xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

607ca84470c8804722dc9c2950ea75318ec4a1d6

31

py

Python

gscraper/__init__.py

AlexNilsson/python-image-scraper

03d88a24cfdca4f4e155932240109db7c2b2d86a

[ "MIT" ]

null

gscraper/__init__.py

AlexNilsson/python-image-scraper

03d88a24cfdca4f4e155932240109db7c2b2d86a

[ "MIT" ]

null

gscraper/__init__.py

AlexNilsson/python-image-scraper

03d88a24cfdca4f4e155932240109db7c2b2d86a

[ "MIT" ]

null

from .core import scrapeImages

15.5

30

0.83871

4

31

6.5

1

0

0.129032

31

1

31

0.962963

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

60d1d7d51896f12ced46ac9ad6e38698310badf8

27

py

Python

adpengine/__init__.py

dice-project/DICE-Anomaly-Detection-Tool

a5eeacb9e888348adbe97be0c26a500f2f03ec6f

[ "Apache-2.0" ]

4

2017-02-06T15:33:06.000Z

2018-05-08T01:43:03.000Z

adpengine/__init__.py

dice-project/DICE-Anomaly-Detection-Tool

a5eeacb9e888348adbe97be0c26a500f2f03ec6f

[ "Apache-2.0" ]

null

adpengine/__init__.py

dice-project/DICE-Anomaly-Detection-Tool

a5eeacb9e888348adbe97be0c26a500f2f03ec6f

[ "Apache-2.0" ]

null

from dmonadpengine import *

27

0.851852

3

27

7.666667

1

0

0.111111

27

1

27

0.958333

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

7160fd9e42bbfc4f6c897a1882e9aa96a7560b97

31

py

Python

TOPSIS-ParthArora-101853039/__init__.py

parthrr510/TOPSIS-ParthArora-101853039

6233ddb24e174eb2e561c288c822a4daa1258684

[ "MIT" ]

null

TOPSIS-ParthArora-101853039/__init__.py

parthrr510/TOPSIS-ParthArora-101853039

6233ddb24e174eb2e561c288c822a4daa1258684

[ "MIT" ]

null

TOPSIS-ParthArora-101853039/__init__.py

parthrr510/TOPSIS-ParthArora-101853039

6233ddb24e174eb2e561c288c822a4daa1258684

[ "MIT" ]

null

from Assignment6 import topsis

15.5

30

0.870968

4

31

6.75

1

0

0.037037

0.129032

31

1

31

0.962963

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

719e77a965d4c33d2c025e9d5e30397a8e2ac23c

67

py

Python

py_tdlib/constructors/get_country_code.py

Mr-TelegramBot/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

24

2018-10-05T13:04:30.000Z

2020-05-12T08:45:34.000Z

py_tdlib/constructors/get_country_code.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

3

2019-06-26T07:20:20.000Z

2021-05-24T13:06:56.000Z

py_tdlib/constructors/get_country_code.py

MrMahdi313/python-tdlib

2e2d21a742ebcd439971a32357f2d0abd0ce61eb

[ "MIT" ]

5

2018-10-05T14:29:28.000Z

2020-08-11T15:04:10.000Z

from ..factory import Method class getCountryCode(Method): pass

11.166667

29

0.776119

8

67

6.5

0.875

0

0.149254

67

5

30

13.4

0.912281

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

71e749ade64252247b048f84b0217018506fe040

9,673

py

Python

tests/core/test_runner.py

iri6e4k0/vedro

dd51c16400993d0fe1fd34bba57edff710ac2638

[ "Apache-2.0" ]

2

2021-08-24T12:49:30.000Z

2022-01-23T07:21:25.000Z

tests/core/test_runner.py

iri6e4k0/vedro

dd51c16400993d0fe1fd34bba57edff710ac2638

[ "Apache-2.0" ]

20

2015-12-09T11:04:23.000Z

2022-03-20T09:18:17.000Z

tests/core/test_runner.py

iri6e4k0/vedro

dd51c16400993d0fe1fd34bba57edff710ac2638

[ "Apache-2.0" ]

3

2015-12-09T07:31:23.000Z

2022-01-28T11:03:24.000Z

import sys from pytest import raises if sys.version_info >= (3, 8): from unittest.mock import AsyncMock else: from asynctest.mock import CoroutineMock as AsyncMock from unittest.mock import Mock, call import pytest from baby_steps import given, then, when from vedro import Scenario from vedro.core import Dispatcher, Runner, VirtualScenario, VirtualStep from vedro.events import ( ExceptionRaisedEvent, ScenarioFailedEvent, ScenarioPassedEvent, ScenarioRunEvent, StepFailedEvent, StepPassedEvent, StepRunEvent, ) @pytest.fixture() def dispatcher_(): return AsyncMock(Dispatcher()) @pytest.fixture() def runner(dispatcher_: Dispatcher): return Runner(dispatcher_) @pytest.mark.asyncio @pytest.mark.parametrize("method_mock_factory", (Mock, AsyncMock,)) async def test_runner_run_step_passed(method_mock_factory: Mock, *, runner: Runner, dispatcher_: Dispatcher): with given: scenario_ = Mock(Scenario, step=method_mock_factory(return_value=None)) step = VirtualStep(scenario_.step) with when: step_result = await runner.run_step(step, scenario_) with then: assert scenario_.mock_calls == [call.step(scenario_)] assert step_result.is_passed() is True assert step_result.exc_info is None assert isinstance(step_result.started_at, float) assert isinstance(step_result.ended_at, float) assert dispatcher_.mock_calls == [ call.fire(StepRunEvent(step_result)), call.fire(StepPassedEvent(step_result)), ] @pytest.mark.asyncio @pytest.mark.parametrize("method_mock_factory", (Mock, AsyncMock)) async def test_runner_run_step_failed(method_mock_factory: Mock, *, runner: Runner, dispatcher_: Dispatcher): with given: exception = AssertionError() scenario_ = Mock(Scenario, step=method_mock_factory(side_effect=exception)) step = VirtualStep(scenario_.step) with when: step_result = await runner.run_step(step, scenario_) with given: assert scenario_.mock_calls == [call.step(scenario_)] assert step_result.is_failed() is True assert step_result.exc_info.value == exception assert isinstance(step_result.started_at, float) assert isinstance(step_result.ended_at, float) assert dispatcher_.mock_calls == [ call.fire(StepRunEvent(step_result)), call.fire(ExceptionRaisedEvent(step_result.exc_info)), call.fire(StepFailedEvent(step_result)), ] @pytest.mark.asyncio @pytest.mark.parametrize("method_mock_factory", (Mock, AsyncMock)) async def test_runner_run_step_interrupted(*, method_mock_factory: Mock, dispatcher_: Dispatcher): with given: interrupt_exception = KeyboardInterrupt scenario_ = Mock(Scenario, step=method_mock_factory(side_effect=interrupt_exception)) virtual_step = VirtualStep(scenario_.step) runner = Runner(dispatcher_, interrupt_exceptions=(interrupt_exception,)) with when, raises(BaseException) as exception: await runner.run_step(virtual_step, scenario_) with given: assert exception.type is interrupt_exception assert scenario_.mock_calls == [call.step(scenario_)] @pytest.mark.asyncio async def test_runner_run_scenario_no_steps_passed(*, runner: Runner, dispatcher_: Dispatcher): with given: scenario_ = Mock(Scenario, step=Mock(return_value=None), __file__="/tmp/scenario.py") virtual_scenario = VirtualScenario(scenario_, []) with when: scenario_result = await runner.run_scenario(virtual_scenario) with then: assert scenario_result.is_passed() is True assert isinstance(scenario_result.started_at, float) assert isinstance(scenario_result.ended_at, float) assert dispatcher_.mock_calls == [ call.fire(ScenarioRunEvent(scenario_result)), call.fire(ScenarioPassedEvent(scenario_result)), ] @pytest.mark.asyncio async def test_runner_run_scenario_single_step_passed(*, runner: Runner, dispatcher_: Dispatcher): with given: scenario_ = Mock(Scenario, step=Mock(return_value=None), __file__="/tmp/scenario.py") step = VirtualStep(scenario_.step) virtual_scenario = VirtualScenario(scenario_, [step]) with when: scenario_result = await runner.run_scenario(virtual_scenario) with then: assert scenario_result.is_passed() is True assert isinstance(scenario_result.started_at, float) assert isinstance(scenario_result.ended_at, float) step_results = scenario_result.step_results assert dispatcher_.mock_calls == [ call.fire(ScenarioRunEvent(scenario_result)), call.fire(StepRunEvent(step_results[0])), call.fire(StepPassedEvent(step_results[0])), call.fire(ScenarioPassedEvent(scenario_result)), ] @pytest.mark.asyncio async def test_runner_run_scenario_single_step_failed(*, runner: Runner, dispatcher_: Dispatcher): with given: exception = AssertionError() scenario_ = Mock(Scenario, step=Mock(side_effect=exception), __file__="/tmp/scenario.py") step = VirtualStep(scenario_.step) virtual_scenario = VirtualScenario(scenario_, [step]) with when: scenario_result = await runner.run_scenario(virtual_scenario) with then: assert scenario_result.is_failed() is True assert isinstance(scenario_result.started_at, float) assert isinstance(scenario_result.ended_at, float) step_results = scenario_result.step_results assert dispatcher_.mock_calls == [ call.fire(ScenarioRunEvent(scenario_result)), call.fire(StepRunEvent(step_results[0])), call.fire(ExceptionRaisedEvent(step_results[0].exc_info)), call.fire(StepFailedEvent(step_results[0])), call.fire(ScenarioFailedEvent(scenario_result)), ] @pytest.mark.asyncio async def test_runner_run_scenario_multiple_steps_passed(*, runner: Runner, dispatcher_: Dispatcher): with given: scenario_ = Mock(Scenario, __file__="/tmp/scenario.py", first_step=Mock(return_value=None), second_step=Mock(return_value=None)) first_step = VirtualStep(scenario_.first_step) second_step = VirtualStep(scenario_.second_step) virtual_scenario = VirtualScenario(scenario_, [first_step, second_step]) with when: scenario_result = await runner.run_scenario(virtual_scenario) with then: assert scenario_result.is_passed() is True assert isinstance(scenario_result.started_at, float) assert isinstance(scenario_result.ended_at, float) first_step_result = scenario_result.step_results[0] second_step_result = scenario_result.step_results[1] assert dispatcher_.mock_calls == [ call.fire(ScenarioRunEvent(scenario_result)), call.fire(StepRunEvent(first_step_result)), call.fire(StepPassedEvent(first_step_result)), call.fire(StepRunEvent(second_step_result)), call.fire(StepPassedEvent(second_step_result)), call.fire(ScenarioPassedEvent(scenario_result)), ] @pytest.mark.asyncio async def test_runner_run_scenario_multiple_steps_failed(): with given: dispatcher = AsyncMock(Dispatcher) runner = Runner(dispatcher) exception = AssertionError() scenario_ = Mock(Scenario, __file__="/tmp/scenario.py", first_step=Mock(return_value=None), second_step=Mock(side_effect=exception), third_step=Mock(return_value=None)) first_step = VirtualStep(scenario_.first_step) second_step = VirtualStep(scenario_.second_step) third_step = VirtualStep(scenario_.third_step) scenario = VirtualScenario(scenario_, [first_step, second_step, third_step]) with when: scenario_result = await runner.run_scenario(scenario) with then: assert scenario_result.is_failed() is True assert isinstance(scenario_result.started_at, float) assert isinstance(scenario_result.ended_at, float) first_step_result = scenario_result.step_results[0] second_step_result = scenario_result.step_results[1] assert dispatcher.mock_calls == [ call.fire(ScenarioRunEvent(scenario_result)), call.fire(StepRunEvent(first_step_result)), call.fire(StepPassedEvent(first_step_result)), call.fire(StepRunEvent(second_step_result)), call.fire(ExceptionRaisedEvent(second_step_result.exc_info)), call.fire(StepFailedEvent(second_step_result)), call.fire(ScenarioFailedEvent(scenario_result)), ] @pytest.mark.asyncio async def test_runner_interrupted_scenario(*, dispatcher_: Dispatcher): with given: interrupt_exception = KeyboardInterrupt runner = Runner(dispatcher_, interrupt_exceptions=(interrupt_exception,)) step_ = Mock(side_effect=interrupt_exception) scenario_ = Mock(Scenario, step=step_, __file__="/tmp/scenario.py") virtual_scenario = VirtualScenario(scenario_, [VirtualStep(step_)]) with when, raises(BaseException) as exception: await runner.run_scenario(virtual_scenario) with then: assert exception.type is interrupt_exception

35.693727

98

0.69389

1,049

9,673

6.080076

0.086749

0.079022

0.032926

0.028222

0.848855

0.814675

0.796174

0.712135

0.697554

0.648479

0

0.001456

0.21896

9,673

270

99

35.825926

0.842753

0

0.625616

0

0.015817

0

0.187192

1

0.009852

false

0.08867

0.049261

0.009852

0.068966

0

null

0

1

0

1

0

null

0

1

0

6

e082b8fd0e8142bceca268718bb070271419def5

27

py

Python

print('hello world').py

BradLyman/MafiaGame

c6f14a303b126886e8593ed91d034650cb7d82b0

[ "MIT" ]

null

print('hello world').py

BradLyman/MafiaGame

c6f14a303b126886e8593ed91d034650cb7d82b0

[ "MIT" ]

null

print('hello world').py

BradLyman/MafiaGame

c6f14a303b126886e8593ed91d034650cb7d82b0

[ "MIT" ]

null

print('hello stupid Brad.')

27

0.740741

4

27

5

1

0

0.074074

27

1

27

0.8

0

0.642857

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

e08cf6eb7f3ec9dc6ba30a19c42910ee06b33e5d

29

py

Python

worker/__init__.py

Alan-Rick/flask_template_two

053b611c687eeee874b941daf4237eec5524ee96

[ "MIT" ]

null

worker/__init__.py

Alan-Rick/flask_template_two

053b611c687eeee874b941daf4237eec5524ee96

[ "MIT" ]

null

worker/__init__.py

Alan-Rick/flask_template_two

053b611c687eeee874b941daf4237eec5524ee96

[ "MIT" ]

null

from .celery_worker import *

14.5

28

0.793103

4

29

5.5

1

0

0.137931

29

1

29

0.88

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

e0bf22ecd82f86fc5e036d4827e425cc9f3a0dfd

167

py

Python

src/combine.py

pranayjoshi/Medico

2508a39d58eec50f5e94f3c878c00f599fff6629

[ "MIT" ]

13

2020-09-04T09:16:15.000Z

2021-01-27T07:03:12.000Z

src/combine.py

bhargavaganti/Medico

9059c59f49211f48a27805a00807121ac6f27b27

[ "MIT" ]

1

2020-10-04T03:23:45.000Z

src/combine.py

bhargavaganti/Medico

9059c59f49211f48a27805a00807121ac6f27b27

[ "MIT" ]

2

2020-11-27T12:25:10.000Z

2022-01-11T06:25:33.000Z

import sys sys.path.append("./src/AI_files") sys.path.append("./src/Speech_process") import speech_to_text import detector speech_to_text.run() print(detector.run())

20.875

39

0.778443

27

167

4.592593

0.518519

0.112903

0.209677

0.258065

0

0.065868

167

8

40

20.875

0.794872

0

0.202381

0

1

0

true

0

0.428571

0

0.428571

0.142857

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

1cb65ed814911faaacc978cdeca369e6ad621eff

47

py

Python

android/red.py

Abdulhadi5692HDI/BIGTEXT

af5e9ac9d89d8a3719f2535129e73ed553043db4

[ "Unlicense" ]

null

android/red.py

Abdulhadi5692HDI/BIGTEXT

af5e9ac9d89d8a3719f2535129e73ed553043db4

[ "Unlicense" ]

null

android/red.py

Abdulhadi5692HDI/BIGTEXT

af5e9ac9d89d8a3719f2535129e73ed553043db4

[ "Unlicense" ]

null

from colorama import Fore print(Fore.RED + "")

15.666667

25

0.723404

7

47

4.857143

0.857143

0

0.148936

47

2

26

23.5

0.85

0

1

0

true

0

0.5

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

1cd499a19627451cb8cb27576706d997a3ee807b

51

py

Python

Class Notes/Flask_app/compute.py

alannanoguchi/DS-2.3-Data-Science-in-Production

df0ebef3db963d848a7a8fdc585da769dcb2c865

[ "MIT" ]

null

Class Notes/Flask_app/compute.py

alannanoguchi/DS-2.3-Data-Science-in-Production

df0ebef3db963d848a7a8fdc585da769dcb2c865

[ "MIT" ]

null

Class Notes/Flask_app/compute.py

alannanoguchi/DS-2.3-Data-Science-in-Production

df0ebef3db963d848a7a8fdc585da769dcb2c865

[ "MIT" ]

null

import math def compute(r): return math.sin(r)

12.75

22

0.686275

9

51

3.888889

0.777778

0

0.196078

51

4

22

12.75

0.853659

0

1

0.333333

false

0

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

1cf84206043ce917f0b51b9586a1a238a7c2d6dc

2,108

py

Python

Ago-Dic-2020/flores-fernandez-fernando/Practicas/Practica-5/Test_Practica-5_strategy.py

bryanbalderas/DAS_Sistemas

1e31f088c0de7134471025a5730b0abfc19d936e

[ "MIT" ]

41

2017-09-26T09:36:32.000Z

2022-03-19T18:05:25.000Z

Ago-Dic-2020/flores-fernandez-fernando/Practicas/Practica-5/Test_Practica-5_strategy.py

bryanbalderas/DAS_Sistemas

1e31f088c0de7134471025a5730b0abfc19d936e

[ "MIT" ]

67

2017-09-11T05:06:12.000Z

2022-02-14T04:44:04.000Z

Ago-Dic-2020/flores-fernandez-fernando/Practicas/Practica-5/Test_Practica-5_strategy.py

bryanbalderas/DAS_Sistemas

1e31f088c0de7134471025a5730b0abfc19d936e

[ "MIT" ]

210

2017-09-01T00:10:08.000Z

2022-03-19T18:05:12.000Z

import unittest from Practica5_strategy import * class StrategyTest(unittest.TestCase): def test_basic_auth_strategy(self): context = AuthContext(BasicAuthConcreteStrategy(usr='tintin', passwd='123456')) self.assertEqual( context.authenticate(), '### Authenticated with Basic Auth\n\tUser: tintin\n\tPass: 123456' ) def test_oauth_strategy(self): cred = { "access_token": "una cadena muy larga", "token_type": "Bearer", "expires_in": 3600, "refresh_token": "una cadena muy larga 2", "scope": "readAndWrite" } context = AuthContext(OauthAuthConcreteStrategy(credentials=cred)) self.assertEqual( context.authenticate(), '### Authenticated with OAuth\n\tCredentials: {"access_token":"una cadena muy larga","token_type":"Bearer","expires_in":3600,"refresh_token":"una cadena muy larga 2","scope":"readAndWrite"}' ) def test_api_key_strategy(self): context = AuthContext(ApiKeyConcreteStrategy(api_key='tintin-123456')) self.assertEqual( context.authenticate(), '### Authenticated with API Key\n\tKey: tintin-123456' ) def test_default_strategy(self): self.assertEqual( AuthContext().authenticate(), '### Authenticated with OAuth\n\tCredentials: {"access_token":"una cadena muy larga","token_type":"Bearer","expires_in":3600,"refresh_token":"una cadena muy larga 2","scope":"default"}' ) def test_updating_strategy(self): context = AuthContext(BasicAuthConcreteStrategy(usr='tintin', passwd='123456')) self.assertEqual( context.authenticate(), '### Authenticated with Basic Auth\n\tUser: tintin\n\tPass: 123456' ) context.set_strategy(ApiKeyConcreteStrategy(api_key='tintin-123456')) self.assertEqual( context.authenticate(), '### Authenticated with API Key\n\tKey: tintin-123456' ) if __name__ == "__main__": unittest.main()

39.773585

202

0.63093

210

2,108

6.161905

0.271429

0.069552

0.134467

0.078825

0.742658

0.725657

0

0.040151

0.243833

2,108

53

203

39.773585

0.771644

0

0.369565

0

0.043478

0.366524

0.105737

0

0.130435

1

0.108696

false

0.086957

0.043478

0

0.173913

0

null

0

1

0

null

0

1

0

6

e8304bc90b617140933d9402630552eae52716b4

121

py

Python

python/faceonnx/__init__.py

QuantumLiu/FaceONNX

cc630020f51f0e8b05e9839c58aa4bd1ac040409

[ "MIT" ]

22

2021-08-02T05:09:13.000Z

2022-03-23T18:44:10.000Z

python/faceonnx/__init__.py

QuantumLiu/FaceONNX

cc630020f51f0e8b05e9839c58aa4bd1ac040409

[ "MIT" ]

6

2021-10-02T22:17:58.000Z

2022-03-27T01:42:44.000Z

python/faceonnx/__init__.py

QuantumLiu/FaceONNX

cc630020f51f0e8b05e9839c58aa4bd1ac040409

[ "MIT" ]

7

2021-08-10T02:41:26.000Z

2022-03-23T18:40:10.000Z

from .engine import * from .imaging import * from .landmarks import * from .embeddings import * from .rectangles import *

24.2

25

0.760331

15

121

6.133333

0.466667

0.434783

0

0.157025

121

5

26

24.2

0.901961

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

1c2927cf1a445c9ca44b216f8f7d15432031eac4

3,208

py

Python

test/test_epifm.py

ecell/scopyon

99436fbfd34bb684966846eba75b206c2806f69c

[ "BSD-3-Clause" ]

6

2018-12-24T16:20:55.000Z

2021-06-12T20:50:04.000Z

test/test_epifm.py

ecell/bioimaging

99436fbfd34bb684966846eba75b206c2806f69c

[ "BSD-3-Clause" ]

9

2019-03-03T15:30:37.000Z

2020-08-27T05:48:33.000Z

test/test_epifm.py

ecell/scopyon

99436fbfd34bb684966846eba75b206c2806f69c

[ "BSD-3-Clause" ]

3

2019-03-05T22:51:38.000Z

2020-02-03T13:58:48.000Z

import unittest class TestEPIFM(unittest.TestCase): def setUp(self): self.radial_cutoff = 1000.0e-9 self.radial_resolution = 1.0e-9 def tearDown(self): pass def test1(self): import scopyon._epifm def test2(self): print('Testing TRITC ...') import numpy from scopyon._epifm import PointSpreadingFunction psf = PointSpreadingFunction(psf_radial_cutoff=self.radial_cutoff, psf_radial_width=None, psf_depth_cutoff=1000.0e-9, fluorophore_type="Tetramethylrhodamine(TRITC)", psf_wavelength=5.78e-07) depth = 0.0 radial = numpy.arange(0.0, self.radial_cutoff, self.radial_resolution, dtype=float) psf_r = psf.get_distribution(radial, depth) self.assertIs(type(psf_r), numpy.ndarray) self.assertEqual(psf_r.ndim, 1) self.assertEqual(psf_r.size, radial.size) self.assertTrue((psf_r >= 0.0).all()) tot_r = numpy.sum(2 * numpy.pi * radial * psf_r) * self.radial_resolution print(f'Integral of radial distribution = {tot_r}') psf_cart = psf.radial_to_cartesian(radial, psf_r, self.radial_cutoff, self.radial_resolution) tot_cart = psf_cart.sum() * (self.radial_resolution * self.radial_resolution) print(f'Integral of cartesian distribution = {tot_cart}') camera = numpy.zeros((512, 512)) pixel_length = 4.444444444444444e-08 psf.overlay_signal_(camera, psf_cart, numpy.zeros(3, dtype=float), pixel_length, self.radial_resolution, 1.0) # tot_camera = camera.sum() * (self.radial_resolution * self.radial_resolution) tot_camera = camera.sum() print(f'Integral of detected = {tot_camera}') def test3(self): print('Testing Gaussian ...') import numpy from scopyon._epifm import PointSpreadingFunction psf = PointSpreadingFunction(psf_radial_cutoff=self.radial_cutoff, psf_radial_width=1.0e-7, psf_depth_cutoff=1000.0e-9, fluorophore_type="Gaussian", psf_wavelength=6.0e-7) depth = 0.0 radial = numpy.arange(0.0, self.radial_cutoff, self.radial_resolution, dtype=float) psf_r = psf.get_distribution(radial, depth) self.assertIs(type(psf_r), numpy.ndarray) self.assertEqual(psf_r.ndim, 1) self.assertEqual(psf_r.size, radial.size) self.assertTrue((psf_r >= 0.0).all()) tot_r = numpy.sum(2 * numpy.pi * radial * psf_r) * self.radial_resolution print(f'Integral of radial distribution = {tot_r}') psf_cart = psf.radial_to_cartesian(radial, psf_r, self.radial_cutoff, self.radial_resolution) tot_cart = psf_cart.sum() * (self.radial_resolution * self.radial_resolution) print(f'Integral of cartesian distribution = {tot_cart}') camera = numpy.zeros((512, 512)) pixel_length = 4.444444444444444e-08 psf.overlay_signal_(camera, psf_cart, numpy.zeros(3, dtype=float), pixel_length, self.radial_resolution, 1.0) # tot_camera = camera.sum() * (self.radial_resolution * self.radial_resolution) tot_camera = camera.sum() print(f'Integral of detected = {tot_camera}') if __name__ == '__main__': unittest.main()

42.773333

198

0.679239

425

3,208

4.894118

0.190588

0.115385

0.163462

0.063462

0.85

0.815385

0

0.041225

0.206047

3,208

74

199

43.351351

0.775422

0.048317

0

0.690909

0

0.106885

0.008852

0

0.145455

1

0.090909

false

0.018182

0.109091

0

0.218182

0.145455

0

null

0

1

0

null

0

6

1c47869bfa0f88eba2e94f57df3c36bcb2331ede

404

py

Python

server/src/prefect_server/utilities/__init__.py

louisditzel/prefect

b1a02fee623b965e756a38aa09059db780ab67eb

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

1

2020-05-10T14:32:32.000Z

server/src/prefect_server/utilities/__init__.py

louisditzel/prefect

b1a02fee623b965e756a38aa09059db780ab67eb

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

3

2022-02-14T11:25:57.000Z

2022-02-27T16:25:14.000Z

server/src/prefect_server/utilities/__init__.py

louisditzel/prefect

b1a02fee623b965e756a38aa09059db780ab67eb

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

1

2020-05-31T04:42:56.000Z

# Licensed under the Prefect Community License, available at # https://www.prefect.io/legal/prefect-community-license import prefect_server.utilities.context import prefect_server.utilities.exceptions import prefect_server.utilities.graphql import prefect_server.utilities.logging import prefect_server.utilities.names import prefect_server.utilities.tests import prefect_server.utilities.asynchronous

33.666667

60

0.868812

51

404

6.745098

0.431373

0.264535

0.386628

0.569767

0

0.066832

404

11

61

36.727273

0.912467

0.279703

0

1

0

true

0

1

0

1

0

null

1

0

null

0

1

0

1

0

1

0

6

1c92bbebf0ef3206a0556424cec456a07a3c2d52

110

py

Python

toontown/pets/PetDCImportsAI.py

MasterLoopyBM/Toontown

ebed7fc3f2ef06a529cf02eda7ab46361aceef9d

[ "MIT" ]

1

2020-02-07T18:15:12.000Z

toontown/pets/PetDCImportsAI.py

TrueBlueDogemon/Toontown

ebed7fc3f2ef06a529cf02eda7ab46361aceef9d

[ "MIT" ]

null

toontown/pets/PetDCImportsAI.py

TrueBlueDogemon/Toontown

ebed7fc3f2ef06a529cf02eda7ab46361aceef9d

[ "MIT" ]

2

2020-11-08T03:38:35.000Z

2021-09-02T07:03:47.000Z

if hasattr(simbase, 'wantPets') and simbase.wantPets: import DistributedPetAI import DistributedPetUD

27.5

53

0.781818

11

110

7.818182

0.727273

0.348837

0

0.154545

110

3

54

36.666667

0.924731

0

0.072727

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

98da8092064f3f8a56e8cbd799f5fca34eac9289

248

py

Python

mllib/supervised/__init__.py

posterrieri/mllib

809265573eb5af5c68f92537ed90390795008e40

[ "MIT" ]

null

mllib/supervised/__init__.py

posterrieri/mllib

809265573eb5af5c68f92537ed90390795008e40

[ "MIT" ]

null

mllib/supervised/__init__.py

posterrieri/mllib

809265573eb5af5c68f92537ed90390795008e40

[ "MIT" ]

null

from .parametric import LinearRegression from .parametric import LogisticRegressionClassifier from .non_parametric import kNearestNeighbors __all__ = ['LinearRegression', 'LogisticRegressionClassifier', 'kNearestNeighbors']

35.428571

52

0.778226

17

248

11.058824

0.470588

0.255319

0.212766

0

0.165323

248

7

53

35.428571

0.908213

0

0.24498

0.11245

0

1

0

false

0

0.5

0

0.5

0

1

0

1

null

1

0

1

0

null

0

1

0

6

98de2a3835095d92f2e4e0e5dd2c9655069d3699

2,560

py

Python

p8_test/test_local/test_eta1.py

crazynayan/tpf1

c81a15d88d4d1f3ed2cf043c90782a4b8509ef14

[ "MIT" ]

1

2020-01-27T10:10:40.000Z

p8_test/test_local/test_eta1.py

crazynayan/tpf1

c81a15d88d4d1f3ed2cf043c90782a4b8509ef14

[ "MIT" ]

4

2019-08-23T05:24:23.000Z

2021-09-16T10:05:55.000Z

p8_test/test_local/test_eta1.py

crazynayan/tpf1

c81a15d88d4d1f3ed2cf043c90782a4b8509ef14

[ "MIT" ]

null

from p1_utils.data_type import DataType from p8_test.test_local import TestDebug class Eta1Test(TestDebug): DEBUG_DATA = list() SEGMENT = "ETA1" def test_eta1_vanilla(self): test_data = self.tpf_server.run("ETA1", self.test_data) self.output = test_data.output self.assertEqual("ETAX265.6", self.output.last_line, self.output.last_node) self.assertIn("UNABLE TO END TRANSACTION - NO PNR PRESENT IN WORK AREA", self.output.messages) self.assertEqual(list(), self.output.dumps) def test_eta1_el_restricted(self): self.test_data.add_fields([("EBW000", 10)], "EB0EB") self.test_data.set_field("MI0ACC", DataType("C", input="EL").to_bytes()) self.test_data.set_field("WA0FNS", DataType("X", input="10").to_bytes()) self.test_data.set_field("WA0UB4", DataType("X", input="08").to_bytes()) test_data = self.tpf_server.run("ETA1", self.test_data) self.output = test_data.output self.assertEqual("$$UIO1$$.2", self.output.last_line, self.output.last_node) self.assertIn("RESTRICTED" + 40 * " ", self.output.messages) def test_eta1_e_no_error(self): self.test_data.set_field("MI0ACC", DataType("C", input="E").to_bytes()) self.test_data.set_field("WA0FNS", DataType("X", input="10").to_bytes()) self.test_data.set_field("WA0UB4", DataType("X", input="08").to_bytes()) test_data = self.tpf_server.run("ETA1", self.test_data) self.output = test_data.output self.assertEqual("ETAX265.6", self.output.last_line, self.output.last_node) self.assertIn("UNABLE TO END TRANSACTION - NO PNR PRESENT IN WORK AREA", self.output.messages) def test_eta1_el_plus_off_queue(self): self.test_data.set_field("MI0ACC", DataType("C", input="EL+").to_bytes()) test_data = self.tpf_server.run("ETA1", self.test_data) self.output = test_data.output self.assertEqual("$$UIO1$$.2", self.output.last_line, self.output.last_node) off_queue = "CANNOT DO THIS IF OFF QUEUE" self.assertIn(off_queue + (50 - len(off_queue)) * " ", self.output.messages) def test_eta1_el_off_queue(self): self.test_data.set_field("MI0ACC", DataType("C", input="EL").to_bytes()) test_data = self.tpf_server.run("ETA1", self.test_data) self.output = test_data.output self.assertEqual("ETAX265.6", self.output.last_line, self.output.last_node) self.assertIn("UNABLE TO END TRANSACTION - NO PNR PRESENT IN WORK AREA", self.output.messages)

52.244898

102

0.677344

371

2,560

4.45283

0.199461

0.116223

0.108959

0.072639

0.807506

0.789952

0.763317

0

0.027462

0.175

2,560

48

103

53.333333

0.754735

0

0.585366

0

0.139844

0

0.268293

1

0.121951

false

0

0.04878

0

0.243902

0

null

0

1

0

null

0

6

98e9860ecd5998386af2393a5a5039b8bdf97a91

2,909

py

Python

tests/test_bpf_idea.py

ulugbekna/angr-platforms

3f374b72e5a141f8b421050e3f800eef10175198

[ "BSD-2-Clause" ]

43

2017-09-21T23:26:50.000Z

2022-03-26T08:51:45.000Z

tests/test_bpf_idea.py

ulugbekna/angr-platforms

3f374b72e5a141f8b421050e3f800eef10175198

[ "BSD-2-Clause" ]

27

2017-09-29T00:00:46.000Z

2022-03-31T01:14:54.000Z

tests/test_bpf_idea.py

ulugbekna/angr-platforms

3f374b72e5a141f8b421050e3f800eef10175198

[ "BSD-2-Clause" ]

23

2017-10-06T19:29:25.000Z

2022-03-19T20:56:24.000Z

import nose import os import angr from angr_platforms.bpf import * from angr_platforms.bpf.lift_bpf import MAX_INSTR_ID TEST_PROGRAMS_BASE = str(os.path.join(os.path.dirname(os.path.realpath(__file__)), '..', 'test_programs', 'bpf')) def test_idea_correct_flag(): idea_bpf = os.path.join(TEST_PROGRAMS_BASE, 'idea.bpf') proj = angr.Project(idea_bpf, main_opts={'backend': 'bpf'}) assert proj.arch.name == 'BPF' state = proj.factory.entry_state() simgr = proj.factory.simulation_manager(state) # Initialize the state with the correct flag flag = "w0w_y0u_are_Master-0F-secc0mp///>_w_<///" # the syscall number must be 0x1337 state.memory.store(proj.arch.DATA_BASE, 0x1337, endness='Iend_LE') # input variables for i in range(0, len(flag), 4): state.memory.store(proj.arch.DATA_BASE + 0x10 + i, state.solver.BVV(ord(flag[i]), 8)) state.memory.store(proj.arch.DATA_BASE + 0x10 + i + 1, state.solver.BVV(ord(flag[i+1]), 8)) state.memory.store(proj.arch.DATA_BASE + 0x10 + i + 2, state.solver.BVV(ord(flag[i+2]), 8)) state.memory.store(proj.arch.DATA_BASE + 0x10 + i + 3, state.solver.BVV(ord(flag[i+3]), 8)) # Execute until it returns simgr.explore(find=(MAX_INSTR_ID * 8,)) nose.tools.assert_equal(len(simgr.found), 1) nose.tools.assert_equal(simgr.found[0].history.addr, 4058 * 8) # executed until "ret ALLOW" nose.tools.assert_equal(simgr.found[0].regs._res._model_concrete.value, 1) # the result is ALLOW def test_idea_incorrect_flag(): idea_bpf = os.path.join(TEST_PROGRAMS_BASE, 'idea.bpf') proj = angr.Project(idea_bpf, main_opts={'backend': 'bpf'}) assert proj.arch.name == 'BPF' state = proj.factory.entry_state() simgr = proj.factory.simulation_manager(state) # Initialize the state with the incorrect flag flag = "w0w_y0u_are_Master-0F-secc0mp///>_w_<//\\" # the syscall number must be 0x1337 state.memory.store(proj.arch.DATA_BASE, 0x1337, endness='Iend_LE') # input variables for i in range(0, len(flag), 4): state.memory.store(proj.arch.DATA_BASE + 0x10 + i, state.solver.BVV(ord(flag[i]), 8)) state.memory.store(proj.arch.DATA_BASE + 0x10 + i + 1, state.solver.BVV(ord(flag[i+1]), 8)) state.memory.store(proj.arch.DATA_BASE + 0x10 + i + 2, state.solver.BVV(ord(flag[i+2]), 8)) state.memory.store(proj.arch.DATA_BASE + 0x10 + i + 3, state.solver.BVV(ord(flag[i+3]), 8)) # Execute until it returns simgr.explore(find=(MAX_INSTR_ID * 8,)) nose.tools.assert_equal(len(simgr.found), 1) nose.tools.assert_equal(simgr.found[0].history.addr, 4045 * 8) # executed until "ret DENY" nose.tools.assert_equal(simgr.found[0].regs._res._model_concrete.value, 0) # the result is DENY def main(): test_idea_correct_flag() test_idea_incorrect_flag() if __name__ == '__main__': main()

37.294872

113

0.683053

458

2,909

4.155022

0.222707

0.050447

0.084078

0.105097

0.805045

0

0.039571

0.166036

2,909

77

114

37.779221

0.744847

0.113097

0

0.577778

0

0.063548

0.031579

0

0.017154

0

0.177778

1

0.066667

false

0

0.111111

0

0.177778

0

null

0

1

0

null

0

6

c7021b6d56675a3c3e62fdc32db22fe76bfe3b25

83

py

Python

pokemongo_bot/walkers/__init__.py

islanderman/PokemonGo-Bot

3c9806b3de71b5c2c38ba92f22ed662901ee700d

[ "MIT" ]

2

2018-11-27T06:02:24.000Z

2019-12-31T19:10:32.000Z

pokemongo_bot/walkers/__init__.py

0x2400/PokemonGo-Bot

3c9806b3de71b5c2c38ba92f22ed662901ee700d

[ "MIT" ]

1

2018-10-28T04:50:46.000Z

pokemongo_bot/walkers/__init__.py

0x2400/PokemonGo-Bot

3c9806b3de71b5c2c38ba92f22ed662901ee700d

[ "MIT" ]

1

2017-10-29T18:59:07.000Z

from polyline_generator import Polyline from polyline_walker import PolylineWalker

27.666667

42

0.903614

10

83

7.3

0.6

0.328767

0

0.096386

83

2

43

41.5

0.973333

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

c779692d791c5e6537aadb868abf7824709e4d21

4,108

py

Python

Python/Scheduling Algorithms/fcfs.py

shruti8301/Algorithms-Cheatsheet-Resources

cece012bba7f47c3a1ecfaff380dcbc787c26149

[ "MIT" ]

199

2019-12-01T01:23:34.000Z

2022-02-28T10:30:40.000Z

Python/Scheduling Algorithms/fcfs.py

shruti8301/Algorithms-Cheatsheet-Resources

cece012bba7f47c3a1ecfaff380dcbc787c26149

[ "MIT" ]

35

2020-06-08T17:59:22.000Z

2021-11-11T04:00:29.000Z

Python/Scheduling Algorithms/fcfs.py

shruti8301/Algorithms-Cheatsheet-Resources

cece012bba7f47c3a1ecfaff380dcbc787c26149

[ "MIT" ]

106

2020-02-05T01:28:19.000Z

2022-03-11T05:38:54.000Z

import numpy as np # Contains the method to calculate Standard Deviation def fcfs(process): case = int(input('Without Interrupt (1) or With Interrupt (2): ')) # If the relative arrival time is 0 this sort according to priority for i in range(1, len(process)): if process[i][1] == '0': if process[i][5] < process[i - 1][5]: j = i while process[j][5] < process[j - 1][5] and j >= 1: process[j], process[j - 1] = process[j - 1], process[j] j-=1 # Case for without interrupt if case == 1: print('Process\tTurnaround Time\t\tWaiting Time\tCompletion Time') print(process[0][0], "\t\t", int(process[0][2]) - int(process[0][1]), "\t\t\t", 0, "\t\t", int(process[0][2]) + int(process[0][1])) arrivalTime = 0 # Arrival Time of every process completionTime = int(process[0][2]) # Overall completion time turnAround = [int(process[0][2]) - int(process[0][1])] # Stores Turnaround time of every process waiting = [0] # Stores Waiting Time of every process for i in range(1, len(process)): arrivalTime += int(process[i][1]) # Arrival time of the current process completionTime = int(completionTime + max(0,int(process[i][1])- int(process[i-1][2]))+int(process[i][2])) # Completion time of the current process #totalCompletion += int(process[i][2]) # Total completion time till current process turnAroundTime = completionTime - arrivalTime # Turnaround Time of the current process turnAround.append(turnAroundTime) # Adding Turnaround time of the current process to the list waiting.append(max(0, turnAroundTime - int(process[i][2]))) # Adding waiting time of the current process to the list print(process[i][0], "\t\t", turnAroundTime, "\t\t\t", waiting[i], "\t\t", completionTime) print('Average Waiting Time : ', sum(waiting) / len(waiting)) # Printing average waiting time print('Standard Deviation of Turnaround Time : ', np.std(turnAround)) # Printing Standard Deviation of the Turnaround time # Case for with interrupt elif case == 2: print('Process\tTurnaround Time\t\tWaiting Time\tCompletion Time') print(process[0][0], "\t\t", int(process[0][2]) + float(process[0][3]) + float(process[0][4]) - int(process[0][1]), "\t\t\t", float(process[0][3]) + float(process[0][4]), "\t\t", int(process[0][2]) + float(process[0][3]) + float(process[0][4]) + int(process[0][1])) arrivalTime = 0 # Arrival Time of every process completionTime = int(process[0][2]) + float(process[0][3]) + float(process[0][4]) # Overall completion time turnAround = [int(process[0][2]) + float(process[0][3]) + float(process[0][4]) - int(process[0][1])] # Stores Turnaround time of every process waiting = [float(process[0][3]) + float(process[0][4])] # Stores Waiting Time of every process for i in range(1, len(process)): arrivalTime += int(process[i][1]) # Arrival time of the current process completionTime = float(completionTime + max(0,int(process[i][1])-int(process[i-1][2]) - float(process[i-1][3]) - float(process[i-1][4])) + float(process[i][2]) + float(process[i][3]) + float(process[i][4])) # Completion time of the current process turnAroundTime = completionTime - arrivalTime # Turnaround Time of the current process turnAround.append(turnAroundTime) # Adding Turnaroud time of the current process to the list waiting.append(max(0, turnAroundTime - (int(process[i][2])))) # Adding waiting tiem of the current process to the list print(process[i][0], "\t\t", turnAroundTime, "\t\t\t", waiting[i], "\t\t", completionTime) print('Average Waiting Time : ', sum(waiting) / len(waiting)) # Printing average waiting time print('Standard Deviation of Turnaround Time : ', np.std(turnAround)) # Printing Standard Deviation of the Turnaround time # Case for invalid input else: print('Invalid Input\nGive Valid input') fcfs(process)

63.2

267

0.638997

585

4,108

4.487179

0.135043

0.085333

0.058667

0.072381

0.80419

0.794286

0.770667

0.76

0.708952

0

0.032348

0.209834

4,108

64

268

64.1875

0.77634

0.282863

0

0.422222

0

0.127915

0

1

0.022222

false

0

0.022222

0

0.044444

0.244444

0

null

0

1

0

null

0

6

c7802d2e0f27b276f1669cd593e3c7d1676807a0

45

py

Python

flask_app/__init__.py

marilynwaldman/flask_gunicorn_nginx_docker

436999062ab7bdab5e40c0a0f403bb2d661dbb0b

[ "MIT" ]

null

flask_app/__init__.py

marilynwaldman/flask_gunicorn_nginx_docker

436999062ab7bdab5e40c0a0f403bb2d661dbb0b

[ "MIT" ]

null

flask_app/__init__.py

marilynwaldman/flask_gunicorn_nginx_docker

436999062ab7bdab5e40c0a0f403bb2d661dbb0b

[ "MIT" ]

null

from flask_app.app import app as application

22.5

44

0.844444

8

45

4.625

0.75

0

0.133333

45

1

45

0.948718

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

c78105f3662dbc3143bae9e8419fa4fc0eaa314b

121

py

Python

src/bnn_priors/bnn_priors/data/__init__.py

activatedgeek/uncertainty-da-bayesian-classification

a270fb095f4790dea15327145897d09d0ba9c80b

[ "Apache-2.0" ]

31

2021-02-16T09:35:03.000Z

2022-03-31T17:18:54.000Z

src/bnn_priors/bnn_priors/data/__init__.py

activatedgeek/understanding-bayesian-classification

a270fb095f4790dea15327145897d09d0ba9c80b

[ "Apache-2.0" ]

1

2021-05-10T15:25:48.000Z

src/bnn_priors/bnn_priors/data/__init__.py

activatedgeek/understanding-bayesian-classification

a270fb095f4790dea15327145897d09d0ba9c80b

[ "Apache-2.0" ]

4

2021-02-21T03:38:00.000Z

2021-12-24T15:13:29.000Z

from .base import * from .toy_data import * from .UCI.uci import * from .CIFAR.cifar import * from .MNIST.mnist import *

20.166667

26

0.727273

19

121

4.578947

0.421053

0.45977

0

0.165289

121

5

27

24.2

0.861386

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

c788cf890934902dfb5476d333aee52513e88347

45

py

Python

src/masonite/filesystem/providers/__init__.py

cercos/masonite

f7f220efa7fae833683e9f07ce13c3795a87d3b8

[ "MIT" ]

1,816

2018-02-14T01:59:51.000Z

2022-03-31T17:09:20.000Z

src/masonite/filesystem/providers/__init__.py

cercos/masonite

f7f220efa7fae833683e9f07ce13c3795a87d3b8

[ "MIT" ]

340

2018-02-11T00:27:26.000Z

2022-03-21T12:00:24.000Z

src/masonite/filesystem/providers/__init__.py

cercos/masonite

f7f220efa7fae833683e9f07ce13c3795a87d3b8

[ "MIT" ]

144

2018-03-18T00:08:16.000Z

2022-02-26T01:51:58.000Z

from .StorageProvider import StorageProvider

22.5

44

0.888889

4

45

10

0.75

0

0.088889

45

1

45

0.97561

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

c797a07eabae67dada4d060a32171070546a531f

7,967

py

Python

test_scripts/ns_instance/duan/service/vfc/nfvo/lcm/lcm/ns/tests/test_query_subscriptions.py

lremember/VFC

837559db1396091811382359100bfc60e1aab5b2

[ "MIT" ]

4

2018-08-29T02:51:38.000Z

2021-11-16T11:36:11.000Z

test_scripts/ns_instance/duan/service/vfc/nfvo/lcm/lcm/ns/tests/test_query_subscriptions.py

lremember/VFC-Files

837559db1396091811382359100bfc60e1aab5b2

[ "MIT" ]

null

test_scripts/ns_instance/duan/service/vfc/nfvo/lcm/lcm/ns/tests/test_query_subscriptions.py

lremember/VFC-Files

837559db1396091811382359100bfc60e1aab5b2

[ "MIT" ]

1

2019-05-12T08:21:19.000Z

# Copyright (c) 2019, CMCC Technologies Co., Ltd. # 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 json from django.test import TestCase from rest_framework import status from rest_framework.test import APIClient from lcm.pub.database.models import SubscriptionModel from lcm.ns.tests import SUBSCRIPTION_DICT class TestQuerySubscriptions(TestCase): def setUp(self): self.client = APIClient() self.test_single_subscription = SUBSCRIPTION_DICT.copy() self.subscription_id = "99442b18-a5c7-11e8-998c-bf1755941f16" self.ns_instance_id = "cd552c9c-ab6f-11e8-b354-236c32aa91a1" SubscriptionModel.objects.all().delete() def tearDown(self): pass def test_get_subscriptions(self): ns_instance_filter = { "nsdIds": [], "nsInstanceIds": [self.ns_instance_id], "nsInstanceNames": [] } links = { "self": { "href": "/api/v1/subscriptions/99442b18-a5c7-11e8-998c-bf1755941f16" } } SubscriptionModel( subscription_id=self.subscription_id, callback_uri="http://aurl.com", auth_info="{}", notification_types="['NsLcmOperationOccurrenceNotification']", operation_types="['INSTANTIATE']", operation_states="['STARTING']", links=json.dumps(links), ns_instance_filter=json.dumps(ns_instance_filter)).save() response = self.client.get("/api/nslcm/v1/subscriptions", format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual([self.test_single_subscription], response.data) def test_get_subscriptions_with_ns_instance_id(self): ns_instance_filter = { "nsdIds": [], "nsInstanceIds": [self.ns_instance_id], "nsInstanceNames": [] } links = { "self": { "href": "/api/v1/subscriptions/99442b18-a5c7-11e8-998c-bf1755941f16" } } SubscriptionModel( subscription_id=self.subscription_id, callback_uri="http://aurl.com", auth_info="{}", notification_types="['NsLcmOperationOccurrenceNotification']", operation_types="['INSTANTIATE']", operation_states="['STARTING']", links=json.dumps(links), ns_instance_filter=json.dumps(ns_instance_filter)).save() dummy_ns_id = "584b35e2-b2a2-11e8-8e11-645106374fd3" dummy_subscription_id = "947dcd2c-b2a2-11e8-b365-645106374fd4" ns_instance_filter["nsInstanceIds"].append(dummy_ns_id) SubscriptionModel( subscription_id=dummy_subscription_id, callback_uri="http://aurl.com", auth_info="{}", notification_types="['NsLcmOperationOccurrenceNotification']", operation_types="['INSTANTIATE']", operation_states="['STARTING']", links=json.dumps(links), ns_instance_filter=json.dumps(ns_instance_filter)).save() response = self.client.get("/api/nslcm/v1/subscriptions?nsInstanceId=" + dummy_ns_id, format='json') expected_response = self.test_single_subscription.copy() expected_response["id"] = dummy_subscription_id expected_response["filter"]["nsInstanceSubscriptionFilter"]["nsInstanceIds"] = ns_instance_filter["nsInstanceIds"] self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual([expected_response], response.data) def test_get_subscriptions_with_unknown_ns_instance_id(self): ns_instance_filter = { "nsdIds": [], "nsInstanceIds": [self.ns_instance_id], "nsInstanceNames": [] } links = { "self": { "href": "/api/v1/subscriptions/99442b18-a5c7-11e8-998c-bf1755941f16" } } SubscriptionModel( subscription_id=self.subscription_id, callback_uri="http://aurl.com", auth_info="{}", notification_types="['NsLcmOperationOccurrenceNotification']", operation_types="['INSTANTIATE']", operation_states="['STARTING']", links=json.dumps(links), ns_instance_filter=json.dumps(ns_instance_filter)).save() response = self.client.get("/api/nslcm/v1/subscriptions?nsInstanceId=dummy", format='json') self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual([], response.data) def test_get_subscriptions_with_invalid_filter(self): ns_instance_filter = { "nsdIds": [], "nsInstanceIds": [self.ns_instance_id], "nsInstanceNames": [] } links = { "self": { "href": "/api/v1/subscriptions/99442b18-a5c7-11e8-998c-bf1755941f16" } } SubscriptionModel( subscription_id=self.subscription_id, callback_uri="http://aurl.com", auth_info="{}", notification_types="['NsLcmOperationOccurrenceNotification']", operation_types="['INSTANTIATE']", operation_states="['STARTING']", links=json.dumps(links), ns_instance_filter=json.dumps(ns_instance_filter)).save() response = self.client.get("/api/nslcm/v1/subscriptions?dummy=dummy", format='json') self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST) def test_get_subscriptions_with_operation_type_filter(self): ns_instance_filter = { "nsdIds": [], "nsInstanceIds": [self.ns_instance_id], "nsInstanceNames": [] } links = { "self": { "href": "/api/v1/subscriptions/99442b18-a5c7-11e8-998c-bf1755941f16" } } SubscriptionModel( subscription_id=self.subscription_id, callback_uri="http://aurl.com", auth_info="{}", notification_types="['NsLcmOperationOccurrenceNotification']", operation_types="['INSTANTIATE']", operation_states="['STARTING']", links=json.dumps(links), ns_instance_filter=json.dumps(ns_instance_filter)).save() dummy_ns_id = "584b35e2-b2a2-11e8-8e11-645106374fd3" dummy_subscription_id = "947dcd2c-b2a2-11e8-b365-645106374fd4" ns_instance_filter["nsInstanceIds"].append(dummy_ns_id) SubscriptionModel( subscription_id=dummy_subscription_id, callback_uri="http://aurl.com", auth_info="{}", notification_types="['NsLcmOperationOccurrenceNotification']", operation_types="['SCALE']", operation_states="['STARTING']", links=json.dumps(links), ns_instance_filter=json.dumps(ns_instance_filter)).save() response = self.client.get("/api/nslcm/v1/subscriptions?operationTypes=SCALE", format='json') expected_response = self.test_single_subscription.copy() expected_response["id"] = dummy_subscription_id expected_response["filter"]["nsInstanceSubscriptionFilter"]["nsInstanceIds"] = ns_instance_filter["nsInstanceIds"] expected_response["filter"]["operationTypes"] = ["SCALE"] self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual([expected_response], response.data)

43.535519

122

0.635998

784

7,967

6.219388

0.205357

0.063577

0.075472

0.03589

0.788761

0.776661

0.755127

0

0.04788

0.245011

7,967

182

123

43.774725

0.76276

0.070918

0

0.71875

0

0.229198

0.141118

0

0.05625

1

0.04375

false

0.00625

0.0375

0

0.0875

0

null

0

1

0

1

0

null

0

6

c7b52d1f13da220694c9e0e412114a0299c924f5

90

py

Python

web/contact_us/services.py

bandirom/django-blog

a8232ee8e4b7380b0760296de865cca2c5feda87

[ "MIT" ]

1

2021-08-11T10:51:28.000Z

web/contact_us/services.py

bandirom/django-blog

a8232ee8e4b7380b0760296de865cca2c5feda87

[ "MIT" ]

null

web/contact_us/services.py

bandirom/django-blog

a8232ee8e4b7380b0760296de865cca2c5feda87

[ "MIT" ]

6

2021-04-07T17:03:52.000Z

2021-07-18T04:46:59.000Z

from django.conf import settings from . import models class ContactUsService: pass

11.25

32

0.766667

11

90

6.272727

0.818182

0

0.2

90

7

33

12.857143

0.958333

0

1

0

true

0.25

0.5

0

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

6

c7e614baccd29a900f233f0e786c61ad5948f74a

6,651

py

Python

tests/ipv6_link_local_test.py

chaoskao/sonic-utilities

47a9a0f56db95265c15c74c4c8dc6a3998bfd2d3

[ "Apache-2.0" ]

null

tests/ipv6_link_local_test.py

chaoskao/sonic-utilities

47a9a0f56db95265c15c74c4c8dc6a3998bfd2d3

[ "Apache-2.0" ]

4

2021-01-12T13:47:39.000Z

2021-09-22T16:38:18.000Z

tests/ipv6_link_local_test.py

chaoskao/sonic-utilities

47a9a0f56db95265c15c74c4c8dc6a3998bfd2d3

[ "Apache-2.0" ]

null

import os from click.testing import CliRunner import config.main as config import show.main as show from utilities_common.db import Db show_ipv6_link_local_mode_output="""\ +------------------+----------+ | Interface Name | Mode | +==================+==========+ | Ethernet0 | Disabled | +------------------+----------+ | PortChannel0001 | Disabled | +------------------+----------+ """ class TestIPv6LinkLocal(object): @classmethod def setup_class(cls): os.environ['UTILITIES_UNIT_TESTING'] = "1" print("SETUP") def test_show_ipv6_link_local_mode(self): runner = CliRunner() db = Db() obj = {'db':db.cfgdb} # show ipv6 link-local-mode output result = runner.invoke(show.cli.commands["ipv6"].commands["link-local-mode"], [], obj=obj) print(result.output) assert result.output == show_ipv6_link_local_mode_output def test_config_enable_disable_ipv6_link_local_on_physical_interface(self): runner = CliRunner() db = Db() obj = {'db':db.cfgdb} # Enable ipv6 link local on Ethernet0 result = runner.invoke(config.config.commands["interface"].commands["ipv6"].commands["enable"].commands["use-link-local-only"], ["Ethernet0"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code == 0 assert result.output == '' # Disable ipv6 link local on Ethernet0 result = runner.invoke(config.config.commands["interface"].commands["ipv6"].commands["disable"].commands["use-link-local-only"], ["Ethernet0"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code == 0 assert result.output == '' def test_config_enable_disable_ipv6_link_local_on_portchannel_interface(self): runner = CliRunner() db = Db() obj = {'db':db.cfgdb} # Enable ipv6 link local on PortChannel0001 result = runner.invoke(config.config.commands["interface"].commands["ipv6"].commands["enable"].commands["use-link-local-only"], ["PortChannel0001"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code == 0 assert result.output == '' # Disable ipv6 link local on PortChannel0001 result = runner.invoke(config.config.commands["interface"].commands["ipv6"].commands["disable"].commands["use-link-local-only"], ["PortChannel0001"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code == 0 assert result.output == '' def test_config_enable_disable_ipv6_link_local_on_invalid_interface(self): runner = CliRunner() db = Db() obj = {'db':db.cfgdb} # Enable ipv6 link local on PortChannel1 result = runner.invoke(config.config.commands["interface"].commands["ipv6"].commands["enable"].commands["use-link-local-only"], ["PortChannel1"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code != 0 assert 'Error: Interface name PortChannel1 is invalid. Please enter a valid interface name!!' in result.output # Disable ipv6 link local on Ethernet500 result = runner.invoke(config.config.commands["interface"].commands["ipv6"].commands["disable"].commands["use-link-local-only"], ["Ethernet500"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code != 0 assert 'Error: Interface name Ethernet500 is invalid. Please enter a valid interface name!!' in result.output def test_config_enable_disable_ipv6_link_local_on_interface_which_is_member_of_vlan(self): runner = CliRunner() db = Db() obj = {'db':db.cfgdb} # Enable ipv6 link local on Ethernet16 result = runner.invoke(config.config.commands["interface"].commands["ipv6"].commands["enable"].commands["use-link-local-only"], ["Ethernet16"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code != 0 assert 'Error: Ethernet16 is configured as a member of vlan. Cannot configure the IPv6 link local mode!' in result.output # Disable ipv6 link local on Ethernet16 result = runner.invoke(config.config.commands["interface"].commands["ipv6"].commands["disable"].commands["use-link-local-only"], ["Ethernet16"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code != 0 assert 'Error: Ethernet16 is configured as a member of vlan. Cannot configure the IPv6 link local mode!' in result.output def test_config_enable_disable_ipv6_link_local_on_interface_which_is_member_of_portchannel(self): runner = CliRunner() db = Db() obj = {'db':db.cfgdb} # Enable ipv6 link local on Ethernet32 result = runner.invoke(config.config.commands["interface"].commands["ipv6"].commands["enable"].commands["use-link-local-only"], ["Ethernet32"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code != 0 assert 'Error: Ethernet32 is configured as a member of portchannel. Cannot configure the IPv6 link local mode!' in result.output # Disable ipv6 link local on Ethernet32 result = runner.invoke(config.config.commands["interface"].commands["ipv6"].commands["disable"].commands["use-link-local-only"], ["Ethernet32"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code != 0 assert 'Error: Ethernet32 is configured as a member of portchannel. Cannot configure the IPv6 link local mode!' in result.output def test_config_enable_disable_ipv6_link_local_on_all_valid_interfaces(self): runner = CliRunner() db = Db() obj = {'db':db.cfgdb} # Enable ipv6 link local on all interfaces result = runner.invoke(config.config.commands["ipv6"].commands["enable"].commands["link-local"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code == 0 assert result.output == '' # Disable ipv6 link local on all interfaces result = runner.invoke(config.config.commands["ipv6"].commands["disable"].commands["link-local"], obj=obj) print(result.exit_code) print(result.output) assert result.exit_code == 0 assert result.output == '' @classmethod def teardown_class(cls): os.environ['UTILITIES_UNIT_TESTING'] = "0" print("TEARDOWN")

43.188312

166

0.654037

807

6,651

5.255266

0.095415

0.082764

0.079698

0.063664

0.890356

0.875501

0.857109

0.83966

0.834473

0.82622

0

0.021876

0.209593

6,651

153

167

43.470588

0.784858

0.075327

0

0.640351

0

0.230807

0.027384

0

0.219298

1

0.078947

false

0

0.04386

0

0.131579

0.236842

0

null

0

1

0

null

0

6

c7f3f608261b139cd2922e3fcb6e19465abeab4a

74

py

Python

rnaindel/__init__.py

rawagiha/RNAIndel

ad0aa6f7dcb36b11e6159b9533aadd3240bb3916

[ "Apache-2.0" ]

21

2019-01-03T22:23:11.000Z

2021-09-05T14:45:14.000Z

rnaindel/__init__.py

rawagiha/RNAIndel

ad0aa6f7dcb36b11e6159b9533aadd3240bb3916

[ "Apache-2.0" ]

7

2019-01-04T23:19:39.000Z

2021-11-03T00:26:54.000Z

rnaindel/__init__.py

rawagiha/RNAIndel

ad0aa6f7dcb36b11e6159b9533aadd3240bb3916

[ "Apache-2.0" ]

9

2019-01-22T19:31:08.000Z

2021-06-28T05:52:57.000Z

from .analysis import * from .occurrence import * from .training import *

18.5

25

0.756757

9

74

6.222222

0.555556

0.357143

0

0.162162

74

3

26

24.666667

0.903226

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

4039ed954a2e2631a3213466e57563133c1ba340

21,813

py

Python

pipe/network/sample_pyramid_add_kpn_FiveLevel.py

dong1015323606/tof_mpi_remove

11ecac5db4b30affbb1785ac01397e7aa53f22cf

[ "MIT" ]

6

2020-08-24T02:03:56.000Z

2021-12-10T02:39:41.000Z

pipe/network/sample_pyramid_add_kpn_FiveLevel.py

dong1015323606/tof_mpi_remove

11ecac5db4b30affbb1785ac01397e7aa53f22cf

[ "MIT" ]

1

2020-10-16T02:15:36.000Z

2021-06-05T02:25:36.000Z

pipe/network/sample_pyramid_add_kpn_FiveLevel.py

dong1015323606/tof_mpi_remove

11ecac5db4b30affbb1785ac01397e7aa53f22cf

[ "MIT" ]

6

2020-09-25T12:20:44.000Z

2021-11-25T03:13:36.000Z

import sys sys.path.insert(0, './module/') import tensorflow as tf from dataset import * from activation import * from conv import conv from dfus_block import dfus_block tf.logging.set_verbosity(tf.logging.INFO) PI = 3.14159265358979323846 flg = False dtype = tf.float32 def feature_extractor_subnet(x, flg, regular): """Build a U-Net architecture""" """ Args: x is the input, 4-D tensor (BxHxWxC) flg represent weather add the BN regular represent the regularizer number Return: output is 4-D Tensor (BxHxWxC) """ pref = 'feature_extractor_subnet_' # whether to train flag train_ae = flg # define initializer for the network keys = ['conv', 'upsample'] keys_avoid = ['OptimizeLoss'] inits = [] init_net = None if init_net != None: for name in init_net.get_variable_names(): # select certain variables flag_init = False for key in keys: if key in name: flag_init = True for key in keys_avoid: if key in name: flag_init = False if flag_init: name_f = name.replace('/', '_') num = str(init_net.get_variable_value(name).tolist()) # self define the initializer function from tensorflow.python.framework import dtypes from tensorflow.python.ops.init_ops import Initializer exec( "class " + name_f + "(Initializer):\n def __init__(self,dtype=tf.float32): self.dtype=dtype \n def __call__(self,shape,dtype=None,partition_info=None): return tf.cast(np.array(" + num + "),dtype=self.dtype)\n def get_config(self):return {\"dtype\": self.dtype.name}") inits.append(name_f) # autoencoder n_filters = [ 16, 16, 32, 32, 96, 96, 128, 128, 256, 256, ] filter_sizes = [ 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ] pool_sizes = [ \ 1, 1, 2, 1, 2, 1, 2, 1, 2, 1, ] pool_strides = [ 1, 1, 2, 1, 2, 1, 2, 1, 2, 1, ] skips = [ \ False, False, True, False, True, False, True, False, True, False, ] # change space ae_inputs = tf.identity(x, name='ae_inputs') # prepare input current_input = tf.identity(ae_inputs, name="input") #################################################################################################################### # convolutional layers: feature extractor features = [] for i in range(0, len(n_filters)): name = pref + "conv_" + str(i) # define the initializer if name + '_bias' in inits: bias_init = eval(name + '_bias()') else: bias_init = tf.zeros_initializer() if name + '_kernel' in inits: kernel_init = eval(name + '_kernel()') else: kernel_init = None # convolution current_input = tf.layers.conv2d( inputs=current_input, filters=n_filters[i], kernel_size=[filter_sizes[i], filter_sizes[i]], padding="same", activation=relu, trainable=train_ae, kernel_initializer=kernel_init, bias_initializer=bias_init, name=name, ) if pool_sizes[i] == 1 and pool_strides[i] == 1: current_input = current_input if (i == len(n_filters) - 1) or (pool_sizes[i + 1] == 2 and pool_strides[i + 1] == 2): features.append(current_input) else: current_input = tf.layers.max_pooling2d( \ inputs=current_input, pool_size=[pool_sizes[i], pool_sizes[i]], strides=pool_strides[i], name=pref + "pool_" + str(i) ) return features def depth_residual_regresssion_subnet(x, flg, regular, subnet_num): """Build a U-Net architecture""" """ Args: x is the input, 4-D tensor (BxHxWxC) flg represent weather add the BN regular represent the regularizer number Return: output is 4-D Tensor (BxHxWxC) """ pref = 'depth_regression_subnet_' + str(subnet_num) + '_' # whether to train flag train_ae = flg # define initializer for the network keys = ['conv', 'upsample'] keys_avoid = ['OptimizeLoss'] inits = [] init_net = None if init_net != None: for name in init_net.get_variable_names(): # select certain variables flag_init = False for key in keys: if key in name: flag_init = True for key in keys_avoid: if key in name: flag_init = False if flag_init: name_f = name.replace('/', '_') num = str(init_net.get_variable_value(name).tolist()) # self define the initializer function from tensorflow.python.framework import dtypes from tensorflow.python.ops.init_ops import Initializer exec( "class " + name_f + "(Initializer):\n def __init__(self,dtype=tf.float32): self.dtype=dtype \n def __call__(self,shape,dtype=None,partition_info=None): return tf.cast(np.array(" + num + "),dtype=self.dtype)\n def get_config(self):return {\"dtype\": self.dtype.name}") inits.append(name_f) # autoencoder n_filters = [ 128, 96, 64, 32, 16, 1, ] filter_sizes = [ 3, 3, 3, 3, 3, 3, ] pool_sizes = [ \ 1, 1, 1, 1, 1, 1, ] pool_strides = [ 1, 1, 1, 1, 1, 1, ] skips = [ \ False, False, False, False, False, False, ] # change space ae_inputs = tf.identity(x, name='ae_inputs') # prepare input current_input = tf.identity(ae_inputs, name="input") #################################################################################################################### # convolutional layers: depth regression feature = [] for i in range(0, len(n_filters)): name = pref + "conv_" + str(i) # define the initializer if name + '_bias' in inits: bias_init = eval(name + '_bias()') else: bias_init = tf.zeros_initializer() if name + '_kernel' in inits: kernel_init = eval(name + '_kernel()') else: kernel_init = None if i == (len(n_filters) - 1): activation = None else: activation = relu # convolution current_input = tf.layers.conv2d( inputs=current_input, filters=n_filters[i], kernel_size=[filter_sizes[i], filter_sizes[i]], padding="same", activation=activation, trainable=train_ae, kernel_initializer=kernel_init, bias_initializer=bias_init, name=name, ) if pool_sizes[i] == 1 and pool_strides[i] == 1: feature.append(current_input) else: feature.append( tf.layers.max_pooling2d( \ inputs=current_input, pool_size=[pool_sizes[i], pool_sizes[i]], strides=pool_strides[i], name=pref + "pool_" + str(i) ) ) current_input = feature[-1] depth_coarse = tf.identity(feature[-1], name='depth_coarse_output') return depth_coarse def residual_output_subnet(x, flg, regular, subnet_num): """Build a U-Net architecture""" """ Args: x is the input, 4-D tensor (BxHxWxC) flg represent weather add the BN regular represent the regularizer number Return: output is 4-D Tensor (BxHxWxC) """ pref = 'residual_output_subnet_' + str(subnet_num) + '_' # whether to train flag train_ae = flg # define initializer for the network keys = ['conv', 'upsample'] keys_avoid = ['OptimizeLoss'] inits = [] init_net = None if init_net != None: for name in init_net.get_variable_names(): # select certain variables flag_init = False for key in keys: if key in name: flag_init = True for key in keys_avoid: if key in name: flag_init = False if flag_init: name_f = name.replace('/', '_') num = str(init_net.get_variable_value(name).tolist()) # self define the initializer function from tensorflow.python.framework import dtypes from tensorflow.python.ops.init_ops import Initializer exec( "class " + name_f + "(Initializer):\n def __init__(self,dtype=tf.float32): self.dtype=dtype \n def __call__(self,shape,dtype=None,partition_info=None): return tf.cast(np.array(" + num + "),dtype=self.dtype)\n def get_config(self):return {\"dtype\": self.dtype.name}") inits.append(name_f) # autoencoder n_filters = [ 1 ] filter_sizes = [ 1 ] pool_sizes = [ \ 1 ] pool_strides = [ 1 ] skips = [ \ False ] # change space ae_inputs = tf.identity(x, name='ae_inputs') # prepare input current_input = tf.identity(ae_inputs, name="input") #################################################################################################################### # convolutional layers: depth regression feature = [] for i in range(0, len(n_filters)): name = pref + "conv_" + str(i) # define the initializer if name + '_bias' in inits: bias_init = eval(name + '_bias()') else: bias_init = tf.zeros_initializer() if name + '_kernel' in inits: kernel_init = eval(name + '_kernel()') else: kernel_init = None if i == (len(n_filters) - 1): activation = None else: activation = relu # convolution current_input = tf.layers.conv2d( inputs=current_input, filters=n_filters[i], kernel_size=[filter_sizes[i], filter_sizes[i]], padding="same", activation=activation, trainable=train_ae, kernel_initializer=kernel_init, bias_initializer=bias_init, name=name, ) if pool_sizes[i] == 1 and pool_strides[i] == 1: feature.append(current_input) else: feature.append( tf.layers.max_pooling2d( \ inputs=current_input, pool_size=[pool_sizes[i], pool_sizes[i]], strides=pool_strides[i], name=pref + "pool_" + str(i) ) ) current_input = feature[-1] depth_residual_coarse = tf.identity(feature[-1], name='depth_coarse_residual_output') return depth_residual_coarse def unet_subnet(x, flg, regular): """Build a U-Net architecture""" """ Args: x is the input, 4-D tensor (BxHxWxC) flg represent weather add the BN regular represent the regularizer number Return: output is 4-D Tensor (BxHxWxC) """ pref = 'unet_subnet_' # whether to train flag train_ae = flg # define initializer for the network keys = ['conv', 'upsample'] keys_avoid = ['OptimizeLoss'] inits = [] init_net = None if init_net != None: for name in init_net.get_variable_names(): # select certain variables flag_init = False for key in keys: if key in name: flag_init = True for key in keys_avoid: if key in name: flag_init = False if flag_init: name_f = name.replace('/', '_') num = str(init_net.get_variable_value(name).tolist()) # self define the initializer function from tensorflow.python.framework import dtypes from tensorflow.python.ops.init_ops import Initializer exec( "class " + name_f + "(Initializer):\n def __init__(self,dtype=tf.float32): self.dtype=dtype \n def __call__(self,shape,dtype=None,partition_info=None): return tf.cast(np.array(" + num + "),dtype=self.dtype)\n def get_config(self):return {\"dtype\": self.dtype.name}") inits.append(name_f) # autoencoder n_filters = [ 16, 16, 32, 32, 64, 64, 128, 128, ] filter_sizes = [ 3, 3, 3, 3, 3, 3, 3, 3, ] pool_sizes = [ \ 1, 1, 2, 1, 2, 1, 2, 1, ] pool_strides = [ 1, 1, 2, 1, 2, 1, 2, 1, ] skips = [ \ False, False, True, False, True, False, True, False, ] # change space ae_inputs = tf.identity(x, name='ae_inputs') # prepare input current_input = tf.identity(ae_inputs, name="input") #################################################################################################################### # convolutional layers: encoder conv = [] pool = [current_input] for i in range(0, len(n_filters)): name = pref + "conv_" + str(i) # define the initializer if name + '_bias' in inits: bias_init = eval(name + '_bias()') else: bias_init = tf.zeros_initializer() if name + '_kernel' in inits: kernel_init = eval(name + '_kernel()') else: kernel_init = None # convolution conv.append( \ tf.layers.conv2d( \ inputs=current_input, filters=n_filters[i], kernel_size=[filter_sizes[i], filter_sizes[i]], padding="same", activation=relu, trainable=train_ae, kernel_initializer=kernel_init, bias_initializer=bias_init, name=name, ) ) if pool_sizes[i] == 1 and pool_strides[i] == 1: pool.append(conv[-1]) else: pool.append( \ tf.layers.max_pooling2d( \ inputs=conv[-1], pool_size=[pool_sizes[i], pool_sizes[i]], strides=pool_strides[i], name=pref + "pool_" + str(i) ) ) current_input = pool[-1] #################################################################################################################### # convolutional layer: decoder # upsampling upsamp = [] current_input = pool[-1] for i in range((len(n_filters) - 1) - 1, 0, -1): name = pref + "upsample_" + str(i) # define the initializer if name + '_bias' in inits: bias_init = eval(name + '_bias()') else: bias_init = tf.zeros_initializer() if name + '_kernel' in inits: kernel_init = eval(name + '_kernel()') else: kernel_init = None ## change the kernel size in upsample process if skips[i] == False and skips[i + 1] == True: filter_sizes[i] = 4 # upsampling current_input = tf.layers.conv2d_transpose( \ inputs=current_input, filters=n_filters[i], kernel_size=[filter_sizes[i], filter_sizes[i]], strides=(pool_strides[i], pool_strides[i]), padding="same", activation=relu, trainable=train_ae, kernel_initializer=kernel_init, bias_initializer=bias_init, name=name ) upsamp.append(current_input) # current_input = tf.layers.batch_normalization( # inputs=current_input, # training=train_ae, # name=pref + "upsamp_BN_" + str(i)) # skip connection if skips[i] == False and skips[i - 1] == True: current_input = tf.concat([current_input, pool[i + 1]], axis=-1) #################################################################################################################### features = tf.identity(upsamp[-1], name='ae_output') return features def depth_output_subnet(inputs, flg, regular, kernel_size): ## x (B,H,W,1), features:(B,H,W,64), samples:(B,H,W,9) pref = 'depth_output_subnet_' # whether to train flag train_ae = flg current_input = inputs # define initializer for the network keys = ['conv', 'upsample'] keys_avoid = ['OptimizeLoss'] inits = [] init_net = None if init_net != None: for name in init_net.get_variable_names(): # select certain variables flag_init = False for key in keys: if key in name: flag_init = True for key in keys_avoid: if key in name: flag_init = False if flag_init: name_f = name.replace('/', '_') num = str(init_net.get_variable_value(name).tolist()) # self define the initializer function from tensorflow.python.framework import dtypes from tensorflow.python.ops.init_ops import Initializer exec( "class " + name_f + "(Initializer):\n def __init__(self,dtype=tf.float32): self.dtype=dtype \n def __call__(self,shape,dtype=None,partition_info=None): return tf.cast(np.array(" + num + "),dtype=self.dtype)\n def get_config(self):return {\"dtype\": self.dtype.name}") inits.append(name_f) n_filters_mix = [kernel_size ** 2] filter_sizes_mix = [1] mix = [] for i in range(len(n_filters_mix)): name = pref + "conv_" + str(i) # define the initializer if name + '_bias' in inits: bias_init = eval(name + '_bias()') else: bias_init = tf.zeros_initializer() if name + '_kernel' in inits: kernel_init = eval(name + '_kernel()') else: kernel_init = None if i == (len(n_filters_mix) - 1): activation = sigmoid else: activation = relu # convolution mix.append( \ tf.layers.conv2d( \ inputs=current_input, filters=n_filters_mix[i], kernel_size=[filter_sizes_mix[i], filter_sizes_mix[i]], padding="same", activation=activation, trainable=train_ae, kernel_initializer=kernel_init, bias_initializer=bias_init, name=name, ) ) current_input = mix[-1] return current_input def dear_kpn(x, flg, regular): kernel_size = 3 features = unet_subnet(x, flg, regular) weights = depth_output_subnet(features, flg, regular, kernel_size=kernel_size) weights = weights / tf.reduce_sum(tf.abs(weights) + 1e-6, axis=-1, keep_dims=True) column = im2col(x, kernel_size=kernel_size) current_output = tf.reduce_sum(column * weights, axis=-1, keep_dims=True) depth_output = tf.identity(current_output, name='depth_output') return depth_output def sample_pyramid_add_kpn_FiveLevel(x, flg, regular, batch_size, deformable_range): depth_residual = [] depth_residual_input = [] h_max = tf.shape(x)[1] w_max = tf.shape(x)[2] depth = tf.expand_dims(x[:, :, :, 0], axis=-1) depth_and_amplitude = x[:, :, :, 0:2] rgb = x[:, :, :, 2:5] features = feature_extractor_subnet(depth_and_amplitude, flg, regular) for i in range(1, len(features) + 1): if i == 1: inputs = features[len(features) - i] else: feature_input = features[len(features) - i] h_max_low_scale = tf.shape(feature_input)[1] w_max_low_scale = tf.shape(feature_input)[2] depth_coarse_input = tf.image.resize_bicubic(depth_residual[-1], size=(h_max_low_scale, w_max_low_scale), align_corners=True) inputs = tf.concat([feature_input, depth_coarse_input], axis=-1) current_depth_residual = depth_residual_regresssion_subnet(inputs, flg, regular, subnet_num=i) depth_residual.append(current_depth_residual) current_depth_residual_input = tf.image.resize_bicubic(current_depth_residual, size=(h_max, w_max), align_corners=True) depth_residual_input.append(current_depth_residual_input) depth_coarse_residual_input = tf.concat(depth_residual_input, axis=-1) final_depth_residual_output = residual_output_subnet(depth_coarse_residual_input, flg, regular, subnet_num=0) current_final_depth_output = depth + final_depth_residual_output final_depth_output = dear_kpn(current_final_depth_output, flg, regular) depth_residual_input.append(final_depth_residual_output) depth_residual_input.append(final_depth_output - current_final_depth_output) depth_residual_input.append(final_depth_output - current_final_depth_output) return final_depth_output, depth_residual_input

32.950151

287

0.530922

2,465

21,813

4.468154

0.081947

0.039223

0.004903

0.005448

0.774106

0.752588

0.739513

0.730071

0.718903

0.714

0

0.0173

0.337505

21,813

662

288

32.950151

0.744862

0.068858

0

0.716

0

0.01

0.094587

0.039545

0

1

0.014

false

0

0.032

0

0.06

0

null

0

1

0

1

0

null

0

6

405405ae573fe34cf3428fd70f217e8ee0e5589d

224,844

py

Python

manila/tests/share/test_manager.py

deiter/manila

ba94d20e823d2edad7e9bd01546cf1642b17d212

[ "Apache-2.0" ]

1

2019-05-06T10:33:38.000Z

manila/tests/share/test_manager.py

deiter/manila

ba94d20e823d2edad7e9bd01546cf1642b17d212

[ "Apache-2.0" ]

4

2019-05-06T11:45:17.000Z

2019-05-09T14:23:28.000Z

manila/tests/share/test_manager.py

deiter/manila

ba94d20e823d2edad7e9bd01546cf1642b17d212

[ "Apache-2.0" ]

3

2019-05-03T12:32:47.000Z

2021-01-30T20:26:19.000Z

# Copyright 2014 Mirantis Inc. # 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. """Test of Share Manager for Manila.""" import datetime import random import ddt import mock from oslo_concurrency import lockutils from oslo_serialization import jsonutils from oslo_utils import importutils from oslo_utils import timeutils import six from manila.common import constants from manila import context from manila.data import rpcapi as data_rpc from manila import db from manila.db.sqlalchemy import models from manila import exception from manila import quota from manila.share import access as share_access from manila.share import drivers_private_data from manila.share import manager from manila.share import migration as migration_api from manila.share import rpcapi from manila.share import share_types from manila import test from manila.tests.api import fakes as test_fakes from manila.tests import db_utils from manila.tests import fake_share as fakes from manila.tests import fake_utils from manila.tests import utils as test_utils from manila import utils def fake_replica(**kwargs): return fakes.fake_replica(for_manager=True, **kwargs) class LockedOperationsTestCase(test.TestCase): class FakeManager(object): @manager.locked_share_replica_operation def fake_replica_operation(self, context, replica, share_id=None): pass def setUp(self): super(self.__class__, self).setUp() self.manager = self.FakeManager() self.fake_context = test_fakes.FakeRequestContext self.lock_call = self.mock_object( utils, 'synchronized', mock.Mock(return_value=lambda f: f)) @ddt.data({'id': 'FAKE_REPLICA_ID'}, 'FAKE_REPLICA_ID') @ddt.unpack def test_locked_share_replica_operation(self, **replica): self.manager.fake_replica_operation(self.fake_context, replica, share_id='FAKE_SHARE_ID') self.assertTrue(self.lock_call.called) @ddt.ddt class ShareManagerTestCase(test.TestCase): def setUp(self): super(ShareManagerTestCase, self).setUp() self.flags(share_driver='manila.tests.fake_driver.FakeShareDriver') # Define class directly, because this test suite dedicated # to specific manager. self.share_manager = importutils.import_object( "manila.share.manager.ShareManager") self.mock_object(self.share_manager.driver, 'do_setup') self.mock_object(self.share_manager.driver, 'check_for_setup_error') self.context = context.get_admin_context() self.share_manager.driver.initialized = True mock.patch.object( lockutils, 'lock', fake_utils.get_fake_lock_context()) self.synchronized_lock_decorator_call = self.mock_object( utils, 'synchronized', mock.Mock(return_value=lambda f: f)) def test_share_manager_instance(self): fake_service_name = "fake_service" import_mock = mock.Mock() self.mock_object(importutils, "import_object", import_mock) private_data_mock = mock.Mock() self.mock_object(drivers_private_data, "DriverPrivateData", private_data_mock) self.mock_object(manager.ShareManager, '_init_hook_drivers') share_manager = manager.ShareManager(service_name=fake_service_name) private_data_mock.assert_called_once_with( context=mock.ANY, backend_host=share_manager.host, config_group=fake_service_name ) self.assertTrue(import_mock.called) self.assertTrue(manager.ShareManager._init_hook_drivers.called) def test__init_hook_drivers(self): fake_service_name = "fake_service" import_mock = mock.Mock() self.mock_object(importutils, "import_object", import_mock) self.mock_object(drivers_private_data, "DriverPrivateData") share_manager = manager.ShareManager(service_name=fake_service_name) share_manager.configuration.safe_get = mock.Mock( return_value=["Foo", "Bar"]) self.assertEqual(0, len(share_manager.hooks)) import_mock.reset() share_manager._init_hook_drivers() self.assertEqual( len(share_manager.configuration.safe_get.return_value), len(share_manager.hooks)) import_mock.assert_has_calls([ mock.call( hook, configuration=share_manager.configuration, host=share_manager.host ) for hook in share_manager.configuration.safe_get.return_value ], any_order=True) def test__execute_periodic_hook(self): share_instances_mock = mock.Mock() hook_data_mock = mock.Mock() self.mock_object( self.share_manager.db, "share_instances_get_all_by_host", share_instances_mock) self.mock_object( self.share_manager.driver, "get_periodic_hook_data", hook_data_mock) self.share_manager.hooks = [mock.Mock(return_value=i) for i in (0, 1)] self.share_manager._execute_periodic_hook(self.context) share_instances_mock.assert_called_once_with( context=self.context, host=self.share_manager.host) hook_data_mock.assert_called_once_with( context=self.context, share_instances=share_instances_mock.return_value) for mock_hook in self.share_manager.hooks: mock_hook.execute_periodic_hook.assert_called_once_with( context=self.context, periodic_hook_data=hook_data_mock.return_value) def test_init_host_with_no_shares(self): self.mock_object(self.share_manager.db, 'share_instances_get_all_by_host', mock.Mock(return_value=[])) self.share_manager.init_host() self.assertTrue(self.share_manager.driver.initialized) self.share_manager.db.share_instances_get_all_by_host.\ assert_called_once_with(utils.IsAMatcher(context.RequestContext), self.share_manager.host) self.share_manager.driver.do_setup.assert_called_once_with( utils.IsAMatcher(context.RequestContext)) self.share_manager.driver.check_for_setup_error.\ assert_called_once_with() @ddt.data( "migration_get_driver_info", "migration_get_info", "migration_cancel", "migration_get_progress", "migration_complete", "migration_start", "create_share_instance", "manage_share", "unmanage_share", "delete_share_instance", "delete_free_share_servers", "create_snapshot", "delete_snapshot", "allow_access", "deny_access", "_report_driver_status", "_execute_periodic_hook", "publish_service_capabilities", "delete_share_server", "extend_share", "shrink_share", "create_consistency_group", "delete_consistency_group", "create_cgsnapshot", "delete_cgsnapshot", "create_share_replica", "delete_share_replica", "promote_share_replica", "periodic_share_replica_update", "update_share_replica", "create_replicated_snapshot", "delete_replicated_snapshot", "periodic_share_replica_snapshot_update", ) def test_call_driver_when_its_init_failed(self, method_name): self.mock_object(self.share_manager.driver, 'do_setup', mock.Mock(side_effect=Exception())) self.share_manager.init_host() self.assertRaises( exception.DriverNotInitialized, getattr(self.share_manager, method_name), 'foo', 'bar', 'quuz' ) @ddt.data("do_setup", "check_for_setup_error") def test_init_host_with_driver_failure(self, method_name): self.mock_object(self.share_manager.driver, method_name, mock.Mock(side_effect=Exception())) self.mock_object(manager.LOG, 'exception') self.share_manager.driver.initialized = False self.share_manager.init_host() manager.LOG.exception.assert_called_once_with( mock.ANY, {'name': self.share_manager.driver.__class__.__name__, 'host': self.share_manager.host, 'exc': mock.ANY}) self.assertFalse(self.share_manager.driver.initialized) def _setup_init_mocks(self, setup_access_rules=True): instances = [ db_utils.create_share(id='fake_id_1', status=constants.STATUS_AVAILABLE, display_name='fake_name_1').instance, db_utils.create_share(id='fake_id_2', status=constants.STATUS_ERROR, display_name='fake_name_2').instance, db_utils.create_share(id='fake_id_3', status=constants.STATUS_AVAILABLE, display_name='fake_name_3').instance, db_utils.create_share( id='fake_id_4', status=constants.STATUS_AVAILABLE, task_state=constants.TASK_STATE_MIGRATION_IN_PROGRESS, display_name='fake_name_4').instance, db_utils.create_share(id='fake_id_5', status=constants.STATUS_AVAILABLE, display_name='fake_name_5').instance, ] instances[4]['access_rules_status'] = constants.STATUS_OUT_OF_SYNC if not setup_access_rules: return instances rules = [ db_utils.create_access(share_id='fake_id_1'), db_utils.create_access(share_id='fake_id_3'), ] return instances, rules def test_init_host_with_shares_and_rules(self): # initialization of test data def raise_share_access_exists(*args, **kwargs): raise exception.ShareAccessExists( access_type='fake_access_type', access='fake_access') instances, rules = self._setup_init_mocks() fake_export_locations = ['fake/path/1', 'fake/path'] share_server = 'fake_share_server_type_does_not_matter' self.mock_object(self.share_manager.db, 'share_instances_get_all_by_host', mock.Mock(return_value=instances)) self.mock_object(self.share_manager.db, 'share_instance_get', mock.Mock(side_effect=[instances[0], instances[2], instances[4]])) self.mock_object(self.share_manager.db, 'share_export_locations_update') self.mock_object(self.share_manager.driver, 'ensure_share', mock.Mock(return_value=fake_export_locations)) self.mock_object(self.share_manager, '_ensure_share_instance_has_pool') self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=share_server)) self.mock_object(self.share_manager, 'publish_service_capabilities', mock.Mock()) self.mock_object(self.share_manager.db, 'share_access_get_all_for_share', mock.Mock(return_value=rules)) self.mock_object( self.share_manager.access_helper, 'update_access_rules', mock.Mock(side_effect=raise_share_access_exists) ) # call of 'init_host' method self.share_manager.init_host() # verification of call self.share_manager.db.share_instances_get_all_by_host.\ assert_called_once_with(utils.IsAMatcher(context.RequestContext), self.share_manager.host) exports_update = self.share_manager.db.share_export_locations_update exports_update.assert_has_calls([ mock.call(mock.ANY, instances[0]['id'], fake_export_locations), mock.call(mock.ANY, instances[2]['id'], fake_export_locations) ]) self.share_manager.driver.do_setup.assert_called_once_with( utils.IsAMatcher(context.RequestContext)) self.share_manager.driver.check_for_setup_error.\ assert_called_once_with() self.share_manager._ensure_share_instance_has_pool.assert_has_calls([ mock.call(utils.IsAMatcher(context.RequestContext), instances[0]), mock.call(utils.IsAMatcher(context.RequestContext), instances[2]), ]) self.share_manager._get_share_server.assert_has_calls([ mock.call(utils.IsAMatcher(context.RequestContext), instances[0]), mock.call(utils.IsAMatcher(context.RequestContext), instances[2]), ]) self.share_manager.driver.ensure_share.assert_has_calls([ mock.call(utils.IsAMatcher(context.RequestContext), instances[0], share_server=share_server), mock.call(utils.IsAMatcher(context.RequestContext), instances[2], share_server=share_server), ]) self.share_manager.publish_service_capabilities.\ assert_called_once_with( utils.IsAMatcher(context.RequestContext)) self.share_manager.access_helper.update_access_rules.assert_has_calls([ mock.call(mock.ANY, instances[4]['id'], share_server=share_server), ]) def test_init_host_with_exception_on_ensure_share(self): def raise_exception(*args, **kwargs): raise exception.ManilaException(message="Fake raise") instances = self._setup_init_mocks(setup_access_rules=False) share_server = 'fake_share_server_type_does_not_matter' self.mock_object(self.share_manager.db, 'share_instances_get_all_by_host', mock.Mock(return_value=instances)) self.mock_object(self.share_manager.db, 'share_instance_get', mock.Mock(side_effect=[instances[0], instances[2], instances[3]])) self.mock_object(self.share_manager.driver, 'ensure_share', mock.Mock(side_effect=raise_exception)) self.mock_object(self.share_manager, '_ensure_share_instance_has_pool') self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=share_server)) self.mock_object(self.share_manager, 'publish_service_capabilities') self.mock_object(manager.LOG, 'error') self.mock_object(manager.LOG, 'info') # call of 'init_host' method self.share_manager.init_host() # verification of call self.share_manager.db.share_instances_get_all_by_host.\ assert_called_once_with(utils.IsAMatcher(context.RequestContext), self.share_manager.host) self.share_manager.driver.do_setup.assert_called_once_with( utils.IsAMatcher(context.RequestContext)) self.share_manager.driver.check_for_setup_error.assert_called_with() self.share_manager._ensure_share_instance_has_pool.assert_has_calls([ mock.call(utils.IsAMatcher(context.RequestContext), instances[0]), mock.call(utils.IsAMatcher(context.RequestContext), instances[2]), ]) self.share_manager._get_share_server.assert_has_calls([ mock.call(utils.IsAMatcher(context.RequestContext), instances[0]), mock.call(utils.IsAMatcher(context.RequestContext), instances[2]), ]) self.share_manager.driver.ensure_share.assert_has_calls([ mock.call(utils.IsAMatcher(context.RequestContext), instances[0], share_server=share_server), mock.call(utils.IsAMatcher(context.RequestContext), instances[2], share_server=share_server), ]) self.share_manager.publish_service_capabilities.\ assert_called_once_with( utils.IsAMatcher(context.RequestContext)) manager.LOG.info.assert_any_call( mock.ANY, {'task': constants.TASK_STATE_MIGRATION_IN_PROGRESS, 'id': instances[3]['id']}, ) manager.LOG.info.assert_any_call( mock.ANY, {'id': instances[1]['id'], 'status': instances[1]['status']}, ) def test_init_host_with_exception_on_update_access_rules(self): def raise_exception(*args, **kwargs): raise exception.ManilaException(message="Fake raise") instances, rules = self._setup_init_mocks() share_server = 'fake_share_server_type_does_not_matter' smanager = self.share_manager self.mock_object(smanager.db, 'share_instances_get_all_by_host', mock.Mock(return_value=instances)) self.mock_object(self.share_manager.db, 'share_instance_get', mock.Mock(side_effect=[instances[0], instances[2], instances[4]])) self.mock_object(self.share_manager.driver, 'ensure_share', mock.Mock(return_value=None)) self.mock_object(smanager, '_ensure_share_instance_has_pool') self.mock_object(smanager, '_get_share_server', mock.Mock(return_value=share_server)) self.mock_object(smanager, 'publish_service_capabilities') self.mock_object(manager.LOG, 'error') self.mock_object(manager.LOG, 'info') self.mock_object(smanager.db, 'share_access_get_all_for_share', mock.Mock(return_value=rules)) self.mock_object(smanager.access_helper, 'update_access_rules', mock.Mock(side_effect=raise_exception)) # call of 'init_host' method smanager.init_host() # verification of call smanager.db.share_instances_get_all_by_host.\ assert_called_once_with(utils.IsAMatcher(context.RequestContext), smanager.host) smanager.driver.do_setup.assert_called_once_with( utils.IsAMatcher(context.RequestContext)) smanager.driver.check_for_setup_error.assert_called_with() smanager._ensure_share_instance_has_pool.assert_has_calls([ mock.call(utils.IsAMatcher(context.RequestContext), instances[0]), mock.call(utils.IsAMatcher(context.RequestContext), instances[2]), ]) smanager._get_share_server.assert_has_calls([ mock.call(utils.IsAMatcher(context.RequestContext), instances[0]), mock.call(utils.IsAMatcher(context.RequestContext), instances[2]), ]) smanager.driver.ensure_share.assert_has_calls([ mock.call(utils.IsAMatcher(context.RequestContext), instances[0], share_server=share_server), mock.call(utils.IsAMatcher(context.RequestContext), instances[2], share_server=share_server), ]) self.share_manager.publish_service_capabilities.\ assert_called_once_with( utils.IsAMatcher(context.RequestContext)) manager.LOG.info.assert_any_call( mock.ANY, {'task': constants.TASK_STATE_MIGRATION_IN_PROGRESS, 'id': instances[3]['id']}, ) manager.LOG.info.assert_any_call( mock.ANY, {'id': instances[1]['id'], 'status': instances[1]['status']}, ) smanager.access_helper.update_access_rules.assert_has_calls([ mock.call(utils.IsAMatcher(context.RequestContext), instances[4]['id'], share_server=share_server), ]) manager.LOG.error.assert_has_calls([ mock.call(mock.ANY, mock.ANY), ]) def test_create_share_instance_from_snapshot_with_server(self): """Test share can be created from snapshot if server exists.""" network = db_utils.create_share_network() server = db_utils.create_share_server( share_network_id=network['id'], host='fake_host', backend_details=dict(fake='fake')) parent_share = db_utils.create_share(share_network_id='net-id', share_server_id=server['id']) share = db_utils.create_share() share_id = share['id'] snapshot = db_utils.create_snapshot(share_id=parent_share['id']) snapshot_id = snapshot['id'] self.share_manager.create_share_instance( self.context, share.instance['id'], snapshot_id=snapshot_id) self.assertEqual(share_id, db.share_get(context.get_admin_context(), share_id).id) shr = db.share_get(self.context, share_id) self.assertEqual(constants.STATUS_AVAILABLE, shr['status']) self.assertEqual(server['id'], shr['instance']['share_server_id']) def test_create_share_instance_from_snapshot_with_server_not_found(self): """Test creation from snapshot fails if server not found.""" parent_share = db_utils.create_share(share_network_id='net-id', share_server_id='fake-id') share = db_utils.create_share() share_id = share['id'] snapshot = db_utils.create_snapshot(share_id=parent_share['id']) snapshot_id = snapshot['id'] self.assertRaises(exception.ShareServerNotFound, self.share_manager.create_share_instance, self.context, share.instance['id'], snapshot_id=snapshot_id ) shr = db.share_get(self.context, share_id) self.assertEqual(constants.STATUS_ERROR, shr['status']) def test_create_share_instance_from_snapshot(self): """Test share can be created from snapshot.""" share = db_utils.create_share() share_id = share['id'] snapshot = db_utils.create_snapshot(share_id=share_id) snapshot_id = snapshot['id'] self.share_manager.create_share_instance( self.context, share.instance['id'], snapshot_id=snapshot_id) self.assertEqual(share_id, db.share_get(context.get_admin_context(), share_id).id) shr = db.share_get(self.context, share_id) self.assertEqual(constants.STATUS_AVAILABLE, shr['status']) self.assertTrue(len(shr['export_location']) > 0) self.assertEqual(2, len(shr['export_locations'])) def test_create_share_instance_for_share_with_replication_support(self): """Test update call is made to update replica_state.""" share = db_utils.create_share(replication_type='writable') share_id = share['id'] self.share_manager.create_share_instance(self.context, share.instance['id']) self.assertEqual(share_id, db.share_get(context.get_admin_context(), share_id).id) shr = db.share_get(self.context, share_id) shr_instance = db.share_instance_get(self.context, share.instance['id']) self.assertEqual(constants.STATUS_AVAILABLE, shr['status'],) self.assertEqual(constants.REPLICA_STATE_ACTIVE, shr_instance['replica_state']) @ddt.data([], None) def test_create_share_replica_no_active_replicas(self, active_replicas): replica = fake_replica() self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=active_replicas)) self.mock_object( db, 'share_replica_get', mock.Mock(return_value=replica)) mock_replica_update_call = self.mock_object(db, 'share_replica_update') mock_driver_replica_call = self.mock_object( self.share_manager.driver, 'create_replica') self.assertRaises(exception.ReplicationException, self.share_manager.create_share_replica, self.context, replica) mock_replica_update_call.assert_called_once_with( mock.ANY, replica['id'], {'status': constants.STATUS_ERROR, 'replica_state': constants.STATUS_ERROR}) self.assertFalse(mock_driver_replica_call.called) def test_create_share_replica_with_share_network_id_and_not_dhss(self): replica = fake_replica() manager.CONF.set_default('driver_handles_share_servers', False) self.mock_object(db, 'share_access_get_all_for_share', mock.Mock(return_value=[])) self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=fake_replica(id='fake2'))) self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) mock_replica_update_call = self.mock_object(db, 'share_replica_update') mock_driver_replica_call = self.mock_object( self.share_manager.driver, 'create_replica') self.assertRaises(exception.InvalidDriverMode, self.share_manager.create_share_replica, self.context, replica) mock_replica_update_call.assert_called_once_with( mock.ANY, replica['id'], {'status': constants.STATUS_ERROR, 'replica_state': constants.STATUS_ERROR}) self.assertFalse(mock_driver_replica_call.called) def test_create_share_replica_with_share_server_exception(self): replica = fake_replica() manager.CONF.set_default('driver_handles_share_servers', True) self.mock_object(db, 'share_instance_access_copy', mock.Mock(return_value=[])) self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=fake_replica(id='fake2'))) self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) mock_replica_update_call = self.mock_object(db, 'share_replica_update') mock_driver_replica_call = self.mock_object( self.share_manager.driver, 'create_replica') self.assertRaises(exception.NotFound, self.share_manager.create_share_replica, self.context, replica) mock_replica_update_call.assert_called_once_with( mock.ANY, replica['id'], {'status': constants.STATUS_ERROR, 'replica_state': constants.STATUS_ERROR}) self.assertFalse(mock_driver_replica_call.called) def test_create_share_replica_driver_error_on_creation(self): fake_access_rules = [{'id': '1'}, {'id': '2'}, {'id': '3'}] replica = fake_replica(share_network_id='') replica_2 = fake_replica(id='fake2') self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_instance_access_copy', mock.Mock(return_value=fake_access_rules)) self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=replica_2)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, replica_2])) self.mock_object(self.share_manager, '_provide_share_server_for_share', mock.Mock(return_value=('FAKE_SERVER', replica))) self.mock_object(self.share_manager, '_get_replica_snapshots_for_snapshot', mock.Mock(return_value=[])) mock_replica_update_call = self.mock_object(db, 'share_replica_update') mock_export_locs_update_call = self.mock_object( db, 'share_export_locations_update') mock_log_error = self.mock_object(manager.LOG, 'error') mock_log_info = self.mock_object(manager.LOG, 'info') self.mock_object(db, 'share_instance_access_get', mock.Mock(return_value=fake_access_rules[0])) mock_share_replica_access_update = self.mock_object( db, 'share_instance_update_access_status') self.mock_object(self.share_manager, '_get_share_server') driver_call = self.mock_object( self.share_manager.driver, 'create_replica', mock.Mock(side_effect=exception.ManilaException)) self.assertRaises(exception.ManilaException, self.share_manager.create_share_replica, self.context, replica) mock_replica_update_call.assert_called_once_with( mock.ANY, replica['id'], {'status': constants.STATUS_ERROR, 'replica_state': constants.STATUS_ERROR}) self.assertEqual(1, mock_share_replica_access_update.call_count) self.assertFalse(mock_export_locs_update_call.called) self.assertTrue(mock_log_error.called) self.assertFalse(mock_log_info.called) self.assertTrue(driver_call.called) def test_create_share_replica_invalid_locations_state(self): driver_retval = { 'export_locations': 'FAKE_EXPORT_LOC', } replica = fake_replica(share_network='') replica_2 = fake_replica(id='fake2') fake_access_rules = [{'id': '1'}, {'id': '2'}] self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=replica_2)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, replica_2])) self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_instance_access_copy', mock.Mock(return_value=fake_access_rules)) self.mock_object(self.share_manager, '_provide_share_server_for_share', mock.Mock(return_value=('FAKE_SERVER', replica))) self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=None)) self.mock_object(self.share_manager, '_get_replica_snapshots_for_snapshot', mock.Mock(return_value=[])) mock_replica_update_call = self.mock_object(db, 'share_replica_update') mock_export_locs_update_call = self.mock_object( db, 'share_export_locations_update') mock_log_info = self.mock_object(manager.LOG, 'info') mock_log_warning = self.mock_object(manager.LOG, 'warning') mock_log_error = self.mock_object(manager.LOG, 'error') driver_call = self.mock_object( self.share_manager.driver, 'create_replica', mock.Mock(return_value=driver_retval)) self.mock_object(db, 'share_instance_access_get', mock.Mock(return_value=fake_access_rules[0])) mock_share_replica_access_update = self.mock_object( db, 'share_instance_update_access_status') self.share_manager.create_share_replica(self.context, replica) self.assertFalse(mock_replica_update_call.called) self.assertEqual(1, mock_share_replica_access_update.call_count) self.assertFalse(mock_export_locs_update_call.called) self.assertTrue(mock_log_info.called) self.assertTrue(mock_log_warning.called) self.assertFalse(mock_log_error.called) self.assertTrue(driver_call.called) call_args = driver_call.call_args_list[0][0] replica_list_arg = call_args[1] r_ids = [r['id'] for r in replica_list_arg] for r in (replica, replica_2): self.assertIn(r['id'], r_ids) self.assertEqual(2, len(r_ids)) def test_create_share_replica_no_availability_zone(self): replica = fake_replica( availability_zone=None, share_network='', replica_state=constants.REPLICA_STATE_OUT_OF_SYNC) replica_2 = fake_replica(id='fake2') self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, replica_2])) manager.CONF.set_default('storage_availability_zone', 'fake_az') fake_access_rules = [{'id': '1'}, {'id': '2'}, {'id': '3'}] self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_instance_access_copy', mock.Mock(return_value=fake_access_rules)) self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=replica_2)) self.mock_object(self.share_manager, '_provide_share_server_for_share', mock.Mock(return_value=('FAKE_SERVER', replica))) self.mock_object(self.share_manager, '_get_replica_snapshots_for_snapshot', mock.Mock(return_value=[])) mock_replica_update_call = self.mock_object( db, 'share_replica_update', mock.Mock(return_value=replica)) mock_calls = [ mock.call(mock.ANY, replica['id'], {'availability_zone': 'fake_az'}, with_share_data=True), mock.call(mock.ANY, replica['id'], {'status': constants.STATUS_AVAILABLE, 'replica_state': constants.REPLICA_STATE_OUT_OF_SYNC}), ] mock_export_locs_update_call = self.mock_object( db, 'share_export_locations_update') mock_log_info = self.mock_object(manager.LOG, 'info') mock_log_warning = self.mock_object(manager.LOG, 'warning') mock_log_error = self.mock_object(manager.LOG, 'warning') self.mock_object(db, 'share_instance_access_get', mock.Mock(return_value=fake_access_rules[0])) mock_share_replica_access_update = self.mock_object( self.share_manager, '_update_share_replica_access_rules_state') driver_call = self.mock_object( self.share_manager.driver, 'create_replica', mock.Mock(return_value=replica)) self.mock_object(self.share_manager, '_get_share_server', mock.Mock()) self.share_manager.create_share_replica(self.context, replica) mock_replica_update_call.assert_has_calls(mock_calls, any_order=False) mock_share_replica_access_update.assert_called_once_with( mock.ANY, replica['id'], replica['access_rules_status']) self.assertTrue(mock_export_locs_update_call.called) self.assertTrue(mock_log_info.called) self.assertFalse(mock_log_warning.called) self.assertFalse(mock_log_error.called) self.assertTrue(driver_call.called) @ddt.data(True, False) def test_create_share_replica(self, has_snapshots): replica = fake_replica( share_network='', replica_state=constants.REPLICA_STATE_IN_SYNC) replica_2 = fake_replica(id='fake2') snapshots = ([fakes.fake_snapshot(create_instance=True)] if has_snapshots else []) snapshot_instances = [ fakes.fake_snapshot_instance(share_instance_id=replica['id']), fakes.fake_snapshot_instance(share_instance_id='fake2'), ] fake_access_rules = [{'id': '1'}, {'id': '2'}, {'id': '3'}] self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_instance_access_copy', mock.Mock(return_value=fake_access_rules)) self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=replica_2)) self.mock_object(self.share_manager, '_provide_share_server_for_share', mock.Mock(return_value=('FAKE_SERVER', replica))) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, replica_2])) self.mock_object(db, 'share_snapshot_get_all_for_share', mock.Mock( return_value=snapshots)) mock_instance_get_call = self.mock_object( db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshot_instances)) mock_replica_update_call = self.mock_object(db, 'share_replica_update') mock_export_locs_update_call = self.mock_object( db, 'share_export_locations_update') mock_log_info = self.mock_object(manager.LOG, 'info') mock_log_warning = self.mock_object(manager.LOG, 'warning') mock_log_error = self.mock_object(manager.LOG, 'warning') self.mock_object(db, 'share_instance_access_get', mock.Mock(return_value=fake_access_rules[0])) mock_share_replica_access_update = self.mock_object( db, 'share_instance_update_access_status') driver_call = self.mock_object( self.share_manager.driver, 'create_replica', mock.Mock(return_value=replica)) self.mock_object(self.share_manager, '_get_share_server') self.share_manager.create_share_replica(self.context, replica) mock_replica_update_call.assert_called_once_with( mock.ANY, replica['id'], {'status': constants.STATUS_AVAILABLE, 'replica_state': constants.REPLICA_STATE_IN_SYNC}) self.assertEqual(1, mock_share_replica_access_update.call_count) self.assertTrue(mock_export_locs_update_call.called) self.assertTrue(mock_log_info.called) self.assertFalse(mock_log_warning.called) self.assertFalse(mock_log_error.called) self.assertTrue(driver_call.called) call_args = driver_call.call_args_list[0][0] replica_list_arg = call_args[1] snapshot_list_arg = call_args[4] r_ids = [r['id'] for r in replica_list_arg] for r in (replica, replica_2): self.assertIn(r['id'], r_ids) self.assertEqual(2, len(r_ids)) if has_snapshots: for snapshot_dict in snapshot_list_arg: self.assertTrue('active_replica_snapshot' in snapshot_dict) self.assertTrue('share_replica_snapshot' in snapshot_dict) else: self.assertFalse(mock_instance_get_call.called) def test_delete_share_replica_access_rules_exception(self): replica = fake_replica() replica_2 = fake_replica(id='fake_2') self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, replica_2])) active_replica = fake_replica( id='Current_active_replica', replica_state=constants.REPLICA_STATE_ACTIVE) mock_exception_log = self.mock_object(manager.LOG, 'exception') self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=active_replica)) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(self.share_manager.access_helper, 'update_access_rules') mock_replica_update_call = self.mock_object(db, 'share_replica_update') mock_replica_delete_call = self.mock_object(db, 'share_replica_delete') mock_drv_delete_replica_call = self.mock_object( self.share_manager.driver, 'delete_replica') self.mock_object( self.share_manager.access_helper, 'update_access_rules', mock.Mock(side_effect=exception.ManilaException)) self.assertRaises(exception.ManilaException, self.share_manager.delete_share_replica, self.context, replica['id'], share_id=replica['share_id']) mock_replica_update_call.assert_called_once_with( mock.ANY, replica['id'], {'status': constants.STATUS_ERROR}) self.assertFalse(mock_drv_delete_replica_call.called) self.assertFalse(mock_replica_delete_call.called) self.assertFalse(mock_exception_log.called) def test_delete_share_replica_drv_misbehavior_ignored_with_the_force(self): replica = fake_replica() active_replica = fake_replica(id='Current_active_replica') mock_exception_log = self.mock_object(manager.LOG, 'exception') self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, active_replica])) self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=active_replica)) self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=None)) self.mock_object(self.share_manager.access_helper, 'update_access_rules') self.mock_object( db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=[])) mock_snap_instance_delete = self.mock_object( db, 'share_snapshot_instance_delete') mock_replica_update_call = self.mock_object(db, 'share_replica_update') mock_replica_delete_call = self.mock_object(db, 'share_replica_delete') mock_drv_delete_replica_call = self.mock_object( self.share_manager.driver, 'delete_replica', mock.Mock(side_effect=exception.ManilaException)) self.mock_object( self.share_manager.access_helper, 'update_access_rules') self.share_manager.delete_share_replica( self.context, replica['id'], share_id=replica['share_id'], force=True) self.assertFalse(mock_replica_update_call.called) self.assertTrue(mock_replica_delete_call.called) self.assertEqual(1, mock_exception_log.call_count) self.assertTrue(mock_drv_delete_replica_call.called) self.assertFalse(mock_snap_instance_delete.called) def test_delete_share_replica_driver_exception(self): replica = fake_replica() active_replica = fake_replica(id='Current_active_replica') self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, active_replica])) self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=active_replica)) self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=None)) mock_snapshot_get_call = self.mock_object( db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=[])) mock_replica_update_call = self.mock_object(db, 'share_replica_update') mock_replica_delete_call = self.mock_object(db, 'share_replica_delete') self.mock_object( self.share_manager.access_helper, 'update_access_rules') mock_drv_delete_replica_call = self.mock_object( self.share_manager.driver, 'delete_replica', mock.Mock(side_effect=exception.ManilaException)) self.assertRaises(exception.ManilaException, self.share_manager.delete_share_replica, self.context, replica['id'], share_id=replica['share_id']) self.assertTrue(mock_replica_update_call.called) self.assertFalse(mock_replica_delete_call.called) self.assertTrue(mock_drv_delete_replica_call.called) self.assertTrue(mock_snapshot_get_call.called) def test_delete_share_replica_both_exceptions_ignored_with_the_force(self): replica = fake_replica() active_replica = fake_replica(id='Current_active_replica') snapshots = [ fakes.fake_snapshot(share_id=replica['id'], status=constants.STATUS_AVAILABLE), fakes.fake_snapshot(share_id=replica['id'], id='test_creating_to_err', status=constants.STATUS_CREATING) ] self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, active_replica])) mock_exception_log = self.mock_object(manager.LOG, 'exception') self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=active_replica)) self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=None)) self.mock_object( db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshots)) mock_snapshot_instance_delete_call = self.mock_object( db, 'share_snapshot_instance_delete') mock_replica_update_call = self.mock_object(db, 'share_replica_update') mock_replica_delete_call = self.mock_object(db, 'share_replica_delete') self.mock_object( self.share_manager.access_helper, 'update_access_rules', mock.Mock(side_effect=exception.ManilaException)) mock_drv_delete_replica_call = self.mock_object( self.share_manager.driver, 'delete_replica', mock.Mock(side_effect=exception.ManilaException)) self.share_manager.delete_share_replica( self.context, replica['id'], share_id=replica['share_id'], force=True) mock_replica_update_call.assert_called_once_with( mock.ANY, replica['id'], {'status': constants.STATUS_ERROR}) self.assertTrue(mock_replica_delete_call.called) self.assertEqual(2, mock_exception_log.call_count) self.assertTrue(mock_drv_delete_replica_call.called) self.assertEqual(2, mock_snapshot_instance_delete_call.call_count) def test_delete_share_replica(self): replica = fake_replica() active_replica = fake_replica(id='current_active_replica') snapshots = [ fakes.fake_snapshot(share_id=replica['share_id'], status=constants.STATUS_AVAILABLE), fakes.fake_snapshot(share_id=replica['share_id'], id='test_creating_to_err', status=constants.STATUS_CREATING) ] self.mock_object( db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshots)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, active_replica])) self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=active_replica)) self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=None)) mock_info_log = self.mock_object(manager.LOG, 'info') mock_snapshot_instance_delete_call = self.mock_object( db, 'share_snapshot_instance_delete') mock_replica_update_call = self.mock_object(db, 'share_replica_update') mock_replica_delete_call = self.mock_object(db, 'share_replica_delete') self.mock_object( self.share_manager.access_helper, 'update_access_rules') mock_drv_delete_replica_call = self.mock_object( self.share_manager.driver, 'delete_replica') self.share_manager.delete_share_replica(self.context, replica) self.assertFalse(mock_replica_update_call.called) self.assertTrue(mock_replica_delete_call.called) self.assertTrue(mock_info_log.called) self.assertTrue(mock_drv_delete_replica_call.called) self.assertEqual(2, mock_snapshot_instance_delete_call.call_count) def test_promote_share_replica_no_active_replica(self): replica = fake_replica() replica_list = [replica] self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_replicas_get_available_active_replica', mock.Mock(return_value=replica_list)) mock_info_log = self.mock_object(manager.LOG, 'info') mock_driver_call = self.mock_object(self.share_manager.driver, 'promote_replica') mock_replica_update = self.mock_object(db, 'share_replica_update') expected_update_call = mock.call( mock.ANY, replica['id'], {'status': constants.STATUS_AVAILABLE}) self.assertRaises(exception.ReplicationException, self.share_manager.promote_share_replica, self.context, replica) self.assertFalse(mock_info_log.called) self.assertFalse(mock_driver_call.called) mock_replica_update.assert_has_calls([expected_update_call]) def test_promote_share_replica_driver_exception(self): replica = fake_replica() active_replica = fake_replica( id='current_active_replica', replica_state=constants.REPLICA_STATE_ACTIVE) replica_list = [replica, active_replica] self.mock_object(db, 'share_access_get_all_for_share', mock.Mock(return_value=[])) self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=replica_list)) self.mock_object(self.share_manager.driver, 'promote_replica', mock.Mock(side_effect=exception.ManilaException)) mock_info_log = self.mock_object(manager.LOG, 'info') mock_replica_update = self.mock_object(db, 'share_replica_update') expected_update_calls = [mock.call( mock.ANY, r['id'], {'status': constants.STATUS_ERROR}) for r in(replica, active_replica)] self.assertRaises(exception.ManilaException, self.share_manager.promote_share_replica, self.context, replica) mock_replica_update.assert_has_calls(expected_update_calls) self.assertFalse(mock_info_log.called) @ddt.data([], None) def test_promote_share_replica_driver_update_nothing_has_snaps(self, retval): replica = fake_replica() active_replica = fake_replica( id='current_active_replica', replica_state=constants.REPLICA_STATE_ACTIVE) snapshots_instances = [ fakes.fake_snapshot(create_instance=True, share_id=replica['share_id'], status=constants.STATUS_AVAILABLE), fakes.fake_snapshot(create_instance=True, share_id=replica['share_id'], id='test_creating_to_err', status=constants.STATUS_CREATING) ] replica_list = [replica, active_replica] self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_access_get_all_for_share', mock.Mock(return_value=[])) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=replica_list)) self.mock_object( db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshots_instances)) self.mock_object( self.share_manager.driver, 'promote_replica', mock.Mock(return_value=retval)) mock_snap_instance_update = self.mock_object( db, 'share_snapshot_instance_update') mock_info_log = self.mock_object(manager.LOG, 'info') mock_export_locs_update = self.mock_object( db, 'share_export_locations_update') mock_replica_update = self.mock_object(db, 'share_replica_update') call_1 = mock.call(mock.ANY, replica['id'], {'status': constants.STATUS_AVAILABLE, 'replica_state': constants.REPLICA_STATE_ACTIVE}) call_2 = mock.call( mock.ANY, 'current_active_replica', {'replica_state': constants.REPLICA_STATE_OUT_OF_SYNC}) expected_update_calls = [call_1, call_2] self.share_manager.promote_share_replica(self.context, replica) self.assertFalse(mock_export_locs_update.called) mock_replica_update.assert_has_calls(expected_update_calls, any_order=True) mock_snap_instance_update.assert_called_once_with( mock.ANY, 'test_creating_to_err', {'status': constants.STATUS_ERROR}) self.assertEqual(2, mock_info_log.call_count) def test_promote_share_replica_driver_updates_replica_list(self): replica = fake_replica() active_replica = fake_replica( id='current_active_replica', replica_state=constants.REPLICA_STATE_ACTIVE) replica_list = [replica, active_replica, fake_replica(id=3)] updated_replica_list = [ { 'id': replica['id'], 'export_locations': ['TEST1', 'TEST2'], 'replica_state': constants.REPLICA_STATE_ACTIVE, }, { 'id': 'current_active_replica', 'export_locations': 'junk_return_value', 'replica_state': constants.REPLICA_STATE_IN_SYNC, }, { 'id': 'other_replica', 'export_locations': ['TEST1', 'TEST2'], }, ] self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object( db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=[])) self.mock_object(db, 'share_access_get_all_for_share', mock.Mock(return_value=[])) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=replica_list)) mock_snap_instance_update = self.mock_object( db, 'share_snapshot_instance_update') self.mock_object( self.share_manager.driver, 'promote_replica', mock.Mock(return_value=updated_replica_list)) mock_info_log = self.mock_object(manager.LOG, 'info') mock_export_locs_update = self.mock_object( db, 'share_export_locations_update') mock_replica_update = self.mock_object(db, 'share_replica_update') reset_replication_change_call = mock.call( mock.ANY, replica['id'], {'replica_state': constants.STATUS_ACTIVE, 'status': constants.STATUS_AVAILABLE}) self.share_manager.promote_share_replica(self.context, replica) self.assertEqual(2, mock_export_locs_update.call_count) self.assertEqual(2, mock_replica_update.call_count) self.assertTrue( reset_replication_change_call in mock_replica_update.mock_calls) self.assertTrue(mock_info_log.called) self.assertFalse(mock_snap_instance_update.called) @ddt.data('openstack1@watson#_pool0', 'openstack1@newton#_pool0') def test_periodic_share_replica_update(self, host): mock_debug_log = self.mock_object(manager.LOG, 'debug') replicas = [ fake_replica(host='openstack1@watson#pool4'), fake_replica(host='openstack1@watson#pool5'), fake_replica(host='openstack1@newton#pool5'), fake_replica(host='openstack1@newton#pool5'), ] self.mock_object(self.share_manager.db, 'share_replicas_get_all', mock.Mock(return_value=replicas)) mock_update_method = self.mock_object( self.share_manager, '_share_replica_update') self.share_manager.host = host self.share_manager.periodic_share_replica_update(self.context) self.assertEqual(2, mock_update_method.call_count) self.assertEqual(1, mock_debug_log.call_count) @ddt.data(constants.REPLICA_STATE_IN_SYNC, constants.REPLICA_STATE_OUT_OF_SYNC) def test__share_replica_update_driver_exception(self, replica_state): mock_debug_log = self.mock_object(manager.LOG, 'debug') replica = fake_replica(replica_state=replica_state) active_replica = fake_replica( replica_state=constants.REPLICA_STATE_ACTIVE) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, active_replica])) self.mock_object(self.share_manager.db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_server_get', mock.Mock(return_value='fake_share_server')) self.mock_object(self.share_manager.driver, 'update_replica_state', mock.Mock(side_effect=exception.ManilaException)) mock_db_update_call = self.mock_object( self.share_manager.db, 'share_replica_update') self.share_manager._share_replica_update( self.context, replica, share_id=replica['share_id']) mock_db_update_call.assert_called_once_with( self.context, replica['id'], {'replica_state': constants.STATUS_ERROR, 'status': constants.STATUS_ERROR} ) self.assertEqual(1, mock_debug_log.call_count) def test__share_replica_update_driver_exception_ignored(self): mock_debug_log = self.mock_object(manager.LOG, 'debug') replica = fake_replica(replica_state=constants.STATUS_ERROR) active_replica = fake_replica(replica_state=constants.STATUS_ACTIVE) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, active_replica])) self.mock_object(self.share_manager.db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_server_get', mock.Mock(return_value='fake_share_server')) self.share_manager.host = replica['host'] self.mock_object(self.share_manager.driver, 'update_replica_state', mock.Mock(side_effect=exception.ManilaException)) mock_db_update_call = self.mock_object( self.share_manager.db, 'share_replica_update') self.share_manager._share_replica_update( self.context, replica, share_id=replica['share_id']) mock_db_update_call.assert_called_once_with( self.context, replica['id'], {'replica_state': constants.STATUS_ERROR, 'status': constants.STATUS_ERROR} ) self.assertEqual(1, mock_debug_log.call_count) @ddt.data({'status': constants.STATUS_AVAILABLE, 'replica_state': constants.REPLICA_STATE_ACTIVE, }, {'status': constants.STATUS_DELETING, 'replica_state': constants.REPLICA_STATE_IN_SYNC, }, {'status': constants.STATUS_CREATING, 'replica_state': constants.REPLICA_STATE_OUT_OF_SYNC, }, {'status': constants.STATUS_MANAGING, 'replica_state': constants.REPLICA_STATE_OUT_OF_SYNC, }, {'status': constants.STATUS_UNMANAGING, 'replica_state': constants.REPLICA_STATE_ACTIVE, }, {'status': constants.STATUS_EXTENDING, 'replica_state': constants.REPLICA_STATE_IN_SYNC, }, {'status': constants.STATUS_SHRINKING, 'replica_state': constants.REPLICA_STATE_IN_SYNC, }) def test__share_replica_update_unqualified_replica(self, state): mock_debug_log = self.mock_object(manager.LOG, 'debug') mock_warning_log = self.mock_object(manager.LOG, 'warning') mock_driver_call = self.mock_object( self.share_manager.driver, 'update_replica_state') mock_db_update_call = self.mock_object( self.share_manager.db, 'share_replica_update') replica = fake_replica(**state) self.mock_object(db, 'share_server_get', mock.Mock(return_value='fake_share_server')) self.mock_object(db, 'share_replica_get', mock.Mock(return_value=replica)) self.share_manager._share_replica_update(self.context, replica, share_id=replica['share_id']) self.assertFalse(mock_debug_log.called) self.assertFalse(mock_warning_log.called) self.assertFalse(mock_driver_call.called) self.assertFalse(mock_db_update_call.called) @ddt.data(None, constants.REPLICA_STATE_IN_SYNC, constants.REPLICA_STATE_OUT_OF_SYNC, constants.REPLICA_STATE_ACTIVE, constants.STATUS_ERROR) def test__share_replica_update(self, retval): mock_debug_log = self.mock_object(manager.LOG, 'debug') mock_warning_log = self.mock_object(manager.LOG, 'warning') replica_states = [constants.REPLICA_STATE_IN_SYNC, constants.REPLICA_STATE_OUT_OF_SYNC] replica = fake_replica(replica_state=random.choice(replica_states), share_server='fake_share_server') active_replica = fake_replica( id='fake2', replica_state=constants.STATUS_ACTIVE) snapshots = [fakes.fake_snapshot( create_instance=True, aggregate_status=constants.STATUS_AVAILABLE)] snapshot_instances = [ fakes.fake_snapshot_instance(share_instance_id=replica['id']), fakes.fake_snapshot_instance(share_instance_id='fake2'), ] del replica['availability_zone'] self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica, active_replica])) self.mock_object(db, 'share_server_get', mock.Mock(return_value='fake_share_server')) mock_db_update_calls = [] self.mock_object(self.share_manager.db, 'share_replica_get', mock.Mock(return_value=replica)) mock_driver_call = self.mock_object( self.share_manager.driver, 'update_replica_state', mock.Mock(return_value=retval)) mock_db_update_call = self.mock_object( self.share_manager.db, 'share_replica_update') self.mock_object(db, 'share_snapshot_get_all_for_share', mock.Mock(return_value=snapshots)) self.mock_object(db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshot_instances)) self.share_manager._share_replica_update( self.context, replica, share_id=replica['share_id']) if retval == constants.REPLICA_STATE_ACTIVE: self.assertEqual(1, mock_warning_log.call_count) elif retval: self.assertEqual(0, mock_warning_log.call_count) self.assertTrue(mock_driver_call.called) snapshot_list_arg = mock_driver_call.call_args[0][4] self.assertTrue('active_replica_snapshot' in snapshot_list_arg[0]) self.assertTrue('share_replica_snapshot' in snapshot_list_arg[0]) mock_db_update_call.assert_has_calls(mock_db_update_calls) self.assertEqual(1, mock_debug_log.call_count) def test_update_share_replica_replica_not_found(self): replica = fake_replica() self.mock_object( self.share_manager.db, 'share_replica_get', mock.Mock( side_effect=exception.ShareReplicaNotFound(replica_id='fake'))) self.mock_object(self.share_manager, '_get_share_server') driver_call = self.mock_object( self.share_manager, '_share_replica_update') self.assertRaises( exception.ShareReplicaNotFound, self.share_manager.update_share_replica, self.context, replica, share_id=replica['share_id']) self.assertFalse(driver_call.called) def test_update_share_replica_replica(self): replica_update_call = self.mock_object( self.share_manager, '_share_replica_update') self.mock_object(self.share_manager.db, 'share_replica_get') retval = self.share_manager.update_share_replica( self.context, 'fake_replica_id', share_id='fake_share_id') self.assertIsNone(retval) self.assertTrue(replica_update_call.called) def test_create_delete_share_snapshot(self): """Test share's snapshot can be created and deleted.""" def _fake_create_snapshot(self, snapshot, **kwargs): snapshot['progress'] = '99%' return snapshot.to_dict() self.mock_object(self.share_manager.driver, "create_snapshot", _fake_create_snapshot) share = db_utils.create_share() share_id = share['id'] snapshot = db_utils.create_snapshot(share_id=share_id) snapshot_id = snapshot['id'] self.share_manager.create_snapshot(self.context, share_id, snapshot_id) self.assertEqual(share_id, db.share_snapshot_get(context.get_admin_context(), snapshot_id).share_id) snap = db.share_snapshot_get(self.context, snapshot_id) self.assertEqual(constants.STATUS_AVAILABLE, snap['status']) self.share_manager.delete_snapshot(self.context, snapshot_id) self.assertRaises(exception.NotFound, db.share_snapshot_get, self.context, snapshot_id) def test_create_delete_share_snapshot_error(self): """Test snapshot can be created and deleted with error.""" def _raise_not_found(self, *args, **kwargs): raise exception.NotFound() self.mock_object(self.share_manager.driver, "create_snapshot", mock.Mock(side_effect=_raise_not_found)) self.mock_object(self.share_manager.driver, "delete_snapshot", mock.Mock(side_effect=_raise_not_found)) share = db_utils.create_share() share_id = share['id'] snapshot = db_utils.create_snapshot(share_id=share_id) snapshot_id = snapshot['id'] self.assertRaises(exception.NotFound, self.share_manager.create_snapshot, self.context, share_id, snapshot_id) snap = db.share_snapshot_get(self.context, snapshot_id) self.assertEqual(constants.STATUS_ERROR, snap['status']) self.assertRaises(exception.NotFound, self.share_manager.delete_snapshot, self.context, snapshot_id) self.assertEqual( constants.STATUS_ERROR_DELETING, db.share_snapshot_get(self.context, snapshot_id).status) self.share_manager.driver.create_snapshot.assert_called_once_with( self.context, utils.IsAMatcher(models.ShareSnapshotInstance), share_server=None) self.share_manager.driver.delete_snapshot.assert_called_once_with( utils.IsAMatcher(context.RequestContext), utils.IsAMatcher(models.ShareSnapshotInstance), share_server=None) def test_delete_snapshot_quota_error(self): share = db_utils.create_share() share_id = share['id'] snapshot = db_utils.create_snapshot(share_id=share_id) snapshot_id = snapshot['id'] snapshot = db_utils.create_snapshot( with_share=True, status=constants.STATUS_AVAILABLE) self.mock_object(quota.QUOTAS, 'reserve', mock.Mock(side_effect=exception.QuotaError('fake'))) self.mock_object(quota.QUOTAS, 'commit') self.share_manager.delete_snapshot(self.context, snapshot_id) quota.QUOTAS.reserve.assert_called_once_with( mock.ANY, project_id=six.text_type(snapshot['project_id']), snapshots=-1, snapshot_gigabytes=-snapshot['size'], user_id=six.text_type(snapshot['user_id']) ) self.assertFalse(quota.QUOTAS.commit.called) def test_delete_share_instance_if_busy(self): """Test snapshot could not be deleted if busy.""" def _raise_share_snapshot_is_busy(self, *args, **kwargs): raise exception.ShareSnapshotIsBusy(snapshot_name='fakename') self.mock_object(self.share_manager.driver, "delete_snapshot", mock.Mock(side_effect=_raise_share_snapshot_is_busy)) share = db_utils.create_share(status=constants.STATUS_ACTIVE) snapshot = db_utils.create_snapshot(share_id=share['id']) snapshot_id = snapshot['id'] self.share_manager.delete_snapshot(self.context, snapshot_id) snap = db.share_snapshot_get(self.context, snapshot_id) self.assertEqual(constants.STATUS_AVAILABLE, snap['status']) self.share_manager.driver.delete_snapshot.assert_called_once_with( utils.IsAMatcher(context.RequestContext), utils.IsAMatcher(models.ShareSnapshotInstance), share_server=None) def test_create_share_instance_with_share_network_dhss_false(self): manager.CONF.set_default('driver_handles_share_servers', False) self.mock_object( self.share_manager.driver.configuration, 'safe_get', mock.Mock(return_value=False)) share_network_id = 'fake_sn' share_instance = db_utils.create_share( share_network_id=share_network_id).instance self.mock_object( self.share_manager.db, 'share_instance_get', mock.Mock(return_value=share_instance)) self.mock_object(self.share_manager.db, 'share_instance_update') self.assertRaisesRegex( exception.ManilaException, '.*%s.*' % share_instance['id'], self.share_manager.create_share_instance, self.context, share_instance['id']) self.share_manager.db.share_instance_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), share_instance['id'], with_share_data=True ) self.share_manager.db.share_instance_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), share_instance['id'], {'status': constants.STATUS_ERROR}) def test_create_share_instance_with_share_network_server_not_exists(self): """Test share can be created without share server.""" share_net = db_utils.create_share_network() share = db_utils.create_share(share_network_id=share_net['id']) share_id = share['id'] def fake_setup_server(context, share_network, *args, **kwargs): return db_utils.create_share_server( share_network_id=share_network['id'], host='fake_host') self.mock_object(manager.LOG, 'info') self.share_manager.driver.create_share = mock.Mock( return_value='fake_location') self.share_manager._setup_server = fake_setup_server self.share_manager.create_share_instance(self.context, share.instance['id']) self.assertEqual(share_id, db.share_get(context.get_admin_context(), share_id).id) manager.LOG.info.assert_called_with(mock.ANY, share.instance['id']) def test_create_share_instance_with_share_network_server_fail(self): fake_share = db_utils.create_share(share_network_id='fake_sn_id', size=1) fake_server = { 'id': 'fake_srv_id', 'status': constants.STATUS_CREATING, } self.mock_object(db, 'share_server_create', mock.Mock(return_value=fake_server)) self.mock_object(db, 'share_instance_update', mock.Mock(return_value=fake_share.instance)) self.mock_object(db, 'share_instance_get', mock.Mock(return_value=fake_share.instance)) self.mock_object(manager.LOG, 'error') def raise_share_server_not_found(*args, **kwargs): raise exception.ShareServerNotFound( share_server_id=fake_server['id']) def raise_manila_exception(*args, **kwargs): raise exception.ManilaException() self.mock_object(db, 'share_server_get_all_by_host_and_share_net_valid', mock.Mock(side_effect=raise_share_server_not_found)) self.mock_object(self.share_manager, '_setup_server', mock.Mock(side_effect=raise_manila_exception)) self.assertRaises( exception.ManilaException, self.share_manager.create_share_instance, self.context, fake_share.instance['id'], ) db.share_server_get_all_by_host_and_share_net_valid.\ assert_called_once_with( utils.IsAMatcher(context.RequestContext), self.share_manager.host, fake_share['share_network_id'], ) db.share_server_create.assert_called_once_with( utils.IsAMatcher(context.RequestContext), mock.ANY) db.share_instance_update.assert_has_calls([ mock.call( utils.IsAMatcher(context.RequestContext), fake_share.instance['id'], {'status': constants.STATUS_ERROR}, ) ]) self.share_manager._setup_server.assert_called_once_with( utils.IsAMatcher(context.RequestContext), fake_server) manager.LOG.error.assert_called_with(mock.ANY, fake_share.instance['id']) def test_create_share_instance_with_share_network_not_found(self): """Test creation fails if share network not found.""" self.mock_object(manager.LOG, 'error') share = db_utils.create_share(share_network_id='fake-net-id') share_id = share['id'] self.assertRaises( exception.ShareNetworkNotFound, self.share_manager.create_share_instance, self.context, share.instance['id'] ) manager.LOG.error.assert_called_with(mock.ANY, share.instance['id']) shr = db.share_get(self.context, share_id) self.assertEqual(constants.STATUS_ERROR, shr['status']) def test_create_share_instance_with_share_network_server_exists(self): """Test share can be created with existing share server.""" share_net = db_utils.create_share_network() share = db_utils.create_share(share_network_id=share_net['id']) share_srv = db_utils.create_share_server( share_network_id=share_net['id'], host=self.share_manager.host) share_id = share['id'] self.mock_object(manager.LOG, 'info') driver_mock = mock.Mock() driver_mock.create_share.return_value = "fake_location" driver_mock.choose_share_server_compatible_with_share.return_value = ( share_srv ) self.share_manager.driver = driver_mock self.share_manager.create_share_instance(self.context, share.instance['id']) self.assertFalse(self.share_manager.driver.setup_network.called) self.assertEqual(share_id, db.share_get(context.get_admin_context(), share_id).id) shr = db.share_get(self.context, share_id) self.assertEqual(shr['status'], constants.STATUS_AVAILABLE) self.assertEqual(shr['share_server_id'], share_srv['id']) self.assertTrue(len(shr['export_location']) > 0) self.assertEqual(1, len(shr['export_locations'])) manager.LOG.info.assert_called_with(mock.ANY, share.instance['id']) @ddt.data('export_location', 'export_locations') def test_create_share_instance_with_error_in_driver(self, details_key): """Test db updates if share creation fails in driver.""" share = db_utils.create_share() share_id = share['id'] some_data = 'fake_location' self.share_manager.driver = mock.Mock() e = exception.ManilaException(detail_data={details_key: some_data}) self.share_manager.driver.create_share.side_effect = e self.assertRaises( exception.ManilaException, self.share_manager.create_share_instance, self.context, share.instance['id'] ) self.assertTrue(self.share_manager.driver.create_share.called) shr = db.share_get(self.context, share_id) self.assertEqual(some_data, shr['export_location']) def test_create_share_instance_with_server_created(self): """Test share can be created and share server is created.""" share_net = db_utils.create_share_network() share = db_utils.create_share(share_network_id=share_net['id']) db_utils.create_share_server( share_network_id=share_net['id'], host=self.share_manager.host, status=constants.STATUS_ERROR) share_id = share['id'] fake_server = { 'id': 'fake_srv_id', 'status': constants.STATUS_CREATING, } self.mock_object(db, 'share_server_create', mock.Mock(return_value=fake_server)) self.mock_object(self.share_manager, '_setup_server', mock.Mock(return_value=fake_server)) self.share_manager.create_share_instance(self.context, share.instance['id']) self.assertEqual(share_id, db.share_get(context.get_admin_context(), share_id).id) shr = db.share_get(self.context, share_id) self.assertEqual(constants.STATUS_AVAILABLE, shr['status']) self.assertEqual('fake_srv_id', shr['share_server_id']) db.share_server_create.assert_called_once_with( utils.IsAMatcher(context.RequestContext), mock.ANY) self.share_manager._setup_server.assert_called_once_with( utils.IsAMatcher(context.RequestContext), fake_server) def test_create_share_instance_update_replica_state(self): share_net = db_utils.create_share_network() share = db_utils.create_share(share_network_id=share_net['id'], replication_type='dr') db_utils.create_share_server( share_network_id=share_net['id'], host=self.share_manager.host, status=constants.STATUS_ERROR) share_id = share['id'] fake_server = { 'id': 'fake_srv_id', 'status': constants.STATUS_CREATING, } self.mock_object(db, 'share_server_create', mock.Mock(return_value=fake_server)) self.mock_object(self.share_manager, '_setup_server', mock.Mock(return_value=fake_server)) self.share_manager.create_share_instance(self.context, share.instance['id']) self.assertEqual(share_id, db.share_get(context.get_admin_context(), share_id).id) shr = db.share_get(self.context, share_id) shr_instances = db.share_instances_get_all_by_share( self.context, shr['id']) self.assertEqual(1, len(shr_instances)) self.assertEqual(constants.STATUS_AVAILABLE, shr['status']) self.assertEqual( constants.REPLICA_STATE_ACTIVE, shr_instances[0]['replica_state']) self.assertEqual('fake_srv_id', shr['share_server_id']) db.share_server_create.assert_called_once_with( utils.IsAMatcher(context.RequestContext), mock.ANY) self.share_manager._setup_server.assert_called_once_with( utils.IsAMatcher(context.RequestContext), fake_server) @ddt.data(True, False) def test_create_delete_share_instance_error(self, exception_update_access): """Test share can be created and deleted with error.""" def _raise_exception(self, *args, **kwargs): raise exception.ManilaException('fake') self.mock_object(self.share_manager.driver, "create_share", mock.Mock(side_effect=_raise_exception)) self.mock_object(self.share_manager.driver, "delete_share", mock.Mock(side_effect=_raise_exception)) if exception_update_access: self.mock_object( self.share_manager.access_helper, "update_access_rules", mock.Mock(side_effect=_raise_exception)) share = db_utils.create_share() share_id = share['id'] self.assertRaises(exception.ManilaException, self.share_manager.create_share_instance, self.context, share.instance['id']) shr = db.share_get(self.context, share_id) self.assertEqual(constants.STATUS_ERROR, shr['status']) self.assertRaises(exception.ManilaException, self.share_manager.delete_share_instance, self.context, share.instance['id']) shr = db.share_get(self.context, share_id) self.assertEqual(constants.STATUS_ERROR_DELETING, shr['status']) self.share_manager.driver.create_share.assert_called_once_with( utils.IsAMatcher(context.RequestContext), utils.IsAMatcher(models.ShareInstance), share_server=None) if not exception_update_access: self.share_manager.driver.delete_share.assert_called_once_with( utils.IsAMatcher(context.RequestContext), utils.IsAMatcher(models.ShareInstance), share_server=None) def test_create_share_instance_update_availability_zone(self): share = db_utils.create_share(availability_zone=None) share_id = share['id'] self.share_manager.create_share_instance( self.context, share.instance['id']) actual_share = db.share_get(context.get_admin_context(), share_id) self.assertIsNotNone(actual_share.availability_zone) self.assertEqual(manager.CONF.storage_availability_zone, actual_share.availability_zone) def test_provide_share_server_for_share_incompatible_servers(self): fake_exception = exception.ManilaException("fake") fake_share_server = {'id': 'fake'} share = db_utils.create_share() self.mock_object(db, 'share_server_get_all_by_host_and_share_net_valid', mock.Mock(return_value=[fake_share_server])) self.mock_object( self.share_manager.driver, "choose_share_server_compatible_with_share", mock.Mock(side_effect=fake_exception) ) self.assertRaises(exception.ManilaException, self.share_manager._provide_share_server_for_share, self.context, "fake_id", share.instance) driver_mock = self.share_manager.driver driver_method_mock = ( driver_mock.choose_share_server_compatible_with_share ) driver_method_mock.assert_called_once_with( self.context, [fake_share_server], share.instance, snapshot=None, consistency_group=None) def test_provide_share_server_for_share_invalid_arguments(self): self.assertRaises(ValueError, self.share_manager._provide_share_server_for_share, self.context, None, None) def test_provide_share_server_for_share_parent_ss_not_found(self): fake_parent_id = "fake_server_id" fake_exception = exception.ShareServerNotFound("fake") share = db_utils.create_share() fake_snapshot = { 'share': { 'instance': { 'share_server_id': fake_parent_id } } } self.mock_object(db, 'share_server_get', mock.Mock(side_effect=fake_exception)) self.assertRaises(exception.ShareServerNotFound, self.share_manager._provide_share_server_for_share, self.context, "fake_id", share.instance, snapshot=fake_snapshot) db.share_server_get.assert_called_once_with( self.context, fake_parent_id) def test_provide_share_server_for_share_parent_ss_invalid(self): fake_parent_id = "fake_server_id" share = db_utils.create_share() fake_snapshot = { 'share': { 'instance': { 'share_server_id': fake_parent_id } } } fake_parent_share_server = {'status': 'fake'} self.mock_object(db, 'share_server_get', mock.Mock(return_value=fake_parent_share_server)) self.assertRaises(exception.InvalidShareServer, self.share_manager._provide_share_server_for_share, self.context, "fake_id", share.instance, snapshot=fake_snapshot) db.share_server_get.assert_called_once_with( self.context, fake_parent_id) def test_provide_share_server_for_cg_incompatible_servers(self): fake_exception = exception.ManilaException("fake") fake_share_server = {'id': 'fake'} cg = db_utils.create_consistency_group() self.mock_object(db, 'share_server_get_all_by_host_and_share_net_valid', mock.Mock(return_value=[fake_share_server])) self.mock_object( self.share_manager.driver, "choose_share_server_compatible_with_cg", mock.Mock(side_effect=fake_exception) ) self.assertRaises(exception.ManilaException, self.share_manager._provide_share_server_for_cg, self.context, "fake_id", cg) driver_mock = self.share_manager.driver driver_method_mock = ( driver_mock.choose_share_server_compatible_with_cg ) driver_method_mock.assert_called_once_with( self.context, [fake_share_server], cg, cgsnapshot=None) def test_provide_share_server_for_cg_invalid_arguments(self): self.assertRaises(exception.InvalidInput, self.share_manager._provide_share_server_for_cg, self.context, None, None) def test_manage_share_invalid_driver(self): self.mock_object(self.share_manager, 'driver', mock.Mock()) self.share_manager.driver.driver_handles_share_servers = True self.mock_object(share_types, 'get_share_type_extra_specs', mock.Mock(return_value='False')) self.mock_object(self.share_manager.db, 'share_update', mock.Mock()) share = db_utils.create_share() share_id = share['id'] self.assertRaises( exception.InvalidDriverMode, self.share_manager.manage_share, self.context, share_id, {}) self.share_manager.db.share_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), share_id, {'status': constants.STATUS_MANAGE_ERROR, 'size': 1}) def test_manage_share_invalid_share_type(self): self.mock_object(self.share_manager, 'driver', mock.Mock()) self.share_manager.driver.driver_handles_share_servers = False self.mock_object(share_types, 'get_share_type_extra_specs', mock.Mock(return_value='True')) self.mock_object(self.share_manager.db, 'share_update', mock.Mock()) share = db_utils.create_share() share_id = share['id'] self.assertRaises( exception.ManageExistingShareTypeMismatch, self.share_manager.manage_share, self.context, share_id, {}) self.share_manager.db.share_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), share_id, {'status': constants.STATUS_MANAGE_ERROR, 'size': 1}) def test_manage_share_driver_exception(self): CustomException = type('CustomException', (Exception,), dict()) self.mock_object(self.share_manager, 'driver', mock.Mock()) self.share_manager.driver.driver_handles_share_servers = False self.mock_object(self.share_manager.driver, 'manage_existing', mock.Mock(side_effect=CustomException)) self.mock_object(share_types, 'get_share_type_extra_specs', mock.Mock(return_value='False')) self.mock_object(self.share_manager.db, 'share_update', mock.Mock()) share = db_utils.create_share() share_id = share['id'] driver_options = {'fake': 'fake'} self.assertRaises( CustomException, self.share_manager.manage_share, self.context, share_id, driver_options) self.share_manager.driver.manage_existing.\ assert_called_once_with(mock.ANY, driver_options) self.share_manager.db.share_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), share_id, {'status': constants.STATUS_MANAGE_ERROR, 'size': 1}) def test_manage_share_invalid_size(self): self.mock_object(self.share_manager, 'driver') self.share_manager.driver.driver_handles_share_servers = False self.mock_object(share_types, 'get_share_type_extra_specs', mock.Mock(return_value='False')) self.mock_object(self.share_manager.driver, "manage_existing", mock.Mock(return_value=None)) self.mock_object(self.share_manager.db, 'share_update', mock.Mock()) share = db_utils.create_share() share_id = share['id'] driver_options = {'fake': 'fake'} self.assertRaises( exception.InvalidShare, self.share_manager.manage_share, self.context, share_id, driver_options) self.share_manager.driver.manage_existing.\ assert_called_once_with(mock.ANY, driver_options) self.share_manager.db.share_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), share_id, {'status': constants.STATUS_MANAGE_ERROR, 'size': 1}) def test_manage_share_quota_error(self): self.mock_object(self.share_manager, 'driver') self.share_manager.driver.driver_handles_share_servers = False self.mock_object(share_types, 'get_share_type_extra_specs', mock.Mock(return_value='False')) self.mock_object(self.share_manager.driver, "manage_existing", mock.Mock(return_value={'size': 3})) self.mock_object(self.share_manager, '_update_quota_usages', mock.Mock(side_effect=exception.QuotaError)) self.mock_object(self.share_manager.db, 'share_update', mock.Mock()) share = db_utils.create_share() share_id = share['id'] driver_options = {'fake': 'fake'} self.assertRaises( exception.QuotaError, self.share_manager.manage_share, self.context, share_id, driver_options) self.share_manager.driver.manage_existing.\ assert_called_once_with(mock.ANY, driver_options) self.share_manager.db.share_update.assert_called_once_with( mock.ANY, share_id, {'status': constants.STATUS_MANAGE_ERROR, 'size': 1}) self.share_manager._update_quota_usages.assert_called_once_with( utils.IsAMatcher(context.RequestContext), share['project_id'], {'shares': 1, 'gigabytes': 3}) @ddt.data( {'size': 1}, {'size': 2, 'name': 'fake'}, {'size': 3, 'export_locations': ['foo', 'bar', 'quuz']}) def test_manage_share_valid_share(self, driver_data): export_locations = driver_data.get('export_locations') self.mock_object(self.share_manager.db, 'share_update', mock.Mock()) self.mock_object(self.share_manager, 'driver', mock.Mock()) self.mock_object(self.share_manager, '_update_quota_usages', mock.Mock()) self.mock_object( self.share_manager.db, 'share_export_locations_update', mock.Mock(side_effect=( self.share_manager.db.share_export_locations_update))) self.share_manager.driver.driver_handles_share_servers = False self.mock_object(share_types, 'get_share_type_extra_specs', mock.Mock(return_value='False')) self.mock_object(self.share_manager.driver, "manage_existing", mock.Mock(return_value=driver_data)) share = db_utils.create_share() share_id = share['id'] driver_options = {'fake': 'fake'} self.share_manager.manage_share(self.context, share_id, driver_options) self.share_manager.driver.manage_existing.\ assert_called_once_with(mock.ANY, driver_options) if export_locations: self.share_manager.db.share_export_locations_update.\ assert_called_once_with( utils.IsAMatcher(context.RequestContext), share.instance['id'], export_locations, delete=True) else: self.assertFalse( self.share_manager.db.share_export_locations_update.called) valid_share_data = { 'status': constants.STATUS_AVAILABLE, 'launched_at': mock.ANY} valid_share_data.update(driver_data) self.share_manager.db.share_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), share_id, valid_share_data) def test_update_quota_usages_new(self): self.mock_object(self.share_manager.db, 'quota_usage_get', mock.Mock(return_value={'in_use': 1})) self.mock_object(self.share_manager.db, 'quota_usage_update') project_id = 'fake_project_id' resource_name = 'fake' usage = 1 self.share_manager._update_quota_usages( self.context, project_id, {resource_name: usage}) self.share_manager.db.quota_usage_get.assert_called_once_with( mock.ANY, project_id, resource_name, mock.ANY) self.share_manager.db.quota_usage_update.assert_called_once_with( mock.ANY, project_id, mock.ANY, resource_name, in_use=2) def test_update_quota_usages_update(self): project_id = 'fake_project_id' resource_name = 'fake' usage = 1 side_effect = exception.QuotaUsageNotFound(project_id=project_id) self.mock_object( self.share_manager.db, 'quota_usage_get', mock.Mock(side_effect=side_effect)) self.mock_object(self.share_manager.db, 'quota_usage_create') self.share_manager._update_quota_usages( self.context, project_id, {resource_name: usage}) self.share_manager.db.quota_usage_get.assert_called_once_with( mock.ANY, project_id, resource_name, mock.ANY) self.share_manager.db.quota_usage_create.assert_called_once_with( mock.ANY, project_id, mock.ANY, resource_name, usage) def _setup_unmanage_mocks(self, mock_driver=True, mock_unmanage=None): if mock_driver: self.mock_object(self.share_manager, 'driver') if mock_unmanage: self.mock_object(self.share_manager.driver, "unmanage", mock_unmanage) self.mock_object(self.share_manager.db, 'share_update') self.mock_object(self.share_manager.db, 'share_instance_delete') @ddt.data(True, False) def test_unmanage_share_invalid_driver(self, driver_handles_share_servers): self._setup_unmanage_mocks() self.share_manager.driver.driver_handles_share_servers = ( driver_handles_share_servers ) share_net = db_utils.create_share_network() share_srv = db_utils.create_share_server( share_network_id=share_net['id'], host=self.share_manager.host) share = db_utils.create_share(share_network_id=share_net['id'], share_server_id=share_srv['id']) self.share_manager.unmanage_share(self.context, share['id']) self.share_manager.db.share_update.assert_called_once_with( mock.ANY, share['id'], {'status': constants.STATUS_UNMANAGE_ERROR}) def test_unmanage_share_invalid_share(self): unmanage = mock.Mock(side_effect=exception.InvalidShare(reason="fake")) self._setup_unmanage_mocks(mock_driver=False, mock_unmanage=unmanage) share = db_utils.create_share() self.share_manager.unmanage_share(self.context, share['id']) self.share_manager.db.share_update.assert_called_once_with( mock.ANY, share['id'], {'status': constants.STATUS_UNMANAGE_ERROR}) def test_unmanage_share_valid_share(self): manager.CONF.set_default('driver_handles_share_servers', False) self._setup_unmanage_mocks(mock_driver=False, mock_unmanage=mock.Mock()) share = db_utils.create_share() share_id = share['id'] share_instance_id = share.instance['id'] self.share_manager.unmanage_share(self.context, share_id) self.share_manager.driver.unmanage.\ assert_called_once_with(mock.ANY) self.share_manager.db.share_instance_delete.assert_called_once_with( mock.ANY, share_instance_id) def test_unmanage_share_valid_share_with_quota_error(self): manager.CONF.set_default('driver_handles_share_servers', False) self._setup_unmanage_mocks(mock_driver=False, mock_unmanage=mock.Mock()) self.mock_object(quota.QUOTAS, 'reserve', mock.Mock(side_effect=Exception())) share = db_utils.create_share() share_instance_id = share.instance['id'] self.share_manager.unmanage_share(self.context, share['id']) self.share_manager.driver.unmanage.\ assert_called_once_with(mock.ANY) self.share_manager.db.share_instance_delete.assert_called_once_with( mock.ANY, share_instance_id) def test_unmanage_share_remove_access_rules_error(self): manager.CONF.set_default('driver_handles_share_servers', False) manager.CONF.unmanage_remove_access_rules = True self._setup_unmanage_mocks(mock_driver=False, mock_unmanage=mock.Mock()) self.mock_object( self.share_manager.access_helper, 'update_access_rules', mock.Mock(side_effect=Exception()) ) self.mock_object(quota.QUOTAS, 'reserve', mock.Mock(return_value=[])) share = db_utils.create_share() self.share_manager.unmanage_share(self.context, share['id']) self.share_manager.db.share_update.assert_called_once_with( mock.ANY, share['id'], {'status': constants.STATUS_UNMANAGE_ERROR}) def test_unmanage_share_valid_share_remove_access_rules(self): manager.CONF.set_default('driver_handles_share_servers', False) manager.CONF.unmanage_remove_access_rules = True self._setup_unmanage_mocks(mock_driver=False, mock_unmanage=mock.Mock()) smanager = self.share_manager self.mock_object(smanager.access_helper, 'update_access_rules') self.mock_object(quota.QUOTAS, 'reserve', mock.Mock(return_value=[])) share = db_utils.create_share() share_id = share['id'] share_instance_id = share.instance['id'] smanager.unmanage_share(self.context, share_id) smanager.driver.unmanage.assert_called_once_with(mock.ANY) smanager.access_helper.update_access_rules.assert_called_once_with( mock.ANY, mock.ANY, delete_rules='all', share_server=None ) smanager.db.share_instance_delete.assert_called_once_with( mock.ANY, share_instance_id) def test_delete_share_instance_share_server_not_found(self): share_net = db_utils.create_share_network() share = db_utils.create_share(share_network_id=share_net['id'], share_server_id='fake-id') self.assertRaises( exception.ShareServerNotFound, self.share_manager.delete_share_instance, self.context, share.instance['id'] ) @ddt.data(True, False) def test_delete_share_instance_last_on_srv_with_sec_service( self, with_details): share_net = db_utils.create_share_network() sec_service = db_utils.create_security_service( share_network_id=share_net['id']) backend_details = dict( security_service_ldap=jsonutils.dumps(sec_service)) if with_details: share_srv = db_utils.create_share_server( share_network_id=share_net['id'], host=self.share_manager.host, backend_details=backend_details) else: share_srv = db_utils.create_share_server( share_network_id=share_net['id'], host=self.share_manager.host) db.share_server_backend_details_set( context.get_admin_context(), share_srv['id'], backend_details) share = db_utils.create_share(share_network_id=share_net['id'], share_server_id=share_srv['id']) self.share_manager.driver = mock.Mock() manager.CONF.delete_share_server_with_last_share = True self.share_manager.delete_share_instance(self.context, share.instance['id']) self.share_manager.driver.teardown_server.assert_called_once_with( server_details=backend_details, security_services=[jsonutils.loads( backend_details['security_service_ldap'])]) @ddt.data({'force': True, 'side_effect': 'update_access'}, {'force': True, 'side_effect': 'delete_share'}, {'force': False, 'side_effect': None}) @ddt.unpack def test_delete_share_instance_last_on_server(self, force, side_effect): share_net = db_utils.create_share_network() share_srv = db_utils.create_share_server( share_network_id=share_net['id'], host=self.share_manager.host ) share = db_utils.create_share(share_network_id=share_net['id'], share_server_id=share_srv['id']) self.share_manager.driver = mock.Mock() if side_effect == 'update_access': self.mock_object( self.share_manager.access_helper, 'update_access_rules', mock.Mock(side_effect=Exception('fake'))) if side_effect == 'delete_share': self.mock_object(self.share_manager.driver, 'delete_share', mock.Mock(side_effect=Exception('fake'))) self.mock_object(manager.LOG, 'error') manager.CONF.delete_share_server_with_last_share = True self.share_manager.delete_share_instance( self.context, share.instance['id'], force=force) self.share_manager.driver.teardown_server.assert_called_once_with( server_details=share_srv.get('backend_details'), security_services=[]) self.assertEqual(force, manager.LOG.error.called) def test_delete_share_instance_last_on_server_deletion_disabled(self): share_net = db_utils.create_share_network() share_srv = db_utils.create_share_server( share_network_id=share_net['id'], host=self.share_manager.host ) share = db_utils.create_share(share_network_id=share_net['id'], share_server_id=share_srv['id']) manager.CONF.delete_share_server_with_last_share = False self.share_manager.driver = mock.Mock() self.share_manager.delete_share_instance(self.context, share.instance['id']) self.assertFalse(self.share_manager.driver.teardown_network.called) def test_delete_share_instance_not_last_on_server(self): share_net = db_utils.create_share_network() share_srv = db_utils.create_share_server( share_network_id=share_net['id'], host=self.share_manager.host ) share = db_utils.create_share(share_network_id=share_net['id'], share_server_id=share_srv['id']) db_utils.create_share(share_network_id=share_net['id'], share_server_id=share_srv['id']) manager.CONF.delete_share_server_with_last_share = True self.share_manager.driver = mock.Mock() self.share_manager.delete_share_instance(self.context, share.instance['id']) self.assertFalse(self.share_manager.driver.teardown_network.called) @ddt.data('update_access', 'delete_share') def test_delete_share_instance_not_found(self, side_effect): share_net = db_utils.create_share_network() share_srv = db_utils.create_share_server( share_network_id=share_net['id'], host=self.share_manager.host) share = db_utils.create_share(share_network_id=share_net['id'], share_server_id=share_srv['id']) access = db_utils.create_access(share_id=share['id']) db_utils.create_share(share_network_id=share_net['id'], share_server_id=share_srv['id']) manager.CONF.delete_share_server_with_last_share = False self.mock_object(db, 'share_server_get', mock.Mock(return_value=share_srv)) self.mock_object(db, 'share_instance_get', mock.Mock(return_value=share.instance)) self.mock_object(db, 'share_access_get_all_for_instance', mock.Mock(return_value=[access])) self.share_manager.driver = mock.Mock() self.share_manager.access_helper.driver = mock.Mock() if side_effect == 'update_access': self.mock_object( self.share_manager.access_helper.driver, 'update_access', mock.Mock(side_effect=exception.ShareResourceNotFound( share_id=share['id']))) if side_effect == 'delete_share': self.mock_object( self.share_manager.driver, 'delete_share', mock.Mock(side_effect=exception.ShareResourceNotFound( share_id=share['id']))) self.mock_object( self.share_manager.access_helper, '_check_needs_refresh', mock.Mock(return_value=False) ) self.mock_object(manager.LOG, 'warning') self.share_manager.delete_share_instance(self.context, share.instance['id']) self.assertFalse(self.share_manager.driver.teardown_network.called) (self.share_manager.access_helper.driver.update_access. assert_called_once_with(utils.IsAMatcher( context.RequestContext), share.instance, [], add_rules=[], delete_rules=[access], share_server=share_srv)) self.assertTrue(manager.LOG.warning.called) def test_allow_deny_access(self): """Test access rules to share can be created and deleted.""" self.mock_object(share_access.LOG, 'info') share = db_utils.create_share() share_id = share['id'] share_instance = db_utils.create_share_instance( share_id=share_id, access_rules_status=constants.STATUS_OUT_OF_SYNC) share_instance_id = share_instance['id'] access = db_utils.create_access(share_id=share_id, share_instance_id=share_instance_id) access_id = access['id'] self.share_manager.allow_access(self.context, share_instance_id, [access_id]) self.assertEqual('active', db.share_instance_get( self.context, share_instance_id).access_rules_status) share_access.LOG.info.assert_called_with(mock.ANY, share_instance_id) share_access.LOG.info.reset_mock() self.share_manager.deny_access(self.context, share_instance_id, [access_id]) share_access.LOG.info.assert_called_with(mock.ANY, share_instance_id) share_access.LOG.info.reset_mock() def test_allow_deny_access_error(self): """Test access rules to share can be created and deleted with error.""" def _fake_allow_access(self, *args, **kwargs): raise exception.NotFound() def _fake_deny_access(self, *args, **kwargs): raise exception.NotFound() self.mock_object(self.share_manager.access_helper.driver, "allow_access", _fake_allow_access) self.mock_object(self.share_manager.access_helper.driver, "deny_access", _fake_deny_access) share = db_utils.create_share() share_id = share['id'] share_instance = db_utils.create_share_instance( share_id=share_id, access_rules_status=constants.STATUS_OUT_OF_SYNC) share_instance_id = share_instance['id'] access = db_utils.create_access(share_id=share_id, share_instance_id=share_instance_id) access_id = access['id'] def validate(method): self.assertRaises(exception.ManilaException, method, self.context, share_instance_id, [access_id]) inst = db.share_instance_get(self.context, share_instance_id) self.assertEqual(constants.STATUS_ERROR, inst['access_rules_status']) validate(self.share_manager.allow_access) validate(self.share_manager.deny_access) def test_setup_server(self): # Setup required test data share_server = { 'id': 'fake_id', 'share_network_id': 'fake_sn_id', } metadata = {'fake_metadata_key': 'fake_metadata_value'} share_network = {'id': 'fake_sn_id'} network_info = {'security_services': []} for ss_type in constants.SECURITY_SERVICES_ALLOWED_TYPES: network_info['security_services'].append({ 'name': 'fake_name' + ss_type, 'domain': 'fake_domain' + ss_type, 'server': 'fake_server' + ss_type, 'dns_ip': 'fake_dns_ip' + ss_type, 'user': 'fake_user' + ss_type, 'type': ss_type, 'password': 'fake_password' + ss_type, }) sec_services = network_info['security_services'] server_info = {'fake_server_info_key': 'fake_server_info_value'} network_info['network_type'] = 'fake_network_type' # mock required stuff self.mock_object(self.share_manager.db, 'share_network_get', mock.Mock(return_value=share_network)) self.mock_object(self.share_manager.driver, 'allocate_network') self.mock_object(self.share_manager, '_form_server_setup_info', mock.Mock(return_value=network_info)) self.mock_object(self.share_manager, '_validate_segmentation_id') self.mock_object(self.share_manager.driver, 'setup_server', mock.Mock(return_value=server_info)) self.mock_object(self.share_manager.db, 'share_server_backend_details_set') self.mock_object(self.share_manager.db, 'share_server_update', mock.Mock(return_value=share_server)) # execute method _setup_server result = self.share_manager._setup_server( self.context, share_server, metadata=metadata) # verify results self.assertEqual(share_server, result) self.share_manager.db.share_network_get.assert_has_calls([ mock.call(self.context, share_server['share_network_id']), mock.call(self.context, share_server['share_network_id']), ]) self.share_manager.driver.allocate_network.assert_called_once_with( self.context, share_server, share_network) self.share_manager._form_server_setup_info.assert_called_once_with( self.context, share_server, share_network) self.share_manager._validate_segmentation_id.assert_called_once_with( network_info) self.share_manager.driver.setup_server.assert_called_once_with( network_info, metadata=metadata) self.share_manager.db.share_server_backend_details_set.\ assert_has_calls([ mock.call(self.context, share_server['id'], {'security_service_' + sec_services[0]['type']: jsonutils.dumps(sec_services[0])}), mock.call(self.context, share_server['id'], {'security_service_' + sec_services[1]['type']: jsonutils.dumps(sec_services[1])}), mock.call(self.context, share_server['id'], {'security_service_' + sec_services[2]['type']: jsonutils.dumps(sec_services[2])}), mock.call(self.context, share_server['id'], server_info), ]) self.share_manager.db.share_server_update.assert_called_once_with( self.context, share_server['id'], {'status': constants.STATUS_ACTIVE}) def test_setup_server_server_info_not_present(self): # Setup required test data share_server = { 'id': 'fake_id', 'share_network_id': 'fake_sn_id', } metadata = {'fake_metadata_key': 'fake_metadata_value'} share_network = {'id': 'fake_sn_id'} network_info = { 'fake_network_info_key': 'fake_network_info_value', 'security_services': [], 'network_type': 'fake_network_type', } server_info = {} # mock required stuff self.mock_object(self.share_manager.db, 'share_network_get', mock.Mock(return_value=share_network)) self.mock_object(self.share_manager, '_form_server_setup_info', mock.Mock(return_value=network_info)) self.mock_object(self.share_manager.driver, 'setup_server', mock.Mock(return_value=server_info)) self.mock_object(self.share_manager.db, 'share_server_update', mock.Mock(return_value=share_server)) self.mock_object(self.share_manager.driver, 'allocate_network') # execute method _setup_server result = self.share_manager._setup_server( self.context, share_server, metadata=metadata) # verify results self.assertEqual(share_server, result) self.share_manager.db.share_network_get.assert_has_calls([ mock.call(self.context, share_server['share_network_id']), mock.call(self.context, share_server['share_network_id'])]) self.share_manager._form_server_setup_info.assert_called_once_with( self.context, share_server, share_network) self.share_manager.driver.setup_server.assert_called_once_with( network_info, metadata=metadata) self.share_manager.db.share_server_update.assert_called_once_with( self.context, share_server['id'], {'status': constants.STATUS_ACTIVE}) self.share_manager.driver.allocate_network.assert_called_once_with( self.context, share_server, share_network) def setup_server_raise_exception(self, detail_data_proper): # Setup required test data share_server = { 'id': 'fake_id', 'share_network_id': 'fake_sn_id', } server_info = {'details_key': 'value'} share_network = {'id': 'fake_sn_id'} network_info = { 'fake_network_info_key': 'fake_network_info_value', 'security_services': [], 'network_type': 'fake_network_type', } if detail_data_proper: detail_data = {'server_details': server_info} self.mock_object(self.share_manager.db, 'share_server_backend_details_set') else: detail_data = 'not dictionary detail data' # Mock required parameters self.mock_object(self.share_manager.db, 'share_network_get', mock.Mock(return_value=share_network)) self.mock_object(self.share_manager.db, 'share_server_update') for m in ['deallocate_network', 'allocate_network']: self.mock_object(self.share_manager.driver, m) self.mock_object(self.share_manager, '_form_server_setup_info', mock.Mock(return_value=network_info)) self.mock_object(self.share_manager.db, 'share_server_backend_details_set') self.mock_object(self.share_manager.driver, 'setup_server', mock.Mock(side_effect=exception.ManilaException( detail_data=detail_data))) # execute method _setup_server self.assertRaises( exception.ManilaException, self.share_manager._setup_server, self.context, share_server, ) # verify results if detail_data_proper: self.share_manager.db.share_server_backend_details_set.\ assert_called_once_with( self.context, share_server['id'], server_info) self.share_manager._form_server_setup_info.assert_called_once_with( self.context, share_server, share_network) self.share_manager.db.share_server_update.assert_called_once_with( self.context, share_server['id'], {'status': constants.STATUS_ERROR}) self.share_manager.db.share_network_get.assert_has_calls([ mock.call(self.context, share_server['share_network_id']), mock.call(self.context, share_server['share_network_id'])]) self.share_manager.driver.allocate_network.assert_has_calls([ mock.call(self.context, share_server, share_network)]) self.share_manager.driver.deallocate_network.assert_has_calls([ mock.call(self.context, share_server['id'])]) def test_setup_server_incorrect_detail_data(self): self.setup_server_raise_exception(detail_data_proper=False) def test_setup_server_exception_in_driver(self): self.setup_server_raise_exception(detail_data_proper=True) @ddt.data({}, {'detail_data': 'fake'}, {'detail_data': {'server_details': 'fake'}}, {'detail_data': {'server_details': {'fake': 'fake'}}}, {'detail_data': { 'server_details': {'fake': 'fake', 'fake2': 'fake2'}}},) def test_setup_server_exception_in_cleanup_after_error(self, data): def get_server_details_from_data(data): d = data.get('detail_data') if not isinstance(d, dict): return {} d = d.get('server_details') if not isinstance(d, dict): return {} return d share_server = {'id': 'fake', 'share_network_id': 'fake'} details = get_server_details_from_data(data) exc_mock = mock.Mock(side_effect=exception.ManilaException(**data)) details_mock = mock.Mock(side_effect=exception.ManilaException()) self.mock_object(self.share_manager.db, 'share_network_get', exc_mock) self.mock_object(self.share_manager.db, 'share_server_backend_details_set', details_mock) self.mock_object(self.share_manager.db, 'share_server_update') self.mock_object(self.share_manager.driver, 'deallocate_network') self.mock_object(manager.LOG, 'debug') self.mock_object(manager.LOG, 'warning') self.assertRaises( exception.ManilaException, self.share_manager._setup_server, self.context, share_server, ) self.assertTrue(self.share_manager.db.share_network_get.called) if details: self.assertEqual(len(details), details_mock.call_count) expected = [mock.call(mock.ANY, share_server['id'], {k: v}) for k, v in details.items()] self.assertEqual(expected, details_mock.call_args_list) self.share_manager.db.share_server_update.assert_called_once_with( self.context, share_server['id'], {'status': constants.STATUS_ERROR}) self.share_manager.driver.deallocate_network.assert_called_once_with( self.context, share_server['id'] ) self.assertFalse(manager.LOG.warning.called) if get_server_details_from_data(data): self.assertTrue(manager.LOG.debug.called) def test_ensure_share_instance_has_pool_with_only_host(self): fake_share = { 'status': constants.STATUS_AVAILABLE, 'host': 'host1', 'id': 1} host = self.share_manager._ensure_share_instance_has_pool( context.get_admin_context(), fake_share) self.assertIsNone(host) def test_ensure_share_instance_has_pool_with_full_pool_name(self): fake_share = {'host': 'host1#pool0', 'id': 1, 'status': constants.STATUS_AVAILABLE} fake_share_expected_value = 'pool0' host = self.share_manager._ensure_share_instance_has_pool( context.get_admin_context(), fake_share) self.assertEqual(fake_share_expected_value, host) def test_ensure_share_instance_has_pool_unable_to_fetch_share(self): fake_share = {'host': 'host@backend', 'id': 1, 'status': constants.STATUS_AVAILABLE} with mock.patch.object(self.share_manager.driver, 'get_pool', side_effect=Exception): with mock.patch.object(manager, 'LOG') as mock_LOG: self.share_manager._ensure_share_instance_has_pool( context.get_admin_context(), fake_share) self.assertEqual(1, mock_LOG.error.call_count) def test__form_server_setup_info(self): def fake_network_allocations_get_for_share_server(*args, **kwargs): if kwargs.get('label') != 'admin': return ['foo', 'bar'] return ['admin-foo', 'admin-bar'] self.mock_object( self.share_manager.db, 'network_allocations_get_for_share_server', mock.Mock( side_effect=fake_network_allocations_get_for_share_server)) fake_share_server = dict( id='fake_share_server_id', backend_details=dict(foo='bar')) fake_share_network = dict( segmentation_id='fake_segmentation_id', cidr='fake_cidr', neutron_net_id='fake_neutron_net_id', neutron_subnet_id='fake_neutron_subnet_id', nova_net_id='fake_nova_net_id', security_services='fake_security_services', network_type='fake_network_type') expected = dict( server_id=fake_share_server['id'], segmentation_id=fake_share_network['segmentation_id'], cidr=fake_share_network['cidr'], neutron_net_id=fake_share_network['neutron_net_id'], neutron_subnet_id=fake_share_network['neutron_subnet_id'], nova_net_id=fake_share_network['nova_net_id'], security_services=fake_share_network['security_services'], network_allocations=( fake_network_allocations_get_for_share_server()), admin_network_allocations=( fake_network_allocations_get_for_share_server(label='admin')), backend_details=fake_share_server['backend_details'], network_type=fake_share_network['network_type']) network_info = self.share_manager._form_server_setup_info( self.context, fake_share_server, fake_share_network) self.assertEqual(expected, network_info) self.share_manager.db.network_allocations_get_for_share_server.\ assert_has_calls([ mock.call(self.context, fake_share_server['id'], label='user'), mock.call(self.context, fake_share_server['id'], label='admin') ]) @ddt.data( {'network_info': {'network_type': 'vlan', 'segmentation_id': '100'}}, {'network_info': {'network_type': 'vlan', 'segmentation_id': '1'}}, {'network_info': {'network_type': 'vlan', 'segmentation_id': '4094'}}, {'network_info': {'network_type': 'vxlan', 'segmentation_id': '100'}}, {'network_info': {'network_type': 'vxlan', 'segmentation_id': '1'}}, {'network_info': {'network_type': 'vxlan', 'segmentation_id': '16777215'}}, {'network_info': {'network_type': 'gre', 'segmentation_id': '100'}}, {'network_info': {'network_type': 'gre', 'segmentation_id': '1'}}, {'network_info': {'network_type': 'gre', 'segmentation_id': '4294967295'}}, {'network_info': {'network_type': 'flat', 'segmentation_id': None}}, {'network_info': {'network_type': 'flat', 'segmentation_id': 0}}, {'network_info': {'network_type': None, 'segmentation_id': None}}, {'network_info': {'network_type': None, 'segmentation_id': 0}}) @ddt.unpack def test_validate_segmentation_id_with_valid_values(self, network_info): self.share_manager._validate_segmentation_id(network_info) @ddt.data( {'network_info': {'network_type': 'vlan', 'segmentation_id': None}}, {'network_info': {'network_type': 'vlan', 'segmentation_id': -1}}, {'network_info': {'network_type': 'vlan', 'segmentation_id': 0}}, {'network_info': {'network_type': 'vlan', 'segmentation_id': '4095'}}, {'network_info': {'network_type': 'vxlan', 'segmentation_id': None}}, {'network_info': {'network_type': 'vxlan', 'segmentation_id': 0}}, {'network_info': {'network_type': 'vxlan', 'segmentation_id': '16777216'}}, {'network_info': {'network_type': 'gre', 'segmentation_id': None}}, {'network_info': {'network_type': 'gre', 'segmentation_id': 0}}, {'network_info': {'network_type': 'gre', 'segmentation_id': '4294967296'}}, {'network_info': {'network_type': 'flat', 'segmentation_id': '1000'}}, {'network_info': {'network_type': None, 'segmentation_id': '1000'}}) @ddt.unpack def test_validate_segmentation_id_with_invalid_values(self, network_info): self.assertRaises(exception.NetworkBadConfigurationException, self.share_manager._validate_segmentation_id, network_info) @ddt.data(5, 70) def test_verify_server_cleanup_interval_invalid_cases(self, val): data = dict(DEFAULT=dict(unused_share_server_cleanup_interval=val)) with test_utils.create_temp_config_with_opts(data): self.assertRaises(exception.InvalidParameterValue, manager.ShareManager) @ddt.data(10, 36, 60) def test_verify_server_cleanup_interval_valid_cases(self, val): data = dict(DEFAULT=dict(unused_share_server_cleanup_interval=val)) with test_utils.create_temp_config_with_opts(data): manager.ShareManager() @mock.patch.object(db, 'share_server_get_all_unused_deletable', mock.Mock()) @mock.patch.object(manager.ShareManager, 'delete_share_server', mock.Mock()) def test_delete_free_share_servers_cleanup_disabled(self): data = dict(DEFAULT=dict(automatic_share_server_cleanup=False)) with test_utils.create_temp_config_with_opts(data): share_manager = manager.ShareManager() share_manager.driver.initialized = True share_manager.delete_free_share_servers(self.context) self.assertFalse(db.share_server_get_all_unused_deletable.called) @mock.patch.object(db, 'share_server_get_all_unused_deletable', mock.Mock()) @mock.patch.object(manager.ShareManager, 'delete_share_server', mock.Mock()) def test_delete_free_share_servers_driver_handles_ss_disabled(self): data = dict(DEFAULT=dict(driver_handles_share_servers=False)) with test_utils.create_temp_config_with_opts(data): share_manager = manager.ShareManager() share_manager.driver.initialized = True share_manager.delete_free_share_servers(self.context) self.assertFalse(db.share_server_get_all_unused_deletable.called) self.assertFalse(share_manager.delete_share_server.called) @mock.patch.object(db, 'share_server_get_all_unused_deletable', mock.Mock(return_value=['server1', ])) @mock.patch.object(manager.ShareManager, 'delete_share_server', mock.Mock()) @mock.patch.object(timeutils, 'utcnow', mock.Mock( return_value=datetime.timedelta(minutes=20))) def test_delete_free_share_servers(self): self.share_manager.delete_free_share_servers(self.context) db.share_server_get_all_unused_deletable.assert_called_once_with( self.context, self.share_manager.host, datetime.timedelta(minutes=10)) self.share_manager.delete_share_server.assert_called_once_with( self.context, 'server1') timeutils.utcnow.assert_called_once_with() def test_extend_share_invalid(self): share = db_utils.create_share() share_id = share['id'] reservations = {} self.mock_object(self.share_manager, 'driver') self.mock_object(self.share_manager.db, 'share_update') self.mock_object(quota.QUOTAS, 'rollback') self.mock_object(self.share_manager.driver, 'extend_share', mock.Mock(side_effect=Exception('fake'))) self.assertRaises( exception.ShareExtendingError, self.share_manager.extend_share, self.context, share_id, 123, {}) quota.QUOTAS.rollback.assert_called_once_with( mock.ANY, reservations, project_id=six.text_type(share['project_id']), user_id=six.text_type(share['user_id']) ) def test_extend_share(self): share = db_utils.create_share() share_id = share['id'] new_size = 123 shr_update = { 'size': int(new_size), 'status': constants.STATUS_AVAILABLE.lower() } reservations = {} fake_share_server = 'fake' manager = self.share_manager self.mock_object(manager, 'driver') self.mock_object(manager.db, 'share_get', mock.Mock(return_value=share)) self.mock_object(manager.db, 'share_update', mock.Mock(return_value=share)) self.mock_object(quota.QUOTAS, 'commit') self.mock_object(manager.driver, 'extend_share') self.mock_object(manager, '_get_share_server', mock.Mock(return_value=fake_share_server)) self.share_manager.extend_share(self.context, share_id, new_size, reservations) self.assertTrue(manager._get_share_server.called) manager.driver.extend_share.assert_called_once_with( utils.IsAMatcher(models.ShareInstance), new_size, share_server=fake_share_server ) quota.QUOTAS.commit.assert_called_once_with( mock.ANY, reservations, project_id=share['project_id'], user_id=share['user_id']) manager.db.share_update.assert_called_once_with( mock.ANY, share_id, shr_update ) def test_shrink_share_quota_error(self): size = 5 new_size = 1 share = db_utils.create_share(size=size) share_id = share['id'] self.mock_object(self.share_manager.db, 'share_update') self.mock_object(quota.QUOTAS, 'reserve', mock.Mock(side_effect=Exception('fake'))) self.assertRaises( exception.ShareShrinkingError, self.share_manager.shrink_share, self.context, share_id, new_size) quota.QUOTAS.reserve.assert_called_with( mock.ANY, project_id=six.text_type(share['project_id']), user_id=six.text_type(share['user_id']), gigabytes=new_size - size ) self.assertTrue(self.share_manager.db.share_update.called) @ddt.data({'exc': exception.InvalidShare('fake'), 'status': constants.STATUS_SHRINKING_ERROR}, {'exc': exception.ShareShrinkingPossibleDataLoss("fake"), 'status': constants.STATUS_SHRINKING_POSSIBLE_DATA_LOSS_ERROR}) @ddt.unpack def test_shrink_share_invalid(self, exc, status): share = db_utils.create_share() new_size = 1 share_id = share['id'] size_decrease = int(share['size']) - new_size self.mock_object(self.share_manager, 'driver') self.mock_object(self.share_manager.db, 'share_update') self.mock_object(self.share_manager.db, 'share_get', mock.Mock(return_value=share)) self.mock_object(quota.QUOTAS, 'reserve') self.mock_object(quota.QUOTAS, 'rollback') self.mock_object(self.share_manager.driver, 'shrink_share', mock.Mock(side_effect=exc)) self.assertRaises( exception.ShareShrinkingError, self.share_manager.shrink_share, self.context, share_id, new_size) self.share_manager.driver.shrink_share.assert_called_once_with( utils.IsAMatcher(models.ShareInstance), new_size, share_server=None ) self.share_manager.db.share_update.assert_called_once_with( mock.ANY, share_id, {'status': status} ) quota.QUOTAS.reserve.assert_called_once_with( mock.ANY, gigabytes=-size_decrease, project_id=share['project_id'], user_id=share['user_id'] ) quota.QUOTAS.rollback.assert_called_once_with( mock.ANY, mock.ANY, project_id=share['project_id'], user_id=share['user_id'] ) self.assertTrue(self.share_manager.db.share_get.called) def test_shrink_share(self): share = db_utils.create_share() share_id = share['id'] new_size = 123 shr_update = { 'size': int(new_size), 'status': constants.STATUS_AVAILABLE } fake_share_server = 'fake' size_decrease = int(share['size']) - new_size manager = self.share_manager self.mock_object(manager, 'driver') self.mock_object(manager.db, 'share_get', mock.Mock(return_value=share)) self.mock_object(manager.db, 'share_update', mock.Mock(return_value=share)) self.mock_object(quota.QUOTAS, 'commit') self.mock_object(quota.QUOTAS, 'reserve') self.mock_object(manager.driver, 'shrink_share') self.mock_object(manager, '_get_share_server', mock.Mock(return_value=fake_share_server)) self.share_manager.shrink_share(self.context, share_id, new_size) self.assertTrue(manager._get_share_server.called) manager.driver.shrink_share.assert_called_once_with( utils.IsAMatcher(models.ShareInstance), new_size, share_server=fake_share_server ) quota.QUOTAS.reserve.assert_called_once_with( mock.ANY, gigabytes=-size_decrease, project_id=share['project_id'], user_id=share['user_id'] ) quota.QUOTAS.commit.assert_called_once_with( mock.ANY, mock.ANY, project_id=share['project_id'], user_id=share['user_id'] ) manager.db.share_update.assert_called_once_with( mock.ANY, share_id, shr_update ) def test_report_driver_status_driver_handles_ss_false(self): fake_stats = {'field': 'val'} fake_pool = {'name': 'pool1'} self.share_manager.last_capabilities = {'field': 'old_val'} self.mock_object(self.share_manager, 'driver', mock.Mock()) driver = self.share_manager.driver driver.get_share_stats = mock.Mock(return_value=fake_stats) self.mock_object(db, 'share_server_get_all_by_host', mock.Mock()) driver.driver_handles_share_servers = False driver.get_share_server_pools = mock.Mock(return_value=fake_pool) self.share_manager._report_driver_status(self.context) driver.get_share_stats.assert_called_once_with( refresh=True) self.assertFalse(db.share_server_get_all_by_host.called) self.assertFalse(driver.get_share_server_pools.called) self.assertEqual(fake_stats, self.share_manager.last_capabilities) def test_report_driver_status_driver_handles_ss(self): fake_stats = {'field': 'val'} fake_ss = {'id': '1234'} fake_pool = {'name': 'pool1'} self.mock_object(self.share_manager, 'driver', mock.Mock()) driver = self.share_manager.driver driver.get_share_stats = mock.Mock(return_value=fake_stats) self.mock_object(db, 'share_server_get_all_by_host', mock.Mock( return_value=[fake_ss])) driver.driver_handles_share_servers = True driver.get_share_server_pools = mock.Mock(return_value=fake_pool) self.share_manager._report_driver_status(self.context) driver.get_share_stats.assert_called_once_with(refresh=True) db.share_server_get_all_by_host.assert_called_once_with( self.context, self.share_manager.host) driver.get_share_server_pools.assert_called_once_with(fake_ss) expected_stats = { 'field': 'val', 'server_pools_mapping': { '1234': fake_pool}, } self.assertEqual(expected_stats, self.share_manager.last_capabilities) def test_report_driver_status_empty_share_stats(self): old_capabilities = {'field': 'old_val'} fake_pool = {'name': 'pool1'} self.share_manager.last_capabilities = old_capabilities self.mock_object(self.share_manager, 'driver', mock.Mock()) driver = self.share_manager.driver driver.get_share_stats = mock.Mock(return_value={}) self.mock_object(db, 'share_server_get_all_by_host', mock.Mock()) driver.driver_handles_share_servers = True driver.get_share_server_pools = mock.Mock(return_value=fake_pool) self.share_manager._report_driver_status(self.context) driver.get_share_stats.assert_called_once_with(refresh=True) self.assertFalse(db.share_server_get_all_by_host.called) self.assertFalse(driver.get_share_server_pools.called) self.assertEqual(old_capabilities, self.share_manager.last_capabilities) def test_create_consistency_group(self): fake_cg = {'id': 'fake_id'} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'consistency_group_update', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.driver, 'create_consistency_group', mock.Mock(return_value=None)) self.share_manager.create_consistency_group(self.context, "fake_id") self.share_manager.db.consistency_group_update.\ assert_called_once_with(mock.ANY, 'fake_id', {'status': constants.STATUS_AVAILABLE, 'created_at': mock.ANY}) def test_create_cg_with_share_network_driver_not_handles_servers(self): manager.CONF.set_default('driver_handles_share_servers', False) self.mock_object( self.share_manager.driver.configuration, 'safe_get', mock.Mock(return_value=False)) cg_id = 'fake_cg_id' share_network_id = 'fake_sn' fake_cg = {'id': 'fake_id', 'share_network_id': share_network_id} self.mock_object( self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'consistency_group_update') self.assertRaises( exception.ManilaException, self.share_manager.create_consistency_group, self.context, cg_id) self.share_manager.db.consistency_group_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), cg_id) self.share_manager.db.consistency_group_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), cg_id, {'status': constants.STATUS_ERROR}) def test_create_cg_with_share_network_driver_handles_servers(self): manager.CONF.set_default('driver_handles_share_servers', True) self.mock_object( self.share_manager.driver.configuration, 'safe_get', mock.Mock(return_value=True)) share_network_id = 'fake_sn' fake_cg = {'id': 'fake_id', 'share_network_id': share_network_id, 'host': "fake_host"} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'consistency_group_update', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager, '_provide_share_server_for_cg', mock.Mock(return_value=({}, fake_cg))) self.mock_object(self.share_manager.driver, 'create_consistency_group', mock.Mock(return_value=None)) self.share_manager.create_consistency_group(self.context, "fake_id") self.share_manager.db.consistency_group_update.\ assert_called_once_with(mock.ANY, 'fake_id', {'status': constants.STATUS_AVAILABLE, 'created_at': mock.ANY}) def test_create_consistency_group_with_update(self): fake_cg = {'id': 'fake_id'} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'consistency_group_update', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.driver, 'create_consistency_group', mock.Mock(return_value={'foo': 'bar'})) self.share_manager.create_consistency_group(self.context, "fake_id") self.share_manager.db.consistency_group_update.\ assert_any_call(mock.ANY, 'fake_id', {'foo': 'bar'}) self.share_manager.db.consistency_group_update.\ assert_any_call(mock.ANY, 'fake_id', {'status': constants.STATUS_AVAILABLE, 'created_at': mock.ANY}) def test_create_consistency_group_with_error(self): fake_cg = {'id': 'fake_id'} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'consistency_group_update', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.driver, 'create_consistency_group', mock.Mock(side_effect=exception.Error)) self.assertRaises(exception.Error, self.share_manager.create_consistency_group, self.context, "fake_id") self.share_manager.db.consistency_group_update.\ assert_called_once_with(mock.ANY, 'fake_id', {'status': constants.STATUS_ERROR}) def test_create_consistency_group_from_cgsnapshot(self): fake_cg = {'id': 'fake_id', 'source_cgsnapshot_id': 'fake_snap_id', 'shares': [], 'share_server_id': 'fake_ss_id'} fake_ss = {'id': 'fake_ss_id', 'share_network_id': 'fake_sn'} fake_snap = {'id': 'fake_snap_id', 'cgsnapshot_members': [], 'consistency_group': {'share_server_id': fake_ss['id']}} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'cgsnapshot_get', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'share_server_get', mock.Mock( return_value=fake_ss)) self.mock_object(self.share_manager.db, 'consistency_group_update', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.driver, 'create_consistency_group_from_cgsnapshot', mock.Mock(return_value=(None, None))) self.share_manager.create_consistency_group(self.context, "fake_id") self.share_manager.db.consistency_group_update.\ assert_called_once_with(mock.ANY, 'fake_id', {'status': constants.STATUS_AVAILABLE, 'created_at': mock.ANY}) self.share_manager.db.share_server_get(mock.ANY, 'fake_ss_id') self.share_manager.driver.create_consistency_group_from_cgsnapshot.\ assert_called_once_with( mock.ANY, fake_cg, fake_snap, share_server=fake_ss) def test_create_cg_cgsnapshot_share_network_driver_not_handles_servers( self): manager.CONF.set_default('driver_handles_share_servers', False) self.mock_object( self.share_manager.driver.configuration, 'safe_get', mock.Mock(return_value=False)) cg_id = 'fake_cg_id' share_network_id = 'fake_sn' fake_cg = {'id': 'fake_id', 'source_cgsnapshot_id': 'fake_snap_id', 'shares': [], 'share_network_id': share_network_id, 'host': "fake_host"} self.mock_object( self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) fake_snap = {'id': 'fake_snap_id', 'cgsnapshot_members': []} self.mock_object(self.share_manager.db, 'cgsnapshot_get', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'consistency_group_update') self.assertRaises(exception.ManilaException, self.share_manager.create_consistency_group, self.context, cg_id) self.share_manager.db.consistency_group_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), cg_id) self.share_manager.db.consistency_group_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), cg_id, {'status': constants.STATUS_ERROR}) def test_create_cg_from_cgsnapshot_share_network_driver_handles_servers( self): manager.CONF.set_default('driver_handles_share_servers', True) self.mock_object(self.share_manager.driver.configuration, 'safe_get', mock.Mock(return_value=True)) share_network_id = 'fake_sn' fake_cg = {'id': 'fake_id', 'source_cgsnapshot_id': 'fake_snap_id', 'shares': [], 'share_network_id': share_network_id} fake_snap = {'id': 'fake_snap_id', 'cgsnapshot_members': []} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'cgsnapshot_get', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'consistency_group_update', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager, '_provide_share_server_for_cg', mock.Mock(return_value=({}, fake_cg))) self.mock_object(self.share_manager.driver, 'create_consistency_group_from_cgsnapshot', mock.Mock(return_value=(None, None))) self.share_manager.create_consistency_group(self.context, "fake_id") self.share_manager.db.consistency_group_update.\ assert_called_once_with(mock.ANY, 'fake_id', {'status': constants.STATUS_AVAILABLE, 'created_at': mock.ANY}) def test_create_consistency_group_from_cgsnapshot_with_update(self): fake_cg = {'id': 'fake_id', 'source_cgsnapshot_id': 'fake_snap_id', 'shares': []} fake_snap = {'id': 'fake_snap_id', 'cgsnapshot_members': []} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'cgsnapshot_get', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'consistency_group_update', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.driver, 'create_consistency_group_from_cgsnapshot', mock.Mock(return_value=({'foo': 'bar'}, None))) self.share_manager.create_consistency_group(self.context, "fake_id") self.share_manager.db.consistency_group_update.\ assert_any_call(mock.ANY, 'fake_id', {'foo': 'bar'}) self.share_manager.db.consistency_group_update.\ assert_any_call(mock.ANY, 'fake_id', {'status': constants.STATUS_AVAILABLE, 'created_at': mock.ANY}) def test_create_consistency_group_from_cgsnapshot_with_share_update(self): fake_share = {'id': 'fake_share_id'} fake_export_locations = ['my_export_location'] fake_cg = {'id': 'fake_id', 'source_cgsnapshot_id': 'fake_snap_id', 'shares': [fake_share]} fake_snap = {'id': 'fake_snap_id', 'cgsnapshot_members': []} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'cgsnapshot_get', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'consistency_group_update') self.mock_object(self.share_manager.db, 'share_instance_update') self.mock_object(self.share_manager.db, 'share_export_locations_update') fake_share_update_list = [{'id': fake_share['id'], 'foo': 'bar', 'export_locations': fake_export_locations}] self.mock_object(self.share_manager.driver, 'create_consistency_group_from_cgsnapshot', mock.Mock( return_value=(None, fake_share_update_list))) self.share_manager.create_consistency_group(self.context, "fake_id") self.share_manager.db.share_instance_update.\ assert_any_call(mock.ANY, 'fake_share_id', {'foo': 'bar'}) self.share_manager.db.share_export_locations_update.\ assert_any_call(mock.ANY, 'fake_share_id', fake_export_locations) self.share_manager.db.consistency_group_update.\ assert_any_call(mock.ANY, 'fake_id', {'status': constants.STATUS_AVAILABLE, 'created_at': mock.ANY}) def test_create_consistency_group_from_cgsnapshot_with_error(self): fake_cg = {'id': 'fake_id', 'source_cgsnapshot_id': 'fake_snap_id', 'shares': []} fake_snap = {'id': 'fake_snap_id', 'cgsnapshot_members': []} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'cgsnapshot_get', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'share_instances_get_all_by_consistency_group_id', mock.Mock(return_value=[])) self.mock_object(self.share_manager.db, 'consistency_group_update', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.driver, 'create_consistency_group_from_cgsnapshot', mock.Mock(side_effect=exception.Error)) self.assertRaises(exception.Error, self.share_manager.create_consistency_group, self.context, "fake_id") self.share_manager.db.consistency_group_update.\ assert_called_once_with(mock.ANY, 'fake_id', {'status': constants.STATUS_ERROR}) def test_create_consistency_group_from_cgsnapshot_with_share_error(self): fake_share = {'id': 'fake_share_id'} fake_cg = {'id': 'fake_id', 'source_cgsnapshot_id': 'fake_snap_id', 'shares': [fake_share]} fake_snap = {'id': 'fake_snap_id', 'cgsnapshot_members': []} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'cgsnapshot_get', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'share_instances_get_all_by_consistency_group_id', mock.Mock(return_value=[fake_share])) self.mock_object(self.share_manager.db, 'consistency_group_update') self.mock_object(self.share_manager.db, 'share_instance_update') self.mock_object(self.share_manager.driver, 'create_consistency_group_from_cgsnapshot', mock.Mock(side_effect=exception.Error)) self.assertRaises(exception.Error, self.share_manager.create_consistency_group, self.context, "fake_id") self.share_manager.db.share_instance_update.\ assert_any_call(mock.ANY, 'fake_share_id', {'status': constants.STATUS_ERROR}) self.share_manager.db.consistency_group_update.\ assert_called_once_with(mock.ANY, 'fake_id', {'status': constants.STATUS_ERROR}) def test_delete_consistency_group(self): fake_cg = {'id': 'fake_id'} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'consistency_group_update', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'consistency_group_destroy', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.driver, 'delete_consistency_group', mock.Mock(return_value=None)) self.share_manager.delete_consistency_group(self.context, "fake_id") self.share_manager.db.consistency_group_destroy.\ assert_called_once_with(mock.ANY, 'fake_id') def test_delete_consistency_group_with_update(self): fake_cg = {'id': 'fake_id'} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'consistency_group_update', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'consistency_group_destroy', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.driver, 'delete_consistency_group', mock.Mock(return_value={'foo': 'bar'})) self.share_manager.delete_consistency_group(self.context, "fake_id") self.share_manager.db.consistency_group_update.\ assert_called_once_with(mock.ANY, 'fake_id', {'foo': 'bar'}) self.share_manager.db.consistency_group_destroy.\ assert_called_once_with(mock.ANY, 'fake_id') def test_delete_consistency_group_with_error(self): fake_cg = {'id': 'fake_id'} self.mock_object(self.share_manager.db, 'consistency_group_get', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.db, 'consistency_group_update', mock.Mock(return_value=fake_cg)) self.mock_object(self.share_manager.driver, 'delete_consistency_group', mock.Mock(side_effect=exception.Error)) self.assertRaises(exception.Error, self.share_manager.delete_consistency_group, self.context, "fake_id") self.share_manager.db.consistency_group_update.\ assert_called_once_with(mock.ANY, 'fake_id', {'status': constants.STATUS_ERROR}) def test_create_cgsnapshot(self): fake_snap = {'id': 'fake_snap_id', 'consistency_group': {}, 'cgsnapshot_members': []} self.mock_object(self.share_manager.db, 'cgsnapshot_get', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'cgsnapshot_update', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.driver, 'create_cgsnapshot', mock.Mock(return_value=(None, None))) self.share_manager.create_cgsnapshot(self.context, fake_snap['id']) self.share_manager.db.cgsnapshot_update.\ assert_called_once_with(mock.ANY, fake_snap['id'], {'status': constants.STATUS_AVAILABLE, 'created_at': mock.ANY}) def test_create_cgsnapshot_with_update(self): fake_snap = {'id': 'fake_snap_id', 'consistency_group': {}, 'cgsnapshot_members': []} self.mock_object(self.share_manager.db, 'cgsnapshot_get', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'cgsnapshot_update', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.driver, 'create_cgsnapshot', mock.Mock(return_value=({'foo': 'bar'}, None))) self.share_manager.create_cgsnapshot(self.context, fake_snap['id']) self.share_manager.db.cgsnapshot_update.\ assert_any_call(mock.ANY, 'fake_snap_id', {'foo': 'bar'}) self.share_manager.db.cgsnapshot_update.assert_any_call( mock.ANY, fake_snap['id'], {'status': constants.STATUS_AVAILABLE, 'created_at': mock.ANY}) def test_create_cgsnapshot_with_member_update(self): fake_member = { 'id': 'fake_member_id', 'share_instance_id': 'blah', } fake_member_update = { 'id': 'fake_member_id', 'foo': 'bar' } fake_snap = {'id': 'fake_snap_id', 'consistency_group': {}, 'cgsnapshot_members': [fake_member]} self.mock_object(self.share_manager.db, 'cgsnapshot_get', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'cgsnapshot_update', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'cgsnapshot_member_update') self.mock_object(self.share_manager.db, 'share_instance_get', mock.Mock(return_value={'id': 'blah'})) self.mock_object(self.share_manager.driver, 'create_cgsnapshot', mock.Mock(return_value=(None, [fake_member_update]))) self.share_manager.create_cgsnapshot(self.context, fake_snap['id']) self.share_manager.db.cgsnapshot_update.assert_any_call( mock.ANY, fake_snap['id'], {'cgsnapshot_members': [fake_member_update]}) self.share_manager.db.cgsnapshot_update.\ assert_any_call(mock.ANY, fake_snap['id'], {'status': constants.STATUS_AVAILABLE, 'created_at': mock.ANY}) self.assertTrue(self.share_manager.db.cgsnapshot_member_update.called) def test_create_cgsnapshot_with_error(self): fake_snap = {'id': 'fake_snap_id', 'consistency_group': {}, 'cgsnapshot_members': []} self.mock_object(self.share_manager.db, 'cgsnapshot_get', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.db, 'cgsnapshot_update', mock.Mock(return_value=fake_snap)) self.mock_object(self.share_manager.driver, 'create_cgsnapshot', mock.Mock(side_effect=exception.Error)) self.assertRaises(exception.Error, self.share_manager.create_cgsnapshot, self.context, fake_snap['id']) self.share_manager.db.cgsnapshot_update.\ assert_called_once_with(mock.ANY, fake_snap['id'], {'status': constants.STATUS_ERROR}) def test_migration_get_info(self): share_instance = {'share_server_id': 'fake_server_id'} share_instance_id = 'fake_id' share_server = 'fake_share_server' migration_info = 'fake_info' # mocks self.mock_object(self.share_manager.db, 'share_instance_get', mock.Mock(return_value=share_instance)) self.mock_object(self.share_manager.db, 'share_server_get', mock.Mock(return_value=share_server)) self.mock_object(self.share_manager.driver, 'migration_get_info', mock.Mock(return_value=migration_info)) # run result = self.share_manager.migration_get_info( self.context, share_instance_id) # asserts self.assertEqual(migration_info, result) self.share_manager.db.share_instance_get.assert_called_once_with( self.context, share_instance_id, with_share_data=True) self.share_manager.driver.migration_get_info.assert_called_once_with( self.context, share_instance, share_server) def test_migration_get_driver_info(self): share_instance = {'share_server_id': 'fake_server_id'} share_instance_id = 'fake-id' share_server = 'fake-share-server' migration_info = 'fake_info' # mocks self.mock_object(self.share_manager.db, 'share_instance_get', mock.Mock(return_value=share_instance)) self.mock_object(self.share_manager.db, 'share_server_get', mock.Mock(return_value=share_server)) self.mock_object(self.share_manager.driver, 'migration_get_driver_info', mock.Mock(return_value=migration_info)) result = self.share_manager.migration_get_driver_info( self.context, share_instance_id) # asserts self.assertEqual(migration_info, result) self.share_manager.db.share_instance_get.assert_called_once_with( self.context, share_instance_id, with_share_data=True) self.share_manager.driver.migration_get_driver_info.\ assert_called_once_with(self.context, share_instance, share_server) @ddt.data((True, 'fake_model_update'), exception.ManilaException()) def test_migration_start(self, exc): server = 'fake_share_server' instance = db_utils.create_share_instance( share_id='fake_id', status=constants.STATUS_AVAILABLE, share_server_id='fake_server_id') share = db_utils.create_share(id='fake_id', instances=[instance]) host = 'fake_host' driver_migration_info = 'driver_fake_info' # mocks self.mock_object(self.share_manager.db, 'share_get', mock.Mock(return_value=share)) self.mock_object(self.share_manager.db, 'share_instance_get', mock.Mock(return_value=instance)) self.mock_object(self.share_manager.db, 'share_server_get', mock.Mock(return_value=server)) self.mock_object(self.share_manager.db, 'share_update') self.mock_object(self.share_manager.db, 'share_instance_update') self.mock_object(rpcapi.ShareAPI, 'migration_get_driver_info', mock.Mock(return_value=driver_migration_info)) if isinstance(exc, exception.ManilaException): self.mock_object(self.share_manager.driver, 'migration_start', mock.Mock(side_effect=exc)) self.mock_object(self.share_manager, '_migration_start_generic', mock.Mock(side_effect=Exception('fake'))) self.mock_object(manager.LOG, 'exception') else: self.mock_object(self.share_manager.driver, 'migration_start', mock.Mock(return_value=exc)) # run if isinstance(exc, exception.ManilaException): self.assertRaises(exception.ShareMigrationFailed, self.share_manager.migration_start, self.context, 'fake_id', host, False, False) else: self.share_manager.migration_start( self.context, 'fake_id', host, False, False) # asserts self.share_manager.db.share_get.assert_called_once_with( self.context, share['id']) self.share_manager.db.share_instance_get.assert_called_once_with( self.context, instance['id'], with_share_data=True) self.share_manager.db.share_server_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), instance['share_server_id']) share_update_calls = [ mock.call( self.context, share['id'], {'task_state': constants.TASK_STATE_MIGRATION_IN_PROGRESS}), mock.call( self.context, share['id'], {'task_state': ( constants.TASK_STATE_MIGRATION_DRIVER_IN_PROGRESS)}) ] share_instance_update_calls = [ mock.call(self.context, instance['id'], {'status': constants.STATUS_MIGRATING}) ] if isinstance(exc, exception.ManilaException): share_update_calls.append(mock.call( self.context, share['id'], {'task_state': constants.TASK_STATE_MIGRATION_ERROR})) share_instance_update_calls.append( mock.call(self.context, instance['id'], {'status': constants.STATUS_AVAILABLE})) self.share_manager._migration_start_generic.\ assert_called_once_with(self.context, share, instance, host, False) self.assertTrue(manager.LOG.exception.called) else: share_update_calls.append(mock.call( self.context, share['id'], {'task_state': constants.TASK_STATE_MIGRATION_DRIVER_PHASE1_DONE})) share_instance_update_calls.append( mock.call(self.context, instance['id'], 'fake_model_update')) self.share_manager.db.share_update.assert_has_calls(share_update_calls) self.share_manager.db.share_instance_update.assert_has_calls( share_instance_update_calls) rpcapi.ShareAPI.migration_get_driver_info.assert_called_once_with( self.context, instance) self.share_manager.driver.migration_start.assert_called_once_with( self.context, instance, server, host, driver_migration_info, False) @ddt.data(None, Exception('fake')) def test__migration_start_generic(self, exc): instance = db_utils.create_share_instance( share_id='fake_id', status=constants.STATUS_AVAILABLE, share_server_id='fake_server_id') new_instance = db_utils.create_share_instance( share_id='new_fake_id', status=constants.STATUS_AVAILABLE) share = db_utils.create_share(id='fake_id', instances=[instance]) server = 'share_server' src_migration_info = 'src_fake_info' dest_migration_info = 'dest_fake_info' # mocks self.mock_object(self.share_manager.db, 'share_server_get', mock.Mock(return_value=server)) self.mock_object(self.share_manager.db, 'share_instance_update', mock.Mock(return_value=server)) self.mock_object(migration_api.ShareMigrationHelper, 'change_to_read_only') if exc is None: self.mock_object(migration_api.ShareMigrationHelper, 'create_instance_and_wait', mock.Mock(return_value=new_instance)) self.mock_object(self.share_manager.driver, 'migration_get_info', mock.Mock(return_value=src_migration_info)) self.mock_object(rpcapi.ShareAPI, 'migration_get_info', mock.Mock(return_value=dest_migration_info)) self.mock_object(data_rpc.DataAPI, 'migration_start', mock.Mock(side_effect=Exception('fake'))) self.mock_object(migration_api.ShareMigrationHelper, 'cleanup_new_instance') else: self.mock_object(migration_api.ShareMigrationHelper, 'create_instance_and_wait', mock.Mock(side_effect=exc)) self.mock_object(migration_api.ShareMigrationHelper, 'cleanup_access_rules') # run self.assertRaises( exception.ShareMigrationFailed, self.share_manager._migration_start_generic, self.context, share, instance, 'fake_host', False) # asserts self.share_manager.db.share_server_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), instance['share_server_id']) migration_api.ShareMigrationHelper.change_to_read_only.\ assert_called_once_with(instance, server, True, self.share_manager.driver) migration_api.ShareMigrationHelper.create_instance_and_wait.\ assert_called_once_with(share, instance, 'fake_host') migration_api.ShareMigrationHelper.\ cleanup_access_rules.assert_called_once_with( instance, server, self.share_manager.driver) if exc is None: self.share_manager.db.share_instance_update.\ assert_called_once_with( self.context, new_instance['id'], {'status': constants.STATUS_MIGRATING_TO}) self.share_manager.driver.migration_get_info.\ assert_called_once_with(self.context, instance, server) rpcapi.ShareAPI.migration_get_info.assert_called_once_with( self.context, new_instance) data_rpc.DataAPI.migration_start.assert_called_once_with( self.context, share['id'], ['lost+found'], instance['id'], new_instance['id'], src_migration_info, dest_migration_info, False) migration_api.ShareMigrationHelper.\ cleanup_new_instance.assert_called_once_with(new_instance) @ddt.data('fake_model_update', Exception('fake')) def test_migration_complete_driver(self, exc): server = 'fake_server' model_update = 'fake_model_update' instance = db_utils.create_share_instance( share_id='fake_id', status=constants.STATUS_AVAILABLE, share_server_id='fake_server_id') share = db_utils.create_share( id='fake_id', instances=[instance], task_state=constants.TASK_STATE_MIGRATION_DRIVER_PHASE1_DONE) # mocks self.mock_object(self.share_manager.db, 'share_get', mock.Mock(return_value=share)) self.mock_object(self.share_manager.db, 'share_instance_get', mock.Mock(return_value=instance)) self.mock_object(self.share_manager.db, 'share_server_get', mock.Mock(return_value=server)) self.mock_object(self.share_manager.db, 'share_update') if isinstance(exc, Exception): self.mock_object(self.share_manager.driver, 'migration_complete', mock.Mock(side_effect=exc)) else: self.mock_object(self.share_manager.driver, 'migration_complete', mock.Mock(return_value=exc)) self.mock_object(self.share_manager.db, 'share_instance_update') self.mock_object(rpcapi.ShareAPI, 'migration_get_driver_info', mock.Mock(return_value='fake_info')) self.mock_object(manager.LOG, 'exception') # run if isinstance(exc, Exception): self.assertRaises( exception.ShareMigrationFailed, self.share_manager.migration_complete, self.context, 'fake_id', 'fake_ins_id', 'new_fake_ins_id') else: self.share_manager.migration_complete( self.context, 'fake_id', 'fake_ins_id', 'new_fake_ins_id') # asserts self.share_manager.db.share_get.assert_called_once_with( self.context, share['id']) self.share_manager.db.share_instance_get.assert_called_once_with( self.context, instance['id'], with_share_data=True) self.share_manager.db.share_server_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), 'fake_server_id') self.share_manager.driver.migration_complete.assert_called_once_with( self.context, instance, server, 'fake_info') rpcapi.ShareAPI.migration_get_driver_info.assert_called_once_with( self.context, instance) if isinstance(exc, Exception): self.share_manager.db.share_update.assert_called_once_with( self.context, share['id'], {'task_state': constants.TASK_STATE_MIGRATION_ERROR}) self.assertTrue(manager.LOG.exception.called) else: self.share_manager.db.share_update.assert_called_once_with( self.context, share['id'], {'task_state': constants.TASK_STATE_MIGRATION_SUCCESS}) self.share_manager.db.share_instance_update.\ assert_called_once_with(self.context, instance['id'], model_update) @ddt.data(None, Exception('fake')) def test_migration_complete_generic(self, exc): share = db_utils.create_share( id='fake_id', task_state=constants.TASK_STATE_DATA_COPYING_COMPLETED) # mocks self.mock_object(self.share_manager.db, 'share_get', mock.Mock(return_value=share)) self.mock_object(self.share_manager, '_migration_complete', mock.Mock(side_effect=exc)) self.mock_object(self.share_manager.db, 'share_update') self.mock_object(self.share_manager.db, 'share_instance_update') self.mock_object(manager.LOG, 'exception') # run if exc: self.assertRaises( exception.ShareMigrationFailed, self.share_manager.migration_complete, self.context, 'fake_id', 'fake_ins_id', 'new_fake_ins_id') else: self.share_manager.migration_complete( self.context, 'fake_id', 'fake_ins_id', 'new_fake_ins_id') # asserts self.share_manager.db.share_get.assert_called_once_with( self.context, share['id']) self.share_manager._migration_complete.assert_called_once_with( self.context, share, 'fake_ins_id', 'new_fake_ins_id') if exc: self.share_manager.db.share_update.assert_called_once_with( self.context, share['id'], {'task_state': constants.TASK_STATE_MIGRATION_ERROR}) self.share_manager.db.share_instance_update.\ assert_called_once_with( self.context, 'fake_ins_id', {'status': constants.STATUS_AVAILABLE}) self.assertTrue(manager.LOG.exception.called) @ddt.data(constants.TASK_STATE_DATA_COPYING_ERROR, constants.TASK_STATE_DATA_COPYING_CANCELLED, constants.TASK_STATE_DATA_COPYING_COMPLETED, 'other') def test__migration_complete_status(self, status): instance = db_utils.create_share_instance( share_id='fake_id', share_server_id='fake_server_id') new_instance = db_utils.create_share_instance(share_id='fake_id') share = db_utils.create_share(id='fake_id', task_state=status) server = 'fake_server' # mocks self.mock_object(self.share_manager.db, 'share_instance_get', mock.Mock(side_effect=[instance, new_instance])) self.mock_object(self.share_manager.db, 'share_server_get', mock.Mock(return_value=server)) self.mock_object(migration_api.ShareMigrationHelper, 'cleanup_new_instance') self.mock_object(migration_api.ShareMigrationHelper, 'cleanup_access_rules') self.mock_object(self.share_manager.db, 'share_instance_update') self.mock_object(self.share_manager.db, 'share_update') if status == constants.TASK_STATE_DATA_COPYING_COMPLETED: self.mock_object(migration_api.ShareMigrationHelper, 'apply_new_access_rules', mock.Mock(side_effect=Exception('fake'))) self.mock_object(manager.LOG, 'exception') # run if status == constants.TASK_STATE_DATA_COPYING_CANCELLED: self.share_manager._migration_complete( self.context, share, instance['id'], new_instance['id']) else: self.assertRaises( exception.ShareMigrationFailed, self.share_manager._migration_complete, self.context, share, instance['id'], new_instance['id']) # asserts self.share_manager.db.share_instance_get.assert_has_calls([ mock.call(self.context, instance['id'], with_share_data=True), mock.call(self.context, new_instance['id'], with_share_data=True) ]) self.share_manager.db.share_server_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), 'fake_server_id') if status != 'other': migration_api.ShareMigrationHelper.cleanup_new_instance.\ assert_called_once_with(new_instance) migration_api.ShareMigrationHelper.cleanup_access_rules.\ assert_called_once_with(instance, server, self.share_manager.driver) if status == constants.TASK_STATE_MIGRATION_CANCELLED: self.share_manager.db.share_instance_update.\ assert_called_once_with(self.context, instance['id'], {'status': constants.STATUS_AVAILABLE}) self.share_manager.db.share_update.assert_called_once_with( self.context, share['id'], {'task_state': constants.TASK_STATE_MIGRATION_CANCELLED}) if status == constants.TASK_STATE_DATA_COPYING_COMPLETED: migration_api.ShareMigrationHelper.apply_new_access_rules.\ assert_called_once_with(new_instance) self.assertTrue(manager.LOG.exception.called) def test__migration_complete(self): instance = db_utils.create_share_instance( share_id='fake_id', share_server_id='fake_server_id') new_instance = db_utils.create_share_instance(share_id='fake_id') share = db_utils.create_share( id='fake_id', task_state=constants.TASK_STATE_DATA_COPYING_COMPLETED) server = 'fake_server' # mocks self.mock_object(self.share_manager.db, 'share_instance_get', mock.Mock(side_effect=[instance, new_instance])) self.mock_object(self.share_manager.db, 'share_server_get', mock.Mock(return_value=server)) self.mock_object(self.share_manager.db, 'share_instance_update') self.mock_object(self.share_manager.db, 'share_update') self.mock_object(migration_api.ShareMigrationHelper, 'delete_instance_and_wait') self.mock_object(migration_api.ShareMigrationHelper, 'apply_new_access_rules') # run self.share_manager._migration_complete( self.context, share, instance['id'], new_instance['id']) # asserts self.share_manager.db.share_instance_get.assert_has_calls([ mock.call(self.context, instance['id'], with_share_data=True), mock.call(self.context, new_instance['id'], with_share_data=True) ]) self.share_manager.db.share_server_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), 'fake_server_id') self.share_manager.db.share_instance_update.assert_has_calls([ mock.call(self.context, new_instance['id'], {'status': constants.STATUS_AVAILABLE}), mock.call(self.context, instance['id'], {'status': constants.STATUS_INACTIVE}) ]) self.share_manager.db.share_update.assert_has_calls([ mock.call( self.context, share['id'], {'task_state': constants.TASK_STATE_MIGRATION_COMPLETING}), mock.call( self.context, share['id'], {'task_state': constants.TASK_STATE_MIGRATION_SUCCESS}), ]) migration_api.ShareMigrationHelper.apply_new_access_rules.\ assert_called_once_with(new_instance) migration_api.ShareMigrationHelper.delete_instance_and_wait.\ assert_called_once_with(instance) def test_migration_cancel(self): server = db_utils.create_share_server() share = db_utils.create_share( task_state=constants.TASK_STATE_MIGRATION_DRIVER_IN_PROGRESS, share_server_id=server['id']) self.mock_object(db, 'share_get', mock.Mock(return_value=share)) self.mock_object(db, 'share_server_get', mock.Mock(return_value=server)) self.mock_object(rpcapi.ShareAPI, 'migration_get_driver_info', mock.Mock(return_value='migration_info')) self.mock_object(self.share_manager.driver, 'migration_cancel') self.share_manager.migration_cancel(self.context, share) rpcapi.ShareAPI.migration_get_driver_info.assert_called_once_with( self.context, share.instance) self.share_manager.driver.migration_cancel.assert_called_once_with( self.context, share.instance, server, 'migration_info') def test_migration_cancel_invalid(self): share = db_utils.create_share() self.mock_object(db, 'share_get', mock.Mock(return_value=share)) self.assertRaises( exception.InvalidShare, self.share_manager.migration_cancel, self.context, share) def test_migration_get_progress(self): server = db_utils.create_share_server() share = db_utils.create_share( task_state=constants.TASK_STATE_MIGRATION_DRIVER_IN_PROGRESS, share_server_id=server['id']) expected = 'fake_progress' self.mock_object(db, 'share_get', mock.Mock(return_value=share)) self.mock_object(db, 'share_server_get', mock.Mock(return_value=server)) self.mock_object(rpcapi.ShareAPI, 'migration_get_driver_info', mock.Mock(return_value='migration_info')) self.mock_object(self.share_manager.driver, 'migration_get_progress', mock.Mock(return_value=expected)) result = self.share_manager.migration_get_progress(self.context, share) self.assertEqual(expected, result) rpcapi.ShareAPI.migration_get_driver_info.assert_called_once_with( self.context, share.instance) self.share_manager.driver.migration_get_progress.\ assert_called_once_with( self.context, share.instance, server, 'migration_info') def test_migration_get_progress_invalid(self): share = db_utils.create_share() self.mock_object(db, 'share_get', mock.Mock(return_value=share)) self.assertRaises( exception.InvalidShare, self.share_manager.migration_get_progress, self.context, share) def test_manage_snapshot_invalid_driver_mode(self): self.mock_object(self.share_manager, 'driver') self.share_manager.driver.driver_handles_share_servers = True share = db_utils.create_share() snapshot = db_utils.create_snapshot(share_id=share['id']) driver_options = {'fake': 'fake'} self.assertRaises( exception.InvalidDriverMode, self.share_manager.manage_snapshot, self.context, snapshot['id'], driver_options) def test_manage_snapshot_invalid_snapshot(self): fake_share_server = 'fake_share_server' self.mock_object(self.share_manager, 'driver') self.share_manager.driver.driver_handles_share_servers = False mock_get_share_server = self.mock_object( self.share_manager, '_get_share_server', mock.Mock(return_value=fake_share_server)) share = db_utils.create_share() snapshot = db_utils.create_snapshot(share_id=share['id']) driver_options = {'fake': 'fake'} mock_get = self.mock_object(self.share_manager.db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.assertRaises( exception.InvalidShareSnapshot, self.share_manager.manage_snapshot, self.context, snapshot['id'], driver_options) mock_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['id']) mock_get_share_server.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['share']) def test_manage_snapshot_driver_exception(self): CustomException = type('CustomException', (Exception,), {}) self.mock_object(self.share_manager, 'driver') self.share_manager.driver.driver_handles_share_servers = False mock_manage = self.mock_object(self.share_manager.driver, 'manage_existing_snapshot', mock.Mock(side_effect=CustomException)) mock_get_share_server = self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=None)) share = db_utils.create_share() snapshot = db_utils.create_snapshot(share_id=share['id']) driver_options = {} mock_get = self.mock_object(self.share_manager.db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.assertRaises( CustomException, self.share_manager.manage_snapshot, self.context, snapshot['id'], driver_options) mock_manage.assert_called_once_with(mock.ANY, driver_options) mock_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['id']) mock_get_share_server.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['share']) @ddt.data( {'size': 1}, {'size': 2, 'name': 'fake'}, {'size': 3}) def test_manage_snapshot_valid_snapshot(self, driver_data): mock_get_share_server = self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=None)) self.mock_object(self.share_manager.db, 'share_snapshot_update') self.mock_object(self.share_manager, 'driver') self.mock_object(self.share_manager, '_update_quota_usages') self.share_manager.driver.driver_handles_share_servers = False mock_manage = self.mock_object( self.share_manager.driver, "manage_existing_snapshot", mock.Mock(return_value=driver_data)) size = driver_data['size'] share = db_utils.create_share(size=size) snapshot = db_utils.create_snapshot(share_id=share['id'], size=size) snapshot_id = snapshot['id'] driver_options = {} mock_get = self.mock_object(self.share_manager.db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.share_manager.manage_snapshot(self.context, snapshot_id, driver_options) mock_manage.assert_called_once_with(mock.ANY, driver_options) valid_snapshot_data = { 'status': constants.STATUS_AVAILABLE} valid_snapshot_data.update(driver_data) self.share_manager.db.share_snapshot_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot_id, valid_snapshot_data) self.share_manager._update_quota_usages.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['project_id'], {'snapshots': 1, 'snapshot_gigabytes': size}) mock_get_share_server.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['share']) mock_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot_id) def test_unmanage_snapshot_invalid_driver_mode(self): self.mock_object(self.share_manager, 'driver') self.share_manager.driver.driver_handles_share_servers = True share = db_utils.create_share() snapshot = db_utils.create_snapshot(share_id=share['id']) self.mock_object(self.share_manager.db, 'share_snapshot_update') ret = self.share_manager.unmanage_snapshot(self.context, snapshot['id']) self.assertIsNone(ret) self.share_manager.db.share_snapshot_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['id'], {'status': constants.STATUS_UNMANAGE_ERROR}) def test_unmanage_snapshot_invalid_snapshot(self): self.mock_object(self.share_manager, 'driver') self.share_manager.driver.driver_handles_share_servers = False mock_get_share_server = self.mock_object( self.share_manager, '_get_share_server', mock.Mock(return_value='fake_share_server')) self.mock_object(self.share_manager.db, 'share_snapshot_update') share = db_utils.create_share() snapshot = db_utils.create_snapshot(share_id=share['id']) mock_get = self.mock_object(self.share_manager.db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) ret = self.share_manager.unmanage_snapshot(self.context, snapshot['id']) self.assertIsNone(ret) self.share_manager.db.share_snapshot_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['id'], {'status': constants.STATUS_UNMANAGE_ERROR}) mock_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['id']) mock_get_share_server.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['share']) def test_unmanage_snapshot_invalid_share(self): self.mock_object(self.share_manager, 'driver') self.share_manager.driver.driver_handles_share_servers = False mock_unmanage = mock.Mock( side_effect=exception.UnmanageInvalidShareSnapshot(reason="fake")) self.mock_object(self.share_manager.driver, "unmanage_snapshot", mock_unmanage) mock_get_share_server = self.mock_object( self.share_manager, '_get_share_server', mock.Mock(return_value=None)) self.mock_object(self.share_manager.db, 'share_snapshot_update') share = db_utils.create_share() snapshot = db_utils.create_snapshot(share_id=share['id']) mock_get = self.mock_object(self.share_manager.db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.share_manager.unmanage_snapshot(self.context, snapshot['id']) self.share_manager.db.share_snapshot_update.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['id'], {'status': constants.STATUS_UNMANAGE_ERROR}) self.share_manager.driver.unmanage_snapshot.assert_called_once_with( mock.ANY) mock_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['id']) mock_get_share_server.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['share']) @ddt.data(False, True) def test_unmanage_snapshot_valid_snapshot(self, quota_error): if quota_error: self.mock_object(quota.QUOTAS, 'reserve', mock.Mock( side_effect=exception.ManilaException(message='error'))) mock_log_warning = self.mock_object(manager.LOG, 'warning') self.mock_object(self.share_manager, 'driver') self.share_manager.driver.driver_handles_share_servers = False self.mock_object(self.share_manager.driver, "unmanage_snapshot") mock_get_share_server = self.mock_object( self.share_manager, '_get_share_server', mock.Mock(return_value=None)) mock_snapshot_instance_destroy_call = self.mock_object( self.share_manager.db, 'share_snapshot_instance_delete') share = db_utils.create_share() snapshot = db_utils.create_snapshot(share_id=share['id']) mock_get = self.mock_object(self.share_manager.db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.share_manager.unmanage_snapshot(self.context, snapshot['id']) self.share_manager.driver.unmanage_snapshot.assert_called_once_with( mock.ANY) mock_snapshot_instance_destroy_call.assert_called_once_with( mock.ANY, snapshot['instance']['id']) mock_get.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['id']) mock_get_share_server.assert_called_once_with( utils.IsAMatcher(context.RequestContext), snapshot['share']) if quota_error: self.assertTrue(mock_log_warning.called) def _setup_crud_replicated_snapshot_data(self): snapshot = fakes.fake_snapshot(create_instance=True) snapshot_instance = fakes.fake_snapshot_instance( base_snapshot=snapshot) snapshot_instances = [snapshot['instance'], snapshot_instance] replicas = [fake_replica(), fake_replica()] return snapshot, snapshot_instances, replicas def test_create_replicated_snapshot_driver_exception(self): snapshot, snapshot_instances, replicas = ( self._setup_crud_replicated_snapshot_data() ) self.mock_object( db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshot_instances)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=replicas)) self.mock_object( self.share_manager.driver, 'create_replicated_snapshot', mock.Mock(side_effect=exception.ManilaException)) mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') self.assertRaises(exception.ManilaException, self.share_manager.create_replicated_snapshot, self.context, snapshot['id'], share_id='fake_share') mock_db_update_call.assert_has_calls([ mock.call( self.context, snapshot['instance']['id'], {'status': constants.STATUS_ERROR}), mock.call( self.context, snapshot_instances[1]['id'], {'status': constants.STATUS_ERROR}), ]) @ddt.data(None, []) def test_create_replicated_snapshot_driver_updates_nothing(self, retval): snapshot, snapshot_instances, replicas = ( self._setup_crud_replicated_snapshot_data() ) self.mock_object( db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshot_instances)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=replicas)) self.mock_object( self.share_manager.driver, 'create_replicated_snapshot', mock.Mock(return_value=retval)) mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') return_value = self.share_manager.create_replicated_snapshot( self.context, snapshot['id'], share_id='fake_share') self.assertIsNone(return_value) self.assertFalse(mock_db_update_call.called) def test_create_replicated_snapshot_driver_updates_snapshot(self): snapshot, snapshot_instances, replicas = ( self._setup_crud_replicated_snapshot_data() ) snapshot_dict = { 'status': constants.STATUS_AVAILABLE, 'provider_location': 'spinners_end', 'progress': '100%', 'id': snapshot['instance']['id'], } self.mock_object( db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshot_instances)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=replicas)) self.mock_object( self.share_manager.driver, 'create_replicated_snapshot', mock.Mock(return_value=[snapshot_dict])) mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') return_value = self.share_manager.create_replicated_snapshot( self.context, snapshot['id'], share_id='fake_share') self.assertIsNone(return_value) mock_db_update_call.assert_called_once_with( self.context, snapshot['instance']['id'], snapshot_dict) def delete_replicated_snapshot_driver_exception(self): snapshot, snapshot_instances, replicas = ( self._setup_crud_replicated_snapshot_data() ) self.mock_object( db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshot_instances)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=replicas)) self.mock_object( self.share_manager.driver, 'delete_replicated_snapshot', mock.Mock(side_effect=exception.ManilaException)) mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') mock_db_delete_call = self.mock_object( db, 'share_snapshot_instance_delete') self.assertRaises(exception.ManilaException, self.share_manager.delete_replicated_snapshot, self.context, snapshot['id'], share_id='fake_share') mock_db_update_call.assert_has_calls([ mock.call( self.context, snapshot['instance']['id'], {'status': constants.STATUS_ERROR_DELETING}), mock.call( self.context, snapshot_instances[1]['id'], {'status': constants.STATUS_ERROR_DELETING}), ]) self.assertFalse(mock_db_delete_call.called) def delete_replicated_snapshot_driver_exception_ignored_with_force(self): snapshot, snapshot_instances, replicas = ( self._setup_crud_replicated_snapshot_data() ) self.mock_object( db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshot_instances)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=replicas)) self.mock_object( self.share_manager.driver, 'delete_replicated_snapshot', mock.Mock(side_effect=exception.ManilaException)) mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') mock_db_delete_call = self.mock_object( db, 'share_snapshot_instance_delete') retval = self.share_manager.delete_replicated_snapshot( self.context, snapshot['id'], share_id='fake_share') self.assertIsNone(retval) mock_db_delete_call.assert_has_calls([ mock.call( self.context, snapshot['instance']['id']), mock.call( self.context, snapshot_instances[1]['id']), ]) self.assertFalse(mock_db_update_call.called) @ddt.data(None, []) def delete_replicated_snapshot_driver_updates_nothing(self, retval): snapshot, snapshot_instances, replicas = ( self._setup_crud_replicated_snapshot_data() ) self.mock_object( db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshot_instances)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=replicas)) self.mock_object( self.share_manager.driver, 'delete_replicated_snapshot', mock.Mock(return_value=retval)) mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') mock_db_delete_call = self.mock_object( db, 'share_snapshot_instance_delete') return_value = self.share_manager.delete_replicated_snapshot( self.context, snapshot['id'], share_id='fake_share') self.assertIsNone(return_value) self.assertFalse(mock_db_delete_call.called) self.assertFalse(mock_db_update_call.called) def delete_replicated_snapshot_driver_deletes_snapshots(self): snapshot, snapshot_instances, replicas = ( self._setup_crud_replicated_snapshot_data() ) retval = [{ 'status': constants.STATUS_DELETED, 'id': snapshot['instance']['id'], }] self.mock_object( db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshot_instances)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=replicas)) self.mock_object( self.share_manager.driver, 'delete_replicated_snapshot', mock.Mock(return_value=retval)) mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') mock_db_delete_call = self.mock_object( db, 'share_snapshot_instance_delete') return_value = self.share_manager.delete_replicated_snapshot( self.context, snapshot['id'], share_id='fake_share') self.assertIsNone(return_value) mock_db_delete_call.assert_called_once_with( self.context, snapshot['instance']['id']) self.assertFalse(mock_db_update_call.called) @ddt.data(True, False) def delete_replicated_snapshot_drv_del_and_updates_snapshots(self, force): snapshot, snapshot_instances, replicas = ( self._setup_crud_replicated_snapshot_data() ) updated_instance_details = { 'status': constants.STATUS_ERROR, 'id': snapshot_instances[1]['id'], 'provider_location': 'azkaban', } retval = [ { 'status': constants.STATUS_DELETED, 'id': snapshot['instance']['id'], }, ] retval.append(updated_instance_details) self.mock_object( db, 'share_snapshot_get', mock.Mock(return_value=snapshot)) self.mock_object(self.share_manager, '_get_share_server') self.mock_object(db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshot_instances)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=replicas)) self.mock_object( self.share_manager.driver, 'delete_replicated_snapshot', mock.Mock(return_value=retval)) mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') mock_db_delete_call = self.mock_object( db, 'share_snapshot_instance_delete') return_value = self.share_manager.delete_replicated_snapshot( self.context, snapshot['id'], share_id='fake_share', force=force) self.assertIsNone(return_value) if force: self.assertTrue(2, mock_db_delete_call.call_count) self.assertFalse(mock_db_update_call.called) else: mock_db_delete_call.assert_called_once_with( self.context, snapshot['instance']['id']) mock_db_update_call.assert_called_once_with( self.context, snapshot_instances[1]['id'], updated_instance_details) def test_periodic_share_replica_snapshot_update(self): mock_debug_log = self.mock_object(manager.LOG, 'debug') replicas = 3 * [ fake_replica(host='malfoy@manor#_pool0', replica_state=constants.REPLICA_STATE_IN_SYNC) ] replicas.append(fake_replica(replica_state=constants.STATUS_ACTIVE)) snapshot = fakes.fake_snapshot(create_instance=True, status=constants.STATUS_DELETING) snapshot_instances = 3 * [ fakes.fake_snapshot_instance(base_snapshot=snapshot) ] self.mock_object( db, 'share_replicas_get_all', mock.Mock(return_value=replicas)) self.mock_object(db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(return_value=snapshot_instances)) mock_snapshot_update_call = self.mock_object( self.share_manager, '_update_replica_snapshot') retval = self.share_manager.periodic_share_replica_snapshot_update( self.context) self.assertIsNone(retval) self.assertEqual(1, mock_debug_log.call_count) self.assertEqual(0, mock_snapshot_update_call.call_count) @ddt.data(True, False) def test_periodic_share_replica_snapshot_update_nothing_to_update( self, has_instances): mock_debug_log = self.mock_object(manager.LOG, 'debug') replicas = 3 * [ fake_replica(host='malfoy@manor#_pool0', replica_state=constants.REPLICA_STATE_IN_SYNC) ] replicas.append(fake_replica(replica_state=constants.STATUS_ACTIVE)) snapshot = fakes.fake_snapshot(create_instance=True, status=constants.STATUS_DELETING) snapshot_instances = 3 * [ fakes.fake_snapshot_instance(base_snapshot=snapshot) ] self.mock_object(db, 'share_replicas_get_all', mock.Mock(side_effect=[[], replicas])) self.mock_object(db, 'share_snapshot_instance_get_all_with_filters', mock.Mock(side_effect=[snapshot_instances, []])) mock_snapshot_update_call = self.mock_object( self.share_manager, '_update_replica_snapshot') retval = self.share_manager.periodic_share_replica_snapshot_update( self.context) self.assertIsNone(retval) self.assertEqual(1, mock_debug_log.call_count) self.assertEqual(0, mock_snapshot_update_call.call_count) def test__update_replica_snapshot_replica_deleted_from_database(self): replica_not_found = exception.ShareReplicaNotFound(replica_id='xyzzy') self.mock_object(db, 'share_replica_get', mock.Mock( side_effect=replica_not_found)) mock_db_delete_call = self.mock_object( db, 'share_snapshot_instance_delete') mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') mock_driver_update_call = self.mock_object( self.share_manager.driver, 'update_replicated_snapshot') snaphot_instance = fakes.fake_snapshot_instance() retval = self.share_manager._update_replica_snapshot( self.context, snaphot_instance) self.assertIsNone(retval) mock_db_delete_call.assert_called_once_with( self.context, snaphot_instance['id']) self.assertFalse(mock_driver_update_call.called) self.assertFalse(mock_db_update_call.called) def test__update_replica_snapshot_both_deleted_from_database(self): replica_not_found = exception.ShareReplicaNotFound(replica_id='xyzzy') instance_not_found = exception.ShareSnapshotInstanceNotFound( instance_id='spoon!') self.mock_object(db, 'share_replica_get', mock.Mock( side_effect=replica_not_found)) mock_db_delete_call = self.mock_object( db, 'share_snapshot_instance_delete', mock.Mock( side_effect=instance_not_found)) mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') mock_driver_update_call = self.mock_object( self.share_manager.driver, 'update_replicated_snapshot') snapshot_instance = fakes.fake_snapshot_instance() retval = self.share_manager._update_replica_snapshot( self.context, snapshot_instance) self.assertIsNone(retval) mock_db_delete_call.assert_called_once_with( self.context, snapshot_instance['id']) self.assertFalse(mock_driver_update_call.called) self.assertFalse(mock_db_update_call.called) def test__update_replica_snapshot_driver_raises_Not_Found_exception(self): mock_debug_log = self.mock_object(manager.LOG, 'debug') replica = fake_replica() snapshot_instance = fakes.fake_snapshot_instance( status=constants.STATUS_DELETING) self.mock_object( db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_snapshot_instance_get', mock.Mock(return_value=snapshot_instance)) self.mock_object(db, 'share_snapshot_instance_get', mock.Mock(return_value=snapshot_instance)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica])) self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=None)) self.mock_object( self.share_manager.driver, 'update_replicated_snapshot', mock.Mock( side_effect=exception.SnapshotResourceNotFound(name='abc'))) mock_db_delete_call = self.mock_object( db, 'share_snapshot_instance_delete') mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') retval = self.share_manager._update_replica_snapshot( self.context, snapshot_instance, replica_snapshots=None) self.assertIsNone(retval) self.assertEqual(1, mock_debug_log.call_count) mock_db_delete_call.assert_called_once_with( self.context, snapshot_instance['id']) self.assertFalse(mock_db_update_call.called) @ddt.data(exception.NotFound, exception.ManilaException) def test__update_replica_snapshot_driver_raises_other_exception(self, exc): mock_debug_log = self.mock_object(manager.LOG, 'debug') mock_info_log = self.mock_object(manager.LOG, 'info') mock_exception_log = self.mock_object(manager.LOG, 'exception') replica = fake_replica() snapshot_instance = fakes.fake_snapshot_instance( status=constants.STATUS_CREATING) self.mock_object( db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_snapshot_instance_get', mock.Mock(return_value=snapshot_instance)) self.mock_object(db, 'share_snapshot_instance_get', mock.Mock(return_value=snapshot_instance)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica])) self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=None)) self.mock_object(self.share_manager.driver, 'update_replicated_snapshot', mock.Mock(side_effect=exc)) mock_db_delete_call = self.mock_object( db, 'share_snapshot_instance_delete') mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') retval = self.share_manager._update_replica_snapshot( self.context, snapshot_instance) self.assertIsNone(retval) self.assertEqual(1, mock_exception_log.call_count) self.assertEqual(1, mock_debug_log.call_count) self.assertFalse(mock_info_log.called) mock_db_update_call.assert_called_once_with( self.context, snapshot_instance['id'], {'status': 'error'}) self.assertFalse(mock_db_delete_call.called) @ddt.data(True, False) def test__update_replica_snapshot_driver_updates_replica(self, update): replica = fake_replica() snapshot_instance = fakes.fake_snapshot_instance() driver_update = {} if update: driver_update = { 'id': snapshot_instance['id'], 'provider_location': 'knockturn_alley', 'status': constants.STATUS_AVAILABLE, } mock_debug_log = self.mock_object(manager.LOG, 'debug') mock_info_log = self.mock_object(manager.LOG, 'info') self.mock_object( db, 'share_replica_get', mock.Mock(return_value=replica)) self.mock_object(db, 'share_snapshot_instance_get', mock.Mock(return_value=snapshot_instance)) self.mock_object(db, 'share_snapshot_instance_get', mock.Mock(return_value=snapshot_instance)) self.mock_object(db, 'share_replicas_get_all_by_share', mock.Mock(return_value=[replica])) self.mock_object(self.share_manager, '_get_share_server', mock.Mock(return_value=None)) self.mock_object(self.share_manager.driver, 'update_replicated_snapshot', mock.Mock(return_value=driver_update)) mock_db_delete_call = self.mock_object( db, 'share_snapshot_instance_delete') mock_db_update_call = self.mock_object( db, 'share_snapshot_instance_update') retval = self.share_manager._update_replica_snapshot( self.context, snapshot_instance, replica_snapshots=None) driver_update['progress'] = '100%' self.assertIsNone(retval) self.assertEqual(1, mock_debug_log.call_count) self.assertFalse(mock_info_log.called) if update: mock_db_update_call.assert_called_once_with( self.context, snapshot_instance['id'], driver_update) else: self.assertFalse(mock_db_update_call.called) self.assertFalse(mock_db_delete_call.called) @ddt.ddt class HookWrapperTestCase(test.TestCase): def setUp(self): super(HookWrapperTestCase, self).setUp() self.configuration = mock.Mock() self.configuration.safe_get.return_value = True @manager.add_hooks def _fake_wrapped_method(self, some_arg, some_kwarg): return "foo" def test_hooks_enabled(self): self.hooks = [mock.Mock(return_value=i) for i in range(2)] result = self._fake_wrapped_method( "some_arg", some_kwarg="some_kwarg_value") self.assertEqual("foo", result) for i, mock_hook in enumerate(self.hooks): mock_hook.execute_pre_hook.assert_called_once_with( "some_arg", func_name="_fake_wrapped_method", some_kwarg="some_kwarg_value") mock_hook.execute_post_hook.assert_called_once_with( "some_arg", func_name="_fake_wrapped_method", driver_action_results="foo", pre_hook_data=self.hooks[i].execute_pre_hook.return_value, some_kwarg="some_kwarg_value") def test_hooks_disabled(self): self.hooks = [] result = self._fake_wrapped_method( "some_arg", some_kwarg="some_kwarg_value") self.assertEqual("foo", result) for mock_hook in self.hooks: self.assertFalse(mock_hook.execute_pre_hook.called) self.assertFalse(mock_hook.execute_post_hook.called)

47.575963

79

0.640871

25,557

224,844

5.236139

0.022186

0.067882

0.087999

0.056554

0.89113

0.858661

0.826297

0.784053

0.751128

0.715603

0

0.002028

0.263276

224,844

4,725

80

47.586032

0.805829

0.009224

0

0.674481

0

0.110083

0.042909

0

0.131868

1

0.044933

false

0.000488

0.009035

0.000733

0.057875

0

null

0

1

0

null

0

6

407fbde3aec5a5072ee1f3a83d887c1fa5e36d45

85

py

Python

sympy/codegen/pynodes.py

utkarshdeorah/sympy

dcdf59bbc6b13ddbc329431adf72fcee294b6389

[ "BSD-3-Clause" ]

1

2020-01-12T17:16:05.000Z

sympy/codegen/pynodes.py

utkarshdeorah/sympy

dcdf59bbc6b13ddbc329431adf72fcee294b6389

[ "BSD-3-Clause" ]

14

2018-02-08T10:11:03.000Z

2019-04-16T10:32:46.000Z

sympy/codegen/pynodes.py

utkarshdeorah/sympy

dcdf59bbc6b13ddbc329431adf72fcee294b6389

[ "BSD-3-Clause" ]

1

2022-02-04T13:50:29.000Z

from .abstract_nodes import List as AbstractList class List(AbstractList): pass

17

48

0.788235

11

85

6

0.818182

0

0.164706

85

4

49

21.25

0.929577

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

40eac44c20cf2d38970f8eaaaab7f040cae8c601

27

py

Python

adet/modeling/solov2/__init__.py

manusheoran/AdelaiDet_DA

04f0843c6be8e436716783300abcba715d560853

[ "BSD-2-Clause" ]

2,597

2020-03-15T06:01:23.000Z

2022-03-31T18:21:31.000Z

adet/modeling/solov2/__init__.py

manusheoran/AdelaiDet_DA

04f0843c6be8e436716783300abcba715d560853

[ "BSD-2-Clause" ]

467

2020-03-16T11:31:52.000Z

2022-03-31T08:50:15.000Z

adet/modeling/solov2/__init__.py

manusheoran/AdelaiDet_DA

04f0843c6be8e436716783300abcba715d560853

[ "BSD-2-Clause" ]

584

2020-03-15T05:53:40.000Z

2022-03-26T02:56:30.000Z

from .solov2 import SOLOv2

13.5

26

0.814815

4

27

5.5

0.75

0

0.086957

0.148148

27

1

27

0.869565

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

906eb50ae4dbd119ca154893bb9c1ee0b7b463db

4,059

py

Python

code/nll_grad_fb.py

mjvakili/supermean

4388a164cc1da41776c0f8dd0060ada6db7e1c9e

[ "MIT" ]

1

2016-12-12T20:58:43.000Z

code/nll_grad_fb.py

mjvakili/supermean

4388a164cc1da41776c0f8dd0060ada6db7e1c9e

[ "MIT" ]

null

code/nll_grad_fb.py

mjvakili/supermean

4388a164cc1da41776c0f8dd0060ada6db7e1c9e

[ "MIT" ]

null

import numpy as np import scipy.optimize as op def fit_single_patch(data, mask , psf, theta, floor, gain): """ Inputs: data = patch, mask = True for healthy pixels, False for flagged pixels psf = psf model rendered at the data grid theta = [old_flux, old_bkg], where: old_flux = current flux estimate for a patch old_back = current bkg estimate for the patch floor = floor variance of the noise model gain = gain of the noise model Outputs: (non-regularized) NLL of the patch, and derivative of (non-regularized) NLL w.r.t flux and bkg of the patch. Note that the regularization is independent of F, B. """ var = floor + gain * np.abs(theta[1] * psf[mask] + theta[0]) A = np.ones((var.size, 2)) A[:, 1] = psf[mask] model = np.dot(A, theta) #masked model res = data[mask] - model func = 0.5*np.sum(((res)**2.)/var) + 0.5*np.sum(np.log(var)) Grad = 0.5*gain*(1./var - res*res/(var*var)) - (res*res)/var grad = np.sum(Grad[:, None]*A , axis = 1) return func , grad # different version of the function defined above. We'll see which one is faster: def v2_fit_single_patch(theta, masked_data, masked_psf, floor, gain): """ Inputs: theta = [old_bkg, old_flux], where: old_flux = current flux estimate for a patch old_back = current bkg estimate for the patch masked_data = patch with flagged pixels masked out masked_psf = psf model rendered at the data grid masked out where pixels are flagged floor = floor variance of the noise model gain = gain of the noise model Outputs: (non-regularized) NLL of the patch, and derivative of (non-regularized) NLL w.r.t flux and bkg of the patch. Note that the regularization is independent of F, B. """ var = floor + gain * np.abs(theta[1]* masked_psf + theta[0]) A = np.ones((var.size, 2)) A[:, 1] = masked_psf model = np.dot(A , theta) #masked model res = masked_data - model func = 0.5*np.sum(((res)**2.)/var) + 0.5*np.sum(np.log(var)) Grad = 0.5*gain*(1./var - res*res/(var*var)) - (res*res)/var grad = np.sum(Grad[:, None]*A , axis = 0) #this could unnecessarily slow down the code!! print func.shape , grad.shape return func , grad ##### this is probably the fastest version! def v3_fit_single_patch(theta, masked_data, masked_psf, floor, gain): """ Inputs: theta = [old_flux, old_bkg], where: old_flux = current flux estimate for a patch old_back = current bkg estimate for the patch masked_data = patch with flagged pixels masked out masked_psf = psf model rendered at the data grid masked out where pixels are flagged floor = floor variance of the noise model gain = gain of the noise model Outputs: (non-regularized) NLL of the patch, and derivative of (non-regularized) NLL w.r.t flux and bkg of the patch. Note that the regularization is independent of F, B. """ grad = np.zeros((2)) var = floor + gain * np.abs(theta[1] * masked_psf + theta[0]) model = theta[0] + theta[1]*masked_psf #masked model res = masked_data - model func = 0.5*np.sum(((res)**2.)/var) + 0.5*np.sum(np.log(var)) gain_term_b = - (gain/2.)*(res**2./var**2.) + (gain/2.)*(var**-1.) #gainp[modelp<0] *= -1. #var=f+g|model| to account for numerical artifacts when sr model is sampled at the data grid grad[0] = -1.*np.sum(res/var) + np.sum(gain_term_b) gain_term_f = (gain/2.)*masked_psf*(var**-1. - res**2./var**2.) #gainp[modelp<0] *= -1. #var=f+g|model| to account for numerical artifacts when sr model is sampled at the data grid grad[1] = np.sum(-1.*res*masked_psf/var) + np.sum(gain_term_f) return func, grad

35.295652

125

0.598916

625

4,059

3.8192

0.1792

0.027231

0.025136

0.037704

0.780059

0.766653

0.733976

0

0.018933

0.284306

4,059

114

126

35.605263

0.802754

0.107169

0

0.470588

0

null

0

0.058824

null

0.029412

0

null

0

1

0

null

0

1

0

6

909680a4f50d339905058a47255f30cb43acfb09

33

py

Python

cct/core2/devices/vacuumgauge/generic/__init__.py

awacha/cct

be1adbed2533df15c778051f3f4f9da0749c873a

[ "BSD-3-Clause" ]

1

2015-11-04T16:37:39.000Z

cct/core2/devices/vacuumgauge/generic/__init__.py

awacha/cct

be1adbed2533df15c778051f3f4f9da0749c873a

[ "BSD-3-Clause" ]

null

cct/core2/devices/vacuumgauge/generic/__init__.py

awacha/cct

be1adbed2533df15c778051f3f4f9da0749c873a

[ "BSD-3-Clause" ]

1

2020-03-05T02:50:43.000Z

from .frontend import VacuumGauge

33

0.878788

4

33

7.25

1

0

0.090909

33

1

33

0.966667

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

90ac11663dc8b10598fe5f239bff717ec89796ac

78

py

Python

src/evaluation/__init__.py

mfederici/dsit

7f26f7ce93edb2075fba4aa965aa1ad9bf773aa5

[ "MIT" ]

17

2021-11-02T17:51:02.000Z

2022-02-21T02:48:56.000Z

src/evaluation/__init__.py

mfederici/dsit

7f26f7ce93edb2075fba4aa965aa1ad9bf773aa5

[ "MIT" ]

null

src/evaluation/__init__.py

mfederici/dsit

7f26f7ce93edb2075fba4aa965aa1ad9bf773aa5

[ "MIT" ]

null

from src.evaluation.accuracy import AccuracyEvaluation, CrossEntropyEvaluation

78

0.910256

7

78

10.142857

1

0

0.051282

78

1

78

0.959459

0

1

0

true

0

1

0

1

0

1

0

1

null

0

1

0

null

0

1

0

1

0

1

0

6

90c262f280d42f7c5aea2d42d91082a004cbe89b

25,992

py

Python

Pyrado/pyrado/environments/rcspysim/box_lifting.py

jacarvalho/SimuRLacra

a6c982862e2ab39a9f65d1c09aa59d9a8b7ac6c5

[ "BSD-3-Clause" ]

null

Pyrado/pyrado/environments/rcspysim/box_lifting.py

jacarvalho/SimuRLacra

a6c982862e2ab39a9f65d1c09aa59d9a8b7ac6c5

[ "BSD-3-Clause" ]

null

Pyrado/pyrado/environments/rcspysim/box_lifting.py

jacarvalho/SimuRLacra

a6c982862e2ab39a9f65d1c09aa59d9a8b7ac6c5

[ "BSD-3-Clause" ]

null

import functools import numpy as np import os.path as osp from init_args_serializer import Serializable from typing import Sequence import rcsenv from pyrado.environments.rcspysim.base import RcsSim from pyrado.spaces.box import BoxSpace from pyrado.spaces.singular import SingularStateSpace from pyrado.tasks.base import Task from pyrado.tasks.desired_state import DesStateTask from pyrado.tasks.endless_flipping import EndlessFlippingTask from pyrado.tasks.masked import MaskedTask from pyrado.tasks.reward_functions import ExpQuadrErrRewFcn, MinusOnePerStepRewFcn, AbsErrRewFcn, CosOfOneEleRewFcn, \ CompoundRewFcn from pyrado.tasks.parallel import ParallelTasks from pyrado.tasks.utils import proximity_succeeded, never_succeeded from pyrado.tasks.predefined import create_check_all_boundaries_task, \ create_task_space_discrepancy_task, create_collision_task from pyrado.utils.data_types import EnvSpec rcsenv.addResourcePath(rcsenv.RCSPYSIM_CONFIG_PATH) def create_box_lift_task(env_spec: EnvSpec, continuous_rew_fcn: bool, succ_thold: float): # Define the indices for selection. This needs to match the observations' names in RcsPySim. idcs = ['Box_Z'] # Get the masked environment specification spec = EnvSpec( env_spec.obs_space, env_spec.act_space, env_spec.state_space.subspace(env_spec.state_space.create_mask(idcs)) ) # Create a desired state task # state_des = np.array([0.3]) # box position is measured relative to the table state_des = np.array([1.1]) # box position is measured world coordinates if continuous_rew_fcn: Q = np.diag([3e1]) R = 1e0*np.eye(spec.act_space.flat_dim) rew_fcn = ExpQuadrErrRewFcn(Q, R) else: rew_fcn = MinusOnePerStepRewFcn() dst = DesStateTask(spec, state_des, rew_fcn, functools.partial(proximity_succeeded, thold_dist=succ_thold)) # Return the masked tasks return MaskedTask(env_spec, dst, idcs) def create_box_flip_task(env_spec: EnvSpec, continuous_rew_fcn): # Define the indices for selection. This needs to match the observations' names in RcsPySim. idcs = ['Box_A'] # Get the masked environment specification spec = EnvSpec( env_spec.obs_space, env_spec.act_space, env_spec.state_space.subspace(env_spec.state_space.create_mask(idcs)) ) # Create a desired state task # state_des = np.array([0.3]) # box position is measured relative to the table state_des = np.array([-np.pi/2]) # box position is measured world coordinates if continuous_rew_fcn: q = np.array([0./np.pi]) r = 1e-6*np.ones(spec.act_space.flat_dim) rew_fcn_act = AbsErrRewFcn(q, r) rew_fcn_box = CosOfOneEleRewFcn(idx=0) rew_fcn = CompoundRewFcn([rew_fcn_act, rew_fcn_box]) else: rew_fcn = MinusOnePerStepRewFcn() ef_task = EndlessFlippingTask(spec, rew_fcn, init_angle=0.) # Return the masked tasks return MaskedTask(env_spec, ef_task, idcs) class BoxLiftingSim(RcsSim, Serializable): """ Base class for 2-armed humanoid robot lifting a box out of a basket """ def __init__(self, task_args: dict, ref_frame: str, position_mps: bool, mps_left: [Sequence[dict], None], mps_right: [Sequence[dict], None], fixed_init_state: bool = False, **kwargs): """ Constructor .. note:: This constructor should only be called via the subclasses. :param task_args: arguments for the task construction :param ref_frame: reference frame for the position and orientation MPs, e.g. 'world', 'basket', or 'box' :param position_mps: `True` if the MPs are defined on position level, `False` if defined on velocity level :param mps_left: left arm's movement primitives holding the dynamical systems and the goal states :param mps_right: right arm's movement primitives holding the dynamical systems and the goal states :param fixed_init_state: use an init state space with only one state (e.g. for debugging) :param kwargs: keyword arguments which are available for all task-based `RcsSim` taskCombinationMethod: str = 'mean', # 'sum', 'mean', 'product', or 'softmax' checkJointLimits: bool = False, collisionAvoidanceIK: bool = True, observeVelocities: bool = True, observeCollisionCost: bool = True, observePredictedCollisionCost: bool = False, observeManipulabilityIndex: bool = False, observeCurrentManipulability: bool = True, observeDynamicalSystemDiscrepancy: bool = False, observeTaskSpaceDiscrepancy: bool = True, observeForceTorque: bool = True """ Serializable._init(self, locals()) # Forward to the RcsSim's constructor RcsSim.__init__( self, envType='BoxLifting', physicsConfigFile='pBoxLifting.xml', extraConfigDir=osp.join(rcsenv.RCSPYSIM_CONFIG_PATH, 'BoxLifting'), hudColor='BLACK_RUBBER', task_args=task_args, refFrame=ref_frame, positionTasks=position_mps, tasksLeft=mps_left, tasksRight=mps_right, **kwargs ) # Initial state space definition if fixed_init_state: dafault_init_state = np.array( [0.2, 0., 0., 0.85, 65.*np.pi/180, -65.*np.pi/180]) # [m, m, rad, m, rad, rad] self._init_space = SingularStateSpace(dafault_init_state, labels=['$x$', '$y$', '$th$', '$z$', '$q_2_L$', '$q_2_R$']) else: min_init_state = np.array([0.05, -0.05, -5*np.pi/180, 0.8, 60*np.pi/180, -70*np.pi/180]) max_init_state = np.array([0.25, 0.05, 5*np.pi/180, 0.9, 70*np.pi/180, -60*np.pi/180]) self._init_space = BoxSpace(min_init_state, max_init_state, # [m, m, rad, m, rad, rad] labels=['$x$', '$y$', '$th$', '$z$', '$q_2$', '$q_4$']) def _create_task(self, task_args: dict) -> Task: # Create the tasks continuous_rew_fcn = task_args.get('continuous_rew_fcn', True) task_box = create_box_lift_task(self.spec, continuous_rew_fcn, succ_thold=0.03) task_check_bounds = create_check_all_boundaries_task(self.spec, penalty=1e3) task_collision = create_collision_task(self.spec, factor=1.) task_ts_discrepancy = create_task_space_discrepancy_task(self.spec, AbsErrRewFcn(q=0.5*np.ones(3), r=np.zeros(self.act_space.shape))) return ParallelTasks([ task_box, task_check_bounds, task_collision, task_ts_discrepancy ], hold_rew_when_done=False) @classmethod def get_nominal_domain_param(cls): return dict(box_length=0.18, box_width=0.14, box_mass=0.3, box_friction_coefficient=1.4, basket_mass=0.5, basket_friction_coefficient=0.6) class BoxLiftingPosMPsSim(BoxLiftingSim, Serializable): """ Humanoid robot lifting a box out of a basket using two arms and position-level movement primitives """ name: str = 'bl-pos' def __init__(self, ref_frame: str, mps_left: [Sequence[dict], None], mps_right: [Sequence[dict], None], continuous_rew_fcn: bool = True, fixed_init_state: bool = False, **kwargs): """ Constructor :param ref_frame: reference frame for the position and orientation MPs, e.g. 'world', 'basket', or 'box' :param mps_left: left arm's movement primitives holding the dynamical systems and the goal states :param mps_right: right arm's movement primitives holding the dynamical systems and the goal states :param continuous_rew_fcn: specify if the continuous or an uninformative reward function should be used :param fixed_init_state: use an init state space with only one state (e.g. for debugging) :param kwargs: keyword arguments which are available for all task-based `RcsSim` taskCombinationMethod: str = 'mean', # 'sum', 'mean', 'product', or 'softmax' checkJointLimits: bool = False, collisionAvoidanceIK: bool = True, observeVelocities: bool = True, observeCollisionCost: bool = True, observePredictedCollisionCost: bool = False, observeManipulabilityIndex: bool = False, observeCurrentManipulability: bool = True, observeDynamicalSystemDiscrepancy: bool = False, observeTaskSpaceDiscrepancy: bool = True, observeForceTorque: bool = True """ Serializable._init(self, locals()) # Fall back to some defaults of no MPs are defined (e.g. for testing) # basket_extends = self.get_body_extents('Basket', 0) if mps_left is None: mps_left = [ # Power grasp position in basket frame (basket width = 0.7) {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.array([0., 0.5, 0.15])}, # [m] {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.array([0., -0.3, 0.15])}, # [m] # Power grasp position in box frame (box width = 0.18) # {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., # 'goal': np.array([0., 0., 0.1])}, # [m] # Power grasp orientation in basket frame {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.pi/180*np.array([180, -90, 0.])}, # [rad] {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.pi/180*np.array([120, -90, 0.])}, # [rad] # Joints SDH {'function': 'msd_nlin', 'attractorStiffness': 50., 'mass': 1., 'damping': 50., 'goal': 10/180*np.pi*np.array([0, 2, -1.5, 2, 0, 2, 0])}, ] if mps_right is None: mps_right = [ # Power grasp position in basket frame (basket width = 0.7) {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.array([0., -0.5, 0.15])}, # [m] {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.array([0., 0.3, 0.15])}, # [m] # Power grasp orientation {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.pi/180*np.array([180, -90, 0.])}, # [rad] {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.pi/180*np.array([240, -90, 0.])}, # [rad] # Joints SDH {'function': 'msd_nlin', 'attractorStiffness': 50., 'mass': 1., 'damping': 50., 'goal': 10/180*np.pi*np.array([0, 1.5, -1, 1, 0, 1.5, 0])}, # Distance # {'function': 'msd', 'attractorStiffness': 50., 'mass': 1., 'damping': 10., {'function': 'lin', 'errorDynamics': 1., # [m/s] 'goal': np.array([0.0])}, # [m] ] # Forward to the BoxLiftingSim's constructor super().__init__( task_args=dict(continuous_rew_fcn=continuous_rew_fcn), ref_frame=ref_frame, position_mps=True, mps_left=mps_left, mps_right=mps_right, **kwargs ) class BoxLiftingVelMPsSim(BoxLiftingSim, Serializable): """ Humanoid robot lifting a box out of a basket using two arms and velocity-level movement primitives """ name: str = 'bl-vel' def __init__(self, ref_frame: str, mps_left: [Sequence[dict], None], mps_right: [Sequence[dict], None], continuous_rew_fcn: bool = True, fixed_init_state: bool = False, **kwargs): """ Constructor :param ref_frame: reference frame for the position and orientation MPs, e.g. 'world', 'basket', or 'box' :param mps_left: left arm's movement primitives holding the dynamical systems and the goal states :param mps_right: right arm's movement primitives holding the dynamical systems and the goal states :param continuous_rew_fcn: specify if the continuous or an uninformative reward function should be used :param fixed_init_state: use an init state space with only one state (e.g. for debugging) :param kwargs: keyword arguments which are available for all task-based `RcsSim` taskCombinationMethod: str = 'mean', # 'sum', 'mean', 'product', or 'softmax' checkJointLimits: bool = False, collisionAvoidanceIK: bool = True, observeCollisionCost: bool = True, observeVelocities: bool = True, observePredictedCollisionCost: bool = False, observeManipulabilityIndex: bool = False, observeCurrentManipulability: bool = True, observeDynamicalSystemDiscrepancy: bool = False, observeTaskSpaceDiscrepancy: bool = True, observeForceTorque: bool = True """ Serializable._init(self, locals()) # Fall back to some defaults of no MPs are defined (e.g. for testing) dt = kwargs.get('dt', 0.01) # 100 Hz is the default # basket_extends = self.get_body_extents('Basket', 0) if mps_left is None: mps_left = [ # Power grasp Xd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([0.15])}, # [m/s] # Power grasp Yd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([0.15])}, # [m/s] # Power grasp Zd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([0.15])}, # [m/s] # Power grasp Ad {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([15/180*np.pi])}, # [rad/s] # Power grasp Bd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([15/180*np.pi])}, # [rad/s] # Power grasp Cd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([15/180*np.pi])}, # [rad/s] # Joints SDH {'function': 'msd_nlin', 'attractorStiffness': 50., 'mass': 2., 'damping': 50., 'goal': 10/180*np.pi*np.array([0, 2, -1.5, 2, 0, 2, 0])}, ] if mps_right is None: mps_right = [ # Power grasp Xd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([0.15])}, # [m/s] # Power grasp Yd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([0.15])}, # [m/s] # Power grasp Zd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([0.15])}, # [m/s] # Power grasp Ad {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([15/180*np.pi])}, # [rad/s] # Power grasp Bd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([15/180*np.pi])}, # [rad/s] # Power grasp Cd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([15/180*np.pi])}, # [rad/s] # Joints SDH {'function': 'msd_nlin', 'attractorStiffness': 50., 'mass': 2., 'damping': 50., 'goal': 10/180*np.pi*np.array([0, 1.5, -1, 1, 0, 1.5, 0])}, ] # Forward to the BoxLiftingSim's constructor super().__init__( task_args=dict(continuous_rew_fcn=continuous_rew_fcn), ref_frame=ref_frame, position_mps=False, mps_left=mps_left, mps_right=mps_right, **kwargs ) class BoxLiftingSimpleSim(RcsSim, Serializable): """ Base class for simplified robotic manipulator turning a box in a basket """ def __init__(self, task_args: dict, ref_frame: str, position_mps: bool, mps_left: [Sequence[dict], None], **kwargs): """ Constructor .. note:: This constructor should only be called via the subclasses. :param task_args: arguments for the task construction :param ref_frame: reference frame for the position and orientation MPs, e.g. 'world', 'basket', or 'box' :param position_mps: `True` if the MPs are defined on position level, `False` if defined on velocity level :param mps_left: left arm's movement primitives holding the dynamical systems and the goal states :param kwargs: keyword arguments which are available for all task-based `RcsSim` taskCombinationMethod: str = 'mean', # 'sum', 'mean', 'product', or 'softmax' checkJointLimits: bool = False, collisionAvoidanceIK: bool = True, observeVelocities: bool = False, observeCollisionCost: bool = True, observePredictedCollisionCost: bool = False, observeManipulabilityIndex: bool = False, observeCurrentManipulability: bool = True, observeDynamicalSystemDiscrepancy: bool = False, observeTaskSpaceDiscrepancy: bool = True, observeForceTorque: bool = True """ Serializable._init(self, locals()) if kwargs.get('collisionConfig', None) is None: kwargs.update(collisionConfig={ 'pairs': [ {'body1': 'Hand', 'body2': 'Table'}, ], 'threshold': 0.07 }) # Forward to the RcsSim's constructor RcsSim.__init__( self, envType='BoxLiftingSimple', physicsConfigFile='pBoxLifting.xml', extraConfigDir=osp.join(rcsenv.RCSPYSIM_CONFIG_PATH, 'BoxLifting'), hudColor='BLACK_RUBBER', task_args=task_args, refFrame=ref_frame, positionTasks=position_mps, tasksLeft=mps_left, **kwargs ) def _create_task(self, task_args: dict) -> Task: # Create the tasks continuous_rew_fcn = task_args.get('continuous_rew_fcn', True) task_box = create_box_flip_task(self.spec, continuous_rew_fcn) task_check_bounds = create_check_all_boundaries_task(self.spec, penalty=1e3) # task_collision = create_collision_task(self.spec, factor=5e-2) from pyrado.environments.rcspysim.box_flipping import create_task_space_discrepancy_task task_ts_discrepancy = create_task_space_discrepancy_task(self.spec, AbsErrRewFcn(q=5e-2*np.ones(2), r=np.zeros(self.act_space.shape))) return ParallelTasks([ task_box, task_check_bounds, # task_collision, task_ts_discrepancy ], hold_rew_when_done=False) @classmethod def get_nominal_domain_param(cls): return dict(box_length=0.14, # x_world dimension box_width=0.18, # y_world dimension box_mass=0.4, box_friction_coefficient=1.3, basket_mass=0.5, basket_friction_coefficient=0.9) class BoxLiftingSimplePosMPsSim(BoxLiftingSimpleSim, Serializable): """ Simplified robotic manipulator turning a box in a basket using position-level movement primitives """ name: str = 'bls-pos' def __init__(self, ref_frame: str, mps_left: [Sequence[dict], None], continuous_rew_fcn: bool = True, **kwargs): """ Constructor :param ref_frame: reference frame for the position and orientation MPs, e.g. 'world', 'basket', or 'box' :param mps_left: left arm's movement primitives holding the dynamical systems and the goal states :param continuous_rew_fcn: specify if the continuous or an uninformative reward function should be used :param kwargs: keyword arguments which are available for all task-based `RcsSim` taskCombinationMethod: str = 'mean', # 'sum', 'mean', 'product', or 'softmax' checkJointLimits: bool = False, collisionAvoidanceIK: bool = True, observeVelocities: bool = False, observeCollisionCost: bool = True, observePredictedCollisionCost: bool = False, observeManipulabilityIndex: bool = False, observeCurrentManipulability: bool = True, observeDynamicalSystemDiscrepancy: bool = False, observeTaskSpaceDiscrepancy: bool = True, observeForceTorque: bool = True """ Serializable._init(self, locals()) # Fall back to some defaults of no MPs are defined (e.g. for testing) if mps_left is None: mps_left = [ # Y {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.array([-0.4])}, # [m] {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.array([+0.4])}, # [m] # Z {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.array([-0.05])}, # [m] {'function': 'msd_nlin', 'attractorStiffness': 30., 'mass': 1., 'damping': 60., 'goal': np.array([+0.3])}, # [m] ] # Forward to the BoxLiftingSimpleSim's constructor super().__init__( task_args=dict(continuous_rew_fcn=continuous_rew_fcn), ref_frame=ref_frame, position_mps=True, mps_left=mps_left, **kwargs ) class BoxLiftingSimpleVelMPsSim(BoxLiftingSimpleSim, Serializable): """ Simplified robotic manipulator turning a box in a basket using velocity-level movement primitives """ name: str = 'bls-vel' def __init__(self, ref_frame: str, mps_left: [Sequence[dict], None], continuous_rew_fcn: bool = True, **kwargs): """ Constructor :param ref_frame: reference frame for the position and orientation MPs, e.g. 'world', 'basket', or 'box' :param mps_left: left arm's movement primitives holding the dynamical systems and the goal states :param continuous_rew_fcn: specify if the continuous or an uninformative reward function should be used :param kwargs: keyword arguments which are available for all task-based `RcsSim` taskCombinationMethod: str = 'mean', # 'sum', 'mean', 'product', or 'softmax' checkJointLimits: bool = False, collisionAvoidanceIK: bool = True, observeVelocities: bool = False, observeCollisionCost: bool = True, observePredictedCollisionCost: bool = False, observeManipulabilityIndex: bool = False, observeCurrentManipulability: bool = True, observeDynamicalSystemDiscrepancy: bool = False, observeTaskSpaceDiscrepancy: bool = True, observeForceTorque: bool = True """ Serializable._init(self, locals()) # Fall back to some defaults of no MPs are defined (e.g. for testing) dt = kwargs.get('dt', 0.01) # 100 Hz is the default # basket_extends = self.get_body_extents('Basket', 0) if mps_left is None: mps_left = [ # Yd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([0.1])}, # [m/s] {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([-0.1])}, # [m/s] # Zd {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([0.1])}, # [m/s] {'function': 'lin', 'errorDynamics': 1., 'goal': dt*np.array([-0.1])}, # [m/s] ] # Forward to the BoxLiftingSimpleSim's constructor super().__init__( task_args=dict(continuous_rew_fcn=continuous_rew_fcn), ref_frame=ref_frame, position_mps=False, mps_left=mps_left, **kwargs )

48.222635

118

0.565251

2,849

25,992

5.002808

0.11934

0.020627

0.016839

0.03936

0.856171

0.835052

0.818073

0.803129

0.791763

0.786852

0

0.025336

0.324254

25,992

538

119

48.312268

0.786154

0.384157

0

0.622449

0

0.102822

0

1

0.040816

false

0

0.064626

0.006803

0.159864

0

null

0

1

0

null

0

6

90d3a76886172f0d9418858ca88bfecbf99f9a81

34,855

py

Python

sdc/tests/test_groupby.py

akharche/hpat

c7889893b49f7b251cd9f0a0889107593d8f1c4a

[ "BSD-2-Clause" ]

null

sdc/tests/test_groupby.py

akharche/hpat

c7889893b49f7b251cd9f0a0889107593d8f1c4a

[ "BSD-2-Clause" ]

null

sdc/tests/test_groupby.py

akharche/hpat

c7889893b49f7b251cd9f0a0889107593d8f1c4a

[ "BSD-2-Clause" ]

null

# ***************************************************************************** # Copyright (c) 2020, Intel Corporation All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # # Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, # THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR # PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR # CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, # EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, # PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; # OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, # WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR # OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, # EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # ***************************************************************************** import numba import numpy as np import pandas as pd import platform import pyarrow.parquet as pq import unittest from itertools import product import sdc from sdc.tests.test_base import TestCase from sdc.tests.test_utils import (count_array_OneDs, count_array_REPs, count_parfor_OneDs, count_parfor_REPs, dist_IR_contains, get_start_end, skip_numba_jit, sdc_limitation) from sdc.tests.test_series import gen_frand_array _pivot_df1 = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo", "bar", "bar", "bar", "bar"], "B": ["one", "one", "one", "two", "two", "one", "one", "two", "two"], "C": ["small", "large", "large", "small", "small", "large", "small", "small", "large"], "D": [1, 2, 2, 6, 3, 4, 5, 6, 9]}) _default_df_numeric_data = { 'A': [2, 1, 2, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(11, dtype=np.intp), 'C': np.arange(11, dtype=np.float_), 'D': [np.nan, 2., -1.3, np.nan, 3.5, 0, 10, 0.42, np.nan, -2.5, 23], 'E': [np.inf, 2., -1.3, -np.inf, 3.5, 0, 10, 0.42, np.nan, -2.5, 23] } class TestGroupBy(TestCase): @sdc_limitation def test_dataframe_groupby_index_name(self): """SDC indexes do not have names, so index created from a named Series looses it's name.""" def test_impl(df): return df.groupby('A').min() hpat_func = self.jit(test_impl) n = 11 df = pd.DataFrame({ 'A': [2, 1, 1, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(n, dtype=np.intp) }) result = hpat_func(df) result_ref = test_impl(df) pd.testing.assert_frame_equal(result, result_ref) def test_dataframe_groupby_by_all_dtypes(self): def test_impl(df): return df.groupby('A').count() hpat_func = self.jit(test_impl) dtype_to_column_data = { 'int': [2, 1, 1, 1, 2, 2, 1, 0, 3, 1, 3], 'float': [2, 1, 1, 1, 2, 2, 1, 3, np.nan, 1, np.nan], 'string': ['b', 'a', 'a', 'a', 'b', 'b', 'a', ' ', None, 'a', None] } df = pd.DataFrame(_default_df_numeric_data) for dtype, col_data in dtype_to_column_data.items(): with self.subTest(by_dtype=dtype, by_data=col_data): df['A'] = col_data result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_sort(self): def test_impl(df, param): return df.groupby('A', sort=param).min() hpat_func = self.jit(test_impl) n, m = 1000, 20 np.random.seed(0) df = pd.DataFrame({ 'A': np.random.choice(np.arange(m), n), 'B': np.arange(n, dtype=np.intp), 'C': np.arange(n, dtype=np.float_), 'D': gen_frand_array(n, nancount=n // 2), }) for value in [True, False]: with self.subTest(sort=value): result = hpat_func(df, value) if value else hpat_func(df, value).sort_index() result_ref = test_impl(df, value) if value else hpat_func(df, value).sort_index() # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_count(self): def test_impl(df): return df.groupby('A').count() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_count_no_unboxing(self): def test_impl(): df = pd.DataFrame({ 'A': [2, 1, 2, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(11), 'C': [np.nan, 2., -1.3, np.nan, 3.5, 0, 10, 0.42, np.nan, -2.5, 23], 'D': [np.inf, 2., -1.3, -np.inf, 3.5, 0, 10, 0.42, np.nan, -2.5, 23] }) return df.groupby('A').count() sdc_impl = self.jit(test_impl) result_jit = sdc_impl() result_ref = test_impl() # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result_jit, result_ref, check_names=False) def test_dataframe_groupby_max(self): def test_impl(df): return df.groupby('A').max() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_max_no_unboxing(self): def test_impl(): df = pd.DataFrame({ 'A': [2, 1, 2, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(11), 'C': [np.nan, 2., -1.3, np.nan, 3.5, 0, 10, 0.42, np.nan, -2.5, 23], 'D': [np.inf, 2., -1.3, -np.inf, 3.5, 0, 10, 0.42, np.nan, -2.5, 23] }) return df.groupby('A').max() sdc_impl = self.jit(test_impl) # TODO: implement index classes, as current indexes do not have names kwargs = {'check_names': False} if platform.system() == 'Windows': # Attribute "dtype" are different on windows int64 vs int32 kwargs['check_dtype'] = False pd.testing.assert_frame_equal(sdc_impl(), test_impl(), **kwargs) def test_dataframe_groupby_min(self): def test_impl(df): return df.groupby('A').min() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_min_no_unboxing(self): def test_impl(): df = pd.DataFrame({ 'A': [2, 1, 2, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(11), 'C': [np.nan, 2., -1.3, np.nan, 3.5, 0, 10, 0.42, np.nan, -2.5, 23], 'D': [np.inf, 2., -1.3, -np.inf, 3.5, 0, 10, 0.42, np.nan, -2.5, 23] }) return df.groupby('A').min() sdc_impl = self.jit(test_impl) # TODO: implement index classes, as current indexes do not have names kwargs = {'check_names': False} if platform.system() == 'Windows': # Attribute "dtype" are different on windows int64 vs int32 kwargs['check_dtype'] = False pd.testing.assert_frame_equal(sdc_impl(), test_impl(), **kwargs) def test_dataframe_groupby_mean(self): def test_impl(df): return df.groupby('A').mean() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_mean_no_unboxing(self): def test_impl(): df = pd.DataFrame({ 'A': [2, 1, 2, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(11), 'C': [np.nan, 2., -1.3, np.nan, 3.5, 0, 10, 0.42, np.nan, -2.5, 23], 'D': [np.inf, 2., -1.3, -np.inf, 3.5, 0, 10, 0.42, np.nan, -2.5, 23] }) return df.groupby('A').mean() sdc_impl = self.jit(test_impl) result_jit = sdc_impl() result_ref = test_impl() # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result_jit, result_ref, check_names=False) def test_dataframe_groupby_median(self): def test_impl(df): return df.groupby('A').median() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_median_no_unboxing(self): def test_impl(): df = pd.DataFrame({ 'A': [2, 1, 2, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(11), 'C': [np.nan, 2., -1.3, np.nan, 3.5, 0, 10, 0.42, np.nan, -2.5, 23], 'D': [np.inf, 2., -1.3, -np.inf, 3.5, 0, 10, 0.42, np.nan, -2.5, 23] }) return df.groupby('A').median() sdc_impl = self.jit(test_impl) result_jit = sdc_impl() result_ref = test_impl() # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result_jit, result_ref, check_names=False) @unittest.expectedFailure # pandas groupby.median returns unstable dtype (int or float) unlike series.median def test_dataframe_groupby_median_result_dtype(self): def test_impl(df): return df.groupby('A').median() hpat_func = self.jit(test_impl) n = 11 df = pd.DataFrame({ 'A': [2, 1, 1, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(n, dtype=np.intp) }) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_prod(self): def test_impl(df): return df.groupby('A').prod() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_prod_no_unboxing(self): def test_impl(): df = pd.DataFrame({ 'A': [2, 1, 2, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(11), 'C': [np.nan, 2., -1.3, np.nan, 3.5, 0, 10, 0.42, np.nan, -2.5, 23], 'D': [np.inf, 2., -1.3, -np.inf, 3.5, 0, 10, 0.42, np.nan, -2.5, 23] }) return df.groupby('A').prod() sdc_impl = self.jit(test_impl) # TODO: implement index classes, as current indexes do not have names kwargs = {'check_names': False} if platform.system() == 'Windows': # Attribute "dtype" are different on windows int64 vs int32 kwargs['check_dtype'] = False pd.testing.assert_frame_equal(sdc_impl(), test_impl(), **kwargs) @skip_numba_jit("BUG: SDC impl of Series.sum returns float64 on as series of ints") def test_dataframe_groupby_sum(self): def test_impl(df): return df.groupby('A').sum() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_sum_no_unboxing(self): def test_impl(): df = pd.DataFrame({ 'A': [2, 1, 2, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(11), 'C': [np.nan, 2., -1.3, np.nan, 3.5, 0, 10, 0.42, np.nan, -2.5, 23], 'D': [np.inf, 2., -1.3, -np.inf, 3.5, 0, 10, 0.42, np.nan, -2.5, 23] }) return df.groupby('A').sum() sdc_impl = self.jit(test_impl) # TODO: implement index classes, as current indexes do not have names # Attribute "dtype" are different int64 vs int32 kwargs = {'check_names': False, 'check_dtype': False} pd.testing.assert_frame_equal(sdc_impl(), test_impl(), **kwargs) def test_dataframe_groupby_std(self): def test_impl(df): return df.groupby('A').std() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_std_no_unboxing(self): def test_impl(): df = pd.DataFrame({ 'A': [2, 1, 2, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(11), 'C': [np.nan, 2., -1.3, np.nan, 3.5, 0, 10, 0.42, np.nan, -2.5, 23], 'D': [np.inf, 2., -1.3, -np.inf, 3.5, 0, 10, 0.42, np.nan, -2.5, 23] }) return df.groupby('A').std() sdc_impl = self.jit(test_impl) result_jit = sdc_impl() result_ref = test_impl() # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result_jit, result_ref, check_names=False) def test_dataframe_groupby_var(self): def test_impl(df): return df.groupby('A').var() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_var_no_unboxing(self): def test_impl(): df = pd.DataFrame({ 'A': [2, 1, 2, 1, 2, 2, 1, 0, 3, 1, 3], 'B': np.arange(11), 'C': [np.nan, 2., -1.3, np.nan, 3.5, 0, 10, 0.42, np.nan, -2.5, 23], 'D': [np.inf, 2., -1.3, -np.inf, 3.5, 0, 10, 0.42, np.nan, -2.5, 23] }) return df.groupby('A').var() sdc_impl = self.jit(test_impl) result_jit = sdc_impl() result_ref = test_impl() # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result_jit, result_ref, check_names=False) @skip_numba_jit def test_agg_seq(self): def test_impl(df): A = df.groupby('A')['B'].agg(lambda x: x.max() - x.min()) return A.values hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) # np.testing.assert_array_equal(hpat_func(df), test_impl(df)) self.assertEqual(set(hpat_func(df)), set(test_impl(df))) @skip_numba_jit("BUG: SDC impl of Series.sum returns float64 on as series of ints") def test_agg_seq_sum(self): def test_impl(df): return df.groupby('A')['B'].sum() hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) result = hpat_func(df) result_ref = test_impl(df) pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_agg_seq_count(self): def test_impl(df): return df.groupby('A')['B'].count() hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) result = hpat_func(df) result_ref = test_impl(df) pd.testing.assert_series_equal(result, result_ref, check_names=False) def test_agg_seq_mean(self): def test_impl(df): return df.groupby('A')['B'].mean() hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) result = hpat_func(df) result_ref = test_impl(df) pd.testing.assert_series_equal(result, result_ref, check_names=False) def test_agg_seq_median(self): def test_impl(df): return df.groupby('A')['B'].median() hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) result = hpat_func(df) result_ref = test_impl(df) pd.testing.assert_series_equal(result, result_ref, check_names=False) def test_agg_seq_min(self): def test_impl(df): return df.groupby('A')['B'].min() hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) result = hpat_func(df) result_ref = test_impl(df) pd.testing.assert_series_equal(result, result_ref, check_names=False) @skip_numba_jit def test_agg_seq_min_date(self): def test_impl(df): df2 = df.groupby('A', as_index=False).min() return df2 hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': pd.date_range('2019-1-3', '2019-1-9')}) self.assertEqual(set(hpat_func(df)), set(test_impl(df))) def test_agg_seq_max(self): def test_impl(df): return df.groupby('A')['B'].max() hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) result = hpat_func(df) result_ref = test_impl(df) pd.testing.assert_series_equal(result, result_ref, check_names=False) @skip_numba_jit def test_agg_seq_as_index(self): def test_impl(df): df2 = df.groupby('A', as_index=False).mean() return df2.A.values hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) self.assertEqual(set(hpat_func(df)), set(test_impl(df))) def test_agg_seq_prod(self): def test_impl(df): return df.groupby('A')['B'].prod() hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) result = hpat_func(df) result_ref = test_impl(df) pd.testing.assert_series_equal(result, result_ref, check_names=False) def test_agg_seq_var(self): def test_impl(df): return df.groupby('A')['B'].var() hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) result = hpat_func(df) result_ref = test_impl(df) pd.testing.assert_series_equal(result, result_ref, check_names=False) def test_agg_seq_std(self): def test_impl(df): return df.groupby('A')['B'].std() hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) result = hpat_func(df) result_ref = test_impl(df) pd.testing.assert_series_equal(result, result_ref, check_names=False) @skip_numba_jit def test_agg_multikey_seq(self): def test_impl(df): A = df.groupby(['A', 'C'])['B'].sum() return A.values hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7], 'C': [3, 5, 6, 5, 4, 4, 3]}) self.assertEqual(set(hpat_func(df)), set(test_impl(df))) @skip_numba_jit def test_agg_multikey_parallel(self): def test_impl(in_A, in_B, in_C): df = pd.DataFrame({'A': in_A, 'B': in_B, 'C': in_C}) A = df.groupby(['A', 'C'])['B'].sum() return A.sum() hpat_func = self.jit(locals={'in_A:input': 'distributed', 'in_B:input': 'distributed', 'in_C:input': 'distributed'})(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7], 'C': [3, 5, 6, 5, 4, 4, 3]}) start, end = get_start_end(len(df)) h_A = df.A.values[start:end] h_B = df.B.values[start:end] h_C = df.C.values[start:end] p_A = df.A.values p_B = df.B.values p_C = df.C.values h_res = hpat_func(h_A, h_B, h_C) p_res = test_impl(p_A, p_B, p_C) self.assertEqual(h_res, p_res) @skip_numba_jit def test_agg_parallel(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) A = df.groupby('A')['B'].agg(lambda x: x.max() - x.min()) return A.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @skip_numba_jit def test_agg_parallel_sum(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) A = df.groupby('A')['B'].sum() return A.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @skip_numba_jit def test_agg_parallel_count(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) A = df.groupby('A')['B'].count() return A.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @skip_numba_jit def test_agg_parallel_mean(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) A = df.groupby('A')['B'].mean() return A.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @skip_numba_jit def test_agg_parallel_min(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) A = df.groupby('A')['B'].min() return A.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @skip_numba_jit def test_agg_parallel_max(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) A = df.groupby('A')['B'].max() return A.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @skip_numba_jit def test_agg_parallel_var(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) A = df.groupby('A')['B'].var() return A.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @skip_numba_jit def test_agg_parallel_std(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) A = df.groupby('A')['B'].std() return A.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @unittest.skip('AssertionError - fix needed\n' '16 != 20\n') def test_agg_parallel_str(self): def test_impl(): df = pq.read_table("groupby3.pq").to_pandas() A = df.groupby('A')['B'].agg(lambda x: x.max() - x.min()) return A.sum() hpat_func = self.jit(test_impl) self.assertEqual(hpat_func(), test_impl()) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @skip_numba_jit def test_agg_parallel_all_col(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) df2 = df.groupby('A').max() return df2.B.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @skip_numba_jit def test_agg_parallel_as_index(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) df2 = df.groupby('A', as_index=False).max() return df2.A.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) @skip_numba_jit def test_muti_hiframes_node_filter_agg(self): def test_impl(df, cond): df2 = df[cond] c = df2.groupby('A')['B'].count() return df2.C, c hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7], 'C': [2, 3, -1, 1, 2, 3, -1]}) cond = df.A > 1 res = test_impl(df, cond) h_res = hpat_func(df, cond) self.assertEqual(set(res[1]), set(h_res[1])) np.testing.assert_array_equal(res[0], h_res[0]) @skip_numba_jit def test_agg_seq_str(self): def test_impl(df): A = df.groupby('A')['B'].agg(lambda x: (x == 'aa').sum()) return A.values hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': ['aa', 'b', 'b', 'b', 'aa', 'aa', 'b'], 'B': ['ccc', 'a', 'bb', 'aa', 'dd', 'ggg', 'rr']}) # np.testing.assert_array_equal(hpat_func(df), test_impl(df)) self.assertEqual(set(hpat_func(df)), set(test_impl(df))) @skip_numba_jit def test_agg_seq_count_str(self): def test_impl(df): A = df.groupby('A')['B'].count() return A.values hpat_func = self.jit(test_impl) df = pd.DataFrame({'A': ['aa', 'b', 'b', 'b', 'aa', 'aa', 'b'], 'B': ['ccc', 'a', 'bb', 'aa', 'dd', 'ggg', 'rr']}) # np.testing.assert_array_equal(hpat_func(df), test_impl(df)) self.assertEqual(set(hpat_func(df)), set(test_impl(df))) @skip_numba_jit def test_pivot(self): def test_impl(df): pt = df.pivot_table(index='A', columns='C', values='D', aggfunc='sum') return (pt.small.values, pt.large.values) hpat_func = self.jit(pivots={'pt': ['small', 'large']})(test_impl) self.assertEqual( set(hpat_func(_pivot_df1)[0]), set(test_impl(_pivot_df1)[0])) self.assertEqual( set(hpat_func(_pivot_df1)[1]), set(test_impl(_pivot_df1)[1])) @skip_numba_jit def test_pivot_parallel(self): def test_impl(): df = pd.read_parquet("pivot2.pq") pt = df.pivot_table(index='A', columns='C', values='D', aggfunc='sum') res = pt.small.values.sum() return res hpat_func = self.jit( pivots={'pt': ['small', 'large']})(test_impl) self.assertEqual(hpat_func(), test_impl()) @skip_numba_jit def test_crosstab1(self): def test_impl(df): pt = pd.crosstab(df.A, df.C) return (pt.small.values, pt.large.values) hpat_func = self.jit(pivots={'pt': ['small', 'large']})(test_impl) self.assertEqual( set(hpat_func(_pivot_df1)[0]), set(test_impl(_pivot_df1)[0])) self.assertEqual( set(hpat_func(_pivot_df1)[1]), set(test_impl(_pivot_df1)[1])) @skip_numba_jit def test_crosstab_parallel1(self): def test_impl(): df = pd.read_parquet("pivot2.pq") pt = pd.crosstab(df.A, df.C) res = pt.small.values.sum() return res hpat_func = self.jit( pivots={'pt': ['small', 'large']})(test_impl) self.assertEqual(hpat_func(), test_impl()) @unittest.skip("Implement groupby(lambda) for DataFrame") def test_groupby_lambda(self): def test_impl(df): group = df.groupby(lambda x: x % 2 == 0) return group.count() df = pd.DataFrame({'A': [2, 1, 1, 1, 2, 2, 1], 'B': [-8, 2, 3, 1, 5, 6, 7]}) hpat_func = self.jit(test_impl) pd.testing.assert_frame_equal(hpat_func(df), test_impl(df)) def test_dataframe_groupby_getitem_literal_tuple(self): def test_impl(df): return df.groupby('A')['B', 'C'].count() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_frame_equal(result, result_ref, check_names=False) def test_dataframe_groupby_getitem_literal_str(self): def test_impl(df): return df.groupby('C')['B'].count() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) result = hpat_func(df) result_ref = test_impl(df) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_series_equal(result, result_ref, check_names=False) def test_dataframe_groupby_getitem_unicode_str(self): def test_impl(df, col_name): return df.groupby('A')[col_name].count() hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) col_name = 'C' # pandas returns groupby.generic.SeriesGroupBy object in this case, hence align result_ref result = hpat_func(df, col_name) result_ref = test_impl(df, col_name) # TODO: implement index classes, as current indexes do not have names pd.testing.assert_series_equal(result, result_ref, check_names=False) def test_dataframe_groupby_getitem_repeated(self): def test_impl(df): return df.groupby('A')['B', 'C']['D'] hpat_func = self.jit(test_impl) df = pd.DataFrame(_default_df_numeric_data) with self.assertRaises(Exception) as context: test_impl(df) pandas_exception = context.exception self.assertRaises(type(pandas_exception), hpat_func, df) def test_series_groupby_by_array(self): def test_impl(A, data): return A.groupby(data).count() hpat_func = self.jit(test_impl) data_to_test = [ [True, False, False, True, False, False, True, False, True, True, False], [2, 1, 1, 1, 2, 2, 1, 0, 3, 1, 3], [2, 1, 1, 1, 2, 2, 1, 3, np.nan, 1, np.nan], ['b', 'a', 'a', 'a', 'b', 'b', 'a', ' ', None, 'a', None] ] for series_data, arr_data in product(data_to_test, data_to_test): S = pd.Series(series_data) by_arr = np.asarray(arr_data) # arrays of dtype object cannot be jitted, so skip group by string data for now if by_arr.dtype.name == 'object': continue with self.subTest(series_data=series_data, by_arr=by_arr): result = hpat_func(S, by_arr) result_ref = test_impl(S, by_arr) pd.testing.assert_series_equal(result, result_ref) @unittest.skip("getiter for this type is not implemented yet") def test_series_groupby_iterator_int(self): def test_impl(): A = pd.Series([13, 11, 21, 13, 13, 51, 42, 21]) grouped = A.groupby(A) return [i for i in grouped] hpat_func = self.jit(test_impl) ref_result = test_impl() result = hpat_func() np.testing.assert_array_equal(result, ref_result) if __name__ == "__main__": unittest.main()

39.428733

114

0.560953

5,072

34,855

3.656743

0.06664

0.081091

0.062005

0.048525

0.812369

0.781528

0.769666

0.757373

0.749717

0.747237

0

0.036877

0.291235

34,855

883

115

39.473386

0.713892

0.109855

0

0.685377

0

0.02994

0

0.001133

0.129985

1

0.180207

false

0

0.016248

0.039882

0.288035

0

null

0

1

0

null

0

6

90d90b51c2e2b1b6ea5095029ea4b6f9ba8c1bdc

25

py

Python

leech/__init__.py

philipphager/leech

89e9d1be5487f502289529aa59318f5ad8c94ed8

[ "MIT" ]

2

2018-04-12T06:08:35.000Z

2018-04-14T05:53:33.000Z

leech/__init__.py

philipphager/leech

89e9d1be5487f502289529aa59318f5ad8c94ed8

[ "MIT" ]

2

2018-04-12T07:46:34.000Z

2018-04-12T07:46:58.000Z

leech/__init__.py

philipphager/leech

89e9d1be5487f502289529aa59318f5ad8c94ed8

[ "MIT" ]

null

from .leech import leech

12.5

24

0.8

4

25

5

0.75

0

0.16

25

1

25

0.952381

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

292caed0910edfcd24f6535a91658873f479dc38

26,235

py

Python

src/cicadad/protos/datastore_pb2_grpc.py

cicadatesting/cicada-distributed

cb9caa4107fd5da30e508f34e6e11d0f8f58c142

[ "Apache-2.0" ]

6

2021-07-12T20:53:13.000Z

2022-01-14T19:34:25.000Z

src/cicadad/protos/datastore_pb2_grpc.py

cicadatesting/cicada-distributed

cb9caa4107fd5da30e508f34e6e11d0f8f58c142

[ "Apache-2.0" ]

9

2021-04-24T04:20:12.000Z

2022-03-22T02:14:17.000Z

src/cicadad/protos/datastore_pb2_grpc.py

cicadatesting/cicada-distributed

cb9caa4107fd5da30e508f34e6e11d0f8f58c142

[ "Apache-2.0" ]

null

# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! """Client and server classes corresponding to protobuf-defined services.""" import grpc from cicadad.protos import datastore_pb2 as cicadad_dot_protos_dot_datastore__pb2 from google.protobuf import empty_pb2 as google_dot_protobuf_dot_empty__pb2 class DatastoreStub(object): """Missing associated documentation comment in .proto file.""" def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.AddTestEvent = channel.unary_unary( '/datastore.Datastore/AddTestEvent', request_serializer=cicadad_dot_protos_dot_datastore__pb2.AddEventRequest.SerializeToString, response_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, ) self.GetTestEvents = channel.unary_unary( '/datastore.Datastore/GetTestEvents', request_serializer=cicadad_dot_protos_dot_datastore__pb2.GetEventsRequest.SerializeToString, response_deserializer=cicadad_dot_protos_dot_datastore__pb2.Events.FromString, ) self.AddUserResult = channel.unary_unary( '/datastore.Datastore/AddUserResult', request_serializer=cicadad_dot_protos_dot_datastore__pb2.AddUserResultRequest.SerializeToString, response_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, ) self.SetScenarioResult = channel.unary_unary( '/datastore.Datastore/SetScenarioResult', request_serializer=cicadad_dot_protos_dot_datastore__pb2.SetScenarioResultRequest.SerializeToString, response_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, ) self.MoveUserResults = channel.unary_unary( '/datastore.Datastore/MoveUserResults', request_serializer=cicadad_dot_protos_dot_datastore__pb2.MoveUserResultsRequest.SerializeToString, response_deserializer=cicadad_dot_protos_dot_datastore__pb2.MoveUserResultsResponse.FromString, ) self.MoveScenarioResult = channel.unary_unary( '/datastore.Datastore/MoveScenarioResult', request_serializer=cicadad_dot_protos_dot_datastore__pb2.MoveScenarioResultRequest.SerializeToString, response_deserializer=cicadad_dot_protos_dot_datastore__pb2.MoveScenarioResultResponse.FromString, ) self.DistributeWork = channel.unary_unary( '/datastore.Datastore/DistributeWork', request_serializer=cicadad_dot_protos_dot_datastore__pb2.DistributeWorkRequest.SerializeToString, response_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, ) self.GetUserWork = channel.unary_unary( '/datastore.Datastore/GetUserWork', request_serializer=cicadad_dot_protos_dot_datastore__pb2.GetUserWorkRequest.SerializeToString, response_deserializer=cicadad_dot_protos_dot_datastore__pb2.GetUserWorkResponse.FromString, ) self.AddUserEvent = channel.unary_unary( '/datastore.Datastore/AddUserEvent', request_serializer=cicadad_dot_protos_dot_datastore__pb2.AddEventRequest.SerializeToString, response_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, ) self.GetUserEvents = channel.unary_unary( '/datastore.Datastore/GetUserEvents', request_serializer=cicadad_dot_protos_dot_datastore__pb2.GetEventsRequest.SerializeToString, response_deserializer=cicadad_dot_protos_dot_datastore__pb2.Events.FromString, ) self.AddMetric = channel.unary_unary( '/datastore.Datastore/AddMetric', request_serializer=cicadad_dot_protos_dot_datastore__pb2.AddMetricRequest.SerializeToString, response_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString, ) self.GetMetricTotal = channel.unary_unary( '/datastore.Datastore/GetMetricTotal', request_serializer=cicadad_dot_protos_dot_datastore__pb2.GetMetricRequest.SerializeToString, response_deserializer=cicadad_dot_protos_dot_datastore__pb2.MetricTotalResponse.FromString, ) self.GetLastMetric = channel.unary_unary( '/datastore.Datastore/GetLastMetric', request_serializer=cicadad_dot_protos_dot_datastore__pb2.GetMetricRequest.SerializeToString, response_deserializer=cicadad_dot_protos_dot_datastore__pb2.LastMetricResponse.FromString, ) self.GetMetricRate = channel.unary_unary( '/datastore.Datastore/GetMetricRate', request_serializer=cicadad_dot_protos_dot_datastore__pb2.GetMetricRateRequest.SerializeToString, response_deserializer=cicadad_dot_protos_dot_datastore__pb2.MetricRateResponse.FromString, ) self.GetMetricStatistics = channel.unary_unary( '/datastore.Datastore/GetMetricStatistics', request_serializer=cicadad_dot_protos_dot_datastore__pb2.GetMetricRequest.SerializeToString, response_deserializer=cicadad_dot_protos_dot_datastore__pb2.MetricStatisticsResponse.FromString, ) class DatastoreServicer(object): """Missing associated documentation comment in .proto file.""" def AddTestEvent(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetTestEvents(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def AddUserResult(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def SetScenarioResult(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MoveUserResults(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def MoveScenarioResult(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def DistributeWork(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetUserWork(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def AddUserEvent(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetUserEvents(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def AddMetric(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetMetricTotal(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetLastMetric(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetMetricRate(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetMetricStatistics(self, request, context): """Missing associated documentation comment in .proto file.""" context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_DatastoreServicer_to_server(servicer, server): rpc_method_handlers = { 'AddTestEvent': grpc.unary_unary_rpc_method_handler( servicer.AddTestEvent, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.AddEventRequest.FromString, response_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, ), 'GetTestEvents': grpc.unary_unary_rpc_method_handler( servicer.GetTestEvents, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.GetEventsRequest.FromString, response_serializer=cicadad_dot_protos_dot_datastore__pb2.Events.SerializeToString, ), 'AddUserResult': grpc.unary_unary_rpc_method_handler( servicer.AddUserResult, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.AddUserResultRequest.FromString, response_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, ), 'SetScenarioResult': grpc.unary_unary_rpc_method_handler( servicer.SetScenarioResult, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.SetScenarioResultRequest.FromString, response_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, ), 'MoveUserResults': grpc.unary_unary_rpc_method_handler( servicer.MoveUserResults, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.MoveUserResultsRequest.FromString, response_serializer=cicadad_dot_protos_dot_datastore__pb2.MoveUserResultsResponse.SerializeToString, ), 'MoveScenarioResult': grpc.unary_unary_rpc_method_handler( servicer.MoveScenarioResult, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.MoveScenarioResultRequest.FromString, response_serializer=cicadad_dot_protos_dot_datastore__pb2.MoveScenarioResultResponse.SerializeToString, ), 'DistributeWork': grpc.unary_unary_rpc_method_handler( servicer.DistributeWork, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.DistributeWorkRequest.FromString, response_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, ), 'GetUserWork': grpc.unary_unary_rpc_method_handler( servicer.GetUserWork, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.GetUserWorkRequest.FromString, response_serializer=cicadad_dot_protos_dot_datastore__pb2.GetUserWorkResponse.SerializeToString, ), 'AddUserEvent': grpc.unary_unary_rpc_method_handler( servicer.AddUserEvent, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.AddEventRequest.FromString, response_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, ), 'GetUserEvents': grpc.unary_unary_rpc_method_handler( servicer.GetUserEvents, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.GetEventsRequest.FromString, response_serializer=cicadad_dot_protos_dot_datastore__pb2.Events.SerializeToString, ), 'AddMetric': grpc.unary_unary_rpc_method_handler( servicer.AddMetric, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.AddMetricRequest.FromString, response_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString, ), 'GetMetricTotal': grpc.unary_unary_rpc_method_handler( servicer.GetMetricTotal, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.GetMetricRequest.FromString, response_serializer=cicadad_dot_protos_dot_datastore__pb2.MetricTotalResponse.SerializeToString, ), 'GetLastMetric': grpc.unary_unary_rpc_method_handler( servicer.GetLastMetric, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.GetMetricRequest.FromString, response_serializer=cicadad_dot_protos_dot_datastore__pb2.LastMetricResponse.SerializeToString, ), 'GetMetricRate': grpc.unary_unary_rpc_method_handler( servicer.GetMetricRate, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.GetMetricRateRequest.FromString, response_serializer=cicadad_dot_protos_dot_datastore__pb2.MetricRateResponse.SerializeToString, ), 'GetMetricStatistics': grpc.unary_unary_rpc_method_handler( servicer.GetMetricStatistics, request_deserializer=cicadad_dot_protos_dot_datastore__pb2.GetMetricRequest.FromString, response_serializer=cicadad_dot_protos_dot_datastore__pb2.MetricStatisticsResponse.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'datastore.Datastore', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,)) # This class is part of an EXPERIMENTAL API. class Datastore(object): """Missing associated documentation comment in .proto file.""" @staticmethod def AddTestEvent(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/AddTestEvent', cicadad_dot_protos_dot_datastore__pb2.AddEventRequest.SerializeToString, google_dot_protobuf_dot_empty__pb2.Empty.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetTestEvents(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/GetTestEvents', cicadad_dot_protos_dot_datastore__pb2.GetEventsRequest.SerializeToString, cicadad_dot_protos_dot_datastore__pb2.Events.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def AddUserResult(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/AddUserResult', cicadad_dot_protos_dot_datastore__pb2.AddUserResultRequest.SerializeToString, google_dot_protobuf_dot_empty__pb2.Empty.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def SetScenarioResult(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/SetScenarioResult', cicadad_dot_protos_dot_datastore__pb2.SetScenarioResultRequest.SerializeToString, google_dot_protobuf_dot_empty__pb2.Empty.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MoveUserResults(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/MoveUserResults', cicadad_dot_protos_dot_datastore__pb2.MoveUserResultsRequest.SerializeToString, cicadad_dot_protos_dot_datastore__pb2.MoveUserResultsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def MoveScenarioResult(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/MoveScenarioResult', cicadad_dot_protos_dot_datastore__pb2.MoveScenarioResultRequest.SerializeToString, cicadad_dot_protos_dot_datastore__pb2.MoveScenarioResultResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def DistributeWork(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/DistributeWork', cicadad_dot_protos_dot_datastore__pb2.DistributeWorkRequest.SerializeToString, google_dot_protobuf_dot_empty__pb2.Empty.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetUserWork(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/GetUserWork', cicadad_dot_protos_dot_datastore__pb2.GetUserWorkRequest.SerializeToString, cicadad_dot_protos_dot_datastore__pb2.GetUserWorkResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def AddUserEvent(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/AddUserEvent', cicadad_dot_protos_dot_datastore__pb2.AddEventRequest.SerializeToString, google_dot_protobuf_dot_empty__pb2.Empty.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetUserEvents(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/GetUserEvents', cicadad_dot_protos_dot_datastore__pb2.GetEventsRequest.SerializeToString, cicadad_dot_protos_dot_datastore__pb2.Events.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def AddMetric(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/AddMetric', cicadad_dot_protos_dot_datastore__pb2.AddMetricRequest.SerializeToString, google_dot_protobuf_dot_empty__pb2.Empty.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetMetricTotal(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/GetMetricTotal', cicadad_dot_protos_dot_datastore__pb2.GetMetricRequest.SerializeToString, cicadad_dot_protos_dot_datastore__pb2.MetricTotalResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetLastMetric(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/GetLastMetric', cicadad_dot_protos_dot_datastore__pb2.GetMetricRequest.SerializeToString, cicadad_dot_protos_dot_datastore__pb2.LastMetricResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetMetricRate(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/GetMetricRate', cicadad_dot_protos_dot_datastore__pb2.GetMetricRateRequest.SerializeToString, cicadad_dot_protos_dot_datastore__pb2.MetricRateResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata) @staticmethod def GetMetricStatistics(request, target, options=(), channel_credentials=None, call_credentials=None, insecure=False, compression=None, wait_for_ready=None, timeout=None, metadata=None): return grpc.experimental.unary_unary(request, target, '/datastore.Datastore/GetMetricStatistics', cicadad_dot_protos_dot_datastore__pb2.GetMetricRequest.SerializeToString, cicadad_dot_protos_dot_datastore__pb2.MetricStatisticsResponse.FromString, options, channel_credentials, insecure, call_credentials, compression, wait_for_ready, timeout, metadata)

49.5

123

0.682752

2,345

26,235

7.266098

0.054158

0.052116

0.068549

0.081401

0.875697

0.844885

0.841423

0.7896

0.673748

0.637244

0

0.004774

0.249438

26,235

529

124

49.593573

0.860545

0.047875

0

0.615551

1

0

0.078746

0.041928

0

1

0.069114

false

0

0.006479

0.032397

0.114471

0

null

0

1

0

1

0

1

0

null

0

6

2961ef2e3b4b3491899de158441864bde07be3a2

20

py

Python

msgtracker/endpoints/__init__.py

mpillar/msg-tracker

16edb9d555795d0eec625dd954e14f914cbbbe2b

[ "MIT" ]

null

msgtracker/endpoints/__init__.py

mpillar/msg-tracker

16edb9d555795d0eec625dd954e14f914cbbbe2b

[ "MIT" ]

null

msgtracker/endpoints/__init__.py

mpillar/msg-tracker

16edb9d555795d0eec625dd954e14f914cbbbe2b

[ "MIT" ]

null

from . import slack

10

19

0.75

3

20

5

1

0

0.2

20

1

20

0.9375

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

296798d4c7b6fd649de9ae9e5d76dd5f38eaa7e0

30

py

Python

messaging_components/brokers/artemis/management/__init__.py

fgiorgetti/qpid-dispatch-tests

164c609d28db87692eed53d5361aa1ee5c97375c

[ "Apache-2.0" ]

null

messaging_components/brokers/artemis/management/__init__.py

fgiorgetti/qpid-dispatch-tests

164c609d28db87692eed53d5361aa1ee5c97375c

[ "Apache-2.0" ]

null

messaging_components/brokers/artemis/management/__init__.py

fgiorgetti/qpid-dispatch-tests

164c609d28db87692eed53d5361aa1ee5c97375c

[ "Apache-2.0" ]

null

from .jolokia_client import *

15

29

0.8

4

30

5.75

1

0

0.133333

30

1

30

0.884615

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

466a5f643ce0af3c0d843317db00fa916b3a8405

40

py

Python

doepy/param_covar/__init__.py

scwolof/doepy

acb2cad95428de2c14b28563cff1aa30679e1f39

[ "MIT" ]

1

2020-04-23T13:43:35.000Z

doepy/param_covar/__init__.py

scwolof/doepy

acb2cad95428de2c14b28563cff1aa30679e1f39

[ "MIT" ]

null

doepy/param_covar/__init__.py

scwolof/doepy

acb2cad95428de2c14b28563cff1aa30679e1f39

[ "MIT" ]

1

2021-06-13T14:38:32.000Z

from .laplace import state_space_laplace

40

0.9

6

40

5.666667

0.833333

0

0.075

40

1

40

0.918919

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

466a895a06163dfc7ddf957ab921a0d41944ec98

126

py

Python

apps/plugins/tanzawa_plugin/now/admin.py

rmdes/tanzawa

d53baa10bd6c217cd18628437a88a43e3bd02b70

[ "Apache-2.0" ]

25

2021-06-13T03:38:44.000Z

2022-03-15T15:53:31.000Z

apps/plugins/tanzawa_plugin/now/admin.py

rmdes/tanzawa

d53baa10bd6c217cd18628437a88a43e3bd02b70

[ "Apache-2.0" ]

59

2021-06-12T23:35:06.000Z

2022-03-24T21:40:24.000Z

apps/plugins/tanzawa_plugin/now/admin.py

rmdes/tanzawa

d53baa10bd6c217cd18628437a88a43e3bd02b70

[ "Apache-2.0" ]

null

from django.contrib import admin from . import models admin.site.register(models.TNow) admin.site.register(models.TFileNow)

18

36

0.809524

18

126

5.666667

0.555556

0.176471

0.333333

0.45098

0

0.095238

126

6

37

21

0.894737

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

46b072cf85bd61275fdf6d2b12fa53f3915d98ce

22,748

py

Python

modules/ESP32/greekc.py

ccccmagicboy/MicroPython_fw

d2049bc19e3d5010f5d6d0d17aa13a8693914fbd

[ "MIT" ]

23

2020-01-22T00:40:20.000Z

2021-08-03T20:42:07.000Z

modules/ESP32/greekc.py

ccccmagicboy/MicroPython_fw

d2049bc19e3d5010f5d6d0d17aa13a8693914fbd

[ "MIT" ]

10

2020-02-18T09:57:04.000Z

2020-03-04T11:39:17.000Z

modules/ESP32/greekc.py

ccccmagicboy/MicroPython_fw

d2049bc19e3d5010f5d6d0d17aa13a8693914fbd

[ "MIT" ]

5

2020-02-20T09:35:45.000Z

2022-01-04T16:23:13.000Z

def glyphs(): return 96 _font =\ b'\x00\x4a\x5a\x0e\x4d\x57\x52\x46\x51\x48\x52\x54\x53\x48\x52'\ b'\x46\x20\x52\x52\x48\x52\x4e\x20\x52\x52\x59\x51\x5a\x52\x5b'\ b'\x53\x5a\x52\x59\x0b\x4a\x5a\x4e\x46\x4d\x4d\x20\x52\x4f\x46'\ b'\x4d\x4d\x20\x52\x56\x46\x55\x4d\x20\x52\x57\x46\x55\x4d\x0b'\ b'\x48\x5d\x53\x42\x4c\x62\x20\x52\x59\x42\x52\x62\x20\x52\x4c'\ b'\x4f\x5a\x4f\x20\x52\x4b\x55\x59\x55\x29\x48\x5c\x50\x42\x50'\ b'\x5f\x20\x52\x54\x42\x54\x5f\x20\x52\x58\x49\x57\x4a\x58\x4b'\ b'\x59\x4a\x59\x49\x57\x47\x54\x46\x50\x46\x4d\x47\x4b\x49\x4b'\ b'\x4b\x4c\x4d\x4d\x4e\x4f\x4f\x55\x51\x57\x52\x59\x54\x20\x52'\ b'\x4b\x4b\x4d\x4d\x4f\x4e\x55\x50\x57\x51\x58\x52\x59\x54\x59'\ b'\x58\x57\x5a\x54\x5b\x50\x5b\x4d\x5a\x4b\x58\x4b\x57\x4c\x56'\ b'\x4d\x57\x4c\x58\x1f\x46\x5e\x5b\x46\x49\x5b\x20\x52\x4e\x46'\ b'\x50\x48\x50\x4a\x4f\x4c\x4d\x4d\x4b\x4d\x49\x4b\x49\x49\x4a'\ b'\x47\x4c\x46\x4e\x46\x50\x47\x53\x48\x56\x48\x59\x47\x5b\x46'\ b'\x20\x52\x57\x54\x55\x55\x54\x57\x54\x59\x56\x5b\x58\x5b\x5a'\ b'\x5a\x5b\x58\x5b\x56\x59\x54\x57\x54\x30\x46\x5f\x5b\x4e\x5a'\ b'\x4f\x5b\x50\x5c\x4f\x5c\x4e\x5b\x4d\x5a\x4d\x59\x4e\x58\x50'\ b'\x56\x55\x54\x58\x52\x5a\x50\x5b\x4d\x5b\x4a\x5a\x49\x58\x49'\ b'\x55\x4a\x53\x50\x4f\x52\x4d\x53\x4b\x53\x49\x52\x47\x50\x46'\ b'\x4e\x47\x4d\x49\x4d\x4b\x4e\x4e\x50\x51\x55\x58\x57\x5a\x5a'\ b'\x5b\x5b\x5b\x5c\x5a\x5c\x59\x20\x52\x4d\x5b\x4b\x5a\x4a\x58'\ b'\x4a\x55\x4b\x53\x4d\x51\x20\x52\x4d\x4b\x4e\x4d\x56\x58\x58'\ b'\x5a\x5a\x5b\x05\x4e\x56\x52\x46\x51\x4d\x20\x52\x53\x46\x51'\ b'\x4d\x17\x4b\x59\x55\x42\x53\x44\x51\x47\x4f\x4b\x4e\x50\x4e'\ b'\x54\x4f\x59\x51\x5d\x53\x60\x55\x62\x56\x62\x20\x52\x55\x42'\ b'\x56\x42\x54\x44\x52\x47\x50\x4b\x4f\x50\x4f\x54\x50\x59\x52'\ b'\x5d\x54\x60\x56\x62\x17\x4b\x59\x4e\x42\x50\x44\x52\x47\x54'\ b'\x4b\x55\x50\x55\x54\x54\x59\x52\x5d\x50\x60\x4e\x62\x4f\x62'\ b'\x20\x52\x4e\x42\x4f\x42\x51\x44\x53\x47\x55\x4b\x56\x50\x56'\ b'\x54\x55\x59\x53\x5d\x51\x60\x4f\x62\x08\x4a\x5a\x52\x4c\x52'\ b'\x58\x20\x52\x4d\x4f\x57\x55\x20\x52\x57\x4f\x4d\x55\x05\x45'\ b'\x5f\x52\x49\x52\x5b\x20\x52\x49\x52\x5b\x52\x07\x4e\x56\x53'\ b'\x57\x52\x58\x51\x57\x52\x56\x53\x57\x53\x59\x51\x5b\x02\x45'\ b'\x5f\x49\x52\x5b\x52\x05\x4e\x56\x52\x56\x51\x57\x52\x58\x53'\ b'\x57\x52\x56\x02\x47\x5d\x5b\x42\x49\x62\x27\x48\x5c\x51\x46'\ b'\x4e\x47\x4c\x4a\x4b\x4f\x4b\x52\x4c\x57\x4e\x5a\x51\x5b\x53'\ b'\x5b\x56\x5a\x58\x57\x59\x52\x59\x4f\x58\x4a\x56\x47\x53\x46'\ b'\x51\x46\x20\x52\x51\x46\x4f\x47\x4e\x48\x4d\x4a\x4c\x4f\x4c'\ b'\x52\x4d\x57\x4e\x59\x4f\x5a\x51\x5b\x20\x52\x53\x5b\x55\x5a'\ b'\x56\x59\x57\x57\x58\x52\x58\x4f\x57\x4a\x56\x48\x55\x47\x53'\ b'\x46\x0a\x48\x5c\x4e\x4a\x50\x49\x53\x46\x53\x5b\x20\x52\x52'\ b'\x47\x52\x5b\x20\x52\x4e\x5b\x57\x5b\x2c\x48\x5c\x4c\x4a\x4d'\ b'\x4b\x4c\x4c\x4b\x4b\x4b\x4a\x4c\x48\x4d\x47\x50\x46\x54\x46'\ b'\x57\x47\x58\x48\x59\x4a\x59\x4c\x58\x4e\x55\x50\x50\x52\x4e'\ b'\x53\x4c\x55\x4b\x58\x4b\x5b\x20\x52\x54\x46\x56\x47\x57\x48'\ b'\x58\x4a\x58\x4c\x57\x4e\x54\x50\x50\x52\x20\x52\x4b\x59\x4c'\ b'\x58\x4e\x58\x53\x5a\x56\x5a\x58\x59\x59\x58\x20\x52\x4e\x58'\ b'\x53\x5b\x57\x5b\x58\x5a\x59\x58\x59\x56\x2e\x48\x5c\x4c\x4a'\ b'\x4d\x4b\x4c\x4c\x4b\x4b\x4b\x4a\x4c\x48\x4d\x47\x50\x46\x54'\ b'\x46\x57\x47\x58\x49\x58\x4c\x57\x4e\x54\x4f\x51\x4f\x20\x52'\ b'\x54\x46\x56\x47\x57\x49\x57\x4c\x56\x4e\x54\x4f\x20\x52\x54'\ b'\x4f\x56\x50\x58\x52\x59\x54\x59\x57\x58\x59\x57\x5a\x54\x5b'\ b'\x50\x5b\x4d\x5a\x4c\x59\x4b\x57\x4b\x56\x4c\x55\x4d\x56\x4c'\ b'\x57\x20\x52\x57\x51\x58\x54\x58\x57\x57\x59\x56\x5a\x54\x5b'\ b'\x0c\x48\x5c\x54\x48\x54\x5b\x20\x52\x55\x46\x55\x5b\x20\x52'\ b'\x55\x46\x4a\x55\x5a\x55\x20\x52\x51\x5b\x58\x5b\x26\x48\x5c'\ b'\x4d\x46\x4b\x50\x20\x52\x4b\x50\x4d\x4e\x50\x4d\x53\x4d\x56'\ b'\x4e\x58\x50\x59\x53\x59\x55\x58\x58\x56\x5a\x53\x5b\x50\x5b'\ b'\x4d\x5a\x4c\x59\x4b\x57\x4b\x56\x4c\x55\x4d\x56\x4c\x57\x20'\ b'\x52\x53\x4d\x55\x4e\x57\x50\x58\x53\x58\x55\x57\x58\x55\x5a'\ b'\x53\x5b\x20\x52\x4d\x46\x57\x46\x20\x52\x4d\x47\x52\x47\x57'\ b'\x46\x2f\x48\x5c\x57\x49\x56\x4a\x57\x4b\x58\x4a\x58\x49\x57'\ b'\x47\x55\x46\x52\x46\x4f\x47\x4d\x49\x4c\x4b\x4b\x4f\x4b\x55'\ b'\x4c\x58\x4e\x5a\x51\x5b\x53\x5b\x56\x5a\x58\x58\x59\x55\x59'\ b'\x54\x58\x51\x56\x4f\x53\x4e\x52\x4e\x4f\x4f\x4d\x51\x4c\x54'\ b'\x20\x52\x52\x46\x50\x47\x4e\x49\x4d\x4b\x4c\x4f\x4c\x55\x4d'\ b'\x58\x4f\x5a\x51\x5b\x20\x52\x53\x5b\x55\x5a\x57\x58\x58\x55'\ b'\x58\x54\x57\x51\x55\x4f\x53\x4e\x1e\x48\x5c\x4b\x46\x4b\x4c'\ b'\x20\x52\x4b\x4a\x4c\x48\x4e\x46\x50\x46\x55\x49\x57\x49\x58'\ b'\x48\x59\x46\x20\x52\x4c\x48\x4e\x47\x50\x47\x55\x49\x20\x52'\ b'\x59\x46\x59\x49\x58\x4c\x54\x51\x53\x53\x52\x56\x52\x5b\x20'\ b'\x52\x58\x4c\x53\x51\x52\x53\x51\x56\x51\x5b\x3e\x48\x5c\x50'\ b'\x46\x4d\x47\x4c\x49\x4c\x4c\x4d\x4e\x50\x4f\x54\x4f\x57\x4e'\ b'\x58\x4c\x58\x49\x57\x47\x54\x46\x50\x46\x20\x52\x50\x46\x4e'\ b'\x47\x4d\x49\x4d\x4c\x4e\x4e\x50\x4f\x20\x52\x54\x4f\x56\x4e'\ b'\x57\x4c\x57\x49\x56\x47\x54\x46\x20\x52\x50\x4f\x4d\x50\x4c'\ b'\x51\x4b\x53\x4b\x57\x4c\x59\x4d\x5a\x50\x5b\x54\x5b\x57\x5a'\ b'\x58\x59\x59\x57\x59\x53\x58\x51\x57\x50\x54\x4f\x20\x52\x50'\ b'\x4f\x4e\x50\x4d\x51\x4c\x53\x4c\x57\x4d\x59\x4e\x5a\x50\x5b'\ b'\x20\x52\x54\x5b\x56\x5a\x57\x59\x58\x57\x58\x53\x57\x51\x56'\ b'\x50\x54\x4f\x2f\x48\x5c\x58\x4d\x57\x50\x55\x52\x52\x53\x51'\ b'\x53\x4e\x52\x4c\x50\x4b\x4d\x4b\x4c\x4c\x49\x4e\x47\x51\x46'\ b'\x53\x46\x56\x47\x58\x49\x59\x4c\x59\x52\x58\x56\x57\x58\x55'\ b'\x5a\x52\x5b\x4f\x5b\x4d\x5a\x4c\x58\x4c\x57\x4d\x56\x4e\x57'\ b'\x4d\x58\x20\x52\x51\x53\x4f\x52\x4d\x50\x4c\x4d\x4c\x4c\x4d'\ b'\x49\x4f\x47\x51\x46\x20\x52\x53\x46\x55\x47\x57\x49\x58\x4c'\ b'\x58\x52\x57\x56\x56\x58\x54\x5a\x52\x5b\x0b\x4e\x56\x52\x4f'\ b'\x51\x50\x52\x51\x53\x50\x52\x4f\x20\x52\x52\x56\x51\x57\x52'\ b'\x58\x53\x57\x52\x56\x0d\x4e\x56\x52\x4f\x51\x50\x52\x51\x53'\ b'\x50\x52\x4f\x20\x52\x53\x57\x52\x58\x51\x57\x52\x56\x53\x57'\ b'\x53\x59\x51\x5b\x03\x46\x5e\x5a\x49\x4a\x52\x5a\x5b\x05\x45'\ b'\x5f\x49\x4f\x5b\x4f\x20\x52\x49\x55\x5b\x55\x03\x46\x5e\x4a'\ b'\x49\x5a\x52\x4a\x5b\x1f\x49\x5b\x4d\x4a\x4e\x4b\x4d\x4c\x4c'\ b'\x4b\x4c\x4a\x4d\x48\x4e\x47\x50\x46\x53\x46\x56\x47\x57\x48'\ b'\x58\x4a\x58\x4c\x57\x4e\x56\x4f\x52\x51\x52\x54\x20\x52\x53'\ b'\x46\x55\x47\x56\x48\x57\x4a\x57\x4c\x56\x4e\x54\x50\x20\x52'\ b'\x52\x59\x51\x5a\x52\x5b\x53\x5a\x52\x59\x37\x45\x60\x57\x4e'\ b'\x56\x4c\x54\x4b\x51\x4b\x4f\x4c\x4e\x4d\x4d\x50\x4d\x53\x4e'\ b'\x55\x50\x56\x53\x56\x55\x55\x56\x53\x20\x52\x51\x4b\x4f\x4d'\ b'\x4e\x50\x4e\x53\x4f\x55\x50\x56\x20\x52\x57\x4b\x56\x53\x56'\ b'\x55\x58\x56\x5a\x56\x5c\x54\x5d\x51\x5d\x4f\x5c\x4c\x5b\x4a'\ b'\x59\x48\x57\x47\x54\x46\x51\x46\x4e\x47\x4c\x48\x4a\x4a\x49'\ b'\x4c\x48\x4f\x48\x52\x49\x55\x4a\x57\x4c\x59\x4e\x5a\x51\x5b'\ b'\x54\x5b\x57\x5a\x59\x59\x5a\x58\x20\x52\x58\x4b\x57\x53\x57'\ b'\x55\x58\x56\x11\x48\x5c\x52\x46\x4b\x5b\x20\x52\x52\x46\x59'\ b'\x5b\x20\x52\x52\x49\x58\x5b\x20\x52\x4d\x55\x56\x55\x20\x52'\ b'\x49\x5b\x4f\x5b\x20\x52\x55\x5b\x5b\x5b\x2c\x47\x5d\x4c\x46'\ b'\x4c\x5b\x20\x52\x4d\x46\x4d\x5b\x20\x52\x49\x46\x55\x46\x58'\ b'\x47\x59\x48\x5a\x4a\x5a\x4c\x59\x4e\x58\x4f\x55\x50\x20\x52'\ b'\x55\x46\x57\x47\x58\x48\x59\x4a\x59\x4c\x58\x4e\x57\x4f\x55'\ b'\x50\x20\x52\x4d\x50\x55\x50\x58\x51\x59\x52\x5a\x54\x5a\x57'\ b'\x59\x59\x58\x5a\x55\x5b\x49\x5b\x20\x52\x55\x50\x57\x51\x58'\ b'\x52\x59\x54\x59\x57\x58\x59\x57\x5a\x55\x5b\x14\x48\x5c\x4b'\ b'\x46\x58\x5b\x20\x52\x4c\x46\x59\x5b\x20\x52\x59\x46\x4b\x5b'\ b'\x20\x52\x49\x46\x4f\x46\x20\x52\x55\x46\x5b\x46\x20\x52\x49'\ b'\x5b\x4f\x5b\x20\x52\x55\x5b\x5b\x5b\x0e\x48\x5c\x52\x46\x4a'\ b'\x5b\x20\x52\x52\x46\x5a\x5b\x20\x52\x52\x49\x59\x5b\x20\x52'\ b'\x4b\x5a\x59\x5a\x20\x52\x4a\x5b\x5a\x5b\x15\x47\x5c\x4c\x46'\ b'\x4c\x5b\x20\x52\x4d\x46\x4d\x5b\x20\x52\x53\x4c\x53\x54\x20'\ b'\x52\x49\x46\x59\x46\x59\x4c\x58\x46\x20\x52\x4d\x50\x53\x50'\ b'\x20\x52\x49\x5b\x59\x5b\x59\x55\x58\x5b\x2f\x48\x5d\x52\x46'\ b'\x52\x5b\x20\x52\x53\x46\x53\x5b\x20\x52\x50\x4b\x4d\x4c\x4c'\ b'\x4d\x4b\x4f\x4b\x52\x4c\x54\x4d\x55\x50\x56\x55\x56\x58\x55'\ b'\x59\x54\x5a\x52\x5a\x4f\x59\x4d\x58\x4c\x55\x4b\x50\x4b\x20'\ b'\x52\x50\x4b\x4e\x4c\x4d\x4d\x4c\x4f\x4c\x52\x4d\x54\x4e\x55'\ b'\x50\x56\x20\x52\x55\x56\x57\x55\x58\x54\x59\x52\x59\x4f\x58'\ b'\x4d\x57\x4c\x55\x4b\x20\x52\x4f\x46\x56\x46\x20\x52\x4f\x5b'\ b'\x56\x5b\x0d\x49\x5b\x4e\x46\x4e\x5b\x20\x52\x4f\x46\x4f\x5b'\ b'\x20\x52\x4b\x46\x5a\x46\x5a\x4c\x59\x46\x20\x52\x4b\x5b\x52'\ b'\x5b\x1a\x46\x5e\x4b\x46\x4b\x5b\x20\x52\x4c\x46\x4c\x5b\x20'\ b'\x52\x58\x46\x58\x5b\x20\x52\x59\x46\x59\x5b\x20\x52\x48\x46'\ b'\x4f\x46\x20\x52\x55\x46\x5c\x46\x20\x52\x4c\x50\x58\x50\x20'\ b'\x52\x48\x5b\x4f\x5b\x20\x52\x55\x5b\x5c\x5b\x0b\x4d\x58\x52'\ b'\x46\x52\x5b\x20\x52\x53\x46\x53\x5b\x20\x52\x4f\x46\x56\x46'\ b'\x20\x52\x4f\x5b\x56\x5b\x05\x50\x55\x52\x51\x52\x52\x53\x52'\ b'\x53\x51\x52\x51\x1a\x46\x5c\x4b\x46\x4b\x5b\x20\x52\x4c\x46'\ b'\x4c\x5b\x20\x52\x59\x46\x4c\x53\x20\x52\x51\x4f\x59\x5b\x20'\ b'\x52\x50\x4f\x58\x5b\x20\x52\x48\x46\x4f\x46\x20\x52\x55\x46'\ b'\x5b\x46\x20\x52\x48\x5b\x4f\x5b\x20\x52\x55\x5b\x5b\x5b\x0e'\ b'\x48\x5c\x52\x46\x4b\x5b\x20\x52\x52\x46\x59\x5b\x20\x52\x52'\ b'\x49\x58\x5b\x20\x52\x49\x5b\x4f\x5b\x20\x52\x55\x5b\x5b\x5b'\ b'\x1d\x46\x5f\x4b\x46\x4b\x5b\x20\x52\x4c\x46\x52\x58\x20\x52'\ b'\x4b\x46\x52\x5b\x20\x52\x59\x46\x52\x5b\x20\x52\x59\x46\x59'\ b'\x5b\x20\x52\x5a\x46\x5a\x5b\x20\x52\x48\x46\x4c\x46\x20\x52'\ b'\x59\x46\x5d\x46\x20\x52\x48\x5b\x4e\x5b\x20\x52\x56\x5b\x5d'\ b'\x5b\x14\x47\x5e\x4c\x46\x4c\x5b\x20\x52\x4d\x46\x59\x59\x20'\ b'\x52\x4d\x48\x59\x5b\x20\x52\x59\x46\x59\x5b\x20\x52\x49\x46'\ b'\x4d\x46\x20\x52\x56\x46\x5c\x46\x20\x52\x49\x5b\x4f\x5b\x2b'\ b'\x47\x5d\x51\x46\x4e\x47\x4c\x49\x4b\x4b\x4a\x4f\x4a\x52\x4b'\ b'\x56\x4c\x58\x4e\x5a\x51\x5b\x53\x5b\x56\x5a\x58\x58\x59\x56'\ b'\x5a\x52\x5a\x4f\x59\x4b\x58\x49\x56\x47\x53\x46\x51\x46\x20'\ b'\x52\x51\x46\x4f\x47\x4d\x49\x4c\x4b\x4b\x4f\x4b\x52\x4c\x56'\ b'\x4d\x58\x4f\x5a\x51\x5b\x20\x52\x53\x5b\x55\x5a\x57\x58\x58'\ b'\x56\x59\x52\x59\x4f\x58\x4b\x57\x49\x55\x47\x53\x46\x14\x46'\ b'\x5e\x4b\x46\x4b\x5b\x20\x52\x4c\x46\x4c\x5b\x20\x52\x58\x46'\ b'\x58\x5b\x20\x52\x59\x46\x59\x5b\x20\x52\x48\x46\x5c\x46\x20'\ b'\x52\x48\x5b\x4f\x5b\x20\x52\x55\x5b\x5c\x5b\x37\x47\x5d\x51'\ b'\x46\x4e\x47\x4c\x49\x4b\x4b\x4a\x4f\x4a\x52\x4b\x56\x4c\x58'\ b'\x4e\x5a\x51\x5b\x53\x5b\x56\x5a\x58\x58\x59\x56\x5a\x52\x5a'\ b'\x4f\x59\x4b\x58\x49\x56\x47\x53\x46\x51\x46\x20\x52\x51\x46'\ b'\x4f\x47\x4d\x49\x4c\x4b\x4b\x4f\x4b\x52\x4c\x56\x4d\x58\x4f'\ b'\x5a\x51\x5b\x20\x52\x53\x5b\x55\x5a\x57\x58\x58\x56\x59\x52'\ b'\x59\x4f\x58\x4b\x57\x49\x55\x47\x53\x46\x20\x52\x4f\x4d\x4f'\ b'\x54\x20\x52\x55\x4d\x55\x54\x20\x52\x4f\x50\x55\x50\x20\x52'\ b'\x4f\x51\x55\x51\x1c\x47\x5d\x4c\x46\x4c\x5b\x20\x52\x4d\x46'\ b'\x4d\x5b\x20\x52\x49\x46\x55\x46\x58\x47\x59\x48\x5a\x4a\x5a'\ b'\x4d\x59\x4f\x58\x50\x55\x51\x4d\x51\x20\x52\x55\x46\x57\x47'\ b'\x58\x48\x59\x4a\x59\x4d\x58\x4f\x57\x50\x55\x51\x20\x52\x49'\ b'\x5b\x50\x5b\x13\x48\x5d\x4b\x46\x52\x50\x4a\x5b\x20\x52\x4a'\ b'\x46\x51\x50\x20\x52\x4a\x46\x59\x46\x5a\x4c\x58\x46\x20\x52'\ b'\x4b\x5a\x58\x5a\x20\x52\x4a\x5b\x59\x5b\x5a\x55\x58\x5b\x0f'\ b'\x49\x5c\x52\x46\x52\x5b\x20\x52\x53\x46\x53\x5b\x20\x52\x4c'\ b'\x46\x4b\x4c\x4b\x46\x5a\x46\x5a\x4c\x59\x46\x20\x52\x4f\x5b'\ b'\x56\x5b\x20\x49\x5c\x4b\x4b\x4b\x49\x4c\x47\x4d\x46\x4f\x46'\ b'\x50\x47\x51\x49\x52\x4d\x52\x5b\x20\x52\x4b\x49\x4d\x47\x4f'\ b'\x47\x51\x49\x20\x52\x5a\x4b\x5a\x49\x59\x47\x58\x46\x56\x46'\ b'\x55\x47\x54\x49\x53\x4d\x53\x5b\x20\x52\x5a\x49\x58\x47\x56'\ b'\x47\x54\x49\x20\x52\x4f\x5b\x56\x5b\x0d\x4b\x59\x51\x46\x4f'\ b'\x47\x4e\x49\x4e\x4b\x4f\x4d\x51\x4e\x53\x4e\x55\x4d\x56\x4b'\ b'\x56\x49\x55\x47\x53\x46\x51\x46\x2a\x47\x5d\x4a\x58\x4b\x5b'\ b'\x4f\x5b\x4d\x57\x4b\x53\x4a\x50\x4a\x4c\x4b\x49\x4d\x47\x50'\ b'\x46\x54\x46\x57\x47\x59\x49\x5a\x4c\x5a\x50\x59\x53\x57\x57'\ b'\x55\x5b\x59\x5b\x5a\x58\x20\x52\x4d\x57\x4c\x54\x4b\x50\x4b'\ b'\x4c\x4c\x49\x4e\x47\x50\x46\x20\x52\x54\x46\x56\x47\x58\x49'\ b'\x59\x4c\x59\x50\x58\x54\x57\x57\x20\x52\x4b\x5a\x4e\x5a\x20'\ b'\x52\x56\x5a\x59\x5a\x23\x47\x5d\x4b\x45\x4a\x4a\x20\x52\x5a'\ b'\x45\x59\x4a\x20\x52\x4f\x4e\x4e\x53\x20\x52\x56\x4e\x55\x53'\ b'\x20\x52\x4b\x57\x4a\x5c\x20\x52\x5a\x57\x59\x5c\x20\x52\x4b'\ b'\x47\x59\x47\x20\x52\x4b\x48\x59\x48\x20\x52\x4f\x50\x55\x50'\ b'\x20\x52\x4f\x51\x55\x51\x20\x52\x4b\x59\x59\x59\x20\x52\x4b'\ b'\x5a\x59\x5a\x28\x47\x5e\x52\x46\x52\x5b\x20\x52\x53\x46\x53'\ b'\x5b\x20\x52\x49\x4d\x4a\x4c\x4c\x4d\x4d\x51\x4e\x53\x4f\x54'\ b'\x51\x55\x20\x52\x4a\x4c\x4b\x4d\x4c\x51\x4d\x53\x4e\x54\x51'\ b'\x55\x54\x55\x57\x54\x58\x53\x59\x51\x5a\x4d\x5b\x4c\x20\x52'\ b'\x54\x55\x56\x54\x57\x53\x58\x51\x59\x4d\x5b\x4c\x5c\x4d\x20'\ b'\x52\x4f\x46\x56\x46\x20\x52\x4f\x5b\x56\x5b\x0f\x48\x5c\x58'\ b'\x46\x4b\x5b\x20\x52\x59\x46\x4c\x5b\x20\x52\x4c\x46\x4b\x4c'\ b'\x4b\x46\x59\x46\x20\x52\x4b\x5b\x59\x5b\x59\x55\x58\x5b\x0b'\ b'\x4b\x59\x4f\x42\x4f\x62\x20\x52\x50\x42\x50\x62\x20\x52\x4f'\ b'\x42\x56\x42\x20\x52\x4f\x62\x56\x62\x02\x4b\x59\x4b\x46\x59'\ b'\x5e\x0b\x4b\x59\x54\x42\x54\x62\x20\x52\x55\x42\x55\x62\x20'\ b'\x52\x4e\x42\x55\x42\x20\x52\x4e\x62\x55\x62\x07\x47\x5d\x4a'\ b'\x54\x52\x4f\x5a\x54\x20\x52\x4a\x54\x52\x50\x5a\x54\x02\x48'\ b'\x5c\x48\x62\x5c\x62\x06\x4c\x58\x50\x46\x55\x4c\x20\x52\x50'\ b'\x46\x4f\x47\x55\x4c\x27\x47\x5e\x51\x4d\x4e\x4e\x4c\x50\x4b'\ b'\x52\x4a\x55\x4a\x58\x4b\x5a\x4e\x5b\x50\x5b\x52\x5a\x55\x57'\ b'\x57\x54\x59\x50\x5a\x4d\x20\x52\x51\x4d\x4f\x4e\x4d\x50\x4c'\ b'\x52\x4b\x55\x4b\x58\x4c\x5a\x4e\x5b\x20\x52\x51\x4d\x53\x4d'\ b'\x55\x4e\x56\x50\x58\x58\x59\x5a\x5a\x5b\x20\x52\x53\x4d\x54'\ b'\x4e\x55\x50\x57\x58\x58\x5a\x5a\x5b\x5b\x5b\x38\x47\x5c\x54'\ b'\x46\x51\x47\x4f\x49\x4d\x4d\x4c\x50\x4b\x54\x4a\x5a\x49\x62'\ b'\x20\x52\x54\x46\x52\x47\x50\x49\x4e\x4d\x4d\x50\x4c\x54\x4b'\ b'\x5a\x4a\x62\x20\x52\x54\x46\x56\x46\x58\x47\x59\x48\x59\x4b'\ b'\x58\x4d\x57\x4e\x54\x4f\x50\x4f\x20\x52\x56\x46\x58\x48\x58'\ b'\x4b\x57\x4d\x56\x4e\x54\x4f\x20\x52\x50\x4f\x54\x50\x56\x52'\ b'\x57\x54\x57\x57\x56\x59\x55\x5a\x52\x5b\x50\x5b\x4e\x5a\x4d'\ b'\x59\x4c\x56\x20\x52\x50\x4f\x53\x50\x55\x52\x56\x54\x56\x57'\ b'\x55\x59\x54\x5a\x52\x5b\x16\x49\x5b\x4b\x4d\x4d\x4d\x4f\x4e'\ b'\x50\x50\x55\x5f\x56\x61\x57\x62\x20\x52\x4d\x4d\x4e\x4e\x4f'\ b'\x50\x54\x5f\x55\x61\x57\x62\x59\x62\x20\x52\x5a\x4d\x59\x4f'\ b'\x57\x52\x4d\x5d\x4b\x60\x4a\x62\x2b\x49\x5c\x56\x4e\x54\x4d'\ b'\x52\x4d\x4f\x4e\x4d\x51\x4c\x54\x4c\x57\x4d\x59\x4e\x5a\x50'\ b'\x5b\x52\x5b\x55\x5a\x57\x57\x58\x54\x58\x51\x57\x4f\x53\x4a'\ b'\x52\x48\x52\x46\x53\x45\x55\x45\x57\x46\x59\x48\x20\x52\x52'\ b'\x4d\x50\x4e\x4e\x51\x4d\x54\x4d\x58\x4e\x5a\x20\x52\x52\x5b'\ b'\x54\x5a\x56\x57\x57\x54\x57\x50\x56\x4e\x54\x4b\x53\x49\x53'\ b'\x47\x54\x46\x56\x46\x59\x48\x1f\x49\x5b\x58\x50\x56\x4e\x54'\ b'\x4d\x50\x4d\x4e\x4e\x4e\x50\x50\x52\x53\x53\x20\x52\x50\x4d'\ b'\x4f\x4e\x4f\x50\x51\x52\x53\x53\x20\x52\x53\x53\x4e\x54\x4c'\ b'\x56\x4c\x58\x4d\x5a\x50\x5b\x53\x5b\x55\x5a\x57\x58\x20\x52'\ b'\x53\x53\x4f\x54\x4d\x56\x4d\x58\x4e\x5a\x50\x5b\x24\x47\x5d'\ b'\x4f\x4e\x4d\x4f\x4b\x51\x4a\x54\x4a\x57\x4b\x59\x4c\x5a\x4e'\ b'\x5b\x51\x5b\x54\x5a\x57\x58\x59\x55\x5a\x52\x5a\x4f\x58\x4d'\ b'\x56\x4d\x54\x4f\x52\x53\x50\x58\x4d\x62\x20\x52\x4a\x57\x4c'\ b'\x59\x4e\x5a\x51\x5a\x54\x59\x57\x57\x59\x55\x20\x52\x5a\x4f'\ b'\x58\x4e\x56\x4e\x54\x50\x52\x53\x50\x59\x4e\x62\x1b\x48\x5c'\ b'\x49\x50\x4b\x4e\x4d\x4d\x4f\x4d\x51\x4e\x52\x4f\x53\x52\x53'\ b'\x56\x52\x5a\x4f\x62\x20\x52\x4a\x4f\x4c\x4e\x50\x4e\x52\x4f'\ b'\x20\x52\x5a\x4d\x59\x50\x58\x52\x53\x59\x50\x5e\x4e\x62\x20'\ b'\x52\x59\x4d\x58\x50\x57\x52\x53\x59\x1f\x47\x5d\x48\x51\x49'\ b'\x4f\x4b\x4d\x4e\x4d\x4f\x4e\x4f\x50\x4e\x54\x4c\x5b\x20\x52'\ b'\x4d\x4d\x4e\x4e\x4e\x50\x4d\x54\x4b\x5b\x20\x52\x4e\x54\x50'\ b'\x50\x52\x4e\x54\x4d\x56\x4d\x58\x4e\x59\x4f\x59\x52\x58\x57'\ b'\x55\x62\x20\x52\x56\x4d\x58\x4f\x58\x52\x57\x57\x54\x62\x0e'\ b'\x4c\x58\x52\x4d\x50\x54\x4f\x58\x4f\x5a\x50\x5b\x53\x5b\x55'\ b'\x59\x56\x57\x20\x52\x53\x4d\x51\x54\x50\x58\x50\x5a\x51\x5b'\ b'\x05\x47\x5d\x4b\x4b\x59\x59\x20\x52\x59\x4b\x4b\x59\x1c\x48'\ b'\x5c\x4e\x4d\x4a\x5b\x20\x52\x4f\x4d\x4b\x5b\x20\x52\x58\x4d'\ b'\x59\x4e\x5a\x4e\x59\x4d\x57\x4d\x55\x4e\x51\x52\x4f\x53\x4d'\ b'\x53\x20\x52\x4f\x53\x51\x54\x53\x5a\x54\x5b\x20\x52\x4f\x53'\ b'\x50\x54\x52\x5a\x53\x5b\x55\x5b\x57\x5a\x59\x57\x16\x48\x5c'\ b'\x4b\x46\x4d\x46\x4f\x47\x50\x48\x51\x4a\x57\x58\x58\x5a\x59'\ b'\x5b\x20\x52\x4d\x46\x4f\x48\x50\x4a\x56\x58\x57\x5a\x59\x5b'\ b'\x5a\x5b\x20\x52\x52\x4d\x4a\x5b\x20\x52\x52\x4d\x4b\x5b\x1b'\ b'\x46\x5d\x4d\x4d\x47\x62\x20\x52\x4e\x4d\x48\x62\x20\x52\x4d'\ b'\x50\x4c\x56\x4c\x59\x4e\x5b\x50\x5b\x52\x5a\x54\x58\x56\x55'\ b'\x20\x52\x58\x4d\x55\x58\x55\x5a\x56\x5b\x59\x5b\x5b\x59\x5c'\ b'\x57\x20\x52\x59\x4d\x56\x58\x56\x5a\x57\x5b\x17\x48\x5c\x4e'\ b'\x4d\x4c\x5b\x20\x52\x4f\x4d\x4e\x53\x4d\x58\x4c\x5b\x20\x52'\ b'\x59\x4d\x58\x51\x56\x55\x20\x52\x5a\x4d\x59\x50\x58\x52\x56'\ b'\x55\x54\x57\x51\x59\x4f\x5a\x4c\x5b\x20\x52\x4b\x4d\x4f\x4d'\ b'\x1f\x49\x5b\x52\x4d\x4f\x4e\x4d\x51\x4c\x54\x4c\x57\x4d\x59'\ b'\x4e\x5a\x50\x5b\x52\x5b\x55\x5a\x57\x57\x58\x54\x58\x51\x57'\ b'\x4f\x56\x4e\x54\x4d\x52\x4d\x20\x52\x52\x4d\x50\x4e\x4e\x51'\ b'\x4d\x54\x4d\x58\x4e\x5a\x20\x52\x52\x5b\x54\x5a\x56\x57\x57'\ b'\x54\x57\x50\x56\x4e\x15\x47\x5d\x50\x4e\x4c\x5b\x20\x52\x50'\ b'\x4e\x4d\x5b\x20\x52\x56\x4e\x56\x5b\x20\x52\x56\x4e\x57\x5b'\ b'\x20\x52\x49\x50\x4b\x4e\x4e\x4d\x5b\x4d\x20\x52\x49\x50\x4b'\ b'\x4f\x4e\x4e\x5b\x4e\x2b\x46\x5d\x47\x51\x48\x4f\x4a\x4d\x4d'\ b'\x4d\x4e\x4e\x4e\x50\x4d\x55\x4d\x58\x4e\x5a\x4f\x5b\x20\x52'\ b'\x4c\x4d\x4d\x4e\x4d\x50\x4c\x55\x4c\x58\x4d\x5a\x4f\x5b\x51'\ b'\x5b\x53\x5a\x55\x58\x57\x55\x58\x52\x59\x4d\x59\x49\x58\x47'\ b'\x56\x46\x54\x46\x52\x48\x52\x4a\x53\x4d\x55\x50\x57\x52\x5a'\ b'\x54\x20\x52\x53\x5a\x55\x57\x56\x55\x57\x52\x58\x4d\x58\x49'\ b'\x57\x47\x56\x46\x1e\x48\x5b\x4c\x56\x4d\x59\x4e\x5a\x50\x5b'\ b'\x52\x5b\x55\x5a\x57\x57\x58\x54\x58\x51\x57\x4f\x56\x4e\x54'\ b'\x4d\x52\x4d\x4f\x4e\x4d\x51\x4c\x54\x48\x62\x20\x52\x52\x5b'\ b'\x54\x5a\x56\x57\x57\x54\x57\x50\x56\x4e\x20\x52\x52\x4d\x50'\ b'\x4e\x4e\x51\x4d\x54\x49\x62\x22\x48\x5d\x5b\x4d\x51\x4d\x4e'\ b'\x4e\x4c\x51\x4b\x54\x4b\x57\x4c\x59\x4d\x5a\x4f\x5b\x51\x5b'\ b'\x54\x5a\x56\x57\x57\x54\x57\x51\x56\x4f\x55\x4e\x53\x4d\x20'\ b'\x52\x51\x4d\x4f\x4e\x4d\x51\x4c\x54\x4c\x58\x4d\x5a\x20\x52'\ b'\x51\x5b\x53\x5a\x55\x57\x56\x54\x56\x50\x55\x4e\x20\x52\x55'\ b'\x4e\x5b\x4e\x0f\x48\x5c\x53\x4e\x50\x5b\x20\x52\x53\x4e\x51'\ b'\x5b\x20\x52\x4a\x50\x4c\x4e\x4f\x4d\x5a\x4d\x20\x52\x4a\x50'\ b'\x4c\x4f\x4f\x4e\x5a\x4e\x1e\x48\x5c\x49\x51\x4a\x4f\x4c\x4d'\ b'\x4f\x4d\x50\x4e\x50\x50\x4e\x56\x4e\x59\x50\x5b\x20\x52\x4e'\ b'\x4d\x4f\x4e\x4f\x50\x4d\x56\x4d\x59\x4e\x5a\x50\x5b\x51\x5b'\ b'\x54\x5a\x56\x58\x58\x55\x59\x52\x59\x4f\x58\x4d\x57\x4e\x58'\ b'\x4f\x59\x52\x20\x52\x58\x55\x59\x4f\x0e\x45\x5f\x52\x49\x51'\ b'\x4a\x52\x4b\x53\x4a\x52\x49\x20\x52\x49\x52\x5b\x52\x20\x52'\ b'\x52\x59\x51\x5a\x52\x5b\x53\x5a\x52\x59\x2b\x46\x5d\x4a\x51'\ b'\x4c\x4f\x4f\x4e\x4e\x4d\x4c\x4e\x4a\x51\x49\x54\x49\x57\x4a'\ b'\x5a\x4b\x5b\x4d\x5b\x4f\x5a\x51\x57\x52\x54\x20\x52\x49\x57'\ b'\x4a\x59\x4b\x5a\x4d\x5a\x4f\x59\x51\x57\x20\x52\x51\x54\x51'\ b'\x57\x52\x5a\x53\x5b\x55\x5b\x57\x5a\x59\x57\x5a\x54\x5a\x51'\ b'\x59\x4e\x58\x4d\x57\x4e\x59\x4f\x5a\x51\x20\x52\x51\x57\x52'\ b'\x59\x53\x5a\x55\x5a\x57\x59\x59\x57\x2c\x49\x5a\x54\x46\x52'\ b'\x47\x51\x48\x51\x49\x52\x4a\x55\x4b\x58\x4b\x20\x52\x55\x4b'\ b'\x51\x4c\x4f\x4d\x4e\x4f\x4e\x51\x50\x53\x53\x54\x56\x54\x20'\ b'\x52\x55\x4b\x52\x4c\x50\x4d\x4f\x4f\x4f\x51\x51\x53\x53\x54'\ b'\x20\x52\x53\x54\x4f\x55\x4d\x56\x4c\x58\x4c\x5a\x4e\x5c\x53'\ b'\x5e\x54\x5f\x54\x61\x52\x62\x50\x62\x20\x52\x53\x54\x50\x55'\ b'\x4e\x56\x4d\x58\x4d\x5a\x4f\x5c\x53\x5e\x21\x46\x5d\x55\x46'\ b'\x4f\x62\x20\x52\x56\x46\x4e\x62\x20\x52\x47\x51\x48\x4f\x4a'\ b'\x4d\x4d\x4d\x4e\x4e\x4e\x50\x4d\x55\x4d\x58\x4f\x5a\x52\x5a'\ b'\x54\x59\x57\x56\x59\x53\x20\x52\x4c\x4d\x4d\x4e\x4d\x50\x4c'\ b'\x55\x4c\x58\x4d\x5a\x4f\x5b\x52\x5b\x54\x5a\x56\x58\x58\x55'\ b'\x59\x53\x5b\x4d\x1e\x49\x5b\x54\x46\x52\x47\x51\x48\x51\x49'\ b'\x52\x4a\x55\x4b\x5a\x4b\x5a\x4a\x57\x4b\x53\x4d\x50\x4f\x4d'\ b'\x52\x4c\x55\x4c\x57\x4d\x59\x50\x5b\x53\x5d\x54\x5f\x54\x61'\ b'\x53\x62\x51\x62\x50\x61\x20\x52\x55\x4c\x51\x4f\x4e\x52\x4d'\ b'\x55\x4d\x57\x4e\x59\x50\x5b\x27\x4b\x59\x54\x42\x52\x43\x51'\ b'\x44\x50\x46\x50\x48\x51\x4a\x52\x4b\x53\x4d\x53\x4f\x51\x51'\ b'\x20\x52\x52\x43\x51\x45\x51\x47\x52\x49\x53\x4a\x54\x4c\x54'\ b'\x4e\x53\x50\x4f\x52\x53\x54\x54\x56\x54\x58\x53\x5a\x52\x5b'\ b'\x51\x5d\x51\x5f\x52\x61\x20\x52\x51\x53\x53\x55\x53\x57\x52'\ b'\x59\x51\x5a\x50\x5c\x50\x5e\x51\x60\x52\x61\x54\x62\x02\x4e'\ b'\x56\x52\x42\x52\x62\x27\x4b\x59\x50\x42\x52\x43\x53\x44\x54'\ b'\x46\x54\x48\x53\x4a\x52\x4b\x51\x4d\x51\x4f\x53\x51\x20\x52'\ b'\x52\x43\x53\x45\x53\x47\x52\x49\x51\x4a\x50\x4c\x50\x4e\x51'\ b'\x50\x55\x52\x51\x54\x50\x56\x50\x58\x51\x5a\x52\x5b\x53\x5d'\ b'\x53\x5f\x52\x61\x20\x52\x53\x53\x51\x55\x51\x57\x52\x59\x53'\ b'\x5a\x54\x5c\x54\x5e\x53\x60\x52\x61\x50\x62\x17\x46\x5e\x49'\ b'\x55\x49\x53\x4a\x50\x4c\x4f\x4e\x4f\x50\x50\x54\x53\x56\x54'\ b'\x58\x54\x5a\x53\x5b\x51\x20\x52\x49\x53\x4a\x51\x4c\x50\x4e'\ b'\x50\x50\x51\x54\x54\x56\x55\x58\x55\x5a\x54\x5b\x51\x5b\x4f'\ b'\x22\x4a\x5a\x4a\x46\x4a\x5b\x4b\x5b\x4b\x46\x4c\x46\x4c\x5b'\ b'\x4d\x5b\x4d\x46\x4e\x46\x4e\x5b\x4f\x5b\x4f\x46\x50\x46\x50'\ b'\x5b\x51\x5b\x51\x46\x52\x46\x52\x5b\x53\x5b\x53\x46\x54\x46'\ b'\x54\x5b\x55\x5b\x55\x46\x56\x46\x56\x5b\x57\x5b\x57\x46\x58'\ b'\x46\x58\x5b\x59\x5b\x59\x46\x5a\x46\x5a\x5b' _index =\ b'\x00\x00\x03\x00\x22\x00\x3b\x00\x54\x00\xa9\x00\xea\x00\x4d'\ b'\x01\x5a\x01\x8b\x01\xbc\x01\xcf\x01\xdc\x01\xed\x01\xf4\x01'\ b'\x01\x02\x08\x02\x59\x02\x70\x02\xcb\x02\x2a\x03\x45\x03\x94'\ b'\x03\xf5\x03\x34\x04\xb3\x04\x14\x05\x2d\x05\x4a\x05\x53\x05'\ b'\x60\x05\x69\x05\xaa\x05\x1b\x06\x40\x06\x9b\x06\xc6\x06\xe5'\ b'\x06\x12\x07\x73\x07\x90\x07\xc7\x07\xe0\x07\xed\x07\x24\x08'\ b'\x43\x08\x80\x08\xab\x08\x04\x09\x2f\x09\xa0\x09\xdb\x09\x04'\ b'\x0a\x25\x0a\x68\x0a\x85\x0a\xdc\x0a\x25\x0b\x78\x0b\x99\x0b'\ b'\xb2\x0b\xb9\x0b\xd2\x0b\xe3\x0b\xea\x0b\xf9\x0b\x4a\x0c\xbd'\ b'\x0c\xec\x0c\x45\x0d\x86\x0d\xd1\x0d\x0a\x0e\x4b\x0e\x6a\x0e'\ b'\x77\x0e\xb2\x0e\xe1\x0e\x1a\x0f\x4b\x0f\x8c\x0f\xb9\x0f\x12'\ b'\x10\x51\x10\x98\x10\xb9\x10\xf8\x10\x17\x11\x70\x11\xcb\x11'\ b'\x10\x12\x4f\x12\xa0\x12\xa7\x12\xf8\x12\x29\x13' _mvfont = memoryview(_font) def _chr_addr(ordch): offset = 2 * (ordch - 32) return int.from_bytes(_index[offset:offset + 2], 'little') def get_ch(ordch): offset = _chr_addr(ordch if 32 <= ordch <= 127 else ord('?')) count = _font[offset] return _mvfont[offset:offset+(count+2)*2-1]

62.323288

65

0.706699

5,564

22,748

2.886952

0.028577

0.094503

0.049866

0.008965

0.31943

0.221565

0.18222

0.156197

0.142999

0.121459

0

0.377127

0.018287

22,748

364

66

62.494505

0.342155

0

0.966387

0.909127

0.908819

0

1

0

1

0.008403

false

0

0.002801

0.016807

0

null

0

1

0

1

0

1

null

1

0

6

46b111fa8d9d3972fe415e19dd61b92183f76201

126

py

Python

config/__init__.py

koravel/friends_displayer

d2505687171b142efff622e31fd3729376a2e86b

[ "Apache-2.0" ]

null

config/__init__.py

koravel/friends_displayer

d2505687171b142efff622e31fd3729376a2e86b

[ "Apache-2.0" ]

null

config/__init__.py

koravel/friends_displayer

d2505687171b142efff622e31fd3729376a2e86b

[ "Apache-2.0" ]

null

import os __root_location = os.path.dirname(os.path.abspath(__file__)) def get_root_location(): return __root_location

15.75

60

0.777778

18

126

4.777778

0.611111

0.418605

0

0.126984

126

7

61

18

0.781818

0

1

0.25

false

0

0.25

0.75

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

d3c11e54e6f7b4fac713a4ac4663afb48915152f

163

py

Python

tasks/loader/types/automated/unused_actions.py

WaffleHacks/application-portal

53d4d47ddb4e9cc38671c1a2859153d1143d526f

[ "MIT" ]

null

tasks/loader/types/automated/unused_actions.py

WaffleHacks/application-portal

53d4d47ddb4e9cc38671c1a2859153d1143d526f

[ "MIT" ]

2

2022-02-15T23:52:50.000Z

2022-03-23T01:05:22.000Z

tasks/loader/types/automated/unused_actions.py

WaffleHacks/application-portal

53d4d47ddb4e9cc38671c1a2859153d1143d526f

[ "MIT" ]

null

from .base_action import BaseAction class Communication(BaseAction): pass class Integrations(BaseAction): pass class Workshops(BaseAction): pass

11.642857

35

0.748466

17

163

7.117647

0.588235

0.347107

0.31405

0

0.190184

163

13

36

12.538462

0.916667

0

0.428571

0

1

0

true

0.428571

0.142857

0

0.571429

0

1

0

null

1

0

null

0

1

0

1

0

6

d3cdc9617af3b5bc7ea44cd5549f9fcfb7b14988

311

py

Python

helloworld/config.py

stuhood/example-python

684d77ead29c39649ec9140514ca160b61dac621

[ "Apache-2.0" ]

null

helloworld/config.py

stuhood/example-python

684d77ead29c39649ec9140514ca160b61dac621

[ "Apache-2.0" ]

null

helloworld/config.py

stuhood/example-python

684d77ead29c39649ec9140514ca160b61dac621

[ "Apache-2.0" ]

null

# Copyright 2020 Pants project contributors. # Licensed under the Apache License, Version 2.0 (see LICENSE). from helloworld.protos.config_pb2 import Config from helloworld.util.config_loader import load_config_from_json def load_config() -> Config: return load_config_from_json(__name__, "config.json")

31.1

63

0.803859

44

311

5.386364

0.613636

0.126582

0.118143

0.151899

0

0.025641

0.122187

311

9

64

34.555556

0.842491

0.334405

0

0.053922

0

1

0.25

true

0

0.5

0.25

1

0

null

0

1

0

null

0

1

0

1

0

6

d3d36a76b47424d9996e5e3f6a86d83c59b8f86e

42

py

Python

CangJie/CTC/__init__.py

bigdata-ustc/CangJie

a3264082fa0432d257b5c4722b14c55f9092a411

[ "MIT" ]

2

2020-03-04T02:27:29.000Z

2020-05-22T04:07:24.000Z

CangJie/CTC/__init__.py

bigdata-ustc/CangJie

a3264082fa0432d257b5c4722b14c55f9092a411

[ "MIT" ]

null

CangJie/CTC/__init__.py

bigdata-ustc/CangJie

a3264082fa0432d257b5c4722b14c55f9092a411

[ "MIT" ]

1

2022-03-12T00:31:59.000Z

# coding: utf-8 # 2019/12/28 @ tongshiwei

14

25

0.666667

7

42

4

1

0

0.257143

0.166667

42

2

26

21

0.542857

0.880952

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

1

0

null

0

1

0

6

315b73084d01749a2c7c9e39660951d41ee0a495

28

py

Python

keras2caffe/__init__.py

jelambrar96/keras2caffe-1

58fa1923191019b4f5fdf5b8081441d27a53f499

[ "MIT" ]

74

2017-09-21T09:11:35.000Z

2022-01-24T05:59:55.000Z

keras2caffe/__init__.py

jelambrar96/keras2caffe-1

58fa1923191019b4f5fdf5b8081441d27a53f499

[ "MIT" ]

24

2018-05-13T04:35:59.000Z

2020-10-22T07:55:27.000Z

keras2caffe/__init__.py

jelambrar96/keras2caffe-1

58fa1923191019b4f5fdf5b8081441d27a53f499

[ "MIT" ]

25

2017-09-21T09:11:41.000Z

2022-02-08T14:34:52.000Z

from .convert import convert

28

0.857143

4

28

6

0.75

0

0.107143

28

1

28

0.96

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

31b2e0a43206897c8bcc5f8a2181c3ad687b1461

13,833

py

Python

test/test_ucx.py

robertmaynard/hpc-container-maker

fdf20b9881eb41f92b7d73c85b20f5f75ddfe262

[ "Apache-2.0" ]

340

2018-03-26T00:11:21.000Z

2022-03-21T03:04:27.000Z

test/test_ucx.py

robertmaynard/hpc-container-maker

fdf20b9881eb41f92b7d73c85b20f5f75ddfe262

[ "Apache-2.0" ]

103

2018-03-24T04:34:24.000Z

2022-03-31T18:49:57.000Z

test/test_ucx.py

robertmaynard/hpc-container-maker

fdf20b9881eb41f92b7d73c85b20f5f75ddfe262

[ "Apache-2.0" ]

75

2018-05-10T15:42:11.000Z

2022-03-28T16:51:14.000Z

# Copyright (c) 2018, NVIDIA CORPORATION. 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. # pylint: disable=invalid-name, too-few-public-methods, bad-continuation """Test cases for the ucx module""" from __future__ import unicode_literals from __future__ import print_function import logging # pylint: disable=unused-import import unittest from helpers import centos, docker, ppc64le, ubuntu, x86_64 from hpccm.building_blocks.ucx import ucx class Test_ucx(unittest.TestCase): def setUp(self): """Disable logging output messages""" logging.disable(logging.ERROR) @x86_64 @ubuntu @docker def test_defaults_ubuntu(self): """Default ucx building block""" u = ucx() self.assertEqual(str(u), r'''# UCX version 1.9.0 RUN apt-get update -y && \ DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ binutils-dev \ file \ libnuma-dev \ make \ wget && \ rm -rf /var/lib/apt/lists/* RUN mkdir -p /var/tmp && wget -q -nc --no-check-certificate -P /var/tmp https://github.com/openucx/ucx/releases/download/v1.9.0/ucx-1.9.0.tar.gz && \ mkdir -p /var/tmp && tar -x -f /var/tmp/ucx-1.9.0.tar.gz -C /var/tmp -z && \ cd /var/tmp/ucx-1.9.0 && ./configure --prefix=/usr/local/ucx --disable-assertions --disable-debug --disable-doxygen-doc --disable-logging --disable-params-check --enable-optimizations --with-cuda=/usr/local/cuda && \ make -j$(nproc) && \ make -j$(nproc) install && \ rm -rf /var/tmp/ucx-1.9.0 /var/tmp/ucx-1.9.0.tar.gz ENV CPATH=/usr/local/ucx/include:$CPATH \ LD_LIBRARY_PATH=/usr/local/ucx/lib:$LD_LIBRARY_PATH \ LIBRARY_PATH=/usr/local/ucx/lib:$LIBRARY_PATH \ PATH=/usr/local/ucx/bin:$PATH''') @x86_64 @centos @docker def test_defaults_centos(self): """Default ucx building block""" u = ucx() self.assertEqual(str(u), r'''# UCX version 1.9.0 RUN yum install -y \ binutils-devel \ file \ make \ numactl-devel \ wget && \ rm -rf /var/cache/yum/* RUN mkdir -p /var/tmp && wget -q -nc --no-check-certificate -P /var/tmp https://github.com/openucx/ucx/releases/download/v1.9.0/ucx-1.9.0.tar.gz && \ mkdir -p /var/tmp && tar -x -f /var/tmp/ucx-1.9.0.tar.gz -C /var/tmp -z && \ cd /var/tmp/ucx-1.9.0 && ./configure --prefix=/usr/local/ucx --disable-assertions --disable-debug --disable-doxygen-doc --disable-logging --disable-params-check --enable-optimizations --with-cuda=/usr/local/cuda && \ make -j$(nproc) && \ make -j$(nproc) install && \ rm -rf /var/tmp/ucx-1.9.0 /var/tmp/ucx-1.9.0.tar.gz ENV CPATH=/usr/local/ucx/include:$CPATH \ LD_LIBRARY_PATH=/usr/local/ucx/lib:$LD_LIBRARY_PATH \ LIBRARY_PATH=/usr/local/ucx/lib:$LIBRARY_PATH \ PATH=/usr/local/ucx/bin:$PATH''') @x86_64 @ubuntu @docker def test_with_paths_ubuntu(self): """ucx building block with paths""" u = ucx(cuda='/cuda', gdrcopy='/gdrcopy', knem='/knem', ofed='/ofed', xpmem='/xpmem', version='1.8.0') self.assertEqual(str(u), r'''# UCX version 1.8.0 RUN apt-get update -y && \ DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ binutils-dev \ file \ libnuma-dev \ make \ wget && \ rm -rf /var/lib/apt/lists/* RUN mkdir -p /var/tmp && wget -q -nc --no-check-certificate -P /var/tmp https://github.com/openucx/ucx/releases/download/v1.8.0/ucx-1.8.0.tar.gz && \ mkdir -p /var/tmp && tar -x -f /var/tmp/ucx-1.8.0.tar.gz -C /var/tmp -z && \ cd /var/tmp/ucx-1.8.0 && ./configure --prefix=/usr/local/ucx --disable-assertions --disable-debug --disable-doxygen-doc --disable-logging --disable-params-check --enable-optimizations --with-cuda=/cuda --with-gdrcopy=/gdrcopy --with-knem=/knem --with-rdmacm=/ofed --with-verbs=/ofed --with-xpmem=/xpmem && \ make -j$(nproc) && \ make -j$(nproc) install && \ rm -rf /var/tmp/ucx-1.8.0 /var/tmp/ucx-1.8.0.tar.gz ENV CPATH=/usr/local/ucx/include:$CPATH \ LD_LIBRARY_PATH=/usr/local/ucx/lib:$LD_LIBRARY_PATH \ LIBRARY_PATH=/usr/local/ucx/lib:$LIBRARY_PATH \ PATH=/usr/local/ucx/bin:$PATH''') @x86_64 @ubuntu @docker def test_with_true_ubuntu(self): """ucx building block with True values""" u = ucx(cuda=True, gdrcopy=True, knem=True, ofed=True, xpmem=True, version='1.8.0') self.assertEqual(str(u), r'''# UCX version 1.8.0 RUN apt-get update -y && \ DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ binutils-dev \ file \ libnuma-dev \ make \ wget && \ rm -rf /var/lib/apt/lists/* RUN mkdir -p /var/tmp && wget -q -nc --no-check-certificate -P /var/tmp https://github.com/openucx/ucx/releases/download/v1.8.0/ucx-1.8.0.tar.gz && \ mkdir -p /var/tmp && tar -x -f /var/tmp/ucx-1.8.0.tar.gz -C /var/tmp -z && \ cd /var/tmp/ucx-1.8.0 && ./configure --prefix=/usr/local/ucx --disable-assertions --disable-debug --disable-doxygen-doc --disable-logging --disable-params-check --enable-optimizations --with-cuda=/usr/local/cuda --with-gdrcopy --with-knem --with-rdmacm --with-verbs --with-xpmem && \ make -j$(nproc) && \ make -j$(nproc) install && \ rm -rf /var/tmp/ucx-1.8.0 /var/tmp/ucx-1.8.0.tar.gz ENV CPATH=/usr/local/ucx/include:$CPATH \ LD_LIBRARY_PATH=/usr/local/ucx/lib:$LD_LIBRARY_PATH \ LIBRARY_PATH=/usr/local/ucx/lib:$LIBRARY_PATH \ PATH=/usr/local/ucx/bin:$PATH''') @x86_64 @ubuntu @docker def test_with_false_ubuntu(self): """ucx building block with False values""" u = ucx(cuda=False, gdrcopy=False, knem=False, ofed=False, xpmem=False, version='1.8.0') self.assertEqual(str(u), r'''# UCX version 1.8.0 RUN apt-get update -y && \ DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ binutils-dev \ file \ libnuma-dev \ make \ wget && \ rm -rf /var/lib/apt/lists/* RUN mkdir -p /var/tmp && wget -q -nc --no-check-certificate -P /var/tmp https://github.com/openucx/ucx/releases/download/v1.8.0/ucx-1.8.0.tar.gz && \ mkdir -p /var/tmp && tar -x -f /var/tmp/ucx-1.8.0.tar.gz -C /var/tmp -z && \ cd /var/tmp/ucx-1.8.0 && ./configure --prefix=/usr/local/ucx --disable-assertions --disable-debug --disable-doxygen-doc --disable-logging --disable-params-check --enable-optimizations --without-cuda --without-gdrcopy --without-knem --without-rdmacm --without-verbs --without-xpmem && \ make -j$(nproc) && \ make -j$(nproc) install && \ rm -rf /var/tmp/ucx-1.8.0 /var/tmp/ucx-1.8.0.tar.gz ENV CPATH=/usr/local/ucx/include:$CPATH \ LD_LIBRARY_PATH=/usr/local/ucx/lib:$LD_LIBRARY_PATH \ LIBRARY_PATH=/usr/local/ucx/lib:$LIBRARY_PATH \ PATH=/usr/local/ucx/bin:$PATH''') @x86_64 @ubuntu @docker def test_ldconfig(self): """ldconfig option""" u = ucx(ldconfig=True, version='1.4.0') self.assertEqual(str(u), r'''# UCX version 1.4.0 RUN apt-get update -y && \ DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ binutils-dev \ file \ libnuma-dev \ make \ wget && \ rm -rf /var/lib/apt/lists/* RUN mkdir -p /var/tmp && wget -q -nc --no-check-certificate -P /var/tmp https://github.com/openucx/ucx/releases/download/v1.4.0/ucx-1.4.0.tar.gz && \ mkdir -p /var/tmp && tar -x -f /var/tmp/ucx-1.4.0.tar.gz -C /var/tmp -z && \ cd /var/tmp/ucx-1.4.0 && ./configure --prefix=/usr/local/ucx --disable-assertions --disable-debug --disable-doxygen-doc --disable-logging --disable-params-check --enable-optimizations --with-cuda=/usr/local/cuda && \ make -j$(nproc) && \ make -j$(nproc) install && \ echo "/usr/local/ucx/lib" >> /etc/ld.so.conf.d/hpccm.conf && ldconfig && \ rm -rf /var/tmp/ucx-1.4.0 /var/tmp/ucx-1.4.0.tar.gz ENV CPATH=/usr/local/ucx/include:$CPATH \ LIBRARY_PATH=/usr/local/ucx/lib:$LIBRARY_PATH \ PATH=/usr/local/ucx/bin:$PATH''') @x86_64 @ubuntu @docker def test_environment(self): """environment option""" u = ucx(environment=False, version='1.4.0') self.assertEqual(str(u), r'''# UCX version 1.4.0 RUN apt-get update -y && \ DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ binutils-dev \ file \ libnuma-dev \ make \ wget && \ rm -rf /var/lib/apt/lists/* RUN mkdir -p /var/tmp && wget -q -nc --no-check-certificate -P /var/tmp https://github.com/openucx/ucx/releases/download/v1.4.0/ucx-1.4.0.tar.gz && \ mkdir -p /var/tmp && tar -x -f /var/tmp/ucx-1.4.0.tar.gz -C /var/tmp -z && \ cd /var/tmp/ucx-1.4.0 && ./configure --prefix=/usr/local/ucx --disable-assertions --disable-debug --disable-doxygen-doc --disable-logging --disable-params-check --enable-optimizations --with-cuda=/usr/local/cuda && \ make -j$(nproc) && \ make -j$(nproc) install && \ rm -rf /var/tmp/ucx-1.4.0 /var/tmp/ucx-1.4.0.tar.gz''') @ppc64le @centos @docker def test_ppc64le(self): """ppc64le""" u = ucx(cuda=False, knem='/usr/local/knem', version='1.5.2') self.assertEqual(str(u), r'''# UCX version 1.5.2 RUN yum install -y \ binutils-devel \ file \ make \ numactl-devel \ wget && \ rm -rf /var/cache/yum/* RUN mkdir -p /var/tmp && wget -q -nc --no-check-certificate -P /var/tmp https://github.com/openucx/ucx/releases/download/v1.5.2/ucx-1.5.2.tar.gz && \ mkdir -p /var/tmp && tar -x -f /var/tmp/ucx-1.5.2.tar.gz -C /var/tmp -z && \ cd /var/tmp/ucx-1.5.2 && CFLAGS=-Wno-error=format ./configure --prefix=/usr/local/ucx --disable-assertions --disable-debug --disable-doxygen-doc --disable-logging --disable-params-check --enable-optimizations --with-knem=/usr/local/knem --without-cuda && \ make -j$(nproc) && \ make -j$(nproc) install && \ rm -rf /var/tmp/ucx-1.5.2 /var/tmp/ucx-1.5.2.tar.gz ENV CPATH=/usr/local/ucx/include:$CPATH \ LD_LIBRARY_PATH=/usr/local/ucx/lib:$LD_LIBRARY_PATH \ LIBRARY_PATH=/usr/local/ucx/lib:$LIBRARY_PATH \ PATH=/usr/local/ucx/bin:$PATH''') @x86_64 @ubuntu @docker def test_git_repository_true(self): u = ucx(repository=True) self.assertEqual(str(u), r'''# UCX https://github.com/openucx/ucx.git RUN apt-get update -y && \ DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ autoconf \ automake \ binutils-dev \ ca-certificates \ file \ git \ libnuma-dev \ libtool \ make \ wget && \ rm -rf /var/lib/apt/lists/* RUN mkdir -p /var/tmp && cd /var/tmp && git clone --depth=1 https://github.com/openucx/ucx.git ucx && cd - && \ cd /var/tmp/ucx && \ ./autogen.sh && \ cd /var/tmp/ucx && ./configure --prefix=/usr/local/ucx --disable-assertions --disable-debug --disable-doxygen-doc --disable-logging --disable-params-check --enable-optimizations --with-cuda=/usr/local/cuda && \ make -j$(nproc) && \ make -j$(nproc) install && \ rm -rf /var/tmp/ucx ENV CPATH=/usr/local/ucx/include:$CPATH \ LD_LIBRARY_PATH=/usr/local/ucx/lib:$LD_LIBRARY_PATH \ LIBRARY_PATH=/usr/local/ucx/lib:$LIBRARY_PATH \ PATH=/usr/local/ucx/bin:$PATH''') @x86_64 @ubuntu @docker def test_git_repository_value(self): u = ucx(branch='v1.8.x', repository='https://github.com/openucx-fork/ucx.git') self.assertEqual(str(u), r'''# UCX https://github.com/openucx-fork/ucx.git v1.8.x RUN apt-get update -y && \ DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ autoconf \ automake \ binutils-dev \ ca-certificates \ file \ git \ libnuma-dev \ libtool \ make \ wget && \ rm -rf /var/lib/apt/lists/* RUN mkdir -p /var/tmp && cd /var/tmp && git clone --depth=1 --branch v1.8.x https://github.com/openucx-fork/ucx.git ucx && cd - && \ cd /var/tmp/ucx && \ ./autogen.sh && \ cd /var/tmp/ucx && ./configure --prefix=/usr/local/ucx --disable-assertions --disable-debug --disable-doxygen-doc --disable-logging --disable-params-check --enable-optimizations --with-cuda=/usr/local/cuda && \ make -j$(nproc) && \ make -j$(nproc) install && \ rm -rf /var/tmp/ucx ENV CPATH=/usr/local/ucx/include:$CPATH \ LD_LIBRARY_PATH=/usr/local/ucx/lib:$LD_LIBRARY_PATH \ LIBRARY_PATH=/usr/local/ucx/lib:$LIBRARY_PATH \ PATH=/usr/local/ucx/bin:$PATH''') @ubuntu @docker def test_runtime(self): """Runtime""" u = ucx() r = u.runtime() self.assertEqual(r, r'''# UCX RUN apt-get update -y && \ DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \ binutils && \ rm -rf /var/lib/apt/lists/* COPY --from=0 /usr/local/ucx /usr/local/ucx ENV CPATH=/usr/local/ucx/include:$CPATH \ LD_LIBRARY_PATH=/usr/local/ucx/lib:$LD_LIBRARY_PATH \ LIBRARY_PATH=/usr/local/ucx/lib:$LIBRARY_PATH \ PATH=/usr/local/ucx/bin:$PATH''')

42.045593

313

0.625967

2,113

13,833

4.045906

0.105537

0.051936

0.066908

0.037431

0.801614

0.781846

0.774126

0.768862

0

0.022578

0.196342

13,833

328

314

42.17378

0.746424

0.069038

0

0.633333

0

0.051293

0

0.122222

1

0.133333

false

0

0.066667

0

0.211111

0.011111

0

null

0

1

0

null

0

6

73128bf2b37664ebb55abe68df45ad038a3bba3a

44

py

Python

mct_camera_trigger/src/mct_camera_trigger/__init__.py

iorodeo/mct

fa8b85f36533c9b1486ca4f6b0c40c3daa6f4e11

[ "Apache-2.0" ]

null

mct_camera_trigger/src/mct_camera_trigger/__init__.py

iorodeo/mct

fa8b85f36533c9b1486ca4f6b0c40c3daa6f4e11

[ "Apache-2.0" ]

null

mct_camera_trigger/src/mct_camera_trigger/__init__.py

iorodeo/mct

fa8b85f36533c9b1486ca4f6b0c40c3daa6f4e11

[ "Apache-2.0" ]

null

import trigger_device import camera_trigger

14.666667

21

0.909091

6

44

6.333333

0.666667

0

0.090909

44

2

22

0.95

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

b4390c5235cea8c58add6cda45c22d5dff35cc08

31,915

py

Python

unrolled-lutnet/training-software/MNIST-CIFAR-SVHN/models/SVHN/scripts/lutnet_init.py

awai54st/LUTNet

81b044f31d1131bee1a7fae41fc4d2fb102ea73a

[ "BSD-2-Clause" ]

38

2019-10-28T10:06:33.000Z

2022-02-21T21:38:39.000Z

unrolled-lutnet/training-software/MNIST-CIFAR-SVHN/models/CIFAR-10/scripts/lutnet_init.py

awai54st/LUTNet

81b044f31d1131bee1a7fae41fc4d2fb102ea73a

[ "BSD-2-Clause" ]

null

unrolled-lutnet/training-software/MNIST-CIFAR-SVHN/models/CIFAR-10/scripts/lutnet_init.py

awai54st/LUTNet

81b044f31d1131bee1a7fae41fc4d2fb102ea73a

[ "BSD-2-Clause" ]

13

2019-10-28T10:17:48.000Z

2021-08-10T21:37:11.000Z

import h5py import numpy as np from shutil import copyfile copyfile("dummy_lutnet.h5", "pretrained_bin.h5") # create pretrained.h5 using datastructure from dummy.h5 bl = h5py.File("baseline_pruned.h5", 'r') #dummy = h5py.File("dummy.h5", 'r') pretrained = h5py.File("pretrained_bin.h5", 'r+') # conv layer 1 bl_w1 = bl["model_weights"]["binary_conv_1"]["binary_conv_1"]["Variable_1:0"] #bl_rand_map = bl["model_weights"]["binary_conv_1"]["binary_conv_1"]["rand_map:0"] bl_pruning_mask = bl["model_weights"]["binary_conv_1"]["binary_conv_1"]["pruning_mask:0"] bl_gamma = bl["model_weights"]["binary_conv_1"]["binary_conv_1"]["Variable:0"] zero_fill = np.zeros(np.shape(np.array(bl_w1))) pret_w1 = pretrained["model_weights"]["binary_conv_1"]["binary_conv_1"]["Variable_1:0"] #pret_rand_map = pretrained["model_weights"]["binary_conv_1"]["binary_conv_1"]["rand_map:0"] pret_pruning_mask = pretrained["model_weights"]["binary_conv_1"]["binary_conv_1"]["pruning_mask:0"] p_gamma = pretrained["model_weights"]["binary_conv_1"]["binary_conv_1"]["Variable:0"] pret_w1[...] = np.array(bl_w1) #pret_rand_map[...] = np.array(bl_rand_map) p_gamma[...] = np.array(bl_gamma) pret_pruning_mask[...] = np.array(bl_pruning_mask) print(np.sum(np.array(bl_pruning_mask)), np.prod(np.shape(np.array(bl_pruning_mask)))) # conv layer 2 bl_w1 = bl["model_weights"]["binary_conv_2"]["binary_conv_2"]["Variable_1:0"] #bl_w2 = bl["model_weights"]["binary_conv_2"]["binary_conv_2"]["Variable_2:0"] #bl_w3 = bl["model_weights"]["binary_conv_2"]["binary_conv_2"]["Variable_3:0"] #bl_w4 = bl["model_weights"]["binary_conv_2"]["binary_conv_2"]["Variable_4:0"] #bl_rand_map = bl["model_weights"]["binary_conv_2"]["binary_conv_2"]["rand_map:0"] bl_pruning_mask = bl["model_weights"]["binary_conv_2"]["binary_conv_2"]["pruning_mask:0"] bl_gamma = bl["model_weights"]["binary_conv_2"]["binary_conv_2"]["Variable:0"] bl_means = bl["model_weights"]["residual_sign_1"]["residual_sign_1"]["means:0"] zero_fill = np.zeros(np.shape(np.array(bl_w1))) pret_w1 = pretrained["model_weights"]["binary_conv_2"]["binary_conv_2"]["Variable_1:0"] #pret_rand_map = pretrained["model_weights"]["binary_conv_2"]["binary_conv_2"]["rand_map:0"] pret_pruning_mask = pretrained["model_weights"]["binary_conv_2"]["binary_conv_2"]["pruning_mask:0"] p_gamma = pretrained["model_weights"]["binary_conv_2"]["binary_conv_2"]["Variable:0"] pret_means = pretrained["model_weights"]["residual_sign_1"]["residual_sign_1"]["means:0"] #weight_shape = np.shape(bl_w1) # pret_w1[...] = np.array(bl_w1) #pret_rand_map[...] = np.array(bl_rand_map) p_gamma[...] = np.array(bl_gamma) pret_means[...] = np.array(bl_means) pret_pruning_mask[...] = np.array(bl_pruning_mask) print(np.sum(np.array(bl_pruning_mask)), np.prod(np.shape(np.array(bl_pruning_mask)))) # conv layer 3 bl_w1 = bl["model_weights"]["binary_conv_3"]["binary_conv_3"]["Variable_1:0"] #bl_rand_map = bl["model_weights"]["binary_conv_3"]["binary_conv_3"]["rand_map:0"] bl_pruning_mask = bl["model_weights"]["binary_conv_3"]["binary_conv_3"]["pruning_mask:0"] bl_gamma = bl["model_weights"]["binary_conv_3"]["binary_conv_3"]["Variable:0"] bl_means = bl["model_weights"]["residual_sign_2"]["residual_sign_2"]["means:0"] zero_fill = np.zeros(np.shape(np.array(bl_w1))) pret_w1 = pretrained["model_weights"]["binary_conv_3"]["binary_conv_3"]["Variable_1:0"] #pret_rand_map = pretrained["model_weights"]["binary_conv_3"]["binary_conv_3"]["rand_map:0"] pret_pruning_mask = pretrained["model_weights"]["binary_conv_3"]["binary_conv_3"]["pruning_mask:0"] p_gamma = pretrained["model_weights"]["binary_conv_3"]["binary_conv_3"]["Variable:0"] pret_means = pretrained["model_weights"]["residual_sign_2"]["residual_sign_2"]["means:0"] pret_w1[...] = np.array(bl_w1) #pret_rand_map[...] = np.array(bl_rand_map) p_gamma[...] = np.array(bl_gamma) pret_means[...] = np.array(bl_means) pret_pruning_mask[...] = np.array(bl_pruning_mask) print(np.sum(np.array(bl_pruning_mask)), np.prod(np.shape(np.array(bl_pruning_mask)))) # conv layer 4 bl_w1 = bl["model_weights"]["binary_conv_4"]["binary_conv_4"]["Variable_1:0"] #bl_rand_map = bl["model_weights"]["binary_conv_4"]["binary_conv_4"]["rand_map:0"] bl_pruning_mask = bl["model_weights"]["binary_conv_4"]["binary_conv_4"]["pruning_mask:0"] bl_gamma = bl["model_weights"]["binary_conv_4"]["binary_conv_4"]["Variable:0"] bl_means = bl["model_weights"]["residual_sign_3"]["residual_sign_3"]["means:0"] zero_fill = np.zeros(np.shape(np.array(bl_w1))) pret_w1 = pretrained["model_weights"]["binary_conv_4"]["binary_conv_4"]["Variable_1:0"] #pret_rand_map = pretrained["model_weights"]["binary_conv_4"]["binary_conv_4"]["rand_map:0"] pret_pruning_mask = pretrained["model_weights"]["binary_conv_4"]["binary_conv_4"]["pruning_mask:0"] p_gamma = pretrained["model_weights"]["binary_conv_4"]["binary_conv_4"]["Variable:0"] pret_means = pretrained["model_weights"]["residual_sign_3"]["residual_sign_3"]["means:0"] pret_w1[...] = np.array(bl_w1) #pret_rand_map[...] = np.array(bl_rand_map) p_gamma[...] = np.array(bl_gamma) pret_means[...] = np.array(bl_means) pret_pruning_mask[...] = np.array(bl_pruning_mask) print(np.sum(np.array(bl_pruning_mask)), np.prod(np.shape(np.array(bl_pruning_mask)))) # conv layer 5 bl_w1 = bl["model_weights"]["binary_conv_5"]["binary_conv_5"]["Variable_1:0"] #bl_rand_map = bl["model_weights"]["binary_conv_5"]["binary_conv_5"]["rand_map:0"] bl_pruning_mask = bl["model_weights"]["binary_conv_5"]["binary_conv_5"]["pruning_mask:0"] bl_gamma = bl["model_weights"]["binary_conv_5"]["binary_conv_5"]["Variable:0"] bl_means = bl["model_weights"]["residual_sign_4"]["residual_sign_4"]["means:0"] zero_fill = np.zeros(np.shape(np.array(bl_w1))) pret_w1 = pretrained["model_weights"]["binary_conv_5"]["binary_conv_5"]["Variable_1:0"] #pret_rand_map = pretrained["model_weights"]["binary_conv_5"]["binary_conv_5"]["rand_map:0"] pret_pruning_mask = pretrained["model_weights"]["binary_conv_5"]["binary_conv_5"]["pruning_mask:0"] p_gamma = pretrained["model_weights"]["binary_conv_5"]["binary_conv_5"]["Variable:0"] pret_means = pretrained["model_weights"]["residual_sign_4"]["residual_sign_4"]["means:0"] pret_w1[...] = np.array(bl_w1) #pret_rand_map[...] = np.array(bl_rand_map) p_gamma[...] = np.array(bl_gamma) pret_means[...] = np.array(bl_means) pret_pruning_mask[...] = np.array(bl_pruning_mask) print(np.sum(np.array(bl_pruning_mask)), np.prod(np.shape(np.array(bl_pruning_mask)))) # conv layer 6 bl_w1 = bl["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_1:0"] #bl_w2 = bl["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_2:0"] #bl_w3 = bl["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_3:0"] #bl_w4 = bl["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_4:0"] bl_rand_map_0 = bl["model_weights"]["binary_conv_6"]["binary_conv_6"]["rand_map_0:0"] bl_rand_map_1 = bl["model_weights"]["binary_conv_6"]["binary_conv_6"]["rand_map_1:0"] bl_rand_map_2 = bl["model_weights"]["binary_conv_6"]["binary_conv_6"]["rand_map_2:0"] bl_pruning_mask = bl["model_weights"]["binary_conv_6"]["binary_conv_6"]["pruning_mask:0"] bl_gamma = bl["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable:0"] bl_means = bl["model_weights"]["residual_sign_5"]["residual_sign_5"]["means:0"] zero_fill = np.zeros(np.shape(np.array(bl_w1))) pret_w1 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_1:0"] pret_w2 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_2:0"] pret_w3 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_3:0"] pret_w4 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_4:0"] pret_w5 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_5:0"] pret_w6 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_6:0"] pret_w7 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_7:0"] pret_w8 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_8:0"] pret_w9 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_9:0"] pret_w10 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_10:0"] pret_w11 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_11:0"] pret_w12 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_12:0"] pret_w13 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_13:0"] pret_w14 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_14:0"] pret_w15 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_15:0"] pret_w16 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_16:0"] pret_w17 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_17:0"] pret_w18 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_18:0"] pret_w19 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_19:0"] pret_w20 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_20:0"] pret_w21 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_21:0"] pret_w22 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_22:0"] pret_w23 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_23:0"] pret_w24 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_24:0"] pret_w25 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_25:0"] pret_w26 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_26:0"] pret_w27 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_27:0"] pret_w28 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_28:0"] pret_w29 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_29:0"] pret_w30 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_30:0"] pret_w31 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_31:0"] pret_w32 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable_32:0"] pret_rand_map_0 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["rand_map_0:0"] pret_rand_map_1 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["rand_map_1:0"] pret_rand_map_2 = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["rand_map_2:0"] pret_pruning_mask = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["pruning_mask:0"] p_gamma = pretrained["model_weights"]["binary_conv_6"]["binary_conv_6"]["Variable:0"] pret_means = pretrained["model_weights"]["residual_sign_5"]["residual_sign_5"]["means:0"] weight_shape = np.shape(bl_w1) # randomisation and pruning recovery bl_w1_unroll = np.reshape(np.array(bl_w1), (-1,weight_shape[3])) bl_w1 = np.array(bl_w1) rand_map_0 = np.arange(weight_shape[0]*weight_shape[1]*weight_shape[2]) np.random.shuffle(rand_map_0) rand_map_1 = np.arange(weight_shape[0]*weight_shape[1]*weight_shape[2]) np.random.shuffle(rand_map_1) rand_map_2 = np.arange(weight_shape[0]*weight_shape[1]*weight_shape[2]) np.random.shuffle(rand_map_2) pruning_mask = np.array(bl_pruning_mask).astype(bool) # weights for extra input 0 init_mask = np.logical_not(pruning_mask[rand_map_0]) pruning_mask_recover = np.logical_and(pruning_mask, init_mask)[np.argsort(rand_map_0)] pruning_mask = np.logical_or(pruning_mask, pruning_mask_recover) init_mask = np.reshape(init_mask, weight_shape) bl_w1_rand = bl_w1_unroll[rand_map_0] bl_w1_rand = np.reshape(bl_w1_rand, weight_shape) w1 = bl_w1 w2 = bl_w1 w3 = bl_w1 w4 = bl_w1 w5 = bl_w1 w6 = bl_w1 w7 = bl_w1 w8 = bl_w1 w9 = -bl_w1 w10 = -bl_w1 w11 = -bl_w1 w12 = -bl_w1 w13 = -bl_w1 w14 = -bl_w1 w15 = -bl_w1 w16 = -bl_w1 w17 = bl_w1 w18 = bl_w1 w19 = bl_w1 w20 = bl_w1 w21 = bl_w1 w22 = bl_w1 w23 = bl_w1 w24 = bl_w1 w25 = -bl_w1 w26 = -bl_w1 w27 = -bl_w1 w28 = -bl_w1 w29 = -bl_w1 w30 = -bl_w1 w31 = -bl_w1 w32 = -bl_w1 w1[init_mask] = w1[init_mask] + bl_w1_rand[init_mask] w2[init_mask] = w2[init_mask] + bl_w1_rand[init_mask] w3[init_mask] = w3[init_mask] + bl_w1_rand[init_mask] w4[init_mask] = w4[init_mask] + bl_w1_rand[init_mask] w5[init_mask] = w5[init_mask] - bl_w1_rand[init_mask] w6[init_mask] = w6[init_mask] - bl_w1_rand[init_mask] w7[init_mask] = w7[init_mask] - bl_w1_rand[init_mask] w8[init_mask] = w8[init_mask] - bl_w1_rand[init_mask] w9[init_mask] = w9[init_mask] + bl_w1_rand[init_mask] w10[init_mask] = w10[init_mask] + bl_w1_rand[init_mask] w11[init_mask] = w11[init_mask] + bl_w1_rand[init_mask] w12[init_mask] = w12[init_mask] + bl_w1_rand[init_mask] w13[init_mask] = w13[init_mask] - bl_w1_rand[init_mask] w14[init_mask] = w14[init_mask] - bl_w1_rand[init_mask] w15[init_mask] = w15[init_mask] - bl_w1_rand[init_mask] w16[init_mask] = w16[init_mask] - bl_w1_rand[init_mask] w17[init_mask] = w17[init_mask] + bl_w1_rand[init_mask] w18[init_mask] = w18[init_mask] + bl_w1_rand[init_mask] w19[init_mask] = w19[init_mask] + bl_w1_rand[init_mask] w20[init_mask] = w20[init_mask] + bl_w1_rand[init_mask] w21[init_mask] = w21[init_mask] - bl_w1_rand[init_mask] w22[init_mask] = w22[init_mask] - bl_w1_rand[init_mask] w23[init_mask] = w23[init_mask] - bl_w1_rand[init_mask] w24[init_mask] = w24[init_mask] - bl_w1_rand[init_mask] w25[init_mask] = w25[init_mask] + bl_w1_rand[init_mask] w26[init_mask] = w26[init_mask] + bl_w1_rand[init_mask] w27[init_mask] = w27[init_mask] + bl_w1_rand[init_mask] w28[init_mask] = w28[init_mask] + bl_w1_rand[init_mask] w29[init_mask] = w29[init_mask] - bl_w1_rand[init_mask] w30[init_mask] = w30[init_mask] - bl_w1_rand[init_mask] w31[init_mask] = w31[init_mask] - bl_w1_rand[init_mask] w32[init_mask] = w32[init_mask] - bl_w1_rand[init_mask] # weights for extra input 2 init_mask = np.logical_not(pruning_mask[rand_map_1]) pruning_mask_recover = np.logical_and(pruning_mask, init_mask)[np.argsort(rand_map_1)] pruning_mask = np.logical_or(pruning_mask, pruning_mask_recover) init_mask = np.reshape(init_mask, weight_shape) bl_w1_rand = bl_w1_unroll[rand_map_1] bl_w1_rand = np.reshape(bl_w1_rand, weight_shape) w1[init_mask] = w1[init_mask] + bl_w1_rand[init_mask] w2[init_mask] = w2[init_mask] + bl_w1_rand[init_mask] w3[init_mask] = w3[init_mask] - bl_w1_rand[init_mask] w4[init_mask] = w4[init_mask] - bl_w1_rand[init_mask] w5[init_mask] = w5[init_mask] + bl_w1_rand[init_mask] w6[init_mask] = w6[init_mask] + bl_w1_rand[init_mask] w7[init_mask] = w7[init_mask] - bl_w1_rand[init_mask] w8[init_mask] = w8[init_mask] - bl_w1_rand[init_mask] w9[init_mask] = w9[init_mask] + bl_w1_rand[init_mask] w10[init_mask] = w10[init_mask] + bl_w1_rand[init_mask] w11[init_mask] = w11[init_mask] - bl_w1_rand[init_mask] w12[init_mask] = w12[init_mask] - bl_w1_rand[init_mask] w13[init_mask] = w13[init_mask] + bl_w1_rand[init_mask] w14[init_mask] = w14[init_mask] + bl_w1_rand[init_mask] w15[init_mask] = w15[init_mask] - bl_w1_rand[init_mask] w16[init_mask] = w16[init_mask] - bl_w1_rand[init_mask] w17[init_mask] = w17[init_mask] + bl_w1_rand[init_mask] w18[init_mask] = w18[init_mask] + bl_w1_rand[init_mask] w19[init_mask] = w19[init_mask] - bl_w1_rand[init_mask] w20[init_mask] = w20[init_mask] - bl_w1_rand[init_mask] w21[init_mask] = w21[init_mask] + bl_w1_rand[init_mask] w22[init_mask] = w22[init_mask] + bl_w1_rand[init_mask] w23[init_mask] = w23[init_mask] - bl_w1_rand[init_mask] w24[init_mask] = w24[init_mask] - bl_w1_rand[init_mask] w25[init_mask] = w25[init_mask] + bl_w1_rand[init_mask] w26[init_mask] = w26[init_mask] + bl_w1_rand[init_mask] w27[init_mask] = w27[init_mask] - bl_w1_rand[init_mask] w28[init_mask] = w28[init_mask] - bl_w1_rand[init_mask] w29[init_mask] = w29[init_mask] + bl_w1_rand[init_mask] w30[init_mask] = w30[init_mask] + bl_w1_rand[init_mask] w31[init_mask] = w31[init_mask] - bl_w1_rand[init_mask] w32[init_mask] = w32[init_mask] - bl_w1_rand[init_mask] # weights for extra input 3 init_mask = np.logical_not(pruning_mask[rand_map_2]) pruning_mask_recover = np.logical_and(pruning_mask, init_mask)[np.argsort(rand_map_2)] pruning_mask = np.logical_or(pruning_mask, pruning_mask_recover) init_mask = np.reshape(init_mask, weight_shape) bl_w1_rand = bl_w1_unroll[rand_map_2] bl_w1_rand = np.reshape(bl_w1_rand, weight_shape) w1[init_mask] = w1[init_mask] + bl_w1_rand[init_mask] w2[init_mask] = w2[init_mask] - bl_w1_rand[init_mask] w3[init_mask] = w3[init_mask] + bl_w1_rand[init_mask] w4[init_mask] = w4[init_mask] - bl_w1_rand[init_mask] w5[init_mask] = w5[init_mask] + bl_w1_rand[init_mask] w6[init_mask] = w6[init_mask] - bl_w1_rand[init_mask] w7[init_mask] = w7[init_mask] + bl_w1_rand[init_mask] w8[init_mask] = w8[init_mask] - bl_w1_rand[init_mask] w9[init_mask] = w9[init_mask] + bl_w1_rand[init_mask] w10[init_mask] = w10[init_mask] - bl_w1_rand[init_mask] w11[init_mask] = w11[init_mask] + bl_w1_rand[init_mask] w12[init_mask] = w12[init_mask] - bl_w1_rand[init_mask] w13[init_mask] = w13[init_mask] + bl_w1_rand[init_mask] w14[init_mask] = w14[init_mask] - bl_w1_rand[init_mask] w15[init_mask] = w15[init_mask] + bl_w1_rand[init_mask] w16[init_mask] = w16[init_mask] - bl_w1_rand[init_mask] w17[init_mask] = w17[init_mask] + bl_w1_rand[init_mask] w18[init_mask] = w18[init_mask] - bl_w1_rand[init_mask] w19[init_mask] = w19[init_mask] + bl_w1_rand[init_mask] w20[init_mask] = w20[init_mask] - bl_w1_rand[init_mask] w21[init_mask] = w21[init_mask] + bl_w1_rand[init_mask] w22[init_mask] = w22[init_mask] - bl_w1_rand[init_mask] w23[init_mask] = w23[init_mask] + bl_w1_rand[init_mask] w24[init_mask] = w24[init_mask] - bl_w1_rand[init_mask] w25[init_mask] = w25[init_mask] + bl_w1_rand[init_mask] w26[init_mask] = w26[init_mask] - bl_w1_rand[init_mask] w27[init_mask] = w27[init_mask] + bl_w1_rand[init_mask] w28[init_mask] = w28[init_mask] - bl_w1_rand[init_mask] w29[init_mask] = w29[init_mask] + bl_w1_rand[init_mask] w30[init_mask] = w30[init_mask] - bl_w1_rand[init_mask] w31[init_mask] = w31[init_mask] + bl_w1_rand[init_mask] w32[init_mask] = w32[init_mask] - bl_w1_rand[init_mask] pret_w1[...] = w1 pret_w2[...] = w2 pret_w3[...] = w3 pret_w4[...] = w4 pret_w5[...] = w5 pret_w6[...] = w6 pret_w7[...] = w7 pret_w8[...] = w8 pret_w9[...] = w9 pret_w10[...] = w10 pret_w11[...] = w11 pret_w12[...] = w12 pret_w13[...] = w13 pret_w14[...] = w14 pret_w15[...] = w15 pret_w16[...] = w16 pret_w17[...] = w17 pret_w18[...] = w18 pret_w19[...] = w19 pret_w20[...] = w20 pret_w21[...] = w21 pret_w22[...] = w22 pret_w23[...] = w23 pret_w24[...] = w24 pret_w25[...] = w25 pret_w26[...] = w26 pret_w27[...] = w27 pret_w28[...] = w28 pret_w29[...] = w29 pret_w30[...] = w30 pret_w31[...] = w31 pret_w32[...] = w32 pret_rand_map_0[...] = np.reshape(rand_map_0, (-1,1)).astype(float) pret_rand_map_1[...] = np.reshape(rand_map_1, (-1,1)).astype(float) pret_rand_map_2[...] = np.reshape(rand_map_2, (-1,1)).astype(float) p_gamma[...] = np.array(bl_gamma) pret_means[...] = np.array(bl_means) pret_pruning_mask[...] = np.array(bl_pruning_mask) print(np.sum(np.array(bl_pruning_mask)), np.prod(np.shape(np.array(bl_pruning_mask)))) # dense layer 1 bl_w1 = bl["model_weights"]["binary_dense_1"]["binary_dense_1"]["Variable_1:0"] #bl_rand_map = bl["model_weights"]["binary_dense_1"]["binary_dense_1"]["rand_map:0"] bl_pruning_mask = bl["model_weights"]["binary_dense_1"]["binary_dense_1"]["pruning_mask:0"] bl_gamma = bl["model_weights"]["binary_dense_1"]["binary_dense_1"]["Variable:0"] bl_means = bl["model_weights"]["residual_sign_6"]["residual_sign_6"]["means:0"] zero_fill = np.zeros(np.shape(np.array(bl_w1))) pret_w1 = pretrained["model_weights"]["binary_dense_1"]["binary_dense_1"]["Variable_1:0"] #pret_rand_map = pretrained["model_weights"]["binary_dense_1"]["binary_dense_1"]["rand_map:0"] pret_pruning_mask = pretrained["model_weights"]["binary_dense_1"]["binary_dense_1"]["pruning_mask:0"] p_gamma = pretrained["model_weights"]["binary_dense_1"]["binary_dense_1"]["Variable:0"] pret_means = pretrained["model_weights"]["residual_sign_6"]["residual_sign_6"]["means:0"] pret_w1[...] = np.array(bl_w1) #pret_rand_map[...] = np.array(bl_rand_map) p_gamma[...] = np.array(bl_gamma) pret_means[...] = np.array(bl_means) pret_pruning_mask[...] = np.array(bl_pruning_mask) print(np.sum(np.array(bl_pruning_mask)), np.prod(np.shape(np.array(bl_pruning_mask)))) # dense layer 2 bl_w1 = bl["model_weights"]["binary_dense_2"]["binary_dense_2"]["Variable_1:0"] #bl_rand_map = bl["model_weights"]["binary_dense_2"]["binary_dense_2"]["rand_map:0"] bl_pruning_mask = bl["model_weights"]["binary_dense_2"]["binary_dense_2"]["pruning_mask:0"] bl_gamma = bl["model_weights"]["binary_dense_2"]["binary_dense_2"]["Variable:0"] bl_means = bl["model_weights"]["residual_sign_7"]["residual_sign_7"]["means:0"] zero_fill = np.zeros(np.shape(np.array(bl_w1))) pret_w1 = pretrained["model_weights"]["binary_dense_2"]["binary_dense_2"]["Variable_1:0"] #pret_rand_map = pretrained["model_weights"]["binary_dense_2"]["binary_dense_2"]["rand_map:0"] pret_pruning_mask = pretrained["model_weights"]["binary_dense_2"]["binary_dense_2"]["pruning_mask:0"] p_gamma = pretrained["model_weights"]["binary_dense_2"]["binary_dense_2"]["Variable:0"] pret_means = pretrained["model_weights"]["residual_sign_7"]["residual_sign_7"]["means:0"] pret_w1[...] = np.array(bl_w1) #pret_rand_map[...] = np.array(bl_rand_map) p_gamma[...] = np.array(bl_gamma) pret_means[...] = np.array(bl_means) pret_pruning_mask[...] = np.array(bl_pruning_mask) print(np.sum(np.array(bl_pruning_mask)), np.prod(np.shape(np.array(bl_pruning_mask)))) # dense layer 3 bl_w1 = bl["model_weights"]["binary_dense_3"]["binary_dense_3"]["Variable_1:0"] #bl_rand_map = bl["model_weights"]["binary_dense_3"]["binary_dense_3"]["rand_map:0"] bl_pruning_mask = bl["model_weights"]["binary_dense_3"]["binary_dense_3"]["pruning_mask:0"] bl_gamma = bl["model_weights"]["binary_dense_3"]["binary_dense_3"]["Variable:0"] bl_means = bl["model_weights"]["residual_sign_8"]["residual_sign_8"]["means:0"] zero_fill = np.zeros(np.shape(np.array(bl_w1))) pret_w1 = pretrained["model_weights"]["binary_dense_3"]["binary_dense_3"]["Variable_1:0"] #pret_rand_map = pretrained["model_weights"]["binary_dense_3"]["binary_dense_3"]["rand_map:0"] pret_pruning_mask = pretrained["model_weights"]["binary_dense_3"]["binary_dense_3"]["pruning_mask:0"] p_gamma = pretrained["model_weights"]["binary_dense_3"]["binary_dense_3"]["Variable:0"] pret_means = pretrained["model_weights"]["residual_sign_8"]["residual_sign_8"]["means:0"] pret_w1[...] = np.array(bl_w1) #pret_rand_map[...] = np.array(bl_rand_map) p_gamma[...] = np.array(bl_gamma) pret_means[...] = np.array(bl_means) pret_pruning_mask[...] = np.array(bl_pruning_mask) print(np.sum(np.array(bl_pruning_mask)), np.prod(np.shape(np.array(bl_pruning_mask)))) # bn 1 bl_beta = bl["model_weights"]["batch_normalization_1"]["batch_normalization_1"]["beta:0"] bl_gamma = bl["model_weights"]["batch_normalization_1"]["batch_normalization_1"]["gamma:0"] bl_moving_mean = bl["model_weights"]["batch_normalization_1"]["batch_normalization_1"]["moving_mean:0"] bl_moving_variance = bl["model_weights"]["batch_normalization_1"]["batch_normalization_1"]["moving_variance:0"] p_beta = pretrained["model_weights"]["batch_normalization_1"]["batch_normalization_1"]["beta:0"] p_gamma = pretrained["model_weights"]["batch_normalization_1"]["batch_normalization_1"]["gamma:0"] p_moving_mean = pretrained["model_weights"]["batch_normalization_1"]["batch_normalization_1"]["moving_mean:0"] p_moving_variance = pretrained["model_weights"]["batch_normalization_1"]["batch_normalization_1"]["moving_variance:0"] p_beta[...] = np.array(bl_beta) p_gamma[...] = np.array(bl_gamma) p_moving_mean[...] = np.array(bl_moving_mean) p_moving_variance[...] = np.array(bl_moving_variance) # bn 2 bl_beta = bl["model_weights"]["batch_normalization_2"]["batch_normalization_2"]["beta:0"] bl_gamma = bl["model_weights"]["batch_normalization_2"]["batch_normalization_2"]["gamma:0"] bl_moving_mean = bl["model_weights"]["batch_normalization_2"]["batch_normalization_2"]["moving_mean:0"] bl_moving_variance = bl["model_weights"]["batch_normalization_2"]["batch_normalization_2"]["moving_variance:0"] p_beta = pretrained["model_weights"]["batch_normalization_2"]["batch_normalization_2"]["beta:0"] p_gamma = pretrained["model_weights"]["batch_normalization_2"]["batch_normalization_2"]["gamma:0"] p_moving_mean = pretrained["model_weights"]["batch_normalization_2"]["batch_normalization_2"]["moving_mean:0"] p_moving_variance = pretrained["model_weights"]["batch_normalization_2"]["batch_normalization_2"]["moving_variance:0"] p_beta[...] = np.array(bl_beta) p_gamma[...] = np.array(bl_gamma) p_moving_mean[...] = np.array(bl_moving_mean) p_moving_variance[...] = np.array(bl_moving_variance) # bn 3 bl_beta = bl["model_weights"]["batch_normalization_3"]["batch_normalization_3"]["beta:0"] bl_gamma = bl["model_weights"]["batch_normalization_3"]["batch_normalization_3"]["gamma:0"] bl_moving_mean = bl["model_weights"]["batch_normalization_3"]["batch_normalization_3"]["moving_mean:0"] bl_moving_variance = bl["model_weights"]["batch_normalization_3"]["batch_normalization_3"]["moving_variance:0"] p_beta = pretrained["model_weights"]["batch_normalization_3"]["batch_normalization_3"]["beta:0"] p_gamma = pretrained["model_weights"]["batch_normalization_3"]["batch_normalization_3"]["gamma:0"] p_moving_mean = pretrained["model_weights"]["batch_normalization_3"]["batch_normalization_3"]["moving_mean:0"] p_moving_variance = pretrained["model_weights"]["batch_normalization_3"]["batch_normalization_3"]["moving_variance:0"] p_beta[...] = np.array(bl_beta) p_gamma[...] = np.array(bl_gamma) p_moving_mean[...] = np.array(bl_moving_mean) p_moving_variance[...] = np.array(bl_moving_variance) # bn 4 bl_beta = bl["model_weights"]["batch_normalization_4"]["batch_normalization_4"]["beta:0"] bl_gamma = bl["model_weights"]["batch_normalization_4"]["batch_normalization_4"]["gamma:0"] bl_moving_mean = bl["model_weights"]["batch_normalization_4"]["batch_normalization_4"]["moving_mean:0"] bl_moving_variance = bl["model_weights"]["batch_normalization_4"]["batch_normalization_4"]["moving_variance:0"] p_beta = pretrained["model_weights"]["batch_normalization_4"]["batch_normalization_4"]["beta:0"] p_gamma = pretrained["model_weights"]["batch_normalization_4"]["batch_normalization_4"]["gamma:0"] p_moving_mean = pretrained["model_weights"]["batch_normalization_4"]["batch_normalization_4"]["moving_mean:0"] p_moving_variance = pretrained["model_weights"]["batch_normalization_4"]["batch_normalization_4"]["moving_variance:0"] p_beta[...] = np.array(bl_beta) p_gamma[...] = np.array(bl_gamma) p_moving_mean[...] = np.array(bl_moving_mean) p_moving_variance[...] = np.array(bl_moving_variance) # bn 5 bl_beta = bl["model_weights"]["batch_normalization_5"]["batch_normalization_5"]["beta:0"] bl_gamma = bl["model_weights"]["batch_normalization_5"]["batch_normalization_5"]["gamma:0"] bl_moving_mean = bl["model_weights"]["batch_normalization_5"]["batch_normalization_5"]["moving_mean:0"] bl_moving_variance = bl["model_weights"]["batch_normalization_5"]["batch_normalization_5"]["moving_variance:0"] p_beta = pretrained["model_weights"]["batch_normalization_5"]["batch_normalization_5"]["beta:0"] p_gamma = pretrained["model_weights"]["batch_normalization_5"]["batch_normalization_5"]["gamma:0"] p_moving_mean = pretrained["model_weights"]["batch_normalization_5"]["batch_normalization_5"]["moving_mean:0"] p_moving_variance = pretrained["model_weights"]["batch_normalization_5"]["batch_normalization_5"]["moving_variance:0"] p_beta[...] = np.array(bl_beta) p_gamma[...] = np.array(bl_gamma) p_moving_mean[...] = np.array(bl_moving_mean) p_moving_variance[...] = np.array(bl_moving_variance) # bn 6 bl_beta = bl["model_weights"]["batch_normalization_6"]["batch_normalization_6"]["beta:0"] bl_gamma = bl["model_weights"]["batch_normalization_6"]["batch_normalization_6"]["gamma:0"] bl_moving_mean = bl["model_weights"]["batch_normalization_6"]["batch_normalization_6"]["moving_mean:0"] bl_moving_variance = bl["model_weights"]["batch_normalization_6"]["batch_normalization_6"]["moving_variance:0"] p_beta = pretrained["model_weights"]["batch_normalization_6"]["batch_normalization_6"]["beta:0"] p_gamma = pretrained["model_weights"]["batch_normalization_6"]["batch_normalization_6"]["gamma:0"] p_moving_mean = pretrained["model_weights"]["batch_normalization_6"]["batch_normalization_6"]["moving_mean:0"] p_moving_variance = pretrained["model_weights"]["batch_normalization_6"]["batch_normalization_6"]["moving_variance:0"] p_beta[...] = np.array(bl_beta) p_gamma[...] = np.array(bl_gamma) p_moving_mean[...] = np.array(bl_moving_mean) p_moving_variance[...] = np.array(bl_moving_variance) # bn 7 bl_beta = bl["model_weights"]["batch_normalization_7"]["batch_normalization_7"]["beta:0"] bl_gamma = bl["model_weights"]["batch_normalization_7"]["batch_normalization_7"]["gamma:0"] bl_moving_mean = bl["model_weights"]["batch_normalization_7"]["batch_normalization_7"]["moving_mean:0"] bl_moving_variance = bl["model_weights"]["batch_normalization_7"]["batch_normalization_7"]["moving_variance:0"] p_beta = pretrained["model_weights"]["batch_normalization_7"]["batch_normalization_7"]["beta:0"] p_gamma = pretrained["model_weights"]["batch_normalization_7"]["batch_normalization_7"]["gamma:0"] p_moving_mean = pretrained["model_weights"]["batch_normalization_7"]["batch_normalization_7"]["moving_mean:0"] p_moving_variance = pretrained["model_weights"]["batch_normalization_7"]["batch_normalization_7"]["moving_variance:0"] p_beta[...] = np.array(bl_beta) p_gamma[...] = np.array(bl_gamma) p_moving_mean[...] = np.array(bl_moving_mean) p_moving_variance[...] = np.array(bl_moving_variance) # bn 8 bl_beta = bl["model_weights"]["batch_normalization_8"]["batch_normalization_8"]["beta:0"] bl_gamma = bl["model_weights"]["batch_normalization_8"]["batch_normalization_8"]["gamma:0"] bl_moving_mean = bl["model_weights"]["batch_normalization_8"]["batch_normalization_8"]["moving_mean:0"] bl_moving_variance = bl["model_weights"]["batch_normalization_8"]["batch_normalization_8"]["moving_variance:0"] p_beta = pretrained["model_weights"]["batch_normalization_8"]["batch_normalization_8"]["beta:0"] p_gamma = pretrained["model_weights"]["batch_normalization_8"]["batch_normalization_8"]["gamma:0"] p_moving_mean = pretrained["model_weights"]["batch_normalization_8"]["batch_normalization_8"]["moving_mean:0"] p_moving_variance = pretrained["model_weights"]["batch_normalization_8"]["batch_normalization_8"]["moving_variance:0"] p_beta[...] = np.array(bl_beta) p_gamma[...] = np.array(bl_gamma) p_moving_mean[...] = np.array(bl_moving_mean) p_moving_variance[...] = np.array(bl_moving_variance) # bn 7 bl_beta = bl["model_weights"]["batch_normalization_9"]["batch_normalization_9"]["beta:0"] bl_gamma = bl["model_weights"]["batch_normalization_9"]["batch_normalization_9"]["gamma:0"] bl_moving_mean = bl["model_weights"]["batch_normalization_9"]["batch_normalization_9"]["moving_mean:0"] bl_moving_variance = bl["model_weights"]["batch_normalization_9"]["batch_normalization_9"]["moving_variance:0"] p_beta = pretrained["model_weights"]["batch_normalization_9"]["batch_normalization_9"]["beta:0"] p_gamma = pretrained["model_weights"]["batch_normalization_9"]["batch_normalization_9"]["gamma:0"] p_moving_mean = pretrained["model_weights"]["batch_normalization_9"]["batch_normalization_9"]["moving_mean:0"] p_moving_variance = pretrained["model_weights"]["batch_normalization_9"]["batch_normalization_9"]["moving_variance:0"] p_beta[...] = np.array(bl_beta) p_gamma[...] = np.array(bl_gamma) p_moving_mean[...] = np.array(bl_moving_mean) p_moving_variance[...] = np.array(bl_moving_variance) pretrained.close()

52.405583

118

0.755162

5,297

31,915

4.097791

0.02643

0.110569

0.093707

0.053073

0.940063

0.938312

0.937759

0.931632

0.927992

0.904174

0

0.050207

0.059502

31,915

608

119

52.491776

0.672941

0.080902

0

0.363441

0

0.351961

0.103293

0

1

0

false

0

0.006452

0

0.006452

0.019355

0

null

0

1

0

null

0

6

b459c48935d5bdcff1db9b6d1cb2edcc44b5afb8

2,889

py

Python

listcord/__init__.py

imkr-vishal/listcord.py

3026d0c09b44f3828f2f0103134f7d6975c3ca18

[ "MIT" ]

1

2021-03-07T18:50:14.000Z

listcord/__init__.py

imkr-vishal/listcord.py

3026d0c09b44f3828f2f0103134f7d6975c3ca18

[ "MIT" ]

null

listcord/__init__.py

imkr-vishal/listcord.py

3026d0c09b44f3828f2f0103134f7d6975c3ca18

[ "MIT" ]

null

import requests import aiohttp class Client(): def __init__(self, token: str): self.token = token self.baseURL = 'https://listcord.xyz/api' def get_bot(self, id: str): data = requests.get(self.baseURL + '/bot/' + id, headers={ 'token': self.token }) return data.json() async def get_bot_async(self, id: str): async with aiohttp.ClientSession() as session: async with session.get(self.baseURL + '/bot/' + id, headers={ 'token': self.token }) as result: return await result.json() def get_bot_reviews(self, id: str): data = requests.get(self.baseURL + '/bot/' + id + '/reviews', headers={ 'token': self.token }) return data.json() async def get_bot_reviews_async(self, id: str): async with aiohttp.ClientSession() as session: async with session.get(self.baseURL + '/bot/' + id + '/reviews', headers={ 'token': self.token }) as result: return await result.json() def get_review(self, user_id: str, bot_id: str): reviews = self.get_bot_reviews(bot_id) if not isinstance(reviews, list): return None for review in reviews: if review['author_id'] == user_id: return review return None async def get_review_async(self, user_id: str, bot_id: str): async with aiohttp.ClientSession() as session: async with session.get(self.baseURL + '/bot/' + bot_id + '/reviews', headers={ 'token': self.token }) as result: reviews = await result.json() if not isinstance(reviews, list): return None for review in reviews: if review['author_id'] == user_id: return review return None def has_voted(self, user_id: str, bot_id: str): data = requests.get(self.baseURL + '/bot/' + bot_id + '/voted', params={ 'user_id': user_id }, headers={ 'token': self.token }) return data.json() async def has_voted_async(self, user_id: str, bot_id: str): async with aiohttp.ClientSession() as session: async with session.get(self.baseURL + '/bot/' + bot_id + '/voted', params={ 'user_id': user_id }, headers={ 'token': self.token }) as result: return await result.json() def search(self, q: str): data = requests.get(self.baseURL + '/bots', params={ 'q': q }, headers={ 'token': self.token }) return data.json() async def search_async(self, q: str): async with aiohttp.ClientSession() as session: async with session.get(self.baseURL + '/bots', params={ 'q': q }, headers={ 'token': self.token }) as result: return await result.json() def __str__(self): return 'Listcord<Client>' __version__ = '1.5.0'

38.52

153

0.583247

363

2,889

4.506887

0.137741

0.036675

0.077017

0.115526

0.826406

0.817237

0.794621

0.78423

0.748778

0

0.001453

0.28522

2,889

75

154

38.52

0.790799

0

0.454545

0

0.070934

0

1

0.127273

false

0

0.036364

0.018182

0.454545

0

null

0

1

0

null

0

6

5ef7ef510f60d776a9bb129251c14820c4983975

4,741

py

Python

raiden/messages/withdraw.py

ExchangeUnion/raiden

2217bcb698fcfce3499dc1f41ad919ed82e8e45f

[ "MIT" ]

null

raiden/messages/withdraw.py

ExchangeUnion/raiden

2217bcb698fcfce3499dc1f41ad919ed82e8e45f

[ "MIT" ]

12

2019-08-09T19:12:17.000Z

2019-12-05T15:49:29.000Z

raiden/messages/withdraw.py

ExchangeUnion/raiden

2217bcb698fcfce3499dc1f41ad919ed82e8e45f

[ "MIT" ]

null

from dataclasses import dataclass from raiden.constants import EMPTY_SIGNATURE from raiden.messages.abstract import SignedRetrieableMessage from raiden.messages.cmdid import CmdId from raiden.utils.signing import pack_data from raiden.utils.typing import ( Address, BlockExpiration, ChainID, ChannelID, ClassVar, Nonce, TokenNetworkAddress, WithdrawAmount, ) from raiden_contracts.constants import MessageTypeId @dataclass(repr=False, eq=False) class WithdrawRequest(SignedRetrieableMessage): """ Requests a signed on-chain withdraw confirmation from partner. """ cmdid: ClassVar[CmdId] = CmdId.WITHDRAW_REQUEST message_type: ClassVar[int] = MessageTypeId.WITHDRAW chain_id: ChainID token_network_address: TokenNetworkAddress channel_identifier: ChannelID participant: Address total_withdraw: WithdrawAmount nonce: Nonce expiration: BlockExpiration @classmethod def from_event(cls, event): return cls( message_identifier=event.message_identifier, chain_id=event.canonical_identifier.chain_identifier, token_network_address=event.canonical_identifier.token_network_address, channel_identifier=event.canonical_identifier.channel_identifier, total_withdraw=event.total_withdraw, participant=event.participant, nonce=event.nonce, expiration=event.expiration, signature=EMPTY_SIGNATURE, ) def _data_to_sign(self) -> bytes: return pack_data( (self.token_network_address, "address"), (self.chain_id, "uint256"), (self.message_type, "uint256"), (self.channel_identifier, "uint256"), (self.participant, "address"), (self.total_withdraw, "uint256"), (self.expiration, "uint256"), ) @dataclass(repr=False, eq=False) class WithdrawConfirmation(SignedRetrieableMessage): """ Confirms withdraw to partner with a signature """ cmdid: ClassVar[CmdId] = CmdId.WITHDRAW_CONFIRMATION message_type: ClassVar[int] = MessageTypeId.WITHDRAW chain_id: ChainID token_network_address: TokenNetworkAddress channel_identifier: ChannelID participant: Address total_withdraw: WithdrawAmount nonce: Nonce expiration: BlockExpiration @classmethod def from_event(cls, event): return cls( message_identifier=event.message_identifier, chain_id=event.canonical_identifier.chain_identifier, token_network_address=event.canonical_identifier.token_network_address, channel_identifier=event.canonical_identifier.channel_identifier, total_withdraw=event.total_withdraw, participant=event.participant, nonce=event.nonce, expiration=event.expiration, signature=EMPTY_SIGNATURE, ) def _data_to_sign(self) -> bytes: return pack_data( (self.token_network_address, "address"), (self.chain_id, "uint256"), (self.message_type, "uint256"), (self.channel_identifier, "uint256"), (self.participant, "address"), (self.total_withdraw, "uint256"), (self.expiration, "uint256"), ) @dataclass class WithdrawExpired(SignedRetrieableMessage): """ Notifies about withdraw expiration/cancellation from partner. """ cmdid: ClassVar[CmdId] = CmdId.WITHDRAW_EXPIRED message_type: ClassVar[int] = MessageTypeId.WITHDRAW chain_id: ChainID token_network_address: TokenNetworkAddress channel_identifier: ChannelID participant: Address total_withdraw: WithdrawAmount expiration: BlockExpiration nonce: Nonce @classmethod def from_event(cls, event): return cls( message_identifier=event.message_identifier, chain_id=event.canonical_identifier.chain_identifier, token_network_address=event.canonical_identifier.token_network_address, channel_identifier=event.canonical_identifier.channel_identifier, total_withdraw=event.total_withdraw, participant=event.participant, nonce=event.nonce, expiration=event.expiration, signature=EMPTY_SIGNATURE, ) def _data_to_sign(self) -> bytes: return pack_data( (self.token_network_address, "address"), (self.chain_id, "uint256"), (self.message_type, "uint256"), (self.channel_identifier, "uint256"), (self.participant, "address"), (self.total_withdraw, "uint256"), (self.expiration, "uint256"), )

33.624113

83

0.678971

451

4,741

6.904656

0.157428

0.046243

0.073218

0.055877

0.787733

0.777778

0.7614

0.734425

0

0.012465

0.238557

4,741

140

84

33.864286

0.850139

0.036279

0

0.754237

0

0.032315

0

1

0.050847

false

0

0.059322

0.050847

0.415254

0

null

0

1

0

1

0

null

0

6

6f0f8bae66d58d55fd063fabcfff3db02ccabf50

28

py

Python

sca/sca_events/__init__.py

open-power-sdk/source-code-advisor

f39d6f59bfd33e5ac1148e1e9b72f472c8429252

[ "Apache-2.0" ]

10

2017-04-11T19:18:40.000Z

2019-10-17T18:00:30.000Z

sca/sca_events/__init__.py

open-power-sdk/source-code-advisor

f39d6f59bfd33e5ac1148e1e9b72f472c8429252

[ "Apache-2.0" ]

2

2017-04-20T17:32:57.000Z

2021-10-18T17:15:00.000Z

sca/sca_events/__init__.py

open-power-sdk/source-code-advisor

f39d6f59bfd33e5ac1148e1e9b72f472c8429252

[ "Apache-2.0" ]

4

2017-04-12T23:59:37.000Z

2018-04-14T14:34:59.000Z

from sca_xml import ScaXml

9.333333

26

0.821429

5

28

4.4

1

0

0.178571

28

2

27

14

0.956522

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

6f139b6a556b9a2fc3e2f7d9c56278f218bdd9ab

5,318

py

Python

community/models.py

loffle/loffle_back

f102d5361ac00abf8fa6e2407e9481222e8201e6

[ "MIT" ]

null

community/models.py

loffle/loffle_back

f102d5361ac00abf8fa6e2407e9481222e8201e6

[ "MIT" ]

null

community/models.py

loffle/loffle_back

f102d5361ac00abf8fa6e2407e9481222e8201e6

[ "MIT" ]

null

from django.db import models from account.models import User class CommonManager(models.Manager): def __init__(self, is_deleted=False): super().__init__() self.is_deleted = is_deleted def get_queryset(self): # queryset = Post.objects.filter(is_deleted=False) # queryset = Post.objects.filter(is_deleted=False).prefetch_related('like').select_related('user') # 세 queryset 성능 및 속도 비교해보기 return super().get_queryset().select_related('user').filter(is_deleted=self.is_deleted) # -------------------------------------------------------- class Post(models.Model): title = models.CharField(max_length=200) content = models.TextField() created_at = models.DateTimeField(auto_now_add=True) modified_at = models.DateTimeField(auto_now=True) is_deleted = models.BooleanField(default=False, editable=False) user = models.ForeignKey(User, related_name="posts", on_delete=models.CASCADE) # file = models.ManyToManyField(File, on_delete=models.SET_NULL, null=True, blank=True) # File like = models.ManyToManyField(User, related_name="liked_posts", blank=True) objects = CommonManager() deleted_objects = CommonManager(is_deleted=True) class PostComment(models.Model): content = models.CharField(max_length=200) created_at = models.DateTimeField(auto_now_add=True) modified_at = models.DateTimeField(auto_now=True) is_deleted = models.BooleanField(default=False, editable=False) post = models.ForeignKey(Post, related_name="comments", on_delete=models.CASCADE) user = models.ForeignKey(User, related_name="postcomments", on_delete=models.CASCADE) like = models.ManyToManyField(User, related_name="liked_postcomments", blank=True) # class Meta: # db_table = '_'.join((__package__, 'post_comment')) objects = CommonManager() deleted_objects = CommonManager(is_deleted=True) class Review(models.Model): # title = models.CharField(max_length=200) content = models.TextField() created_at = models.DateTimeField(auto_now_add=True) modified_at = models.DateTimeField(auto_now=True) is_deleted = models.BooleanField(default=False, editable=False) user = models.ForeignKey(User, related_name="reviews", on_delete=models.CASCADE) # file = models.ManyToManyField(File, on_delete=models.SET_NULL, null=True, blank=True) # raffle = models.ForeignKey(Raffle, on_delete=models.CASCADE) like = models.ManyToManyField(User, related_name="liked_reviews", blank=True) objects = CommonManager() deleted_objects = CommonManager(is_deleted=True) class ReviewComment(models.Model): content = models.CharField(max_length=200) created_at = models.DateTimeField(auto_now_add=True) modified_at = models.DateTimeField(auto_now=True) is_deleted = models.BooleanField(default=False, editable=False) review = models.ForeignKey(Review, related_name="comments", on_delete=models.CASCADE) user = models.ForeignKey(User, related_name="reviewcomments", on_delete=models.CASCADE) like = models.ManyToManyField(User, related_name="liked_reviewcomments", blank=True) objects = CommonManager() deleted_objects = CommonManager(is_deleted=True) class Notice(models.Model): title = models.CharField(max_length=200) content = models.TextField() created_at = models.DateTimeField(auto_now_add=True) modified_at = models.DateTimeField(auto_now=True) is_deleted = models.BooleanField(default=False, editable=False) user = models.ForeignKey(User, related_name="notices", on_delete=models.CASCADE) # file = models.ManyToManyField(File, on_delete=models.SET_NULL, null=True, blank=True) # File objects = CommonManager() deleted_objects = CommonManager(is_deleted=True) # ================= # # Question & Answer # # ================= # class QuestionType(models.Model): name = models.CharField(max_length=100, unique=True) def __str__(self): return self.name class Question(models.Model): title = models.CharField(max_length=200) content = models.TextField() created_at = models.DateTimeField(auto_now_add=True) modified_at = models.DateTimeField(auto_now=True) is_deleted = models.BooleanField(default=False, editable=False) user = models.ForeignKey(User, related_name="questions", on_delete=models.CASCADE) # file = models.ManyToManyField(File, on_delete=models.SET_NULL, null=True, blank=True) # File question_type = models.ForeignKey(QuestionType, related_name="questions", on_delete=models.PROTECT) objects = CommonManager() deleted_objects = CommonManager(is_deleted=True) class Answer(models.Model): title = models.CharField(max_length=200) content = models.TextField() created_at = models.DateTimeField(auto_now_add=True) modified_at = models.DateTimeField(auto_now=True) is_deleted = models.BooleanField(default=False, editable=False) user = models.ForeignKey(User, related_name="answers", on_delete=models.CASCADE) # file = models.ForeignKey(File, on_delete=models.SET_NULL, null=True, blank=True) # File question = models.ForeignKey(Question, related_name="answers", on_delete=models.CASCADE) objects = CommonManager() deleted_objects = CommonManager(is_deleted=True)

39.392593

106

0.730726

639

5,318

5.86698

0.137715

0.050413

0.063484

0.093358

0.804748

0.790611

0.739931

0.707922

0.673246

0

0.005264

0.142723

5,318

134

107

39.686567

0.817065

0.170365

0

0.575

0

0.036235

0

1

0.0375

false

0

0.025

0.975

0

null

0

1

0

null

0

6

489279d382b3707de270cd825475979160375be8

132

py

Python

dCC_Python_SodaMachine/backpack.py

JaredMartin0351/SodaMachineDebugging

f2959322b6e5bdfc74388e5bdd754766870ff5e4

[ "MIT" ]

null

dCC_Python_SodaMachine/backpack.py

JaredMartin0351/SodaMachineDebugging

f2959322b6e5bdfc74388e5bdd754766870ff5e4

[ "MIT" ]

null

dCC_Python_SodaMachine/backpack.py

JaredMartin0351/SodaMachineDebugging

f2959322b6e5bdfc74388e5bdd754766870ff5e4

[ "MIT" ]

null

class Backpack: purchased_cans = [] def __init__(self, purchased_cans): self.purchased_cans = purchased_cans

16.5

44

0.666667

14

132

5.714286

0.5

0.65

0.425

0

0.257576

132

7

45

18.857143

0.816327

0

1

0.25

false

0

0.75

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

489bc275e9cec96dccb77b11044248b29a1c8489

5,556

py

Python

tests/s3/test_s3_actions.py

farhanangullia/chaostoolkit-aws

2789ab91a7ac2373352fbf50cb60176cead7eccb

[ "Apache-2.0" ]

85

2018-01-31T16:55:37.000Z

2022-02-01T03:23:42.000Z

tests/s3/test_s3_actions.py

farhanangullia/chaostoolkit-aws

2789ab91a7ac2373352fbf50cb60176cead7eccb

[ "Apache-2.0" ]

88

2018-01-31T17:00:53.000Z

2021-12-13T08:18:42.000Z

tests/s3/test_s3_actions.py

farhanangullia/chaostoolkit-aws

2789ab91a7ac2373352fbf50cb60176cead7eccb

[ "Apache-2.0" ]

58

2018-01-30T19:33:19.000Z

2021-12-13T08:18:57.000Z

import json import os from unittest.mock import MagicMock, patch import pytest from botocore.exceptions import ClientError from chaoslib.exceptions import FailedActivity from chaosaws import aws_client from chaosaws.s3.actions import delete_object, toggle_versioning data_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "data") def read_configs(filename: str) -> dict: config = os.path.join(data_path, filename) with open(config, "r") as fh: return json.loads(fh.read()) def mock_client_error(*args, **kwargs) -> ClientError: return ClientError( operation_name=kwargs["op"], error_response={ "Error": {"Code": kwargs["Code"], "Message": kwargs["Message"]} }, ) @patch("chaosaws.s3.actions.aws_client", autospec=True) def test_delete_object_true(test_client: aws_client): client = MagicMock() test_client.return_value = client client.list_buckets.return_value = read_configs("list_buckets_1.json") client.get_object.return_value = read_configs("get_object_1.json") client.delete_object.return_value = {} delete_object(bucket_name="Test-Bucket-1", object_key="path/to/some/file.json") client.delete_object.assert_called_with( Bucket="Test-Bucket-1", Key="path/to/some/file.json" ) @patch("chaosaws.s3.actions.aws_client", autospec=True) def test_delete_object_false_invalid_bucket(test_client: aws_client): client = MagicMock() test_client.return_value = client client.list_buckets.return_value = read_configs("list_buckets_1.json") client.get_object.return_value = read_configs("get_object_1.json") client.delete_object.return_value = {} with pytest.raises(FailedActivity) as x: delete_object(bucket_name="Test-Bucket-99", object_key="path/to/some/file.json") assert 'Bucket "Test-Bucket-99" does not exist!' in str(x) @patch("chaosaws.s3.actions.aws_client", autospec=True) def test_delete_object_version_true(test_client: aws_client): client = MagicMock() test_client.return_value = client client.list_buckets.return_value = read_configs("list_buckets_1.json") client.get_object.return_value = read_configs("get_object_1.json") client.delete_object.return_value = {} delete_object( bucket_name="Test-Bucket-1", object_key="path/to/some/file.json", version_id="ab_cDefGhiJklMnoPqRsTu.aBcdEfGhi", ) client.delete_object.assert_called_with( Bucket="Test-Bucket-1", Key="path/to/some/file.json", VersionId="ab_cDefGhiJklMnoPqRsTu.aBcdEfGhi", ) @patch("chaosaws.s3.actions.aws_client", autospec=True) def test_toggle_versioning_no_bucket(test_client: aws_client): client = MagicMock() test_client.return_value = client client.list_buckets.return_value = read_configs("list_buckets_1.json") client.get_bucket_versioning.return_value = read_configs( "get_bucket_versioning_1.json" ) params = {"bucket_name": "Test-Bucket-15", "status": "Enabled"} with pytest.raises(FailedActivity) as x: toggle_versioning(**params) assert 'Bucket "Test-Bucket-15" does not exist!' in str(x) @patch("chaosaws.s3.actions.aws_client", autospec=True) def test_toggle_versioning_enable(test_client: aws_client): client = MagicMock() test_client.return_value = client client.list_buckets.return_value = read_configs("list_buckets_1.json") client.get_bucket_versioning.return_value = read_configs( "get_bucket_versioning_1.json" ) params = {"bucket_name": "Test-Bucket-8", "status": "Enabled"} toggle_versioning(**params) client.put_bucket_versioning.assert_called_with( Bucket="Test-Bucket-8", VersioningConfiguration={"Status": "Enabled"} ) @patch("chaosaws.s3.actions.aws_client", autospec=True) def test_toggle_versioning_enable_auto(test_client: aws_client): client = MagicMock() test_client.return_value = client client.list_buckets.return_value = read_configs("list_buckets_1.json") client.get_bucket_versioning.return_value = read_configs( "get_bucket_versioning_1.json" ) params = {"bucket_name": "Test-Bucket-8"} toggle_versioning(**params) client.put_bucket_versioning.assert_called_with( Bucket="Test-Bucket-8", VersioningConfiguration={"Status": "Enabled"} ) @patch("chaosaws.s3.actions.aws_client", autospec=True) def test_toggle_versioning_suspend(test_client: aws_client): client = MagicMock() test_client.return_value = client client.list_buckets.return_value = read_configs("list_buckets_1.json") client.get_bucket_versioning.return_value = read_configs( "get_bucket_versioning_2.json" ) params = {"bucket_name": "Test-Bucket-8", "status": "Suspended"} toggle_versioning(**params) client.put_bucket_versioning.assert_called_with( Bucket="Test-Bucket-8", VersioningConfiguration={"Status": "Suspended"} ) @patch("chaosaws.s3.actions.aws_client", autospec=True) def test_toggle_versioning_suspend_auto(test_client: aws_client): client = MagicMock() test_client.return_value = client client.list_buckets.return_value = read_configs("list_buckets_1.json") client.get_bucket_versioning.return_value = read_configs( "get_bucket_versioning_2.json" ) params = {"bucket_name": "Test-Bucket-8"} toggle_versioning(**params) client.put_bucket_versioning.assert_called_with( Bucket="Test-Bucket-8", VersioningConfiguration={"Status": "Suspended"} )

34.296296

88

0.732361

718

5,556

5.355153

0.130919

0.077243

0.062419

0.091547

0.814564

0.789077

0.782055

0.778934

0

0.009516

0.148848

5,556

161

89

34.509317

0.803553

0

0.54918

0

0.216883

0.099712

0

0.065574

1

0.081967

false

0

0.065574

0.008197

0.163934

0

null

0

1

0

null

0

6

48af6370ea1017398505127c6cfc19db7e51020f

120

py

Python

examples/x01separated/team_and_user/_lazy.py

Danil-Grigorev/swagger-marshmallow-codegen

4c077f6e1ef535bcbdbf1f643f97bc4cbc62c0e8

[ "MIT" ]

49

2017-02-05T17:32:18.000Z

2022-01-30T13:20:22.000Z

examples/x01separated/team_and_user/_lazy.py

Danil-Grigorev/swagger-marshmallow-codegen

4c077f6e1ef535bcbdbf1f643f97bc4cbc62c0e8

[ "MIT" ]

62

2016-12-27T15:38:28.000Z

2021-09-30T02:47:00.000Z

examples/x01separated/team_and_user/_lazy.py

Danil-Grigorev/swagger-marshmallow-codegen

4c077f6e1ef535bcbdbf1f643f97bc4cbc62c0e8

[ "MIT" ]

10

2017-07-19T12:38:25.000Z

2020-04-07T09:11:22.000Z

def _useTeam(): from .team import Team return Team def _useUser(): from .user import User return User

13.333333

26

0.65

16

120

4.75

0.5

0

0.283333

120

8

27

15

0.883721

0

1

0.333333

true

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

82a31f6c80f26083638302c6505310e263c7a0ce

1,972

py

Python

fuzzy_grassmann_numbers/fuzzy_number.py

ly3xqhl8g9/fuzzy-grassmann-numbers

d12798df8d633fd1a7b250804334b388b0aa35d7

[ "MIT" ]

null

fuzzy_grassmann_numbers/fuzzy_number.py

ly3xqhl8g9/fuzzy-grassmann-numbers

d12798df8d633fd1a7b250804334b388b0aa35d7

[ "MIT" ]

null

fuzzy_grassmann_numbers/fuzzy_number.py

ly3xqhl8g9/fuzzy-grassmann-numbers

d12798df8d633fd1a7b250804334b388b0aa35d7

[ "MIT" ]

null

class FN(): """Fuzzy Number """ def __init__(self, limits, granularity=0.1): self.lower_limit = limits[0] self.upper_limit = limits[1] self.granularity = granularity def add(self, other): if isinstance(other, FN): newFN = [] newFN.append(self.lower_limit + other.lower_limit) newFN.append(self.upper_limit + other.upper_limit) return FN(newFN) else: print('The number needs to be a Fuzzy Number (FN instance).') def subtract(self, other): if isinstance(other, FN): newFN = [] newFN.append(self.lower_limit - other.lower_limit) newFN.append(self.upper_limit - other.upper_limit) return FN(newFN) else: print('The number needs to be a Fuzzy Number (FN instance).') def multiply(self, other): if isinstance(other, FN): newFN = [] x1 = self.lower_limit x2 = self.upper_limit y1 = other.lower_limit y2 = other.upper_limit calculation = [ x1*y1, x1*y2, x2*y1, x2*y2 ] lower_limit_min = min(calculation) upper_limit_max = max(calculation) newFN.append(lower_limit_min) newFN.append(upper_limit_max) return FN(newFN) def divide(self, other): if isinstance(other, FN): newFN = [] x1 = self.lower_limit x2 = self.upper_limit y1 = other.lower_limit y2 = other.upper_limit calculation = [ x1/y1, x1/y2, x2/y1, x2/y2 ] lower_limit_min = min(calculation) upper_limit_max = max(calculation) newFN.append(lower_limit_min) newFN.append(upper_limit_max) return FN(newFN) def display(self): fn = '[' + str(self.lower_limit) + ', ' + str(self.upper_limit) + ']' return fn

28.57971

77

0.549189

232

1,972

4.49569

0.176724

0.134228

0.080537

0.809204

0

0.021807

0.348884

1,972

68

78

29

0.790498

0.006085

0

0.64

0

0.055441

0

1

0.12

false

0

0.24

0.04

0

null

0

1

0

null

0

6

82a553ab24dbdbd863f0f5b4ea18ab9f0031c0df

27

py

Python

projects/CFPN/cfpn/util/__init__.py

Shamazo/detectron2

ab8c4aa2e0dfa1347bb45b35ba452537f692debe

[ "Apache-2.0" ]

null

projects/CFPN/cfpn/util/__init__.py

Shamazo/detectron2

ab8c4aa2e0dfa1347bb45b35ba452537f692debe

[ "Apache-2.0" ]

null

projects/CFPN/cfpn/util/__init__.py

Shamazo/detectron2

ab8c4aa2e0dfa1347bb45b35ba452537f692debe

[ "Apache-2.0" ]

null

from .util import PatchUtil

27

0.851852

4

27

5.75

1

0

0.111111

27

1

27

0.958333

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

7d9d9ec5dab0e00f89d35b05f6bfa59ccecb1056

1,456

py

Python

src/dataset.py

tungkw/AEVB

89a2cad8b000c681904d18e0021fbc9e5d491b06

[ "MIT" ]

null

src/dataset.py

tungkw/AEVB

89a2cad8b000c681904d18e0021fbc9e5d491b06

[ "MIT" ]

null

src/dataset.py

tungkw/AEVB

89a2cad8b000c681904d18e0021fbc9e5d491b06

[ "MIT" ]

null

import numpy as np import torch from torch.utils.data import Dataset from FreyFaceHelper import FreyFaceHelper from MINSThelper import MINSTHelper class FreyFaceDataset(Dataset): def __init__(self, root_dir, transform=None): self.data = FreyFaceHelper(root_dir).data / 255 self.data_size, h, w = self.data.shape self.sample_dim = h*w self.data = self.data.reshape(self.data_size, self.sample_dim) self.data = torch.from_numpy(self.data).float() self.transform = transform def __len__(self): return self.data_size def __getitem__(self, idx): if torch.is_tensor(idx): idx = idx.tolist() sample = self.data[idx] if self.transform: sample = self.transform(sample) return sample class MINSTDataset(Dataset): def __init__(self, root_dir, transform=None): self.data = MINSTHelper(root_dir).train_images / 255 self.data_size, h, w = self.data.shape self.sample_dim = h*w self.data = self.data.reshape(self.data_size, self.sample_dim) self.data = torch.from_numpy(self.data).float() self.transform = transform def __len__(self): return self.data_size def __getitem__(self, idx): if torch.is_tensor(idx): idx = idx.tolist() sample = self.data[idx] if self.transform: sample = self.transform(sample) return sample

32.355556

70

0.646291

189

1,456

4.751323

0.21164

0.178174

0.080178

0.044543

0.757238

0

0.00554

0.256181

1,456

45

71

32.355556

0.823638

0

0.769231

0

1

0.153846

false

0

0.128205

0.051282

0.435897

0

null

0

1

0

1

0

null

0

6

7db6ead6b9d411021c0fd775e3283bf9cced610d

9,377

py

Python

Utils/DataLoader.py

Felix660/DNNDeepeningPruning

4b61ca19ebf6570fb6210d556fde89910465b691

[ "MIT" ]

1

2021-09-16T21:52:09.000Z

Utils/DataLoader.py

Felix660/DNNDeepeningPruning

4b61ca19ebf6570fb6210d556fde89910465b691

[ "MIT" ]

1

2020-12-29T13:57:40.000Z

2020-12-29T14:11:50.000Z

Utils/DataLoader.py

Felix660/DNNDeepeningPruning

4b61ca19ebf6570fb6210d556fde89910465b691

[ "MIT" ]

1

2021-05-23T14:44:40.000Z

import os import matplotlib.pyplot as plt import pandas from PIL import Image import torch from torchvision import transforms, datasets import numpy as np from sklearn.utils import shuffle from torch.utils.data.sampler import SubsetRandomSampler class ISIC2016(torch.utils.data.Dataset): def __init__(self, df_data, data_dir, transform=None): super().__init__() self.df = df_data self.data_dir = data_dir self.transform = transform def __len__(self): return len(self.df) def __getitem__(self, id): img_name = self.df['image'][id] img_label = self.df['class'][id].astype(float) img_path = os.path.join(self.data_dir, img_name + '.jpg') image = Image.open(img_path) if self.transform is not None: image = self.transform(image) return image, img_label def data_loader(dataset_root_path, dataset_name, batch_size): if dataset_name == "ISIC2016": train_loader, valid_loader, test_loader = load_ISIC2016(dataset_root_path, batch_size) elif dataset_name == "ChestXRay": train_loader, valid_loader, test_loader = load_ChestXRay(dataset_root_path, batch_size) elif dataset_name == "CIFAR10": train_loader, valid_loader, test_loader = load_CIFAR10(dataset_root_path, batch_size) elif dataset_name == "CIFAR100": train_loader, valid_loader, test_loader = load_CIFAR100(dataset_root_path, batch_size) return train_loader, valid_loader, test_loader def load_ISIC2016(dataset_root_path, batch_size): data_path = dataset_root_path + "/ISIC2016/" # Create train dataframe train_df = pandas.read_csv(data_path + "Training_GroundTruth.csv") # Create test dataframe test_df = pandas.read_csv(data_path + "Test_GroundTruth.csv") normalize = transforms.Normalize(mean=[0.72839737, 0.6002146, 0.5401608], std=[0.15253444, 0.17805147, 0.19754663]) transform = transforms.Compose([ transforms.Resize(256), transforms.CenterCrop(size=(224, 224)), transforms.ToTensor(), normalize]) transform_valid = transforms.Compose([ transforms.Resize(256), transforms.CenterCrop(size=(224, 224)), transforms.ToTensor(), normalize]) transform_test = transforms.Compose([ transforms.Resize(256), transforms.CenterCrop(size=(224, 224)), transforms.ToTensor(), normalize]) train_path = data_path + "train_images/" # ISIC 2016 test_path = data_path + "test_images/" train_set = ISIC2016(df_data=train_df, data_dir=train_path, transform=transform) valid_set = ISIC2016(df_data=train_df, data_dir=train_path, transform=transform_valid) test_set = ISIC2016(df_data=test_df, data_dir=test_path, transform=transform_test) dataset_len = len(train_set) indices = list(range(dataset_len)) # Randomly splitting indices: val_len = int(np.floor(0.2 * dataset_len)) validation_idx = np.random.choice(indices, size=val_len, replace=False) train_idx = list(set(indices) - set(validation_idx)) train_sampler = SubsetRandomSampler(train_idx) validation_sampler = SubsetRandomSampler(validation_idx) train_loader = torch.utils.data.DataLoader( dataset=train_set, batch_size=batch_size, sampler=train_sampler, num_workers=4, pin_memory=True) valid_loader = torch.utils.data.DataLoader( dataset=valid_set, batch_size=batch_size, sampler=validation_sampler, num_workers=4, pin_memory=True) test_loader = torch.utils.data.DataLoader( dataset=test_set, batch_size=batch_size, num_workers=4, pin_memory=True) return train_loader, valid_loader, test_loader def load_ChestXRay(dataset_root_path, batch_size): data_path = dataset_root_path + "/chest_xray/" normalize = transforms.Normalize(mean=[0.58450365, 0.58450365, 0.58450365], std=[0.16148868, 0.16148868, 0.16148868]) transform = transforms.Compose([ transforms.Resize(256), transforms.CenterCrop(size=(224, 224)), transforms.ToTensor(), normalize]) transform_valid = transforms.Compose([ #transforms.Grayscale(num_output_channels=1), transforms.Resize(256), transforms.CenterCrop(size=(224, 224)), transforms.ToTensor(), normalize]) transform_test = transforms.Compose([ #transforms.Grayscale(num_output_channels=1), transforms.Resize(256), transforms.CenterCrop(size=(224, 224)), transforms.ToTensor(), normalize]) train_path = data_path + "train/" valid_path = data_path + "val/" test_path = data_path + "test/" train_set = datasets.ImageFolder(root=train_path, transform=transform) test_set = datasets.ImageFolder(root=test_path, transform=transform_test) dataset_len = len(train_set) indices = list(range(dataset_len)) # Randomly splitting indices: val_len = int(np.floor(0.2 * dataset_len)) validation_idx = np.random.choice(indices, size=val_len, replace=False) train_idx = list(set(indices) - set(validation_idx)) train_sampler = SubsetRandomSampler(train_idx) validation_sampler = SubsetRandomSampler(validation_idx) train_loader = torch.utils.data.DataLoader( dataset=train_set, batch_size=batch_size, sampler=train_sampler, num_workers=4, pin_memory=True) valid_loader = torch.utils.data.DataLoader( dataset=train_set, batch_size=batch_size, sampler=validation_sampler, num_workers=4, pin_memory=True) test_loader = torch.utils.data.DataLoader( dataset=test_set, batch_size=batch_size, shuffle=True, num_workers=4, pin_memory=True) return train_loader, valid_loader, test_loader def load_CIFAR10(dataset_root_path, batch_size): data_path = dataset_root_path + "/CIFAR10/" validation_split = 0.2 normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) transform_train = transforms.Compose([ transforms.RandomCrop(32, 4), transforms.RandomHorizontalFlip(), transforms.ToTensor(), normalize]) transform_test = transforms.Compose([ transforms.ToTensor(), normalize]) train_set = datasets.CIFAR10(root=data_path, train=True, transform=transform_train, download=True) test_set = datasets.CIFAR10(root=data_path, train=False, transform=transform_test, download=False) dataset_len = len(train_set) indices = list(range(dataset_len)) # Randomly splitting indices: val_len = int(np.floor(validation_split * dataset_len)) validation_idx = np.random.choice(indices, size=val_len, replace=False) train_idx = list(set(indices) - set(validation_idx)) train_sampler = SubsetRandomSampler(train_idx) validation_sampler = SubsetRandomSampler(validation_idx) train_loader = torch.utils.data.DataLoader( dataset=train_set, batch_size=batch_size, sampler=train_sampler, num_workers=8) validation_loader = torch.utils.data.DataLoader( dataset=train_set, batch_size=batch_size, sampler=validation_sampler, num_workers=8) test_loader = torch.utils.data.DataLoader( dataset=test_set, batch_size=batch_size, num_workers=8) return train_loader, validation_loader, test_loader def load_CIFAR100(dataset_root_path, batch_size): data_path = dataset_root_path + "/CIFAR100/" validation_split = 0.2 normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) transform_train = transforms.Compose([ transforms.RandomCrop(32, 4), transforms.RandomHorizontalFlip(), transforms.ToTensor(), normalize]) transform_test = transforms.Compose([ transforms.ToTensor(), normalize]) train_set = datasets.CIFAR100(root=data_path, train=True, transform=transform_train, download=True) test_set = datasets.CIFAR100(root=data_path, train=False, transform=transform_test, download=False) dataset_len = len(train_set) indices = list(range(dataset_len)) # Randomly splitting indices: val_len = int(np.floor(validation_split * dataset_len)) validation_idx = np.random.choice(indices, size=val_len, replace=False) train_idx = list(set(indices) - set(validation_idx)) train_sampler = SubsetRandomSampler(train_idx) validation_sampler = SubsetRandomSampler(validation_idx) train_loader = torch.utils.data.DataLoader( dataset=train_set, batch_size=batch_size, sampler=train_sampler, num_workers=8) validation_loader = torch.utils.data.DataLoader( dataset=train_set, batch_size=batch_size, sampler=validation_sampler, num_workers=8) test_loader = torch.utils.data.DataLoader( dataset=test_set, batch_size=batch_size, num_workers=8) return train_loader, validation_loader, test_loader

32.113014

103

0.679535

1,117

9,377

5.431513

0.115488

0.048953

0.032306

0.039558

0.82446

0.806494

0.798912

0.755068

0.735784

0.728367

0

0.041415

0.222353

9,377

291

104

32.223368

0.790592

0.027088

0

0.695238

0

0.018766

0.002634

0

1

0.038095

false

0

0.042857

0.004762

0.119048

0

null

0

1

0

null

0

6

81469ecdf098555a759abfa7e1946f053c232186

24

py

Python

lps/lopops/__init__.py

arup-group/london-pop-synth

38e56230d440d49ddb2e2841d46a5cbaab260c35

[ "MIT" ]

1

2020-11-25T06:56:43.000Z

lps/lopops/__init__.py

arup-group/london-pop-synth

38e56230d440d49ddb2e2841d46a5cbaab260c35

[ "MIT" ]

null

lps/lopops/__init__.py

arup-group/london-pop-synth

38e56230d440d49ddb2e2841d46a5cbaab260c35

[ "MIT" ]

null

from .lopops import Data

24

0.833333

4

24

5

1

0

0.125

24

1

24

0.952381

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

81c382c5ef6a696198197dce63fef0ffbc9f9d1c

33

py

Python

new_csaf/csaf/utils/__init__.py

yokian/csaf

a94f0943541a21a270b753577979989b98e84497

[ "BSD-3-Clause" ]

6

2021-08-17T23:31:13.000Z

2022-02-19T22:23:15.000Z

new_csaf/csaf/utils/__init__.py

yokian/csaf

a94f0943541a21a270b753577979989b98e84497

[ "BSD-3-Clause" ]

29

2021-08-24T17:32:39.000Z

2022-02-28T16:28:35.000Z

new_csaf/csaf/utils/__init__.py

yokian/csaf

a94f0943541a21a270b753577979989b98e84497

[ "BSD-3-Clause" ]

3

2021-09-15T14:20:30.000Z

2021-12-06T22:03:26.000Z

from csaf.utils.notebook import *

33

0.818182

5

33

5.4

1

0

0.090909

33

1

33

0.9

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

c4eb7c4a49498abba2aed4de5fc9ac620f9d48cc

69

py

Python

multilingual_t5/r_baseline_mr/__init__.py

sumanthd17/mt5

c99b4e3ad1c69908c852c730a1323ccb52d48f58

[ "Apache-2.0" ]

null

multilingual_t5/r_baseline_mr/__init__.py

sumanthd17/mt5

c99b4e3ad1c69908c852c730a1323ccb52d48f58

[ "Apache-2.0" ]

null

multilingual_t5/r_baseline_mr/__init__.py

sumanthd17/mt5

c99b4e3ad1c69908c852c730a1323ccb52d48f58

[ "Apache-2.0" ]

null

"""r_baseline_mr dataset.""" from .r_baseline_mr import RBaselineMr

17.25

38

0.782609

10

69

5

0.7

0.36

0.44

0

0.101449

69

3

39

23

0.806452

0.318841

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

f20ea3b60a2d1d29b3a9dc8eeaae21beeb5daa22

74

py

Python

train.py

zfar-/icm

0d0c31885a2df264a67eb83442865d3bdcbc0bd1

[ "MIT" ]

null

train.py

zfar-/icm

0d0c31885a2df264a67eb83442865d3bdcbc0bd1

[ "MIT" ]

null

train.py

zfar-/icm

0d0c31885a2df264a67eb83442865d3bdcbc0bd1

[ "MIT" ]

null

import numpy as np import argparse import keras import keras.backend as K

14.8

25

0.824324

13

74

4.692308

0.615385

0.360656

0

0.162162

74

4

26

18.5

0.983871

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

48151af5fce33c9f618af846da873ab27d2b2b07

74

py

Python

python/ql/src/Imports/from_import.py

vadi2/codeql

a806a4f08696d241ab295a286999251b56a6860c

[ "MIT" ]

4,036

2020-04-29T00:09:57.000Z

2022-03-31T14:16:38.000Z

python/ql/src/Imports/from_import.py

vadi2/codeql

a806a4f08696d241ab295a286999251b56a6860c

[ "MIT" ]

2,970

2020-04-28T17:24:18.000Z

2022-03-31T22:40:46.000Z

python/ql/src/Imports/from_import.py

ScriptBox99/github-codeql

2ecf0d3264db8fb4904b2056964da469372a235c

[ "MIT" ]

794

2020-04-29T00:28:25.000Z

2022-03-30T08:21:46.000Z

from sys import stdout def main(): stdout.write("Hello World!")

12.333333

32

0.635135

10

74

4.7

0.9

0

0.243243

74

5

33

14.8

0.839286

0

0.162162

0

1

0.333333

true

0

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

48507852ace8048d3534f8e18fd81bbd9b3b6eb3

7,717

py

Python

utils.py

giova86/Python-LIS

34107bece9f8471a5576b61e3eec4ad4dfce25bf

[ "MIT" ]

1

2021-11-29T08:52:32.000Z

utils.py

giova86/Python-LIS

34107bece9f8471a5576b61e3eec4ad4dfce25bf

[ "MIT" ]

null

utils.py

giova86/Python-LIS

34107bece9f8471a5576b61e3eec4ad4dfce25bf

[ "MIT" ]

null

# methods import cv2 import time import mediapipe as mp import numpy as np import os import numpy as np import pandas as pd mp_holistic = mp.solutions.holistic mp_drawing = mp.solutions.drawing_utils def mediapipe_detection(image, model): image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) image.flags.writeable = False results = model.process(image) image.flags.writeable = True image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR) return image, results def draw_landmarks(image, results): mp_drawing.draw_landmarks(image, results.face_landmarks, mp_holistic.FACEMESH_TESSELATION) mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_holistic.POSE_CONNECTIONS) mp_drawing.draw_landmarks(image, results.left_hand_landmarks, mp_holistic.HAND_CONNECTIONS) mp_drawing.draw_landmarks(image, results.right_hand_landmarks, mp_holistic.HAND_CONNECTIONS) def draw_landmarks_custom(image, results): mp_drawing.draw_landmarks(image, results.face_landmarks, mp_holistic.FACEMESH_TESSELATION, mp_drawing.DrawingSpec(color=(255,255,255),thickness=1, circle_radius=1), mp_drawing.DrawingSpec(color=(255,255,255),thickness=1, circle_radius=1), ) mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_holistic.POSE_CONNECTIONS, mp_drawing.DrawingSpec(color=(80,110,10),thickness=2, circle_radius=1), mp_drawing.DrawingSpec(color=(80,256,121),thickness=2, circle_radius=1), ) mp_drawing.draw_landmarks(image, results.left_hand_landmarks, mp_holistic.HAND_CONNECTIONS, mp_drawing.DrawingSpec(color=(0,0,255),thickness=3, circle_radius=5), mp_drawing.DrawingSpec(color=(0,0,255),thickness=3, circle_radius=5), ) mp_drawing.draw_landmarks(image, results.right_hand_landmarks, mp_holistic.HAND_CONNECTIONS, mp_drawing.DrawingSpec(color=(255,0,0),thickness=3, circle_radius=5), mp_drawing.DrawingSpec(color=(255,0,0),thickness=3, circle_radius=5), ) #cv2.rectangle(image, start_point, end_point, color, thickness) def draw_limit_rh(image, results): if results.right_hand_landmarks: xMax = max([i.x for i in results.right_hand_landmarks.landmark]) xMin = min([i.x for i in results.right_hand_landmarks.landmark]) yMax = max([i.y for i in results.right_hand_landmarks.landmark]) yMin = min([i.y for i in results.right_hand_landmarks.landmark]) xMax=xMax+0.1*(xMax-xMin) yMax=yMax+0.1*(yMax-yMin) xMin=xMin-0.1*(xMax-xMin) yMin=yMin-0.1*(yMax-yMin) h,w,_ = image.shape cv2.rectangle(image, (int(xMin*w), int(yMin*h)), (int(xMax*w), int(yMax*h)), (255,0,0), 1) cv2.line(image, (int(xMin*w), int(yMin*h)), (int(xMin*w), int(yMin*h)+int((yMax*h-yMin*h)/5)), (255,0,0),8) cv2.line(image, (int(xMin*w), int(yMin*h)), (int(xMin*w)+int((xMax*w-xMin*w)/5), int(yMin*h)), (255,0,0),8) cv2.line(image, (int(xMax*w), int(yMax*h)), (int(xMax*w), int(yMax*h)-int((yMax*h-yMin*h)/5)), (255,0,0),8) cv2.line(image, (int(xMax*w), int(yMax*h)), (int(xMax*w)-int((xMax*w-xMin*w)/5), int(yMax*h)), (255,0,0),8) cv2.line(image, (int(xMin*w), int(yMax*h)), (int(xMin*w), int(yMax*h)-int((yMax*h-yMin*h)/5)), (255,0,0),8) cv2.line(image, (int(xMin*w), int(yMax*h)), (int(xMin*w)+int((xMax*w-xMin*w)/5), int(yMax*h)), (255,0,0),8) cv2.line(image, (int(xMax*w), int(yMin*h)), (int(xMax*w), int(yMin*h)+int((yMax*h-yMin*h)/5)), (255,0,0),8) cv2.line(image, (int(xMax*w), int(yMin*h)), (int(xMax*w)-int((xMax*w-xMin*w)/5), int(yMin*h)), (255,0,0),8) cv2.putText(image, 'Right Hand',(int(xMin*w), int(yMin*h-(yMax*h-yMin*h)/20)), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,0,0), 2) def draw_limit_lh(image, results): if results.left_hand_landmarks: xMax = max([i.x for i in results.left_hand_landmarks.landmark]) xMin = min([i.x for i in results.left_hand_landmarks.landmark]) yMax = max([i.y for i in results.left_hand_landmarks.landmark]) yMin = min([i.y for i in results.left_hand_landmarks.landmark]) xMax=xMax+0.1*(xMax-xMin) yMax=yMax+0.1*(yMax-yMin) xMin=xMin-0.1*(xMax-xMin) yMin=yMin-0.1*(yMax-yMin) h,w,_ = image.shape cv2.rectangle(image, (int(xMin*w), int(yMin*h)), (int(xMax*w), int(yMax*h)), (0,0,255), 1) cv2.line(image, (int(xMin*w), int(yMin*h)), (int(xMin*w), int(yMin*h)+int((yMax*h-yMin*h)/5)), (0,0,255),8) cv2.line(image, (int(xMin*w), int(yMin*h)), (int(xMin*w)+int((xMax*w-xMin*w)/5), int(yMin*h)), (0,0,255),8) cv2.line(image, (int(xMax*w), int(yMax*h)), (int(xMax*w), int(yMax*h)-int((yMax*h-yMin*h)/5)), (0,0,255),8) cv2.line(image, (int(xMax*w), int(yMax*h)), (int(xMax*w)-int((xMax*w-xMin*w)/5), int(yMax*h)), (0,0,255),8) cv2.line(image, (int(xMin*w), int(yMax*h)), (int(xMin*w), int(yMax*h)-int((yMax*h-yMin*h)/5)), (0,0,255),8) cv2.line(image, (int(xMin*w), int(yMax*h)), (int(xMin*w)+int((xMax*w-xMin*w)/5), int(yMax*h)), (0,0,255),8) cv2.line(image, (int(xMax*w), int(yMin*h)), (int(xMax*w), int(yMin*h)+int((yMax*h-yMin*h)/5)), (0,0,255),8) cv2.line(image, (int(xMax*w), int(yMin*h)), (int(xMax*w)-int((xMax*w-xMin*w)/5), int(yMin*h)), (0,0,255),8) cv2.putText(image, 'Left Hand',(int(xMin*w), int(yMin*h-(yMax*h-yMin*h)/20)), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255), 2) def check_detection(image, results): if results.left_hand_landmarks: cv2.putText(image, 'Left Hand: DETECTED',(10,30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255), 2) else: cv2.putText(image, 'Left Hand: NOT DETECTED',(10,30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255), 2) if results.right_hand_landmarks: cv2.putText(image, 'Right Hand: DETECTED',(10,70), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,0,0), 2) else: cv2.putText(image, 'Right Hand: NOT DETECTED',(10,70), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,0,0), 2) if results.face_landmarks: cv2.putText(image, 'Face: DETECTED',(10,110), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255), 2) else: cv2.putText(image, 'Face: NOT DETECTED',(10,110), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,255), 2) if results.face_landmarks: cv2.putText(image, 'Pose: DETECTED',(10,150), cv2.FONT_HERSHEY_SIMPLEX, 1, (80,256,121), 2) else: cv2.putText(image, 'Pose: NOT DETECTED',(10,150), cv2.FONT_HERSHEY_SIMPLEX, 1, (80,256,121), 2) def points_detection(results): xMax = max([i.x for i in results.right_hand_landmarks.landmark]) xMin = min([i.x for i in results.right_hand_landmarks.landmark]) yMax = max([i.y for i in results.right_hand_landmarks.landmark]) yMin = min([i.y for i in results.right_hand_landmarks.landmark]) rh = np.array([[points.x, points.y, points.z] for points in results.right_hand_landmarks.landmark]).flatten() if results.right_hand_landmarks else np.zeros(21*3) for i in np.arange(0, 63, 3): rh[i]=(rh[i]-xMin)/(xMax-xMin) for i in np.arange(1, 63, 3): rh[i]=(rh[i]-yMin)/(yMax-yMin) # lh = np.array([[points.x, points.y, points.z] for points in results.left_hand_landmarks.landmark]).flatten() if results.left_hand_landmarks else np.zeros(21*3) # po = np.array([[points.x, points.y, points.z] for points in results.pose_landmarks.landmark]).flatten() if results.pose_landmarks else np.zeros(99) # return np.concatenate([lh, rh, po]) return rh

58.908397

165

0.63859

1,280

7,717

3.738281

0.082813

0.031766

0.043469

0.045977

0.884013

0.819645

0.776385

0.739812

0.724347

0.719122

0

0.062332

0.178826

7,717

130

166

59.361538

0.692757

0.053518

0

0.333333

0

0.023157

0

1

0.064815

false

0

0.064815

0

0.148148

0

null

0

1

0

null

0

6

487e118af55a3a303eee82b7b0325503088c2550

1,261

py

Python

leapy/sklearn/transformers/export/test/test_OneHotEncoderExporter.py

nonabelian/leapy

152152eed87572983dd61b27a4a1726b5cb2e615

[ "BSD-3-Clause" ]

1

2019-05-01T01:59:03.000Z

leapy/sklearn/transformers/export/test/test_OneHotEncoderExporter.py

nonabelian/leapy

152152eed87572983dd61b27a4a1726b5cb2e615

[ "BSD-3-Clause" ]

null

leapy/sklearn/transformers/export/test/test_OneHotEncoderExporter.py

nonabelian/leapy

152152eed87572983dd61b27a4a1726b5cb2e615

[ "BSD-3-Clause" ]

null

import numpy as np import dask.array as da import leapy.sklearn from sklearn.preprocessing import OneHotEncoder from .. import OneHotEncoderExporter def test_ohe_export_function(): ohe = OneHotEncoder() X_np = np.array([['a'], ['b']]) X_act = ohe.fit_transform(X_np) ohe_runtime = OneHotEncoderExporter.to_runtime(ohe) X_exp = ohe_runtime.transform(X_np) # Runtime always outputs np.array assert np.all(X_exp == X_act.toarray()) ohe = OneHotEncoder(sparse=False) X_np = np.array([['a'], ['b']]) X_act = ohe.fit_transform(X_np) ohe_runtime = OneHotEncoderExporter.to_runtime(ohe) X_exp = ohe_runtime.transform(X_np) assert np.all(X_exp == X_act) def test_add_to_class_export(): ohe = OneHotEncoder() X_np = np.array([['a'], ['b']]) X_act = ohe.fit_transform(X_np) ohe_runtime = ohe.to_runtime() X_exp = ohe_runtime.transform(X_np) # Runtime always outputs np.array assert np.all(X_exp == X_act.toarray()) ohe = OneHotEncoder(sparse=False) X_np = np.array([['a'], ['b']]) X = da.from_array(X_np, chunks=X_np.shape) X_act = ohe.fit_transform(X_np) ohe_runtime = ohe.to_runtime() X_exp = ohe_runtime.transform(X_np) assert np.all(X_exp == X_act)

27.413043

55

0.678826

195

1,261

4.112821

0.194872

0.052369

0.119701

0.049875

0.749377

0

0.18636

1,261

45

56

28.022222

0.781676

0.04996

0

0.75

0

0.006695

0

0.125

1

0.0625

false

0

0.15625

0

0.21875

0

null

0

1

0

1

0

null

0

6

6f927ffbdbc204d48c75ded8cf3e18cbd2763925

129

py

Python

environments/simple-road/simple_road/envs/maps.py

KarlRong/Safe-RL-for-Driving

67484911ca8ad9f1476e96043c379c01cd5ced8c

[ "Apache-2.0" ]

null

environments/simple-road/simple_road/envs/maps.py

KarlRong/Safe-RL-for-Driving

67484911ca8ad9f1476e96043c379c01cd5ced8c

[ "Apache-2.0" ]

null

environments/simple-road/simple_road/envs/maps.py

KarlRong/Safe-RL-for-Driving

67484911ca8ad9f1476e96043c379c01cd5ced8c

[ "Apache-2.0" ]

null

class Map: def __init__(self): pass def process(self): pass def render(self, screen): pass

12.9

29

0.527132

15

129

4.266667

0.6

0.25

0.34375

0

0.387597

129

9

30

14.333333

0.810127

0

0.428571

0

1

0.428571

false

0.428571

0

0.571429

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

6f938554d5b661bd603ddbdfb2312be6ee6b1406

20,394

py

Python

mit/6-006-fall-2011/contents/readings/python-cost-model/timing.py

andreramosilva/algorithms

17686a8ab4b2f5935da851464d9493114607211c

[ "MIT" ]

null

mit/6-006-fall-2011/contents/readings/python-cost-model/timing.py

andreramosilva/algorithms

17686a8ab4b2f5935da851464d9493114607211c

[ "MIT" ]

null

mit/6-006-fall-2011/contents/readings/python-cost-model/timing.py

andreramosilva/algorithms

17686a8ab4b2f5935da851464d9493114607211c

[ "MIT" ]

null

# timing.py # Author: Ronald L. Rivest # Date last modified: March 6, 2007 # Routines to help in timing the execution of # various code fragments or routines, and to # infer a good formula for the resulting runtimes. import math import scipy.linalg import string import sys import timeit # Parameter generation routines def lg(x): return math.log(x)/math.log(2.0) def sqrt(x): return math.sqrt(x) def make_param_list(spec_string,growth_factor): """ Generate a list of dictionaries given maximum and minimum values for each range. Each min and max value is a *string* that can be evaluted; each string may depend on earlier variable values Values increment by factor of growth_factor from min to max Example: make_param_list("1<=n<=1000") make_param_list("1<=n<=1000;1<=m<=1000;min(n,m)<=k<=max(n,m)") """ var_list = [] spec_list = string.split(spec_string,";") D = {} D['lg']=lg D['sqrt'] = sqrt D_list = [D] for spec in spec_list: spec_parts = string.split(spec,"<=") assert len(spec_parts)==3 lower_spec = spec_parts[0] var_name = spec_parts[1] assert len(var_name)==1 var_list.append(var_name) upper_spec = spec_parts[2] new_D_list = [] for D in D_list: new_D = D.copy() val = eval(lower_spec,D) while val<=eval(upper_spec,D): new_D[var_name] = val new_D_list.append(new_D.copy()) val *= growth_factor D_list = new_D_list # for D in D_list: print D return (var_list,D_list) # sample("1<=n<=1000;1<=m<=1000;min(n,m)<=k<=max(n,m)",2) def fit(var_list,param_list,run_times,f_list): """ Return matrix A needed for least-squares fit. Given: list of variable names list of sample dicts for various parameter sets list of corresponding run times list of functions to be considered for fit these are *strings*, e.g. "n","n**2","min(n,m)",etc. prints: coefficients for each function in f_list """ print "var_list",var_list print "Function list:",f_list print "run times:", for i in range(len(param_list)): print for v in var_list: print v,"= %6s"%param_list[i][v], print ": %8f"%run_times[i],"microseconds", # print " n = %(n)6s"%param_list[i],run_times[i],"microseconds" print rows = len(run_times) cols = len(f_list) A = [ [0 for j in range(cols)] for i in range(rows) ] for i in range(rows): D = param_list[i] for j in range(cols): A[i][j] = float(eval(f_list[j],D)) b = run_times # print "A:" # print A # print "b:" # print b # (x,resids,rank,s) = scipy.linalg.lstsq(A,b) (x,resids,rank,s) = fit2(A,b) print "Coefficients as interpolated from data:" for j in range(cols): sign = '' if x[j]>0 and j>0: sign="+" elif x[j]>0: sign = " " print "%s%g*%s"%(sign,x[j],f_list[j]) print "(measuring time in microseconds)" print "Sum of squares of residuals:",resids print "RMS error = %0.2g percent"%(math.sqrt(resids/len(A))*100.0) # print "Rank:",rank # print "SVD:",s sys.stdout.flush() import scipy.optimize def fit2(A,b): """ Relative error minimizer """ def f(x): assert len(x) == len(A[0]) resids = [] for i in range(len(A)): sum = 0.0 for j in range(len(A[0])): sum += A[i][j]*x[j] relative_error = (sum-b[i])/b[i] resids.append(relative_error) return resids ans = scipy.optimize.leastsq(f,[0.0]*len(A[0])) # print "ans:",ans if len(A[0])==1: x = [ans[0]] else: x = ans[0] resids = sum([r*r for r in f(x)]) return (x,resids,0,0) def test_misc(): print print "Test Misc-1 -- running time should be n+2*m+7+3*n*lg(n)+17*n*m" spec_string = "1<=n<=100000;1<=m<=100000" growth_factor = 10 print "Spec_string: ",spec_string,"by factors of",growth_factor var_list,param_list = make_param_list(spec_string,growth_factor) run_times = [ eval("n+2*m+7+3*n*lg(n)+17*n*m",D) for D in param_list ] f_list = ("(n*m)","n**2","n*lg(n)","n","m","1") fit(var_list,param_list,run_times,f_list) print print "Test Misc-2: pass" spec_string = "10000<=n<=1000000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("1",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("pass") run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) def test_number(): print print "Test Number-1 -- time to compute int('1'*n)" spec_string = "1000<=n<=10000" growth_factor = 2 print "Spec_string: ",spec_string,"by factors of",growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n**2","n","1") f_list = ("n**2",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("string.atoi(x)","import string;x='1'*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test Number-2 -- time to compute repr(2**n)" spec_string = "1000<=n<=10000" growth_factor = 2 print "Spec_string: ",spec_string,"by factors of",growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n**2","n","1") f_list = ("n**2",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("repr(x)","x=2**%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test Number-3 -- time to convert (2**n) to hex" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string,"by factors of",growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n**2","n","1") f_list = ("n",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("'%x'%x","x=2**%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test Number-4 -- time to add 2**n to itself" spec_string = "1000<=n<=1000000" growth_factor = 2 print "Spec_string: ",spec_string,"by factors of",growth_factor var_list,param_list = make_param_list(spec_string,growth_factor) # f_list = ("n**2","n*lg(n)","n","1") f_list = ("n",) run_times = [] trials = 10000 for D in param_list: t = timeit.Timer("x+x","x=2**%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test Number-5 -- time to multiply (2**n/3) by itself" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string,"by factors of",growth_factor var_list,param_list = make_param_list(spec_string,growth_factor) # f_list = ("n**2","n*lg(n)","n","1") f_list = ("n**1.585",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("x*x","x=(2**%(n)s)/3"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test Number-6 -- time to divide (2**(2n) by (2**n))" spec_string = "1000<=n<=50000" growth_factor = 2 print "Spec_string: ",spec_string,"by factors of",growth_factor var_list,param_list = make_param_list(spec_string,growth_factor) # f_list = ("n**2","n*lg(n)","n","1") f_list = ("n**2",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("w/x","w=(2**(2*%(n)s));x=(2**(%(n)s))"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test Number-7 -- time to compute remainder of (2**(2n) by (2**n))" spec_string = "1000<=n<=50000" growth_factor = 2 print "Spec_string: ",spec_string,"by factors of",growth_factor var_list,param_list = make_param_list(spec_string,growth_factor) # f_list = ("n**2","n*lg(n)","n","1") f_list = ("n**2",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("w%x","w=(2**(2*%(n)s));x=(2**(%(n)s))"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test Number-8 -- time to compute pow(x,y,z)" spec_string = "1000<=n<=5000" growth_factor = 2 print "Spec_string: ",spec_string,"by factors of",growth_factor var_list,param_list = make_param_list(spec_string,growth_factor) # f_list = ("n**2","n*lg(n)","n","1") f_list = ("n**3",) run_times = [] trials = 10 for D in param_list: t = timeit.Timer("pow(x,y,z)","z=(2**%(n)s)+3;x=y=(2**%(n)s)+1"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test Number-9 -- time to compute 2**n" spec_string = "1000<=n<=1000000" growth_factor = 2 print "Spec_string: ",spec_string,"by factors of",growth_factor var_list,param_list = make_param_list(spec_string,growth_factor) # f_list = ("n**2","n*lg(n)","n","1") f_list = ("1",) run_times = [] trials = 10000 for D in param_list: t = timeit.Timer("2**%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) def test_string(): print print "Test String-1: extract a byte from a string" spec_string = "1000<=n<=1000000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("1",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("s[500]","s='0'*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test String-2: concatenate two string of length n" spec_string = "1000<=n<=500000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("s+t","s=t='0'*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test String-3: extract a string of length n/2" spec_string = "1000<=n<=500000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("s[0:%(n)s/2]"%D,"s='0'*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test String-4: translate a string of length n" spec_string = "1000<=n<=500000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("string.translate(s,T)"%D, "s='0'*%(n)s;import string;T=string.maketrans('1','2')"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) def test_list(): print print "Test List-1: create an empty list" spec_string = "1<=n<=10" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("1",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("x = list()") run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test List-2: list (array) lookup" spec_string = "10000<=n<=1000000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("1",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("x=L[5]","L=[0]*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test List-3: appending to a list of length n" spec_string = "10000<=n<=1000000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("1") run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("L.append(0)","L=[0]*%(n)s;L.append(0)"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test List-4: Pop" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("1",) run_times = [] trials = 200 for D in param_list: t = timeit.Timer("L.pop()","L=[0]*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test List-5: concatenating two lists of length n" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n",) run_times = [] trials = 2000 for D in param_list: t = timeit.Timer("L+L","L=[0]*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test List-6: extracting a slice of length n/2" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n",) run_times = [] trials = 2000 for D in param_list: t = timeit.Timer("L[0:%(n)s/2]"%D,"L=[0]*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test List-7: copy" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n",) run_times = [] trials = 2000 for D in param_list: t = timeit.Timer("L[:]","L=[0]*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test List-8: assigning a slice of length n/2" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n",) run_times = [] trials = 2000 for D in param_list: t = timeit.Timer("L[0:%(n)s/2]=L[1:1+%(n)s/2]"%D,"L=[0]*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test List-9: Delete first" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n",) run_times = [] trials = 200 for D in param_list: t = timeit.Timer("del L[0]","L=[0]*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test List-10: Reverse" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n",) run_times = [] trials = 200 for D in param_list: t = timeit.Timer("L.reverse()","L=[0]*%(n)s"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test List-11: Sort" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n*lg(n)",) run_times = [] trials = 200 for D in param_list: t = timeit.Timer("L.sort()","import random;L=[random.random() for i in range(%(n)s)]"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) def test_dict(): print print "Test Dict-1: create an empty dictionary" spec_string = "1<=n<=1" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("1",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("x = dict()") run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test Dict-2: dictionary lookup" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("1",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("x = d[1]", "d = dict([(i,i) for i in range(%(n)s)])"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test Dict-3: dictionary copy" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("d.copy()", "d = dict([(i,i) for i in range(%(n)s)])"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) print print "Test Dict-4: dictionary list items" spec_string = "1000<=n<=100000" growth_factor = 2 print "Spec_string: ",spec_string, "by factors of", growth_factor var_list, param_list = make_param_list(spec_string,growth_factor) # f_list = ("n","1") f_list = ("n*lg(n)",) run_times = [] trials = 1000 for D in param_list: t = timeit.Timer("d.items()", "d = dict([(i,i) for i in range(%(n)s)])"%D) run_times.append(t.timeit(trials)*1e6/float(trials)) fit(var_list,param_list,run_times,f_list) def main(): test_misc() test_number() test_string() test_list() test_dict() if False: import profile profile.run("main()") else: main()

33.432787

96

0.613955

3,261

20,394

3.633241

0.073904

0.097232

0.061783

0.082377

0.76764

0.744345

0.7408

0.737086

0.730672

0.727887

0

0.046102

0.228891

20,394

609

97

33.487685

0.7073

0.058105

0

0.663265

0

0.012245

0.18923

0.016133

0

0.006122

0

null

0.004082

0.020408

null

0.208163

0

null

0

1

0

null

0

1

0

6

6fbb62a06e66044b8b91be8274dd6027c2ea4579

96

py

Python

spikeforest/spikeforest_analysis/sfmdaextractors/__init__.py

mhhennig/spikeforest

5b4507ead724af3de0be5d48a3b23aaedb0be170

[ "Apache-2.0" ]

1

2021-09-23T01:07:19.000Z

spikeforest/spikeforest_analysis/sfmdaextractors/__init__.py

mhhennig/spikeforest

5b4507ead724af3de0be5d48a3b23aaedb0be170

[ "Apache-2.0" ]

null

spikeforest/spikeforest_analysis/sfmdaextractors/__init__.py

mhhennig/spikeforest

5b4507ead724af3de0be5d48a3b23aaedb0be170

[ "Apache-2.0" ]

1

2021-09-23T01:07:21.000Z

from .sfmdaextractors import SFMdaRecordingExtractor, SFMdaSortingExtractor from . import mdaio

32

75

0.875

8

96

10.5

0.75

0

0.09375

96

2

76

48

0.965517

0

1

0

true

0

1

0

1

0

1

0

1

null

0

1

0

null

0

1

0

1

0

1

0

6

6fd41877ed9c63f2e05febb990db5aa1b74f6159

28,873

py

Python

airflow/providers/google/cloud/operators/vertex_ai/endpoint_service.py

JGoldman110/airflow

93e2c945b1be5b7c9700e780d2aa67846503763b

[ "Apache-2.0" ]

1

2020-07-12T19:17:00.000Z

airflow/providers/google/cloud/operators/vertex_ai/endpoint_service.py

JGoldman110/airflow

93e2c945b1be5b7c9700e780d2aa67846503763b

[ "Apache-2.0" ]

null

airflow/providers/google/cloud/operators/vertex_ai/endpoint_service.py

JGoldman110/airflow

93e2c945b1be5b7c9700e780d2aa67846503763b

[ "Apache-2.0" ]

null

# # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. # """This module contains Google Vertex AI operators. .. spelling:: undeployed undeploy Undeploys aiplatform FieldMask unassigns """ from typing import TYPE_CHECKING, Dict, Optional, Sequence, Tuple, Union from google.api_core.exceptions import NotFound from google.api_core.retry import Retry from google.cloud.aiplatform_v1.types import DeployedModel, Endpoint, endpoint_service from google.protobuf.field_mask_pb2 import FieldMask from airflow.models import BaseOperator from airflow.providers.google.cloud.hooks.vertex_ai.endpoint_service import EndpointServiceHook from airflow.providers.google.cloud.links.vertex_ai import ( VertexAIEndpointLink, VertexAIEndpointListLink, VertexAIModelLink, ) if TYPE_CHECKING: from airflow.utils.context import Context class CreateEndpointOperator(BaseOperator): """ Creates an Endpoint. :param project_id: Required. The ID of the Google Cloud project that the service belongs to. :param region: Required. The ID of the Google Cloud region that the service belongs to. :param endpoint: Required. The Endpoint to create. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields = ("region", "project_id", "impersonation_chain") operator_extra_links = (VertexAIEndpointLink(),) def __init__( self, *, region: str, project_id: str, endpoint: Union[Endpoint, Dict], retry: Optional[Retry] = None, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.endpoint = endpoint self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context'): hook = EndpointServiceHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) self.log.info("Creating endpoint") operation = hook.create_endpoint( project_id=self.project_id, region=self.region, endpoint=self.endpoint, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) result = hook.wait_for_operation(timeout=self.timeout, operation=operation) endpoint = Endpoint.to_dict(result) endpoint_id = hook.extract_endpoint_id(endpoint) self.log.info("Endpoint was created. Endpoint ID: %s", endpoint_id) self.xcom_push(context, key="endpoint_id", value=endpoint_id) VertexAIEndpointLink.persist(context=context, task_instance=self, endpoint_id=endpoint_id) return endpoint class DeleteEndpointOperator(BaseOperator): """ Deletes an Endpoint. :param project_id: Required. The ID of the Google Cloud project that the service belongs to. :param region: Required. The ID of the Google Cloud region that the service belongs to. :param endpoint_id: Required. The Endpoint ID to delete. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields = ("region", "endpoint_id", "project_id", "impersonation_chain") def __init__( self, *, region: str, project_id: str, endpoint_id: str, retry: Optional[Retry] = None, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.endpoint_id = endpoint_id self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context'): hook = EndpointServiceHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) try: self.log.info("Deleting endpoint: %s", self.endpoint_id) operation = hook.delete_endpoint( project_id=self.project_id, region=self.region, endpoint=self.endpoint_id, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) hook.wait_for_operation(timeout=self.timeout, operation=operation) self.log.info("Endpoint was deleted.") except NotFound: self.log.info("The Endpoint ID %s does not exist.", self.endpoint_id) class DeployModelOperator(BaseOperator): """ Deploys a Model into this Endpoint, creating a DeployedModel within it. :param project_id: Required. The ID of the Google Cloud project that the service belongs to. :param region: Required. The ID of the Google Cloud region that the service belongs to. :param endpoint_id: Required. The name of the Endpoint resource into which to deploy a Model. Format: ``projects/{project}/locations/{location}/endpoints/{endpoint}`` :param deployed_model: Required. The DeployedModel to be created within the Endpoint. Note that [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split] must be updated for the DeployedModel to start receiving traffic, either as part of this call, or via [EndpointService.UpdateEndpoint][google.cloud.aiplatform.v1.EndpointService.UpdateEndpoint]. :param traffic_split: A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If this field is non-empty, then the Endpoint's [traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split] will be overwritten with it. To refer to the ID of the just being deployed Model, a "0" should be used, and the actual ID of the new DeployedModel will be filled in its place by this method. The traffic percentage values must add up to 100. If this field is empty, then the Endpoint's [traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split] is not updated. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields = ("region", "endpoint_id", "project_id", "impersonation_chain") operator_extra_links = (VertexAIModelLink(),) def __init__( self, *, region: str, project_id: str, endpoint_id: str, deployed_model: Union[DeployedModel, Dict], traffic_split: Optional[Union[Sequence, Dict]] = None, retry: Optional[Retry] = None, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.endpoint_id = endpoint_id self.deployed_model = deployed_model self.traffic_split = traffic_split self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context'): hook = EndpointServiceHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) self.log.info("Deploying model") operation = hook.deploy_model( project_id=self.project_id, region=self.region, endpoint=self.endpoint_id, deployed_model=self.deployed_model, traffic_split=self.traffic_split, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) result = hook.wait_for_operation(timeout=self.timeout, operation=operation) deploy_model = endpoint_service.DeployModelResponse.to_dict(result) deployed_model_id = hook.extract_deployed_model_id(deploy_model) self.log.info("Model was deployed. Deployed Model ID: %s", deployed_model_id) self.xcom_push(context, key="deployed_model_id", value=deployed_model_id) VertexAIModelLink.persist(context=context, task_instance=self, model_id=deployed_model_id) return deploy_model class GetEndpointOperator(BaseOperator): """ Gets an Endpoint. :param project_id: Required. The ID of the Google Cloud project that the service belongs to. :param region: Required. The ID of the Google Cloud region that the service belongs to. :param endpoint_id: Required. The Endpoint ID to get. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields = ("region", "endpoint_id", "project_id", "impersonation_chain") operator_extra_links = (VertexAIEndpointLink(),) def __init__( self, *, region: str, project_id: str, endpoint_id: str, retry: Optional[Retry] = None, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.endpoint_id = endpoint_id self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context'): hook = EndpointServiceHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) try: self.log.info("Get endpoint: %s", self.endpoint_id) endpoint_obj = hook.get_endpoint( project_id=self.project_id, region=self.region, endpoint=self.endpoint_id, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) VertexAIEndpointLink.persist(context=context, task_instance=self, endpoint_id=self.endpoint_id) self.log.info("Endpoint was gotten.") return Endpoint.to_dict(endpoint_obj) except NotFound: self.log.info("The Endpoint ID %s does not exist.", self.endpoint_id) class ListEndpointsOperator(BaseOperator): """ Lists Endpoints in a Location. :param project_id: Required. The ID of the Google Cloud project that the service belongs to. :param region: Required. The ID of the Google Cloud region that the service belongs to. :param filter: The standard list filter. Supported fields: - ``display_name`` supports = and !=. - ``state`` supports = and !=. - ``model_display_name`` supports = and != Some examples of using the filter are: - ``state="JOB_STATE_SUCCEEDED" AND display_name="my_job"`` - ``state="JOB_STATE_RUNNING" OR display_name="my_job"`` - ``NOT display_name="my_job"`` - ``state="JOB_STATE_FAILED"`` :param page_size: The standard list page size. :param page_token: The standard list page token. :param read_mask: Mask specifying which fields to read. :param order_by: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: - ``display_name`` - ``create_time`` - ``update_time`` Example: ``display_name, create_time desc``. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields = ("region", "project_id", "impersonation_chain") operator_extra_links = (VertexAIEndpointListLink(),) def __init__( self, *, region: str, project_id: str, filter: Optional[str] = None, page_size: Optional[int] = None, page_token: Optional[str] = None, read_mask: Optional[str] = None, order_by: Optional[str] = None, retry: Optional[Retry] = None, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.filter = filter self.page_size = page_size self.page_token = page_token self.read_mask = read_mask self.order_by = order_by self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context'): hook = EndpointServiceHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) results = hook.list_endpoints( project_id=self.project_id, region=self.region, filter=self.filter, page_size=self.page_size, page_token=self.page_token, read_mask=self.read_mask, order_by=self.order_by, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) VertexAIEndpointListLink.persist(context=context, task_instance=self) return [Endpoint.to_dict(result) for result in results] class UndeployModelOperator(BaseOperator): """ Undeploys a Model from an Endpoint, removing a DeployedModel from it, and freeing all resources it's using. :param project_id: Required. The ID of the Google Cloud project that the service belongs to. :param region: Required. The ID of the Google Cloud region that the service belongs to. :param endpoint_id: Required. The name of the Endpoint resource from which to undeploy a Model. Format: ``projects/{project}/locations/{location}/endpoints/{endpoint}`` :param deployed_model_id: Required. The ID of the DeployedModel to be undeployed from the Endpoint. :param traffic_split: If this field is provided, then the Endpoint's [traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split] will be overwritten with it. If last DeployedModel is being undeployed from the Endpoint, the [Endpoint.traffic_split] will always end up empty when this call returns. A DeployedModel will be successfully undeployed only if it doesn't have any traffic assigned to it when this method executes, or if this field unassigns any traffic to it. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields = ("region", "endpoint_id", "deployed_model_id", "project_id", "impersonation_chain") def __init__( self, *, region: str, project_id: str, endpoint_id: str, deployed_model_id: str, traffic_split: Optional[Union[Sequence, Dict]] = None, retry: Optional[Retry] = None, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.region = region self.project_id = project_id self.endpoint_id = endpoint_id self.deployed_model_id = deployed_model_id self.traffic_split = traffic_split self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context'): hook = EndpointServiceHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) self.log.info(f"Removing a DeployedModel {self.deployed_model_id}") operation = hook.undeploy_model( project_id=self.project_id, region=self.region, endpoint=self.endpoint_id, deployed_model_id=self.deployed_model_id, traffic_split=self.traffic_split, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) hook.wait_for_operation(timeout=self.timeout, operation=operation) self.log.info("DeployedModel was removed successfully") class UpdateEndpointOperator(BaseOperator): """ Updates an Endpoint. :param project_id: Required. The ID of the Google Cloud project that the service belongs to. :param region: Required. The ID of the Google Cloud region that the service belongs to. :param endpoint_id: Required. The ID of the Endpoint to update. :param endpoint: Required. The Endpoint which replaces the resource on the server. :param update_mask: Required. The update mask applies to the resource. See [google.protobuf.FieldMask][google.protobuf.FieldMask]. :param retry: Designation of what errors, if any, should be retried. :param timeout: The timeout for this request. :param metadata: Strings which should be sent along with the request as metadata. :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :param delegate_to: The account to impersonate using domain-wide delegation of authority, if any. For this to work, the service account making the request must have domain-wide delegation enabled. :param impersonation_chain: Optional service account to impersonate using short-term credentials, or chained list of accounts required to get the access_token of the last account in the list, which will be impersonated in the request. If set as a string, the account must grant the originating account the Service Account Token Creator IAM role. If set as a sequence, the identities from the list must grant Service Account Token Creator IAM role to the directly preceding identity, with first account from the list granting this role to the originating account (templated). """ template_fields = ("region", "endpoint_id", "project_id", "impersonation_chain") operator_extra_links = (VertexAIEndpointLink(),) def __init__( self, *, project_id: str, region: str, endpoint_id: str, endpoint: Union[Endpoint, Dict], update_mask: Union[FieldMask, Dict], retry: Optional[Retry] = None, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = (), gcp_conn_id: str = "google_cloud_default", delegate_to: Optional[str] = None, impersonation_chain: Optional[Union[str, Sequence[str]]] = None, **kwargs, ) -> None: super().__init__(**kwargs) self.project_id = project_id self.region = region self.endpoint_id = endpoint_id self.endpoint = endpoint self.update_mask = update_mask self.retry = retry self.timeout = timeout self.metadata = metadata self.gcp_conn_id = gcp_conn_id self.delegate_to = delegate_to self.impersonation_chain = impersonation_chain def execute(self, context: 'Context'): hook = EndpointServiceHook( gcp_conn_id=self.gcp_conn_id, delegate_to=self.delegate_to, impersonation_chain=self.impersonation_chain, ) self.log.info("Updating endpoint: %s", self.endpoint_id) result = hook.update_endpoint( project_id=self.project_id, region=self.region, endpoint_id=self.endpoint_id, endpoint=self.endpoint, update_mask=self.update_mask, retry=self.retry, timeout=self.timeout, metadata=self.metadata, ) self.log.info("Endpoint was updated") VertexAIEndpointLink.persist(context=context, task_instance=self, endpoint_id=self.endpoint_id) return Endpoint.to_dict(result)

44.557099

108

0.67932

3,649

28,873

5.233489

0.09345

0.027229

0.019794

0.008902

0.766298

0.742944

0.730272

0.727235

0.723569

0.711735

0

0.000692

0.248952

28,873

647

109

44.625966

0.879963

0.461227

0

0.73842

0

0.062267

0.001628

0

1

0.038147

false

0

0.024523

0

0.128065

0

null

0

1

0

1

0

null

0

6

6fe15b7cf8e415e0865f7afbe112b4eb21eebb90

38

py

Python

vnpy/app/chart_wizard/ui/__init__.py

funrunskypalace/vnpy

2d87aede685fa46278d8d3392432cc127b797926

[ "MIT" ]

248

2020-12-12T02:18:27.000Z

2022-03-28T05:27:06.000Z

vnpy/app/chart_wizard/ui/__init__.py

funrunskypalace/vnpy

2d87aede685fa46278d8d3392432cc127b797926

[ "MIT" ]

6

2020-12-22T10:49:09.000Z

2021-06-15T11:31:12.000Z

vnpy/app/chart_wizard/ui/__init__.py

funrunskypalace/vnpy

2d87aede685fa46278d8d3392432cc127b797926

[ "MIT" ]

140

2020-12-17T15:02:57.000Z

2022-03-28T05:27:07.000Z

from .widget import ChartWizardWidget

19

37

0.868421

4

38

8.25

1

0

0.105263

38

1

38

0.970588

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

82ed3d6ade8741f05add09ea887fda894aeac9d3

69

py

Python

src/resources/baserouter.py

solnsumei/claims-management

0a9db243e954fbe390f6f81f64eabd6efa4dcc81

[ "MIT" ]

null

src/resources/baserouter.py

solnsumei/claims-management

0a9db243e954fbe390f6f81f64eabd6efa4dcc81

[ "MIT" ]

null

src/resources/baserouter.py

solnsumei/claims-management

0a9db243e954fbe390f6f81f64eabd6efa4dcc81

[ "MIT" ]

null

from fastapi import APIRouter class BaseRouter(APIRouter): pass

13.8

29

0.782609

8

69

6.75

0.875

0

0.173913

69

5

30

13.8

0.947368

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

82f0e4bfac09fb4807970339774d3f576a742113

292

py

Python

engine/subsystems/physics_engine.py

Dogeek/game_engine

bf020e436352a02d34e17981b2b4950374d938c0

[ "MIT" ]

1

2019-08-21T12:40:19.000Z

engine/subsystems/physics_engine.py

Dogeek/game_engine

bf020e436352a02d34e17981b2b4950374d938c0

[ "MIT" ]

null

engine/subsystems/physics_engine.py

Dogeek/game_engine

bf020e436352a02d34e17981b2b4950374d938c0

[ "MIT" ]

null

class PhysicsEngine: def __init__(self, game_manager): self.game_manager = game_manager def iterate(self): for go in self.game_manager.game_objects: if go.has_component("Rigidbody2D"): go.get_component("Rigidbody2D").update() pass

29.2

56

0.636986

34

292

5.147059

0.558824

0.251429

0.257143

0.217143

0

0.00939

0.270548

292

9

57

32.444444

0.812207

0

0.075342

0

1

0.25

false

0.125

0

0.375

0

null

1

0

1

0

null

0

1

0

1

0

6

82f6c1fd32328a04cb8cda594a02e17100d05dec

41

py

Python

atcoder/abc/b069.py

tomato-300yen/coding

db6f440a96d8c83f486005c650461a69f27e3926

[ "MIT" ]

null

atcoder/abc/b069.py

tomato-300yen/coding

db6f440a96d8c83f486005c650461a69f27e3926

[ "MIT" ]

null

atcoder/abc/b069.py

tomato-300yen/coding

db6f440a96d8c83f486005c650461a69f27e3926

[ "MIT" ]

null

a, *b, c = input() print(a + len(b) + c)

13.666667

21

0.463415

9

41

2.111111

0.666667

0.210526

0

0.243902

41

2

22

20.5

0.612903

0

1

0

true

0

0.5

1

0

null

1

0

1

0

null

0

1

0

1

0

6

d21093528b1cab2d951cda2026142bc1ca7cc150

47

py

Python

speaker_model/__init__.py

happylittlecat2333/FastSpeech2

55efb879db0d7458f97d79fa605c889b2df8321f

[ "MIT" ]

null

speaker_model/__init__.py

happylittlecat2333/FastSpeech2

55efb879db0d7458f97d79fa605c889b2df8321f

[ "MIT" ]

null

speaker_model/__init__.py

happylittlecat2333/FastSpeech2

55efb879db0d7458f97d79fa605c889b2df8321f

[ "MIT" ]

null

from .speaker_embedding import SpeakerEmbedding

47

0.914894

5

47

8.4

1

0

0.06383

47

1

47

0.954545

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

9629930a848cf9da1831deaff00c3cf1cb8ee5e1

102

py

Python

app/main/__init__.py

Jamesmwangi245/Blogg

e76d8049867a9f3bc1da5a824eca76d53da8f17b

[ "MIT" ]

null

app/main/__init__.py

Jamesmwangi245/Blogg

e76d8049867a9f3bc1da5a824eca76d53da8f17b

[ "MIT" ]

null

app/main/__init__.py

Jamesmwangi245/Blogg

e76d8049867a9f3bc1da5a824eca76d53da8f17b

[ "MIT" ]

null

from flask import Blueprint from .. import views main = Blueprint('main',__name__) from .import erro

17

33

0.764706

14

102

5.285714

0.571429

0.27027

0

0.147059

102

6

34

17

0.850575

0

0.038835

0

1

0

false

0

0.75

0

0.75

0.5

1

0

null

1

0

1

0

null

0

1

0

1

0

6

963ea0a36bb5dc4a9d8195199b093cc7b1855ee3

105

py

Python

SurPyval/node/__init__.py

JakeColtman/SurPyval

71ab77231ba39eccba165088689282b247c015f2

[ "MIT" ]

2

2018-02-17T23:40:46.000Z

2021-03-08T20:08:50.000Z

SurPyval/node/__init__.py

JakeColtman/SurPyval

71ab77231ba39eccba165088689282b247c015f2

[ "MIT" ]

null

SurPyval/node/__init__.py

JakeColtman/SurPyval

71ab77231ba39eccba165088689282b247c015f2

[ "MIT" ]

null

from SurPyval.node.node import Node, gamma, exponential, gaussian from SurPyval.node.tree import NodeTree

52.5

65

0.838095

15

105

5.866667

0.6

0.272727

0.363636

0

0.095238

105

2

66

52.5

0.926316

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

9667429642b836e495719f4d97dbd5c90ef1ccd4

26

py

Python

dask_cudf/io/__init__.py

quasiben/dask-cudf

79671a9b0d1ea20e9c37fdba257f95a128ea98e5

[ "Apache-2.0" ]

null

dask_cudf/io/__init__.py

quasiben/dask-cudf

79671a9b0d1ea20e9c37fdba257f95a128ea98e5

[ "Apache-2.0" ]

null

dask_cudf/io/__init__.py

quasiben/dask-cudf

79671a9b0d1ea20e9c37fdba257f95a128ea98e5

[ "Apache-2.0" ]

null

from .csv import read_csv

13

25

0.807692

5

26

4

0.8

0

0.153846

26

1

26

0.909091

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

969019b72493c2417b51ae3664eb18a321edea17

178

py

Python

alternatives/server-flask/src/common/utils/__init__.py

TaitoUnited/full-stack-template

58529515c2f3dd765074b4c5f326f6336646f4e7

[ "MIT" ]

21

2019-10-12T06:04:43.000Z

2022-03-31T06:03:34.000Z

alternatives/server-flask/src/common/utils/__init__.py

TaitoUnited/server-template

67f370f212adefd96da2404077e575764f6a1b11

[ "MIT" ]

64

2018-04-22T09:39:19.000Z

2019-06-14T12:32:08.000Z

alternatives/server-flask/src/common/utils/__init__.py

TaitoUnited/full-stack-template

58529515c2f3dd765074b4c5f326f6336646f4e7

[ "MIT" ]

4

2019-11-03T22:47:56.000Z

2022-01-09T11:52:15.000Z

from . import database # noqa from . import format # noqa from . import misc # noqa from . import powerbi # noqa from . import storage # noqa from . import validate # noqa

25.428571

30

0.696629

24

178

5.166667

0.375

0.483871

0.564516

0

0.235955

178

6

31

29.666667

0.911765

0.162921

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

96b8de7cdf71843e7fe6a35670ef3afb9b5dd2ab

148

py

Python

Planet_tools/__init__.py

tundeakins/Planet_parameter_conversions

7d7c4eb7f6e6fcf6e31979cfa72aa414a5f9e760

[ "MIT" ]

null

Planet_tools/__init__.py

tundeakins/Planet_parameter_conversions

7d7c4eb7f6e6fcf6e31979cfa72aa414a5f9e760

[ "MIT" ]

null

Planet_tools/__init__.py

tundeakins/Planet_parameter_conversions

7d7c4eb7f6e6fcf6e31979cfa72aa414a5f9e760

[ "MIT" ]

null

from Planet_tools import convert_param, calculate_param, some_stats, estimate_effect, utils, ring from Planet_tools.__version__ import __version__

49.333333

97

0.864865

20

148

5.7

0.7

0.175439

0.263158

0

0.094595

148

2

98

74

0.850746

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

96bcaf471d55f0f506530f804b1e8575c6f46825

96

py

Python

venv/lib/python3.8/site-packages/platformdirs/macos.py

Retraces/UkraineBot

3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71

[ "MIT" ]

2

2022-03-13T01:58:52.000Z

2022-03-31T06:07:54.000Z

venv/lib/python3.8/site-packages/platformdirs/macos.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

19

2021-11-20T04:09:18.000Z

2022-03-23T15:05:55.000Z

venv/lib/python3.8/site-packages/platformdirs/macos.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

null

/home/runner/.cache/pip/pool/bc/8a/30/3d82a41e4b09716563a874286bea08d62d83d12ee0b127721736432440

96

0.895833

9

96

9.555556

1

0

0.489583

0

96

1

96

0.40625

0

1

0

null

0

null

0

1

0

null

0

1

0

1

0

1

0

null

1

0

1

0

6

96c2b9f478794a95ae0c4c748f0db978967cf61b

6,149

py

Python

tests/test_utils.py

tecknicaltom/smoketest

07cf553508f924ba620cb8b397d9226283e32499

[ "MIT" ]

null

tests/test_utils.py

tecknicaltom/smoketest

07cf553508f924ba620cb8b397d9226283e32499

[ "MIT" ]

null

tests/test_utils.py

tecknicaltom/smoketest

07cf553508f924ba620cb8b397d9226283e32499

[ "MIT" ]

null

import unittest class TestUtilities(unittest.TestCase): def test_chunkify(self): from smoketest.utils import chunkify # ordinary case where 2 < n < len(seq) self.assertEqual( chunkify(list(range(10)), 3), [[0, 1, 2, ], [3, 4, 5, ], [6, 7, 8, 9, ]] ) # n = 1 case self.assertEqual( chunkify(list(range(10)), 1), [list(range(10))], ) # n == len(seq) case self.assertEqual( chunkify(list(range(10)), 10), list(map(lambda x: [x], range(10))), ) # n > len(seq) case self.assertEqual( chunkify(list(range(1)), 2), [[], [0]], ) def test_uncachebust_no_cachebuster(self): from smoketest.utils import uncachebust expected = 'usnews.com?b=2&a=1&c=' actual = uncachebust('usnews.com?b=2&a=1&c=') self.assertEqual(expected, actual) def test_uncachebust_with_cachebuster(self): from smoketest.utils import uncachebust expected = 'usnews.com?b=2&a=1&c=' actual = uncachebust('usnews.com?_=123&b=2&a=1&c=') self.assertEqual(expected, actual) class TestTransformUrlBasedOnOptions(unittest.TestCase): def test_cachebusting(self): from smoketest.utils import transform_url_based_on_options from collections import namedtuple import re Options = namedtuple('Options', ('scheme', 'level', 'port', 'cachebust')) url = 'http://www.usnews.com' cachebust_pattern = re.compile(r'\?_=\d+$') options = Options(None, 'stag', None, True) transformed = transform_url_based_on_options(url, options) self.assertTrue(cachebust_pattern.search(transformed)) options = Options(None, 'stag', None, False) transformed = transform_url_based_on_options(url, options) self.assertFalse(cachebust_pattern.search(transformed)) def test_level(self): from smoketest.utils import transform_url_based_on_options from collections import namedtuple Options = namedtuple('Options', ('scheme', 'level', 'port', 'cachebust')) url = 'http://www.usnews.com' options = Options(None, 'live', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, url) options = Options(None, 'stag', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://www-stag.usnews.com') def test_custom_level(self): from smoketest.utils import transform_url_based_on_options from collections import namedtuple Options = namedtuple('Options', ('scheme', 'level', 'port', 'cachebust')) url = 'http://www-{LEVEL}.usnews.com' options = Options(None, 'live', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://www.usnews.com') options = Options(None, 'stag', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://www-stag.usnews.com') url = 'http://{LEVEL}.usnews.com' options = Options(None, 'live', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://usnews.com') options = Options(None, 'stag', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://stag.usnews.com') url = 'http://{LEVEL}-www.usnews.com' options = Options(None, 'live', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://www.usnews.com') options = Options(None, 'stag', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://stag-www.usnews.com') url = 'http://www.usnews.com/{LEVEL}/' options = Options(None, 'live', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://www.usnews.com/') options = Options(None, 'stag', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://www.usnews.com/stag/') url = 'http://www.usnews{LEVEL}.com' options = Options(None, '-staging', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://www.usnews-staging.com') options = Options(None, '', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://www.usnews.com') def test_port(self): from smoketest.utils import transform_url_based_on_options from collections import namedtuple Options = namedtuple('Options', ('scheme', 'level', 'port', 'cachebust')) url = 'http://www.usnews.com' options = Options(None, 'live', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, url) options = Options(None, 'live', 8999, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'http://www.usnews.com:8999') def test_scheme(self): from smoketest.utils import transform_url_based_on_options from collections import namedtuple Options = namedtuple('Options', ('scheme', 'level', 'port', 'cachebust')) url = 'http://www.usnews.com' options = Options('https', 'live', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'https://www.usnews.com') options = Options('https', 'stag', None, False) transformed = transform_url_based_on_options(url, options) self.assertEqual(transformed, 'https://www-stag.usnews.com')

38.672956

81

0.642056

704

6,149

5.451705

0.113636

0.058624

0.101876

0.113861

0.858781

0.83976

0.815008

0.804586

0.77358

0

0.010118

0.228492

6,149

158

82

38.917722

0.798904

0.013661

0

0.568966

0

0.14736

0.014851

0

0.206897

1

0.068966

false

0

0.12931

0

0.215517

0

null

0

1

0

null

0

6

738fc1eaed3425e3780ab78109c895bf32037744

17,803

py

Python

unirep_models.py

Tessier-Lab-UMich/Emi_Pareto_Opt_ML

0ed9ea241ad154de86acce0bdc63586ce66d99fa

[ "MIT" ]

null

unirep_models.py

Tessier-Lab-UMich/Emi_Pareto_Opt_ML

0ed9ea241ad154de86acce0bdc63586ce66d99fa

[ "MIT" ]

null

unirep_models.py

Tessier-Lab-UMich/Emi_Pareto_Opt_ML

0ed9ea241ad154de86acce0bdc63586ce66d99fa

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Sun Sep 12 13:13:21 2021 @author: makow """ from holdout_utils import * emi_binding = pd.read_csv("emi_binding.csv", header = 0, index_col = 0) iso_binding = pd.read_csv("iso_binding.csv", header = 0, index_col = 0) igg_binding = pd.read_csv("igg_binding.csv", header = 0, index_col = 0) emi_reps = pd.read_csv("emi_reps.csv", header = 0, index_col = 0) iso_reps = pd.read_csv("iso_reps.csv", header = 0, index_col = 0) igg_reps = pd.read_csv("igg_reps.csv", header = 0, index_col = 0) #%% lda_ant = LDA() cv_results = cv(lda_ant, emi_reps, emi_binding.iloc[:,0]) print('Antigen model cross validation average test accuracy: ' + str(np.mean(cv_results['test_score']))) emi_ant_transform = pd.DataFrame(lda_ant.fit_transform(emi_reps, emi_binding.iloc[:,0])).set_index(emi_binding.index) emi_ant_predict = pd.DataFrame(lda_ant.predict(emi_reps)).set_index(emi_binding.index) print('Antigen model accuracy: ' + str(accuracy_score(emi_ant_predict.iloc[:,0], emi_binding.iloc[:,0]))) iso_ant_transform = pd.DataFrame(lda_ant.transform(iso_reps)).set_index(iso_binding.index) iso_ant_predict = pd.DataFrame(lda_ant.predict(iso_reps)).set_index(iso_binding.index) igg_ant_transform = pd.DataFrame(lda_ant.transform(igg_reps)).set_index(igg_binding.index) lda_psy = LDA() cv_results = cv(lda_psy, emi_reps, emi_binding.iloc[:,1]) print('Specificity model cross validation average test accuracy: ' + str(np.mean(cv_results['test_score']))) emi_psy_transform = pd.DataFrame(lda_psy.fit_transform(emi_reps, emi_binding.iloc[:,1])).set_index(emi_binding.index) emi_psy_predict = pd.DataFrame(lda_psy.predict(emi_reps)).set_index(emi_binding.index) print('Specificity model accuracy: ' + str(accuracy_score(emi_psy_predict.iloc[:,0], emi_binding.iloc[:,1]))) iso_psy_transform = pd.DataFrame(lda_psy.transform(iso_reps)).set_index(iso_binding.index) iso_psy_predict = pd.DataFrame(lda_psy.predict(iso_reps)).set_index(iso_binding.index) igg_psy_transform = pd.DataFrame(lda_psy.transform(igg_reps)).set_index(igg_binding.index) #%% """ # sample size elbow plot emi_data = pd.concat([emi_binding, emi_reps.set_index(emi_binding.index)], axis = 1) ant_test_acc = [] psy_test_acc = [] for i in np.arange(25,4000,25): emi_data_subset = emi_data.sample(i) emi_data_subset_train, emi_data_subset_test, emi_data_subset_target_train, emi_data_subset_target_test = train_test_split(emi_data_subset.iloc[:,3:8000], emi_data_subset.iloc[:,0:3]) cv_results = cv(lda_ant, emi_data_subset.iloc[:,3:8000], emi_data_subset.iloc[:,0]) ant_test_acc.append(np.mean(cv_results['test_score'])) cv_results = cv(lda_psy, emi_data_subset.iloc[:,3:8000], emi_data_subset.iloc[:,1]) psy_test_acc.append(np.mean(cv_results['test_score'])) #%% plt.scatter(np.arange(25,4000,25), ant_test_acc, c = 'blue', edgecolor = 'k', linewidth = 0.25, s = 50) plt.scatter(np.arange(25,4000,25), psy_test_acc, c = 'red', edgecolor = 'k', linewidth = 0.25, s = 50) plt.xticks([0,1000,2000,3000,4000], fontsize = 24) plt.yticks([0.5, 0.6, 0.7,0.8, 0.9, 1.0], [50, 60, 70, 80, 90, 100], fontsize = 24) #%% #KNN of sequences from sklearn.neighbors import KNeighborsClassifier as KNC emi_data = pd.concat([emi_binding, emi_reps.set_index(emi_binding.index)], axis = 1) ant_predict_acc = [] psy_predict_acc = [] for j in np.arange(1,25): knc = KNC(n_neighbors = j) cv_results = cv(knc, emi_data.iloc[:,3:8000], emi_data.iloc[:,0]) ant_predict_acc.append(np.mean(cv_results['test_score'])) cv_results = cv(knc, emi_data.iloc[:,3:8000], emi_data.iloc[:,1]) psy_predict_acc.append(np.mean(cv_results['test_score'])) #%% plt.scatter(np.arange(1,25), ant_predict_acc, c = 'blue', edgecolor = 'k', linewidth = 0.25, s = 50) plt.scatter(np.arange(1,25), psy_predict_acc, c = 'red', edgecolor = 'k', linewidth = 0.25, s = 50) plt.xticks(fontsize = 24) plt.yticks([0.8, 0.9, 1.0], [80, 90, 100], fontsize = 24) """ #%% #model accuracy distributions plt.figure() sns.distplot(emi_ant_transform.loc[emi_binding['ANT Binding'] == 0, 0], color = 'red') sns.distplot(emi_ant_transform.loc[emi_binding['ANT Binding'] == 1, 0], color = 'blue') plt.xticks([-4, -2, 0, 2, 4], [-4, -2, 0, 2, 4], fontsize = 26) plt.yticks([0.0, 0.2, 0.4, 0.6], [0.0, 0.2, 0.4, 0.6], fontsize = 26) plt.ylabel('') plt.xlim(-5,5) plt.figure() sns.distplot(emi_psy_transform.loc[emi_binding['OVA Binding'] == 0, 0], color = 'blue') sns.distplot(emi_psy_transform.loc[emi_binding['OVA Binding'] == 1, 0], color = 'red') plt.xticks([-4, -2, 0, 2, 4], [-4, -2, 0, 2, 4], fontsize = 26) plt.yticks([0.0, 0.2, 0.4, 0.6], [0.0, 0.2, 0.4, 0.6], fontsize = 26) plt.ylabel('') #%% #yeast data correlations plt.figure() plt.scatter(iso_ant_transform.iloc[:,0], iso_binding.iloc[:,1], c = iso_ant_predict.iloc[:,0], cmap = cmap9r, s = 150, edgecolor = 'k', linewidth = 0.25) plt.scatter(iso_ant_transform.iloc[125,0], iso_binding.iloc[125,1], c = 'k', s = 250, edgecolor = 'k', linewidth = 0.25) plt.xticks([-4, -2, 0, 2, 4], [-4, -2, 0, 2, 4], fontsize = 26) plt.yticks([0.0, 0.4, 0.8, 1.2, 1.6], [0.0, 0.4, 0.8, 1.2, 1.6], fontsize = 26) plt.ylim(-0.15, 1.85) print('Antigen model scFab correlation: ' + str(sc.stats.spearmanr(iso_ant_transform.iloc[:,0], iso_binding.iloc[:,1]))) plt.figure() plt.scatter(iso_psy_transform.iloc[:,0], iso_binding.iloc[:,2], c = iso_psy_predict.iloc[:,0], cmap = cmap9, s = 150, edgecolor = 'k', linewidth = 0.25) plt.scatter(iso_psy_transform.iloc[125,0], iso_binding.iloc[125,2], c = 'k', s = 250, edgecolor = 'k', linewidth = 0.25) plt.xticks([-4, -2, 0, 2, 4], [-4, -2, 0, 2, 4], fontsize = 26) plt.yticks([0.0, 0.4, 0.8, 1.2, 1.6], [0.0, 0.4, 0.8, 1.2, 1.6], fontsize = 26) plt.ylim(-0.15, 1.85) print('Specificity model scFab correlation: ' + str(sc.stats.spearmanr(iso_psy_transform.iloc[:,0], iso_binding.iloc[:,2]))) #%% #pareto plots plt.figure() plt.scatter(emi_ant_transform, emi_psy_transform, color = 'white', edgecolor = 'k', s = 40, linewidth = 0.25) plt.scatter(igg_ant_transform.iloc[0:41,0], igg_psy_transform.iloc[0:41,0], color = cmap(0.15), edgecolor= 'k', s = 80, linewidth = 0.25) plt.scatter(igg_ant_transform.iloc[41:42,0], igg_psy_transform.iloc[41:42,0], color = 'black', s = 150, edgecolor= 'k', linewidth = 0.25) plt.xticks([-6, -4, -2, 0, 2, 4, 6], [-6, -4, -2, 0, 2, 4, 6], fontsize = 26) plt.yticks([-6, -4, -2, 0, 2, 4, 6], [-6, -4, -2, 0, 2, 4, 6], fontsize = 26) plt.ylabel('') #print(len(emi_ant_transform)) plt.figure() plt.scatter(emi_ant_transform, emi_psy_transform, color = 'white', edgecolor = 'k', s = 40, linewidth = 0.25) plt.scatter(igg_ant_transform.loc[igg_binding['Blosum62'] == 1,0], igg_psy_transform.loc[igg_binding['Blosum62'] == 1,0], color = cmap(0.15), edgecolor= 'k', s = 80, linewidth = 0.25) plt.scatter(igg_ant_transform.iloc[41:42,0], igg_psy_transform.iloc[41:42,0], color = 'black', s = 150, edgecolor= 'k', linewidth = 0.25) plt.scatter(igg_ant_transform.iloc[8,0], igg_psy_transform.iloc[8,0], c = 'orange', s = 150, edgecolor = 'k', linewidth = 0.25, zorder = 3) plt.xticks([-6, -4, -2, 0, 2, 4, 6], [-6, -4, -2, 0, 2, 4, 6], fontsize = 26) plt.yticks([-6, -4, -2, 0, 2, 4, 6], [-6, -4, -2, 0, 2, 4, 6], fontsize = 26) plt.ylabel('') #%% #in-library IgG correlations plt.figure() plt.errorbar(igg_ant_transform.iloc[0:41,0], igg_binding.iloc[0:41,1], yerr = igg_binding.iloc[0:41,3], linewidth = 0, elinewidth = 0.5, ecolor = 'k', capsize = 3, zorder = 1) plt.scatter(igg_ant_transform.iloc[0:41,0], igg_binding.iloc[0:41,1], c = cmap(0.15), s = 150, edgecolor = 'k', linewidth = 0.25, zorder = 2) plt.scatter(igg_ant_transform.iloc[41:42,0], 1, color = 'k', s = 250, edgecolor= 'k', linewidth = 0.25, zorder = 3) plt.xticks([1, 2, 3], [1, 2, 3], fontsize = 26) plt.yticks([0.0, 0.4, 0.8, 1.2, 1.6], [0.0, 0.4, 0.8, 1.2, 1.6], fontsize = 26) plt.ylim(-0.05, 1.65) print('Antigen model in-library IgG correlation: ' + str(sc.stats.spearmanr(igg_ant_transform.iloc[0:42,0], igg_binding.iloc[0:42,1]))) plt.figure() plt.errorbar(igg_psy_transform.iloc[0:41,0], igg_binding.iloc[0:41,2], yerr = igg_binding.iloc[0:41,4], linewidth = 0, elinewidth = 0.5, ecolor = 'k', capsize = 3, zorder = 1) plt.scatter(igg_psy_transform.iloc[0:41,0], igg_binding.iloc[0:41,2], c = cmap(0.85), s = 150, edgecolor = 'k', linewidth = 0.25, zorder = 2) plt.scatter(igg_psy_transform.iloc[41:42,0], 1, color = 'k', s = 250, edgecolor= 'k', linewidth = 0.25) plt.xticks([0,1, 2, 3], [0,1, 2, 3], fontsize = 26) plt.yticks([0.0, 0.4, 0.8, 1.2], [0.0, 0.4, 0.8, 1.2], fontsize = 26) plt.ylim(-0.15, 1.45) print('Specificity model in-library IgG correlation: ' + str(sc.stats.spearmanr(igg_psy_transform.iloc[0:42,0], igg_binding.iloc[0:42,2]))) #%% #experimental pareto plt.figure() plt.errorbar(igg_binding.iloc[0:41,1], igg_binding.iloc[0:41,2], xerr = igg_binding.iloc[0:41,3], yerr = igg_binding.iloc[0:41,4], linewidth = 0, elinewidth = 0.5, ecolor = 'k', capsize = 3, zorder = 1) plt.scatter(igg_binding.iloc[0:41,1], igg_binding.iloc[0:41,2], s = 150, c = 'blueviolet', edgecolor = 'k', linewidth = 0.25, zorder = 2) #plt.scatter(igg_binding.loc[igg_binding['Scaffold'] == 1,'ANT Binding'], igg_binding.loc[igg_binding['Scaffold'] == 1,'OVA Binding'], s = 150, c = cmap(0.65), edgecolor = 'k', linewidth = 0.5, zorder = 3) plt.scatter(1,1, s = 200, c = 'k', edgecolor = 'k', linewidth = 0.25, zorder = 4) plt.scatter(1.2,0.51, s = 200, c = cmap(0.85), edgecolor = 'k', linewidth = 0.25, zorder = 4) plt.xticks([0.0, 0.4, 0.8, 1.2], [0.0, 0.4, 0.8, 1.2], fontsize = 26) plt.xlim(-0.05, 1.45) plt.yticks([0.0, 0.4, 0.8, 1.2], [0.0, 0.4, 0.8, 1.2], fontsize = 26) plt.ylim(-0.15, 1.35) #%% #novel IgG correlations plt.figure() plt.errorbar(igg_ant_transform.loc[igg_binding['Blosum62'] == 1,0], igg_binding.loc[igg_binding['Blosum62'] == 1,'ANT Binding'], yerr = igg_binding.loc[igg_binding['Blosum62'] == 1,'ANT STDEV'], linewidth = 0, elinewidth = 0.25, ecolor = 'k', capsize = 3, zorder = 1) plt.scatter(igg_ant_transform.loc[igg_binding['Blosum62'] == 1,0], igg_binding.loc[igg_binding['Blosum62'] == 1,'ANT Binding'], c = cmap(0.15), s = 150, edgecolor = 'k', linewidth = 0.25, zorder = 2) plt.scatter(igg_ant_transform.iloc[8,0], 1.2, c = 'orange', s = 250, edgecolor = 'k', linewidth = 0.25, zorder = 3) plt.scatter(igg_ant_transform.iloc[41:42,0], 1, color = 'k', s = 250, edgecolor= 'k', linewidth = 0.25, zorder = 3) plt.xticks([1, 2, 3,4], [1, 2, 3,4], fontsize = 26) plt.yticks([0.0, 0.4, 0.8, 1.2, 1.6], [0.0, 0.4, 0.8, 1.2, 1.6], fontsize = 26) plt.ylim(-0.05, 1.8) print('Antigen model novel IgG correlation: ' + str(sc.stats.spearmanr(igg_ant_transform.loc[igg_binding['Blosum62'] == 1,0], igg_binding.loc[igg_binding['Blosum62'] == 1,'ANT Binding']))) plt.figure() plt.errorbar(igg_psy_transform.loc[igg_binding['Blosum62'] == 1,0], igg_binding.loc[igg_binding['Blosum62'] == 1,'OVA Binding'], yerr = igg_binding.loc[igg_binding['Blosum62'] == 1,'OVA STDEV'], linewidth = 0, elinewidth = 0.25, ecolor = 'k', capsize = 3, zorder = 1) plt.scatter(igg_psy_transform.loc[igg_binding['Blosum62'] == 1,0], igg_binding.loc[igg_binding['Blosum62'] == 1,'OVA Binding'], c = cmap(0.85), s = 150, edgecolor = 'k', linewidth = 0.25, zorder = 2) plt.scatter(igg_psy_transform.iloc[8,0], 0.51, c = 'orange', s = 250, edgecolor = 'k', linewidth = 0.25, zorder = 3) plt.scatter(igg_psy_transform.iloc[41:42,0], 1, color = 'k', s = 250, edgecolor= 'k', linewidth = 0.25, zorder = 3) plt.xticks([0,1, 2, 3], [0,1, 2, 3], fontsize = 26) plt.yticks([0.0, 0.4, 0.8, 1.2], [0.0, 0.4, 0.8, 1.2], fontsize = 26) plt.ylim(-0.15, 1.45) print('Specificity model novel IgG correlation: ' + str(sc.stats.spearmanr(igg_psy_transform.loc[igg_binding['Blosum62'] == 1,0], igg_binding.loc[igg_binding['Blosum62'] == 1,'OVA Binding']))) #%% #novel IgG correlations without Blosum62 filter print('Antigen model novel IgG correlation: ' + str(sc.stats.spearmanr(igg_ant_transform.iloc[42:100,0], igg_binding.iloc[42:100,1]))) print('Specificity model novel IgG correlation: ' + str(sc.stats.spearmanr(igg_psy_transform.iloc[42:100,0], igg_binding.iloc[42:100,2]))) #%% #experimental pareto plt.figure() plt.errorbar(igg_binding.iloc[0:41,1], igg_binding.iloc[0:41,2], xerr = igg_binding.iloc[0:41,3], yerr = igg_binding.iloc[0:41,4], linewidth = 0, elinewidth = 0.5, ecolor = 'k', capsize = 3, zorder = 1) plt.scatter(igg_binding.iloc[0:41,1], igg_binding.iloc[0:41,2], s = 150, c = 'blueviolet', edgecolor = 'k', linewidth = 0.5, zorder = 2) plt.errorbar(igg_binding.loc[igg_binding['Blosum62'] == 1,'ANT Binding'], igg_binding.loc[igg_binding['Blosum62'] == 1,'OVA Binding'], yerr = igg_binding.loc[igg_binding['Blosum62'] == 1,'ANT STDEV'], linewidth = 0, elinewidth = 0.25, ecolor = 'k', capsize = 3, zorder = 1) plt.scatter(igg_binding.loc[igg_binding['Blosum62'] == 1,'ANT Binding'], igg_binding.loc[igg_binding['Blosum62'] == 1,'OVA Binding'], c = 'mediumspringgreen', s = 150, edgecolor = 'k', linewidth = 0.25, zorder = 2) #plt.scatter(igg_binding.loc[igg_binding['Scaffold'] == 1,'ANT Binding'], igg_binding.loc[igg_binding['Scaffold'] == 1,'OVA Binding'], s = 150, c = cmap(0.65), edgecolor = 'k', linewidth = 0.5, zorder = 3) plt.scatter(1,1, s = 250, c = 'k', edgecolor = 'k', linewidth = 0.5, zorder = 4) plt.scatter(1.2,0.51, s = 250, c = 'orange', edgecolor = 'k', linewidth = 0.5, zorder = 4) plt.scatter(1.28, 0.3, s = 250, c = 'red', edgecolor = 'k', linewidth = 0.5, zorder = 4) plt.xticks([0.0, 0.4, 0.8, 1.2], [0.0, 0.4, 0.8, 1.2], fontsize = 26) plt.xlim(-0.05, 1.45) plt.yticks([0.0, 0.4, 0.8, 1.2], [0.0, 0.4, 0.8, 1.2], fontsize = 26) plt.ylim(-0.15, 1.35) #%% ax = plt.subplots() sc.stats.probplot(iso_binding.iloc[:,1], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(iso_binding.iloc[:,1]) print(p) #%% ax = plt.subplots() sc.stats.probplot(iso_binding.iloc[:,2], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(iso_binding.iloc[:,2]) print(p) #%% ax = plt.subplots() sc.stats.probplot(igg_binding.iloc[0:42,1], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(igg_binding.iloc[0:42,1]) print(p) #%% ax = plt.subplots() sc.stats.probplot(igg_binding.iloc[0:42,2], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(igg_binding.iloc[0:42,2]) print(p) #%% ax = plt.subplots() sc.stats.probplot(igg_binding.loc[igg_binding['Blosum62'] == 1,'ANT Binding'], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(igg_binding.loc[igg_binding['Blosum62'] == 1,'ANT Binding']) print(p) #%% ax = plt.subplots() sc.stats.probplot(igg_binding.loc[igg_binding['Blosum62'] == 1,'OVA Binding'], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(igg_binding.loc[igg_binding['Blosum62'] == 1,'OVA Binding']) print(p) #%% ax = plt.subplots() sc.stats.probplot(iso_ant_transform.iloc[:,0], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(iso_ant_transform.iloc[:,0]) print(p) #%% ax = plt.subplots() sc.stats.probplot(iso_psy_transform.iloc[:,0], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(iso_psy_transform.iloc[:,0]) print(p) #%% ax = plt.subplots() sc.stats.probplot(igg_ant_transform.iloc[:,0], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(igg_binding.iloc[0:42,1]) print(p) #%% ax = plt.subplots() sc.stats.probplot(igg_psy_transform.iloc[:,0], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(igg_binding.iloc[0:42,2]) print(p) #%% ax = plt.subplots() sc.stats.probplot(igg_ant_transform.loc[igg_binding['Blosum62'] == 1,0], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(igg_ant_transform.loc[igg_binding['Blosum62'] == 1,0]) print(p) #%% ax = plt.subplots() sc.stats.probplot(igg_psy_transform.loc[igg_binding['Blosum62'] == 1,0], dist = "norm", plot=plt) plt.xticks(fontsize = 20) plt.xlabel('Theoretical quantiles', fontsize = 24) plt.yticks(fontsize = 20) plt.ylabel('Ordered values', fontsize = 24) plt.tight_layout() stat, p = sc.stats.shapiro(igg_psy_transform.loc[igg_binding['Blosum62'] == 1,0]) print(p)

48.775342

273

0.683649

3,120

17,803

3.767308

0.060256

0.073167

0.036498

0.052748

0.916794

0.905139

0.868215

0.823635

0.797941

0.727412

0

0.086695

0.113015

17,803

364

274

48.909341

0.657653

0.042184

0

0.612069

0

0.108834

0

1

0

false

0

0.00431

0

0.00431

0.103448

0

null

0

1

0

null

0

6

73a6709248282e9ba0b4c8204e7c73b33d4df79d

2,488

py

Python

src/tests/test_group_read.py

devsetgo/test-api

2a84bbacbf5cd043b2227e74332e8518927a8238

[ "MIT" ]

9

2019-05-22T08:46:01.000Z

2021-12-10T06:44:56.000Z

src/tests/test_group_read.py

devsetgo/test-api

2a84bbacbf5cd043b2227e74332e8518927a8238

[ "MIT" ]

285

2019-09-03T00:52:39.000Z

2022-02-13T02:13:59.000Z

src/tests/test_group_read.py

devsetgo/test-api

2a84bbacbf5cd043b2227e74332e8518927a8238

[ "MIT" ]

4

2019-09-19T18:14:09.000Z

2020-12-15T18:35:07.000Z

# -*- coding: utf-8 -*- import unittest from starlette.testclient import TestClient from src.main import app client = TestClient(app) directory_to__files: str = "data" # api/v1/groups/list?delay=1&qty=10&offset=1&active=true&groupType=approval class Test(unittest.TestCase): def test_groups_get_list_error_delay(self): url = f"/api/v1/groups/list?delay=122" response = client.get(url) assert response.status_code == 422 def test_groups_get_list_error_qty(self): url = f"/api/v1/groups/list?qty=501" response = client.get(url) assert response.status_code == 422 def test_groups_get_list_error_type(self): url = f"/api/v1/groups/list?groupType=bob" response = client.get(url) assert response.status_code == 422 def test_groups_get_list_all_options(self): url = f"/api/v1/groups/list?delay=1&qty=10&offset=1&active=true&groupType=approval" response = client.get(url) assert response.status_code == 200 def test_groups_get_list(self): url = f"/api/v1/groups/list" response = client.get(url) assert response.status_code == 200 def test_groups_get_list_name(self): url = f"/api/v1/groups/list?groupName=test" response = client.get(url) assert response.status_code == 200 def test_groups_get_list_count(self): url = f"/api/v1/groups/list/count" response = client.get(url) assert response.status_code == 200 def test_groups_get_list_count_error_delay(self): url = f"/api/v1/groups/list/count?delay=122" response = client.get(url) assert response.status_code == 422 def test_groups_get_list_count_all_options(self): group_type: list = ["approval", "notification"] active_state: list = ["true", "false"] for g in group_type: for a in active_state: url = f"/api/v1/groups/list/count?delay=1&active={a}&groupType={g}" response = client.get(url) assert response.status_code == 200 def test_groups_get_list_count_invalid_group(self): url = f"/api/v1/groups/list/count?groupType=bob" response = client.get(url) assert response.status_code == 422 def test_groups_get_list_count_invalid_group(self): url = f"/api/v1/groups/list/?groupType=bob" response = client.get(url) assert response.status_code == 422

28.272727

91

0.655547

348

2,488

4.477011

0.181034

0.038511

0.084724

0.115533

0.800385

0.787548

0.743261

0.695122

0.65276

0

0.033455

0.231109

2,488

87

92

28.597701

0.780972

0.038183

0

0.444444

0

0.037037

0.1841

0.162343

0

0.203704

1

0.203704

false

0

0.055556

0

0.277778

0

null

0

1

0

1

0

null

0

1

0

6

73bfa100052e5c93bcbc991642712c72f1cdf7db

1,722

py

Python

old/stoper2.py

Faralaks/the-game

cd08f1f0222eee71916763a11f99ea631dbad578

[ "MIT" ]

null

old/stoper2.py

Faralaks/the-game

cd08f1f0222eee71916763a11f99ea631dbad578

[ "MIT" ]

null

old/stoper2.py

Faralaks/the-game

cd08f1f0222eee71916763a11f99ea631dbad578

[ "MIT" ]

null

#UTF-8 def stoper(x_object, y_object, side, stop_kords=False): if stop_kords != False: stop = True if side == 0: for i in stop_kords: temp = i.split(' ') x1 = int(temp[0]) y1 = int(temp[1]) x2 = int(temp[2]) y2 = int(temp[3]) if x_object + 48 >= x1 and x_object + 2 <= x2 and y_object + 52 >= y1 and y_object + 28 <= y2: stop = False if side == 1: for i in stop_kords: temp = i.split(' ') x1 = int(temp[0]) y1 = int(temp[1]) x2 = int(temp[2]) y2 = int(temp[3]) if x_object + 48 >= x1 and x_object + 2 <= x2 and y_object + 38 >= y1 and y_object + 24 <= y2: stop = False if side == 2: for i in stop_kords: temp = i.split(' ') x1 = int(temp[0]) y1 = int(temp[1]) x2 = int(temp[2]) y2 = int(temp[3]) if x_object + 50 >= x1 and x_object + 40 <= x2 and y_object + 38 >= y1 and y_object + 28 <= y2: stop = False if side == 3: for i in stop_kords: temp = i.split(' ') x1 = int(temp[0]) y1 = int(temp[1]) x2 = int(temp[2]) y2 = int(temp[3]) if x_object + 45 >= x1 and x_object <= x2 and y_object + 38 >= y1 and y_object + 28 <= y2: stop = False return stop else: return True

28.7

111

0.381533

218

1,722

2.90367

0.174312

0.176935

0.126382

0.063191

0.78357

0.756714

0.734597

0

0.095745

0.508711

1,722

60

112

28.7

0.652482

0.002904

0

0.682927

0

0.00233

0

1

0.02439

false

0

0.04878

0

null

0

1

0

1

0

null

0

6

73d42f338df026b4117d0fe5d196c3dfa45ebf91

3,171

py

Python

gitlint/tests/rules/test_configuration_rules.py

dzhu/gitlint

c77d4a1009a8e9b567134b295720f92173911b33

[ "MIT" ]

null

gitlint/tests/rules/test_configuration_rules.py

dzhu/gitlint

c77d4a1009a8e9b567134b295720f92173911b33

[ "MIT" ]

null

gitlint/tests/rules/test_configuration_rules.py

dzhu/gitlint

c77d4a1009a8e9b567134b295720f92173911b33

[ "MIT" ]

null

# -*- coding: utf-8 -*- from gitlint.tests.base import BaseTestCase from gitlint import rules from gitlint.config import LintConfig class ConfigurationRuleTests(BaseTestCase): def test_ignore_by_title(self): commit = self.gitcommit(u"Releäse\n\nThis is the secōnd body line") # No regex specified -> Config shouldn't be changed rule = rules.IgnoreByTitle() config = LintConfig() rule.apply(config, commit) self.assertEqual(config, LintConfig()) self.assert_logged([]) # nothing logged -> nothing ignored # Matching regex -> expect config to ignore all rules rule = rules.IgnoreByTitle({"regex": u"^Releäse(.*)"}) expected_config = LintConfig() expected_config.ignore = "all" rule.apply(config, commit) self.assertEqual(config, expected_config) expected_log_message = u"DEBUG: gitlint.rules Ignoring commit because of rule 'I1': " + \ u"Commit title 'Releäse' matches the regex '^Releäse(.*)', ignoring rules: all" self.assert_log_contains(expected_log_message) # Matching regex with specific ignore rule = rules.IgnoreByTitle({"regex": u"^Releäse(.*)", "ignore": "T1,B2"}) expected_config = LintConfig() expected_config.ignore = "T1,B2" rule.apply(config, commit) self.assertEqual(config, expected_config) expected_log_message = u"DEBUG: gitlint.rules Ignoring commit because of rule 'I1': " + \ u"Commit title 'Releäse' matches the regex '^Releäse(.*)', ignoring rules: T1,B2" def test_ignore_by_body(self): commit = self.gitcommit(u"Tïtle\n\nThis is\n a relëase body\n line") # No regex specified -> Config shouldn't be changed rule = rules.IgnoreByBody() config = LintConfig() rule.apply(config, commit) self.assertEqual(config, LintConfig()) self.assert_logged([]) # nothing logged -> nothing ignored # Matching regex -> expect config to ignore all rules rule = rules.IgnoreByBody({"regex": u"(.*)relëase(.*)"}) expected_config = LintConfig() expected_config.ignore = "all" rule.apply(config, commit) self.assertEqual(config, expected_config) expected_log_message = u"DEBUG: gitlint.rules Ignoring commit because of rule 'I2': " + \ u"Commit message line ' a relëase body' matches the regex '(.*)relëase(.*)'," + \ u" ignoring rules: all" self.assert_log_contains(expected_log_message) # Matching regex with specific ignore rule = rules.IgnoreByBody({"regex": u"(.*)relëase(.*)", "ignore": "T1,B2"}) expected_config = LintConfig() expected_config.ignore = "T1,B2" rule.apply(config, commit) self.assertEqual(config, expected_config) expected_log_message = u"DEBUG: gitlint.rules Ignoring commit because of rule 'I1': " + \ u"Commit message line ' a relëase body' matches the regex '(.*)relëase(.*)', ignoring rules: T1,B2"

44.041667

112

0.623778

356

3,171

5.455056

0.19382

0.086509

0.046344

0.064882

0.853244

0.828527

0.776004

0

0.007268

0.262378

3,171

71

113

44.661972

0.823001

0.115106

0

0.607843

0

0.275751

0

0.196078

1

0.039216

false

0

0.058824

0

0.117647

0

null

0

1

0

null

0

6

73f72336b88416e9c8be927bcb101e66f9f70838

154

py

Python

ProgrammingBasicWithPython-KCL/Chapter-5/queuetest.py

mrmyothet/IPND

204e010f815fa10951daf38669a9323cb6b13147

[ "MIT" ]

1

2020-07-04T14:00:48.000Z

ProgrammingBasicWithPython-KCL/Chapter-5/queuetest.py

mrmyothet/IPND

204e010f815fa10951daf38669a9323cb6b13147

[ "MIT" ]

20

2020-06-01T04:32:16.000Z

2020-09-14T07:18:54.000Z

ProgrammingBasicWithPython-KCL/Chapter-5/queuetest.py

mrmyothet/ipnd

204e010f815fa10951daf38669a9323cb6b13147

[ "MIT" ]

null

from pyqueue import Queue q = Queue() q.enqueue(6) q.enqueue("cat") q.enqueue(True) print(q.size()) print(q.dequeue()) print(q.dequeue()) print(q.size())

15.4

25

0.688312

27

154

3.925926

0.444444

0.226415

0.188679

0.339623

0.301887

0

0.007143

0.090909

154

9

26

17.111111

0.75

0

0.444444

0

0.019481

0

1

0

false

0

0.111111

0

0.111111

0.444444

1

0

null

1

0

1

0

null

0

1

0

6

fb923e0361e58c340873980a3f63e0ee4f51099f

381

py

Python

pygrim/components/utils/__init__.py

ondrejkajinek/pyGrim

1a99f88c790386d111d4978200a309514f7c8a1f

[ "MIT" ]

3

2017-04-21T12:57:07.000Z

2017-08-02T14:45:51.000Z

pygrim/components/utils/__init__.py

ondrejkajinek/pyGrim

1a99f88c790386d111d4978200a309514f7c8a1f

[ "MIT" ]

14

2017-05-09T15:25:10.000Z

2017-08-03T08:21:24.000Z

pygrim/components/utils/__init__.py

ondrejkajinek/pyGrim

1a99f88c790386d111d4978200a309514f7c8a1f

[ "MIT" ]

null

# coding: utf8 from .counter import Counter # noqa from .functions import deep_update # noqa from .functions import ensure_string, ensure_tuple # noqa from .functions import fix_trailing_slash, remove_trailing_slash # noqa from .functions import get_class_name, get_instance_name, get_method_name # noqa from .functions import is_regex # noqa from . import json2 # noqa

38.1

82

0.790026

54

381

5.314815

0.444444

0.167247

0.296167

0.400697

0

0.006231

0.15748

381

9

83

42.333333

0.88785

0.12336

0

1

0

true

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

fbd98843bbc94548ba02ac6399baf7b72fb70d8a

26

py

Python

intake/catalog/__init__.py

ah-/intake

1c971a9e579a18be603b4a74a71dbc111afbcb0c

[ "BSD-2-Clause" ]

null

intake/catalog/__init__.py

ah-/intake

1c971a9e579a18be603b4a74a71dbc111afbcb0c

[ "BSD-2-Clause" ]

null

intake/catalog/__init__.py

ah-/intake

1c971a9e579a18be603b4a74a71dbc111afbcb0c

[ "BSD-2-Clause" ]

null

from .base import Catalog

13

25

0.807692

4

26

5.25

1

0

0.153846

26

1

26

0.954545

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

8384d725e6f46dbff5c34caa60cbadf4b6f552b4

37,900

py

Python

instances/passenger_demand/pas-20210421-2109-int14000000000000001e/11.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

instances/passenger_demand/pas-20210421-2109-int14000000000000001e/11.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

instances/passenger_demand/pas-20210421-2109-int14000000000000001e/11.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

""" PASSENGERS """ numPassengers = 3220 passenger_arriving = ( (7, 9, 8, 2, 0, 0, 8, 3, 6, 5, 1, 0), # 0 (4, 12, 8, 6, 3, 0, 7, 8, 3, 5, 2, 0), # 1 (6, 10, 9, 3, 2, 0, 3, 15, 5, 7, 1, 0), # 2 (3, 14, 15, 2, 3, 0, 6, 4, 4, 2, 2, 0), # 3 (3, 5, 15, 3, 2, 0, 9, 7, 10, 5, 1, 0), # 4 (4, 3, 3, 2, 1, 0, 3, 5, 6, 3, 0, 0), # 5 (5, 9, 7, 0, 1, 0, 6, 8, 9, 4, 1, 0), # 6 (3, 9, 8, 4, 3, 0, 6, 9, 5, 5, 1, 0), # 7 (8, 8, 11, 5, 1, 0, 7, 12, 3, 4, 4, 0), # 8 (2, 8, 9, 1, 2, 0, 6, 11, 8, 6, 2, 0), # 9 (3, 6, 4, 1, 4, 0, 9, 7, 6, 2, 2, 0), # 10 (2, 12, 6, 3, 2, 0, 11, 11, 4, 4, 6, 0), # 11 (3, 8, 5, 6, 3, 0, 5, 6, 9, 2, 4, 0), # 12 (3, 8, 7, 3, 1, 0, 2, 11, 6, 3, 0, 0), # 13 (5, 6, 8, 2, 1, 0, 10, 5, 7, 2, 1, 0), # 14 (11, 4, 9, 5, 2, 0, 5, 7, 10, 6, 4, 0), # 15 (3, 8, 5, 2, 2, 0, 10, 10, 4, 2, 1, 0), # 16 (8, 13, 8, 5, 3, 0, 9, 7, 6, 0, 2, 0), # 17 (7, 3, 3, 1, 2, 0, 7, 7, 2, 3, 4, 0), # 18 (5, 10, 4, 5, 3, 0, 4, 8, 4, 9, 2, 0), # 19 (4, 7, 10, 4, 4, 0, 2, 11, 7, 6, 2, 0), # 20 (2, 8, 6, 2, 2, 0, 7, 9, 4, 9, 4, 0), # 21 (2, 3, 7, 2, 5, 0, 4, 16, 6, 3, 3, 0), # 22 (2, 7, 4, 2, 0, 0, 7, 17, 3, 1, 4, 0), # 23 (3, 7, 5, 7, 3, 0, 4, 10, 5, 5, 4, 0), # 24 (4, 6, 8, 6, 2, 0, 6, 4, 7, 3, 1, 0), # 25 (5, 8, 11, 5, 1, 0, 9, 13, 5, 7, 3, 0), # 26 (4, 7, 7, 1, 2, 0, 2, 10, 9, 8, 1, 0), # 27 (4, 10, 10, 4, 0, 0, 7, 8, 5, 6, 2, 0), # 28 (5, 7, 10, 9, 2, 0, 6, 11, 8, 3, 2, 0), # 29 (3, 8, 9, 3, 4, 0, 10, 15, 7, 3, 2, 0), # 30 (6, 11, 4, 2, 3, 0, 6, 6, 6, 6, 1, 0), # 31 (1, 13, 3, 3, 0, 0, 5, 8, 7, 6, 4, 0), # 32 (4, 8, 4, 5, 3, 0, 6, 10, 12, 3, 2, 0), # 33 (5, 8, 5, 1, 4, 0, 7, 10, 8, 2, 4, 0), # 34 (6, 5, 12, 6, 4, 0, 8, 4, 9, 8, 5, 0), # 35 (7, 11, 5, 5, 7, 0, 4, 14, 5, 4, 2, 0), # 36 (6, 11, 7, 5, 2, 0, 4, 7, 7, 11, 3, 0), # 37 (10, 5, 8, 7, 0, 0, 2, 10, 5, 3, 3, 0), # 38 (3, 10, 4, 2, 2, 0, 2, 6, 8, 1, 4, 0), # 39 (4, 5, 7, 4, 2, 0, 6, 13, 6, 5, 1, 0), # 40 (3, 5, 8, 1, 3, 0, 8, 14, 5, 4, 1, 0), # 41 (4, 7, 6, 2, 4, 0, 7, 9, 5, 5, 5, 0), # 42 (3, 10, 11, 4, 5, 0, 8, 8, 3, 6, 1, 0), # 43 (4, 10, 6, 4, 3, 0, 8, 12, 3, 7, 4, 0), # 44 (6, 13, 3, 2, 2, 0, 7, 6, 3, 4, 3, 0), # 45 (3, 5, 4, 6, 3, 0, 9, 10, 15, 3, 1, 0), # 46 (7, 5, 10, 2, 2, 0, 6, 8, 9, 6, 2, 0), # 47 (9, 9, 3, 3, 2, 0, 9, 5, 6, 8, 2, 0), # 48 (9, 8, 4, 2, 3, 0, 5, 6, 6, 4, 4, 0), # 49 (5, 15, 9, 1, 2, 0, 3, 11, 5, 3, 3, 0), # 50 (4, 11, 9, 6, 2, 0, 8, 7, 8, 4, 2, 0), # 51 (2, 12, 10, 4, 2, 0, 4, 6, 4, 9, 1, 0), # 52 (1, 13, 11, 4, 4, 0, 4, 8, 8, 6, 0, 0), # 53 (5, 5, 9, 4, 1, 0, 4, 9, 6, 5, 3, 0), # 54 (5, 10, 4, 8, 1, 0, 3, 8, 9, 3, 2, 0), # 55 (6, 9, 3, 3, 0, 0, 8, 8, 9, 7, 2, 0), # 56 (4, 12, 9, 6, 2, 0, 5, 17, 5, 2, 1, 0), # 57 (8, 13, 10, 2, 2, 0, 5, 11, 5, 4, 1, 0), # 58 (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # 59 ) station_arriving_intensity = ( (3.7095121817383676, 9.515044981060607, 11.19193043059126, 8.87078804347826, 10.000240384615385, 6.659510869565219), # 0 (3.7443308140669203, 9.620858238197952, 11.252381752534994, 8.920190141908213, 10.075193108974359, 6.657240994867151), # 1 (3.7787518681104277, 9.725101964085297, 11.31139817195087, 8.968504830917876, 10.148564102564103, 6.654901690821256), # 2 (3.8127461259877085, 9.827663671875001, 11.368936576156813, 9.01569089673913, 10.22028605769231, 6.652493274456523), # 3 (3.8462843698175795, 9.928430874719417, 11.424953852470724, 9.061707125603865, 10.290291666666668, 6.6500160628019325), # 4 (3.879337381718857, 10.027291085770905, 11.479406888210512, 9.106512303743962, 10.358513621794872, 6.647470372886473), # 5 (3.9118759438103607, 10.12413181818182, 11.53225257069409, 9.150065217391306, 10.424884615384617, 6.644856521739131), # 6 (3.943870838210907, 10.218840585104518, 11.58344778723936, 9.19232465277778, 10.489337339743592, 6.64217482638889), # 7 (3.975292847039314, 10.311304899691358, 11.632949425164242, 9.233249396135266, 10.551804487179488, 6.639425603864735), # 8 (4.006112752414399, 10.401412275094698, 11.680714371786634, 9.272798233695653, 10.61221875, 6.636609171195653), # 9 (4.03630133645498, 10.489050224466892, 11.72669951442445, 9.310929951690824, 10.670512820512823, 6.633725845410628), # 10 (4.065829381279876, 10.5741062609603, 11.7708617403956, 9.347603336352659, 10.726619391025642, 6.630775943538648), # 11 (4.094667669007903, 10.656467897727273, 11.813157937017996, 9.382777173913043, 10.780471153846154, 6.627759782608695), # 12 (4.122786981757876, 10.736022647920176, 11.85354499160954, 9.416410250603866, 10.832000801282053, 6.624677679649759), # 13 (4.15015810164862, 10.81265802469136, 11.891979791488144, 9.448461352657004, 10.881141025641025, 6.621529951690821), # 14 (4.1767518107989465, 10.886261541193182, 11.928419223971721, 9.478889266304348, 10.92782451923077, 6.618316915760871), # 15 (4.202538891327675, 10.956720710578002, 11.96282017637818, 9.507652777777778, 10.971983974358976, 6.61503888888889), # 16 (4.227490125353625, 11.023923045998176, 11.995139536025421, 9.53471067330918, 11.013552083333336, 6.611696188103866), # 17 (4.25157629499561, 11.087756060606061, 12.025334190231364, 9.560021739130436, 11.052461538461543, 6.608289130434783), # 18 (4.274768182372451, 11.148107267554012, 12.053361026313912, 9.58354476147343, 11.088645032051284, 6.604818032910629), # 19 (4.297036569602966, 11.204864179994388, 12.079176931590974, 9.60523852657005, 11.122035256410259, 6.601283212560387), # 20 (4.318352238805971, 11.257914311079544, 12.102738793380466, 9.625061820652174, 11.152564903846153, 6.597684986413044), # 21 (4.338685972100283, 11.307145173961842, 12.124003499000287, 9.642973429951692, 11.180166666666667, 6.5940236714975855), # 22 (4.358008551604722, 11.352444281793632, 12.142927935768354, 9.658932140700484, 11.204773237179488, 6.590299584842997), # 23 (4.3762907594381035, 11.393699147727272, 12.159468991002571, 9.672896739130437, 11.226317307692307, 6.586513043478261), # 24 (4.393503377719247, 11.430797284915124, 12.173583552020853, 9.684826011473431, 11.244731570512819, 6.582664364432368), # 25 (4.409617188566969, 11.46362620650954, 12.185228506141103, 9.694678743961353, 11.259948717948719, 6.5787538647343), # 26 (4.424602974100088, 11.492073425662877, 12.194360740681233, 9.702413722826089, 11.271901442307694, 6.574781861413045), # 27 (4.438431516437421, 11.516026455527497, 12.200937142959157, 9.707989734299519, 11.280522435897437, 6.570748671497586), # 28 (4.4510735976977855, 11.535372809255753, 12.204914600292774, 9.711365564613528, 11.285744391025641, 6.566654612016909), # 29 (4.4625, 11.55, 12.20625, 9.7125, 11.287500000000001, 6.562500000000001), # 30 (4.47319183983376, 11.56215031960227, 12.205248928140096, 9.712295118464054, 11.286861125886526, 6.556726763701484), # 31 (4.4836528452685425, 11.574140056818184, 12.202274033816424, 9.711684477124184, 11.28495815602837, 6.547834661835751), # 32 (4.493887715792838, 11.585967720170455, 12.197367798913046, 9.710674080882354, 11.281811569148937, 6.535910757121439), # 33 (4.503901150895141, 11.597631818181819, 12.19057270531401, 9.709269934640524, 11.277441843971632, 6.521042112277196), # 34 (4.513697850063939, 11.609130859374998, 12.181931234903383, 9.707478043300654, 11.27186945921986, 6.503315790021656), # 35 (4.523282512787724, 11.62046335227273, 12.171485869565219, 9.705304411764708, 11.265114893617023, 6.482818853073463), # 36 (4.532659838554988, 11.631627805397729, 12.159279091183576, 9.70275504493464, 11.257198625886524, 6.4596383641512585), # 37 (4.5418345268542195, 11.642622727272729, 12.145353381642513, 9.699835947712419, 11.248141134751775, 6.433861385973679), # 38 (4.5508112771739135, 11.653446626420456, 12.129751222826087, 9.696553125000001, 11.23796289893617, 6.40557498125937), # 39 (4.559594789002558, 11.664098011363638, 12.11251509661836, 9.692912581699348, 11.22668439716312, 6.37486621272697), # 40 (4.568189761828645, 11.674575390625, 12.093687484903382, 9.68892032271242, 11.214326108156028, 6.34182214309512), # 41 (4.576600895140665, 11.684877272727276, 12.07331086956522, 9.684582352941177, 11.2009085106383, 6.3065298350824595), # 42 (4.584832888427111, 11.69500216619318, 12.051427732487923, 9.679904677287583, 11.186452083333334, 6.26907635140763), # 43 (4.592890441176471, 11.704948579545455, 12.028080555555556, 9.674893300653595, 11.17097730496454, 6.229548754789272), # 44 (4.600778252877237, 11.714715021306818, 12.003311820652177, 9.669554227941177, 11.15450465425532, 6.188034107946028), # 45 (4.6085010230179035, 11.724300000000003, 11.97716400966184, 9.663893464052288, 11.137054609929079, 6.144619473596536), # 46 (4.616063451086957, 11.733702024147728, 11.9496796044686, 9.65791701388889, 11.118647650709221, 6.099391914459438), # 47 (4.623470236572891, 11.742919602272728, 11.920901086956523, 9.651630882352942, 11.099304255319149, 6.052438493253375), # 48 (4.630726078964194, 11.751951242897727, 11.890870939009663, 9.645041074346407, 11.079044902482272, 6.003846272696985), # 49 (4.6378356777493615, 11.760795454545454, 11.85963164251208, 9.638153594771243, 11.057890070921987, 5.953702315508913), # 50 (4.6448037324168805, 11.769450745738636, 11.827225679347826, 9.630974448529413, 11.035860239361703, 5.902093684407797), # 51 (4.651634942455243, 11.777915625, 11.793695531400965, 9.623509640522876, 11.012975886524824, 5.849107442112278), # 52 (4.658334007352941, 11.786188600852274, 11.759083680555555, 9.615765175653596, 10.989257491134753, 5.794830651340996), # 53 (4.6649056265984665, 11.79426818181818, 11.723432608695653, 9.60774705882353, 10.964725531914894, 5.739350374812594), # 54 (4.671354499680307, 11.802152876420456, 11.686784797705313, 9.599461294934642, 10.939400487588653, 5.682753675245711), # 55 (4.677685326086957, 11.809841193181818, 11.649182729468599, 9.59091388888889, 10.913302836879433, 5.625127615358988), # 56 (4.683902805306906, 11.817331640625003, 11.610668885869565, 9.582110845588236, 10.886453058510638, 5.566559257871065), # 57 (4.690011636828645, 11.824622727272727, 11.57128574879227, 9.573058169934642, 10.858871631205675, 5.507135665500583), # 58 (0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 59 ) passenger_arriving_acc = ( (7, 9, 8, 2, 0, 0, 8, 3, 6, 5, 1, 0), # 0 (11, 21, 16, 8, 3, 0, 15, 11, 9, 10, 3, 0), # 1 (17, 31, 25, 11, 5, 0, 18, 26, 14, 17, 4, 0), # 2 (20, 45, 40, 13, 8, 0, 24, 30, 18, 19, 6, 0), # 3 (23, 50, 55, 16, 10, 0, 33, 37, 28, 24, 7, 0), # 4 (27, 53, 58, 18, 11, 0, 36, 42, 34, 27, 7, 0), # 5 (32, 62, 65, 18, 12, 0, 42, 50, 43, 31, 8, 0), # 6 (35, 71, 73, 22, 15, 0, 48, 59, 48, 36, 9, 0), # 7 (43, 79, 84, 27, 16, 0, 55, 71, 51, 40, 13, 0), # 8 (45, 87, 93, 28, 18, 0, 61, 82, 59, 46, 15, 0), # 9 (48, 93, 97, 29, 22, 0, 70, 89, 65, 48, 17, 0), # 10 (50, 105, 103, 32, 24, 0, 81, 100, 69, 52, 23, 0), # 11 (53, 113, 108, 38, 27, 0, 86, 106, 78, 54, 27, 0), # 12 (56, 121, 115, 41, 28, 0, 88, 117, 84, 57, 27, 0), # 13 (61, 127, 123, 43, 29, 0, 98, 122, 91, 59, 28, 0), # 14 (72, 131, 132, 48, 31, 0, 103, 129, 101, 65, 32, 0), # 15 (75, 139, 137, 50, 33, 0, 113, 139, 105, 67, 33, 0), # 16 (83, 152, 145, 55, 36, 0, 122, 146, 111, 67, 35, 0), # 17 (90, 155, 148, 56, 38, 0, 129, 153, 113, 70, 39, 0), # 18 (95, 165, 152, 61, 41, 0, 133, 161, 117, 79, 41, 0), # 19 (99, 172, 162, 65, 45, 0, 135, 172, 124, 85, 43, 0), # 20 (101, 180, 168, 67, 47, 0, 142, 181, 128, 94, 47, 0), # 21 (103, 183, 175, 69, 52, 0, 146, 197, 134, 97, 50, 0), # 22 (105, 190, 179, 71, 52, 0, 153, 214, 137, 98, 54, 0), # 23 (108, 197, 184, 78, 55, 0, 157, 224, 142, 103, 58, 0), # 24 (112, 203, 192, 84, 57, 0, 163, 228, 149, 106, 59, 0), # 25 (117, 211, 203, 89, 58, 0, 172, 241, 154, 113, 62, 0), # 26 (121, 218, 210, 90, 60, 0, 174, 251, 163, 121, 63, 0), # 27 (125, 228, 220, 94, 60, 0, 181, 259, 168, 127, 65, 0), # 28 (130, 235, 230, 103, 62, 0, 187, 270, 176, 130, 67, 0), # 29 (133, 243, 239, 106, 66, 0, 197, 285, 183, 133, 69, 0), # 30 (139, 254, 243, 108, 69, 0, 203, 291, 189, 139, 70, 0), # 31 (140, 267, 246, 111, 69, 0, 208, 299, 196, 145, 74, 0), # 32 (144, 275, 250, 116, 72, 0, 214, 309, 208, 148, 76, 0), # 33 (149, 283, 255, 117, 76, 0, 221, 319, 216, 150, 80, 0), # 34 (155, 288, 267, 123, 80, 0, 229, 323, 225, 158, 85, 0), # 35 (162, 299, 272, 128, 87, 0, 233, 337, 230, 162, 87, 0), # 36 (168, 310, 279, 133, 89, 0, 237, 344, 237, 173, 90, 0), # 37 (178, 315, 287, 140, 89, 0, 239, 354, 242, 176, 93, 0), # 38 (181, 325, 291, 142, 91, 0, 241, 360, 250, 177, 97, 0), # 39 (185, 330, 298, 146, 93, 0, 247, 373, 256, 182, 98, 0), # 40 (188, 335, 306, 147, 96, 0, 255, 387, 261, 186, 99, 0), # 41 (192, 342, 312, 149, 100, 0, 262, 396, 266, 191, 104, 0), # 42 (195, 352, 323, 153, 105, 0, 270, 404, 269, 197, 105, 0), # 43 (199, 362, 329, 157, 108, 0, 278, 416, 272, 204, 109, 0), # 44 (205, 375, 332, 159, 110, 0, 285, 422, 275, 208, 112, 0), # 45 (208, 380, 336, 165, 113, 0, 294, 432, 290, 211, 113, 0), # 46 (215, 385, 346, 167, 115, 0, 300, 440, 299, 217, 115, 0), # 47 (224, 394, 349, 170, 117, 0, 309, 445, 305, 225, 117, 0), # 48 (233, 402, 353, 172, 120, 0, 314, 451, 311, 229, 121, 0), # 49 (238, 417, 362, 173, 122, 0, 317, 462, 316, 232, 124, 0), # 50 (242, 428, 371, 179, 124, 0, 325, 469, 324, 236, 126, 0), # 51 (244, 440, 381, 183, 126, 0, 329, 475, 328, 245, 127, 0), # 52 (245, 453, 392, 187, 130, 0, 333, 483, 336, 251, 127, 0), # 53 (250, 458, 401, 191, 131, 0, 337, 492, 342, 256, 130, 0), # 54 (255, 468, 405, 199, 132, 0, 340, 500, 351, 259, 132, 0), # 55 (261, 477, 408, 202, 132, 0, 348, 508, 360, 266, 134, 0), # 56 (265, 489, 417, 208, 134, 0, 353, 525, 365, 268, 135, 0), # 57 (273, 502, 427, 210, 136, 0, 358, 536, 370, 272, 136, 0), # 58 (273, 502, 427, 210, 136, 0, 358, 536, 370, 272, 136, 0), # 59 ) passenger_arriving_rate = ( (3.7095121817383676, 7.612035984848484, 6.715158258354756, 3.5483152173913037, 2.000048076923077, 0.0, 6.659510869565219, 8.000192307692307, 5.322472826086956, 4.476772172236504, 1.903008996212121, 0.0), # 0 (3.7443308140669203, 7.696686590558361, 6.751429051520996, 3.5680760567632848, 2.0150386217948717, 0.0, 6.657240994867151, 8.060154487179487, 5.352114085144928, 4.500952701013997, 1.9241716476395903, 0.0), # 1 (3.7787518681104277, 7.780081571268237, 6.786838903170522, 3.58740193236715, 2.0297128205128203, 0.0, 6.654901690821256, 8.118851282051281, 5.381102898550726, 4.524559268780347, 1.9450203928170593, 0.0), # 2 (3.8127461259877085, 7.8621309375, 6.821361945694087, 3.6062763586956517, 2.044057211538462, 0.0, 6.652493274456523, 8.176228846153847, 5.409414538043478, 4.547574630462725, 1.965532734375, 0.0), # 3 (3.8462843698175795, 7.942744699775533, 6.854972311482434, 3.624682850241546, 2.0580583333333333, 0.0, 6.6500160628019325, 8.232233333333333, 5.437024275362319, 4.569981540988289, 1.9856861749438832, 0.0), # 4 (3.879337381718857, 8.021832868616723, 6.887644132926307, 3.6426049214975844, 2.0717027243589743, 0.0, 6.647470372886473, 8.286810897435897, 5.463907382246377, 4.591762755284204, 2.005458217154181, 0.0), # 5 (3.9118759438103607, 8.099305454545455, 6.919351542416455, 3.660026086956522, 2.084976923076923, 0.0, 6.644856521739131, 8.339907692307692, 5.490039130434783, 4.612901028277636, 2.0248263636363637, 0.0), # 6 (3.943870838210907, 8.175072468083613, 6.950068672343615, 3.6769298611111116, 2.0978674679487184, 0.0, 6.64217482638889, 8.391469871794873, 5.515394791666668, 4.633379114895743, 2.043768117020903, 0.0), # 7 (3.975292847039314, 8.249043919753085, 6.979769655098544, 3.693299758454106, 2.1103608974358976, 0.0, 6.639425603864735, 8.44144358974359, 5.5399496376811594, 4.653179770065696, 2.062260979938271, 0.0), # 8 (4.006112752414399, 8.321129820075758, 7.00842862307198, 3.709119293478261, 2.12244375, 0.0, 6.636609171195653, 8.489775, 5.563678940217391, 4.672285748714653, 2.0802824550189394, 0.0), # 9 (4.03630133645498, 8.391240179573513, 7.03601970865467, 3.724371980676329, 2.134102564102564, 0.0, 6.633725845410628, 8.536410256410257, 5.586557971014494, 4.690679805769779, 2.0978100448933783, 0.0), # 10 (4.065829381279876, 8.459285008768239, 7.06251704423736, 3.739041334541063, 2.145323878205128, 0.0, 6.630775943538648, 8.581295512820512, 5.608562001811595, 4.70834469615824, 2.1148212521920597, 0.0), # 11 (4.094667669007903, 8.525174318181818, 7.087894762210797, 3.7531108695652167, 2.156094230769231, 0.0, 6.627759782608695, 8.624376923076923, 5.6296663043478254, 4.725263174807198, 2.1312935795454546, 0.0), # 12 (4.122786981757876, 8.58881811833614, 7.112126994965724, 3.766564100241546, 2.1664001602564102, 0.0, 6.624677679649759, 8.665600641025641, 5.649846150362319, 4.741417996643816, 2.147204529584035, 0.0), # 13 (4.15015810164862, 8.650126419753088, 7.135187874892886, 3.779384541062801, 2.1762282051282047, 0.0, 6.621529951690821, 8.704912820512819, 5.669076811594202, 4.756791916595257, 2.162531604938272, 0.0), # 14 (4.1767518107989465, 8.709009232954545, 7.157051534383032, 3.7915557065217387, 2.1855649038461538, 0.0, 6.618316915760871, 8.742259615384615, 5.6873335597826085, 4.771367689588688, 2.177252308238636, 0.0), # 15 (4.202538891327675, 8.7653765684624, 7.177692105826908, 3.803061111111111, 2.194396794871795, 0.0, 6.61503888888889, 8.77758717948718, 5.7045916666666665, 4.785128070551272, 2.1913441421156, 0.0), # 16 (4.227490125353625, 8.81913843679854, 7.197083721615253, 3.8138842693236716, 2.202710416666667, 0.0, 6.611696188103866, 8.810841666666668, 5.720826403985508, 4.798055814410168, 2.204784609199635, 0.0), # 17 (4.25157629499561, 8.870204848484848, 7.215200514138818, 3.824008695652174, 2.2104923076923084, 0.0, 6.608289130434783, 8.841969230769234, 5.736013043478262, 4.810133676092545, 2.217551212121212, 0.0), # 18 (4.274768182372451, 8.918485814043208, 7.232016615788346, 3.8334179045893717, 2.2177290064102566, 0.0, 6.604818032910629, 8.870916025641026, 5.750126856884058, 4.8213444105255645, 2.229621453510802, 0.0), # 19 (4.297036569602966, 8.96389134399551, 7.247506158954584, 3.8420954106280196, 2.2244070512820517, 0.0, 6.601283212560387, 8.897628205128207, 5.76314311594203, 4.831670772636389, 2.2409728359988774, 0.0), # 20 (4.318352238805971, 9.006331448863634, 7.261643276028279, 3.8500247282608693, 2.2305129807692303, 0.0, 6.597684986413044, 8.922051923076921, 5.775037092391305, 4.841095517352186, 2.2515828622159084, 0.0), # 21 (4.338685972100283, 9.045716139169473, 7.274402099400172, 3.8571893719806765, 2.2360333333333333, 0.0, 6.5940236714975855, 8.944133333333333, 5.785784057971015, 4.849601399600115, 2.2614290347923682, 0.0), # 22 (4.358008551604722, 9.081955425434906, 7.285756761461012, 3.8635728562801934, 2.2409546474358972, 0.0, 6.590299584842997, 8.963818589743589, 5.79535928442029, 4.857171174307341, 2.2704888563587264, 0.0), # 23 (4.3762907594381035, 9.114959318181818, 7.295681394601543, 3.869158695652174, 2.2452634615384612, 0.0, 6.586513043478261, 8.981053846153845, 5.803738043478262, 4.863787596401028, 2.2787398295454544, 0.0), # 24 (4.393503377719247, 9.1446378279321, 7.304150131212511, 3.8739304045893723, 2.2489463141025636, 0.0, 6.582664364432368, 8.995785256410255, 5.810895606884059, 4.869433420808341, 2.286159456983025, 0.0), # 25 (4.409617188566969, 9.17090096520763, 7.311137103684661, 3.8778714975845405, 2.2519897435897436, 0.0, 6.5787538647343, 9.007958974358974, 5.816807246376811, 4.874091402456441, 2.2927252413019077, 0.0), # 26 (4.424602974100088, 9.193658740530301, 7.31661644440874, 3.880965489130435, 2.2543802884615385, 0.0, 6.574781861413045, 9.017521153846154, 5.821448233695653, 4.877744296272493, 2.2984146851325753, 0.0), # 27 (4.438431516437421, 9.212821164421996, 7.320562285775494, 3.8831958937198072, 2.256104487179487, 0.0, 6.570748671497586, 9.024417948717948, 5.824793840579711, 4.8803748571836625, 2.303205291105499, 0.0), # 28 (4.4510735976977855, 9.228298247404602, 7.322948760175664, 3.884546225845411, 2.257148878205128, 0.0, 6.566654612016909, 9.028595512820512, 5.826819338768117, 4.881965840117109, 2.3070745618511506, 0.0), # 29 (4.4625, 9.24, 7.32375, 3.885, 2.2575000000000003, 0.0, 6.562500000000001, 9.030000000000001, 5.8275, 4.8825, 2.31, 0.0), # 30 (4.47319183983376, 9.249720255681815, 7.323149356884057, 3.884918047385621, 2.257372225177305, 0.0, 6.556726763701484, 9.02948890070922, 5.827377071078432, 4.882099571256038, 2.312430063920454, 0.0), # 31 (4.4836528452685425, 9.259312045454546, 7.3213644202898545, 3.884673790849673, 2.2569916312056737, 0.0, 6.547834661835751, 9.027966524822695, 5.82701068627451, 4.880909613526569, 2.3148280113636366, 0.0), # 32 (4.493887715792838, 9.268774176136363, 7.3184206793478275, 3.8842696323529413, 2.2563623138297872, 0.0, 6.535910757121439, 9.025449255319149, 5.826404448529412, 4.878947119565218, 2.3171935440340907, 0.0), # 33 (4.503901150895141, 9.278105454545454, 7.314343623188405, 3.8837079738562093, 2.2554883687943263, 0.0, 6.521042112277196, 9.021953475177305, 5.825561960784314, 4.876229082125604, 2.3195263636363634, 0.0), # 34 (4.513697850063939, 9.287304687499997, 7.3091587409420296, 3.882991217320261, 2.2543738918439717, 0.0, 6.503315790021656, 9.017495567375887, 5.824486825980392, 4.872772493961353, 2.3218261718749993, 0.0), # 35 (4.523282512787724, 9.296370681818182, 7.302891521739131, 3.8821217647058828, 2.253022978723404, 0.0, 6.482818853073463, 9.012091914893617, 5.823182647058824, 4.868594347826087, 2.3240926704545455, 0.0), # 36 (4.532659838554988, 9.305302244318183, 7.295567454710145, 3.881102017973856, 2.2514397251773044, 0.0, 6.4596383641512585, 9.005758900709218, 5.821653026960784, 4.86371163647343, 2.3263255610795457, 0.0), # 37 (4.5418345268542195, 9.314098181818181, 7.287212028985508, 3.8799343790849674, 2.249628226950355, 0.0, 6.433861385973679, 8.99851290780142, 5.819901568627452, 4.858141352657005, 2.3285245454545453, 0.0), # 38 (4.5508112771739135, 9.322757301136363, 7.277850733695652, 3.87862125, 2.247592579787234, 0.0, 6.40557498125937, 8.990370319148935, 5.817931875, 4.8519004891304345, 2.330689325284091, 0.0), # 39 (4.559594789002558, 9.33127840909091, 7.267509057971015, 3.8771650326797387, 2.245336879432624, 0.0, 6.37486621272697, 8.981347517730496, 5.815747549019608, 4.845006038647344, 2.3328196022727274, 0.0), # 40 (4.568189761828645, 9.3396603125, 7.256212490942029, 3.8755681290849675, 2.2428652216312055, 0.0, 6.34182214309512, 8.971460886524822, 5.813352193627452, 4.837474993961353, 2.334915078125, 0.0), # 41 (4.576600895140665, 9.34790181818182, 7.2439865217391315, 3.8738329411764707, 2.2401817021276598, 0.0, 6.3065298350824595, 8.960726808510639, 5.810749411764706, 4.829324347826088, 2.336975454545455, 0.0), # 42 (4.584832888427111, 9.356001732954544, 7.230856639492753, 3.8719618709150327, 2.2372904166666667, 0.0, 6.26907635140763, 8.949161666666667, 5.80794280637255, 4.820571092995169, 2.339000433238636, 0.0), # 43 (4.592890441176471, 9.363958863636363, 7.216848333333333, 3.8699573202614377, 2.2341954609929076, 0.0, 6.229548754789272, 8.93678184397163, 5.804935980392157, 4.811232222222222, 2.3409897159090907, 0.0), # 44 (4.600778252877237, 9.371772017045453, 7.201987092391306, 3.8678216911764705, 2.230900930851064, 0.0, 6.188034107946028, 8.923603723404256, 5.801732536764706, 4.80132472826087, 2.3429430042613633, 0.0), # 45 (4.6085010230179035, 9.379440000000002, 7.186298405797103, 3.8655573856209147, 2.2274109219858156, 0.0, 6.144619473596536, 8.909643687943262, 5.798336078431372, 4.790865603864735, 2.3448600000000006, 0.0), # 46 (4.616063451086957, 9.386961619318182, 7.16980776268116, 3.8631668055555552, 2.223729530141844, 0.0, 6.099391914459438, 8.894918120567375, 5.794750208333333, 4.77987184178744, 2.3467404048295455, 0.0), # 47 (4.623470236572891, 9.394335681818182, 7.152540652173913, 3.8606523529411763, 2.21986085106383, 0.0, 6.052438493253375, 8.87944340425532, 5.790978529411765, 4.7683604347826085, 2.3485839204545456, 0.0), # 48 (4.630726078964194, 9.401560994318181, 7.134522563405797, 3.8580164297385626, 2.2158089804964543, 0.0, 6.003846272696985, 8.863235921985817, 5.787024644607844, 4.7563483756038645, 2.3503902485795454, 0.0), # 49 (4.6378356777493615, 9.408636363636361, 7.115778985507247, 3.8552614379084966, 2.211578014184397, 0.0, 5.953702315508913, 8.846312056737588, 5.782892156862745, 4.743852657004831, 2.3521590909090904, 0.0), # 50 (4.6448037324168805, 9.415560596590907, 7.096335407608696, 3.852389779411765, 2.2071720478723407, 0.0, 5.902093684407797, 8.828688191489363, 5.778584669117648, 4.73089027173913, 2.353890149147727, 0.0), # 51 (4.651634942455243, 9.4223325, 7.0762173188405795, 3.84940385620915, 2.2025951773049646, 0.0, 5.849107442112278, 8.810380709219858, 5.774105784313726, 4.717478212560386, 2.355583125, 0.0), # 52 (4.658334007352941, 9.428950880681818, 7.055450208333333, 3.8463060702614382, 2.1978514982269504, 0.0, 5.794830651340996, 8.791405992907801, 5.769459105392158, 4.703633472222222, 2.3572377201704544, 0.0), # 53 (4.6649056265984665, 9.435414545454544, 7.034059565217391, 3.843098823529412, 2.192945106382979, 0.0, 5.739350374812594, 8.771780425531915, 5.764648235294119, 4.689373043478261, 2.358853636363636, 0.0), # 54 (4.671354499680307, 9.441722301136364, 7.012070878623187, 3.8397845179738566, 2.1878800975177306, 0.0, 5.682753675245711, 8.751520390070922, 5.759676776960785, 4.674713919082125, 2.360430575284091, 0.0), # 55 (4.677685326086957, 9.447872954545453, 6.989509637681159, 3.8363655555555556, 2.1826605673758865, 0.0, 5.625127615358988, 8.730642269503546, 5.754548333333334, 4.65967309178744, 2.361968238636363, 0.0), # 56 (4.683902805306906, 9.453865312500001, 6.966401331521738, 3.832844338235294, 2.1772906117021273, 0.0, 5.566559257871065, 8.70916244680851, 5.749266507352941, 4.644267554347826, 2.3634663281250003, 0.0), # 57 (4.690011636828645, 9.459698181818181, 6.942771449275362, 3.8292232679738563, 2.1717743262411346, 0.0, 5.507135665500583, 8.687097304964539, 5.743834901960785, 4.628514299516908, 2.3649245454545453, 0.0), # 58 (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 59 ) passenger_allighting_rate = ( (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 0 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 1 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 2 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 3 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 4 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 5 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 6 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 7 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 8 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 9 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 10 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 11 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 12 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 13 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 14 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 15 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 16 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 17 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 18 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 19 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 20 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 21 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 22 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 23 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 24 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 25 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 26 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 27 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 28 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 29 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 30 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 31 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 32 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 33 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 34 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 35 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 36 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 37 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 38 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 39 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 40 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 41 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 42 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 43 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 44 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 45 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 46 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 47 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 48 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 49 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 50 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 51 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 52 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 53 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 54 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 55 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 56 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 57 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 58 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 59 ) """ parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html """ #initial entropy entropy = 258194110137029475889902652135037600173 #index for seed sequence child child_seed_index = ( 1, # 0 10, # 1 )

113.134328

212

0.729182

5,147

37,900

5.367204

0.227511

0.31276

0.247602

0.46914

0.328543

0.327674

0

0.819086

0.119103

37,900

334

213

113.473054

0.008357

0.031953

0

0.202532

0

1

0

false

0.015823

0

null

1

0

1

0

1

0

null

0

6

83bb6951dce2c5f54e34fd8ba576b3f4b3dd1b3b

10,741

py

Python

src/complement.py

Lain-progressivehouse/probspace-youtube

04740862fb28fb9a38131554369d6c54eb560fc5

[ "MIT" ]

5

2020-06-29T04:32:07.000Z

2021-02-08T03:54:29.000Z

src/complement.py

Lain-progressivehouse/probspace-youtube

04740862fb28fb9a38131554369d6c54eb560fc5

[ "MIT" ]

null

src/complement.py

Lain-progressivehouse/probspace-youtube

04740862fb28fb9a38131554369d6c54eb560fc5

[ "MIT" ]

null

import re import unicodedata from collections import Counter from itertools import product import numpy as np import pandas as pd from sklearn.decomposition import TruncatedSVD from sklearn.model_selection import StratifiedKFold from sklearn.preprocessing import LabelEncoder from src import sentence_splitter, data_frame, learn_sklearn, learn_lgb def rating_dataset(): # target: ["likes", "dislikes"] all_df = pd.concat( [pd.read_csv("./data/input/train_data.csv").drop(["y"], axis=1), pd.read_csv("./data/input/test_data.csv")] ).reset_index(drop=True) # train = all_df[~all_df["ratings_disabled"] & ~all_df["comments_disabled"]].reset_index(drop=True) # test = all_df[all_df["ratings_disabled"] & ~all_df["comments_disabled"]].reset_index(drop=True) train = all_df[~all_df["ratings_disabled"]].reset_index(drop=True) test = all_df[all_df["ratings_disabled"]].reset_index(drop=True) test = test.drop(["likes", "dislikes"], axis=1) train.likes = train.likes.apply(np.log1p) train.dislikes = train.dislikes.apply(np.log1p) train.comment_count = train.comment_count.apply(np.log1p) test.comment_count = test.comment_count.apply(np.log1p) train["publishedAt"] = pd.to_datetime(train.publishedAt).apply(lambda x: x.value) test["publishedAt"] = pd.to_datetime(test.publishedAt).apply(lambda x: x.value) train["title_len"] = train.title.apply(lambda x: len(str(x))) test["title_len"] = test.title.apply(lambda x: len(str(x))) train["channelTitle_len"] = train.channelTitle.apply(lambda x: len(str(x))) test["channelTitle_len"] = test.channelTitle.apply(lambda x: len(str(x))) train["description_len"] = train.description.apply(lambda x: len(str(x))) test["description_len"] = test.description.apply(lambda x: len(str(x))) train["tags_count"] = train.tags.apply(lambda x: str(x).count("|")) test["tags_count"] = test.tags.apply(lambda x: str(x).count("|")) # 日本語を含むかかどうかの判定 train["title_ja_count"] = train.title.apply(data_frame.is_japanese) test["title_ja_count"] = test.title.apply(data_frame.is_japanese) train["channelTitle_ja_count"] = train.channelTitle.apply(data_frame.is_japanese) test["channelTitle_ja_count"] = test.channelTitle.apply(data_frame.is_japanese) train["description_ja_count"] = train.description.apply(data_frame.is_japanese) test["description_ja_count"] = test.description.apply(data_frame.is_japanese) # アルファベットのカウント train["title_en_count"] = train.title.apply(data_frame.count_alphabet) test["title_en_count"] = test.title.apply(data_frame.count_alphabet) train["channelTitle_en_count"] = train.channelTitle.apply(data_frame.count_alphabet) test["channelTitle_en_count"] = test.channelTitle.apply(data_frame.count_alphabet) train["description_en_count"] = train.description.apply(data_frame.count_alphabet) test["description_en_count"] = test.description.apply(data_frame.count_alphabet) # 数字のカウント train["description_num_count"] = train.description.apply(data_frame.count_number) test["description_num_count"] = test.description.apply(data_frame.count_number) # urlのカウント train["description_url_count"] = train.description.apply(lambda x: str(x).count("://")) test["description_url_count"] = test.description.apply(lambda x: str(x).count("://")) all_df: pd.DataFrame = pd.concat( [train.drop(["likes", "dislikes"], axis=1), test], ignore_index=True).reset_index(drop=True) category = ["channelId", "categoryId", "collection_date"] target_list = ["comment_count", "title_len", "channelTitle_len", "description_len", "tags_count", "description_ja_count", "description_en_count", "title_ja_count", "title_en_count", "publishedAt"] for col, target in product(category, target_list): print(col, target) data_frame.group(train, test, col, target, all_df) data_frame.TE(train, test, "mean", train.likes, ["categoryId", "collection_date"]) data_frame.TE(train, test, "std", train.likes, ["categoryId", "collection_date"]) data_frame.TE(train, test, "mean", train.dislikes, ["categoryId", "collection_date"]) data_frame.TE(train, test, "std", train.dislikes, ["categoryId", "collection_date"]) return train, test def comment_dataset(): # target: ["comment_dataset"] all_df = pd.concat( [pd.read_csv("./data/input/train_data.csv").drop(["y"], axis=1), pd.read_csv("./data/input/test_data.csv")] ).reset_index(drop=True) # train = all_df[~all_df["ratings_disabled"] & ~all_df["comments_disabled"]].reset_index(drop=True) # test = all_df[~all_df["ratings_disabled"] & all_df["comments_disabled"]].reset_index(drop=True) train = all_df[~all_df["comments_disabled"]].reset_index(drop=True) test = all_df[all_df["comments_disabled"]].reset_index(drop=True) test = test.drop(["comment_count"], axis=1) train.likes = train.likes.apply(np.log1p) train.dislikes = train.dislikes.apply(np.log1p) test.likes = test.likes.apply(np.log1p) test.dislikes = test.dislikes.apply(np.log1p) train.comment_count = train.comment_count.apply(np.log1p) train["publishedAt"] = pd.to_datetime(train.publishedAt).apply(lambda x: x.value) test["publishedAt"] = pd.to_datetime(test.publishedAt).apply(lambda x: x.value) train["title_len"] = train.title.apply(lambda x: len(str(x))) test["title_len"] = test.title.apply(lambda x: len(str(x))) train["channelTitle_len"] = train.channelTitle.apply(lambda x: len(str(x))) test["channelTitle_len"] = test.channelTitle.apply(lambda x: len(str(x))) train["description_len"] = train.description.apply(lambda x: len(str(x))) test["description_len"] = test.description.apply(lambda x: len(str(x))) train["tags_count"] = train.tags.apply(lambda x: str(x).count("|")) test["tags_count"] = test.tags.apply(lambda x: str(x).count("|")) # 日本語を含むかかどうかの判定 train["title_ja_count"] = train.title.apply(data_frame.is_japanese) test["title_ja_count"] = test.title.apply(data_frame.is_japanese) train["channelTitle_ja_count"] = train.channelTitle.apply(data_frame.is_japanese) test["channelTitle_ja_count"] = test.channelTitle.apply(data_frame.is_japanese) train["description_ja_count"] = train.description.apply(data_frame.is_japanese) test["description_ja_count"] = test.description.apply(data_frame.is_japanese) # アルファベットのカウント train["title_en_count"] = train.title.apply(data_frame.count_alphabet) test["title_en_count"] = test.title.apply(data_frame.count_alphabet) train["channelTitle_en_count"] = train.channelTitle.apply(data_frame.count_alphabet) test["channelTitle_en_count"] = test.channelTitle.apply(data_frame.count_alphabet) train["description_en_count"] = train.description.apply(data_frame.count_alphabet) test["description_en_count"] = test.description.apply(data_frame.count_alphabet) # 数字のカウント train["description_num_count"] = train.description.apply(data_frame.count_number) test["description_num_count"] = test.description.apply(data_frame.count_number) # urlのカウント train["description_url_count"] = train.description.apply(lambda x: str(x).count("://")) test["description_url_count"] = test.description.apply(lambda x: str(x).count("://")) all_df: pd.DataFrame = pd.concat( [train.drop(["likes", "dislikes"], axis=1), test], ignore_index=True).reset_index(drop=True) category = ["channelId", "categoryId", "collection_date"] target_list = ["likes", "dislikes", "title_len", "channelTitle_len", "description_len", "tags_count", "description_ja_count", "description_en_count", "title_ja_count", "title_en_count", "publishedAt"] for col, target in product(category, target_list): data_frame.group(train, test, col, target, all_df) data_frame.TE(train, test, "mean", train.comment_count, ["categoryId", "collection_date"]) data_frame.TE(train, test, "std", train.comment_count, ["categoryId", "collection_date"]) return train, test def rating_main(): train, test = rating_dataset() drop_list = ["id", "video_id", "title", "channelId", "channelTitle", "tags", "thumbnail_link", "description"] ids = test.video_id train_y_likes = train["likes"] train_y_dislikes = train["dislikes"] train_x = train.drop(drop_list + ["likes", "dislikes"], axis=1) test_x = test.drop(drop_list, axis=1) ensemble(train_x, train_y_likes, test_x, ids, "likes") ensemble(train_x, train_y_dislikes, test_x, ids, "dislikes") # return train_x, train_y_likes, train_y_dislikes, test_x, ids def comment_main(): train, test = comment_dataset() drop_list = ["id", "video_id", "title", "channelId", "channelTitle", "tags", "thumbnail_link", "description"] ids = test.video_id train_y = train["comment_count"] train_x = train.drop(drop_list + ["comment_count"], axis=1) test_x = test.drop(drop_list, axis=1) ensemble(train_x, train_y, test_x, ids, "comment") # return train_x, train_y_likes, train_y_dislikes, test_x, ids params = { 'objective': 'mean_squared_error', # 'max_depth': 6, 'learning_rate': 0.1, "boosting_type": "gbdt", "metric": 'rmse', 'lambda_l1': 2.94393343297745e-08, 'lambda_l2': 0.00010003095098613326, 'num_leaves': 31, 'feature_fraction': 0.5, 'bagging_fraction': 0.8176254967309975, 'bagging_freq': 1, 'min_child_samples': 5, 'random_state': 0, 'early_stopping_rounds': 200, 'n_estimators': 50000, } def ensemble(train_x, train_y, test_x, ids, name): preds_train = [] preds_test = [] drop_null = set(test_x.keys()[test_x.isna().any()].to_list() + train_x.keys()[train_x.isna().any()].to_list()) drop_list = ["publishedAt", "categoryId", "collection_date"] + list(drop_null) train_x = train_x.drop(drop_list, axis=1) test_x = test_x.drop(drop_list, axis=1) for i in range(5): # pred_train, pred_test = learn_sklearn.main(train_x, train_y, test_x, ids, i) params["random_state"] = i pred_train, pred_test = learn_lgb.predict_cv(params, train_x, train_y, test_x, seed=i) preds_train.append(pred_train) preds_test.append(pred_test) pred_train = np.mean(preds_train, axis=0) pred_test = np.mean(preds_test, axis=0) learn_lgb.output_metrics(train_y, pred_train) learn_lgb.output_metrics(np.expm1(train_y), np.expm1(pred_train)) sub = pd.DataFrame() sub["video_id"] = ids sub['y'] = np.expm1(pred_test) sub.to_csv(f'./data/input/complement_{name}.csv', index=False)

45.706383

114

0.701983

1,478

10,741

4.841678

0.112314

0.046534

0.054779

0.042482

0.805757

0.785914

0.765651

0.74986

0.742594

0

0.011105

0.144865

10,741

234

115

45.901709

0.767991

0.069826

0

0.535714

0

0.211693

0.04984

0

1

0.029762

false

0

0.059524

0

0.10119

0.005952

0

null

0

1

0

null

0

6

83c56e6865214f8954cb512a3f76b04cefd56e51

114

py

Python

spa/static/__init__.py

btubbs/spa

9e14986a1e6a079dfeaf1b0b0c83d749cf38dd54

[ "BSD-3-Clause" ]

14

2015-06-05T19:29:20.000Z

2021-05-07T15:02:56.000Z

spa/static/__init__.py

btubbs/spa

9e14986a1e6a079dfeaf1b0b0c83d749cf38dd54

[ "BSD-3-Clause" ]

5

2015-06-20T17:53:24.000Z

2015-12-14T20:50:24.000Z

spa/static/__init__.py

btubbs/spa

9e14986a1e6a079dfeaf1b0b0c83d749cf38dd54

[ "BSD-3-Clause" ]

3

2015-05-29T09:21:08.000Z

2015-08-06T12:06:22.000Z

from spa.static.handlers import Static, StaticHandler, StaticFileHandler from spa.static.smart import SmartStatic

38

72

0.859649

14

114

7

0.642857

0.142857

0.265306

0

0.087719

114

2

73

57

0.942308

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

f7ba313d0ea9a997702b9b07d4bdfb2ead122f3d

21,171

py

Python

tests/environments/execution/test_fargate_task_environment.py

trapped/prefect

128f11570c35e7156d65ba65fdcbc1f4ccd7c2b7

[ "Apache-2.0" ]

null

tests/environments/execution/test_fargate_task_environment.py

trapped/prefect

128f11570c35e7156d65ba65fdcbc1f4ccd7c2b7

[ "Apache-2.0" ]

null

tests/environments/execution/test_fargate_task_environment.py

trapped/prefect

128f11570c35e7156d65ba65fdcbc1f4ccd7c2b7

[ "Apache-2.0" ]

null

import os import tempfile from unittest.mock import MagicMock import cloudpickle import prefect from prefect.environments import FargateTaskEnvironment from prefect.environments.storage import Docker from prefect.utilities.configuration import set_temporary_config from botocore.exceptions import ClientError def test_create_fargate_task_environment(): environment = FargateTaskEnvironment() assert environment assert environment.labels == set() assert environment.on_start is None assert environment.on_exit is None assert environment.logger.name == "prefect.FargateTaskEnvironment" def test_create_fargate_task_environment_labels(): environment = FargateTaskEnvironment(labels=["foo"]) assert environment assert environment.labels == set(["foo"]) def test_create_fargate_task_environment_callbacks(): def f(): pass environment = FargateTaskEnvironment(labels=["foo"], on_start=f, on_exit=f) assert environment assert environment.labels == set(["foo"]) assert environment.on_start is f assert environment.on_exit is f def test_fargate_task_environment_dependencies(): environment = FargateTaskEnvironment() assert environment.dependencies == ["boto3", "botocore"] def test_create_fargate_task_environment_aws_creds_provided(): environment = FargateTaskEnvironment( labels=["foo"], aws_access_key_id="id", aws_secret_access_key="secret", aws_session_token="session", region_name="region", ) assert environment assert environment.labels == set(["foo"]) assert environment.aws_access_key_id == "id" assert environment.aws_secret_access_key == "secret" assert environment.aws_session_token == "session" assert environment.region_name == "region" def test_create_fargate_task_environment_aws_creds_environment(monkeypatch): monkeypatch.setenv("AWS_ACCESS_KEY_ID", "id") monkeypatch.setenv("AWS_SECRET_ACCESS_KEY", "secret") monkeypatch.setenv("AWS_SESSION_TOKEN", "session") monkeypatch.setenv("REGION_NAME", "region") environment = FargateTaskEnvironment(labels=["foo"]) assert environment assert environment.labels == set(["foo"]) assert environment.aws_access_key_id == "id" assert environment.aws_secret_access_key == "secret" assert environment.aws_session_token == "session" assert environment.region_name == "region" def test_parse_task_definition_kwargs(): environment = FargateTaskEnvironment() kwarg_dict = { "family": "test", "taskRoleArn": "test", "executionRoleArn": "test", "networkMode": "test", "containerDefinitions": "test", "volumes": "test", "placementConstraints": "test", "requiresCompatibilities": "test", "cpu": "test", "memory": "test", "tags": "test", "pidMode": "test", "ipcMode": "test", "proxyConfiguration": "test", "inferenceAccelerators": "test", } task_definition_kwargs, task_run_kwargs = environment._parse_kwargs(kwarg_dict) assert task_definition_kwargs == kwarg_dict assert task_run_kwargs == {"placementConstraints": "test", "tags": "test"} def test_parse_task_run_kwargs(): environment = FargateTaskEnvironment() kwarg_dict = { "cluster": "test", "taskDefinition": "test", "count": "test", "startedBy": "test", "group": "test", "placementConstraints": "test", "placementStrategy": "test", "platformVersion": "test", "networkConfiguration": "test", "tags": "test", "enableECSManagedTags": "test", "propagateTags": "test", } task_definition_kwargs, task_run_kwargs = environment._parse_kwargs(kwarg_dict) assert task_run_kwargs == kwarg_dict assert task_definition_kwargs == {"placementConstraints": "test", "tags": "test"} def test_parse_task_definition_and_run_kwargs(): environment = FargateTaskEnvironment() def_kwarg_dict = { "family": "test", "taskRoleArn": "test", "executionRoleArn": "test", "networkMode": "test", "containerDefinitions": "test", "volumes": "test", "placementConstraints": "test", "requiresCompatibilities": "test", "cpu": "test", "memory": "test", "tags": "test", "pidMode": "test", "ipcMode": "test", "proxyConfiguration": "test", "inferenceAccelerators": "test", } run_kwarg_dict = { "cluster": "test", "taskDefinition": "test", "count": "test", "startedBy": "test", "group": "test", "placementConstraints": "test", "placementStrategy": "test", "platformVersion": "test", "networkConfiguration": "test", "tags": "test", "enableECSManagedTags": "test", "propagateTags": "test", } kwarg_dict = { "family": "test", "taskRoleArn": "test", "executionRoleArn": "test", "networkMode": "test", "containerDefinitions": "test", "volumes": "test", "placementConstraints": "test", "requiresCompatibilities": "test", "cpu": "test", "memory": "test", "tags": "test", "pidMode": "test", "ipcMode": "test", "proxyConfiguration": "test", "inferenceAccelerators": "test", "cluster": "test", "taskDefinition": "test", "count": "test", "startedBy": "test", "group": "test", "placementStrategy": "test", "platformVersion": "test", "networkConfiguration": "test", "enableECSManagedTags": "test", "propagateTags": "test", } task_definition_kwargs, task_run_kwargs = environment._parse_kwargs(kwarg_dict) assert task_definition_kwargs == def_kwarg_dict assert task_run_kwargs == run_kwarg_dict def test_parse_task_kwargs_invalid_value_removed(): environment = FargateTaskEnvironment() kwarg_dict = {"test": "not_real"} task_definition_kwargs, task_run_kwargs = environment._parse_kwargs(kwarg_dict) assert task_definition_kwargs == {} assert task_run_kwargs == {} def test_setup_definition_exists(monkeypatch): boto3_client = MagicMock() boto3_client.describe_task_definition.return_value = {} monkeypatch.setattr("boto3.client", MagicMock(return_value=boto3_client)) environment = FargateTaskEnvironment() environment.setup(Docker(registry_url="test", image_name="image", image_tag="tag")) assert boto3_client.describe_task_definition.called def test_setup_definition_register(monkeypatch): boto3_client = MagicMock() boto3_client.describe_task_definition.side_effect = ClientError({}, None) boto3_client.register_task_definition.return_value = {} monkeypatch.setattr("boto3.client", MagicMock(return_value=boto3_client)) environment = FargateTaskEnvironment( family="test", containerDefinitions=[ { "name": "flow-container", "image": "image", "command": [], "environment": [], "essential": True, } ], ) environment.setup(Docker(registry_url="test", image_name="image", image_tag="tag")) assert boto3_client.describe_task_definition.called assert boto3_client.register_task_definition.called assert boto3_client.register_task_definition.call_args[1]["family"] == "test" assert boto3_client.register_task_definition.call_args[1][ "containerDefinitions" ] == [ { "name": "flow-container", "image": "test/image:tag", "command": [ "/bin/sh", "-c", "python -c 'import prefect; prefect.Flow.load(prefect.context.flow_file_path).environment.run_flow()'", ], "environment": [ { "name": "PREFECT__CLOUD__GRAPHQL", "value": prefect.config.cloud.graphql, }, {"name": "PREFECT__CLOUD__USE_LOCAL_SECRETS", "value": "false"}, { "name": "PREFECT__ENGINE__FLOW_RUNNER__DEFAULT_CLASS", "value": "prefect.engine.cloud.CloudFlowRunner", }, { "name": "PREFECT__ENGINE__TASK_RUNNER__DEFAULT_CLASS", "value": "prefect.engine.cloud.CloudTaskRunner", }, {"name": "PREFECT__LOGGING__LOG_TO_CLOUD", "value": "true"}, ], "essential": True, } ] def test_setup_definition_register_no_defintions(monkeypatch): boto3_client = MagicMock() boto3_client.describe_task_definition.side_effect = ClientError({}, None) boto3_client.register_task_definition.return_value = {} monkeypatch.setattr("boto3.client", MagicMock(return_value=boto3_client)) environment = FargateTaskEnvironment(family="test") environment.setup(Docker(registry_url="test", image_name="image", image_tag="tag")) assert boto3_client.describe_task_definition.called assert boto3_client.register_task_definition.called assert boto3_client.register_task_definition.call_args[1]["family"] == "test" assert boto3_client.register_task_definition.call_args[1][ "containerDefinitions" ] == [ { "environment": [ { "name": "PREFECT__CLOUD__GRAPHQL", "value": prefect.config.cloud.graphql, }, {"name": "PREFECT__CLOUD__USE_LOCAL_SECRETS", "value": "false"}, { "name": "PREFECT__ENGINE__FLOW_RUNNER__DEFAULT_CLASS", "value": "prefect.engine.cloud.CloudFlowRunner", }, { "name": "PREFECT__ENGINE__TASK_RUNNER__DEFAULT_CLASS", "value": "prefect.engine.cloud.CloudTaskRunner", }, {"name": "PREFECT__LOGGING__LOG_TO_CLOUD", "value": "true"}, ], "name": "flow-container", "image": "test/image:tag", "command": [ "/bin/sh", "-c", "python -c 'import prefect; prefect.Flow.load(prefect.context.flow_file_path).environment.run_flow()'", ], } ] def test_execute_run_task(monkeypatch): boto3_client = MagicMock() boto3_client.run_task.return_value = {} monkeypatch.setattr("boto3.client", MagicMock(return_value=boto3_client)) with set_temporary_config({"cloud.auth_token": "test"}): environment = FargateTaskEnvironment( cluster="test", family="test", taskDefinition="test" ) environment.execute( storage=Docker(registry_url="test", image_name="image", image_tag="tag"), flow_location=".prefect/flows", ) assert boto3_client.run_task.called assert boto3_client.run_task.call_args[1]["taskDefinition"] == "test" assert boto3_client.run_task.call_args[1]["overrides"] == { "containerOverrides": [ { "name": "flow-container", "environment": [ { "name": "PREFECT__CLOUD__AUTH_TOKEN", "value": prefect.config.cloud.get("auth_token"), }, {"name": "PREFECT__CONTEXT__FLOW_RUN_ID", "value": "unknown"}, {"name": "PREFECT__CONTEXT__IMAGE", "value": "test/image:tag"}, { "name": "PREFECT__CONTEXT__FLOW_FILE_PATH", "value": ".prefect/flows", }, ], } ] } assert boto3_client.run_task.call_args[1]["launchType"] == "FARGATE" assert boto3_client.run_task.call_args[1]["cluster"] == "test" def test_execute_run_task_agent_token(monkeypatch): boto3_client = MagicMock() boto3_client.run_task.return_value = {} monkeypatch.setattr("boto3.client", MagicMock(return_value=boto3_client)) with set_temporary_config({"cloud.agent.auth_token": "test"}): environment = FargateTaskEnvironment( cluster="test", family="test", taskDefinition="test" ) environment.execute( storage=Docker(registry_url="test", image_name="image", image_tag="tag"), flow_location=".prefect/flows", ) assert boto3_client.run_task.called assert boto3_client.run_task.call_args[1]["taskDefinition"] == "test" assert boto3_client.run_task.call_args[1]["overrides"] == { "containerOverrides": [ { "name": "flow-container", "environment": [ { "name": "PREFECT__CLOUD__AUTH_TOKEN", "value": prefect.config.cloud.agent.get("auth_token"), }, {"name": "PREFECT__CONTEXT__FLOW_RUN_ID", "value": "unknown"}, {"name": "PREFECT__CONTEXT__IMAGE", "value": "test/image:tag"}, { "name": "PREFECT__CONTEXT__FLOW_FILE_PATH", "value": ".prefect/flows", }, ], } ] } assert boto3_client.run_task.call_args[1]["launchType"] == "FARGATE" assert boto3_client.run_task.call_args[1]["cluster"] == "test" def test_run_flow(monkeypatch): environment = FargateTaskEnvironment() flow_runner = MagicMock() monkeypatch.setattr( "prefect.engine.get_default_flow_runner_class", MagicMock(return_value=flow_runner), ) with tempfile.TemporaryDirectory() as directory: with open(os.path.join(directory, "flow_env.prefect"), "w+"): flow = prefect.Flow("test") flow_path = os.path.join(directory, "flow_env.prefect") with open(flow_path, "wb") as f: cloudpickle.dump(flow, f) with set_temporary_config({"cloud.auth_token": "test"}): with prefect.context( flow_file_path=os.path.join(directory, "flow_env.prefect") ): environment.run_flow() assert flow_runner.call_args[1]["flow"].name == "test" def test_run_flow_calls_callbacks(monkeypatch): start_func = MagicMock() exit_func = MagicMock() environment = FargateTaskEnvironment(on_start=start_func, on_exit=exit_func) flow_runner = MagicMock() monkeypatch.setattr( "prefect.engine.get_default_flow_runner_class", MagicMock(return_value=flow_runner), ) with tempfile.TemporaryDirectory() as directory: with open(os.path.join(directory, "flow_env.prefect"), "w+"): flow = prefect.Flow("test") flow_path = os.path.join(directory, "flow_env.prefect") with open(flow_path, "wb") as f: cloudpickle.dump(flow, f) with set_temporary_config({"cloud.auth_token": "test"}): with prefect.context( flow_file_path=os.path.join(directory, "flow_env.prefect") ): environment.run_flow() assert flow_runner.call_args[1]["flow"].name == "test" assert start_func.called assert exit_func.called def test_entire_environment_process_together(monkeypatch): boto3_client = MagicMock() boto3_client.describe_task_definition.side_effect = ClientError({}, None) boto3_client.register_task_definition.return_value = {} boto3_client.run_task.return_value = {} monkeypatch.setattr("boto3.client", MagicMock(return_value=boto3_client)) flow_runner = MagicMock() monkeypatch.setattr( "prefect.engine.get_default_flow_runner_class", MagicMock(return_value=flow_runner), ) monkeypatch.setenv("AWS_ACCESS_KEY_ID", "id") monkeypatch.setenv("AWS_SECRET_ACCESS_KEY", "secret") monkeypatch.setenv("AWS_SESSION_TOKEN", "session") monkeypatch.setenv("REGION_NAME", "region") with prefect.context({"flow_run_id": "id"}), set_temporary_config( {"cloud.auth_token": "test"} ): storage = Docker(registry_url="test", image_name="image", image_tag="tag") environment = FargateTaskEnvironment( containerDefinitions=[ { "name": "flow-container", "image": "image", "command": [], "environment": [], "essential": True, } ], cluster="test", family="test", taskDefinition="test", ) assert environment assert environment.aws_access_key_id == "id" assert environment.aws_secret_access_key == "secret" assert environment.aws_session_token == "session" assert environment.region_name == "region" environment.setup(storage=storage) assert boto3_client.describe_task_definition.called assert boto3_client.register_task_definition.called assert boto3_client.register_task_definition.call_args[1]["family"] == "test" assert boto3_client.register_task_definition.call_args[1][ "containerDefinitions" ] == [ { "name": "flow-container", "image": "test/image:tag", "command": [ "/bin/sh", "-c", "python -c 'import prefect; prefect.Flow.load(prefect.context.flow_file_path).environment.run_flow()'", ], "environment": [ { "name": "PREFECT__CLOUD__GRAPHQL", "value": prefect.config.cloud.graphql, }, {"name": "PREFECT__CLOUD__USE_LOCAL_SECRETS", "value": "false"}, { "name": "PREFECT__ENGINE__FLOW_RUNNER__DEFAULT_CLASS", "value": "prefect.engine.cloud.CloudFlowRunner", }, { "name": "PREFECT__ENGINE__TASK_RUNNER__DEFAULT_CLASS", "value": "prefect.engine.cloud.CloudTaskRunner", }, {"name": "PREFECT__LOGGING__LOG_TO_CLOUD", "value": "true"}, ], "essential": True, } ] environment.execute(storage=storage, flow_location=".prefect/flows") assert boto3_client.run_task.called assert boto3_client.run_task.call_args[1]["taskDefinition"] == "test" assert boto3_client.run_task.call_args[1]["overrides"] == { "containerOverrides": [ { "name": "flow-container", "environment": [ { "name": "PREFECT__CLOUD__AUTH_TOKEN", "value": prefect.config.cloud.get("auth_token"), }, {"name": "PREFECT__CONTEXT__FLOW_RUN_ID", "value": "id"}, {"name": "PREFECT__CONTEXT__IMAGE", "value": "test/image:tag"}, { "name": "PREFECT__CONTEXT__FLOW_FILE_PATH", "value": ".prefect/flows", }, ], } ] } assert boto3_client.run_task.call_args[1]["launchType"] == "FARGATE" assert boto3_client.run_task.call_args[1]["cluster"] == "test" with tempfile.TemporaryDirectory() as directory: with open(os.path.join(directory, "flow_env.prefect"), "w+"): flow = prefect.Flow("test") flow_path = os.path.join(directory, "flow_env.prefect") with open(flow_path, "wb") as f: cloudpickle.dump(flow, f) with set_temporary_config({"cloud.auth_token": "test"}): with prefect.context( flow_file_path=os.path.join(directory, "flow_env.prefect") ): environment.run_flow() assert flow_runner.call_args[1]["flow"].name == "test" def test_roundtrip_cloudpickle(): with tempfile.TemporaryDirectory() as directory: with open(os.path.join(directory, "job.yaml"), "w+") as file: file.write("job") environment = FargateTaskEnvironment(cluster="test") assert environment.task_run_kwargs == {"cluster": "test"} new = cloudpickle.loads(cloudpickle.dumps(environment)) assert isinstance(new, FargateTaskEnvironment) assert new.task_run_kwargs == {"cluster": "test"}

35.761824

123

0.586368

1,955

21,171

6.032225

0.087468

0.052234

0.040363

0.027474

0.873739

0.838803

0.820572

0.807343

0.800644

0.781905

0

0.005194

0.290633

21,171

591

124

35.822335

0.780064

0

0.699797

0

0.006085

0.230976

0.077417

0

0.148073

1

0.040568

false

0.002028

0.024341

0

0.064909

0

null

0

1

0

null

0

6

f7ef62793c02b04ad0ace931db793a934399d930

29,059

py

Python

peering/tests/test_api.py

adamgent/peering-manager

46858766cf131da2378010189d13485dec98332f

[ "Apache-2.0" ]

null

peering/tests/test_api.py

adamgent/peering-manager

46858766cf131da2378010189d13485dec98332f

[ "Apache-2.0" ]

null

peering/tests/test_api.py

adamgent/peering-manager

46858766cf131da2378010189d13485dec98332f

[ "Apache-2.0" ]

null

from django.urls import reverse from rest_framework import status from peering.constants import * from peering.models import ( AutonomousSystem, Community, ConfigurationTemplate, DirectPeeringSession, InternetExchange, InternetExchangePeeringSession, Router, RoutingPolicy, ) from utils.testing import APITestCase class StaticChoiceTest(APITestCase): def test_get_static_choice(self): url = reverse( "peering-api:field-choice-detail", kwargs={"pk": "router:platform"} ) response = self.client.get(url, **self.header) self.assertEqual(len(response.data), 6) def test_list_static_choices(self): url = reverse("peering-api:field-choice-list") response = self.client.get(url, **self.header) self.assertEqual(len(response.data), 6) class AutonomousSystemTest(APITestCase): def setUp(self): super().setUp() self.autonomous_system = AutonomousSystem.objects.create( asn=201281, name="Guillaume Mazoyer" ) def test_get_autonomous_system(self): url = reverse( "peering-api:autonomoussystem-detail", kwargs={"pk": self.autonomous_system.pk}, ) response = self.client.get(url, **self.header) self.assertEqual(response.data["asn"], self.autonomous_system.asn) def test_list_autonomous_systems(self): url = reverse("peering-api:autonomoussystem-list") response = self.client.get(url, **self.header) self.assertEqual(response.data["count"], 1) def test_create_autonomous_system(self): data = {"asn": 29467, "name": "LuxNetwork S.A."} url = reverse("peering-api:autonomoussystem-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(AutonomousSystem.objects.count(), 2) autonomous_system = AutonomousSystem.objects.get(pk=response.data["id"]) self.assertEqual(autonomous_system.asn, data["asn"]) def test_create_autonomous_system_bulk(self): data = [{"asn": 15169, "name": "Google"}, {"asn": 32934, "name": "Facebook"}] url = reverse("peering-api:autonomoussystem-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(AutonomousSystem.objects.count(), 3) self.assertEqual(response.data[0]["asn"], data[0]["asn"]) self.assertEqual(response.data[1]["asn"], data[1]["asn"]) def test_update_autonomous_system(self): data = {"asn": 201281, "name": "Guillaume Mazoyer"} url = reverse( "peering-api:autonomoussystem-detail", kwargs={"pk": self.autonomous_system.pk}, ) response = self.client.put(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_200_OK) self.assertEqual(AutonomousSystem.objects.count(), 1) autonomous_system = AutonomousSystem.objects.get(pk=response.data["id"]) self.assertEqual(autonomous_system.asn, data["asn"]) def test_delete_autonomous_system(self): url = reverse( "peering-api:autonomoussystem-detail", kwargs={"pk": self.autonomous_system.pk}, ) response = self.client.delete(url, **self.header) self.assertStatus(response, status.HTTP_204_NO_CONTENT) self.assertEqual(AutonomousSystem.objects.count(), 0) def test_synchronize_with_peeringdb(self): url = reverse( "peering-api:autonomoussystem-synchronize-with-peeringdb", kwargs={"pk": self.autonomous_system.pk}, ) response = self.client.post(url, format="json", **self.header) self.assertStatus(response, status.HTTP_200_OK) def test_common_internet_exchanges(self): url = reverse( "peering-api:autonomoussystem-common-internet-exchanges", kwargs={"pk": self.autonomous_system.pk}, ) response = self.client.get(url, format="json", **self.header) self.assertEqual(response.data["common-internet-exchanges"], []) def test_find_potential_ix_peering_sessions(self): url = reverse( "peering-api:autonomoussystem-find-potential-ix-peering-sessions", kwargs={"pk": self.autonomous_system.pk}, ) response = self.client.patch(url, format="json", **self.header) self.assertStatus(response, status.HTTP_200_OK) class CommunityTest(APITestCase): def setUp(self): super().setUp() self.community = Community.objects.create( name="Test", value="64500:1", type=COMMUNITY_TYPE_EGRESS ) def test_get_community(self): url = reverse("peering-api:community-detail", kwargs={"pk": self.community.pk}) response = self.client.get(url, **self.header) self.assertEqual(response.data["value"], self.community.value) def test_list_communities(self): url = reverse("peering-api:community-list") response = self.client.get(url, **self.header) self.assertEqual(response.data["count"], 1) def test_create_community(self): data = {"name": "Other", "value": "64500:2", "type": COMMUNITY_TYPE_EGRESS} url = reverse("peering-api:community-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(Community.objects.count(), 2) community = Community.objects.get(pk=response.data["id"]) self.assertEqual(community.value, data["value"]) def test_create_community_bulk(self): data = [ {"name": "Test1", "value": "64500:11", "type": COMMUNITY_TYPE_EGRESS}, {"name": "Test2", "value": "64500:12", "type": COMMUNITY_TYPE_EGRESS}, ] url = reverse("peering-api:community-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(Community.objects.count(), 3) self.assertEqual(response.data[0]["value"], data[0]["value"]) self.assertEqual(response.data[1]["value"], data[1]["value"]) def test_update_community(self): data = {"name": "Other", "value": "64500:2", "type": COMMUNITY_TYPE_INGRESS} url = reverse("peering-api:community-detail", kwargs={"pk": self.community.pk}) response = self.client.put(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_200_OK) self.assertEqual(Community.objects.count(), 1) community = Community.objects.get(pk=response.data["id"]) self.assertEqual(community.value, data["value"]) def test_delete_community(self): url = reverse("peering-api:community-detail", kwargs={"pk": self.community.pk}) response = self.client.delete(url, **self.header) self.assertStatus(response, status.HTTP_204_NO_CONTENT) self.assertEqual(Community.objects.count(), 0) class ConfigurationTemplateTest(APITestCase): def setUp(self): super().setUp() self.configuration_template = ConfigurationTemplate.objects.create( name="Test", template="test_template" ) def test_get_configuration_template(self): url = reverse( "peering-api:configurationtemplate-detail", kwargs={"pk": self.configuration_template.pk}, ) response = self.client.get(url, **self.header) self.assertEqual( response.data["template"], self.configuration_template.template ) def test_list_configuration_templates(self): url = reverse("peering-api:configurationtemplate-list") response = self.client.get(url, **self.header) self.assertEqual(response.data["count"], 1) def test_create_configuration_template(self): data = {"name": "Other", "template": "other_template"} url = reverse("peering-api:configurationtemplate-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(ConfigurationTemplate.objects.count(), 2) configuration_template = ConfigurationTemplate.objects.get( pk=response.data["id"] ) self.assertEqual(configuration_template.template, data["template"]) def test_create_configuration_template_bulk(self): data = [ {"name": "Test1", "template": "test1_template"}, {"name": "Test2", "template": "test2_template"}, ] url = reverse("peering-api:configurationtemplate-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(ConfigurationTemplate.objects.count(), 3) self.assertEqual(response.data[0]["template"], data[0]["template"]) self.assertEqual(response.data[1]["template"], data[1]["template"]) def test_update_configuration_template(self): data = {"name": "Test", "template": "updated_template"} url = reverse( "peering-api:configurationtemplate-detail", kwargs={"pk": self.configuration_template.pk}, ) response = self.client.put(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_200_OK) self.assertEqual(ConfigurationTemplate.objects.count(), 1) configuration_template = ConfigurationTemplate.objects.get( pk=response.data["id"] ) self.assertEqual(configuration_template.template, data["template"]) def test_delete_configuration_template(self): url = reverse( "peering-api:configurationtemplate-detail", kwargs={"pk": self.configuration_template.pk}, ) response = self.client.delete(url, **self.header) self.assertStatus(response, status.HTTP_204_NO_CONTENT) self.assertEqual(ConfigurationTemplate.objects.count(), 0) class DirectPeeringSessionTest(APITestCase): def setUp(self): super().setUp() self.autonomous_system = AutonomousSystem.objects.create( asn=201281, name="Guillaume Mazoyer" ) self.direct_peering_session = DirectPeeringSession.objects.create( autonomous_system=self.autonomous_system, relationship=BGP_RELATIONSHIP_PRIVATE_PEERING, ip_address="2001:db8::1", ) def test_get_direct_peering_session(self): url = reverse( "peering-api:directpeeringsession-detail", kwargs={"pk": self.direct_peering_session.pk}, ) response = self.client.get(url, **self.header) self.assertEqual( response.data["ip_address"], self.direct_peering_session.ip_address ) def test_list_direct_peering_sessions(self): url = reverse("peering-api:directpeeringsession-list") response = self.client.get(url, **self.header) self.assertEqual(response.data["count"], 1) def test_create_direct_peering_session(self): data = { "autonomous_system": self.autonomous_system.pk, "relationship": BGP_RELATIONSHIP_PRIVATE_PEERING, "ip_address": "192.168.0.1", } url = reverse("peering-api:directpeeringsession-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(DirectPeeringSession.objects.count(), 2) direct_peering_session = DirectPeeringSession.objects.get( pk=response.data["id"] ) self.assertEqual(direct_peering_session.ip_address, data["ip_address"]) def test_create_direct_peering_session_bulk(self): data = [ { "autonomous_system": self.autonomous_system.pk, "relationship": BGP_RELATIONSHIP_PRIVATE_PEERING, "ip_address": "10.0.0.1", }, { "autonomous_system": self.autonomous_system.pk, "relationship": BGP_RELATIONSHIP_PRIVATE_PEERING, "ip_address": "10.0.0.2", }, ] url = reverse("peering-api:directpeeringsession-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(DirectPeeringSession.objects.count(), 3) self.assertEqual(response.data[0]["ip_address"], data[0]["ip_address"]) self.assertEqual(response.data[1]["ip_address"], data[1]["ip_address"]) def test_update_direct_peering_session(self): data = { "autonomous_system": self.autonomous_system.pk, "relationship": BGP_RELATIONSHIP_PRIVATE_PEERING, "ip_address": "2001:db8::2", } url = reverse( "peering-api:directpeeringsession-detail", kwargs={"pk": self.direct_peering_session.pk}, ) response = self.client.put(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_200_OK) self.assertEqual(DirectPeeringSession.objects.count(), 1) direct_peering_session = DirectPeeringSession.objects.get( pk=response.data["id"] ) self.assertEqual(direct_peering_session.ip_address, data["ip_address"]) def test_delete_direct_peering_session(self): url = reverse( "peering-api:directpeeringsession-detail", kwargs={"pk": self.direct_peering_session.pk}, ) response = self.client.delete(url, **self.header) self.assertStatus(response, status.HTTP_204_NO_CONTENT) self.assertEqual(DirectPeeringSession.objects.count(), 0) class InternetExchangeTest(APITestCase): def setUp(self): super().setUp() self.internet_exchange = InternetExchange.objects.create( name="Test", slug="test" ) def test_get_internet_exchange(self): url = reverse( "peering-api:internetexchange-detail", kwargs={"pk": self.internet_exchange.pk}, ) response = self.client.get(url, **self.header) self.assertEqual(response.data["slug"], self.internet_exchange.slug) def test_list_internet_exchanges(self): url = reverse("peering-api:internetexchange-list") response = self.client.get(url, **self.header) self.assertEqual(response.data["count"], 1) def test_create_internet_exchange(self): data = {"name": "Other", "slug": "other"} url = reverse("peering-api:internetexchange-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(InternetExchange.objects.count(), 2) internet_exchange = InternetExchange.objects.get(pk=response.data["id"]) self.assertEqual(internet_exchange.slug, data["slug"]) def test_create_internet_exchange_bulk(self): data = [{"name": "Test1", "slug": "test1"}, {"name": "Test2", "slug": "test2"}] url = reverse("peering-api:internetexchange-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(InternetExchange.objects.count(), 3) self.assertEqual(response.data[0]["slug"], data[0]["slug"]) self.assertEqual(response.data[1]["slug"], data[1]["slug"]) def test_update_internet_exchange(self): data = {"name": "Test", "slug": "test"} url = reverse( "peering-api:internetexchange-detail", kwargs={"pk": self.internet_exchange.pk}, ) response = self.client.put(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_200_OK) self.assertEqual(InternetExchange.objects.count(), 1) internet_exchange = InternetExchange.objects.get(pk=response.data["id"]) self.assertEqual(internet_exchange.slug, data["slug"]) def test_delete_internet_exchange(self): url = reverse( "peering-api:internetexchange-detail", kwargs={"pk": self.internet_exchange.pk}, ) response = self.client.delete(url, **self.header) self.assertStatus(response, status.HTTP_204_NO_CONTENT) self.assertEqual(InternetExchange.objects.count(), 0) def test_available_peers(self): url = reverse( "peering-api:internetexchange-available-peers", kwargs={"pk": self.internet_exchange.pk}, ) response = self.client.get(url, **self.header) self.assertStatus(response, status.HTTP_503_SERVICE_UNAVAILABLE) def test_configuration(self): url = reverse( "peering-api:internetexchange-configuration", kwargs={"pk": self.internet_exchange.pk}, ) response = self.client.get(url, **self.header) self.assertStatus(response, status.HTTP_200_OK) self.assertEqual(response.data["configuration"], "") def test_import_peering_sessions(self): url = reverse( "peering-api:internetexchange-import-peering-sessions", kwargs={"pk": self.internet_exchange.pk}, ) response = self.client.post(url, **self.header) self.assertStatus(response, status.HTTP_503_SERVICE_UNAVAILABLE) def test_prefixes(self): url = reverse( "peering-api:internetexchange-prefixes", kwargs={"pk": self.internet_exchange.pk}, ) response = self.client.get(url, **self.header) self.assertStatus(response, status.HTTP_200_OK) self.assertEqual(response.data["prefixes"], []) def test_configure_router(self): url = reverse( "peering-api:internetexchange-configure-router", kwargs={"pk": self.internet_exchange.pk}, ) response = self.client.get(url, **self.header) self.assertStatus(response, status.HTTP_503_SERVICE_UNAVAILABLE) response = self.client.post(url, **self.header) self.assertStatus(response, status.HTTP_503_SERVICE_UNAVAILABLE) def test_update_peering_sessions(self): url = reverse( "peering-api:internetexchange-update-peering-sessions", kwargs={"pk": self.internet_exchange.pk}, ) response = self.client.post(url, **self.header) self.assertStatus(response, status.HTTP_503_SERVICE_UNAVAILABLE) class InternetExchangePeeringSessionTest(APITestCase): def setUp(self): super().setUp() self.autonomous_system = AutonomousSystem.objects.create( asn=201281, name="Guillaume Mazoyer" ) self.internet_exchange = InternetExchange.objects.create( name="Test", slug="test" ) self.internet_exchange_peering_session = InternetExchangePeeringSession.objects.create( autonomous_system=self.autonomous_system, internet_exchange=self.internet_exchange, ip_address="2001:db8::1", ) def test_get_internet_exchange_peering_session(self): url = reverse( "peering-api:internetexchangepeeringsession-detail", kwargs={"pk": self.internet_exchange_peering_session.pk}, ) response = self.client.get(url, **self.header) self.assertEqual( response.data["ip_address"], self.internet_exchange_peering_session.ip_address, ) def test_list_internet_exchange_peering_sessions(self): url = reverse("peering-api:internetexchangepeeringsession-list") response = self.client.get(url, **self.header) self.assertEqual(response.data["count"], 1) def test_create_internet_exchange_peering_session(self): data = { "autonomous_system": self.autonomous_system.pk, "internet_exchange": self.internet_exchange.pk, "ip_address": "192.168.0.1", } url = reverse("peering-api:internetexchangepeeringsession-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(InternetExchangePeeringSession.objects.count(), 2) internet_exchange_peering_session = InternetExchangePeeringSession.objects.get( pk=response.data["id"] ) self.assertEqual( internet_exchange_peering_session.ip_address, data["ip_address"] ) def test_create_internet_exchange_peering_session_bulk(self): data = [ { "autonomous_system": self.autonomous_system.pk, "internet_exchange": self.internet_exchange.pk, "ip_address": "10.0.0.1", }, { "autonomous_system": self.autonomous_system.pk, "internet_exchange": self.internet_exchange.pk, "ip_address": "10.0.0.2", }, ] url = reverse("peering-api:internetexchangepeeringsession-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(InternetExchangePeeringSession.objects.count(), 3) self.assertEqual(response.data[0]["ip_address"], data[0]["ip_address"]) self.assertEqual(response.data[1]["ip_address"], data[1]["ip_address"]) def test_update_internet_exchange_peering_session(self): data = { "autonomous_system": self.autonomous_system.pk, "internet_exchange": self.internet_exchange.pk, "ip_address": "2001:db8::2", } url = reverse( "peering-api:internetexchangepeeringsession-detail", kwargs={"pk": self.internet_exchange_peering_session.pk}, ) response = self.client.put(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_200_OK) self.assertEqual(InternetExchangePeeringSession.objects.count(), 1) internet_exchange_peering_session = InternetExchangePeeringSession.objects.get( pk=response.data["id"] ) self.assertEqual( internet_exchange_peering_session.ip_address, data["ip_address"] ) def test_delete_internet_exchange_peering_session(self): url = reverse( "peering-api:internetexchangepeeringsession-detail", kwargs={"pk": self.internet_exchange_peering_session.pk}, ) response = self.client.delete(url, **self.header) self.assertStatus(response, status.HTTP_204_NO_CONTENT) self.assertEqual(InternetExchangePeeringSession.objects.count(), 0) class RouterTest(APITestCase): def setUp(self): super().setUp() self.router = Router.objects.create( name="Test", hostname="test.example.com", platform=PLATFORM_JUNOS ) def test_get_router(self): url = reverse("peering-api:router-detail", kwargs={"pk": self.router.pk}) response = self.client.get(url, **self.header) self.assertEqual(response.data["hostname"], self.router.hostname) def test_list_routers(self): url = reverse("peering-api:router-list") response = self.client.get(url, **self.header) self.assertEqual(response.data["count"], 1) def test_create_router(self): data = { "name": "Other", "hostname": "other.example.com", "platform": PLATFORM_JUNOS, } url = reverse("peering-api:router-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(Router.objects.count(), 2) router = Router.objects.get(pk=response.data["id"]) self.assertEqual(router.hostname, data["hostname"]) def test_create_router_bulk(self): data = [ { "name": "Test1", "hostname": "test1.example.com", "platform": PLATFORM_JUNOS, }, { "name": "Test2", "hostname": "test2.example.com", "platform": PLATFORM_JUNOS, }, ] url = reverse("peering-api:router-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(Router.objects.count(), 3) self.assertEqual(response.data[0]["hostname"], data[0]["hostname"]) self.assertEqual(response.data[1]["hostname"], data[1]["hostname"]) def test_update_router(self): data = { "name": "Test", "hostname": "test.example.com", "platform": PLATFORM_IOSXR, } url = reverse("peering-api:router-detail", kwargs={"pk": self.router.pk}) response = self.client.put(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_200_OK) self.assertEqual(Router.objects.count(), 1) router = Router.objects.get(pk=response.data["id"]) self.assertEqual(router.hostname, data["hostname"]) def test_delete_router(self): url = reverse("peering-api:router-detail", kwargs={"pk": self.router.pk}) response = self.client.delete(url, **self.header) self.assertStatus(response, status.HTTP_204_NO_CONTENT) self.assertEqual(Router.objects.count(), 0) def test_test_napalm_connection(self): url = reverse( "peering-api:router-test-napalm-connection", kwargs={"pk": self.router.pk} ) response = self.client.get(url, **self.header) self.assertStatus(response, status.HTTP_503_SERVICE_UNAVAILABLE) class RoutingPolicyTest(APITestCase): def setUp(self): super().setUp() self.routing_policy = RoutingPolicy.objects.create( name="Test", slug="test", type=ROUTING_POLICY_TYPE_EXPORT ) def test_get_routing_policy(self): url = reverse( "peering-api:routingpolicy-detail", kwargs={"pk": self.routing_policy.pk} ) response = self.client.get(url, **self.header) self.assertEqual(response.data["slug"], self.routing_policy.slug) def test_list_routing_policies(self): url = reverse("peering-api:routingpolicy-list") response = self.client.get(url, **self.header) self.assertEqual(response.data["count"], 1) def test_create_routing_policy(self): data = {"name": "Other", "slug": "other", "type": ROUTING_POLICY_TYPE_EXPORT} url = reverse("peering-api:routingpolicy-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(RoutingPolicy.objects.count(), 2) routing_policy = RoutingPolicy.objects.get(pk=response.data["id"]) self.assertEqual(routing_policy.slug, data["slug"]) def test_create_routing_policy_bulk(self): data = [ {"name": "Test1", "slug": "test1", "type": ROUTING_POLICY_TYPE_EXPORT}, {"name": "Test2", "slug": "test2", "type": ROUTING_POLICY_TYPE_EXPORT}, ] url = reverse("peering-api:routingpolicy-list") response = self.client.post(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_201_CREATED) self.assertEqual(RoutingPolicy.objects.count(), 3) self.assertEqual(response.data[0]["slug"], data[0]["slug"]) self.assertEqual(response.data[1]["slug"], data[1]["slug"]) def test_update_routing_policy(self): data = {"name": "Test", "slug": "test", "type": ROUTING_POLICY_TYPE_IMPORT} url = reverse( "peering-api:routingpolicy-detail", kwargs={"pk": self.routing_policy.pk} ) response = self.client.put(url, data, format="json", **self.header) self.assertStatus(response, status.HTTP_200_OK) self.assertEqual(RoutingPolicy.objects.count(), 1) routing_policy = RoutingPolicy.objects.get(pk=response.data["id"]) self.assertEqual(routing_policy.type, data["type"]) def test_delete_routing_policy(self): url = reverse( "peering-api:routingpolicy-detail", kwargs={"pk": self.routing_policy.pk} ) response = self.client.delete(url, **self.header) self.assertStatus(response, status.HTTP_204_NO_CONTENT) self.assertEqual(RoutingPolicy.objects.count(), 0)

39.057796

95

0.643209

3,112

29,059

5.848008

0.049807

0.070059

0.060333

0.065938

0.885873

0.823287

0.792681

0.757954

0.734326

0.70905

0

0.015497

0.224991

29,059

743

96

39.110363

0.792594

0

0.552941

0

0.139234

0.076396

0

0.213445

1

0.114286

false

0

0.013445

0

0.142857

0

null

0

1

0

null

0

6

79169b5cb801edc7c206eba43dd90f933f65461d

76

py

Python

src/lib/kombi/TaskHolder/Dispatcher/Local/__init__.py

paulondc/chilopoda

046dbb0c1b4ff20ea5f2e1679f8d89f3089b6aa4

[ "MIT" ]

2

2019-09-24T18:56:27.000Z

2021-02-07T04:58:49.000Z

src/lib/kombi/TaskHolder/Dispatcher/Local/__init__.py

paulondc/kombi

046dbb0c1b4ff20ea5f2e1679f8d89f3089b6aa4

[ "MIT" ]

20

2019-02-16T04:21:13.000Z

2019-03-09T21:21:21.000Z

src/lib/kombi/TaskHolder/Dispatcher/Local/__init__.py

paulondc/kombi

046dbb0c1b4ff20ea5f2e1679f8d89f3089b6aa4

[ "MIT" ]

3

2019-11-15T05:16:32.000Z

2021-09-28T21:28:29.000Z

from .LocalDispatcher import LocalDispatcher, LocalDispatcherExecutionError

38

75

0.907895

5

76

13.8

0.8

0

0.065789

76

1

76

0.971831

0

1

0

true

0

1

0

1

0

1

0

1

null

0

1

0

null

0

1

0

1

0

1

0

6

792401234e894fa2658b87004196cc67e02d7771

39

py

Python

src/workshop2022/background/__init__.py

VladimirMakhanov/workshop2022

421ca87fc86f99955083c7103efba540dd7765af

[ "MIT" ]

null

src/workshop2022/background/__init__.py

VladimirMakhanov/workshop2022

421ca87fc86f99955083c7103efba540dd7765af

[ "MIT" ]

null

src/workshop2022/background/__init__.py

VladimirMakhanov/workshop2022

421ca87fc86f99955083c7103efba540dd7765af

[ "MIT" ]

2

2022-02-02T14:12:29.000Z

2022-02-10T17:51:24.000Z

from .app import BackgroundApplication

19.5

38

0.871795

4

39

8.5

1

0

0.102564

39

1

39

0.971429

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

f70802eb0367315e5902b750a11bf191194df1bf

41

py

Python

tools/uniqprimer/uniqprimer/test.py

InternationalRiceResearchInstitute/RiceGalaxy

35083ed17d59ae91e622613587228d3f7ae7d794

[ "CC-BY-3.0" ]

4

2018-10-29T18:34:38.000Z

2021-09-29T23:30:42.000Z

tools/uniqprimer/uniqprimer/test.py

InternationalRiceResearchInstitute/RiceGalaxy

35083ed17d59ae91e622613587228d3f7ae7d794

[ "CC-BY-3.0" ]

null

tools/uniqprimer/uniqprimer/test.py

InternationalRiceResearchInstitute/RiceGalaxy

35083ed17d59ae91e622613587228d3f7ae7d794

[ "CC-BY-3.0" ]

3

2020-02-12T15:22:24.000Z

2021-08-19T10:27:39.000Z

#!/usr/bin/python from Bio import SeqIO

10.25

21

0.731707

7

41

4.285714

1

0

0.146341

41

3

22

13.666667

0.857143

0.390244

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6