079dcb6f5a27a15460a7a773255408abdc

91

py

Python

fsdviz/stocking/forms/__init__.py

AdamCottrill/fsdivz

98dd1f35a08dba26424e2951a40715e01399478c

[ "MIT" ]

null

fsdviz/stocking/forms/__init__.py

AdamCottrill/fsdivz

98dd1f35a08dba26424e2951a40715e01399478c

[ "MIT" ]

6

2020-02-12T00:03:40.000Z

2020-11-30T01:20:56.000Z

fsdviz/stocking/forms/__init__.py

AdamCottrill/fsdviz

98dd1f35a08dba26424e2951a40715e01399478c

[ "MIT" ]

null

from .FindEventsForm import * from .StockingEventForm import * from .XlsEventForm import *

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null

0

1

0

1

0

5

aabebbb877a1c20f697d7ae81aa297513ca02e1b

55

py

Python

dcstats/__init__.py

aplested/DC_Pyps

da33fc7d0e7365044e368488d1c7cbbae7473cc7

[ "MIT" ]

1

2021-03-25T18:09:25.000Z

dcstats/__init__.py

aplested/DC_Pyps

da33fc7d0e7365044e368488d1c7cbbae7473cc7

[ "MIT" ]

null

dcstats/__init__.py

aplested/DC_Pyps

da33fc7d0e7365044e368488d1c7cbbae7473cc7

[ "MIT" ]

null

from dcstats import * from _version import __version__

18.333333

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true

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1

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null

0

1

0

1

0

1

0

5

2a9a4d87b28f9436adbf59fa348294bf68f453a8

155

py

Python

revuo/forms/__init__.py

Lasanha/revuo

3fb2a06515194416aff3b9a9efac321f1af3209a

[ "BSD-3-Clause" ]

1

2020-03-24T23:33:57.000Z

revuo/forms/__init__.py

Lasanha/revuo

3fb2a06515194416aff3b9a9efac321f1af3209a

[ "BSD-3-Clause" ]

26

2015-01-20T13:31:57.000Z

2020-06-05T17:26:18.000Z

revuo/forms/__init__.py

Lasanha/revuo

3fb2a06515194416aff3b9a9efac321f1af3209a

[ "BSD-3-Clause" ]

null

from .blog_item import FormBlogItem from .edit_profile import FormEditProfile from .news_item import FormNewsItem from .publication import FormPublication

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155

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null

0

1

0

1

0

1

0

5

2d5d4b0e8ee8b61a38dc6be3798b8feb193f02e1

61

py

Python

mp2ragelib/ui.py

ofgulban/mp2ragelib

3df294f02ae4aadd0c9f91e8a101305f3f5f15fe

[ "BSD-3-Clause" ]

1

2020-09-04T19:36:58.000Z

mp2ragelib/ui.py

ofgulban/mp2ragelib

3df294f02ae4aadd0c9f91e8a101305f3f5f15fe

[ "BSD-3-Clause" ]

null

mp2ragelib/ui.py

ofgulban/mp2ragelib

3df294f02ae4aadd0c9f91e8a101305f3f5f15fe

[ "BSD-3-Clause" ]

null

"""Commandline interface.""" # TODO: After scripting works.

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1

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null

0

1

0

1

0

5

2dcefc70c84d3f4061e0e716788bdf5dca8ba63f

74

py

Python

lib/datatools/build/__init__.py

JokerWDL/PyAnomaly

cf93437e5d7ae87fa916141cf4b5cc2e929b8199

[ "Apache-2.0" ]

1

2020-11-22T17:55:10.000Z

lib/datatools/build/__init__.py

JokerWDL/PyAnomaly

cf93437e5d7ae87fa916141cf4b5cc2e929b8199

[ "Apache-2.0" ]

null

lib/datatools/build/__init__.py

JokerWDL/PyAnomaly

cf93437e5d7ae87fa916141cf4b5cc2e929b8199

[ "Apache-2.0" ]

null

from .. import dataclass # trigger the register in the dataclass package

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true

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null

0

1

0

null

0

1

0

1

0

1

0

5

93095d98ffed279b01860ac139ac53ed5312a8e1

206

py

Python

aiosnow/models/__init__.py

michaeldcanady/aiosnow

db515b1560d651fc7696a184990c2a2d68db8961

[ "MIT" ]

38

2020-08-03T17:58:48.000Z

2022-03-30T19:39:24.000Z

aiosnow/models/__init__.py

michaeldcanady/aiosnow

db515b1560d651fc7696a184990c2a2d68db8961

[ "MIT" ]

34

2020-01-20T10:11:46.000Z

2020-06-05T21:25:23.000Z

aiosnow/models/__init__.py

michaeldcanady/aiosnow

db515b1560d651fc7696a184990c2a2d68db8961

[ "MIT" ]

5

2021-03-26T19:35:20.000Z

2022-01-23T20:09:55.000Z

from ._base import BaseModel, BaseModelMeta, BaseTableModel from ._schema import BaseField, ModelSchema, ModelSchemaMeta, Pluck, fields from .attachment import AttachmentModel from .table import TableModel

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true

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null

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1

0

1

0

1

0

5

933b4da8586a2940f3a4d00ebc21c1950b2eb3db

241

py

Python

website/music/views.py

mrsmartpants/DjangoTutorial-Beginners

11e64f4f982a576f814db5ed466f8b31bba5ae5c

[ "MIT" ]

null

website/music/views.py

mrsmartpants/DjangoTutorial-Beginners

11e64f4f982a576f814db5ed466f8b31bba5ae5c

[ "MIT" ]

null

website/music/views.py

mrsmartpants/DjangoTutorial-Beginners

11e64f4f982a576f814db5ed466f8b31bba5ae5c

[ "MIT" ]

null

from django.shortcuts import render # Python functions - user is going to request an url # Create your views here. from django.http import HttpResponse def index(request): return HttpResponse("<h1> This is the music app homepage</h1>")

30.125

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241

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1

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null

0

1

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1

0

5

93717d5c39265a03944d975e47f65b92a746680b

84

py

Python

src/vpnchooser/__init__.py

cbrand/vpnchooser

0982baeb14eff1e0b7ef5dbc8f11b3a7213f341c

[ "MIT" ]

null

src/vpnchooser/__init__.py

cbrand/vpnchooser

0982baeb14eff1e0b7ef5dbc8f11b3a7213f341c

[ "MIT" ]

null

src/vpnchooser/__init__.py

cbrand/vpnchooser

0982baeb14eff1e0b7ef5dbc8f11b3a7213f341c

[ "MIT" ]

1

2016-05-31T16:14:37.000Z

# -*- encoding: utf-8 -*- from .applicaton import app, api from . import resources

16.8

32

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11

84

5.181818

0.818182

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0.014493

0.178571

84

4

33

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true

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null

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0

null

0

1

0

1

0

1

0

5

9373d6bbb7c1cbcacd636bf497c2f411b745ae3a

188

py

Python

8kyu/Beginner Series #2 Clock.py

walkgo/codewars_tasks

4c0ab6f0e1d2181318fc15b12dd55ef565ecd223

[ "MIT" ]

null

8kyu/Beginner Series #2 Clock.py

walkgo/codewars_tasks

4c0ab6f0e1d2181318fc15b12dd55ef565ecd223

[ "MIT" ]

null

8kyu/Beginner Series #2 Clock.py

walkgo/codewars_tasks

4c0ab6f0e1d2181318fc15b12dd55ef565ecd223

[ "MIT" ]

null

def past(h, m, s): h_ms = h * 3600000 m_ms = m * 60000 s_ms = s * 1000 return h_ms + m_ms + s_ms # Best Practices def past(h, m, s): return (3600*h + 60*m + s) * 1000

18.8

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188

2.5

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0.168421

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0

0.204724

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188

10

37

18.8

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1

0.285714

false

0

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0.571429

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null

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1

0

null

0

1

0

1

0

5

9376fd70f43fc6254d25d8d9de6182ad6d1f30d5

32

py

Python

tests/test_placeholder.py

symonk/stashie-cli

f18eec8a8e4bcb0b947a934e25b9a9f8066335fc

[ "Apache-2.0" ]

null

tests/test_placeholder.py

symonk/stashie-cli

f18eec8a8e4bcb0b947a934e25b9a9f8066335fc

[ "Apache-2.0" ]

null

tests/test_placeholder.py

symonk/stashie-cli

f18eec8a8e4bcb0b947a934e25b9a9f8066335fc

[ "Apache-2.0" ]

null

def test_placeholder(): ...

10.666667

23

0.59375

3

32

6

1

0

0.21875

32

2

24

16

0.72

0

1

0.5

true

0

0.5

0

1

0

null

0

1

0

null

0

1

0

5

fa8ea4a787dbe3d2892d7a449c5a14c4d96bc740

105

py

Python

mak/libs/pyxx/cxx/grammar/expression/primary/requires/__init__.py

motor-dev/Motor

98cb099fe1c2d31e455ed868cc2a25eae51e79f0

[ "BSD-3-Clause" ]

4

2015-05-13T16:28:36.000Z

2017-05-24T15:34:14.000Z

mak/libs/pyxx/cxx/grammar/expression/primary/requires/__init__.py

motor-dev/Motor

98cb099fe1c2d31e455ed868cc2a25eae51e79f0

[ "BSD-3-Clause" ]

null

mak/libs/pyxx/cxx/grammar/expression/primary/requires/__init__.py

motor-dev/Motor

98cb099fe1c2d31e455ed868cc2a25eae51e79f0

[ "BSD-3-Clause" ]

1

2017-03-21T08:28:07.000Z

from . import general from . import simple from . import type from . import compound from . import nested

21

22

0.771429

15

105

5.4

0.466667

0.617284

0

0.180952

105

5

23

21

0.94186

0

1

0

true

0

1

0

1

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1

0

null

1

0

1

0

null

0

1

0

1

0

5

fa954cccfdb16470bfc0b5d84f0c0d0b0bc56f46

70

py

Python

task_list_dev/__main__.py

HenriqueLR/task-list-dev

a623543bbf882458bca476f7a94156cd30d544ab

[ "MIT" ]

null

task_list_dev/__main__.py

HenriqueLR/task-list-dev

a623543bbf882458bca476f7a94156cd30d544ab

[ "MIT" ]

5

2017-11-25T17:05:47.000Z

2017-11-28T16:06:16.000Z

task_list_dev/__main__.py

HenriqueLR/task-list-dev

a623543bbf882458bca476f7a94156cd30d544ab

[ "MIT" ]

null

# coding: utf-8 print(__import__('task_list_dev').tools.get_list())

14

51

0.728571

11

70

4

0.909091

0

0.015625

0.085714

70

4

52

17.5

0.671875

0.185714

0

0.236364

0

1

0

true

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

fab1c59f92d41695f6c520dc6fa5d7c7dc7fd893

533

py

Python

documentstore_migracao/main/__init__.py

jamilatta/document-store-migracao

dc0473fb3ccf8c6c5f8d599b353f8c9caf104f55

[ "BSD-2-Clause" ]

null

documentstore_migracao/main/__init__.py

jamilatta/document-store-migracao

dc0473fb3ccf8c6c5f8d599b353f8c9caf104f55

[ "BSD-2-Clause" ]

null

documentstore_migracao/main/__init__.py

jamilatta/document-store-migracao

dc0473fb3ccf8c6c5f8d599b353f8c9caf104f55

[ "BSD-2-Clause" ]

null

""" module to methods to main """ import sys from .migrate_isis import migrate_isis_parser from .migrate_articlemeta import migrate_articlemeta_parser from .tools import tools_parser def main_migrate_articlemeta(): """ method main to script setup.py """ sys.exit(migrate_articlemeta_parser(sys.argv[1:])) def main_migrate_isis(): sys.exit(migrate_isis_parser(sys.argv[1:])) def tools(): sys.exit(tools_parser(sys.argv[1:])) if __name__ == "__main__": sys.exit(migrate_articlemeta_parser(sys.argv[1:]))

21.32

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76

533

4.842105

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0

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0.136961

533

24

60

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true

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null

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0

null

0

1

0

1

0

1

0

5

fae347d92c6318856795474c7e5ee0e6b5c0295e

31

py

Python

src/DeepReinforcementLearning/__init__.py

Quantum56/AlphaZero-AI

504522feb4e67211d5fb592f4b14a2cb8271d015

[ "MIT" ]

1

2019-11-12T01:55:36.000Z

src/DeepReinforcementLearning/__init__.py

Quantum56/AlphaZero-AI

504522feb4e67211d5fb592f4b14a2cb8271d015

[ "MIT" ]

14

2019-11-12T00:09:26.000Z

2022-02-10T00:46:30.000Z

src/DeepReinforcementLearning/__init__.py

Quantum56/AlphaZero-AI

504522feb4e67211d5fb592f4b14a2cb8271d015

[ "MIT" ]

null

# from AlphaZero-AI import game

31

0.806452

5

31

5

1

0

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31

1

31

0.925926

0.935484

0

null

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null

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null

1

null

true

0

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1

0

null

0

1

0

1

0

null

0

1

0

5

87dab20f9aff7e74782e7e82bc9833799c25002f

9,867

py

Python

django-ng/django_ng_project/django_ng_app/views.py

bounouhmahmoud/ensi

209e57340359af3ea063c064982198848dc36c5f

[ "MIT" ]

1

2018-07-10T06:59:05.000Z

django-ng/django_ng_project/django_ng_app/views.py

Arsalen/BusinessStrategies

209e57340359af3ea063c064982198848dc36c5f

[ "MIT" ]

null

django-ng/django_ng_project/django_ng_app/views.py

Arsalen/BusinessStrategies

209e57340359af3ea063c064982198848dc36c5f

[ "MIT" ]

null

# coding=utf-8 from django.shortcuts import render from rest_framework import viewsets, generics, status from .serializers import ClientSerializer, MessageSerializer, SearchSerializer, ManageSearchSerializer, PreferenceSerializer from .models import Client, Message, Search, ManageSearch, Preference from rest_framework.decorators import api_view from rest_framework.response import Response from rest_framework.views import APIView from django.http import Http404 import simplejson from django.contrib.auth.models import User from rest_framework.permissions import IsAuthenticated class ClientList(APIView): permission_classes = (IsAuthenticated,) def get(self, request, format=None): clients = Client.objects.all() serializer = ClientSerializer(clients, many=True) return Response(serializer.data) def post(self, request, format=None): serializer = ClientSerializer(data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data, status=status.HTTP_201_CREATED) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) class ClientDetail(APIView): permission_classes = (IsAuthenticated,) def get_object(self, pk): try: return Client.objects.get(pk=pk) except Client.DoesNotExist: raise Http404 def get(self, request, pk, format=None): snippet = self.get_object(pk) serializer = ClientSerializer(snippet) return Response(serializer.data) def put(self, request, pk, format=None): snippet = self.get_object(request.data['id']) if ( int(pk) == request.data['id'] ): if (snippet.password == request.data['oldpassword']): serializer = ClientSerializer(snippet, data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data) else: serializer = ClientSerializer(snippet, data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) def delete(self, request, pk, format=None): snippet = self.get_object(pk) snippet.delete() return Response(status=status.HTTP_204_NO_CONTENT) class ClientAuth(APIView): #permission_classes = (IsAuthenticated,) def get_object(self, request): try: return Client.objects.get(email=request['email'],password=request['password'],admn=request['admin']) except Client.DoesNotExist: raise Http404 def post(self, request, format=None): snippet = self.get_object(request.data) serializer = ClientSerializer(snippet) if(serializer.data['held'] == False): return Response(serializer.data) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) ################################################################################################################################ class MessageList(APIView): permission_classes = (IsAuthenticated,) def get(self, request, format=None): messages = Message.objects.all() serializer = MessageSerializer(messages, many=True) return Response(serializer.data) def post(self, request, format=None): serializer = MessageSerializer(data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data, status=status.HTTP_201_CREATED) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) class MessageDetail(APIView): permission_classes = (IsAuthenticated,) def get_object(self, pk): try: return Message.objects.get(pk=pk) except Message.DoesNotExist: raise Http404 def get(self, request, pk, format=None): snippet = self.get_object(pk) serializer = MessageSerializer(snippet) return Response(serializer.data) def put(self, request, pk, format=None): snippet = self.get_object(pk) serializer = MessageSerializer(snippet, data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) def delete(self, request, pk, format=None): snippet = self.get_object(pk) snippet.delete() return Response(status=status.HTTP_204_NO_CONTENT) ################################################################################################################################ class SearchList(APIView): permission_classes = (IsAuthenticated,) def get(self, request, format=None): searchs = Search.objects.all() serializer = SearchSerializer(searchs, many=True) return Response(serializer.data) def post(self, request, format=None): #print(simplejson.loads(request.body)['period']) #from rest_framework import status serializer = SearchSerializer(data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data, status=status.HTTP_201_CREATED) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) class SearchDetail(APIView): permission_classes = (IsAuthenticated,) def get_object(self, pk): try: return Search.objects.get(pk=pk) except Search.DoesNotExist: raise Http404 def get(self, request, pk, format=None): snippet = self.get_object(pk) serializer = SearchSerializer(snippet) return Response(serializer.data) def put(self, request, pk, format=None): snippet = self.get_object(pk) serializer = SearchSerializer(snippet, data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) def delete(self, request, pk, format=None): snippet = self.get_object(pk) snippet.delete() return Response(status=status.HTTP_204_NO_CONTENT) ################################################################################################################################ class ManageSearchList(APIView): permission_classes = (IsAuthenticated,) def get(self, request, format=None): managesearchs = ManageSearch.objects.all() serializer = ManageSearchSerializer(managesearchs, many=True) return Response(serializer.data) def post(self, request, format=None): serializer = ManageSearchSerializer(data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data, status=status.HTTP_201_CREATED) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) class ManageSearchDetail(APIView): permission_classes = (IsAuthenticated,) def get_object(self, pk): try: return ManageSearch.objects.get(pk=pk) except ManageSearch.DoesNotExist: raise Http404 def get(self, request, pk, format=None): snippet = self.get_object(pk) serializer = ManageSearchSerializer(snippet) return Response(serializer.data) def put(self, request, pk, format=None): snippet = self.get_object(pk) serializer = ManageSearchSerializer(snippet, data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) def delete(self, request, pk, format=None): snippet = self.get_object(pk) snippet.delete() return Response(status=status.HTTP_204_NO_CONTENT) ################################################################################################################################ class PreferenceList(APIView): permission_classes = (IsAuthenticated,) def get(self, request, format=None): preferences = Preference.objects.all() serializer = PreferenceSerializer(preferences, many=True) return Response(serializer.data) def post(self, request, format=None): serializer = PreferenceSerializer(data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data, status=status.HTTP_201_CREATED) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) class PreferenceDetail(APIView): permission_classes = (IsAuthenticated,) def get_object(self, pk): try: return Preference.objects.get(pk=pk) except Preference.DoesNotExist: raise Http404 def get(self, request, pk, format=None): snippet = self.get_object(pk) serializer = PreferenceSerializer(snippet) return Response(serializer.data) def put(self, request, pk, format=None): snippet = self.get_object(pk) serializer = PreferenceSerializer(snippet, data=request.data) if serializer.is_valid(): serializer.save() return Response(serializer.data) return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST) def delete(self, request, pk, format=None): snippet = self.get_object(pk) snippet.delete() return Response(status=status.HTTP_204_NO_CONTENT) ################################################################################################################################

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