xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

da0eb7121970c719157241f0e3005acdbf721883

202

py

Python

grax/__main__.py

jackd/grax

99baaea786c59c1f5fe4314ba26d04b9a69499d6

[ "Apache-2.0" ]

6

2021-02-18T08:21:02.000Z

2021-07-29T09:09:30.000Z

grax/__main__.py

jackd/grax

99baaea786c59c1f5fe4314ba26d04b9a69499d6

[ "Apache-2.0" ]

null

grax/__main__.py

jackd/grax

99baaea786c59c1f5fe4314ba26d04b9a69499d6

[ "Apache-2.0" ]

null

import huf.cli from absl import app import grax.config # pylint: disable=unused-import import grax.huf_utils # pylint: disable=unused-import if __name__ == "__main__": app.run(huf.cli.app_main)

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da49dc40829c326e4f8dae04904f108dc74b5fbe

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py

Python

delayed_assert/__init__.py

pr4bh4sh/python-delayedssert

b1be71fa0a9714f4a1e7ff669264c8047aba2f1e

[ "Unlicense" ]

20

2019-08-02T12:42:40.000Z

2022-01-07T11:53:26.000Z

delayed_assert/__init__.py

pr4bh4sh/python-delayedssert

b1be71fa0a9714f4a1e7ff669264c8047aba2f1e

[ "Unlicense" ]

16

2019-08-27T12:19:30.000Z

2022-01-07T14:05:54.000Z

delayed_assert/__init__.py

pr4bh4sh/python-delayedssert

b1be71fa0a9714f4a1e7ff669264c8047aba2f1e

[ "Unlicense" ]

6

2019-10-09T19:05:38.000Z

2021-09-17T15:36:10.000Z

from .delayed_assert import expect, assert_expectations

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16f4e800765c56c3f2aef3526d0b5a702e0bc3d9

152

py

Python

src_nlp/tensorflow/toward_control/data/imdb/__init__.py

ashishpatel26/finch

bf2958c0f268575e5d51ad08fbc08b151cbea962

[ "MIT" ]

1

2019-02-12T09:22:00.000Z

src_nlp/tensorflow/toward_control/data/imdb/__init__.py

loopzxl/finch

bf2958c0f268575e5d51ad08fbc08b151cbea962

[ "MIT" ]

null

src_nlp/tensorflow/toward_control/data/imdb/__init__.py

loopzxl/finch

bf2958c0f268575e5d51ad08fbc08b151cbea962

[ "MIT" ]

1

2020-10-15T21:34:17.000Z

from .vae_pipeline import VAEDataLoader from .wake_sleep_pipeline import WakeSleepDataLoader from .discriminator_pipeline import DiscriminatorDataLoader

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6

e56ce7a5da79ae9108f2d4441d4d0e5928aa2093

109

py

Python

lightRaven/utils/__init__.py

M0gician/lightRaven

edcaed1ffbfab95064fc2719f2e3f79375ce6f04

[ "MIT" ]

1

2020-12-16T07:41:44.000Z

lightRaven/utils/__init__.py

M0gician/lightRaven

edcaed1ffbfab95064fc2719f2e3f79375ce6f04

[ "MIT" ]

null

lightRaven/utils/__init__.py

M0gician/lightRaven

edcaed1ffbfab95064fc2719f2e3f79375ce6f04

[ "MIT" ]

null

from .data_gen import generate_dataset, get_theta_perf, get_policy_perf from .safety_test import safety_test

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6

e5765b7f6c03edbfc1edb0c24c8cdbf8ff228236

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py

Python

advanced_led_control/models/leds.py

weshouman/advanced_led_control

ecf9bd74cee90d7a6a94455adde9308a4c4f48bb

[ "MIT" ]

null

advanced_led_control/models/leds.py

weshouman/advanced_led_control

ecf9bd74cee90d7a6a94455adde9308a4c4f48bb

[ "MIT" ]

null

advanced_led_control/models/leds.py

weshouman/advanced_led_control

ecf9bd74cee90d7a6a94455adde9308a4c4f48bb

[ "MIT" ]

null

LED_1 = 0 LED_2 = 1

6.666667

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6

e5e18dad2158b65c4230a4f93bb3a44e09ef817d

35

py

Python

03_GraphBasedPlanner/graph_ltpl/online_graph/__init__.py

f1tenth/ESweek2021_educationclassA3

7620a36d21c1824efba8a83f0671926bf8e028f3

[ "MIT" ]

15

2021-10-09T13:48:49.000Z

2022-03-27T04:36:44.000Z

03_GraphBasedPlanner/graph_ltpl/online_graph/__init__.py

yinflight/ESweek2021_educationclassA3

7a32bacdb7f3154a773d28b6b6abffdaa154a526

[ "MIT" ]

1

2021-11-27T01:47:25.000Z

2021-11-27T02:44:04.000Z

03_GraphBasedPlanner/graph_ltpl/online_graph/__init__.py

yinflight/ESweek2021_educationclassA3

7a32bacdb7f3154a773d28b6b6abffdaa154a526

[ "MIT" ]

2

2021-11-03T19:32:55.000Z

2021-11-27T02:43:13.000Z

import graph_ltpl.online_graph.src

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e5e45896351155c56dca8c33d5e5b9f3e9411005

139

py

Python

whats_this/bin/pyWhat/what_call.py

roaldi/Whats-This

c98c27b88225094409bff8d2a826f6fba99ffe47

[ "Apache-2.0" ]

null

whats_this/bin/pyWhat/what_call.py

roaldi/Whats-This

c98c27b88225094409bff8d2a826f6fba99ffe47

[ "Apache-2.0" ]

null

whats_this/bin/pyWhat/what_call.py

roaldi/Whats-This

c98c27b88225094409bff8d2a826f6fba99ffe47

[ "Apache-2.0" ]

null

import pyWhat.regex_identifier def export_cli(text): ident = pyWhat.regex_identifier.RegexIdentifier() return ident.check(text)

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6

f900449b614a206da7abbd737b02a52a10cf5d9a

62

py

Python

models/__init__.py

israelvf/snake_game

08932c570b843493aad0473c7d70ecf500344549

[ "MIT" ]

null

models/__init__.py

israelvf/snake_game

08932c570b843493aad0473c7d70ecf500344549

[ "MIT" ]

null

models/__init__.py

israelvf/snake_game

08932c570b843493aad0473c7d70ecf500344549

[ "MIT" ]

null

from models.apple import Apple from models.snake import Snake

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6

005c05ca7972e1118074147ae629deeb87ef83b3

18

py

Python

examples/core/tools/__init__.py

zyh1999/pytorch-quantum

c00bd564a99001fee2fd6b30e5e34562ab981e28

[ "MIT" ]

98

2021-07-23T07:11:32.000Z

2021-12-19T14:04:58.000Z

examples/core/tools/__init__.py

zyh1999/pytorch-quantum

c00bd564a99001fee2fd6b30e5e34562ab981e28

[ "MIT" ]

2

2021-02-11T19:01:48.000Z

2021-04-04T20:29:57.000Z

examples/core/tools/__init__.py

zyh1999/pytorch-quantum

c00bd564a99001fee2fd6b30e5e34562ab981e28

[ "MIT" ]

12

2021-07-23T07:10:47.000Z

2021-12-16T23:44:44.000Z

from .es import *

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6

008b02c0ccf9a8f46721c3ad9ca6bdaccbf51164

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py

Python

tests/asgard/workers/autoscaler/test_decision_component.py

b2wdigital/asgard-api

5444d81be33bf4af3c9cf5a2185c16ff10357034

[ "MIT" ]

3

2020-01-10T02:16:09.000Z

2020-02-19T18:42:37.000Z

tests/asgard/workers/autoscaler/test_decision_component.py

b2wdigital/asgard-api

5444d81be33bf4af3c9cf5a2185c16ff10357034

[ "MIT" ]

13

2020-01-15T18:22:35.000Z

2021-03-31T19:21:54.000Z

tests/asgard/workers/autoscaler/test_decision_component.py

b2wdigital/asgard-api

5444d81be33bf4af3c9cf5a2185c16ff10357034

[ "MIT" ]

6

2020-03-07T09:49:19.000Z

2021-07-25T03:14:10.000Z

from unittest.mock import NonCallableMock from asynctest import TestCase from asgard.workers.autoscaler.decision_events import DecisionEvents from asgard.workers.autoscaler.simple_decision_component import ( DecisionComponent, ) from asgard.workers.models.app_stats import AppStats from asgard.workers.models.scalable_app import ScalableApp class TestDecisionComponent(TestCase): async def test_scales_app_when_difference_greater_than_5_percent(self): apps = [ ScalableApp( "test", cpu_allocated=1.0, mem_allocated=1.0, cpu_threshold=0.5, mem_threshold=0.7, app_stats=AppStats(cpu_usage=0.4499, mem_usage=0.7501), ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(1, len(decisions)) self.assertEqual("test", decisions[0].id) async def test_does_not_scale_app_when_difference_less_than_5_percent(self): apps = [ ScalableApp( "test", cpu_allocated=1.0, mem_allocated=1.0, cpu_threshold=0.5, mem_threshold=0.7, app_stats=AppStats(cpu_usage=0.4501, mem_usage=0.7499), ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(0, len(decisions)) async def test_does_not_make_cpu_decision_when_cpu_is_ignored(self): apps = [ ScalableApp( "test", cpu_allocated=1.0, mem_allocated=1.0, cpu_threshold=None, mem_threshold=0.7, app_stats=AppStats(cpu_usage=0.8, mem_usage=0.3), ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(1, len(decisions), "makes decision for the app only") self.assertEqual("test", decisions[0].id, "returns the correct app") self.assertEqual(None, decisions[0].cpu, "does not return cpu decision") self.assertNotEqual(None, decisions[0].mem, "returns memory decision") async def test_does_not_make_memory_decision_when_memory_is_ignored(self): apps = [ ScalableApp( "test", cpu_allocated=1.0, mem_allocated=1.0, cpu_threshold=0.7, mem_threshold=None, app_stats=AppStats(cpu_usage=0.8, mem_usage=0.3), ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(1, len(decisions), "makes decision for the app only") self.assertEqual("test", decisions[0].id, "returns the correct app") self.assertNotEqual(None, decisions[0].cpu, "returns cpu decision") self.assertEqual( None, decisions[0].mem, "does not return memory decision" ) async def test_does_not_make_any_decision_when_everything_is_ignored(self): apps = [ ScalableApp( "test", cpu_allocated=1.0, mem_allocated=1.0, cpu_threshold=None, mem_threshold=None, app_stats=AppStats(cpu_usage=0.8, mem_usage=0.3), ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(0, len(decisions), "does not return any decisions") async def test_scales_cpu_and_mem_to_correct_value(self): apps = [ ScalableApp( "test1", cpu_allocated=3.5, mem_allocated=1.0, cpu_threshold=0.1, mem_threshold=0.1, app_stats=AppStats(cpu_usage=1.0, mem_usage=1.0), ), ScalableApp( "test2", cpu_allocated=3.5, mem_allocated=1.0, cpu_threshold=0.5, mem_threshold=0.7, app_stats=AppStats(cpu_usage=1.0, mem_usage=1.0), ), ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(2, len(decisions), "makes decisions for both apps") self.assertEqual( "test1", decisions[0].id, "returns correct apps in correct order" ) self.assertEqual( "test2", decisions[1].id, "returns correct apps in correct order" ) self.assertEqual(35, decisions[0].cpu, "decides correct values for cpu") self.assertEqual( 10, decisions[0].mem, "decides correct values for memory" ) self.assertEqual(7, decisions[1].cpu, "decides correct values for cpu") self.assertEqual( 1.4286, round(decisions[1].mem, 4), "decides correct values for memory", ) async def test_scales_memory_to_correct_value(self): apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, mem_threshold=0.2, app_stats=AppStats(cpu_usage=0.4129, mem_usage=0.6262), ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(1, len(decisions), "did not return any decisions") self.assertEqual(400.768, decisions[0].mem) async def test_does_not_scale_cpu_below_min_scale_limit(self): min_cpu_limit = float("inf") max_cpu_limit = float("inf") apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, cpu_threshold=0.6, app_stats=AppStats(cpu_usage=0.4129, mem_usage=0.6262), min_cpu_scale_limit=min_cpu_limit, max_cpu_scale_limit=max_cpu_limit, ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(1, len(decisions), "did not return any decisions") self.assertGreaterEqual( min_cpu_limit, decisions[0].cpu, "cpu value is less than the min limit", ) async def test_does_not_scale_mem_below_min_scale_limit(self): min_mem_limit = float("inf") max_mem_limit = float("inf") apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, mem_threshold=0.5, app_stats=AppStats(cpu_usage=0.4129, mem_usage=0.35), min_mem_scale_limit=min_mem_limit, max_mem_scale_limit=max_mem_limit, ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(1, len(decisions), "did not return any decisions") self.assertGreaterEqual( min_mem_limit, decisions[0].mem, "mem value is less than the min limit", ) async def test_does_not_scale_mem_above_max_scale_limit(self): max_mem_limit = float("-inf") min_mem_limit = float("-inf") apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, mem_threshold=0.5, app_stats=AppStats(cpu_usage=0.4129, mem_usage=0.8), max_mem_scale_limit=max_mem_limit, min_mem_scale_limit=min_mem_limit, ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(1, len(decisions), "did not return any decisions") self.assertLessEqual( max_mem_limit, decisions[0].mem, "mem value is greater than the max limit", ) async def test_does_not_scale_cpu_above_max_scale_limit(self): max_cpu_limit = float("-inf") min_cpu_limit = float("-inf") apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, cpu_threshold=0.2, app_stats=AppStats(cpu_usage=0.4129, mem_usage=0.8), max_cpu_scale_limit=max_cpu_limit, min_cpu_scale_limit=min_cpu_limit, ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(1, len(decisions), "did not return any decisions") self.assertLessEqual( max_cpu_limit, decisions[0].cpu, "cpu value is greater than the max limit", ) async def test_does_not_make_decision_when_app_is_using_min_cpu_and_decision_would_downscale( self ): apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, cpu_threshold=0.75, app_stats=AppStats(cpu_usage=0.1, mem_usage=0.8), min_cpu_scale_limit=0.5, ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(0, len(decisions), "a decision was made") async def test_does_not_make_decision_when_app_is_using_max_cpu_and_decision_would_upscale( self ): apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, cpu_threshold=0.75, app_stats=AppStats(cpu_usage=1.0, mem_usage=0.8), max_cpu_scale_limit=0.5, ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(0, len(decisions), "a decision was made") async def test_does_not_make_decision_when_app_is_using_min_mem_and_decision_would_downscale( self ): apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, mem_threshold=0.75, app_stats=AppStats(cpu_usage=0.1, mem_usage=0.2), min_mem_scale_limit=128, ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(0, len(decisions), "a decision was made") async def test_does_not_make_decision_when_app_is_using_max_mem_and_decision_would_upscale( self ): apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, mem_threshold=0.75, app_stats=AppStats(cpu_usage=0.1, mem_usage=1.0), max_mem_scale_limit=128, ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(0, len(decisions), "a decision was made") async def test_does_not_make_decision_when_there_are_no_stats(self): apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, cpu_threshold=0.2, app_stats=None, ) ] decider = DecisionComponent() decisions = decider.decide_scaling_actions(apps) self.assertEqual(0, len(decisions), "decision was made") async def test_logs_cpu_upscaling_decisions(self): apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, cpu_threshold=0.2, app_stats=AppStats(cpu_usage=1.0, mem_usage=0.1), ) ] mock_logger = NonCallableMock() decider = DecisionComponent(logger=mock_logger) decisions = decider.decide_scaling_actions(apps) mock_logger.info.assert_called() logged_dict = mock_logger.info.call_args[0][0] self.assertIn("appname", logged_dict, "did not log correct app id") self.assertEqual( apps[0].id, logged_dict["appname"], "did not log correct app id" ) self.assertIn("event", logged_dict, "did not log an event") self.assertEqual( DecisionEvents.CPU_SCALE_UP, logged_dict["event"], "did not log correct event", ) self.assertIn( "previous_value", logged_dict, "did not log previous CPU value" ) self.assertEqual( logged_dict["previous_value"], apps[0].cpu_allocated, "did not log correct previous CPU value", ) self.assertIn("new_value", logged_dict, "did not log new CPU value") self.assertEqual( logged_dict["new_value"], decisions[0].cpu, "did not log correct new CPU value", ) async def test_logs_memory_upscaling_decisions(self): apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, mem_threshold=0.2, app_stats=AppStats(cpu_usage=0.1, mem_usage=1.0), ) ] mock_logger = NonCallableMock() decider = DecisionComponent(logger=mock_logger) decisions = decider.decide_scaling_actions(apps) mock_logger.info.assert_called() logged_dict = mock_logger.info.call_args[0][0] self.assertIn("appname", logged_dict, "did not log correct app id") self.assertEqual( apps[0].id, logged_dict["appname"], "did not log correct app id" ) self.assertIn("event", logged_dict, "did not log an event") self.assertEqual( DecisionEvents.MEM_SCALE_UP, logged_dict["event"], "did not log correct event", ) self.assertIn( "previous_value", logged_dict, "did not log previous memory value" ) self.assertEqual( apps[0].mem_allocated, logged_dict["previous_value"], "did not log correct previous memory value", ) self.assertIn("new_value", logged_dict, "did not log new memory value") self.assertEqual( decisions[0].mem, logged_dict["new_value"], "did not log correct new memory value", ) def test_logs_cpu_downscaling_decisions(self): apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, cpu_threshold=1, app_stats=AppStats(cpu_usage=0.1, mem_usage=0.1), ) ] mock_logger = NonCallableMock() decider = DecisionComponent(logger=mock_logger) decisions = decider.decide_scaling_actions(apps) mock_logger.info.assert_called() logged_dict = mock_logger.info.call_args[0][0] self.assertIn("appname", logged_dict, "did not log correct app id") self.assertEqual( apps[0].id, logged_dict["appname"], "did not log correct app id" ) self.assertIn("event", logged_dict, "did not log an event") self.assertEqual( DecisionEvents.CPU_SCALE_DOWN, logged_dict["event"], "did not log correct event", ) self.assertIn( "previous_value", logged_dict, "did not log previous CPU value" ) self.assertEqual( apps[0].cpu_allocated, logged_dict["previous_value"], "did not log correct previous CPU value", ) self.assertIn("new_value", logged_dict, "did not log new CPU value") self.assertEqual( decisions[0].cpu, logged_dict["new_value"], "did not log correct new CPU value", ) def test_logs_memory_downscaling_decisions(self): apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, mem_threshold=1, app_stats=AppStats(cpu_usage=0.1, mem_usage=0.1), ) ] mock_logger = NonCallableMock() decider = DecisionComponent(logger=mock_logger) decisions = decider.decide_scaling_actions(apps) mock_logger.info.assert_called() logged_dict = mock_logger.info.call_args[0][0] self.assertIn("appname", logged_dict, "did not log correct app id") self.assertEqual( apps[0].id, logged_dict["appname"], "did not log correct app id" ) self.assertIn("event", logged_dict, "did not log an event") self.assertEqual( DecisionEvents.MEM_SCALE_DOWN, logged_dict["event"], "did not log correct event", ) self.assertIn( "previous_value", logged_dict, "did not log previous memory value" ) self.assertEqual( apps[0].mem_allocated, logged_dict["previous_value"], "did not log correct previous memory value", ) self.assertIn("new_value", logged_dict, "did not log new memory value") self.assertEqual( decisions[0].mem, logged_dict["new_value"], "did not log correct new memory value", ) def test_logs_cpu_and_memory_scaling_decisions(self): apps = [ ScalableApp( "test", cpu_allocated=0.5, mem_allocated=128, mem_threshold=1, cpu_threshold=0.2, app_stats=AppStats(cpu_usage=1.0, mem_usage=0.1), ) ] mock_logger = NonCallableMock() decider = DecisionComponent(logger=mock_logger) decisions = decider.decide_scaling_actions(apps) mock_logger.info.assert_called() logger_calls = [call[0][0] for call in mock_logger.info.call_args_list] self.assertEqual(len(logger_calls), 2, "did not call log.info 2 times") logger_calls.sort(key=lambda call: call["event"]) cpu_log_dict = logger_calls[0] mem_log_dict = logger_calls[1] self.assertIn("appname", cpu_log_dict, "did not log correct app id") self.assertEqual( mem_log_dict["appname"], apps[0].id, "did not log correct app id" ) self.assertIn("event", cpu_log_dict, "did not log an event") self.assertEqual( DecisionEvents.CPU_SCALE_UP, cpu_log_dict["event"], "did not log correct event", ) self.assertIn( "previous_value", cpu_log_dict, "did not log previous memory value" ) self.assertEqual( 0.5, cpu_log_dict["previous_value"], "did not log correct previous memory value", ) self.assertIn("new_value", cpu_log_dict, "did not log new memory value") self.assertEqual( decisions[0].cpu, cpu_log_dict["new_value"], "did not log correct new memory value", ) self.assertIn("appname", mem_log_dict, "did not log correct app id") self.assertEqual( apps[0].id, mem_log_dict["appname"], "did not log correct app id" ) self.assertIn("event", mem_log_dict, "did not log an event") self.assertEqual( DecisionEvents.MEM_SCALE_DOWN, mem_log_dict["event"], "did not log correct event", ) self.assertIn( "previous_value", mem_log_dict, "did not log previous memory value" ) self.assertEqual( apps[0].mem_allocated, mem_log_dict["previous_value"], "did not log correct previous memory value", ) self.assertIn("new_value", mem_log_dict, "did not log new memory value") self.assertEqual( decisions[0].mem, mem_log_dict["new_value"], "did not log correct new memory value", )

32.58121

97

0.568007

2,303

20,461

4.79201

0.063396

0.029358

0.039145

0.043494

0.883925

0.859007

0.831733

0.809351

0.784433

0.768757

0

0.027751

0.341332

20,461

627

98

32.633174

0.791126

0

0.646503

0

0.138361

0

0.166352

1

0.005671

false

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0.011342

0

0.018904

0

null

0

1

0

null

0

6

008bb982795cf8dc2faeb1f37f5199132ad6afc0

213

py

Python

departure/board/renderer.py

Woll78/departure-python

86eccd40291ad560d5859a120dd6c99aa5c4bd12

[ "MIT" ]

4

2020-10-18T18:12:04.000Z

2022-03-31T19:13:08.000Z

departure/board/renderer.py

Woll78/departure-python

86eccd40291ad560d5859a120dd6c99aa5c4bd12

[ "MIT" ]

null

departure/board/renderer.py

Woll78/departure-python

86eccd40291ad560d5859a120dd6c99aa5c4bd12

[ "MIT" ]

1

2021-11-19T10:37:26.000Z

class Renderer: def initialise(self): raise NotImplementedError() def render_frame(self, pixels): raise NotImplementedError() def terminate(self): raise NotImplementedError()

21.3

35

0.671362

19

213

7.473684

0.578947

0.507042

0.394366

0

0.248826

213

9

36

23.666667

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0.428571

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1

0.428571

false

0

0.571429

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null

1

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1

0

null

0

1

0

1

0

6

0094b82a16dd3bc07f73b32a25e1fc2cb23a8a6f

138,281

py

Python

Task 2.9.1 Kung Fu : Chopping Chain Punch.py

varipon/Work-Plan-2.-Biomechanical-simulation-of-human

9c6bf4685189cb6970f6b36426250b08919f4801

[ "MIT" ]

null

Task 2.9.1 Kung Fu : Chopping Chain Punch.py

varipon/Work-Plan-2.-Biomechanical-simulation-of-human

9c6bf4685189cb6970f6b36426250b08919f4801

[ "MIT" ]

null

Task 2.9.1 Kung Fu : Chopping Chain Punch.py

varipon/Work-Plan-2.-Biomechanical-simulation-of-human

9c6bf4685189cb6970f6b36426250b08919f4801

[ "MIT" ]

null

# ================ # SOFTWARE LICENSE # ================ # The MIT License (MIT) # Copyright (c) 2018 Yutaka Sawai (Varipon) # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. # ============================================================== # LICENSE FOR CONTENT PROCEDURALLY GENERATED USING THIS SOFTWARE # ============================================================== # All content procedurally generated by this software and its permutations # are licensed under Creative Commons Attribution By 3.0: # https://creativecommons.org/licenses/by/3.0/ #!/usr/bin/python import bpy from bpy import * import mathutils import math from mathutils import * from math import * class Formula: J = 18 #joint number #frame_start = bpy.context.scene.frame_start #frame_end = bpy.context.scene.frame_end #bpy.context.scene.frame_current = frame_end interval = 120 frame_start = 0 frame_end = 120 def __init__(self, P, A, move, part, helicity, start, end): # pivot factor self.P = P # scale factor self.A = A # name self.move = move # element self.part = part # element helicity self.helicity = helicity self.start = start self.end = end bpy.ops.object.mode_set(mode='OBJECT') # Create armature and object self.amt = bpy.data.armatures.new(move + '.' + part + '.' + helicity + '.data') self.rig = bpy.data.objects.new(move + '.' + part + '.' + helicity, self.amt) # Joints α(n) -> a[n], β(n) -> b[n], γ(n) -> y[n], δ(n) -> o[n] self.a = [0 for i in range(4)] # Joint α self.b = [0 for i in range(self.J)] # Joint β self.y = [0 for i in range(self.J)] # Joint γ self.o = [0 for i in range(self.J)] # Joint δ # Configuration Movement self.configMovement(self.P, self.A, self.J, self.a, self.b, self.y, self.o) # Construction Movement self.constructMovement(self.J, self.helicity, self.amt, self.rig, self.a, self.b, self.y, self.o) # Construction Rotation self.configRotation(self.rig, self.interval, self.frame_start, self.frame_end, self.start, self.end) # Configuration Linkage self.configLink(self.A, self.J, self.helicity, self.rig, self.move, self.part) # Construction Linkage self.constructLink(self.A, self.J, self.helicity, self.rig, self.move, self.part) def configMovement(self, P, A, J, a, b, y, o): mat_a = [0 for i in range(4)] # Joint α matrix mat_b = [0 for i in range(self.J)] # Joint β matrix mat_y = [0 for i in range(self.J)] # Joint γ matrix mat_o = [0 for i in range(self.J)] # Joint δ matrix a[1] = mathutils.Euler((P, A, 0), 'XYZ') print ("a1 =", a[1]) a[2] = mathutils.Euler((A, -A, 0), 'XYZ') print ("a2 =", a[2]) b[1] = mathutils.Euler((-A, A, 0), 'XYZ') print ("b1 =", b[1]) o[1] = mathutils.Euler((A, A, 0), 'XYZ') print ("o1 =", o[1]) B = A * 2 * sqrt (2) C = B + (B * sqrt (2)) D = C * sqrt (2) E = C + D a[0] = mathutils.Euler((-A - E + (D * 0.5), -A - (D * 0.5), 0), 'XYZ') print ("a0 =", a[0]) mat_a[0] = Matrix.Translation(a[0]) a[3] = mathutils.Euler((0-a[0].x, 0-a[0].y, 0-a[0].z), 'XYZ') print ("a3 =", a[3]) mat_a[3] = Matrix.Translation(a[3]) y[1] = mathutils.Euler((-A, -A, 0), 'XYZ') print ("y1 =", y[1]) mat_y[1] = Matrix.Translation(y[1]) ### pattern A b[2] = mathutils.Euler((a[0].x + E + (A * 2), a[0].y + (A * 2), 0), 'XYZ') print ("b2 =", b[2]) mat_b[2] = Matrix.Translation(b[2]) b[3] = mathutils.Euler((a[0].x + E - (D * 0.5), a[0].y - (A * 2), 0), 'XYZ') print ("b3 =", b[3]) mat_b[3] = Matrix.Translation(b[3]) y[2] = mathutils.Euler((a[0].x + E, a[0].y, 0), 'XYZ') print ("y2 =", y[2]) mat_y[2] = Matrix.Translation(y[2]) y[3] = mathutils.Euler((a[0].x + E - (D * 0.5), a[0].y - (D * 0.5), 0), 'XYZ') print ("y3 =", y[3]) mat_y[3] = Matrix.Translation(y[3]) o[2] = mathutils.Euler((a[0].x + E + (A * 2), a[0].y - (A * 2), 0), 'XYZ') print ("o2 =", o[2]) mat_o[2] = Matrix.Translation(o[2]) o[3] = mathutils.Euler((a[0].x + E - (D * 0.5) - (A * 2), a[0].y - (D * 0.5) - (A * 2), 0), 'XYZ') print ("o3 =", o[3]) mat_o[3] = Matrix.Translation(o[3]) ### pattern A end org_rot_mat = Matrix.Rotation(math.radians(0), 4, 'Z') # define the rotation rot_mat = Matrix.Rotation(math.radians(-45), 4, 'Z') for j in range(2, J - 2): mat_y[j + 2] = mat_a[0] * org_rot_mat * rot_mat * mat_a[3] * mat_y[j] # obj.matrix_world = mat_y[j + 2] # extract components back out of the matrix loc, rot, sca = mat_y[j + 2].decompose() y[j + 2] = mathutils.Euler(loc, 'XYZ') print("y"+str(j + 2)+" = ", y[j + 2], rot, sca) mat_b[j + 2] = mat_a[0] * org_rot_mat * rot_mat * mat_a[3] * mat_b[j] # obj.matrix_world = mat_b[j + 2] # extract components back out of the matrix loc, rot, sca = mat_b[j + 2].decompose() b[j + 2] = mathutils.Euler(loc, 'XYZ') print("b"+str(j + 2)+" = ", b[j + 2], rot, sca) mat_o[j + 2] = mat_a[0] * org_rot_mat * rot_mat * mat_a[3] * mat_o[j] # obj.matrix_world = mat_o[j + 2] # extract components back out of the matrix loc, rot, sca = mat_o[j + 2].decompose() o[j + 2] = mathutils.Euler(loc, 'XYZ') print("o"+str(j + 2)+" = ", o[j + 2], rot, sca) def constructMovement(self, J, helicity, amt, rig, a, b, y, o): # Linkages aa = [[0 for i in range(4)] for j in range(4)] # Link α(i) - α(j) ab = [[0 for i in range(4)] for j in range(4)] # Link α(i) - β(j) ya = [[0 for i in range(4)] for j in range(4)] # Link γ(i) - α(j) ao = [[0 for i in range(4)] for j in range(4)] # Link α(i) - δ(j) ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) rig.location = mathutils.Euler((0.0, 0.0, 0.0), 'XYZ') rig.show_x_ray = True amt.show_names = True # amt.draw_type = 'STICK' amt.draw_type = 'BBONE' # Link object to scene scn = bpy.context.scene scn.objects.link(rig) scn.objects.active = rig scn.update() # Edit bpy.ops.object.editmode_toggle() # Construction Linkage aa[2][1] = amt.edit_bones.new('a2a1') aa[2][1].head = a[2] aa[2][1].tail = a[1] ab[1][1] = amt.edit_bones.new('a1b1') ab[1][1].head = a[1] ab[1][1].tail = b[1] ab[1][1].parent = aa[2][1] by[1][1] = amt.edit_bones.new('b1y1') by[1][1].head = b[1] by[1][1].tail = y[1] by[1][1].parent = ab[1][1] by[1][1].use_inherit_rotation = False ya[1][2] = amt.edit_bones.new('y1a2') ya[1][2].head = y[1] ya[1][2].tail = a[2] ya[1][2].parent = by[1][1] ao[2][1] = amt.edit_bones.new('a2o1') ao[2][1].head = a[2] ao[2][1].tail = o[1] ao[2][1].parent = ya[1][2] ob[1][2] = amt.edit_bones.new('o1b2') ob[1][2].head = o[1] ob[1][2].tail = b[2] ob[1][2].parent = ao[2][1] yy[1][2] = amt.edit_bones.new('y1y2') yy[1][2].head = y[1] yy[1][2].tail = y[2] yy[1][2].parent = by[1][1] for j in range(2, J - 1): by[j][j] = amt.edit_bones.new('b'+ str(j) + 'y'+ str(j)) by[j][j].head = b[j] by[j][j].tail = y[j] by[j][j].parent = ob[j-1][j] yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j)) yo[j][j].head = y[j] yo[j][j].tail = o[j] yo[j][j].parent = yy[j-1][j] yy[j][j+1] = amt.edit_bones.new('y'+ str(j) + 'y'+ str(j+1)) yy[j][j+1].head = y[j] yy[j][j+1].tail = y[j+1] yy[j][j+1].parent = by[j][j] if j < (J-2): ob[j][j+1] = amt.edit_bones.new('o'+ str(j) + 'b'+ str(j+1)) ob[j][j+1].head = o[j] ob[j][j+1].tail = b[j+1] ob[j][j+1].parent = yo[j][j] # all bones select #bpy.ops.pose.select_all(action="SELECT") for b in amt.edit_bones: b.select = True if helicity == 'right': bpy.ops.armature.calculate_roll(type='GLOBAL_POS_Z') else: bpy.ops.armature.calculate_roll(type='GLOBAL_NEG_Z') # Bone constraints. Armature must be in pose mode. bpy.ops.object.mode_set(mode='POSE') # IK constraint cns = rig.pose.bones['y1a2'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'a2a1' cns.chain_count = 2 cns.use_stretch = False for j in range(2, J - 1): cns = rig.pose.bones['b'+str(j) +'y'+str(j)].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'y'+str(j)+'o'+str(j) cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False bpy.ops.object.mode_set(mode='OBJECT') def configRotation(self, rig, interval, frame_start, frame_end, start, end): # Bone constraints. Armature must be in pose mode. bpy.ops.object.mode_set(mode='POSE') # key insert keyframe_insert_interval = interval rig.pose.bones["a1b1"].rotation_mode = 'XYZ' rig.pose.bones["a1b1"].rotation_euler.z = math.radians(start) rig.pose.bones["a1b1"].keyframe_insert(data_path="rotation_euler",frame=frame_start) rig.pose.bones["a1b1"].rotation_mode = 'XYZ' rig.pose.bones["a1b1"].rotation_euler.z = math.radians(end) rig.pose.bones["a1b1"].keyframe_insert(data_path="rotation_euler",frame=frame_end) for curve in bpy.context.active_object.animation_data.action.fcurves: cycles = curve.modifiers.new(type='CYCLES') cycles.mode_before = 'REPEAT_OFFSET' cycles.mode_after = 'REPEAT_OFFSET' for keyframe in curve.keyframe_points: keyframe.interpolation = 'LINEAR' bpy.ops.object.mode_set(mode='OBJECT') def configLink(self, A, J, helicity, rig, move, part): bpy.ops.object.mode_set(mode='OBJECT') Q = (0.18648+0.146446)*A # Z = -Q*2 Z = 0.0 obj_joint = bpy.data.objects["joint.gold.000"].copy() obj_joint.location = (0.0, 0.0, -Q*3+Z) obj_joint.scale = (A, A, A) obj_joint.name = "a2a1.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.silver.001"].copy() obj_joint.location = (0.0, 0.0, +Q+Z) obj_joint.scale = (A, A, A) obj_joint.name = "y1a2.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, +Q*3+Z) obj_joint.scale = (A, A, A) obj_joint.name = "a2o1.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, -Q*2+Z) obj_joint.scale = (A, A, A) obj_joint.name = "a1b1.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) for n in range(1, J - 1): if n <= (J-2): # Pattern 2 of by obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*((n+1) % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yy obj_joint = bpy.data.objects["joint.gold.00"+str(1 + (n+1) % 2)].copy() obj_joint.location = (0.0, 0.0, +Q*(1 - (n % 2))*2+Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"y"+str(n+1)+".mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) if n <= (J-3): # Pattern 1 of ob obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, -Q*2 + Q*(n % 2)*6 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yo obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*((n+1) % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n+1)+"o"+str(n+1)+".mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) for ob in context.scene.objects: if "mesh" in ob.name: ob.select = True bpy.ops.object.make_single_user(type='SELECTED_OBJECTS', object=True, obdata=True, material=True, texture=True, animation=True) bpy.context.scene.cursor_location = (0.0, 0.0, 0.0) bpy.ops.object.origin_set(type='ORIGIN_CURSOR') def constructLink(self, A, J, helicity, rig, move, part): # Move and rotate the tip bone in pose mode bpy.context.scene.objects.active = rig Y = 1.1838*A for n in rig.pose.bones: if n.name != "o" + str(J-2) + "b" + str(J-1): # we can get the object from the pose bone obj = n.id_data matrix_final = obj.matrix_world * n.matrix # Create armature and object lnk = bpy.data.armatures.new(n.name[:len(n.name)]+'.data.' + helicity) lnk_rig = bpy.data.objects.new(n.name[:len(n.name)]+'.link.' + helicity, lnk) lnk_rig.location = mathutils.Euler((0.0, 0.0, 0.0), 'XYZ') # rig.show_x_ray = True lnk.show_names = True lnk.draw_type = 'STICK' # Link object to scene scn = bpy.context.scene scn.objects.link(lnk_rig) scn.objects.active = lnk_rig scn.update() # Create bones # mode='EDIT' bpy.ops.object.editmode_toggle() link = lnk.edit_bones.new(n.name[:len(n.name)]) link.head = (0, 0, 0) link.tail = (0, Y, 0) link_head = lnk.edit_bones.new('head') link_head.head = (0, 0, 0.1) link_head.tail = (0, 0, 0) link_head.parent = link link_head.use_inherit_scale = False link_tail = lnk.edit_bones.new('tail') link_tail.head = (0, Y, 0) link_tail.tail = (0, Y, -0.1) link_tail.parent = link link_tail.use_inherit_scale = False bpy.ops.object.mode_set(mode='OBJECT') ob = bpy.data.objects[n.name[:len(n.name)]+'.mesh.' + move + '.' + part +'.' + helicity] ob.location = mathutils.Euler((0, 0, 0), 'XYZ') # Give mesh object an armature modifier, using vertex groups but # not envelopes mod = ob.modifiers.new('MyRigModif', 'ARMATURE') mod.object = lnk_rig mod.use_bone_envelopes = False mod.use_vertex_groups = True # Bone constraints. Armature must be in pose mode. bpy.ops.object.mode_set(mode='POSE') # Copy rotation constraints Base -> Tip pBase = lnk_rig.pose.bones[n.name[:len(n.name)]] cns = pBase.constraints.new('COPY_LOCATION') cns.name = 'Copy_Location' cns.target = rig cns.subtarget = n.name[:len(n.name)] cns.owner_space = 'WORLD' cns.target_space = 'WORLD' # Copy rotation constraints Base -> Tip pBase = lnk_rig.pose.bones[n.name[:len(n.name)]] cns = pBase.constraints.new('COPY_ROTATION') cns.name = 'Copy_Rotation' cns.target = rig cns.subtarget = n.name[:len(n.name)] cns.owner_space = 'WORLD' cns.target_space = 'WORLD' # StretchTo constraint Mid -> Tip with influence 0.5 cns1 = pBase.constraints.new('STRETCH_TO') cns1.name = 'Stretch' cns1.target = rig cns1.subtarget = n.name[:len(n.name)] cns1.head_tail = 1 cns1.rest_length = Y cns1.influence = 1 cns1.keep_axis = 'PLANE_Z' cns1.volume = 'NO_VOLUME' bpy.ops.object.mode_set(mode='OBJECT') class Yaw(Formula): J = 7 #joint number #frame_start = bpy.context.scene.frame_start #frame_end = bpy.context.scene.frame_end #bpy.context.scene.frame_current = frame_end interval = 120 frame_start = 133 frame_end = 148 def __init__(self, P, A, move, part, helicity, start, end, yaw_loc, yaw_rot, pitch_loc, pitch_rot, pitch, body): # pivot factor self.P = P # scale factor self.A = A # name self.move = move # element self.part = part # element helicity self.helicity = helicity self.start = start self.end = end # yaw self.yaw_loc = yaw_loc self.yaw_rot = yaw_rot # pitch self.pitch_loc = pitch_loc self.pitch_rot = pitch_rot self.pitch = pitch self.body = body bpy.ops.object.mode_set(mode='OBJECT') # Create armature and object self.amt = bpy.data.armatures.new(move + '.' + part + '.' + helicity + '.data') self.rig = bpy.data.objects.new(move + '.' + part + '.' + helicity, self.amt) # Joints α(n) -> a[n], β(n) -> b[n], γ(n) -> y[n], δ(n) -> o[n] self.a = [0 for i in range(4)] # Joint α self.b = [0 for i in range(self.J)] # Joint β self.y = [0 for i in range(self.J)] # Joint γ self.o = [0 for i in range(self.J)] # Joint δ self.upper_b = [0 for i in range(self.J)] # Joint β matrix self.upper_y = [0 for i in range(self.J)] # Joint γ matrix self.upper_o = [0 for i in range(self.J)] # Joint δ matrix self.upper_w = [0 for i in range(self.J)] # Joint ω matrix self.lower_b = [0 for i in range(self.J)] # Joint β matrix self.lower_y = [0 for i in range(self.J)] # Joint γ matrix self.lower_w = [0 for i in range(2)] # Joint ω matrix self.lower_left_b = [0 for i in range(self.J)] # Joint β matrix self.lower_left_y = [0 for i in range(self.J)] # Joint γ matrix self.lower_left_o = [0 for i in range(self.J)] # Joint δ matrix self.lower_left_w = [0 for i in range(2)] # Joint ω matrix self.lower_right_b = [0 for i in range(self.J)] # Joint β matrix self.lower_right_y = [0 for i in range(self.J)] # Joint γ matrix self.lower_right_o = [0 for i in range(self.J)] # Joint δ matrix self.lower_right_w = [0 for i in range(2)] # Joint ω matrix # Configuration Movement self.configMovement(self.P, self.A, self.J, self.a, self.b, self.y, self.o, self.upper_b, self.upper_y, self.upper_o, self.upper_w, self.lower_b, self.lower_y, self.lower_w, self.lower_left_b, self.lower_left_y, self.lower_left_o, self.lower_left_w, self.lower_right_b, self.lower_right_y, self.lower_right_o, self.lower_right_w) # Construction Movement self.constructMovement(self.J, self.helicity, self.amt, self.rig, self.a, self.b, self.y, self.o, self.upper_b, self.upper_y, self.upper_o, self.upper_w, self.lower_b, self.lower_y, self.lower_w, self.lower_left_b, self.lower_left_y, self.lower_left_o, self.lower_left_w, self.lower_right_b, self.lower_right_y, self.lower_right_o, self.lower_right_w) # Parent set pitch to yaw self.setParent(self.helicity, self.move, self.rig, yaw_loc, yaw_rot, pitch_loc, pitch_rot, pitch, body) # Construction Rotation self.configRotation(self.rig, self.interval, self.frame_start, self.frame_end, self.start, self.end) # Configuration Linkage self.configLink(self.A * 0.25, self.J, self.helicity, self.rig, self.move, self.part) # Construction Linkage self.constructLink(self.A * 0.25, self.J, self.helicity, self.rig, self.move, self.part) def configMovement(self, P, A, J, a, b, y, o, upper_b, upper_y, upper_o, upper_w, lower_b, lower_y, lower_w, lower_left_b, lower_left_y, lower_left_o, lower_left_w, lower_right_b, lower_right_y, lower_right_o, lower_right_w): mat_a = [0 for i in range(4)] # Joint α matrix mat_b = [0 for i in range(self.J)] # Joint β matrix mat_y = [0 for i in range(self.J)] # Joint γ matrix mat_o = [0 for i in range(self.J)] # Joint δ matrix upper_mat_b = [0 for i in range(self.J)] # Joint β matrix upper_mat_y = [0 for i in range(self.J)] # Joint γ matrix upper_mat_o = [0 for i in range(self.J)] # Joint δ matrix upper_mat_w = [0 for i in range(self.J)] # Joint ω matrix lower_mat_b = [0 for i in range(self.J)] # Joint β matrix lower_mat_y = [0 for i in range(self.J)] # Joint γ matrix lower_mat_w = [0 for i in range(2)] # Joint ω matrix lower_left_mat_b = [0 for i in range(self.J)] # Joint β matrix lower_left_mat_y = [0 for i in range(self.J)] # Joint γ matrix lower_left_mat_o = [0 for i in range(self.J)] # Joint δ matrix lower_left_mat_w = [0 for i in range(2)] # Joint ω matrix lower_right_mat_b = [0 for i in range(self.J)] # Joint β matrix lower_right_mat_y = [0 for i in range(self.J)] # Joint γ matrix lower_right_mat_o = [0 for i in range(self.J)] # Joint δ matrix lower_right_mat_w = [0 for i in range(2)] # Joint ω matrix a[1] = mathutils.Euler((P, A, 0), 'XYZ') print ("a1 =", a[1]) a[2] = mathutils.Euler((A, -A, 0), 'XYZ') print ("a2 =", a[2]) b[1] = mathutils.Euler((-A, A, 0), 'XYZ') print ("b1 =", b[1]) y[1] = mathutils.Euler((-A, -A, 0), 'XYZ') print ("y1 =", y[1]) mat_y[1] = Matrix.Translation(y[1]) o[1] = mathutils.Euler((A, A, 0), 'XYZ') print ("o1 =", o[1]) upper_b[2] = mathutils.Euler((5.40939, -2.87735, 0), 'XYZ') print ("upper_b2 =", upper_b[2]) upper_mat_b[2] = Matrix.Translation(upper_b[2]) upper_y[2] = mathutils.Euler((4.39357, -2.95756, 0), 'XYZ') print ("upper_y2 =", upper_y[2]) upper_mat_y[2] = Matrix.Translation(upper_y[2]) upper_o[2] = mathutils.Euler((3.61516, -2.09638, 0), 'XYZ') print ("o2 =", o[2]) upper_mat_o[2] = Matrix.Translation(upper_o[2]) upper_w[1] = mathutils.Euler((4.39357, -2.95756, 23.2308), 'XYZ') print ("upper_w1 =", upper_w[1]) upper_mat_w[1] = Matrix.Translation(upper_w[1]) upper_w[2] = mathutils.Euler((8.19003, -8.48921, 2.42495), 'XYZ') print ("upper_w2 =", upper_w[2]) upper_mat_w[2] = Matrix.Translation(upper_w[2]) upper_w[3] = mathutils.Euler((13.3388, -1.17576, 2.42495), 'XYZ') print ("upper_w3 =", upper_w[3]) upper_mat_w[3] = Matrix.Translation(upper_w[3]) upper_w[4] = mathutils.Euler((13.3388, -1.17576, 30.6122), 'XYZ') print ("upper_w4 =", upper_w[4]) upper_mat_w[4] = Matrix.Translation(upper_w[4]) upper_w[5] = mathutils.Euler((13.3388, -1.17576, 29.9866), 'XYZ') print ("upper_w5 =", upper_w[5]) upper_mat_w[5] = Matrix.Translation(upper_w[5]) upper_w[6] = mathutils.Euler((13.3388, 0, 29.9866), 'XYZ') print ("upper_w6 =", upper_w[6]) upper_mat_w[6] = Matrix.Translation(upper_w[6]) lower_w[1] = mathutils.Euler((8.19003, -8.48921, 0), 'XYZ') print ("lower_w1 =", lower_w[1]) lower_mat_w[1] = Matrix.Translation(lower_w[1]) lower_b[2] = mathutils.Euler((5.72759, -6.1022, 0), 'XYZ') print ("lower_b2 =", lower_b[2]) lower_mat_b[2] = Matrix.Translation(lower_b[2]) lower_y[2] = mathutils.Euler((7.29866, -4.39351, 0), 'XYZ') print ("lower_y2 =", lower_y[2]) lower_mat_y[2] = Matrix.Translation(lower_y[2]) lower_left_o[2] = mathutils.Euler((0.333433, 8.17479, 0), 'XYZ') print ("lower_left_o2 =", lower_left_o[2]) lower_left_mat_o[2] = Matrix.Translation(lower_left_o[2]) lower_left_b[3] = mathutils.Euler((7.33373, 7.72061, 0), 'XYZ') print ("lower_left_b3 =", lower_left_b[3]) lower_left_mat_b[3] = Matrix.Translation(lower_left_b[3]) lower_left_y[3] = mathutils.Euler((-1.15831, 3.11248, 0), 'XYZ') print ("lower_left_y3 =", lower_left_y[3]) lower_left_mat_y[3] = Matrix.Translation(lower_left_y[3]) lower_left_o[3] = mathutils.Euler((-1.15831, 4.12125, 0), 'XYZ') print ("lower_left_o3 =", lower_left_o[3]) lower_left_mat_o[3] = Matrix.Translation(lower_left_o[3]) lower_left_w[1] = mathutils.Euler((3.02315, 8.00786, 0), 'XYZ') print ("lower_left_w1 =", lower_left_w[1]) lower_left_mat_w[1] = Matrix.Translation(lower_left_w[1]) lower_right_o[2] = mathutils.Euler((6.72417, -15.9045, 0), 'XYZ') print ("lower_right_o2 =", lower_right_o[2]) lower_right_mat_o[2] = Matrix.Translation(lower_right_o[2]) lower_right_b[3] = mathutils.Euler((13.0432, -17.9857, 0), 'XYZ') print ("lower_right_b3 =", lower_right_b[3]) lower_right_mat_b[3] = Matrix.Translation(lower_right_b[3]) lower_right_y[3] = mathutils.Euler((6.09549, -14.1632, 0), 'XYZ') print ("lower_right_y3 =", lower_right_y[3]) lower_right_mat_y[3] = Matrix.Translation(lower_right_y[3]) lower_right_o[3] = mathutils.Euler((5.79574, -15.2852, 0), 'XYZ') print ("lower_right_o3 =", lower_right_o[3]) lower_right_mat_o[3] = Matrix.Translation(lower_right_o[3]) lower_right_w[1] = mathutils.Euler((8.93583, -16.6329, 0), 'XYZ') print ("lower_right_w1 =", lower_right_w[1]) lower_right_mat_w[1] = Matrix.Translation(lower_right_w[1]) def constructMovement(self, J, helicity, amt, rig, a, b, y, o, upper_b, upper_y, upper_o, upper_w, lower_b, lower_y, lower_w, lower_left_b, lower_left_y, lower_left_o, lower_left_w, lower_right_b, lower_right_y, lower_right_o, lower_right_w): # Linkages aa = [[0 for i in range(4)] for j in range(4)] # Link α(i) - α(j) ab = [[0 for i in range(4)] for j in range(4)] # Link α(i) - β(j) ya = [[0 for i in range(4)] for j in range(4)] # Link γ(i) - α(j) ao = [[0 for i in range(4)] for j in range(4)] # Link α(i) - δ(j) ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) upper_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) upper_yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) upper_by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) upper_yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) upper_yw = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - ω(j) upper_ww = [[0 for i in range(self.J)] for j in range(self.J)] # Link ω(i) - ω(j) lower_aw = [[0 for i in range(2)] for j in range(3)] # Link α(i) - ω(j) lower_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) lower_yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) lower_by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) lower_left_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) lower_left_yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) lower_left_by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) lower_left_yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) lower_left_wb = [[0 for i in range(self.J)] for j in range(2)] # Link β(i) - ω(j) lower_right_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) lower_right_yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) lower_right_by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) lower_right_yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) lower_right_wb = [[0 for i in range(self.J)] for j in range(2)] # Link β(i) - ω(j) rig.location = mathutils.Euler((0.0, 0.0, 0.0), 'XYZ') rig.show_x_ray = True amt.show_names = True # amt.draw_type = 'STICK' amt.draw_type = 'BBONE' # Link object to scene scn = bpy.context.scene scn.objects.link(rig) scn.objects.active = rig scn.update() # Edit bpy.ops.object.editmode_toggle() j = 1 # Construction Linkage aa[j+1][j] = amt.edit_bones.new('a' + str(j+1) + 'a' + str(j)) aa[j+1][j].head = a[j+1] aa[j+1][j].tail = a[j] ab[j][j] = amt.edit_bones.new('a' + str(j) + 'b' + str(j)) ab[j][j].head = a[j] ab[j][j].tail = b[j] ab[j][j].parent = aa[j+1][j] by[j][j] = amt.edit_bones.new('b' + str(j) + 'y' + str(j)) by[j][j].head = b[j] by[j][j].tail = y[j] by[j][j].parent = ab[j][j] by[j][j].use_inherit_rotation = False ya[j][j+1] = amt.edit_bones.new('y' + str(j) + 'a' + str(j+1)) ya[j][j+1].head = y[j] ya[j][j+1].tail = a[j+1] ya[j][j+1].parent = by[j][j] ao[j+1][j] = amt.edit_bones.new('a' + str(j+1) + 'o' + str(j)) ao[j+1][j].head = a[j+1] ao[j+1][j].tail = o[j] ao[j+1][j].parent = ya[j][j+1] upper_ob[j][j+1] = amt.edit_bones.new('o' + str(j) + 'b' + str(j+1) +'.upper') upper_ob[j][j+1].head = o[j] upper_ob[j][j+1].tail = upper_b[j+1] upper_ob[j][j+1].parent = ao[j+1][j] upper_yy[j][j+1] = amt.edit_bones.new('y' + str(j) + 'y' + str(j+1) +'.upper') upper_yy[j][j+1].head = y[j] upper_yy[j][j+1].tail = upper_y[j+1] upper_yy[j][j+1].parent = by[j][j] lower_ob[j][j+1] = amt.edit_bones.new('o' + str(j) + 'b' + str(j+1) +'.lower') lower_ob[j][j+1].head = o[j] lower_ob[j][j+1].tail = lower_b[j+1] lower_ob[j][j+1].parent = ao[j+1][j] lower_yy[j][j+1] = amt.edit_bones.new('y' + str(j) + 'y' + str(j+1) +'.lower') lower_yy[j][j+1].head = y[j] lower_yy[j][j+1].tail = lower_y[j+1] lower_yy[j][j+1].parent = by[j][j] lower_aw[j+1][j] = amt.edit_bones.new('a' + str(j+1) + 'w' + str(j) +'.lower') lower_aw[j+1][j].head = a[j+1] lower_aw[j+1][j].tail = lower_w[j] lower_aw[j+1][j].parent = aa[j+1][j] upper_ww[j][j+1] = amt.edit_bones.new('w' + str(j) + 'w' + str(j+1) +'.upper') upper_ww[j][j+1].head = lower_w[j] upper_ww[j][j+1].tail = upper_w[j+1] upper_ww[j][j+1].parent = lower_aw[j+1][j] j = 2 upper_ww[j][j+1] = amt.edit_bones.new('w' + str(j) + 'w' + str(j+1) +'.upper') upper_ww[j][j+1].head = upper_w[j] upper_ww[j][j+1].tail = upper_w[j+1] upper_ww[j][j+1].parent = upper_ww[j-1][j] upper_by[j][j] = amt.edit_bones.new('b'+ str(j) + 'y'+ str(j) +'.upper') upper_by[j][j].head = upper_b[j] upper_by[j][j].tail = upper_y[j] upper_by[j][j].parent = upper_ob[j-1][j] upper_yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j) +'.upper') upper_yo[j][j].head = upper_y[j] upper_yo[j][j].tail = upper_o[j] upper_yo[j][j].parent = upper_yy[j-1][j] upper_yw[j][j-1] = amt.edit_bones.new('y'+ str(j) + 'w'+ str(j-1) +'.upper') upper_yw[j][j-1].head = upper_y[j] upper_yw[j][j-1].tail = upper_w[j-1] upper_yw[j][j-1].parent = upper_by[j][j] lower_by[j][j] = amt.edit_bones.new('b'+ str(j) + 'y'+ str(j) + '.lower') lower_by[j][j].head = lower_b[j] lower_by[j][j].tail = lower_y[j] lower_by[j][j].parent = lower_ob[j-1][j] lower_left_yy[j][j+1] = amt.edit_bones.new('y' + str(j) + 'y' + str(j+1) +'.lower.left') lower_left_yy[j][j+1].head = lower_y[j] lower_left_yy[j][j+1].tail = lower_left_y[j+1] lower_left_yy[j][j+1].parent = lower_by[j][j] lower_left_yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j) +'.lower.left') lower_left_yo[j][j].head = lower_y[j] lower_left_yo[j][j].tail = lower_left_o[j] lower_left_yo[j][j].parent = lower_yy[j-1][j] lower_left_ob[j][j+1] = amt.edit_bones.new('o'+ str(j) + 'b'+ str(j+1) +'.lower.left') lower_left_ob[j][j+1].head = lower_left_o[j] lower_left_ob[j][j+1].tail = lower_left_b[j+1] lower_left_ob[j][j+1].parent = lower_left_yo[j][j] lower_right_yy[j][j+1] = amt.edit_bones.new('y' + str(j) + 'y' + str(j+1) +'.lower.right') lower_right_yy[j][j+1].head = lower_y[j] lower_right_yy[j][j+1].tail = lower_right_y[j+1] lower_right_yy[j][j+1].parent = lower_by[j][j] lower_right_yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j) +'.lower.right') lower_right_yo[j][j].head = lower_y[j] lower_right_yo[j][j].tail = lower_right_o[j] lower_right_yo[j][j].parent = lower_yy[j-1][j] lower_right_ob[j][j+1] = amt.edit_bones.new('o'+ str(j) + 'b'+ str(j+1) +'.lower.right') lower_right_ob[j][j+1].head = lower_right_o[j] lower_right_ob[j][j+1].tail = lower_right_b[j+1] lower_right_ob[j][j+1].parent = lower_right_yo[j][j] j = 3 upper_ww[j][j+1] = amt.edit_bones.new('w' + str(j) + 'w' + str(j+1) +'.upper') upper_ww[j][j+1].head = upper_w[j] upper_ww[j][j+1].tail = upper_w[j+1] upper_ww[j][j+1].parent = upper_ww[j-1][j] lower_left_by[j][j] = amt.edit_bones.new('b'+ str(j) + 'y'+ str(j) + '.lower.left') lower_left_by[j][j].head = lower_left_b[j] lower_left_by[j][j].tail = lower_left_y[j] lower_left_by[j][j].parent = lower_left_ob[j-1][j] lower_left_wb[1][j] = amt.edit_bones.new('w'+ str(1) + 'b'+ str(j) +'.lower.left') lower_left_wb[1][j].head = lower_left_w[1] lower_left_wb[1][j].tail = lower_left_b[j] lower_left_wb[1][j].parent = lower_left_ob[j-1][j] lower_left_yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j) +'.lower.left') lower_left_yo[j][j].head = lower_left_y[j] lower_left_yo[j][j].tail = lower_left_o[j] lower_left_yo[j][j].parent = lower_left_yy[j-1][j] lower_right_by[j][j] = amt.edit_bones.new('b'+ str(j) + 'y'+ str(j) + '.lower.right') lower_right_by[j][j].head = lower_right_b[j] lower_right_by[j][j].tail = lower_right_y[j] lower_right_by[j][j].parent = lower_right_ob[j-1][j] lower_right_wb[1][j] = amt.edit_bones.new('w'+ str(1) + 'b'+ str(j) +'.lower.right') lower_right_wb[1][j].head = lower_right_w[1] lower_right_wb[1][j].tail = lower_right_b[j] lower_right_wb[1][j].parent = lower_right_ob[j-1][j] lower_right_yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j) +'.lower.right') lower_right_yo[j][j].head = lower_right_y[j] lower_right_yo[j][j].tail = lower_right_o[j] lower_right_yo[j][j].parent = lower_right_yy[j-1][j] for j in range(4, 6): upper_ww[j][j+1] = amt.edit_bones.new('w' + str(j) + 'w' + str(j+1) +'.upper') upper_ww[j][j+1].head = upper_w[j] upper_ww[j][j+1].tail = upper_w[j+1] upper_ww[j][j+1].parent = upper_ww[j-1][j] # all bones select #bpy.ops.pose.select_all(action="SELECT") for b in amt.edit_bones: b.select = True if helicity == 'right': bpy.ops.armature.calculate_roll(type='GLOBAL_POS_Z') else: bpy.ops.armature.calculate_roll(type='GLOBAL_NEG_Z') # Bone constraints. Armature must be in pose mode. bpy.ops.object.mode_set(mode='POSE') # IK constraint cns = rig.pose.bones['y1a2'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'a2a1' cns.chain_count = 2 cns.use_stretch = False j = 2 cns = rig.pose.bones['b'+str(j) +'y'+str(j) +'.upper'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'y'+str(j)+'o'+str(j) +'.upper' cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False cns = rig.pose.bones['b'+str(j) +'y'+str(j) +'.lower'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'y'+str(j)+'o'+str(j) +'.lower.left' cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False j = 3 cns = rig.pose.bones['b'+str(j) +'y'+str(j) +'.lower.left'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'y'+str(j)+'o'+str(j) +'.lower.left' cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False cns = rig.pose.bones['b'+str(j) +'y'+str(j) +'.lower.right'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'y'+str(j)+'o'+str(j) +'.lower.right' cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False bpy.ops.object.mode_set(mode='OBJECT') def configLink(self, A, J, helicity, rig, move, part): bpy.ops.object.mode_set(mode='OBJECT') Q = (0.18648+0.146446)*A # Z = -Q*2 Z = 0.0 obj_joint = bpy.data.objects["joint.gold.000"].copy() obj_joint.location = (0.0, 0.0, -Q*3+Z) obj_joint.scale = (A, A, A) obj_joint.name = "a2a1.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.silver.001"].copy() obj_joint.location = (0.0, 0.0, +Q*1+Z) obj_joint.scale = (A, A, A) obj_joint.name = "y1a2.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, +Q*3+Z) obj_joint.scale = (A, A, A) obj_joint.name = "a2o1.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, -Q*2+Z) obj_joint.scale = (A, A, A) obj_joint.name = "a1b1.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) n = 1 # Pattern 2 of by obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, -Q*1 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 1 of ob obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, +Q*2 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yy obj_joint = bpy.data.objects["joint.gold.B"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"y"+str(n+1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 1 of ob obj_joint = bpy.data.objects["joint.blue.A"].copy() obj_joint.location = (0.0, 0.0, +Q*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".lower.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yy obj_joint = bpy.data.objects["joint.gold.C"].copy() obj_joint.location = (0.0, 0.0, -Q*2+Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"y"+str(n+1)+".lower.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.gold.B"].copy() obj_joint.location = (0.0, 0.0, +Q*2 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "a"+str(n+1)+"w"+str(n)+".lower.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.gold.A3"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n)+"w"+str(n+1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) n = 2 obj_joint = bpy.data.objects["joint.gold.B"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n)+"w"+str(n+1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of by obj_joint = bpy.data.objects["joint.green.A"].copy() obj_joint.location = (0.0, 0.0, -Q*1 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yo obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, +Q*1 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yo obj_joint = bpy.data.objects["joint.gold.D"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"w"+str(n-1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of by obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, +Q*7 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".lower.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yy obj_joint = bpy.data.objects["joint.gold.B"].copy() obj_joint.location = (0.0, 0.0, +Q*6 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"y"+str(n+1)+".lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yo obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, +Q*5 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 1 of ob obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, +Q*6 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yy obj_joint = bpy.data.objects["joint.gold.B"].copy() obj_joint.location = (0.0, 0.0, +Q*6 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"y"+str(n+1)+".lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yo obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, +Q*5 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 1 of ob obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, +Q*6 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) n = 3 obj_joint = bpy.data.objects["joint.gold.A2"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n)+"w"+str(n+1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of by obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, +Q*7 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 1 of ob obj_joint = bpy.data.objects["joint.blue.C"].copy() obj_joint.location = (0.0, 0.0, +Q*1 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(1)+"b"+str(n)+".lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yo obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, +Q*8 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of by obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, +Q*7 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 1 of ob obj_joint = bpy.data.objects["joint.blue.C"].copy() obj_joint.location = (0.0, 0.0, +Q*1 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(1)+"b"+str(n)+".lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # Pattern 2 of yo obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, +Q*8 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) for n in range(4, 6): obj_joint = bpy.data.objects["joint.cursor"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n)+"w"+str(n+1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) for ob in context.scene.objects: if "mesh" in ob.name: ob.select = True bpy.ops.object.make_single_user(type='SELECTED_OBJECTS', object=True, obdata=True, material=True, texture=True, animation=True) bpy.context.scene.cursor_location = (0.0, 0.0, 0.0) bpy.ops.object.origin_set(type='ORIGIN_CURSOR') # Parent set fingers to arm def setParent(self, helicity, move, rig, yaw_loc, yaw_rot, pitch_loc, pitch_rot, pitch, body): # yaw position rig.location = yaw_loc rig.rotation_euler = yaw_rot # pitch position pitch.rig.location = pitch_loc pitch.rig.rotation_euler = pitch_rot # pitch to yaw bpy.ops.object.mode_set(mode='OBJECT') bpy.context.scene.frame_current = 0 bpy.ops.object.select_all(action='DESELECT') rig.select = True bpy.context.scene.objects.active = rig bpy.ops.object.editmode_toggle() parent_bone = 'y2w1.upper' # choose the bone name which you want to be the parent rig.data.edit_bones.active = rig.data.edit_bones[parent_bone] bpy.ops.object.mode_set(mode='OBJECT') bpy.ops.object.select_all(action='DESELECT') #deselect all objects pitch.rig.select = True rig.select = True bpy.context.scene.objects.active = rig #the active object will be the parent of all selected object bpy.ops.object.parent_set(type='BONE', keep_transform=True) bpy.ops.object.select_all(action='DESELECT') #deselect all objects # end j = 1 cns = body.rig.pose.bones['w' +str(j) +'w' +str(j+2)+'.upper.right'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'w5w6.upper' cns.chain_count = 1 cns.use_stretch = False cns = body.rig.pose.bones['w' +str(j) +'w' +str(j+2)+'.upper.left'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'w5w6.upper' cns.chain_count = 1 cns.use_stretch = False j = 2 cns = body.rig.pose.bones['w' +str(j) +'w' +str(j+1)+'.upper'].constraints.new('COPY_LOCATION') cns.name = 'Copy Location' cns.target = rig cns.subtarget = 'w4w5.upper' cns = body.rig.pose.bones['w' +str(j) +'w' +str(j+1)+'.upper'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'w5w6.upper' cns.chain_count = 1 cns.use_stretch = False cns = body.rig.pose.bones['w' +str(j) +'w' +str(j+1)+'.upper'].constraints.new('COPY_ROTATION') cns.name = 'Copy Rotation' cns.target = rig cns.subtarget = 'a2a1' cns.target_space = 'LOCAL' cns.owner_space = 'WORLD' j = 4 cns = body.rig.pose.bones['y'+str(j) +'y'+str(j+1)+'.lower.left'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'w1b3.lower.left' cns.pole_target = rig cns.pole_subtarget = 'o2b3.lower.left' cns.pole_angle = 0 cns.iterations = 500 cns.chain_count = 3 cns.use_stretch = False cns = body.rig.pose.bones['y'+str(j) +'y'+str(j+1)+'.lower.right'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'w1b3.lower.right' cns.pole_target = rig cns.pole_subtarget = 'o2b3.lower.right' cns.pole_angle = math.radians(180) cns.iterations = 500 cns.chain_count = 3 cns.use_stretch = False class Pitch(Formula): J = 2 #joint number #frame_start = bpy.context.scene.frame_start #frame_end = bpy.context.scene.frame_end #bpy.context.scene.frame_current = frame_end interval = 120 frame_start = 133 frame_end = 148 # Overriding def __init__(self, P, A, move, part, helicity, start, end, body_loc, body_rot, body): # pivot factor self.P = P # scale factor self.A = A # name self.move = move # element self.part = part # element helicity self.helicity = helicity self.start = start self.end = end # body self.body_loc = body_loc self.body_rot = body_rot self.body = body bpy.ops.object.mode_set(mode='OBJECT') # Create armature and object self.amt = bpy.data.armatures.new(move + '.' + part + '.' + helicity + '.data') self.rig = bpy.data.objects.new(move + '.' + part + '.' + helicity, self.amt) # Joints α(n) -> a[n], β(n) -> b[n], γ(n) -> y[n] self.a = [0 for i in range(4)] # Joint α self.b = [0 for i in range(self.J)] # Joint β self.y = [0 for i in range(self.J)] # Joint γ # Configuration Movement self.configMovement(self.P, self.A, self.J, self.a, self.b, self.y) # Construction Movement self.constructMovement(self.J, self.helicity, self.amt, self.rig, self.a, self.b, self.y) # Parent body to pitch self.setParent(self.helicity, self.move, self.rig, self.body_loc, self.body_rot, self.body) # Construction Rotation self.configRotation(self.rig, self.interval, self.frame_start, self.frame_end, self.start, self.end) # Configuration Linkage self.configLink(self.A*0.3, self.J, self.helicity, self.rig, self.move, self.part) # Construction Linkage self.constructLink(self.A*0.3, self.J, self.helicity, self.rig, self.move, self.part) def configMovement(self, P, A, J, a, b, y): mat_a = [0 for i in range(4)] # Joint α matrix mat_b = [0 for i in range(self.J)] # Joint β matrix mat_y = [0 for i in range(self.J)] # Joint γ matrix a[1] = mathutils.Euler((P, A, 0), 'XYZ') print ("a1 =", a[1]) a[2] = mathutils.Euler((A, -A, 0), 'XYZ') print ("a2 =", a[2]) b[1] = mathutils.Euler((-A, A, 0), 'XYZ') print ("b1 =", b[1]) y[1] = mathutils.Euler((-A, -A, 0), 'XYZ') print ("y1 =", y[1]) mat_y[1] = Matrix.Translation(y[1]) def constructMovement(self, J, helicity, amt, rig, a, b, y): # Linkages aa = [[0 for i in range(4)] for j in range(4)] # Link α(i) - α(j) ab = [[0 for i in range(4)] for j in range(4)] # Link α(i) - β(j) ya = [[0 for i in range(4)] for j in range(4)] # Link γ(i) - α(j) by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) rig.location = mathutils.Euler((0.0, 0.0, 0.0), 'XYZ') rig.show_x_ray = True amt.show_names = True # amt.draw_type = 'STICK' amt.draw_type = 'BBONE' # Link object to scene scn = bpy.context.scene scn.objects.link(rig) scn.objects.active = rig scn.update() # Edit bpy.ops.object.editmode_toggle() # Construction Linkage aa[2][1] = amt.edit_bones.new('a2a1') aa[2][1].head = a[2] aa[2][1].tail = a[1] ab[1][1] = amt.edit_bones.new('a1b1') ab[1][1].head = a[1] ab[1][1].tail = b[1] ab[1][1].parent = aa[2][1] by[1][1] = amt.edit_bones.new('b1y1') by[1][1].head = b[1] by[1][1].tail = y[1] by[1][1].parent = ab[1][1] by[1][1].use_inherit_rotation = False ya[1][2] = amt.edit_bones.new('y1a2') ya[1][2].head = y[1] ya[1][2].tail = a[2] ya[1][2].parent = by[1][1] # all bones select #bpy.ops.pose.select_all(action="SELECT") for b in amt.edit_bones: b.select = True if helicity == 'right': bpy.ops.armature.calculate_roll(type='GLOBAL_POS_Z') else: bpy.ops.armature.calculate_roll(type='GLOBAL_NEG_Z') # Bone constraints. Armature must be in pose mode. bpy.ops.object.mode_set(mode='POSE') # IK constraint cns = rig.pose.bones['y1a2'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'a2a1' cns.chain_count = 2 cns.use_stretch = False bpy.ops.object.mode_set(mode='OBJECT') def configLink(self, A, J, helicity, rig, move, part): bpy.ops.object.mode_set(mode='OBJECT') Q = (0.18648+0.146446)*A # Z = -Q*2 Z = 0.0 obj_joint = bpy.data.objects["joint.gold.000"].copy() obj_joint.location = (0.0, 0.0, -Q*3+Z) obj_joint.scale = (A, A, A) obj_joint.name = "a2a1.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.silver.A"].copy() obj_joint.location = (0.0, 0.0, +Q+Z) obj_joint.scale = (A, A, A) obj_joint.name = "y1a2.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, -Q*2+Z) obj_joint.scale = (A, A, A) obj_joint.name = "a1b1.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) n = 1 obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*((n+1) % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) for ob in context.scene.objects: if "mesh" in ob.name: ob.select = True bpy.ops.object.make_single_user(type='SELECTED_OBJECTS', object=True, obdata=True, material=True, texture=True, animation=True) bpy.context.scene.cursor_location = (0.0, 0.0, 0.0) bpy.ops.object.origin_set(type='ORIGIN_CURSOR') # Parent set fingers to arm def setParent(self, helicity, move, rig, body_loc, body_rot, body): # body position body.rig.location = body_loc body.rig.rotation_euler = body_rot # body to pitch bpy.ops.object.mode_set(mode='OBJECT') bpy.context.scene.frame_current = 0 bpy.ops.object.select_all(action='DESELECT') rig.select = True bpy.context.scene.objects.active = rig bpy.ops.object.editmode_toggle() parent_bone = 'b1y1' # choose the bone name which you want to be the parent rig.data.edit_bones.active = rig.data.edit_bones[parent_bone] bpy.ops.object.mode_set(mode='OBJECT') bpy.ops.object.select_all(action='DESELECT') #deselect all objects body.rig.select = True rig.select = True bpy.context.scene.objects.active = rig #the active object will be the parent of all selected object bpy.ops.object.parent_set(type='BONE', keep_transform=True) bpy.ops.object.select_all(action='DESELECT') #deselect all objects # end class Body(Formula): J = 7 #joint number #frame_start = bpy.context.scene.frame_start #frame_end = bpy.context.scene.frame_end #bpy.context.scene.frame_current = frame_end interval = 120 frame_start = 133 frame_end = 148 # Overriding def __init__(self, P, A, move, part, helicity, start, end, arm_left_loc, arm_left_rot, arm_left, arm_right_loc, arm_right_rot, arm_right): # pivot factor self.P = P # scale factor self.A = A # name self.move = move # element self.part = part # element helicity self.helicity = helicity self.start = start self.end = end bpy.ops.object.mode_set(mode='OBJECT') # Create armature and object self.amt = bpy.data.armatures.new(move + '.' + part + '.' + helicity + '.data') self.rig = bpy.data.objects.new(move + '.' + part + '.' + helicity, self.amt) self.arm_left_loc = arm_left_loc self.arm_left_rot = arm_left_rot self.arm_left = arm_left self.arm_right_loc = arm_right_loc self.arm_right_rot = arm_right_rot self.arm_right = arm_right # Centroid # Joints α(n) -> a[n], β(n) -> b[n], γ(n) -> y[n], δ(n) -> o[n] self.a = [0 for i in range(3)] # Joint α self.b = [0 for i in range(2)] # Joint β self.y = [0 for i in range(2)] # Joint γ self.o = [0 for i in range(2)] # Joint δ # Upper body # Joints α(n) -> a[n], β(n) -> b[n], γ(n) -> y[n], δ(n) -> o[n] self.upper_b = [0 for i in range(self.J)] # Joint β self.upper_y = [0 for i in range(self.J)] # Joint γ self.upper_o = [0 for i in range(self.J)] # Joint δ # Joints ω(n) -> w[n] self.upper_w = [0 for i in range(self.J)] # Joint ω # Left shoulder # Joints α(n) -> a[n], β(n) -> b[n], γ(n) -> y[n], δ(n) -> o[n] self.upper_left_b = [0 for i in range(self.J)] # Joint β self.upper_left_y = [0 for i in range(self.J)] # Joint γ self.upper_left_o = [0 for i in range(self.J)] # Joint δ self.upper_left_w = [0 for i in range(self.J)] # Joint ω matrix # Right shoulder # Joints α(n) -> a[n], β(n) -> b[n], γ(n) -> y[n], δ(n) -> o[n] self.upper_right_b = [0 for i in range(self.J)] # Joint β self.upper_right_y = [0 for i in range(self.J)] # Joint γ self.upper_right_o = [0 for i in range(self.J)] # Joint δ self.upper_right_w = [0 for i in range(self.J)] # Joint ω matrix # Lower body # Joints α(n) -> a[n], β(n) -> b[n], γ(n) -> y[n], δ(n) -> o[n] self.lower_b = [0 for i in range(self.J)] # Joint β self.lower_y = [0 for i in range(self.J)] # Joint γ self.lower_o = [0 for i in range(self.J)] # Joint δ # Joints ω(n) -> w[n] self.lower_w = [0 for i in range(self.J)] # Joint ω # Left leg # Joints α(n) -> a[n], β(n) -> b[n], γ(n) -> y[n], δ(n) -> o[n] self.lower_left_b = [0 for i in range(self.J)] # Joint β self.lower_left_y = [0 for i in range(self.J)] # Joint γ self.lower_left_o = [0 for i in range(self.J)] # Joint δ # Right leg # Joints α(n) -> a[n], β(n) -> b[n], γ(n) -> y[n], δ(n) -> o[n] self.lower_right_b = [0 for i in range(self.J)] # Joint β self.lower_right_y = [0 for i in range(self.J)] # Joint γ self.lower_right_o = [0 for i in range(self.J)] # Joint δ # gimbal self.gimbal_lower_left_o = [0 for i in range(self.J)] # Joint δ self.gimbal_lower_left_b = [0 for i in range(self.J)] # Joint β self.gimbal_lower_right_o = [0 for i in range(self.J)] # Joint δ self.gimbal_lower_right_b = [0 for i in range(self.J)] # Joint β # Configuration Movement self.configMovement(self.P, self.A, self.J, self.a, self.b, self.y, self.o, self.upper_b, self.upper_y, self.upper_o, self.upper_w, self.upper_left_b, self.upper_left_y, self.upper_left_o, self.upper_left_w, self.upper_right_b, self.upper_right_y, self.upper_right_o, self.upper_right_w, self.lower_b, self.lower_y, self.lower_o, self.lower_w, self.lower_left_b, self.lower_left_y, self.lower_left_o, self.lower_right_b, self.lower_right_y, self.lower_right_o, self.gimbal_lower_left_o, self.gimbal_lower_left_b, self.gimbal_lower_right_o, self.gimbal_lower_right_b) # Construction Movement self.constructMovement(self.J, self.amt, self.rig, self.a, self.b, self.y, self.o, self.upper_b, self.upper_y, self.upper_o, self.upper_w, self.upper_left_b, self.upper_left_y, self.upper_left_o, self.upper_left_w, self.upper_right_b, self.upper_right_y, self.upper_right_o, self.upper_right_w, self.lower_b, self.lower_y, self.lower_o, self.lower_w, self.lower_left_b, self.lower_left_y, self.lower_left_o, self.lower_right_b, self.lower_right_y, self.lower_right_o, self.gimbal_lower_left_o, self.gimbal_lower_left_b, self.gimbal_lower_right_o, self.gimbal_lower_right_b) # Parent set arms to body self.setParent(self.helicity, self.move, self.rig, self.arm_left_loc, self.arm_left_rot, self.arm_left, self.arm_right_loc, self.arm_right_rot, self.arm_right) # Construction Rotation self.configRotation(self.rig, self.interval, self.frame_start, self.frame_end, self.start, self.end) self.configLink(self.A*0.7, self.J, self.helicity, self.rig, self.move, self.part) # Construction Linkage self.constructLink(self.A*0.7, self.J, self.helicity, self.rig, self.move, self.part) # Overriding Configuration Movement def configMovement(self, P, A, J, a, b, y, o, upper_b, upper_y, upper_o, upper_w, upper_left_b, upper_left_y, upper_left_o, upper_left_w, upper_right_b, upper_right_y, upper_right_o, upper_right_w, lower_b, lower_y, lower_o, lower_w, lower_left_b, lower_left_y, lower_left_o, lower_right_b, lower_right_y, lower_right_o, gimbal_lower_left_o, gimbal_lower_left_b, gimbal_lower_right_o, gimbal_lower_right_b): a[1] = mathutils.Euler((P, A, 0), 'XYZ') print ("a1 =", a[1]) a[2] = mathutils.Euler((A, -A, 0), 'XYZ') print ("a2 =", a[2]) b[1] = mathutils.Euler((-A, A, 0), 'XYZ') print ("b1 =", b[1]) o[1] = mathutils.Euler((A, A, 0), 'XYZ') print ("o1 =", o[1]) y[1] = mathutils.Euler((-A, -A, 0), 'XYZ') print ("y1 =", y[1]) lower_b[2] = mathutils.Euler((1.35031, -1.93408, 0), 'XYZ') print ("b2.lower =", lower_b[2]) lower_o[2] = mathutils.Euler((-1.18173, -3.18999, 0), 'XYZ') print ("o2.lower =", lower_o[2]) lower_y[2] = mathutils.Euler((-0.761987, -3.11885, 0), 'XYZ') print ("y2.lower =", lower_y[2]) lower_y[3] = mathutils.Euler((-0.425565, -8.51839, 0), 'XYZ') print ("y3.lower =", lower_y[3]) lower_w[1] = mathutils.Euler((-0.425565, -8.51839, 2.50277), 'XYZ') print ("w1.lower =", lower_w[1]) lower_left_o[3] = mathutils.Euler((1.76787, -8.43042, 1.81914), 'XYZ') print ("o3.lower.left =", lower_left_o[3]) lower_left_b[4] = mathutils.Euler((1.76787, -19.2299, 5.0545), 'XYZ') print ("b4.lower.left =", lower_left_b[4]) lower_left_y[4] = mathutils.Euler((1.76787, -27.4568, 2.13126), 'XYZ') print ("y4.lower.left =", lower_left_y[4]) lower_left_y[5] = mathutils.Euler((1.76787, -29.0398, 4.39707), 'XYZ') print ("y5.lower.left =", lower_left_y[5]) gimbal_lower_left_o[3] = mathutils.Euler((1.87361, -8.51839, 2.50277), 'XYZ') print ("o3.gimbal.lower.left =", gimbal_lower_left_o[3]) gimbal_lower_left_b[4] = mathutils.Euler((1.87361, -19.7847, 2.50277), 'XYZ') print ("b4.gimbal.lower.left =", gimbal_lower_left_b[4]) lower_right_o[3] = mathutils.Euler((-2.89871, -8.60219, 1.75624), 'XYZ') print ("o3.lower.right =", lower_right_o[3]) lower_right_b[4] = mathutils.Euler((-2.89871, -19.3735, 5.04104), 'XYZ') print ("b4.lower.right =", lower_right_b[4]) lower_right_y[4] = mathutils.Euler((-2.89871, -27.5528, 1.98242), 'XYZ') print ("y4.lower.right =", lower_right_y[4]) lower_right_y[5] = mathutils.Euler((-2.89871, -29.1751, 4.22026), 'XYZ') print ("y5.lower.right =", lower_right_y[5]) gimbal_lower_right_o[3] = mathutils.Euler((-3.01028, -8.51839, 2.50277), 'XYZ') print ("o3.gimbal.lower.right =", gimbal_lower_right_o[3]) gimbal_lower_right_b[4] = mathutils.Euler((-3.01028, -19.7726, 2.50277), 'XYZ') print ("b4.gimbal.lower.right =", gimbal_lower_right_b[4]) upper_b[2] = mathutils.Euler((0.510293, 5.22315, 0), 'XYZ') print ("b2.upper =", upper_b[2]) upper_o[2] = mathutils.Euler((-1.65578, 4.62023, 0), 'XYZ') print ("o2.upper =", upper_o[2]) upper_y[2] = mathutils.Euler((-1.56747, 4.00093, 0), 'XYZ') print ("y2.upper =", upper_y[2]) upper_w[3] = mathutils.Euler((-1.56747, 4.00093, 9.05079), 'XYZ') print ("w3.upper =", upper_w[3]) upper_w[4] = mathutils.Euler((-1.65459, 3.99465, 9.05079), 'XYZ') print ("w4.upper =", upper_w[4]) upper_w[5] = mathutils.Euler((-1.65459, 3.99465, 1.61675), 'XYZ') print ("w5.upper =", upper_w[5]) upper_y[3] = mathutils.Euler((-1.65459, 4.6204, 0), 'XYZ') print ("y3.upper.left =", upper_y[3]) upper_w[2] = mathutils.Euler((-1.65459, 4.6204, 9.05079), 'XYZ') print ("w2.upper =", upper_w[2]) upper_o[3] = mathutils.Euler((-2.07892, 9.71201, 0), 'XYZ') print ("o3.upper =", upper_o[3]) upper_w[1] = mathutils.Euler((-2.07852, 9.71278, 0.712845), 'XYZ') print ("w1.upper =", upper_w[1]) upper_b[4] = mathutils.Euler((-2.07852, 10.4327, 0.669667), 'XYZ') print ("o3.upper =", upper_o[3]) upper_left_y[3] = mathutils.Euler((-1.65578, 4.62023, 0), 'XYZ') print ("y3.upper.left =", upper_left_y[3]) upper_left_b[3] = mathutils.Euler((2.04941, 4.82274, 0), 'XYZ') print ("b3.upper.left =", upper_left_b[3]) upper_left_y[2] = mathutils.Euler((-1.56747, 3.99717, 0), 'XYZ') print ("y2.upper.left =", upper_left_y[2]) upper_left_o[2] = mathutils.Euler((2.28887, 4.24878, 0), 'XYZ') print ("o2.upper.left =", upper_left_o[2]) upper_left_w[1] = mathutils.Euler((2.52833, 3.67482, 0), 'XYZ') print ("w1.upper.left =", upper_left_w[1]) upper_left_w[2] = mathutils.Euler((1.49581, 3.75702, 2.28162), 'XYZ') print ("w2.upper.left =", upper_left_w[2]) upper_left_w[3] = mathutils.Euler((0.480431, 3.83787, 4.52539), 'XYZ') print ("w3.upper.left =", upper_left_w[3]) upper_left_w[4] = mathutils.Euler((-0.54352, 3.9194, 6.78809), 'XYZ') print ("w4.upper.left =", upper_left_w[4]) upper_left_w[5] = mathutils.Euler((2.28863, 3.62687, 0), 'XYZ') print ("w5.upper.left =", upper_left_w[5]) upper_left_w[6] = mathutils.Euler((2.28863, 3.62687, 4.96987), 'XYZ') print ("w6.upper.left =", upper_left_w[6]) upper_right_y[3] = mathutils.Euler((-1.65578, 4.62023, 0), 'XYZ') print ("y3.upper.right =", upper_right_y[3]) upper_right_b[3] = mathutils.Euler((-5.45688, 3.83647, 0), 'XYZ') print ("b3.upper.right =", upper_right_b[3]) upper_right_y[2] = mathutils.Euler((-1.56747, 3.99717, 0), 'XYZ') print ("y2.upper.right =", upper_right_y[2]) upper_right_o[2] = mathutils.Euler((-5.37016, 3.21603, 0), 'XYZ') print ("o2.upper.right =", upper_right_o[2]) upper_right_w[1] = mathutils.Euler((-5.28344, 2.59559, 0), 'XYZ') print ("w1.upper.right =", upper_right_w[1]) upper_right_w[2] = mathutils.Euler((-4.36226, 2.94397, 2.24368), 'XYZ') print ("w2.upper.right =", upper_right_w[2]) upper_right_w[3] = mathutils.Euler((-3.42546, 3.29826, 4.52539), 'XYZ') print ("w3.upper.right =", upper_right_w[3]) upper_right_w[4] = mathutils.Euler((-2.49646, 3.64959, 6.78809), 'XYZ') print ("w4.upper.right =", upper_right_w[4]) upper_right_w[5] = mathutils.Euler((-5.37016, 2.58956, 0), 'XYZ') print ("w5.upper.right =", upper_right_w[5]) upper_right_w[6] = mathutils.Euler((-5.37016, 2.58956, 4.94216), 'XYZ') print ("w6.upper.right =", upper_right_w[6]) def constructMovement(self, J, amt, rig, a, b, y, o, upper_b, upper_y, upper_o, upper_w, upper_left_b, upper_left_y, upper_left_o, upper_left_w, upper_right_b, upper_right_y, upper_right_o, upper_right_w, lower_b, lower_y, lower_o, lower_w, lower_left_b, lower_left_y, lower_left_o, lower_right_b, lower_right_y, lower_right_o, gimbal_lower_left_o, gimbal_lower_left_b, gimbal_lower_right_o, gimbal_lower_right_b): # Linkages aa = [[0 for i in range(3)] for j in range(3)] # Link α(i) - α(j) ab = [[0 for i in range(3)] for j in range(3)] # Link α(i) - β(j) ya = [[0 for i in range(3)] for j in range(3)] # Link γ(i) - α(j) ao = [[0 for i in range(3)] for j in range(3)] # Link α(i) - δ(j) by = [[0 for i in range(2)] for j in range(2)] # Link β(i) - γ(j) upper_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) upper_yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) upper_by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) upper_yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) upper_ow = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) upper_ww = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) upper_left_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) upper_left_yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) upper_left_by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) upper_left_yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) upper_left_ow = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - ω(j) upper_left_ww = [[0 for i in range(self.J)] for j in range(self.J)] # Link ω(i) - ω(j) upper_right_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) upper_right_yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) upper_right_by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) upper_right_yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) upper_right_ow = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - ω(j) upper_right_ww = [[0 for i in range(self.J)] for j in range(self.J)] # Link ω(i) - ω(j) lower_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) lower_yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) lower_by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) lower_yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) lower_yw = [[0 for i in range(2)] for j in range(self.J)] # Link γ(i) - ω(j) lower_left_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) lower_left_yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) lower_left_by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) lower_left_yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) lower_right_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) lower_right_yy = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - δ(j) lower_right_by = [[0 for i in range(self.J)] for j in range(self.J)] # Link β(i) - γ(j) lower_right_yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link γ(i) - γ(j) gimbal_lower_left_yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) gimbal_lower_left_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) gimbal_lower_right_yo = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) gimbal_lower_right_ob = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - β(j) gimbal_upper_left_ow = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - ω(j) gimbal_upper_left_ww = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - ω(j) gimbal_upper_right_ow = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - ω(j) gimbal_upper_right_ww = [[0 for i in range(self.J)] for j in range(self.J)] # Link δ(i) - ω(j) rig.location = mathutils.Euler((0.0, 0.0, 0.0), 'XYZ') rig.show_x_ray = True amt.show_names = True # amt.draw_type = 'STICK' amt.draw_type = 'BBONE' # Link object to scene scn = bpy.context.scene scn.objects.link(rig) scn.objects.active = rig scn.update() # Edit bpy.ops.object.editmode_toggle() j = 1 # Construction Linkage aa[j+1][j] = amt.edit_bones.new('a'+ str(j+1)+'a'+ str(j)) aa[j+1][j].head = a[j+1] aa[j+1][j].tail = a[j] # aa[j+1][j].parent = by[j][j]_body ab[j][j] = amt.edit_bones.new('a'+ str(j)+'b'+ str(j)) ab[j][j].head = a[j] ab[j][j].tail = b[j] ab[j][j].parent = aa[j+1][j] by[j][j] = amt.edit_bones.new('b'+ str(j)+'y'+ str(j)) by[j][j].head = b[j] by[j][j].tail = y[j] by[j][j].parent = ab[j][j] by[j][j].use_inherit_rotation = False ya[j][j+1] = amt.edit_bones.new('y'+ str(j)+'a'+ str(j+1)) ya[j][j+1].head = y[j] ya[j][j+1].tail = a[j+1] ya[j][j+1].parent = by[j][j] ao[j+1][j] = amt.edit_bones.new('a'+ str(j+1)+'o'+str(j)) ao[j+1][j].head = a[j+1] ao[j+1][j].tail = o[j] ao[j+1][j].parent = ya[j][j+1] lower_ob[j][j+1] = amt.edit_bones.new('o'+ str(j)+'b'+ str(j+1)+'.lower') lower_ob[j][j+1].head = o[j] lower_ob[j][j+1].tail = lower_b[j+1] lower_ob[j][j+1].parent = ao[j+1][j] lower_yy[j][j+1] = amt.edit_bones.new('y'+ str(j)+'y'+ str(j+1)+'.lower') lower_yy[j][j+1].head = y[j] lower_yy[j][j+1].tail = lower_y[j+1] lower_yy[j][j+1].parent = by[j][j] upper_ob[j][j+1] = amt.edit_bones.new('o'+ str(j)+'b'+ str(j+1)+'.upper') upper_ob[j][j+1].head = o[j] upper_ob[j][j+1].tail = upper_b[j+1] upper_ob[j][j+1].parent = ao[j+1][j] upper_yy[j][j+1] = amt.edit_bones.new('y'+ str(j)+'y'+ str(j+1)+'.upper') upper_yy[j][j+1].head = y[j] upper_yy[j][j+1].tail = upper_y[j+1] upper_yy[j][j+1].parent = by[j][j] j = 2 lower_by[j][j] = amt.edit_bones.new('b'+ str(j) + 'y'+ str(j) + '.lower') lower_by[j][j].head = lower_b[j] lower_by[j][j].tail = lower_y[j] lower_by[j][j].parent = lower_ob[j-1][j] lower_yy[j][j+1] = amt.edit_bones.new('y'+ str(j) + 'y'+ str(j+1) + '.lower') lower_yy[j][j+1].head = lower_y[j] lower_yy[j][j+1].tail = lower_y[j+1] lower_yy[j][j+1].parent = lower_by[j][j] lower_yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j) + '.lower') lower_yo[j][j].head = lower_y[j] lower_yo[j][j].tail = lower_o[j] lower_yo[j][j].parent = lower_yy[j-1][j] upper_by[j][j] = amt.edit_bones.new('b'+ str(j) + 'y'+ str(j) + '.upper') upper_by[j][j].head = upper_b[j] upper_by[j][j].tail = upper_y[j] upper_by[j][j].parent = upper_ob[j-1][j] upper_yy[j][j+1] = amt.edit_bones.new('y'+ str(j) + 'y'+ str(j+1) + '.upper') upper_yy[j][j+1].head = upper_y[j] upper_yy[j][j+1].tail = upper_y[j+1] upper_yy[j][j+1].parent = upper_by[j][j] # upper w2w3 upper_ww[j][j+1] = amt.edit_bones.new('w'+ str(j) + 'w'+ str(j+1) + '.upper') upper_ww[j][j+1].head = upper_w[j] upper_ww[j][j+1].tail = upper_w[j+1] # upper_ww[j][j+1].parent = upper_yy[j][j+1] # left shoulder gimbal upper_left_yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j) + '.upper.left') upper_left_yo[j][j].head = upper_y[j] upper_left_yo[j][j].tail = upper_left_o[j] upper_left_yo[j][j].parent = upper_yy[j-1][j] upper_left_ob[j][j+1] = amt.edit_bones.new('o' + str(j) + 'b'+ str(j+1) + '.upper.left') upper_left_ob[j][j+1].head = upper_left_o[j] upper_left_ob[j][j+1].tail = upper_left_b[j+1] upper_left_ob[j][j+1].parent = upper_left_yo[j][j] # gimbal o2w5 gimbal_upper_left_ow[j][j+3] = amt.edit_bones.new('o' + str(j) + 'w'+ str(j+3) + '.gimbal.upper.left') gimbal_upper_left_ow[j][j+3].head = upper_left_o[j] gimbal_upper_left_ow[j][j+3].tail = upper_left_w[j+3] gimbal_upper_left_ow[j][j+3].parent = upper_left_ob[j][j+1] upper_left_ow[j][j-1] = amt.edit_bones.new('o' + str(j) + 'w'+ str(j-1) + '.upper.left') upper_left_ow[j][j-1].head = upper_left_o[j] upper_left_ow[j][j-1].tail = upper_left_w[j-1] upper_left_ow[j][j-1].parent = upper_left_ob[j][j+1] # w1w3 upper_left_ww[j-1][j+1] = amt.edit_bones.new('w' + str(j-1) + 'w'+ str(j+1) + '.upper.left') upper_left_ww[j-1][j+1].head = upper_left_w[j-1] upper_left_ww[j-1][j+1].tail = upper_left_w[j+1] upper_left_ww[j-1][j+1].parent = upper_left_ow[j][j-1] # left w3w2 upper_left_ww[j+1][j] = amt.edit_bones.new('w' + str(j+1) + 'w'+ str(j) + '.upper.left') upper_left_ww[j+1][j].head = upper_w[j+1] upper_left_ww[j+1][j].tail = upper_left_w[j] upper_left_ww[j+1][j].parent = upper_ww[j][j+1] # left w2w1 upper_left_ww[j][j-1] = amt.edit_bones.new('w' + str(j) + 'w'+ str(j-1) + '.upper.left') upper_left_ww[j][j-1].head = upper_left_w[j] upper_left_ww[j][j-1].tail = upper_left_w[j-1] upper_left_ww[j][j-1].parent = upper_left_ww[j+1][j] # left gimbal w2w4 gimbal_upper_left_ww[j][j+2] = amt.edit_bones.new('w' + str(j) + 'w'+ str(j+2) +'.gimbal.upper.left') gimbal_upper_left_ww[j][j+2].head = upper_w[j] gimbal_upper_left_ww[j][j+2].tail = upper_w[j+2] gimbal_upper_left_ww[j][j+2].parent = upper_ww[j][j+1] # right shoulder gimbal upper_right_yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j) + '.upper.right') upper_right_yo[j][j].head = upper_y[j] upper_right_yo[j][j].tail = upper_right_o[j] upper_right_yo[j][j].parent = upper_yy[j-1][j] upper_right_ob[j][j+1] = amt.edit_bones.new('o' + str(j) + 'b'+ str(j+1) + '.upper.right') upper_right_ob[j][j+1].head = upper_right_o[j] upper_right_ob[j][j+1].tail = upper_right_b[j+1] upper_right_ob[j][j+1].parent = upper_right_yo[j][j] # gimbal o2w5 gimbal_upper_right_ow[j][j+3] = amt.edit_bones.new('o' + str(j) + 'w'+ str(j+3) + '.gimbal.upper.right') gimbal_upper_right_ow[j][j+3].head = upper_right_o[j] gimbal_upper_right_ow[j][j+3].tail = upper_right_w[j+3] gimbal_upper_right_ow[j][j+3].parent = upper_right_ob[j][j+1] upper_right_ow[j][j-1] = amt.edit_bones.new('o' + str(j) + 'w'+ str(j-1) + '.upper.right') upper_right_ow[j][j-1].head = upper_right_o[j] upper_right_ow[j][j-1].tail = upper_right_w[j-1] upper_right_ow[j][j-1].parent = upper_right_ob[j][j+1] # w1w3 upper_right_ww[j-1][j+1] = amt.edit_bones.new('w' + str(j-1) + 'w'+ str(j+1) + '.upper.right') upper_right_ww[j-1][j+1].head = upper_right_w[j-1] upper_right_ww[j-1][j+1].tail = upper_right_w[j+1] upper_right_ww[j-1][j+1].parent = upper_right_ow[j][j-1] # right w3w2 upper_right_ww[j+1][j] = amt.edit_bones.new('w' + str(j+1) + 'w'+ str(j) + '.upper.right') upper_right_ww[j+1][j].head = upper_w[j+1] upper_right_ww[j+1][j].tail = upper_right_w[j] upper_right_ww[j+1][j].parent = upper_ww[j][j+1] # right w2w1 upper_right_ww[j][j-1] = amt.edit_bones.new('w' + str(j) + 'w'+ str(j-1) + '.upper.right') upper_right_ww[j][j-1].head = upper_right_w[j] upper_right_ww[j][j-1].tail = upper_right_w[j-1] upper_right_ww[j][j-1].parent = upper_right_ww[j+1][j] # right gimbal w2w4 gimbal_upper_right_ww[j][j+2] = amt.edit_bones.new('w' + str(j) + 'w'+ str(j+2) +'.gimbal.upper.right') gimbal_upper_right_ww[j][j+2].head = upper_w[j] gimbal_upper_right_ww[j][j+2].tail = upper_w[j+2] gimbal_upper_right_ww[j][j+2].parent = upper_ww[j][j+1] j = 3 lower_yw[j][1] = amt.edit_bones.new('y'+ str(j) + 'w'+ str(1) + '.lower') lower_yw[j][1].head = lower_y[j] lower_yw[j][1].tail = lower_w[1] lower_yw[j][1].parent = lower_yy[2][j] lower_left_yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j) + '.lower.left') lower_left_yo[j][j].head = lower_w[1] lower_left_yo[j][j].tail = lower_left_o[j] lower_left_yo[j][j].parent = lower_yw[j][1] lower_left_ob[j][j+1] = amt.edit_bones.new('o' + str(j) + 'b'+ str(j+1) + '.lower.left') lower_left_ob[j][j+1].head = lower_left_o[j] lower_left_ob[j][j+1].tail = lower_left_b[j+1] lower_left_ob[j][j+1].parent = lower_left_yo[j][j] lower_right_yo[j][j] = amt.edit_bones.new('y' + str(j) + 'o'+ str(j) +'.lower.right') lower_right_yo[j][j].head = lower_w[1] lower_right_yo[j][j].tail = lower_right_o[j] lower_right_yo[j][j].parent = lower_yw[j][1] lower_right_ob[j][j+1] = amt.edit_bones.new('o' + str(j) + 'b'+ str(j+1) +'.lower.right') lower_right_ob[j][j+1].head = lower_right_o[j] lower_right_ob[j][j+1].tail = lower_right_b[j+1] lower_right_ob[j][j+1].parent = lower_right_yo[j][j] # gimbal gimbal_lower_left_yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j) + '.gimbal.lower.left') gimbal_lower_left_yo[j][j].head = lower_w[1] gimbal_lower_left_yo[j][j].tail = gimbal_lower_left_o[j] gimbal_lower_left_yo[j][j].parent = lower_yw[j][1] gimbal_lower_left_ob[j][j+1] = amt.edit_bones.new('o' + str(j) + 'b'+ str(j+1) + '.gimbal.lower.left') gimbal_lower_left_ob[j][j+1].head = gimbal_lower_left_o[j] gimbal_lower_left_ob[j][j+1].tail = gimbal_lower_left_b[j+1] gimbal_lower_left_ob[j][j+1].parent = gimbal_lower_left_yo[j][j] gimbal_lower_right_yo[j][j] = amt.edit_bones.new('y' + str(j) + 'o'+ str(j) +'.gimbal.lower.right') gimbal_lower_right_yo[j][j].head = lower_w[1] gimbal_lower_right_yo[j][j].tail = gimbal_lower_right_o[j] gimbal_lower_right_yo[j][j].parent = lower_yw[j][1] gimbal_lower_right_ob[j][j+1] = amt.edit_bones.new('o' + str(j) + 'b'+ str(j+1) +'.gimbal.lower.right') gimbal_lower_right_ob[j][j+1].head = gimbal_lower_right_o[j] gimbal_lower_right_ob[j][j+1].tail = gimbal_lower_right_b[j+1] gimbal_lower_right_ob[j][j+1].parent = gimbal_lower_right_yo[j][j] # end upper_left_by[j][j] = amt.edit_bones.new('b'+ str(j) + 'y'+ str(j) + '.upper.left') upper_left_by[j][j].head = upper_left_b[j] upper_left_by[j][j].tail = upper_left_y[j] upper_left_by[j][j].parent = upper_left_ob[j-1][j] upper_right_by[j][j] = amt.edit_bones.new('b'+ str(j) + 'y'+ str(j) + '.upper.right') upper_right_by[j][j].head = upper_right_b[j] upper_right_by[j][j].tail = upper_right_y[j] upper_right_by[j][j].parent = upper_right_ob[j-1][j] upper_yo[j][j] = amt.edit_bones.new('y'+ str(j) + 'o'+ str(j) + '.upper') upper_yo[j][j].head = upper_y[j] upper_yo[j][j].tail = upper_o[j] upper_yo[j][j].parent = upper_yy[j-1][j] upper_ob[j][j+1] = amt.edit_bones.new('o' + str(j) + 'b'+ str(j+1) + '.upper') upper_ob[j][j+1].head = upper_w[1] upper_ob[j][j+1].tail = upper_b[j+1] upper_ob[j][j+1].parent = upper_yo[j][j] upper_left_ww[j][j+1] = amt.edit_bones.new('w' + str(j) + 'w'+ str(j+1) + '.upper.left') upper_left_ww[j][j+1].head = upper_left_w[j] upper_left_ww[j][j+1].tail = upper_left_w[j+1] upper_left_ww[j][j+1].parent = upper_left_ww[j-2][j] upper_right_ww[j][j+1] = amt.edit_bones.new('w' + str(j) + 'w'+ str(j+1) + '.upper.right') upper_right_ww[j][j+1].head = upper_right_w[j] upper_right_ww[j][j+1].tail = upper_right_w[j+1] upper_right_ww[j][j+1].parent = upper_right_ww[j-2][j] j = 4 lower_left_by[j][j] = amt.edit_bones.new('b' + str(j) + 'y' + str(j) +'.lower.left') lower_left_by[j][j].head = lower_left_b[j] lower_left_by[j][j].tail = lower_left_y[j] lower_left_by[j][j].parent = lower_left_ob[j-1][j] lower_left_yy[j][j+1] = amt.edit_bones.new('y' + str(j) + 'y' + str(j+1) +'.lower.left') lower_left_yy[j][j+1].head = lower_left_y[j] lower_left_yy[j][j+1].tail = lower_left_y[j+1] lower_left_yy[j][j+1].parent = lower_left_by[j][j] # gimbal w4w5 gimbal_upper_left_ww[j][j+1] = amt.edit_bones.new('w' + str(j) + 'w'+ str(j+1) +'.gimbal.upper.left') gimbal_upper_left_ww[j][j+1].head = upper_w[j] gimbal_upper_left_ww[j][j+1].tail = upper_w[j+1] gimbal_upper_left_ww[j][j+1].parent = gimbal_upper_left_ww[j-2][j] lower_right_by[j][j] = amt.edit_bones.new('b' + str(j) + 'y' + str(j) +'.lower.right') lower_right_by[j][j].head = lower_right_b[j] lower_right_by[j][j].tail = lower_right_y[j] lower_right_by[j][j].parent = lower_right_ob[j-1][j] lower_right_yy[j][j+1] = amt.edit_bones.new('y' + str(j) + 'y' + str(j+1) +'.lower.right') lower_right_yy[j][j+1].head = lower_right_y[j] lower_right_yy[j][j+1].tail = lower_right_y[j+1] lower_right_yy[j][j+1].parent = lower_right_by[j][j] # gimbal w4w5 gimbal_upper_right_ww[j][j+1] = amt.edit_bones.new('w' + str(j) + 'w'+ str(j+1) +'.gimbal.upper.right') gimbal_upper_right_ww[j][j+1].head = upper_w[j] gimbal_upper_right_ww[j][j+1].tail = upper_w[j+1] gimbal_upper_right_ww[j][j+1].parent = gimbal_upper_right_ww[j-2][j] j = 5 # gimbal w5w6 gimbal_upper_left_ww[j][j+1] = amt.edit_bones.new('w' + str(j) + 'w'+ str(j+1) + '.gimbal.upper.left') gimbal_upper_left_ww[j][j+1].head = upper_left_w[j] gimbal_upper_left_ww[j][j+1].tail = upper_left_w[j+1] gimbal_upper_left_ww[j][j+1].parent = gimbal_upper_left_ow[j-3][j] gimbal_upper_right_ww[j][j+1] = amt.edit_bones.new('w' + str(j) + 'w'+ str(j+1) + '.gimbal.upper.right') gimbal_upper_right_ww[j][j+1].head = upper_right_w[j] gimbal_upper_right_ww[j][j+1].tail = upper_right_w[j+1] gimbal_upper_right_ww[j][j+1].parent = gimbal_upper_right_ow[j-3][j] # all bones select #bpy.ops.pose.select_all(action="SELECT") for b in amt.edit_bones: b.select = True bpy.ops.armature.calculate_roll(type='GLOBAL_NEG_Z') for b in amt.edit_bones: b.select = False amt.edit_bones["o3b4.lower.left"].select = True amt.edit_bones["b4y4.lower.left"].select = True amt.edit_bones["y4y5.lower.left"].select = True bpy.ops.armature.calculate_roll(type='GLOBAL_NEG_X') for b in amt.edit_bones: b.select = False amt.edit_bones["o3b4.lower.right"].select = True amt.edit_bones["b4y4.lower.right"].select = True amt.edit_bones["y4y5.lower.right"].select = True bpy.ops.armature.calculate_roll(type='GLOBAL_POS_X') # Bone constraints. Armature must be in pose mode. bpy.ops.object.mode_set(mode='POSE') # IK constraint j = 1 cns = rig.pose.bones['y' +str(j) +'a' +str(j+1)].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'a'+str(j+1)+'a'+str(j) cns.chain_count = 2 cns.use_stretch = False j = 2 cns = rig.pose.bones['b'+str(j) +'y'+str(j)+'.lower'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'y'+str(j)+'o'+str(j)+'.lower' cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False cns = rig.pose.bones['b'+str(j) +'y'+str(j)+'.upper'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'y'+str(j)+'o'+str(j)+'.upper.left' cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False cns = rig.pose.bones['w' +str(j+1) +'w' +str(j)+'.upper.left'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'w' +str(j-1) +'w' +str(j+1)+'.upper.left' cns.chain_count = 1 cns.use_stretch = False cns = rig.pose.bones['w' +str(j+1) +'w' +str(j)+'.upper.right'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'w' +str(j-1) +'w' +str(j+1)+'.upper.right' cns.chain_count = 1 cns.use_stretch = False j = 3 cns = rig.pose.bones['b'+str(j) +'y'+str(j)+'.upper.left'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'y'+str(j)+'o'+str(j)+'.upper' cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False cns = rig.pose.bones['b'+str(j) +'y'+str(j)+'.upper.right'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'y'+str(j)+'o'+str(j)+'.upper' cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False cns = rig.pose.bones['o'+str(j) +'b'+str(j+1)+'.gimbal.lower.left'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'b'+str(j+1)+'y'+str(j+1)+'.lower.left' cns.pole_target = rig cns.pole_subtarget = 'o'+str(j)+'b'+str(j+1)+'.lower.left' cns.pole_angle = 0 cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False cns = rig.pose.bones['o'+str(j) +'b'+str(j+1)+'.gimbal.lower.right'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'b'+str(j+1)+'y'+str(j+1)+'.lower.right' cns.pole_target = rig cns.pole_subtarget = 'o'+str(j)+'b'+str(j+1)+'.lower.right' cns.pole_angle = math.radians(180) cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False j = 4 cns = rig.pose.bones['w'+str(j) +'w'+str(j+1)+'.gimbal.upper.left'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'w'+str(j-2)+'w'+str(j-3)+'.upper.left' cns.pole_target = rig cns.pole_subtarget = 'w'+str(j-1)+'w'+str(j-2)+'.upper.left' cns.pole_angle = math.radians(-90) cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False cns = rig.pose.bones['w'+str(j) +'w'+str(j+1)+'.gimbal.upper.right'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'w'+str(j-2)+'w'+str(j-3)+'.upper.right' cns.pole_target = rig cns.pole_subtarget = 'w'+str(j-1)+'w'+str(j-2)+'.upper.right' cns.pole_angle = math.radians(-90) cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False j = 5 cns = rig.pose.bones['w'+str(j) +'w'+str(j+1)+'.gimbal.upper.left'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'w'+str(j-2)+'w'+str(j-1)+'.upper.left' cns.pole_target = rig cns.pole_subtarget = 'w'+str(j-4)+'w'+str(j-2)+'.upper.left' cns.pole_angle = math.radians(90) cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False cns = rig.pose.bones['w'+str(j) +'w'+str(j+1)+'.gimbal.upper.right'].constraints.new('IK') cns.name = 'Ik' cns.target = rig cns.subtarget = 'w'+str(j-2)+'w'+str(j-1)+'.upper.right' cns.pole_target = rig cns.pole_subtarget = 'w'+str(j-4)+'w'+str(j-2)+'.upper.right' cns.pole_angle = math.radians(90) cns.iterations = 500 cns.chain_count = 2 cns.use_stretch = False bpy.ops.object.mode_set(mode='OBJECT') def configLink(self, A, J, helicity, rig, move, part): bpy.ops.object.mode_set(mode='OBJECT') Q = (0.18648+0.146446)*A # Z = -Q*2 Z = 0.0 n = 1 obj_joint = bpy.data.objects["joint.gold.E"].copy() obj_joint.location = (0.0, 0.0, -Q*3+Z) obj_joint.scale = (A, A, A) obj_joint.name = 'a'+ str(n+1)+'a'+ str(n)+ ".mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, -Q*2+Z) obj_joint.scale = (A, A, A) obj_joint.name = 'a'+ str(n)+'b'+ str(n)+ ".mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*((n+1) % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.silver.001"].copy() obj_joint.location = (0.0, 0.0, +Q+Z) obj_joint.scale = (A, A, A) obj_joint.name = 'y'+ str(n)+'a'+ str(n+1)+".mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, +Q*3+Z) obj_joint.scale = (A, A, A) obj_joint.name = 'a'+ str(n+1)+'o'+ str(n)+".mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, -Q*2 + Q*(n % 2)*6 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".lower.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.gold.00"+str(1 + (n+1) % 2)].copy() obj_joint.location = (0.0, 0.0, +Q*(1 - (n % 2))*2+Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"y"+str(n+1)+".lower.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, -Q*2 + Q*(n % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.gold.00"+str(1 + (n+1) % 2)].copy() obj_joint.location = (0.0, 0.0, +Q*(1 - (n % 2))*2+Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"y"+str(n+1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) n = 2 obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*((n+1) % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".lower.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.gold.00"+str(1 + (n+1) % 2)].copy() obj_joint.location = (0.0, 0.0, +Q*(1 - (n % 2))*2+Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"y"+str(n+1)+".lower.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*(n % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".lower.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*((n+1) % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.gold.00"+str(1 + (n+1) % 2)].copy() obj_joint.location = (0.0, 0.0, +Q*(1 - (n % 2))*2+Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"y"+str(n+1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*(n % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*(n % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.gold.B.R"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"w"+str(n-1)+".upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.cursor"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n-1)+"w"+str(n+1)+".upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.cursor"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n+1)+"w"+str(n+2)+".upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w2w5.gimbal obj_joint = bpy.data.objects["joint.gold.g1.y.C.R2"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"w"+str(n+3)+".gimbal.upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w5w6.gimbal obj_joint = bpy.data.objects["joint.silver.g1.z.C.R2"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n+3)+"w"+str(n+4)+".gimbal.upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.gold.B.L"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"w"+str(n-1)+".upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.cursor"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n-1)+"w"+str(n+1)+".upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.cursor"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n+1)+"w"+str(n+2)+".upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w2w5.gimbal obj_joint = bpy.data.objects["joint.gold.g1.y.C.L2"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"w"+str(n+3)+".gimbal.upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w5w6.gimbal obj_joint = bpy.data.objects["joint.silver.g1.z.C.L2"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n+3)+"w"+str(n+4)+".gimbal.upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w2w3.upper obj_joint = bpy.data.objects["joint.gold.B2"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n)+"w"+str(n+1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w2w4.gimbal.upper.left obj_joint = bpy.data.objects["joint.gold.g1.y.C.L"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n)+"w"+str(n+2)+".gimbal.upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w4w5.gimbal.upper.left obj_joint = bpy.data.objects["joint.silver.g1.z.C.L"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n+2)+"w"+str(n+3)+".gimbal.upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w3w2.upper.left obj_joint = bpy.data.objects["joint.cursor"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n+1)+"w"+str(n)+".upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w2w1.upper.left obj_joint = bpy.data.objects["joint.cursor"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n)+"w"+str(n-1)+".upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w2w4.gimbal.upper.right obj_joint = bpy.data.objects["joint.gold.g1.y.C.R"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n)+"w"+str(n+2)+".gimbal.upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w4w5.gimbal.upper.right obj_joint = bpy.data.objects["joint.silver.g1.z.C.R"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n+2)+"w"+str(n+3)+".gimbal.upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w3w2.upper.right obj_joint = bpy.data.objects["joint.cursor"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n+1)+"w"+str(n)+".upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) # w2w1.upper.right obj_joint = bpy.data.objects["joint.cursor"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "w"+str(n)+"w"+str(n-1)+".upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) n = 3 obj_joint = bpy.data.objects["joint.gold.A"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"w"+str(1)+".lower.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.copper.A"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.B"].copy() # obj_joint.location = (0.0, 0.0, -Q*2 + Q*(n % 2)*6 +Z) obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.copper.A"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.B"].copy() # obj_joint.location = (0.0, 0.0, -Q*2 + Q*(n % 2)*6 +Z) obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.copper.g1.y.B"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".gimbal.lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.g1.z.B"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".gimbal.lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.copper.g1.y.B"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".gimbal.lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.g1.z.B"].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".gimbal.lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*((n+1) % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".upper.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*((n+1) % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".upper.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.copper.001"].copy() obj_joint.location = (0.0, 0.0, -Q + Q*(n % 2)*4 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"o"+str(n)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.blue.001"].copy() obj_joint.location = (0.0, 0.0, -Q*2 + Q*(n % 2)*6 +Z) obj_joint.scale = (A, A, A) obj_joint.name = "o"+str(n)+"b"+str(n+1)+".upper.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) n = 4 obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, Q +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.gold.00"+str(1 + (n+1) % 2)].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"y"+str(n+1)+".lower.left.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.green.001"].copy() obj_joint.location = (0.0, 0.0, Q +Z) obj_joint.scale = (A, A, A) obj_joint.name = "b"+str(n)+"y"+str(n)+".lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) obj_joint = bpy.data.objects["joint.gold.00"+str(1 + (n+1) % 2)].copy() obj_joint.location = (0.0, 0.0, 0.0) obj_joint.scale = (A, A, A) obj_joint.name = "y"+str(n)+"y"+str(n+1)+".lower.right.mesh." + move + '.' + part +'.' + helicity bpy.context.scene.objects.link(obj_joint) for ob in context.scene.objects: if "mesh" in ob.name: ob.select = True bpy.ops.object.make_single_user(type='SELECTED_OBJECTS', object=True, obdata=True, material=True, texture=True, animation=True) bpy.context.scene.cursor_location = (0.0, 0.0, 0.0) bpy.ops.object.origin_set(type='ORIGIN_CURSOR') # Parent set arms to body def setParent(self, helicity, move, rig, arm_left_loc, arm_left_rot, arm_left, arm_right_loc, arm_right_rot, arm_right): bpy.ops.object.mode_set(mode='OBJECT') bpy.context.scene.frame_current = 0 # arm left bpy.ops.object.select_all(action='DESELECT') rig.select = True bpy.context.scene.objects.active = rig bpy.ops.object.editmode_toggle() # parent_bone = 'o2b3.upper.left' # choose the bone name which you want to be the parent parent_bone = 'o2w5.gimbal.upper.left' # choose the bone name which you want to be the parent rig.data.edit_bones.active = rig.data.edit_bones[parent_bone] bpy.ops.object.mode_set(mode='OBJECT') bpy.ops.object.select_all(action='DESELECT') #deselect all objects arm_left.rig.select = True rig.select = True bpy.context.scene.objects.active = rig #the active object will be the parent of all selected object bpy.ops.object.parent_set(type='BONE', keep_transform=True) # arm left end # arm right bpy.ops.object.select_all(action='DESELECT') #deselect all objects rig.select = True bpy.context.scene.objects.active = rig bpy.ops.object.editmode_toggle() # parent_bone = 'o2b3.upper.right' # choose the bone name which you want to be the parent parent_bone = 'o2w5.gimbal.upper.right' # choose the bone name which you want to be the parent rig.data.edit_bones.active = rig.data.edit_bones[parent_bone] bpy.ops.object.mode_set(mode='OBJECT') bpy.ops.object.select_all(action='DESELECT') #deselect all objects arm_right.rig.select = True rig.select = True bpy.context.scene.objects.active = rig #the active object will be the parent of all selected object bpy.ops.object.parent_set(type='BONE', keep_transform=True) # arm right end bpy.ops.object.select_all(action='DESELECT') #deselect all objects # arms position arm_left.rig.location = arm_left_loc arm_left.rig.rotation_euler = arm_left_rot arm_right.rig.location = arm_right_loc arm_right.rig.rotation_euler = arm_right_rot class Arm(Formula): J = 5 #joint number #frame_start = bpy.context.scene.frame_start #frame_end = bpy.context.scene.frame_end #bpy.context.scene.frame_current = frame_end interval = 120 frame_start = 133 frame_end = 148 # Overriding def __init__(self, P, A, move, part, helicity, start, end, fingers_loc, fingers_rot, middle_finger): # pivot factor self.P = P # scale factor self.A = A # name self.move = move # element self.part = part # element helicity self.helicity = helicity self.start = start self.end = end # fingers position self.fingers_loc = fingers_loc self.fingers_rot = fingers_rot # middle_finger self.middle_finger = middle_finger bpy.ops.object.mode_set(mode='OBJECT') # Create armature and object self.amt = bpy.data.armatures.new(move + '.' + part + '.' + helicity + '.data') self.rig = bpy.data.objects.new(move + '.' + part + '.' + helicity, self.amt) # Joints self.a = [0 for i in range(4)] # Joint α self.b = [0 for i in range(self.J)] # Joint β self.y = [0 for i in range(self.J)] # Joint γ self.o = [0 for i in range(self.J)] # Joint δ # Configuration Movement self.configMovement(self.P, self.A, self.J, self.a, self.b, self.y, self.o) # Construction Movement self.constructMovement(self.J, self.helicity, self.amt, self.rig, self.a, self.b, self.y, self.o) # Parent set fingers to arm self.setParent(self.helicity, self.move, self.rig, self.fingers_loc, self.fingers_rot, self.middle_finger) # Construction Rotation self.configRotation(self.rig, self.interval, self.frame_start, self.frame_end, self.start, self.end) # Configuration Linkage self.configLink(self.A, self.J, self.helicity, self.rig, self.move, self.part) # Construction Linkage self.constructLink(self.A, self.J, self.helicity, self.rig, self.move, self.part) # Overriding Configuration Movement def configMovement(self, P, A, J, a, b, y, o): a[1] = mathutils.Euler((P, A, 0), 'XYZ') print ("a1 =", a[1]) a[2] = mathutils.Euler((A, -A, 0), 'XYZ') print ("a2 =", a[2]) b[1] = mathutils.Euler((-A, A, 0), 'XYZ') print ("b1 =", b[1]) o[1] = mathutils.Euler((A, A, 0), 'XYZ') print ("o1 =", o[1]) B = A * 2 * sqrt (2) C = B + (B * sqrt (2)) D = C * sqrt (2) E = C + D y[1] = mathutils.Euler((-A, -A, 0), 'XYZ') print ("y1 =", y[1]) b[2] = mathutils.Euler((5.36277, -3.83599, 0), 'XYZ') print ("b2 =", b[2]) b[3] = mathutils.Euler((8.70172, -3.80032, 0), 'XYZ') print ("b3 =", b[3]) y[2] = mathutils.Euler((4.45922, -4.71667, 0), 'XYZ') print ("y2 =", y[2]) y[3] = mathutils.Euler((9.98465, -3.94095, 0), 'XYZ') print ("y3 =", y[3]) o[2] = mathutils.Euler((3.97637, -4.57217, 0), 'XYZ') print ("o2 =", o[2]) o[3] = mathutils.Euler((10.0529, -4.3022, 0), 'XYZ') print ("o3 =", o[3]) y[4] = mathutils.Euler((10.8499, -3.82056, 0), 'XYZ') print ("y4 =", y[4]) # Parent set fingers to arm def setParent(self, helicity, move, rig, fingers_loc, fingers_rot, middle_finger): bpy.ops.object.mode_set(mode='OBJECT') bpy.context.scene.frame_current = 0 bpy.ops.object.select_all(action='DESELECT') rig.select = True bpy.context.scene.objects.active = rig bpy.ops.object.editmode_toggle() parent_bone = 'y3y4' # choose the bone name which you want to be the parent rig.data.edit_bones.active = rig.data.edit_bones[parent_bone] bpy.ops.object.mode_set(mode='OBJECT') bpy.ops.object.select_all(action='DESELECT') #deselect all objects middle_finger.rig.select = True # bpy.data.objects[move+'.middle.'+ helicity].select = True rig.select = True bpy.context.scene.objects.active = rig #the active object will be the parent of all selected object bpy.ops.object.parent_set(type='BONE', keep_transform=True) bpy.ops.object.select_all(action='DESELECT') #deselect all objects # fingers position middle_finger.rig.location.x += fingers_loc[0] middle_finger.rig.location.y += fingers_loc[1] middle_finger.rig.location.z += fingers_loc[2] middle_finger.rig.rotation_euler = fingers_rot class Finger(Formula): J = 6 #joint number #frame_start = bpy.context.scene.frame_start #frame_end = bpy.context.scene.frame_end #bpy.context.scene.frame_current = frame_end interval = 120 frame_start = 0 frame_end = 120 # Overriding def __init__(self, P, A, move, part, helicity, start, end, y2, y3, y4, y5): # pivot factor self.P = P # scale factor self.A = A # name self.move = move # element self.part = part # element helicity self.helicity = helicity self.start = start self.end = end # phalanx length self.y2 = y2 self.y3 = y3 self.y4 = y4 self.y5 = y5 bpy.ops.object.mode_set(mode='OBJECT') # Create armature and object self.amt = bpy.data.armatures.new(move + '.' + part + '.' + helicity + '.data') self.rig = bpy.data.objects.new(move + '.' + part + '.' + helicity, self.amt) # Joints self.a = [0 for i in range(4)] # Joint α self.b = [0 for i in range(self.J)] # Joint β self.y = [0 for i in range(self.J)] # Joint γ self.o = [0 for i in range(self.J)] # Joint δ # Configuration Movement self.configMovement(self.P, self.A, self.J, self.a, self.b, self.y, self.o, self.y2, self.y3, self.y4, self.y5) # Construction Movement self.constructMovement(self.J, self.helicity, self.amt, self.rig, self.a, self.b, self.y, self.o) # Construction Rotation self.configRotation(self.rig, self.interval, self.frame_start, self.frame_end, self.start, self.end) # Configuration Linkage self.configLink(self.A, self.J, self.helicity, self.rig, self.move, self.part) # Construction Linkage self.constructLink(self.A, self.J, self.helicity, self.rig, self.move, self.part) # Overriding Configuration Movement def configMovement(self, P, A, J, a, b, y, o, y2, y3, y4, y5): a[1] = mathutils.Euler((P, A, 0), 'XYZ') print ("a1 =", a[1]) a[2] = mathutils.Euler((A, -A, 0), 'XYZ') print ("a2 =", a[2]) b[1] = mathutils.Euler((-A, A, 0), 'XYZ') print ("b1 =", b[1]) o[1] = mathutils.Euler((A, A, 0), 'XYZ') print ("o1 =", o[1]) B = A * 2 * sqrt (2) C = B + (B * sqrt (2)) D = C * sqrt (2) E = C + D y[1] = mathutils.Euler((-A, -A, 0), 'XYZ') print ("y1 =", y[1]) y[2] = y2 print ("y2 =", y[2]) y[3] = y3 print ("y3 =", y[3]) y[4] = y4 print ("y4 =", y[4]) y[5] = y5 print ("y5 =", y[5]) b[2] = mathutils.Euler((y[2].x+0.10012, y[2].y+0.170067, 0), 'XYZ') print ("b2 =", b[2]) b[3] = mathutils.Euler((y[3].x-0.12471, y[3].y-0.03395, 0), 'XYZ') print ("b3 =", b[3]) b[4] = mathutils.Euler((y[4].x-0.11426, y[4].y-0.03342, 0), 'XYZ') print ("b4 =", b[4]) o[2] = mathutils.Euler((y[2].x+0.09016, y[2].y+0.142795, 0), 'XYZ') print ("o2 =", o[2]) o[3] = mathutils.Euler((y[3].x+0.07367, y[3].y+0.09711, 0), 'XYZ') print ("o3 =", o[3]) o[4] = mathutils.Euler((y[4].x+0.00899, y[4].y+0.03297, 0), 'XYZ') print ("o4 =", o[4]) def formula(): # pivot factor P = 0 # scale factor A = 1 # name move = 'formula' # element part = 'universe' # left or right helicity = 'left' start = 0 end = start+360 formula = Formula(P, A, move, part, helicity, start, end) def hands(): # name move = 'kungfu' # scale factor A = 0.107 # pivot factor P = -0.048266 # finger element part = 'middle' # phalanx length y2 = mathutils.Euler((1.427, -1.08668, 0), 'XYZ') y3 = mathutils.Euler((2.15534, -1.56395, 0), 'XYZ') y4 = mathutils.Euler((2.67012, -1.90121, 0), 'XYZ') y5 = mathutils.Euler((2.90459, -2.05473, 0), 'XYZ') # config nonlocal global middle_left global middle_right # left finger element helicity = 'left' start = 720-124 end = start middle_left = Finger(P, A, move, part, helicity, start, end, y2, y3, y4, y5) middle_left.rig.location = (0, 0, 0) middle_left.rig.rotation_euler = mathutils.Euler((math.radians(0), math.radians(0), math.radians(0)), 'XYZ') # right finger element helicity = 'right' start = 124 end = start middle_right = Finger(P, A, move, part, helicity, start, end, y2, y3, y4, y5) middle_right.rig.location = (0, 0, 0) middle_right.rig.rotation_euler = mathutils.Euler((math.radians(180-0), math.radians(0), math.radians(0)), 'XYZ') # finger element part = 'ring' y2 = mathutils.Euler((1.36978, -1.04933, 0), 'XYZ') y3 = mathutils.Euler((2.16696, -1.57161, 0), 'XYZ') y4 = mathutils.Euler((2.63809, -1.8803, 0), 'XYZ') y5 = mathutils.Euler((2.87256, -2.03382, 0), 'XYZ') # left finger element helicity = 'left' start = 720-124 end = start ring_left = Finger(P, A, move, part, helicity, start, end, y2, y3, y4, y5) ring_left.rig.location = (-0.010689, 0.001192, 0.241051) ring_left.rig.rotation_euler = mathutils.Euler((math.radians(-5.10153), math.radians(-1.70737), math.radians(0.02464)), 'XYZ') # right finger element helicity = 'right' start = 124 end = start ring_right = Finger(P, A, move, part, helicity, start, end, y2, y3, y4, y5) ring_right.rig.location = (-0.010689, -0.001192, 0.241051) ring_right.rig.rotation_euler = mathutils.Euler((math.radians(180+5.10153), math.radians(-1.70737), math.radians(-0.02464)), 'XYZ') # finger element part = 'little' y2 = mathutils.Euler((1.45986, -1.08525, 0), 'XYZ') y3 = mathutils.Euler((2.10861, -1.50077, 0), 'XYZ') y4 = mathutils.Euler((2.5324, -1.77219, 0), 'XYZ') y5 = mathutils.Euler((2.72302, -1.89418, 0), 'XYZ') # left finger element helicity = 'left' start = 720-124 end = start little_left = Finger(P, A, move, part, helicity, start, end, y2, y3, y4, y5) little_left.rig.location = (-0.020568, 0.002289, 0.463882) little_left.rig.rotation_euler = mathutils.Euler((math.radians(-10.1646), math.radians(-2.09755), math.radians(-0.518101)), 'XYZ') # right finger element helicity = 'right' start = 124 end = start little_right = Finger(P, A, move, part, helicity, start, end, y2, y3, y4, y5) little_right.rig.location = (-0.020568, -0.002289, 0.463882) little_right.rig.rotation_euler = mathutils.Euler((math.radians(180+10.1646), math.radians(-2.09755), math.radians(0.518101)), 'XYZ') # finger element part = 'index' y2 = mathutils.Euler((1.36561, -1.0465, 0), 'XYZ') y3 = mathutils.Euler((2.0559, -1.49887, 0), 'XYZ') y4 = mathutils.Euler((2.52701, -1.80756, 0), 'XYZ') y5 = mathutils.Euler((2.76149, -1.96108, 0), 'XYZ') # left finger element helicity = 'left' start = 720-124 end = start index_left = Finger(P, A, move, part, helicity, start, end, y2, y3, y4, y5) index_left.rig.location = (0.012703, -0.00141, -0.286505) index_left.rig.rotation_euler = mathutils.Euler((math.radians(2.53073), math.radians(2.85122), math.radians(0.320067)), 'XYZ') # right finger element helicity = 'right' start = 124 end = start index_right = Finger(P, A, move, part, helicity, start, end, y2, y3, y4, y5) index_right.rig.location = (0.012703, 0.00141, -0.286505) index_right.rig.rotation_euler = mathutils.Euler((math.radians(180-2.53073), math.radians(2.85122), math.radians(-0.320067)), 'XYZ') # finger element P = -0.075869 #pivot factor start = 124 end = start part = 'thumb' y2 = mathutils.Euler((0.265988, -0.219792, 0), 'XYZ') y3 = mathutils.Euler((1.0999, -0.768173, 0), 'XYZ') y4 = mathutils.Euler((1.71494, -1.17263, 0), 'XYZ') y5 = mathutils.Euler((1.97601, -1.3443, 0), 'XYZ') # left finger element helicity = 'left' start = 720-124 end = start thumb_left = Finger(P, A, move, part, helicity, start, end, y2, y3, y4, y5) thumb_left.rig.location = (0.009956, -0.090396, -0.3247) thumb_left.rig.rotation_euler = mathutils.Euler((math.radians(87.8968), math.radians(-3.16487), math.radians(-23.1096)), 'XYZ') # right finger element helicity = 'right' start = 124 end = start thumb_right = Finger(P, A, move, part, helicity, start, end, y2, y3, y4, y5) thumb_right.rig.location = (0.009956, 0.090396, -0.3247) thumb_right.rig.rotation_euler = mathutils.Euler((math.radians(180-87.8968), math.radians(-3.16487), math.radians(23.1096)), 'XYZ') # Parent set four fingers to middle finger bpy.ops.object.mode_set(mode='OBJECT') bpy.context.scene.frame_current = 0 # left hand bpy.ops.object.select_all(action='DESELECT') middle_left.rig.select = True bpy.context.scene.objects.active = middle_left.rig bpy.ops.object.editmode_toggle() parent_bone = 'a2a1' # choose the bone name which you want to be the parent middle_left.rig.data.edit_bones.active = middle_left.rig.data.edit_bones[parent_bone] bpy.ops.object.mode_set(mode='OBJECT') bpy.ops.object.select_all(action='DESELECT') #deselect all objects ring_left.rig.select = True little_left.rig.select = True index_left.rig.select = True thumb_left.rig.select = True middle_left.rig.select = True bpy.context.scene.objects.active = middle_left.rig #the active object will be the parent of all selected object bpy.ops.object.parent_set(type='BONE', keep_transform=True) # right hand bpy.ops.object.select_all(action='DESELECT') #deselect all objects middle_right.rig.select = True bpy.context.scene.objects.active = middle_right.rig bpy.ops.object.editmode_toggle() parent_bone = 'a2a1' # choose the bone name which you want to be the parent middle_right.rig.data.edit_bones.active = middle_right.rig.data.edit_bones[parent_bone] bpy.ops.object.mode_set(mode='OBJECT') bpy.ops.object.select_all(action='DESELECT') #deselect all objects ring_right.rig.select = True little_right.rig.select = True index_right.rig.select = True thumb_right.rig.select = True middle_right.rig.select = True bpy.context.scene.objects.active = middle_right.rig #the active object will be the parent of all selected object bpy.ops.object.parent_set(type='BONE', keep_transform=True) bpy.ops.object.select_all(action='DESELECT') #deselect all objects def arms(): # scale factor A = 0.473 # pivot factor P = (A * 0.5) # name move = 'kungfu' # arm element part = 'arm' # left arm element helicity = 'left' start = -1138-67+180 end = start+360 fingers_loc = (9.93914, -3.98605, 0.102497) fingers_rot = mathutils.Euler((math.radians(71.0974), math.radians(-37.0012), math.radians(24.6771)), 'XYZ') global middle_left middle_finger = middle_left global arm_left arm_left = Arm(P, A, move, part, helicity, start, end, fingers_loc, fingers_rot, middle_finger) # right arm element helicity = 'right' start = 720-(-1138-67) end = start-360 fingers_loc = (9.93914, -3.98605, 0.102497) fingers_rot = mathutils.Euler((math.radians(-47.5806), math.radians(41.2298), math.radians(26.8721)), 'XYZ') global middle_right middle_finger = middle_right global arm_right arm_right = Arm(P, A, move, part, helicity, start, end, fingers_loc, fingers_rot, middle_finger) def body(): # scale factor A = 1 # pivot factor P = -(A * 0.724843) # name move = 'kungfu' # arm element part = 'body' # helicity of element helicity = 'right' start = 720 - 425 end = start + 360 # start = 295 # end = 632.6244 global arm_left global arm_right arm_left_loc = (2.74172, 4.13548, -0.088542) arm_left_rot = mathutils.Euler((math.radians(-120.006), math.radians(-53.0662), math.radians(148.417)), 'XYZ') arm_right_loc = (-5.56559, 3.16373, -0.440029) arm_right_rot = mathutils.Euler((math.radians(110.568), math.radians(-134.792), math.radians(-131.795)), 'XYZ') global body body = Body(P, A, move, part, helicity, start, end, arm_left_loc, arm_left_rot, arm_left, arm_right_loc, arm_right_rot, arm_right) def pitch(): # scale factor A = 2 # pivot factor P = -1.65 # name move = 'kungfu' # arm element part = 'pitch' # helicity of element helicity = 'left' start = -3170.27 end = -2450.27 global body body_loc = (-2.02365, 1.5293, -2.88764) body_rot = mathutils.Euler((math.radians(11.0558), math.radians(95.1801), math.radians(60.6234)), 'XYZ') global pitch pitch = Pitch(P, A, move, part, helicity, start, end, body_loc, body_rot, body) def yaw(): # scale factor A = 5 # pivot factor P = -4.6 # name move = 'kungfu' # arm element part = 'yaw' # helicity of element helicity = 'left' start = 2084+95 end = 1724+95 global pitch pitch_loc = (-0.588748, -2.53526, 25.8234) pitch_rot = mathutils.Euler((math.radians(90.0), math.radians(45.0), math.radians(-125.0)), 'XYZ') global body yaw_loc = (5.13868, -0.546263, 1.65167) yaw_rot = mathutils.Euler((math.radians(0.0), math.radians(0.0), math.radians(0.0-104.719)), 'XYZ') yaw = Yaw(P, A, move, part, helicity, start, end, yaw_loc, yaw_rot, pitch_loc, pitch_rot, pitch, body) def main(origin): # formula() hands() arms() body() #roll pitch() yaw() if __name__ == "__main__": # renaming of corrada objects # for ob in context.scene.objects: # if "joint_" in ob.name: # ob.name = ob.name.replace("_", ".") main((0,0,0))

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null

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6

00f1a90195dc859aa38834bb2958b9eb7af2fd6f

84

py

Python

dask/dataframe/io/parquet/__init__.py

Juanlu001/dask

ba29ba377ae71e5a90fa5ef5198c7d317b45c06a

[ "BSD-3-Clause" ]

9,684

2016-02-12T16:09:21.000Z

2022-03-31T19:38:26.000Z

dask/dataframe/io/parquet/__init__.py

Juanlu001/dask

ba29ba377ae71e5a90fa5ef5198c7d317b45c06a

[ "BSD-3-Clause" ]

7,059

2016-02-11T18:32:45.000Z

2022-03-31T22:12:40.000Z

dask/dataframe/io/parquet/__init__.py

Juanlu001/dask

ba29ba377ae71e5a90fa5ef5198c7d317b45c06a

[ "BSD-3-Clause" ]

1,794

2016-02-13T23:28:39.000Z

2022-03-30T14:33:19.000Z

from .core import create_metadata_file, read_parquet, read_parquet_part, to_parquet

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6

dafbc3bec26a74b4d432d63450fc177a7ba0d8ac

103

py

Python

common/views.py

vanflymen/Twenty-One

1b425dd11a53b135ead5e6d721980b22f4a54672

[ "MIT" ]

3

2017-01-06T20:01:12.000Z

2021-04-07T10:59:26.000Z

common/views.py

vanflymen/Twenty-One

1b425dd11a53b135ead5e6d721980b22f4a54672

[ "MIT" ]

null

common/views.py

vanflymen/Twenty-One

1b425dd11a53b135ead5e6d721980b22f4a54672

[ "MIT" ]

2

2019-09-17T18:36:56.000Z

2021-04-17T13:48:31.000Z

from django.shortcuts import render, redirect def index(request): return redirect('habit:index')

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9757253d8495985fe04a747cc7fc9f38d1b08559

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py

Python

servicedirectory/src/sd-api/classes/tests/tests_serializers.py

ealogar/servicedirectory

fb4f4bfa8b499b93c03af589ef2f34c08a830b17

[ "Apache-2.0" ]

null

servicedirectory/src/sd-api/classes/tests/tests_serializers.py

ealogar/servicedirectory

fb4f4bfa8b499b93c03af589ef2f34c08a830b17

[ "Apache-2.0" ]

null

servicedirectory/src/sd-api/classes/tests/tests_serializers.py

ealogar/servicedirectory

fb4f4bfa8b499b93c03af589ef2f34c08a830b17

[ "Apache-2.0" ]

null

''' (c) Copyright 2013 Telefonica, I+D. Printed in Spain (Europe). All Rights Reserved. The copyright to the software program(s) is property of Telefonica I+D. The program(s) may be used and or copied only with the express written consent of Telefonica I+D or in accordance with the terms and conditions stipulated in the agreement/contract under which the program(s) have been supplied. ''' from unittest import TestCase from mock import MagicMock, patch from commons.json_schema_validator.schema_reader import SchemaField from bson.objectid import ObjectId from classes.serializers import ServiceInstanceSerializer, ServiceClassCollectionSerializer,\ ServiceClassItemSerializer from commons.json_schema_validator.schema_reader import SchemaReader from re import match class InstancesSerializerTests(TestCase): def setUp(self): super(InstancesSerializerTests, self).setUp() mock_schema_instance = MagicMock(name='mock_schema_instance') mock_schema_instance.return_value = [ SchemaField(name='uri', field_type='string', required=True, min_length=1, max_length=2048), SchemaField(name='version', field_type='string', required=True, min_length=1, max_length=256), SchemaField(name='environment', field_type='string', required=False, min_length=1, max_length=512, default='production'), SchemaField(name='class_name', field_type='string', required=True, min_length=1, max_length=512) ] # mock schema instance schema_reader = SchemaReader() self.patcher_validate = patch.object(schema_reader, 'validate_object') # @UndefinedVariable self.patcher_schema = patch.object(schema_reader, # @UndefinedVariable 'get_schema_fields', mock_schema_instance) self.patcher_schema.start() self.patcher_validate.start() def tearDown(self): self.patcher_schema.stop() self.patcher_validate.stop() def test_deserialize_instance_should_work(self): serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class'}) self.assertEquals(True, serializer.is_valid(), "Serialization invalid") def test_serialize_valid_instance_should_work(self): id_ = ObjectId() serializer = ServiceInstanceSerializer({'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', '_id': id_}) self.assertEquals(serializer.data['id'], str(id_)) def test_deserialize_instance_empty_params_should_return_invalid(self): serializer = ServiceInstanceSerializer(data={'uri': '', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class'}) self.assertEquals(False, serializer.is_valid(), "Deserialization invalid") self.assertEquals(serializer.errors['uri'][0], 'invalid') serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '', 'environment': 'test', 'class_name': 'test_class'}) self.assertEquals(False, serializer.is_valid(), "Deserialization invalid") self.assertEquals(serializer.errors['version'][0], 'invalid') serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': ''}) self.assertEquals(False, serializer.is_valid(), "Deserialization invalid") self.assertEquals(serializer.errors['class_name'][0], 'invalid') def test_deserialize_instance_null_required_params_should_return_required(self): serializer = ServiceInstanceSerializer(data={'version': '1.0', 'environment': 'test', 'class_name': 'test_class'}) self.assertEquals(False, serializer.is_valid(), "Deserialization invalid") self.assertEquals(serializer.errors['uri'][0], 'required') serializer = ServiceInstanceSerializer(data={'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'uri': None}) self.assertEquals(False, serializer.is_valid(), "Deserialization invalid") self.assertEquals(serializer.errors['uri'][0], 'required') serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'environment': 'test', 'class_name': 'test_class'}) self.assertEquals(False, serializer.is_valid(), "Deserialization invalid") self.assertEquals(serializer.errors['version'][0], 'required') serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test'}) self.assertEquals(False, serializer.is_valid(), "Deserialization invalid") self.assertEquals(serializer.errors['class_name'][0], 'required') def test_deserialize_instance_large_params_should_return_invalid(self): serializer = ServiceInstanceSerializer(data={'uri': 'a' * 2500, 'version': '1.0', 'environment': 'test', 'class_name': 'test_class'}) self.assertEquals(False, serializer.is_valid(), "Deserialization invalid") self.assertEquals(serializer.errors['uri'][0], 'invalid') serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': 'v' * 300, 'environment': 'test', 'class_name': 'test_class'}) self.assertEquals(False, serializer.is_valid(), "Deserialization invalid") self.assertEquals(serializer.errors['version'][0], 'invalid') serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'a' * 600}) self.assertEquals(False, serializer.is_valid(), "Deserialization invalid") self.assertEquals(serializer.errors['class_name'][0], 'invalid') def test_deserialize_instance_with_attributes_should_work(self): serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': {'key': 'keyvalue'}}) self.assertEquals(True, serializer.is_valid(), "Serialization invalid") def test_deserialize_several_instances_with_attributes_should_work(self): serializer_lists = [ {'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': {'key': 'keyvalue'}}, {'uri': 'url_test2', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': {'key_dos': 'keyvalue'}} ] serializer = ServiceInstanceSerializer(data=serializer_lists, many=True) self.assertEquals(True, serializer.is_valid(), "Serialization invalid") # Ensure that attributes keys are not included when null data is given self.assertTrue('key_dos' not in serializer.data[0]['attributes'], 'key_dos is present in attributes') self.assertTrue('key' not in serializer.data[1]['attributes'], 'key is present in attributes') def test_deserialize_instance_with_invalid_attributes_should_give_error(self): serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': {'key': 1}}) self.assertEquals(False, serializer.is_valid()) self.assertEquals("Invalid parameter value: 1", serializer.errors['attributes'][0], 'Invalid error message') def test_deserialize_instance_with_uppercase_attributes_should_give_error(self): serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': {'KEY': '1'}}) self.assertEquals(False, serializer.is_valid()) self.assertEquals("Invalid parameter value: KEY", serializer.errors['attributes'][0], 'Invalid error message') def test_deserialize_instance_with_null_attributes_should_give_error(self): serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': None }) self.assertEquals(False, serializer.is_valid()) self.assertEquals("Invalid parameter value: null", serializer.errors['attributes'][0], 'Invalid error message') def test_deserialize_instance_with_bad_format_attributes_should_give_error(self): serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': 25 }) self.assertEquals(False, serializer.is_valid()) self.assertEquals("Invalid parameter value: 25", serializer.errors['attributes'][0], 'Invalid error message') def test_deserialize_instance_with_wrong_size_attributes_should_give_error(self): attributes = dict((str(e), str(e)) for e in range(129)) serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': attributes }) self.assertEquals(False, serializer.is_valid()) self.assertTrue(match("Invalid parameter value: {*", serializer.errors['attributes'][0])) def test_deserialize_instance_with_wrong_key_size_attributes_should_give_error(self): attributes = {'': 'value'} serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': attributes }) self.assertEquals(False, serializer.is_valid()) self.assertTrue(match("Invalid parameter value: empty-string", serializer.errors['attributes'][0])) attributes = {'k' * 513: 'value'} serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': attributes }) self.assertEquals(False, serializer.is_valid()) self.assertTrue(match("Invalid parameter value: {0}".format('k' * 513), serializer.errors['attributes'][0])) def test_deserialize_instance_with_wrong_value_size_attributes_should_give_error(self): attributes = {'kye': ''} serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': attributes }) self.assertEquals(False, serializer.is_valid()) self.assertTrue(match("invalid", serializer.errors['attributes'][0]['kye'][0])) attributes = {'key': 'k' * 513} serializer = ServiceInstanceSerializer(data={'uri': 'url_test', 'version': '1.0', 'environment': 'test', 'class_name': 'test_class', 'attributes': attributes }) self.assertEquals(False, serializer.is_valid()) self.assertTrue(match("invalid", serializer.errors['attributes'][0]['key'][0])) def test_deserialize_instance_with_bad_format_url_should_give_error(self): serializer = ServiceInstanceSerializer(data={'uri': 1, 'version': '1.0', 'environment': 'test', 'class_name': 'test_class'}) self.assertEquals(False, serializer.is_valid()) self.assertEquals("invalid", serializer.errors['uri'][0], 'Invalid error message') def test_deserialize_instance_with_empty_string_environment_should_give_error(self): serializer = ServiceInstanceSerializer(data={'uri': "http", 'version': '1.0', 'environment': '', 'class_name': 'test_class'}) self.assertEquals(False, serializer.is_valid()) self.assertEquals("invalid", serializer.errors['environment'][0], 'Invalid error message') class ClassesSerializerTests(TestCase): def setUp(self): super(ClassesSerializerTests, self).setUp() mock_schema_instance = MagicMock(name='mock_schema_instance') mock_schema_instance.return_value = [ SchemaField(name='_id', field_type='string', required=True, min_length=1, max_length=512), SchemaField(name='description', field_type='string', required=False), SchemaField(name='default_version', field_type='string', required=True, min_length=1, max_length=256) ] mock_get_schema_fields = MagicMock(name='mock_get_schema') mock_get_schema_fields.return_value = mock_schema_instance # mock schema instance schema_reader = SchemaReader() self.patcher_validate = patch.object(schema_reader, 'validate_object') # @UndefinedVariable self.patcher_schema = patch.object(schema_reader, # @UndefinedVariable 'get_schema_fields', mock_schema_instance) self.patcher_schema.start() self.patcher_validate.start() def tearDown(self): self.patcher_schema.stop() self.patcher_validate.stop() def test_deserialize_class_should_work(self): # We need to do import here in order generic patches work serializer = ServiceClassCollectionSerializer(data={'class_name': 'class_test', 'default_version': '1.0', 'description': 'test'}) self.assertEquals(True, serializer.is_valid(), "Serialization invalid") def test_deserialize_class_empty_class_name_should_give_error_invalid(self): # We need to do import here in order generic patches work serializer = ServiceClassCollectionSerializer(data={'class_name': '', 'version': '1.0', 'description': 'test'}) self.assertEquals(False, serializer.is_valid(), "Serialization invalid") self.assertEquals(u"invalid", serializer.errors['class_name'][0], 'Invalid error message') def test_deserialize_class_null_class_name_should_give_required_error(self): # We need to do import here in order generic patches work serializer = ServiceClassCollectionSerializer(data={'default_version': '1.0', 'description': 'test'}) self.assertEquals(False, serializer.is_valid(), "Serialization invalid") self.assertEquals(u"required", serializer.errors['class_name'][0], 'Invalid error message') def test_deserialize_class_large_user_ne_should_give_invalid_error(self): # We need to do import here in order generic patches work serializer = ServiceClassCollectionSerializer(data={'class_name': 'a' * 600, 'default_version': '1.0', 'description': 'test'}) self.assertEquals(False, serializer.is_valid(), "Serialization invalid") self.assertEquals(u"invalid", serializer.errors['class_name'][0], 'Invalid error message') def test_serialize_class_item_should_return_class_name(self): # We need to do import here in order generic patches work serializer = ServiceClassItemSerializer({'_id': 'my_class', 'default_version': '1.0', 'description': 'test'}) self.assertTrue('class_name' in serializer.data, 'class_name not returned')

59.328671

119

0.605787

1,631

16,968

6.077866

0.112201

0.077474

0.025421

0.058106

0.80571

0.791688

0.781802

0.759609

0.726924

0.707556

0

0.012016

0.274104

16,968

285

120

59.536842

0.792807

0.050212

0

0.565789

0

0.198733

0

0.245614

1

0.109649

false

0

0.030702

0

0.149123

0

null

0

1

0

null

0

6

97896605f94b2b9815b4eec103d0e79022b4737e

29

py

Python

07_debug_exceptions_testing/entropy/__init__.py

UWSEDS/lecture-materials

42f24ce191efc4a193ac4a84e067519045f7f7c3

[ "BSD-2-Clause" ]

null

07_debug_exceptions_testing/entropy/__init__.py

UWSEDS/lecture-materials

42f24ce191efc4a193ac4a84e067519045f7f7c3

[ "BSD-2-Clause" ]

null

07_debug_exceptions_testing/entropy/__init__.py

UWSEDS/lecture-materials

42f24ce191efc4a193ac4a84e067519045f7f7c3

[ "BSD-2-Clause" ]

4

2020-10-09T01:07:19.000Z

2020-12-11T23:11:35.000Z

from .entropy import entropy

14.5

28

0.827586

4

29

6

0.75

0

0.137931

29

1

29

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

8ae7cffe61a2e3b67f1d98d3ccd23249c93da3f8

2,790

py

Python

CEC/ideal_F.py

ZongSingHuang/Metaheuristic-benchmark

a454ee02ffe206d925a6193a60cf6bcb772213a0

[ "MIT" ]

null

CEC/ideal_F.py

ZongSingHuang/Metaheuristic-benchmark

a454ee02ffe206d925a6193a60cf6bcb772213a0

[ "MIT" ]

null

CEC/ideal_F.py

ZongSingHuang/Metaheuristic-benchmark

a454ee02ffe206d925a6193a60cf6bcb772213a0

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Thu Aug 26 15:01:28 2021 @author: zongsing.huang """ def Sphere(): return 0.0 def Rastrigin(): return 0.0 def Ackley(): return 0.0 def Griewank(): return 0.0 def Schwefel_P222(): return 0.0 def Rosenbrock(): return 0.0 def Sehwwefel_P221(): return 0.0 def Quartic(): return 0.0 def Schwefel_P12(): return 0.0 def Penalized1(): return 0.0 def Penalized2(): return 0.0 def Schwefel_226(D): return -418.982887272433799807913601398*D def Step(): return 0 def Kowalik(): return 0.00030748610 def ShekelFoxholes(): return 0.998003837794449325873406851315 def GoldsteinPrice(): return 3 def Shekel(m=5): if m==5: return -10.1532 if m==7: return -10.4029 if m==10: return -10.5364 def Branin(): return 0.39788735772973816 def Hartmann3(): return -3.86278214782076 def SixHumpCamelBack(): return -1.031628453489877 def Hartmann6(): return -3.32236801141551 def Zakharov(): return 0.0 def SumSquares(): return 0.0 def Alpine(): return 0.0 def Michalewicz(D): if D==1: return -0.801303410098552549 if D==2: return -1.80130341009855321 if D==5: return -4.687658 if D==10: return -9.66015 def Exponential(): return -1.0 def Schaffer(): return 0.0 def BentCigar(): return 0.0 def Bohachevsky1(): return 0.0 def Elliptic(): return 0.0 def DropWave(): return -1.0 def CosineMixture(D): return -0.1*D def Ellipsoidal(): return 0.0 def LevyandMontalvo1(): return 0.0 #%% def Easom(): return -1.0 def SumofDifferentPower(): return 0.0 def LevyandMontalvo2(): return 0.0 def Holzman(): return 0.0 def XinSheYang1(): return -1.0 def XinSheYang6(): return -1.0 def Beale(): return 0.0 def Shubert(): return -186.7309 def InvertedCosineMixture(): return 0.0 def Salomon(): return 0.0 def Matyas(): return 0.0 def Leon(): return 0.0 def Paviani(): return -45.7784684040686 def Sinusoidal(): return -3.5 def ktablet(): return 0.0 def NoncontinuousRastrigin(): return 0.0 def Fletcher(): pass def Levy(): return 0.0 def Davis(): return 0.0 def Pathological(): return 0.0 def Schwefel_P220(): return 0.0 def Booth(): return 0.0 def Zettl(): return -0.003791237220468656 def PowellQuartic(): return 0.0 def Tablet(): return 0.0 def Brown(): return 0.0 def ChungReynolds(): return 0.0 def Csendes(): return 0.0 def Bohachevsky2(): return 0.0 def Bohachevsky3(): return 0.0 def Colville(): return 0.0 def BartelsConn(): return 1.0 def Bird(): return -106.7645367198034

12.624434

45

0.62043

394

2,790

4.380711

0.307107

0.202781

0.199305

0.274044

0.044032

0

0.2

0.258065

2,790

221

46

12.624434

0.633816

0.030466

0

0.328767

0

1

0.458904

false

0.006849

0

0.438356

0.945205

0

null

1

0

null

0

1

0

1

0

6

8af3e0b2f22116348f4996e037e2fc3b8297536e

256

py

Python

hubspot/marketing/transactional/api/__init__.py

Ronfer/hubspot-api-python

1c87274ecbba4aa3c7728f890ccc6e77b2b6d2e4

[ "Apache-2.0" ]

117

2020-04-06T08:22:53.000Z

2022-03-18T03:41:29.000Z

hubspot/marketing/transactional/api/__init__.py

Ronfer/hubspot-api-python

1c87274ecbba4aa3c7728f890ccc6e77b2b6d2e4

[ "Apache-2.0" ]

62

2020-04-06T16:21:06.000Z

2022-03-17T16:50:44.000Z

hubspot/marketing/transactional/api/__init__.py

Ronfer/hubspot-api-python

1c87274ecbba4aa3c7728f890ccc6e77b2b6d2e4

[ "Apache-2.0" ]

45

2020-04-06T16:13:52.000Z

2022-03-30T21:33:17.000Z

from __future__ import absolute_import # flake8: noqa # import apis into api package from hubspot.marketing.transactional.api.public_smtp_tokens_api import PublicSmtpTokensApi from hubspot.marketing.transactional.api.single_send_api import SingleSendApi

32

90

0.867188

33

256

6.424242

0.606061

0.103774

0.188679

0.311321

0.339623

0

0.004292

0.089844

256

7

91

36.571429

0.905579

0.160156

0

1

0

true

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

8afe00c79d21ea37a05f2b67de714d2fc75b4224

182

py

Python

microsetta_private_api/db/hotfix_vioscreen.py

charles-cowart/microsetta-private-api

96d3c09c8e30e00c87ce82c5e7d16ba4eb93ce74

[ "BSD-3-Clause" ]

4

2020-02-28T22:40:42.000Z

2021-03-01T03:31:04.000Z

microsetta_private_api/db/hotfix_vioscreen.py

charles-cowart/microsetta-private-api

96d3c09c8e30e00c87ce82c5e7d16ba4eb93ce74

[ "BSD-3-Clause" ]

248

2019-12-30T17:05:25.000Z

2022-03-09T02:46:46.000Z

microsetta_private_api/db/hotfix_vioscreen.py

charles-cowart/microsetta-private-api

96d3c09c8e30e00c87ce82c5e7d16ba4eb93ce74

[ "BSD-3-Clause" ]

9

2019-10-29T04:50:27.000Z

2021-11-30T19:02:03.000Z

from microsetta_private_api.LEGACY.sql_connection import TRN from microsetta_private_api.db.migration_support import MigrationSupport with TRN: MigrationSupport.migrate_82(TRN)

30.333333

72

0.868132

24

182

6.291667

0.666667

0.18543

0.278146

0.317881

0

0.012048

0.087912

182

5

73

36.4

0.89759

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

c1224345de63ec3ed3cc8056a60b06018916b8bc

64

py

Python

inverter.py

JDJGInc/JDJGBotSupreme

fd8a5679f05cb90ebec8dbfc297445f9773ebe5f

[ "MIT" ]

4

2020-07-10T04:02:23.000Z

2021-02-13T16:38:54.000Z

inverter.py

JDJGInc/JDJGBotSupreme

fd8a5679f05cb90ebec8dbfc297445f9773ebe5f

[ "MIT" ]

3

2021-07-13T15:38:39.000Z

2022-02-15T15:17:17.000Z

inverter.py

johndpope/JDJGBotSupreme

64fde0e169811e1866eb29174ac5dd8e052d830a

[ "MIT" ]

2

2020-08-01T11:15:09.000Z

2022-02-15T11:46:22.000Z

from PIL import Image,ImageOps def invert(image): return image

21.333333

30

0.796875

10

64

5.1

0.8

0

0.140625

64

3

31

21.333333

0.927273

0

1

0.333333

false

0

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

c169aac9f971b8706f81fbd94ca68908c42e196e

78

py

Python

balderdash/__init__.py

charleskubicek/balderdash

0ddd1ac2ed7de1fff7afd41697d32220e3a41779

[ "Apache-2.0" ]

5

2015-06-29T10:47:11.000Z

2020-12-19T20:22:26.000Z

balderdash/__init__.py

charleskubicek/balderdash

0ddd1ac2ed7de1fff7afd41697d32220e3a41779

[ "Apache-2.0" ]

5

2016-02-16T20:51:24.000Z

2021-04-08T09:29:07.000Z

balderdash/__init__.py

charleskubicek/balderdash

0ddd1ac2ed7de1fff7afd41697d32220e3a41779

[ "Apache-2.0" ]

7

2016-02-16T10:21:37.000Z

2021-04-07T16:38:53.000Z

# coding=utf-8 from . import kibana as kibana from . import grafana as grafana

26

32

0.769231

13

78

4.615385

0.615385

0.333333

0

0.015385

0.166667

78

3

32

26

0.907692

0.153846

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

c1a5616f018e69445da384d988ac242347244509

83

py

Python

Object detection and depth estimation/catkin_ws/devel/lib/python2.7/dist-packages/race/msg/__init__.py

UF-f1tenth/F1tenth-UFL

93b0a822c67b2b425664642955342138e65974f4

[ "Apache-2.0" ]

null

Object detection and depth estimation/catkin_ws/devel/lib/python2.7/dist-packages/race/msg/__init__.py

UF-f1tenth/F1tenth-UFL

93b0a822c67b2b425664642955342138e65974f4

[ "Apache-2.0" ]

null

Object detection and depth estimation/catkin_ws/devel/lib/python2.7/dist-packages/race/msg/__init__.py

UF-f1tenth/F1tenth-UFL

93b0a822c67b2b425664642955342138e65974f4

[ "Apache-2.0" ]

null

from ._drive_param import * from ._drive_values import * from ._pid_input import *

20.75

28

0.783133

12

83

4.916667

0.583333

0.305085

0

0.144578

83

3

29

27.666667

0.830986

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

c1b0c75304a7d207e5218cc2a9572573d4093ac9

49

py

Python

social/backends/uber.py

raccoongang/python-social-auth

81c0a542d158772bd3486d31834c10af5d5f08b0

[ "BSD-3-Clause" ]

1,987

2015-01-01T16:12:45.000Z

2022-03-29T14:24:25.000Z

social/backends/uber.py

raccoongang/python-social-auth

81c0a542d158772bd3486d31834c10af5d5f08b0

[ "BSD-3-Clause" ]

731

2015-01-01T22:55:25.000Z

2022-03-10T15:07:51.000Z

virtual/lib/python3.6/site-packages/social/backends/uber.py

dennismwaniki67/awards

80ed10541f5f751aee5f8285ab1ad54cfecba95f

[ "MIT" ]

1,082

2015-01-01T16:27:26.000Z

2022-03-22T21:18:33.000Z

from social_core.backends.uber import UberOAuth2

24.5

48

0.877551

7

49

6

1

0

0.022222

0.081633

49

1

49

0.911111

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

c1d56551c42a54a66b94ebd084f374696dfbd562

15,119

py

Python

off_django/migrations/0001_initial.py

klorophyl/openfoodfacts-django

696e701355af9911e726c5579eacca8989f4c629

[ "Apache-2.0" ]

1

2022-02-02T19:54:34.000Z

off_django/migrations/0001_initial.py

klorophyl/openfoodfacts-django

696e701355af9911e726c5579eacca8989f4c629

[ "Apache-2.0" ]

null

off_django/migrations/0001_initial.py

klorophyl/openfoodfacts-django

696e701355af9911e726c5579eacca8989f4c629

[ "Apache-2.0" ]

1

2021-12-27T20:40:18.000Z

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations import off_django.models_extensions class Migration(migrations.Migration): dependencies = [ ] operations = [ migrations.CreateModel( name='OFFFood', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('code', models.TextField(default=None, null=True, db_index=True)), ('url', models.TextField(default=None, null=True)), ('creator', models.TextField(default=None, null=True)), ('created_t', models.IntegerField(default=None, null=True)), ('created_datetime', models.DateTimeField(default=None, null=True)), ('last_modified_t', models.IntegerField(default=None, null=True)), ('last_modified_datetime', models.DateTimeField(default=None, null=True)), ('product_name', models.TextField(default=None, null=True)), ('generic_name', models.TextField(default=None, null=True)), ('quantity', models.TextField(default=None, null=True)), ('packaging', off_django.models_extensions.ListField(default=None, null=True)), ('packaging_tags', off_django.models_extensions.ListField(default=None, null=True)), ('brands', off_django.models_extensions.ListField(default=None, null=True)), ('brands_tags', off_django.models_extensions.ListField(default=None, null=True)), ('categories', off_django.models_extensions.ListField(default=None, null=True)), ('categories_en', off_django.models_extensions.ListField(default=None, null=True)), ('categories_tags', off_django.models_extensions.ListField(default=None, null=True)), ('origins', off_django.models_extensions.ListField(default=None, null=True)), ('origins_tags', off_django.models_extensions.ListField(default=None, null=True)), ('manufacturing_places', off_django.models_extensions.ListField(default=None, null=True)), ('manufacturing_places_tags', off_django.models_extensions.ListField(default=None, null=True)), ('labels', off_django.models_extensions.ListField(default=None, null=True)), ('labels_en', off_django.models_extensions.ListField(default=None, null=True)), ('labels_tags', off_django.models_extensions.ListField(default=None, null=True)), ('emb_codes', models.TextField(default=None, null=True)), ('emb_codes_tags', off_django.models_extensions.ListField(default=None, null=True)), ('first_packaging_code_geo', off_django.models_extensions.ListField(default=None, null=True)), ('cities', off_django.models_extensions.ListField(default=None, null=True)), ('cities_tags', off_django.models_extensions.ListField(default=None, null=True)), ('purchase_places', off_django.models_extensions.ListField(default=None, null=True)), ('stores', off_django.models_extensions.ListField(default=None, null=True)), ('countries', off_django.models_extensions.ListField(default=None, null=True)), ('countries_en', off_django.models_extensions.ListField(default=None, null=True)), ('countries_tags', off_django.models_extensions.ListField(default=None, null=True)), ('ingredients_text', off_django.models_extensions.ListField(default=None, null=True)), ('traces', off_django.models_extensions.ListField(default=None, null=True)), ('traces_en', off_django.models_extensions.ListField(default=None, null=True)), ('traces_tags', off_django.models_extensions.ListField(default=None, null=True)), ('additives', off_django.models_extensions.ListField(default=None, null=True)), ('additives_en', off_django.models_extensions.ListField(default=None, null=True)), ('additives_n', models.IntegerField(default=None, null=True)), ('additives_tags', off_django.models_extensions.ListField(default=None, null=True)), ('allergens', off_django.models_extensions.ListField(default=None, null=True)), ('allergens_en', off_django.models_extensions.ListField(default=None, null=True)), ('image_small_url', models.TextField(default=None, null=True)), ('image_url', models.TextField(default=None, null=True)), ('ingredients_from_palm_oil', off_django.models_extensions.ListField(default=None, null=True)), ('ingredients_from_palm_oil_n', models.IntegerField(default=None, null=True)), ('ingredients_from_palm_oil_tags', off_django.models_extensions.ListField(default=None, null=True)), ('ingredients_that_may_be_from_palm_oil', off_django.models_extensions.ListField(default=None, null=True)), ('ingredients_that_may_be_from_palm_oil_n', models.IntegerField(default=None, null=True)), ('ingredients_that_may_be_from_palm_oil_tags', off_django.models_extensions.ListField(default=None, null=True)), ('main_category', models.TextField(default=None, null=True)), ('main_category_en', models.TextField(default=None, null=True)), ('no_nutriments', models.TextField(default=None, null=True)), ('nutrition_grade_fr', models.CharField(default=None, max_length=1, null=True)), ('nutrition_grade_uk', models.CharField(default=None, max_length=1, null=True)), ('pnns_groups_1', models.TextField(default=None, null=True)), ('pnns_groups_2', models.TextField(default=None, null=True)), ('serving_size', models.TextField(default=None, null=True)), ('states', off_django.models_extensions.ListField(default=None, null=True)), ('states_en', off_django.models_extensions.ListField(default=None, null=True)), ('states_tags', off_django.models_extensions.ListField(default=None, null=True)), ('_alpha_linolenic_acid_100g', models.FloatField(default=None, null=True)), ('_arachidic_acid_100g', models.FloatField(default=None, null=True)), ('_arachidonic_acid_100g', models.FloatField(default=None, null=True)), ('_behenic_acid_100g', models.FloatField(default=None, null=True)), ('_butyric_acid_100g', models.FloatField(default=None, null=True)), ('_capric_acid_100g', models.FloatField(default=None, null=True)), ('_caproic_acid_100g', models.FloatField(default=None, null=True)), ('_caprylic_acid_100g', models.FloatField(default=None, null=True)), ('_cerotic_acid_100g', models.FloatField(default=None, null=True)), ('_dihomo_gamma_linolenic_acid_100g', models.FloatField(default=None, null=True)), ('_docosahexaenoic_acid_100g', models.FloatField(default=None, null=True)), ('_eicosapentaenoic_acid_100g', models.FloatField(default=None, null=True)), ('_elaidic_acid_100g', models.FloatField(default=None, null=True)), ('_erucic_acid_100g', models.FloatField(default=None, null=True)), ('_fructose_100g', models.FloatField(default=None, null=True)), ('_gamma_linolenic_acid_100g', models.FloatField(default=None, null=True)), ('_glucose_100g', models.FloatField(default=None, null=True)), ('_gondoic_acid_100g', models.FloatField(default=None, null=True)), ('_lactose_100g', models.FloatField(default=None, null=True)), ('_lauric_acid_100g', models.FloatField(default=None, null=True)), ('_lignoceric_acid_100g', models.FloatField(default=None, null=True)), ('_linoleic_acid_100g', models.FloatField(default=None, null=True)), ('_maltodextrins_100g', models.FloatField(default=None, null=True)), ('_maltose_100g', models.FloatField(default=None, null=True)), ('_mead_acid_100g', models.FloatField(default=None, null=True)), ('_melissic_acid_100g', models.FloatField(default=None, null=True)), ('_montanic_acid_100g', models.FloatField(default=None, null=True)), ('_myristic_acid_100g', models.FloatField(default=None, null=True)), ('_nervonic_acid_100g', models.FloatField(default=None, null=True)), ('_oleic_acid_100g', models.FloatField(default=None, null=True)), ('_palmitic_acid_100g', models.FloatField(default=None, null=True)), ('_stearic_acid_100g', models.FloatField(default=None, null=True)), ('_sucrose_100g', models.FloatField(default=None, null=True)), ('alcohol_100g', models.FloatField(default=None, null=True)), ('beta_carotene_100g', models.FloatField(default=None, null=True)), ('beta_glucan_100g', models.FloatField(default=None, null=True)), ('bicarbonate_100g', models.FloatField(default=None, null=True)), ('biotin_100g', models.FloatField(default=None, null=True)), ('caffeine_100g', models.FloatField(default=None, null=True)), ('calcium_100g', models.FloatField(default=None, null=True)), ('carbohydrates_100g', models.FloatField(default=None, null=True)), ('carbon_footprint_100g', models.FloatField(default=None, null=True)), ('carnitine_100g', models.FloatField(default=None, null=True)), ('casein_100g', models.FloatField(default=None, null=True)), ('chloride_100g', models.FloatField(default=None, null=True)), ('chlorophyl_100g', models.FloatField(default=None, null=True)), ('cholesterol_100g', models.FloatField(default=None, null=True)), ('choline_100g', models.FloatField(default=None, null=True)), ('chromium_100g', models.FloatField(default=None, null=True)), ('cocoa_100g', models.FloatField(default=None, null=True)), ('collagen_meat_protein_ratio_100g', models.FloatField(default=None, null=True)), ('copper_100g', models.FloatField(default=None, null=True)), ('energy_100g', models.FloatField(default=None, null=True)), ('energy_from_fat_100g', models.FloatField(default=None, null=True)), ('fat_100g', models.FloatField(default=None, null=True)), ('fiber_100g', models.FloatField(default=None, null=True)), ('fluoride_100g', models.FloatField(default=None, null=True)), ('folates_100g', models.FloatField(default=None, null=True)), ('fruits_vegetables_nuts_100g', models.FloatField(default=None, null=True)), ('fruits_vegetables_nuts_estimate_100g', models.FloatField(default=None, null=True)), ('glycemic_index_100g', models.FloatField(default=None, null=True)), ('inositol_100g', models.FloatField(default=None, null=True)), ('iodine_100g', models.FloatField(default=None, null=True)), ('iron_100g', models.FloatField(default=None, null=True)), ('magnesium_100g', models.FloatField(default=None, null=True)), ('manganese_100g', models.FloatField(default=None, null=True)), ('molybdenum_100g', models.FloatField(default=None, null=True)), ('monounsaturated_fat_100g', models.FloatField(default=None, null=True)), ('nucleotides_100g', models.FloatField(default=None, null=True)), ('nutrition_score_fr_100g', models.FloatField(default=None, null=True)), ('nutrition_score_uk_100g', models.FloatField(default=None, null=True)), ('omega_3_fat_100g', models.FloatField(default=None, null=True)), ('omega_6_fat_100g', models.FloatField(default=None, null=True)), ('omega_9_fat_100g', models.FloatField(default=None, null=True)), ('pantothenic_acid_100g', models.FloatField(default=None, null=True)), ('ph_100g', models.FloatField(default=None, null=True)), ('phosphorus_100g', models.FloatField(default=None, null=True)), ('phylloquinone_100g', models.FloatField(default=None, null=True)), ('polyols_100g', models.FloatField(default=None, null=True)), ('polyunsaturated_fat_100g', models.FloatField(default=None, null=True)), ('potassium_100g', models.FloatField(default=None, null=True)), ('proteins_100g', models.FloatField(default=None, null=True)), ('salt_100g', models.FloatField(default=None, null=True)), ('saturated_fat_100g', models.FloatField(default=None, null=True)), ('selenium_100g', models.FloatField(default=None, null=True)), ('serum_proteins_100g', models.FloatField(default=None, null=True)), ('silica_100g', models.FloatField(default=None, null=True)), ('sodium_100g', models.FloatField(default=None, null=True)), ('starch_100g', models.FloatField(default=None, null=True)), ('sugars_100g', models.FloatField(default=None, null=True)), ('taurine_100g', models.FloatField(default=None, null=True)), ('trans_fat_100g', models.FloatField(default=None, null=True)), ('vitamin_a_100g', models.FloatField(default=None, null=True)), ('vitamin_b12_100g', models.FloatField(default=None, null=True)), ('vitamin_b1_100g', models.FloatField(default=None, null=True)), ('vitamin_b2_100g', models.FloatField(default=None, null=True)), ('vitamin_b6_100g', models.FloatField(default=None, null=True)), ('vitamin_b9_100g', models.FloatField(default=None, null=True)), ('vitamin_c_100g', models.FloatField(default=None, null=True)), ('vitamin_d_100g', models.FloatField(default=None, null=True)), ('vitamin_e_100g', models.FloatField(default=None, null=True)), ('vitamin_k_100g', models.FloatField(default=None, null=True)), ('vitamin_pp_100g', models.FloatField(default=None, null=True)), ('water_hardness_100g', models.FloatField(default=None, null=True)), ('zinc_100g', models.FloatField(default=None, null=True)), ], options={ 'verbose_name': 'OFFFood - Model for Open Food Facts food product', }, ), ]

78.744792

128

0.636484

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0.136504

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15,119

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0.032432

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null

1

0

null

0

6

de01db1620da02a39d9df1806996099ebff78cb8

407

py

Python

dependencies/dependency.py

elondon/TheDeployer

0d36f064f55244145aa5859d914a7257fa758b89

[ "MIT" ]

null

dependencies/dependency.py

elondon/TheDeployer

0d36f064f55244145aa5859d914a7257fa758b89

[ "MIT" ]

null

dependencies/dependency.py

elondon/TheDeployer

0d36f064f55244145aa5859d914a7257fa758b89

[ "MIT" ]

null

from abc import ABCMeta, abstractmethod class Dependency: def __init__(self, dep_config): self.dependency_name = dep_config['name'] self.config = dep_config __metaclass__ = ABCMeta @abstractmethod def install(self): pass @abstractmethod def configure(self): pass @abstractmethod def uninstall(self): pass @abstractmethod def update(self): pass

18.5

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407

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0.255639

0.24812

0.281955

0

0.240786

407

21

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19.380952

0.860841

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0.285714

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0.357143

false

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null

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1

0

1

0

1

0

6

de02b7c9044490329822c8cd7ebbf5d677cb294c

231

py

Python

tests/classes/nonnull_user.py

Jesse-Yung/jsonclasses

d40c52aec42bcb978a80ceb98b93ab38134dc790

[ "MIT" ]

50

2021-08-18T08:08:04.000Z

2022-03-20T07:23:26.000Z

tests/classes/nonnull_user.py

Jesse-Yung/jsonclasses

d40c52aec42bcb978a80ceb98b93ab38134dc790

[ "MIT" ]

1

2021-02-21T03:18:09.000Z

2021-03-08T01:07:52.000Z

tests/classes/nonnull_user.py

Jesse-Yung/jsonclasses

d40c52aec42bcb978a80ceb98b93ab38134dc790

[ "MIT" ]

8

2021-07-01T02:39:15.000Z

2021-12-10T02:20:18.000Z

from __future__ import annotations from jsonclasses import jsonclass, types @jsonclass class NonnullUser: name: str = types.str.writenonnull.required nickname: str = types.str.writenonnull.default('KuiPêkBvang').required

25.666667

74

0.792208

26

231

6.884615

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0.122905

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231

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null

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1

0

1

0

1

0

6

a9ba6628be23e35f0ea7a772bc88739c445be057

22,960

py

Python

tests/tests.py

nitely/sakaio

b43a0f96d0f2ab72f38d8dea69a480570742498b

[ "MIT" ]

1

2018-09-08T21:42:38.000Z

tests/tests.py

nitely/sakaio

b43a0f96d0f2ab72f38d8dea69a480570742498b

[ "MIT" ]

null

tests/tests.py

nitely/sakaio

b43a0f96d0f2ab72f38d8dea69a480570742498b

[ "MIT" ]

null

# -*- coding: utf-8 -*- import asyncio import logging import asynctest import unittest import sakaio from sakaio.sakaio import _chain_exceptions class WasteException(Exception): pass class SomeOtherException(Exception): pass async def waste_cycles(cycles): for _ in range(cycles): await asyncio.sleep(0) def call_later(cycles, callback): async def _call_later(): await waste_cycles(cycles) callback() loop = asyncio.get_event_loop() return loop.create_task(_call_later()) # XXX make public? class Waster: """Waste event loop cycles""" def __init__(self): self.completion_order = [] self.cancelled = [] async def waste(self, name, *, cycles, raise_err=False, ignore_cancel=False): """ Waste cycles, record execution order, raise some exception and ignore cancellation """ try: await waste_cycles(cycles) except asyncio.CancelledError: if not ignore_cancel: self.cancelled.append(name) raise await waste_cycles(cycles) if raise_err: raise WasteException(str(name)) self.completion_order.append(name) return name class ChainExceptionsTest(unittest.TestCase): def test_chain(self): try: raise SomeOtherException('A') except SomeOtherException as err: ex1 = err try: raise SomeOtherException('B') except SomeOtherException as err: ex2 = err err = _chain_exceptions([ex1, ex2]) self.assertEqual(err, ex2) self.assertEqual(err.__context__, ex1) self.assertIsNone(err.__context__.__context__) with self.assertRaises(SomeOtherException): raise err def test_chain_nested(self): try: raise SomeOtherException('A') except SomeOtherException as err: ex1 = err try: raise SomeOtherException('B') except SomeOtherException as err: ex2 = err try: raise SomeOtherException('C') except SomeOtherException as err: ex3 = err err = _chain_exceptions([ex2, ex3]) self.assertEqual(err, ex3) self.assertEqual(err.__context__, ex2) self.assertEqual(err.__context__.__context__, ex1) self.assertIsNone(err.__context__.__context__.__context__) with self.assertRaises(SomeOtherException): raise err def test_chain_from(self): try: raise SomeOtherException('A') except SomeOtherException as err: ex1 = err try: raise SomeOtherException('B') from ex1 except SomeOtherException as err: ex2 = err err = _chain_exceptions([ex2]) self.assertEqual(err, ex2) self.assertEqual(err.__context__, ex1) self.assertIsNone(err.__context__.__context__) with self.assertRaises(SomeOtherException): raise err def test_chain_simple(self): try: raise SomeOtherException('A') except SomeOtherException as err: ex1 = err err = _chain_exceptions([ex1, ex1]) self.assertEqual(err, ex1) self.assertIsNone(err.__context__) with self.assertRaises(SomeOtherException): raise err def test_chain_dups(self): try: raise SomeOtherException('A') except SomeOtherException as err: ex1 = err try: raise SomeOtherException('B') except SomeOtherException as err: ex2 = err err = _chain_exceptions([ex1, ex2, ex1, ex2]) self.assertEqual(err, ex2) self.assertEqual(err.__context__, ex1) self.assertIsNone(err.__context__.__context__) with self.assertRaises(SomeOtherException): raise err def test_chain_dups_nested(self): try: raise SomeOtherException('A') except SomeOtherException as err: ex1 = err try: raise SomeOtherException('B') except SomeOtherException as err: ex2 = err err = _chain_exceptions([ex1, ex2, ex1, ex2]) self.assertEqual(err, ex2) self.assertEqual(err.__context__, ex1) self.assertIsNone(err.__context__.__context__) with self.assertRaises(SomeOtherException): raise err def test_chain_dups_from(self): try: raise SomeOtherException('A') except SomeOtherException as err: ex1 = err try: raise SomeOtherException('B') from ex1 except SomeOtherException as err: ex2 = err err = _chain_exceptions([ex2, ex2]) self.assertEqual(err, ex2) self.assertEqual(err.__cause__, ex1) self.assertEqual(err.__context__, ex1) self.assertIsNone(err.__context__.__context__) with self.assertRaises(SomeOtherException): raise err class ConcurrentSequentialTest(asynctest.TestCase): def setUp(self): self.waster = Waster() async def test_concurrent(self): """ Should run the coros concurrently and\ return the results in the coros order """ results = await sakaio.concurrent( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), self.waster.waste('C', cycles=30), self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15)) self.assertEqual(results, [ 'A', 'B', 'C', 'D', 'E']) self.assertEqual(self.waster.completion_order, [ 'B', 'E', 'A', 'C', 'D']) async def test_sequential(self): """ Should run the coros sequentially and\ return the results in the coros order """ results = await sakaio.sequential( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), self.waster.waste('C', cycles=30), self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15)) self.assertEqual(results, [ 'A', 'B', 'C', 'D', 'E']) self.assertEqual(self.waster.completion_order, [ 'A', 'B', 'C', 'D', 'E']) async def test_sequential_concurrent(self): """ Should run coros sequentially/concurrently as given """ results = await sakaio.concurrent( self.waster.waste("A", cycles=30), self.waster.waste("B", cycles=20), sakaio.sequential( self.waster.waste("C", cycles=40), sakaio.concurrent( self.waster.waste("D", cycles=50), self.waster.waste("E", cycles=20)), self.waster.waste("F", cycles=10))) self.assertEqual(results, [ 'A', 'B', 'C', 'D', 'E', 'F']) self.assertEqual(self.waster.completion_order, [ 'B', 'A', 'C', 'E', 'D', 'F']) async def test_concurrent_err(self): with self.assertRaises(WasteException) as cm: await sakaio.concurrent( self.waster.waste('Z', cycles=300, raise_err=True, ignore_cancel=True), self.waster.waste('X', cycles=200, ignore_cancel=True), self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), self.waster.waste('C', cycles=30, raise_err=True), self.waster.waste('D', cycles=40), # won't run self.waster.waste('E', cycles=15)) self.assertIsInstance(cm.exception, WasteException) self.assertEqual(str(cm.exception), "Z") self.assertIsInstance(cm.exception.__context__, WasteException) self.assertEqual(str(cm.exception.__context__), "C") self.assertIsNone(cm.exception.__context__.__context__) self.assertEqual(self.waster.completion_order, [ 'B', 'E', 'A', 'X']) async def test_concurrent_err_ret(self): results = await sakaio.concurrent( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), self.waster.waste('C', cycles=30, raise_err=True), self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15), exception_handling=sakaio.RETURN_EXCEPTIONS) self.assertEqual(results[:2], [ 'A', 'B']) self.assertTrue(isinstance(results[2], WasteException)) self.assertEqual(results[3:], [ 'D', 'E']) self.assertEqual(self.waster.completion_order, [ 'B', 'E', 'A', 'D']) async def test_concurrent_cancel_inner(self): c_task = self.loop.create_task( self.waster.waste('C', cycles=30)) call_later(cycles=15, callback=c_task.cancel) task = self.loop.create_task(sakaio.concurrent( self.waster.waste('X', cycles=200, ignore_cancel=True), self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), c_task, self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15))) # Same behaviour as asyncio.gather with self.assertRaises(asyncio.CancelledError): await task self.assertTrue(task.cancelled()) self.assertEqual(self.waster.completion_order, ['B', 'E', 'A', 'D', 'X']) async def test_concurrent_cancel_inner_ret(self): c_task = self.loop.create_task( self.waster.waste('C', cycles=30)) call_later(cycles=15, callback=c_task.cancel) results = await sakaio.concurrent( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), c_task, self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15), exception_handling=sakaio.RETURN_EXCEPTIONS) self.assertEqual(results[:2], [ 'A', 'B']) self.assertIsInstance(results[2], asyncio.CancelledError) self.assertEqual(results[3:], [ 'D', 'E']) self.assertEqual(self.waster.completion_order, [ 'B', 'E', 'A', 'D']) async def test_concurrent_cancel_outer(self): task = self.loop.create_task(sakaio.concurrent( self.waster.waste('X', cycles=200, ignore_cancel=True), self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), self.waster.waste('C', cycles=30), self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15))) call_later(cycles=5, callback=task.cancel) with self.assertRaises(asyncio.CancelledError): await task self.assertTrue(task.cancelled()) self.assertEqual(self.waster.completion_order, ['X']) async def test_concurrent_cancel_outer_ret(self): task = self.loop.create_task(sakaio.concurrent( self.waster.waste('X', cycles=200, ignore_cancel=True), self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), self.waster.waste('C', cycles=30), self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15), exception_handling=sakaio.RETURN_EXCEPTIONS)) call_later(cycles=5, callback=task.cancel) with self.assertRaises(asyncio.CancelledError): await task self.assertTrue(task.cancelled()) self.assertEqual(self.waster.completion_order, ['X']) async def test_sequential_err(self): with self.assertRaises(WasteException): await sakaio.sequential( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), self.waster.waste('C', cycles=30, raise_err=True), self.waster.waste('D', cycles=40), # won't run self.waster.waste('E', cycles=15)) # won't run await waste_cycles(200) self.assertEqual(self.waster.completion_order, [ 'A', 'B']) async def test_sequential_err_ret(self): results = await sakaio.sequential( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), self.waster.waste('C', cycles=30, raise_err=True), self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15), return_exceptions=True) await waste_cycles(200) self.assertEqual(results[:2], [ 'A', 'B']) self.assertIsInstance(results[2], WasteException) self.assertEqual(results[3:], [ 'D', 'E']) self.assertEqual(self.waster.completion_order, [ 'A', 'B', 'D', 'E']) async def test_sequential_cancel_inner(self): c_task = self.loop.create_task( self.waster.waste('C', cycles=30)) task = self.loop.create_task(sakaio.sequential( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), c_task, self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15))) await waste_cycles(12) c_task.cancel() with self.assertRaises(asyncio.CancelledError): await task self.assertTrue(task.cancelled()) self.assertEqual(self.waster.completion_order, ['A', 'B', 'D', 'E']) async def test_sequential_cancel_inner_ret(self): c_task = self.loop.create_task( self.waster.waste('C', cycles=30)) task = sakaio.sequential( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), c_task, self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15), return_exceptions=True) await waste_cycles(5) c_task.cancel() results = await task await waste_cycles(200) self.assertEqual(len(results), 5) self.assertEqual(results[:2], [ 'A', 'B']) print(results[2]) self.assertIsInstance(results[2], asyncio.CancelledError) self.assertEqual(results[3:], [ 'D', 'E']) self.assertEqual(self.waster.completion_order, [ 'A', 'B', 'D', 'E']) async def test_sequential_cancel_outer(self): task = self.loop.create_task(sakaio.sequential( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), self.waster.waste('C', cycles=30), self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15))) await waste_cycles(5) task.cancel() with self.assertRaises(asyncio.CancelledError): await task await waste_cycles(200) self.assertEqual(self.waster.completion_order, []) async def test_sequential_cancel_outer_ret(self): task = self.loop.create_task(sakaio.sequential( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), self.waster.waste('C', cycles=30), self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15), return_exceptions=True)) await waste_cycles(5) task.cancel() with self.assertRaises(asyncio.CancelledError): await task await waste_cycles(200) self.assertEqual(self.waster.completion_order, []) async def test_gather_behaviour(self): task_c = self.loop.create_task(self.waster.waste('C', cycles=30)) call_later(cycles=10, callback=task_c.cancel) async def gather(): await asyncio.gather( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), task_c, self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15)) task = self.loop.create_task(gather()) with self.assertRaises(asyncio.CancelledError): await task await waste_cycles(200) self.assertTrue(task.cancelled()) self.assertEqual(self.waster.completion_order, ['B', 'E', 'A', 'D']) async def test_gather_behaviour_ret(self): task_c = self.loop.create_task(self.waster.waste('C', cycles=30)) task = asyncio.gather( self.waster.waste('A', cycles=20), self.waster.waste('B', cycles=10), task_c, self.waster.waste('D', cycles=40), self.waster.waste('E', cycles=15), return_exceptions=True) await waste_cycles(5) task_c.cancel() result = await task await waste_cycles(200) self.assertEqual(result[:2], ['A', 'B']) self.assertIsInstance(result[2], asyncio.CancelledError) self.assertEqual(result[3:], ['D', 'E']) self.assertEqual(self.waster.completion_order, ['B', 'E', 'A', 'D']) class TaskGuardTest(asynctest.TestCase): def setUp(self): self.waster = Waster() async def test_guard(self): loop = asyncio.get_event_loop() async with sakaio.TaskGuard(loop) as guard: guard.create_task(self.waster.waste('C', cycles=30)) guard.create_task(self.waster.waste('A', cycles=10)) guard.create_task(self.waster.waste('B', cycles=20)) self.assertEqual(self.waster.completion_order, ['A', 'B', 'C']) async def test_guard_err(self): loop = asyncio.get_event_loop() with self.assertRaises(WasteException): async with sakaio.TaskGuard(loop) as guard: guard.create_task(self.waster.waste('D', cycles=200, ignore_cancel=True)) guard.create_task(self.waster.waste('C', cycles=30)) # will get cancelled guard.create_task(self.waster.waste('A', cycles=10)) guard.create_task(self.waster.waste('B', cycles=20, raise_err=True)) self.assertEqual(self.waster.completion_order, ['A', 'D']) async def test_guard_err_outside_err(self): loop = asyncio.get_event_loop() with self.assertRaises(WasteException): async with sakaio.TaskGuard(loop) as guard: # all get cancelled guard.create_task(self.waster.waste('D', cycles=200, ignore_cancel=True)) guard.create_task(self.waster.waste('C', cycles=30)) guard.create_task(self.waster.waste('A', cycles=10)) guard.create_task(self.waster.waste('B', cycles=20)) await waste_cycles(1) raise WasteException() self.assertEqual(self.waster.completion_order, ['D']) async def test_guard_err_inside_err(self): loop = asyncio.get_event_loop() with self.assertRaises(WasteException) as cm: async with sakaio.TaskGuard(loop) as guard: guard.create_task(self.waster.waste('D', cycles=200, ignore_cancel=True)) guard.create_task(self.waster.waste('C', cycles=30)) guard.create_task(self.waster.waste('A', cycles=10)) t = guard.create_task(self.waster.waste('B', cycles=20, raise_err=True)) await t # raises raise SomeOtherException("should not raise this") self.assertIsNone(cm.exception.__context__) # No SomeOtherException self.assertEqual(self.waster.completion_order, ['A', 'D']) async def test_guard_err_mixed_err(self): loop = asyncio.get_event_loop() with self.assertRaises(SomeOtherException) as cm: async with sakaio.TaskGuard(loop) as guard: guard.create_task(self.waster.waste('D', cycles=200, ignore_cancel=True)) guard.create_task(self.waster.waste('C', cycles=30)) # gets cancelled guard.create_task(self.waster.waste('A', cycles=10)) t = guard.create_task(self.waster.waste('B', cycles=20, raise_err=True)) await asyncio.wait([t], loop=loop) raise SomeOtherException() # gets raised as well self.assertIsInstance(cm.exception.__context__, WasteException) self.assertEqual(self.waster.completion_order, ['A', 'D']) async def test_guard_cancel_some_task(self): loop = asyncio.get_event_loop() async with sakaio.TaskGuard(loop) as guard: guard.create_task(self.waster.waste('C', cycles=30)) guard.create_task(self.waster.waste('A', cycles=10)) t = guard.create_task(self.waster.waste('B', cycles=20)) t.cancel() self.assertEqual(self.waster.completion_order, ['A', 'C']) async def test_guard_cancel_outer_task(self): async def task_guard(): loop = asyncio.get_event_loop() async with sakaio.TaskGuard(loop) as guard: guard.create_task(self.waster.waste('D', cycles=200, ignore_cancel=True)) guard.create_task(self.waster.waste('C', cycles=30)) guard.create_task(self.waster.waste('A', cycles=10)) guard.create_task(self.waster.waste('B', cycles=20)) task = self.loop.create_task(task_guard()) call_later(cycles=15, callback=task.cancel) await asyncio.wait([task], loop=self.loop) self.assertTrue(task.cancelled()) self.assertEqual(self.waster.completion_order, ['A', 'D']) class CancelAllTasksTest(asynctest.TestCase): def setUp(self): self.waster = Waster() async def test_cancel_all_tasks(self): loop = asyncio.get_event_loop() t1 = loop.create_task(self.waster.waste('A', cycles=100)) t2 = loop.create_task(self.waster.waste('B', cycles=200)) assert t1 and t2 # shut up lint await waste_cycles(10) await sakaio.cancel_all_tasks(raise_timeout_error=True) self.assertEqual(self.waster.cancelled, ['A', 'B']) self.assertFalse(self.waster.completion_order) async def test_cancel_all_tasks_timeout(self): terminate = False async def never_ending(): nonlocal terminate while True: try: await waste_cycles(1) except asyncio.CancelledError: pass if terminate: return loop = asyncio.get_event_loop() t1 = loop.create_task(never_ending()) await waste_cycles(10) with self.assertRaises(asyncio.TimeoutError), \ self.assertLogs('sakaio', logging.WARNING): await sakaio.cancel_all_tasks(timeout=0, raise_timeout_error=True) terminate = True await t1 if __name__ == '__main__': asynctest.main()

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a9e073e10fabe88b3d31671d9108961f0105c28b

52,683

py

Python

tests/test_elasticsearch.py

campagnucci/querido-diario-api

6d44baa4b2d60b0762dc72cbf3ce7170298c11a8

[ "MIT" ]

null

tests/test_elasticsearch.py

campagnucci/querido-diario-api

6d44baa4b2d60b0762dc72cbf3ce7170298c11a8

[ "MIT" ]

null

tests/test_elasticsearch.py

campagnucci/querido-diario-api

6d44baa4b2d60b0762dc72cbf3ce7170298c11a8

[ "MIT" ]

null

from datetime import date, timedelta, datetime from unittest import TestCase, skip, skipIf, skipUnless from unittest.mock import patch, MagicMock import os import unittest import uuid import time import elasticsearch from index import ElasticSearchDataMapper, create_elasticsearch_data_mapper from gazettes import GazetteDataGateway, Gazette FILE_ENDPOINT = "http://test.com" class ElasticSearchInterfaceTest(TestCase): @patch("elasticsearch.Elasticsearch") def test_create_elasticsearch_mapper(self, es_mock): mapper = create_elasticsearch_data_mapper("localhost", "gazettes") self.assertIsInstance(mapper, GazetteDataGateway) @patch("elasticsearch.Elasticsearch") @unittest.expectedFailure def test_create_elasticsearch_mapper_should_fail_without_host(self, es_mock): create_elasticsearch_data_mapper() @patch("elasticsearch.Elasticsearch") def test_create_elasticsearch_mapper_without_host(self, es_mock): with self.assertRaisesRegex(Exception, "Missing host") as cm: mapper = create_elasticsearch_data_mapper("", "gazettes") @patch("elasticsearch.Elasticsearch") def test_create_elasticsearch_mapper_without_index_name(self, es_mock): with self.assertRaisesRegex(Exception, "Missing index name") as cm: mapper = create_elasticsearch_data_mapper("localhost") def configure_es_mock_to_return_itself_in_the_es_constructor( self, es_mock, indices_mock ): es_mock.indices = indices_mock es_mock.return_value = es_mock @patch("elasticsearch.Elasticsearch") @patch("elasticsearch.client.IndicesClient") def test_create_elasticsearch_mapper_using_non_existing_index_should_fail( self, indices_mock, es_mock ): indices_mock.exists.return_value = False self.configure_es_mock_to_return_itself_in_the_es_constructor( es_mock, indices_mock ) with self.assertRaisesRegex(Exception, "Index does not exist") as cm: create_elasticsearch_data_mapper("localhost", "zpto") class ElasticSearchBaseTestCase(TestCase): INDEX = "gazettes" _data = [] def build_expected_query( self, since=None, until=None, keywords=None, territory_id=None, offset=0, size=10, ): query = { "query": {"bool": {"must": [], "should": [],}}, "from": offset, "size": size, "sort": [{"date": {"order": "desc"}}], "highlight": { "fields": { "source_text": { "fragment_size": 150, "number_of_fragments": 1, "type": "unified", "pre_tags": [""], "post_tags": [""], } } }, } date_query = {"range": {"date": {}}} if since: date_query["range"]["date"]["gte"] = since.strftime("%Y-%m-%d") if until: date_query["range"]["date"]["lte"] = until.strftime("%Y-%m-%d") if since or until: query["query"]["bool"]["must"].append(date_query) if territory_id: query["query"]["bool"]["must"].append( {"term": {"territory_id": territory_id}} ) if since or until or territory_id: return query return {"query": {"match_none": {}}} def setUp(self): self.es_mock = self.create_patch("elasticsearch.Elasticsearch") self.indices_mock = self.create_patch("elasticsearch.client.IndicesClient") self.generate_data() self._mapper = ElasticSearchDataMapper("localhost", self.INDEX) self.configure_es_mock_to_return_itself_in_the_es_constructor() self.set_mock_search_return() def create_patch(self, name): patcher = patch(name) self.addCleanup(patcher.stop) return patcher.start() def configure_es_mock_to_return_itself_in_the_es_constructor(self): self.es_mock.indices = self.indices_mock self.es_mock = self.es_mock.return_value def set_mock_search_return(self): hits = [ { "_index": "", "_type": "_doc", "_id": hit["file_checksum"], "_score": None, "_source": hit, "highlight": {"source_text": []}, } for hit in self._data ] self.es_mock.search.return_value = { "took": 4, "timed_out": False, "_shards": {"total": 1, "successful": 1, "skipped": 0, "failed": 0}, "hits": { "total": {"value": len(self._data), "relation": "eq"}, "max_score": None, "hits": hits, }, } def get_latest_gazettes_files(self, gazettes_count): self._data.sort(reverse=True, key=lambda x: x["date"]) return [ Gazette( d["territory_id"], datetime.strptime(d["date"], "%Y-%m-%d").date(), d["url"], d["file_checksum"], d["territory_name"], d["state_code"], d["highlight_texts"], d["edition_number"], d["is_extra_edition"], ) for d in self._data[:gazettes_count] ] def get_expected_document_page(self, page_number, page_size): end_slice = start_slice + page_size total_documents = len(self._data) expected_gazettes = self.get_latest_gazettes_files(total_documents) return expected_gazettes[start_slice:end_slice] class ElasticSearchDataMapperTest(ElasticSearchBaseTestCase): TERRITORY_ID1 = "3304557" TERRITORY_ID2 = "4205902" TERRITORY_ID3 = "4205919" TERRITORY_ID4 = "4205920" maxDiff = None def generate_data(self): week_ago = date.today() - timedelta(days=7) day = timedelta(days=1) self._data = [ { "source_text": "This is a fake gazette content", "date": datetime.strftime(date.today(), "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e5", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID1, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, { "source_text": "This is a fake gazette content", "date": datetime.strftime(date.today() - day, "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e52", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID2, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, { "source_text": "This is a fake gazette content", "date": datetime.strftime(date.today() + day, "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e53", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID2, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, { "source_text": "This is a fake gazette content. anotherkeyword", "date": datetime.strftime(date.today() - day, "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e54", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID1, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, { "source_text": "This is a fake gazette content. keyword1", "date": datetime.strftime(date.today() + day, "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e55", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID2, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, { "source_text": "This is a fake gazette with some keywork which is: 000.000.000-00", "date": datetime.strftime(date.today(), "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e56", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID1, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, { "source_text": "This is a fake gazette content from ID 6", "date": datetime.strftime(week_ago - day, "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e57", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID3, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, { "source_text": "This is a fake gazette content from ID 7", "date": datetime.strftime(week_ago, "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e58", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID3, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, { "source_text": "This is a fake gazette content from ID 8", "date": datetime.strftime(week_ago + day, "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e59", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID3, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, { "source_text": "This is a fake gazette content from ID 9", "date": datetime.strftime(week_ago - day, "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e510", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID4, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, { "source_text": "This is a fake gazette content from ID 10", "date": datetime.strftime(week_ago, "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e511", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID4, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, { "source_text": "This is a fake gazette content from ID 11", "date": datetime.strftime(week_ago + day, "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e512", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID4, "territory_name": "Rio de Janeiro", "state_code": "RJ", "edition_number": "123.456", "is_extra_edition": False, "highlight_texts": [], }, ] def assert_basic_function_calls( self, since=None, until=None, keywords=None, territory_id=None, offset=0, size=10, ): expected_query = self.build_expected_query( since=since, until=until, keywords=keywords, territory_id=territory_id, offset=offset, size=size, ) self.es_mock.search.assert_called_with(body=expected_query, index=self.INDEX) def test_get_none_gazettes(self): self._data = [] self.set_mock_search_return() gazettes = self._mapper.get_gazettes()[1] self.assert_basic_function_calls() self.assertEqual(0, len(gazettes)) def test_return_gazette_objects(self): week_ago = date.today() - timedelta(days=7) day = timedelta(days=1) gazettes = self._mapper.get_gazettes(since=week_ago - day)[1] self.assert_basic_function_calls(since=week_ago - day) self.assertGreater(len(gazettes), 0) for gazette in gazettes: self.assertIsInstance(gazette, Gazette) def test_gazettes_fields(self): week_ago = date.today() - timedelta(days=7) day = timedelta(days=1) gazettes = self._mapper.get_gazettes(since=week_ago - day)[1] self.assert_basic_function_calls(since=week_ago - day) for g in gazettes: self.assertIsInstance(g.territory_id, str) self.assertIsInstance(g.url, str) self.assertIsInstance(g.date, date) def test_return_get_gazettes_sort_by_date_in_descending_order(self): two_weeks_ago = date.today() - timedelta(days=14) gazettes = self._mapper.get_gazettes(since=two_weeks_ago)[1] expected_gazettes = [ Gazette( d["territory_id"], d["date"], d["url"], d["territory_name"], d["state_code"], d["highlight_texts"], d["edition_number"], d["is_extra_edition"], ) for d in self._data ] self.assert_basic_function_calls(since=two_weeks_ago) self.assertGreater(len(gazettes), 0) self.assertGreater(gazettes[0].date, gazettes[-1].date) def set_empty_es_return(self): self._data = [] self.set_mock_search_return() def set_search_results_returned_by_date( self, since=None, until=None, territory_id=None, keywords=None ): """ Define the entries returned by the ES mock in the search method call and return a list of Gazettes object of those entries """ data = self._data if since: data = [ d for d in data if datetime.strptime(d["date"], "%Y-%m-%d").date() >= since ] if until: data = [ d for d in data if datetime.strptime(d["date"], "%Y-%m-%d").date() <= until ] if territory_id: data = [d for d in data if d["territory_id"] == territory_id] if keywords: for keyword in keywords: data = [d for d in data if keyword in d["source_text"]] self._data = data self.set_mock_search_return() expected_gazettes = [ Gazette( d["territory_id"], datetime.strptime(d["date"], "%Y-%m-%d").date(), d["url"], d["file_checksum"], d["territory_name"], d["state_code"], d["highlight_texts"], d["edition_number"], d["is_extra_edition"], ) for d in self._data ] return expected_gazettes def test_search_gazettes_since_date(self): today = date.today() expected_gazettes = self.set_search_results_returned_by_date(since=today) gazettes = self._mapper.get_gazettes(since=today)[1] self.assert_basic_function_calls(since=today) self.assertCountEqual(gazettes, expected_gazettes) def test_search_gazettes_until_date(self): yesterday = date.today() - timedelta(days=1) expected_gazettes = self.set_search_results_returned_by_date(until=yesterday) gazettes = self._mapper.get_gazettes(until=yesterday)[1] self.assert_basic_function_calls(until=yesterday) self.assertCountEqual(gazettes, expected_gazettes) def test_search_gazettes_by_territory_id(self): expected_gazettes = self.set_search_results_returned_by_date( territory_id=self.TERRITORY_ID1 ) gazettes = self._mapper.get_gazettes(territory_id=self.TERRITORY_ID1)[1] self.assert_basic_function_calls(territory_id=self.TERRITORY_ID1) self.assertCountEqual(gazettes, expected_gazettes) def test_search_gazettes_by_territory_id_and_dates(self): week_ago = date.today() - timedelta(days=7) day = timedelta(days=1) expected_gazettes = self.set_search_results_returned_by_date( territory_id=self.TERRITORY_ID4, since=week_ago - day, until=week_ago + day ) gazettes = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID4, since=week_ago - day, until=week_ago + day )[1] self.assert_basic_function_calls( territory_id=self.TERRITORY_ID4, since=week_ago - day, until=week_ago + day ) self.assertCountEqual(gazettes, expected_gazettes) def test_get_gazettes_by_keywords(self): expected_gazettes = self.set_search_results_returned_by_date( keywords=["000.000.000-00"] ) gazettes = self._mapper.get_gazettes(keywords=["000.000.000-00"])[1] self.assertCountEqual(gazettes, expected_gazettes) expected_gazettes = self.set_search_results_returned_by_date( keywords=["anotherkeyword"] ) gazettes = self._mapper.get_gazettes(keywords=["anotherkeyword"])[1] self.assertCountEqual(gazettes, expected_gazettes) expected_gazettes = self.set_search_results_returned_by_date( keywords=["keyword1"] ) gazettes = self._mapper.get_gazettes(keywords=["keyword1"])[1] self.assertCountEqual(gazettes, expected_gazettes) def test_get_gazettes_by_invalid_since_date(self): self.set_empty_es_return() two_months_future = date.today() + timedelta(weeks=8) gazettes = self._mapper.get_gazettes(since=two_months_future)[1] self.assertEqual(0, len(gazettes), msg="No gazettes should be return ") def test_get_gazettes_by_invalid_until_date(self): self.set_empty_es_return() two_months_ago = date.today() - timedelta(weeks=8) gazettes = self._mapper.get_gazettes(until=two_months_ago)[1] self.assertEqual(0, len(gazettes), msg="No gazettes should be return ") def test_from_and_size_fields(self): today = date.today() self._mapper.get_gazettes(until=today, offset=5, size=15) self.assert_basic_function_calls(until=today, offset=5, size=15) def is_running_integration_tests(): return os.environ.get("RUN_INTEGRATION_TESTS", 0) == "1" class ElasticSearchIntegrationBaseTestCase(TestCase): _data = [] def delete_index(self): for attempt in range(3): try: self._es.indices.delete( index=self.INDEX, ignore_unavailable=True, timeout="30s" ) self._es.indices.refresh() return except Exception as e: time.sleep(10) def create_index(self): for attempt in range(3): try: self._es.indices.create( index=self.INDEX, body={"mappings": {"properties": {"date": {"type": "date"}}}}, timeout="30s", ) self._es.indices.refresh() return except Exception as e: time.sleep(10) def recreate_index(self): self.delete_index() self.create_index() def try_push_data_to_index(self, bulk_data): for attempt in range(3): try: self._es.bulk(bulk_data, index=self.INDEX, refresh=True, timeout="30s") return except Exception as e: time.sleep(10) def add_data_on_index(self): bulk_data = [] for gazette in self._data: bulk_data.append( {"index": {"_index": self.INDEX, "_id": gazette["file_checksum"]}} ) bulk_data.append(gazette) self.try_push_data_to_index(bulk_data) def setUp(self): self._es = elasticsearch.Elasticsearch(hosts=["localhost"]) self.recreate_index() self.generate_data() self.add_data_on_index() self._mapper = create_elasticsearch_data_mapper("localhost", self.INDEX) def tearDown(self): self._es.close() def get_latest_gazettes_files(self, gazettes_count): self._data.sort(reverse=True, key=lambda x: x["date"]) return [ Gazette( d["territory_id"], datetime.strptime(d["date"], "%Y-%m-%d").date(), d["url"], d["file_checksum"], d["territory_name"], d["state_code"], d["highlight_texts"], d["edition_number"], d["is_extra_edition"], ) for d in self._data[:gazettes_count] ] def get_expected_document_page(self, offset, size): total_documents = len(self._data) expected_gazettes = self.get_latest_gazettes_files(total_documents) return expected_gazettes[offset : offset + size] @skipUnless(is_running_integration_tests(), "Integration tests disable") class ElasticSearchDataMapperPaginationTest(ElasticSearchIntegrationBaseTestCase): INDEX = "gazettes_pagination" TERRITORY_ID = "3304557" maxDiff = None def generate_data(self): if len(self._data) > 0: return for days_old in range(50): self.create_new_fake_gazette(days_old) def create_new_fake_gazette(self, days_old: int): document_uuid = str(uuid.uuid1()) document_date = date.today() - timedelta(days=days_old) gazette = { "source_text": "This is a fake gazette content", "date": datetime.strftime(document_date, "%Y-%m-%d"), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": document_uuid, "file_path": f"3304557/2019-02-26/{document_uuid}", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/{document_uuid}", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": self.TERRITORY_ID, "territory_name": "Rio de Janeiro", "state_code": "RJ", "highlight_texts": [], } self._data.append(gazette) def assert_basic_function_calls( self, since=None, until=None, keywords=None, territory_id=None, offset=0, size=10, ): expected_query = self.build_expected_query( since=since, until=until, keywords=keywords, territory_id=territory_id, offset=offset, size=size, ) self.es_mock.search.assert_called_with(body=expected_query, index=self.INDEX) def test_page_size(self): gazettes = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=0, size=10 )[1] self.assertEqual(10, len(gazettes), msg="Invalid page size.") gazettes = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=0, size=20 )[1] self.assertEqual(20, len(gazettes), msg="Invalid page size.") gazettes = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=0, size=30 )[1] self.assertEqual(30, len(gazettes), msg="Invalid page size.") def test_pages_should_return_gazette_items(self): gazettes = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=0, size=10 )[1] self.assertNotEqual(0, len(gazettes)) for gazette in gazettes: self.assertIsInstance(gazette, Gazette) def test_first_page_should_return_latest_gazettes(self): page_size = 10 gazettes = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=0, size=page_size )[1] self.assertCountEqual(gazettes, self.get_expected_document_page(0, page_size)) def test_consecutive_page_items_should_have_older_dates(self): page_size = 10 first_page = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=0, size=page_size )[1] second_page = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=page_size, size=page_size )[1] expected_gazettes = self.get_latest_gazettes_files(20) self.assertCountEqual(first_page, expected_gazettes[:page_size]) self.assertCountEqual(second_page, expected_gazettes[page_size:]) def test_get_switching_between_gazettes_pages(self): page_size = 10 first_page = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=0, size=page_size )[1] second_page = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=page_size, size=page_size )[1] first_page_second_time = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=0, size=page_size )[1] second_page_second_time = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=page_size, size=page_size )[1] expected_second_page = self.get_expected_document_page(page_size, page_size) expected_first_page = self.get_expected_document_page(0, page_size) self.assertCountEqual( first_page, expected_first_page, msg="Unexpected first page" ) self.assertCountEqual( second_page, expected_second_page, msg="Unexpected second page" ) self.assertCountEqual( first_page_second_time, expected_first_page, msg="Unexpected first page" ) self.assertCountEqual( second_page_second_time, expected_second_page, msg="Unexpected second page" ) self.assertCountEqual( first_page, first_page_second_time, msg="Page request second time is different from the first one", ) self.assertCountEqual( second_page, second_page_second_time, msg="Page request second time is different from the first one", ) def test_get_page_does_not_exist(self): _, gazettes = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=99 ) self.assertCountEqual( [], gazettes, msg="When requesting a page that does not exists. Not gazettes should be return", ) def test_get_all_pages_available(self): page_size = 10 total_documents = len(self._data) for page_number in range(int(total_documents / page_size)): page = self._mapper.get_gazettes( territory_id=self.TERRITORY_ID, offset=page_size * page_number, size=page_size, )[1] expected_page = self.get_expected_document_page( page_size * page_number, page_size ) self.assertCountEqual( page, expected_page, msg=f"Page {page_number} is not right", ) @skipUnless(is_running_integration_tests(), "Integration tests disable") class ElasticSearchDataMapperKeywordTest(ElasticSearchIntegrationBaseTestCase): INDEX = "gazettes_keywords" def generate_data(self): week_ago = date.today() - timedelta(days=7) day = timedelta(days=1) self._data = [ { "source_text": "This is a fake gazette content. prefeitura", "date": date.today(), "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e5", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "3304557", "processed": False, "territory_name": "Rio de Janeiro", "state_code": "RJ", "highlight_texts": [], }, { "source_text": "This is a fake gazette content. prefeitura foobar xpto piraporinha", "date": date.today() - day, "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e51", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "3304557", "processed": False, "territory_name": "Rio de Janeiro", "state_code": "RJ", "highlight_texts": [], }, { "source_text": "This is a fake gazette content. prefeitura, piraporinha and cafundo", "date": date.today() + day, "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e52", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "3304557", "processed": False, "territory_name": "Rio de Janeiro", "state_code": "RJ", "highlight_texts": [], }, { "source_text": "This is a fake gazette content. piraporinha and cafundo", "date": date.today() + day, "edition_number": None, "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e53", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": f"{FILE_ENDPOINT}/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "3304557", "processed": False, "territory_name": "Rio de Janeiro", "state_code": "RJ", "highlight_texts": [], }, ] def test_get_gazettes_by_keywords_does_not_exist_return_nothing(self): _, gazettes = self._mapper.get_gazettes(keywords=["wasd1234xxx"]) self.assertEqual(0, len(gazettes), msg="No gazettes should be return ") def test_get_gazettes_return_only_documents_containing_all_keywords(self): _, gazettes = self._mapper.get_gazettes(keywords=["prefeitura"]) self.assertEqual( 3, len(gazettes), msg="3 gazettes should be returned because has the keyword 'prefeitura'", ) _, gazettes = self._mapper.get_gazettes(keywords=["piraporinha"]) self.assertEqual( 3, len(gazettes), msg="3 gazettes should be returned because has the keyword 'piraporinha'", ) _, gazettes = self._mapper.get_gazettes(keywords=["piraporinha", "cafundo"]) self.assertEqual(2, len(gazettes), msg="Only 2 gazettes should be return") class Elasticsearch(TestCase): def setUp(self): self.host = "localhost" self.index = "gazettes" self.search_result_json = { "took": 4, "timed_out": False, "_shards": {"total": 1, "successful": 1, "skipped": 0, "failed": 0}, "hits": { "total": {"value": 8, "relation": "eq"}, "max_score": None, "hits": [ { "_index": "gazettes", "_type": "_doc", "_id": "2566f0e0ff98d899ee0633da64bc65e52", "_score": None, "_source": { "source_text": "This is a fake gazette content", "date": "2021-01-07", "edition_number": "123.456", "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e52", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": "http://test.com/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "4205902", "territory_name": "Rio de Janeiro", "state_code": "RJ", }, "highlight": {"source_text": []}, "sort": [1609977600000], }, { "_index": "gazettes", "_type": "_doc", "_id": "2566f0e0ff98d899ee0633da64bc65e54", "_score": None, "_source": { "source_text": "This is a fake gazette content. anotherkeyword", "date": "2021-01-07", "edition_number": "123.456", "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e54", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": "http://test.com/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "3304557", "territory_name": "Rio de Janeiro", "state_code": "RJ", }, "highlight": {"source_text": []}, "sort": [1609977600000], }, { "_index": "gazettes", "_type": "_doc", "_id": "2566f0e0ff98d899ee0633da64bc65e59", "_score": None, "_source": { "source_text": "This is a fake gazette content from ID 8", "date": "2021-01-02", "edition_number": "123.456", "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e59", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": "http://test.com/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "4205919", "territory_name": "Rio de Janeiro", "state_code": "RJ", }, "highlight": {"source_text": []}, "sort": [1609545600000], }, { "_index": "gazettes", "_type": "_doc", "_id": "2566f0e0ff98d899ee0633da64bc65e512", "_score": None, "_source": { "source_text": "This is a fake gazette content from ID 11", "date": "2021-01-02", "edition_number": "123.456", "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e512", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": "http://test.com/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "4205920", "territory_name": "Rio de Janeiro", "state_code": "RJ", }, "highlight": {"source_text": []}, "sort": [1609545600000], }, { "_index": "gazettes", "_type": "_doc", "_id": "2566f0e0ff98d899ee0633da64bc65e58", "_score": None, "_source": { "source_text": "This is a fake gazette content from ID 7", "date": "2021-01-01", "edition_number": "123.456", "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e58", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": "http://test.com/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "4205919", "territory_name": "Rio de Janeiro", "state_code": "RJ", }, "highlight": {"source_text": []}, "sort": [1609459200000], }, { "_index": "gazettes", "_type": "_doc", "_id": "2566f0e0ff98d899ee0633da64bc65e511", "_score": None, "_source": { "source_text": "This is a fake gazette content from ID 10", "date": "2021-01-01", "edition_number": "123.456", "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e511", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": "http://test.com/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "4205920", "territory_name": "Rio de Janeiro", "state_code": "RJ", }, "highlight": {"source_text": []}, "sort": [1609459200000], }, { "_index": "gazettes", "_type": "_doc", "_id": "2566f0e0ff98d899ee0633da64bc65e57", "_score": None, "_source": { "source_text": "This is a fake gazette content from ID 6", "date": "2020-12-31", "edition_number": "123.456", "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e57", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": "http://test.com/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "4205919", "territory_name": "Rio de Janeiro", "state_code": "RJ", }, "highlight": {"source_text": []}, "sort": [1609372800000], }, { "_index": "gazettes", "_type": "_doc", "_id": "2566f0e0ff98d899ee0633da64bc65e510", "_score": None, "_source": { "source_text": "This is a fake gazette content from ID 9", "date": "2020-12-31", "edition_number": "123.456", "is_extra_edition": False, "power": "executive", "file_checksum": "2566f0e0ff98d899ee0633da64bc65e510", "file_path": "3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "url": "http://test.com/3304557/2019-02-26/c942328486185aa09ec19a7c723b3a33847258ee", "file_url": "https://doweb.rio.rj.gov.br/portal/edicoes/download/4067", "scraped_at": "2020-10-30T07:04:29.796347", "created_at": "2020-10-30T07:05:33.094289", "territory_id": "4205920", "territory_name": "Rio de Janeiro", "state_code": "RJ", }, "highlight": {"source_text": []}, "sort": [1609372800000], }, ], }, } def test_elasticsearch_data_mapper_creation(self): with patch("elasticsearch.Elasticsearch") as es_mock: es = ElasticSearchDataMapper(self.host, self.index) es._es.indices.exists.assert_called_once() @patch("elasticsearch.Elasticsearch") def test_get_total_number_items(self, es_mock): es = ElasticSearchDataMapper(self.host, self.index) total_items = es.get_total_number_items(self.search_result_json) self.assertEqual(total_items, 8) @patch("elasticsearch.Elasticsearch") def test_total_number_of_items_found_return(self, es_mock): es_mock.search.return_value = self.search_result_json es = ElasticSearchDataMapper(self.host, self.index) es._es = es_mock total_items, _ = es.get_gazettes("4205920", None, None, None, 1, 4) self.assertEqual(total_items, 8)

44.420742

113

0.540326

5,102

52,683

5.329675

0.071933

0.032767

0.023904

0.027582

0.813989

0.768314

0.73746

0.721462

0.70267

0.677994

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0.131611

0.342482

52,683

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114

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0.090156

0

null

0

1

0

null

0

6

a9f5362ecd776f81de7ab829aac7a2945d67005e

83

py

Python

test-juicyapi.py

The-New-Fork/python-blocknotify

56733218c0231044e859a967f767a6674b4ac85e

[ "Apache-2.0" ]

1

2021-10-01T15:54:51.000Z

test-juicyapi.py

The-New-Fork/python-blocknotify

56733218c0231044e859a967f767a6674b4ac85e

[ "Apache-2.0" ]

null

test-juicyapi.py

The-New-Fork/python-blocknotify

56733218c0231044e859a967f767a6674b4ac85e

[ "Apache-2.0" ]

1

2021-07-22T08:11:50.000Z

from dotenv import load_dotenv import json import pytest load_dotenv(verbose=True)

16.6

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0.855422

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83

5.307692

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true

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null

0

1

0

1

0

1

0

6

e726515d41cb1364005ba231d31143f8b5ff6ff2

4,185

py

Python

qtcurate/connect.py

quantxt/qtcurate-sdk-python

7c60a97c808381680889b2934aa5146e9303274e

[ "Apache-2.0" ]

null

qtcurate/connect.py

quantxt/qtcurate-sdk-python

7c60a97c808381680889b2934aa5146e9303274e

[ "Apache-2.0" ]

null

qtcurate/connect.py

quantxt/qtcurate-sdk-python

7c60a97c808381680889b2934aa5146e9303274e

[ "Apache-2.0" ]

null

import requests from qtcurate.exceptions import QtConnectionError, QtRestApiError, QtArgumentError def connect(method: str, uri: str, headers: str, data_type: str = None, data=None) -> requests.Response: s = requests.Session() res = None if data_type not in [None, "data", "files", "params"]: raise QtArgumentError("Unknown data type. params, data and files are allowed") if method.lower() == 'get': if data_type is None: try: res = s.get(uri, headers=headers) except requests.exceptions.RequestException as e: raise QtConnectionError(f"Connection error: {e}") if res.status_code not in [200, 201, 202, 204]: raise QtRestApiError(f"HTTP error: Full authentication is required to access this resource. " f"HTTP status code: {res.status_code}. Server message: {res.json()}") elif data_type == "params": try: res = s.get(uri, headers=headers, params=data) except requests.exceptions.RequestException as e: raise QtConnectionError(f"Connection error: {e}") if res.status_code not in [200, 201, 202, 204]: raise QtRestApiError(f"HTTP error: Full authentication is required to access this resource. " f"HTTP status code: {res.status_code}. Server message: {res.json()}") elif method.lower() == "delete": try: res = s.delete(uri, headers=headers) except requests.exceptions.RequestException as e: raise QtConnectionError(f"Connection error: {e}") if res.status_code not in [200, 201, 202, 204]: raise QtRestApiError(f"HTTP error: Full authentication is required to access this resource. " f"HTTP status code: {res.status_code}. Server message: {res.json()}") elif method.lower() == "post": if data_type == "data": try: res = s.post(uri, headers=headers, data=data) except requests.exceptions.RequestException as e: raise QtConnectionError(f"Connection error: {e}") if res.status_code not in [200, 201, 202, 204]: raise QtRestApiError(f"HTTP error: Full authentication is required to access this resource. " f"HTTP status code: {res.status_code}. Server message: {res.json()}") elif data_type == "files": try: res = s.post(uri, headers=headers, files=data) except requests.exceptions.RequestException as e: raise QtConnectionError(f"Connection error: {e}") if res.status_code not in [200, 201, 202, 204]: raise QtRestApiError(f"HTTP error: Full authentication is required to access this resource. " f"HTTP status code: {res.status_code}. Server message: {res.json()}") elif method.lower() == "put": if data_type == "data": try: res = s.put(uri, headers=headers, data=data) except requests.exceptions.RequestException as e: raise QtConnectionError(f"Connection error: {e}") if res.status_code not in [200, 201, 202, 204]: raise QtRestApiError(f"HTTP error: Full authentication is required to access this resource. " f"HTTP status code: {res.status_code}. Server message: {res.json()}") elif data_type == "files": try: res = s.put(uri, headers=headers, files=data) except requests.exceptions.RequestException as e: raise QtConnectionError(f"Connection error: {e}") if res.status_code not in [200, 201, 202, 204]: raise QtRestApiError(f"HTTP error: Full authentication is required to access this resource. " f"HTTP status code: {res.status_code}. Server message: {res.json()}") else: raise QtArgumentError("Unknown data type. data and files are allowed") return res

57.328767

109

0.586619

485

4,185

5.016495

0.134021

0.086313

0.074805

0.115084

0.873407

0.826552

0.788327

0

0.029248

0.31374

4,185

72

110

58.125

0.817897

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false

0

0.028986

0

0.057971

0

null

0

1

0

null

0

6

e76cf5dc2081760dd0826fdc592e01ef3836af6a

226

py

Python

Actions/actioninterface.py

dz1domin/bachelors

8be6b67535afd19a1bc9a116b26efa427a8a1e8c

[ "MIT" ]

null

Actions/actioninterface.py

dz1domin/bachelors

8be6b67535afd19a1bc9a116b26efa427a8a1e8c

[ "MIT" ]

null

Actions/actioninterface.py

dz1domin/bachelors

8be6b67535afd19a1bc9a116b26efa427a8a1e8c

[ "MIT" ]

1

2020-02-27T18:15:21.000Z

import abc class ActionInterface(abc.ABC): def do_action(self, moduleResult, runtimeOptions): pass def setup(self, runtimeOptions): pass def finish(self, runtimeOptions): pass

18.833333

55

0.628319

23

226

6.130435

0.565217

0.382979

0.297872

0

0.29646

226

12

56

18.833333

0.886792

0

0.375

0

1

0.375

false

0.375

0.125

0

0.625

0

1

0

null

1

0

null

0

1

0

1

0

1

0

6

e790fe1d9f57f21c9976c765a89d1abcf8c85a37

196

py

Python

cuddly-chameleons/cuddly_chameleons/retro_news/admin.py

Vthechamp22/summer-code-jam-2021

0a8bf1f22f6c73300891fd779da36efd8e1304c1

[ "MIT" ]

40

2020-08-02T07:38:22.000Z

2021-07-26T01:46:50.000Z

cuddly-chameleons/cuddly_chameleons/retro_news/admin.py

Vthechamp22/summer-code-jam-2021

0a8bf1f22f6c73300891fd779da36efd8e1304c1

[ "MIT" ]

134

2020-07-31T12:15:45.000Z

2020-12-13T04:42:19.000Z

cuddly-chameleons/cuddly_chameleons/retro_news/admin.py

ks129/summer-code-jam-2020

819ac854269af8ef482c83f851c39c1887a27c5b

[ "MIT" ]

101

2020-07-31T12:00:47.000Z

2021-11-01T09:06:58.000Z

from django.contrib import admin from .models import ArticleComment, CustomUser, BlogArticle admin.site.register(CustomUser) admin.site.register(BlogArticle) admin.site.register(ArticleComment)

24.5

59

0.841837

23

196

7.173913

0.478261

0.163636

0.309091

0.339394

0

0.076531

196

7

60

28

0.911602

0

1

0

true

0

0.4

0

0.4

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

e79ffd2fb5e9e4e1399072bc4a42d0def78e33c0

41

py

Python

src/vitalert/alerts/__init__.py

Vitalert/vitalert-python

6ee91063412320cb561634de73ad8522a1453c50

[ "MIT" ]

null

src/vitalert/alerts/__init__.py

Vitalert/vitalert-python

6ee91063412320cb561634de73ad8522a1453c50

[ "MIT" ]

null

src/vitalert/alerts/__init__.py

Vitalert/vitalert-python

6ee91063412320cb561634de73ad8522a1453c50

[ "MIT" ]

null

from vitalert.alerts.alerts import Alerts

41

0.878049

6

41

6

0.666667

0

0.073171

41

1

41

0.947368

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

e7c9c8cdb07c2a7ba7ec32b98bab75f28c11cdc5

92

py

Python

kcore_migrate/backends/asyncpg.py

tigeraniya/migrate

40c9e5b252953001440bf9bd3922ab8b66ca6af3

[ "MIT" ]

null

kcore_migrate/backends/asyncpg.py

tigeraniya/migrate

40c9e5b252953001440bf9bd3922ab8b66ca6af3

[ "MIT" ]

null

kcore_migrate/backends/asyncpg.py

tigeraniya/migrate

40c9e5b252953001440bf9bd3922ab8b66ca6af3

[ "MIT" ]

null

from .. ibackend import IMigrationBackend class AsyncpgBackend(IMigrationBackend): pass

23

41

0.815217

8

92

9.375

0.875

0

0.130435

92

4

42

23

0.9375

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

99eaf549c150852e17bcedce00f255e94fb76efd

39

py

Python

main.py

HeeYong4496/test

a72411bf62c25b9c18c9f20d6785a0d35fa230f2

[ "Apache-2.0" ]

1

2021-11-04T14:04:17.000Z

main.py

HeeYong4496/HeeYong4496

8d7793dd8f3fe3db21eda3b7086921b1b1c97308

[ "Apache-2.0" ]

null

main.py

HeeYong4496/HeeYong4496

8d7793dd8f3fe3db21eda3b7086921b1b1c97308

[ "Apache-2.0" ]

null

print("Hello") print("Hello Seoul")

6.5

20

0.641026

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39

5

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0.153846

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5

21

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true

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1

0

null

0

1

0

1

0

6

413269c6c31e60634d6c00521d05c10c359a01dd

118

py

Python

service/__init__.py

tmby1314/BlogSite

5b1da0e4eb9829d010d6d9a5c0d4e5b89586f8f5

[ "Apache-2.0" ]

null

service/__init__.py

tmby1314/BlogSite

5b1da0e4eb9829d010d6d9a5c0d4e5b89586f8f5

[ "Apache-2.0" ]

null

service/__init__.py

tmby1314/BlogSite

5b1da0e4eb9829d010d6d9a5c0d4e5b89586f8f5

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # @Time : 2017/11/16 23:43 # @Author : zhaoshun # @Email : tmby1314@163.com """ """

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1

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null

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6

419d969f556fcd8bc224ae680db81ee03fb3ff74

27

py

Python

src/euler_python_package/euler_python/medium/p220.py

wilsonify/euler

5214b776175e6d76a7c6d8915d0e062d189d9b79

[ "MIT" ]

null

src/euler_python_package/euler_python/medium/p220.py

wilsonify/euler

5214b776175e6d76a7c6d8915d0e062d189d9b79

[ "MIT" ]

null

src/euler_python_package/euler_python/medium/p220.py

wilsonify/euler

5214b776175e6d76a7c6d8915d0e062d189d9b79

[ "MIT" ]

null

def problem220(): pass

9

17

0.62963

3

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5.666667

1

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0.259259

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null

0

1

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null

0

1

0

6

68f6b62260e6b604ffaebfffb5a1ef8b555e1322

6,494

py

Python

tools/miso/psi_estimators.py

globusgenomics/galaxy

7caf74d9700057587b3e3434c64e82c5b16540f1

[ "CC-BY-3.0" ]

1

2021-02-05T13:19:58.000Z

tools/miso/psi_estimators.py

globusgenomics/galaxy

7caf74d9700057587b3e3434c64e82c5b16540f1

[ "CC-BY-3.0" ]

null

tools/miso/psi_estimators.py

globusgenomics/galaxy

7caf74d9700057587b3e3434c64e82c5b16540f1

[ "CC-BY-3.0" ]

null

from scipy import * from numpy import * def curr_psi(NI, NE, skipped_exon_len, read_len, overhang_len, min_reads=0): """ Compute the Psi value. \Psi = DI / (DI + DE) NI is: number of reads in upstream inclusion jxn + number of reads in downstream inclusion jxn + number of body reads in the skipped exon itself (for a skipped exon event, for example.) Note that NI + NE <= min_reads. Return 'n/a' if this is not met. """ if (NI + NE) < min_reads: raise Exception, "curr_psi: min_reads not satisfied." # First term of DI's denominator accounts for body reads, the # second for the two junctions (upstream, downstream) if skipped_exon_len - read_len < 0: raise Exception, "curr_psi: Exon too short for read length." DI = float(NI) / float((skipped_exon_len - read_len + 1) + 2*(read_len + 1 - (2*overhang_len))) # Denominator of DE accounts for the number of positions that our # read (minus the overhang) can be aligned to two adjacent # junctions DE = float(NE) / float(read_len + 1 - (2*overhang_len)) if DI == 0 and DE == 0: raise Exception, "curr_psi undefined." psi = float(DI) / float(DI + DE) if psi > 1 or psi < 0: raise Exception, "Psi out of bounds [0, 1]." return psi def get_psi_densities(NI, NE, skipped_exon_len, read_len, overhang_len): DI = float(NI) / float((skipped_exon_len - read_len + 1) + 2*(read_len + 1 - (2*overhang_len))) DE = float(NE) / float(read_len + 1 - (2*overhang_len)) return DI, DE def curr_psi_one_incjxn(NI, NE, skipped_exon_len, read_len, overhang_len, min_reads=0): """ Compute the Psi value, using only one inclusion junction as the source of inclusion reads. \Psi = DI / (DI + DE) NI is: number of reads in upstream inclusion jxn + number of reads in downstream inclusion jxn + number of body reads in the skipped exon itself (for a skipped exon event, for example.) Note that NI + NE <= min_reads. Return 'n/a' if this is not met. """ if (NI + NE) < min_reads: return 'n/a' DI = float(NI) / float(read_len + 1 - (2*overhang_len)) # Denominator of DE accounts for the number of positions that our # read (minus the overhang) can be aligned to two adjacent # junctions DE = float(NE) / float(read_len + 1 - (2*overhang_len)) ## Temporary # if DI == 0 and DE == 0: # return 0 if DI == 0 and DE == 0: print NI, NE print "Estimator not defined for DI = 0, DE = 0." # return NaN psi = float(DI) / float(DI + DE) return psi def curr_psi_bodyinc(NI, NE, skipped_exon_len, read_len, overhang_len, min_reads=0): """ Compute the Psi value, using only body reads from skipped exon as source of inclusion reads. \Psi = DI / (DI + DE) NI is: number of reads in upstream inclusion jxn + number of reads in downstream inclusion jxn + number of body reads in the skipped exon itself (for a skipped exon event, for example.) Note that NI + NE <= min_reads. Return 'n/a' if this is not met. """ if (NI + NE) < min_reads: return 'n/a' # First term of DI's denominator accounts for body reads, the # second for the two junctions (upstream, downstream) DI = float(NI) / float(skipped_exon_len - read_len + 1) # Denominator of DE accounts for the number of positions that our # read (minus the overhang) can be aligned to two adjacent # junctions DE = float(NE) / float(read_len + 1 - (2*overhang_len)) if DI == 0 and DE == 0: return 0 psi = float(DI) / float(DI + DE) return psi def curr_psi_both_incjxns(NI, NE, skipped_exon_len, read_len, overhang_len, min_reads=0): """ Compute the Psi value, using both inclusion junctions as source of inclusion reads. \Psi = DI / (DI + DE) NI is: number of reads in upstream inclusion jxn + number of reads in downstream inclusion jxn + number of body reads in the skipped exon itself (for a skipped exon event, for example.) Note that NI + NE <= min_reads. Return 'n/a' if this is not met. """ if (NI + NE) < min_reads: return 'n/a' # First term of DI's denominator accounts for body reads, the # second for the two junctions (upstream, downstream) DI = float(NI) / float((read_len + 1 - (2*overhang_len)) + (read_len + 1 - (2*overhang_len))) # Denominator of DE accounts for the number of positions that our # read (minus the overhang) can be aligned to two adjacent # junctions DE = float(NE) / float(read_len + 1 - (2*overhang_len)) if DI == 0 and DE == 0: return 0 psi = float(DI) / float(DI + DE) return psi def psi_bayes(n1, n2, nb, iso1_len, iso2_len, read_len, overhang_len, num_exons=3): """ The MAP/MLE estimator for \Psi, based on a mixture model with uniform prior on \Psi. """ p1 = 1/float((iso1_len - read_len + 1) - 4*(overhang_len-1)) p2 = 1/float((iso2_len - read_len + 1) - 2*(overhang_len-1)) if n1 == 0 and n2 == 0: raise Exception, "Psi Bayes undefined for n1, n2 == 0." psi = (n1*p1 + nb*p1 - 2*n1*p2 - n2*p2 - nb*p2 + sqrt(4*n1*p2*(n1*p1 + n2*p1 + nb*p1 - n1*p2 - n2*p2 - nb*p2) + power((-n1*p1 - nb*p1 + 2*n1*p2 + n2*p2 + nb*p2),2)))/(2*(n1*p1 + n2*p1 + nb*p1 - n1*p2 - n2*p2 - nb*p2)) return psi def transformed_psi_bayes(n1, n2, nb, iso1_len, iso2_len, read_len, overhang_len, num_exons=3): """ Transformed MAP/MLE estimator for \Psi, taking into account lengths of isoforms. """ if (n1 == 0 and n2 == 0) or (nb == 0): raise Exception, "transformed_psi_bayes not defined with: n1=%d, n2=%d, nb=%d" %(n1, n2, nb) psi_bayes_estimate = psi_bayes(n1, n2, nb, iso1_len, iso2_len, read_len, overhang_len, num_exons) ## ## Shouldn't take into account overhang, since it wasn't sampled with ## overhangs in mind ## num_positions_iso1 = (iso1_len - read_len + 1) num_positions_iso2 = (iso2_len - read_len + 1) trans_psi_bayes = (num_positions_iso2*psi_bayes_estimate)/(num_positions_iso1-num_positions_iso1*psi_bayes_estimate + num_positions_iso2*psi_bayes_estimate) return trans_psi_bayes

41.628205

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6,494

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0.130178

0.046679

0.043601

0.030008

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0.718133

0.712234

0.707617

0.698384

0

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6,494

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0.797918

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0

null

0

1

0

null

0

1

0

6

ec00ae13223155e091718ebe8d9619e62c2b089f

31

py

Python

a38/__init__.py

tappoz/python-a38

12d817d82f57019b818f4fd9a76ae1cffd955af7

[ "Apache-2.0" ]

null

a38/__init__.py

tappoz/python-a38

12d817d82f57019b818f4fd9a76ae1cffd955af7

[ "Apache-2.0" ]

null

a38/__init__.py

tappoz/python-a38

12d817d82f57019b818f4fd9a76ae1cffd955af7

[ "Apache-2.0" ]

null

from .fattura import * # noqa

15.5

30

0.677419

4

31

5.25

1

0

0.225806

31

1

31

0.875

0.129032

0

1

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true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

ec2e785f4019da6bb42b504c5bf11c80bef18cb3

143,150

py

Python

satellite_combos.py

mfkiwl/snapshot-gnss-algorithms

4ee4a7874f6b69db08506bf50d4b44ae2aee0bea

[ "0BSD" ]

8

2021-06-19T20:39:17.000Z

2022-01-14T01:29:54.000Z

satellite_combos.py

zhufengGNSS/snapshot-gnss-algorithms

d9ca013c3738926b71abc3c0df55f7f34ece2fe3

[ "0BSD" ]

null

satellite_combos.py

zhufengGNSS/snapshot-gnss-algorithms

d9ca013c3738926b71abc3c0df55f7f34ece2fe3

[ "0BSD" ]

4

2021-06-26T13:18:20.000Z

2022-02-14T11:01:39.000Z

# -*- coding: utf-8 -*- """ Get specific pre-computed index combinations without itertools.combiantions(). Author: Jonas Beuchert """ import numpy as np storage = {} def get_combos(n, k): """Get all combinations of indices. Choose k elements from indices 0...n-1. Inputs: n - Total number of indices k - Number of indices to choose Outputs: combos - 2D NumPy array with all combinations with k elements Author: Jonas Beuchert """ if n not in storage: # Create storage for later use storage[n] = {} # Check if entry exists already if k not in storage[n]: if n == 15 and k == 1: storage[n][k] = np.array( [[0],[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14]] ) elif n == 15 and k == 2: storage[n][k] = np.array( [[0,1],[0,2],[0,3],[0,4],[0,5],[0,6],[0,7],[0,8],[0,9],[0,10],[0,11],[0,12],[0,13],[0,14],[1,2],[1,3],[1,4],[1,5],[1,6],[1,7],[1,8],[1,9],[1,10],[1,11],[1,12],[1,13],[1,14],[2,3],[2,4],[2,5],[2,6],[2,7],[2,8],[2,9],[2,10],[2,11],[2,12],[2,13],[2,14],[3,4],[3,5],[3,6],[3,7],[3,8],[3,9],[3,10],[3,11],[3,12],[3,13],[3,14],[4,5],[4,6],[4,7],[4,8],[4,9],[4,10],[4,11],[4,12],[4,13],[4,14],[5,6],[5,7],[5,8],[5,9],[5,10],[5,11],[5,12],[5,13],[5,14],[6,7],[6,8],[6,9],[6,10],[6,11],[6,12],[6,13],[6,14],[7,8],[7,9],[7,10],[7,11],[7,12],[7,13],[7,14],[8,9],[8,10],[8,11],[8,12],[8,13],[8,14],[9,10],[9,11],[9,12],[9,13],[9,14],[10,11],[10,12],[10,13],[10,14],[11,12],[11,13],[11,14],[12,13],[12,14],[13,14]] ) elif n == 15 and k == 3: storage[n][k] = np.array( [[0,1,2],[0,1,3],[0,1,4],[0,1,5],[0,1,6],[0,1,7],[0,1,8],[0,1,9],[0,1,10],[0,1,11],[0,1,12],[0,1,13],[0,1,14],[0,2,3],[0,2,4],[0,2,5],[0,2,6],[0,2,7],[0,2,8],[0,2,9],[0,2,10],[0,2,11],[0,2,12],[0,2,13],[0,2,14],[0,3,4],[0,3,5],[0,3,6],[0,3,7],[0,3,8],[0,3,9],[0,3,10],[0,3,11],[0,3,12],[0,3,13],[0,3,14],[0,4,5],[0,4,6],[0,4,7],[0,4,8],[0,4,9],[0,4,10],[0,4,11],[0,4,12],[0,4,13],[0,4,14],[0,5,6],[0,5,7],[0,5,8],[0,5,9],[0,5,10],[0,5,11],[0,5,12],[0,5,13],[0,5,14],[0,6,7],[0,6,8],[0,6,9],[0,6,10],[0,6,11],[0,6,12],[0,6,13],[0,6,14],[0,7,8],[0,7,9],[0,7,10],[0,7,11],[0,7,12],[0,7,13],[0,7,14],[0,8,9],[0,8,10],[0,8,11],[0,8,12],[0,8,13],[0,8,14],[0,9,10],[0,9,11],[0,9,12],[0,9,13],[0,9,14],[0,10,11],[0,10,12],[0,10,13],[0,10,14],[0,11,12],[0,11,13],[0,11,14],[0,12,13],[0,12,14],[0,13,14],[1,2,3],[1,2,4],[1,2,5],[1,2,6],[1,2,7],[1,2,8],[1,2,9],[1,2,10],[1,2,11],[1,2,12],[1,2,13],[1,2,14],[1,3,4],[1,3,5],[1,3,6],[1,3,7],[1,3,8],[1,3,9],[1,3,10],[1,3,11],[1,3,12],[1,3,13],[1,3,14],[1,4,5],[1,4,6],[1,4,7],[1,4,8],[1,4,9],[1,4,10],[1,4,11],[1,4,12],[1,4,13],[1,4,14],[1,5,6],[1,5,7],[1,5,8],[1,5,9],[1,5,10],[1,5,11],[1,5,12],[1,5,13],[1,5,14],[1,6,7],[1,6,8],[1,6,9],[1,6,10],[1,6,11],[1,6,12],[1,6,13],[1,6,14],[1,7,8],[1,7,9],[1,7,10],[1,7,11],[1,7,12],[1,7,13],[1,7,14],[1,8,9],[1,8,10],[1,8,11],[1,8,12],[1,8,13],[1,8,14],[1,9,10],[1,9,11],[1,9,12],[1,9,13],[1,9,14],[1,10,11],[1,10,12],[1,10,13],[1,10,14],[1,11,12],[1,11,13],[1,11,14],[1,12,13],[1,12,14],[1,13,14],[2,3,4],[2,3,5],[2,3,6],[2,3,7],[2,3,8],[2,3,9],[2,3,10],[2,3,11],[2,3,12],[2,3,13],[2,3,14],[2,4,5],[2,4,6],[2,4,7],[2,4,8],[2,4,9],[2,4,10],[2,4,11],[2,4,12],[2,4,13],[2,4,14],[2,5,6],[2,5,7],[2,5,8],[2,5,9],[2,5,10],[2,5,11],[2,5,12],[2,5,13],[2,5,14],[2,6,7],[2,6,8],[2,6,9],[2,6,10],[2,6,11],[2,6,12],[2,6,13],[2,6,14],[2,7,8],[2,7,9],[2,7,10],[2,7,11],[2,7,12],[2,7,13],[2,7,14],[2,8,9],[2,8,10],[2,8,11],[2,8,12],[2,8,13],[2,8,14],[2,9,10],[2,9,11],[2,9,12],[2,9,13],[2,9,14],[2,10,11],[2,10,12],[2,10,13],[2,10,14],[2,11,12],[2,11,13],[2,11,14],[2,12,13],[2,12,14],[2,13,14],[3,4,5],[3,4,6],[3,4,7],[3,4,8],[3,4,9],[3,4,10],[3,4,11],[3,4,12],[3,4,13],[3,4,14],[3,5,6],[3,5,7],[3,5,8],[3,5,9],[3,5,10],[3,5,11],[3,5,12],[3,5,13],[3,5,14],[3,6,7],[3,6,8],[3,6,9],[3,6,10],[3,6,11],[3,6,12],[3,6,13],[3,6,14],[3,7,8],[3,7,9],[3,7,10],[3,7,11],[3,7,12],[3,7,13],[3,7,14],[3,8,9],[3,8,10],[3,8,11],[3,8,12],[3,8,13],[3,8,14],[3,9,10],[3,9,11],[3,9,12],[3,9,13],[3,9,14],[3,10,11],[3,10,12],[3,10,13],[3,10,14],[3,11,12],[3,11,13],[3,11,14],[3,12,13],[3,12,14],[3,13,14],[4,5,6],[4,5,7],[4,5,8],[4,5,9],[4,5,10],[4,5,11],[4,5,12],[4,5,13],[4,5,14],[4,6,7],[4,6,8],[4,6,9],[4,6,10],[4,6,11],[4,6,12],[4,6,13],[4,6,14],[4,7,8],[4,7,9],[4,7,10],[4,7,11],[4,7,12],[4,7,13],[4,7,14],[4,8,9],[4,8,10],[4,8,11],[4,8,12],[4,8,13],[4,8,14],[4,9,10],[4,9,11],[4,9,12],[4,9,13],[4,9,14],[4,10,11],[4,10,12],[4,10,13],[4,10,14],[4,11,12],[4,11,13],[4,11,14],[4,12,13],[4,12,14],[4,13,14],[5,6,7],[5,6,8],[5,6,9],[5,6,10],[5,6,11],[5,6,12],[5,6,13],[5,6,14],[5,7,8],[5,7,9],[5,7,10],[5,7,11],[5,7,12],[5,7,13],[5,7,14],[5,8,9],[5,8,10],[5,8,11],[5,8,12],[5,8,13],[5,8,14],[5,9,10],[5,9,11],[5,9,12],[5,9,13],[5,9,14],[5,10,11],[5,10,12],[5,10,13],[5,10,14],[5,11,12],[5,11,13],[5,11,14],[5,12,13],[5,12,14],[5,13,14],[6,7,8],[6,7,9],[6,7,10],[6,7,11],[6,7,12],[6,7,13],[6,7,14],[6,8,9],[6,8,10],[6,8,11],[6,8,12],[6,8,13],[6,8,14],[6,9,10],[6,9,11],[6,9,12],[6,9,13],[6,9,14],[6,10,11],[6,10,12],[6,10,13],[6,10,14],[6,11,12],[6,11,13],[6,11,14],[6,12,13],[6,12,14],[6,13,14],[7,8,9],[7,8,10],[7,8,11],[7,8,12],[7,8,13],[7,8,14],[7,9,10],[7,9,11],[7,9,12],[7,9,13],[7,9,14],[7,10,11],[7,10,12],[7,10,13],[7,10,14],[7,11,12],[7,11,13],[7,11,14],[7,12,13],[7,12,14],[7,13,14],[8,9,10],[8,9,11],[8,9,12],[8,9,13],[8,9,14],[8,10,11],[8,10,12],[8,10,13],[8,10,14],[8,11,12],[8,11,13],[8,11,14],[8,12,13],[8,12,14],[8,13,14],[9,10,11],[9,10,12],[9,10,13],[9,10,14],[9,11,12],[9,11,13],[9,11,14],[9,12,13],[9,12,14],[9,13,14],[10,11,12],[10,11,13],[10,11,14],[10,12,13],[10,12,14],[10,13,14],[11,12,13],[11,12,14],[11,13,14],[12,13,14]] ) elif n == 15 and k == 4: storage[n][k] = np.array( 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,13,14],[7,12,13,14],[8,9,10,11],[8,9,10,12],[8,9,10,13],[8,9,10,14],[8,9,11,12],[8,9,11,13],[8,9,11,14],[8,9,12,13],[8,9,12,14],[8,9,13,14],[8,10,11,12],[8,10,11,13],[8,10,11,14],[8,10,12,13],[8,10,12,14],[8,10,13,14],[8,11,12,13],[8,11,12,14],[8,11,13,14],[8,12,13,14],[9,10,11,12],[9,10,11,13],[9,10,11,14],[9,10,12,13],[9,10,12,14],[9,10,13,14],[9,11,12,13],[9,11,12,14],[9,11,13,14],[9,12,13,14],[10,11,12,13],[10,11,12,14],[10,11,13,14],[10,12,13,14],[11,12,13,14]] ) elif n == 15 and k == 5: storage[n][k] = np.array( 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10,11,14],[6,9,10,12,13],[6,9,10,12,14],[6,9,10,13,14],[6,9,11,12,13],[6,9,11,12,14],[6,9,11,13,14],[6,9,12,13,14],[6,10,11,12,13],[6,10,11,12,14],[6,10,11,13,14],[6,10,12,13,14],[6,11,12,13,14],[7,8,9,10,11],[7,8,9,10,12],[7,8,9,10,13],[7,8,9,10,14],[7,8,9,11,12],[7,8,9,11,13],[7,8,9,11,14],[7,8,9,12,13],[7,8,9,12,14],[7,8,9,13,14],[7,8,10,11,12],[7,8,10,11,13],[7,8,10,11,14],[7,8,10,12,13],[7,8,10,12,14],[7,8,10,13,14],[7,8,11,12,13],[7,8,11,12,14],[7,8,11,13,14],[7,8,12,13,14],[7,9,10,11,12],[7,9,10,11,13],[7,9,10,11,14],[7,9,10,12,13],[7,9,10,12,14],[7,9,10,13,14],[7,9,11,12,13],[7,9,11,12,14],[7,9,11,13,14],[7,9,12,13,14],[7,10,11,12,13],[7,10,11,12,14],[7,10,11,13,14],[7,10,12,13,14],[7,11,12,13,14],[8,9,10,11,12],[8,9,10,11,13],[8,9,10,11,14],[8,9,10,12,13],[8,9,10,12,14],[8,9,10,13,14],[8,9,11,12,13],[8,9,11,12,14],[8,9,11,13,14],[8,9,12,13,14],[8,10,11,12,13],[8,10,11,12,14],[8,10,11,13,14],[8,10,12,13,14],[8,11,12,13,14],[9,10,11,12,13],[9,10,11,12,14],[9,10,11,13,14],[9,10,12,13,14],[9,11,12,13,14],[10,11,12,13,14]] ) elif n == 15 and k == 6: storage[n][k] = np.array( 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13,14],[8,9,10,12,13,14],[8,9,11,12,13,14],[8,10,11,12,13,14],[9,10,11,12,13,14]] ) else: print( """ n={} and k={} not supported by acceleration. Choose n=15 and k=1...6 for speed-up.""".format(n, k) ) from itertools import combinations # Cannot use pre-calculated values sat_combinations = combinations(iter(np.arange(n)), k) storage[n][k] = np.array([*sat_combinations]) return storage[n][k]

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Python

bip_utils/bip/conf/bip84/__init__.py

MIPPLTeam/bip_utils

c66446e7ac3879d2cf6308c5b8eb7f7705292660

[ "MIT" ]

149

2020-05-15T08:11:43.000Z

2022-03-29T16:34:42.000Z

bip_utils/bip/conf/bip84/__init__.py

MIPPLTeam/bip_utils

c66446e7ac3879d2cf6308c5b8eb7f7705292660

[ "MIT" ]

41

2020-04-03T15:57:56.000Z

2022-03-31T08:25:11.000Z

bip_utils/bip/conf/bip84/__init__.py

MIPPLTeam/bip_utils

c66446e7ac3879d2cf6308c5b8eb7f7705292660

[ "MIT" ]

55

2020-04-03T17:05:15.000Z

2022-03-24T12:43:42.000Z

from bip_utils.bip.conf.bip84.bip84_coins import Bip84Coins from bip_utils.bip.conf.bip84.bip84_conf import Bip84Conf from bip_utils.bip.conf.bip84.bip84_conf_getter import Bip84ConfGetter

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6

6b65510013770dc24b57a454e8258f4463ebcfc6

13,832

py

Python

frites/simulations/sim_local_mi.py

StanSStanman/frites

53f4745979dc2e7b27145cd63eab6a82fe893ec7

[ "BSD-3-Clause" ]

35

2019-10-09T11:01:29.000Z

2022-03-12T02:24:39.000Z

frites/simulations/sim_local_mi.py

StanSStanman/frites

53f4745979dc2e7b27145cd63eab6a82fe893ec7

[ "BSD-3-Clause" ]

14

2020-12-05T09:26:00.000Z

2022-01-17T08:24:06.000Z

frites/simulations/sim_local_mi.py

StanSStanman/frites

53f4745979dc2e7b27145cd63eab6a82fe893ec7

[ "BSD-3-Clause" ]

13

2021-01-06T12:58:47.000Z

2022-03-09T14:55:24.000Z

"""Simulate local representation of mutual information.""" import numpy as np """ ############################################################################### I(C; C) ############################################################################### - MI between two continuous variables - Single / Multi subjects simulations """ def sim_local_cc_ms(n_subjects, random_state=None, **kwargs): """Multi-subjects simulations for computing local MI (CC). This function can be used for simulating local representations of mutual information between two continuous variables (CC) across multiple subjects. Parameters ---------- n_subjects : int Number of subjects kwargs : dict | {} Additional arguments are send to the function :func:`sim_local_cc_ss` Returns ------- x : list List length n_subjects composed of data arrays each one with a shape of (n_epochs, n_channels, n_times) y : list List of length n_subjects composed of regressor arrays each one with a shape of (n_epochs) roi : list List of length n_subjects composed of roi arrays each one with a shape of (n_roi) times : array_like Time vector """ # get the default cluster indices and covariance cl_index = kwargs.get('cl_index', [40, 60]) cl_cov = kwargs.get('cl_cov', [.8]) cl_sgn = kwargs.get('cl_sgn', [1]) # repeat if not equal to subject length if len(cl_index) != n_subjects: cl_index = [cl_index] * n_subjects if len(cl_cov) != n_subjects: cl_cov = [cl_cov] * n_subjects if len(cl_sgn) != n_subjects: cl_sgn = cl_sgn * n_subjects if not isinstance(random_state, int): random_state = np.random.randint(1000) # now generate the data x, y, roi = [], [], [] for n_s in range(n_subjects): # re-inject the indices and covariance kwargs['cl_index'] = cl_index[n_s] kwargs['cl_cov'] = cl_cov[n_s] kwargs['cl_sgn'] = cl_sgn[n_s] # generate the data of a single subject _x, _y, _roi, times = sim_local_cc_ss(random_state=random_state + n_s, **kwargs) # merge data x += [_x] y += [_y] roi += [_roi] return x, y, roi, times def sim_local_cc_ss(n_epochs=10, n_times=100, n_roi=1, cl_index=[40, 60], cl_cov=[.8], cl_sgn=1, random_state=None): """Single-subject simulations for computing local MI (CC). This function can be used for simulating local representations of mutual information between two continuous variables (CC) for a single subject. Parameters ---------- n_epochs : int | 30 Number of trials n_times : int | 100 Number of time points n_roi : int | 1 Number of ROI cl_index : array_like | [40, 60] Sample indices where the clusters are located. Should be an array of shape (n_clusters, 2) cl_cov : array_like | [.8] Covariance level between the data and the regressor variable. Should be an array of shape (n_clusters,) cl_sgn : {-1, 1} Sign of the correlation. Use -1 for anti-correlated variables and 1 for correlated variables random_state : int | None Random state (use it for reproducibility) Returns ------- x : array_like Data array of shape (n_epochs, n_channels, n_times) y : array_like Regressor array of shape (n_epochs,) roi : array_like Array of ROI names of shape (n_roi,) times : array_like Time vector of shape (n_times,) """ random_state = np.random.randint(100) if not isinstance( random_state, int) else random_state rnd = np.random.RandomState(random_state) # ------------------------------------------------------------------------- # Pick random n_roi roi = np.array([f"roi_{k}" for k in range(n_roi)]) # ------------------------------------------------------------------------- # check cluster types cl_index, cl_cov = np.atleast_2d(cl_index), np.asarray(cl_cov) assert (cl_index.shape[-1] == 2) and (cl_cov.ndim == 1) assert cl_sgn in [-1, 1] if cl_index.shape[0] == 1: cl_index = np.tile(cl_index, (n_roi, 1)) if cl_cov.shape[0] == 1: cl_cov = np.repeat(cl_cov, n_roi) assert (cl_index.shape == (n_roi, 2)) and (cl_cov.shape == (n_roi,)) # ------------------------------------------------------------------------- # Built a random dataset x = rnd.randn(n_epochs, n_roi, n_times) y = rnd.randn(n_epochs).reshape(-1, 1) # ------------------------------------------------------------------------- # Introduce a correlation between the data and the regressor for num, (idx, cov) in enumerate(zip(cl_index, cl_cov)): if not np.isfinite(cov): continue # noqa # define correlation strength t_len = idx[1] - idx[0] epsilon = np.sqrt((1. - cov ** 2) / cov ** 2) # Generate noise rnd_noise = np.random.RandomState(random_state + num + 1) noise = epsilon * rnd_noise.randn(n_epochs, t_len) x[:, num, idx[0]:idx[1]] = cl_sgn * y + noise times = np.arange(n_times) return x, y.ravel(), roi, times """ ############################################################################### I(C; D) ############################################################################### - MI between a continuous and a discret variable - Single / Multi subjects simulations """ def sim_local_cd_ms(n_subjects, **kwargs): """Multi-subjects simulations for computing local MI (CD). This function can be used for simulating local representations of mutual information between a continuous and a discret variables (CD) for a single subject. Parameters ---------- n_subjects : int Number of subjects kwargs : dict | {} Additional arguments are send to the function :func:`sim_local_cd_ss` Returns ------- x : list List length n_subjects composed of data arrays each one with a shape of (n_epochs, n_channels, n_times) y : list List of length n_subjects composed of regressor arrays each one with a shape of (n_epochs) roi : list List of length n_subjects composed of roi arrays each one with a shape of (n_roi) times : array_like Time vector of shape (n_times,) """ # get the default cluster indices and covariance cl_index = kwargs.get('cl_index', [40, 60]) cl_cov = kwargs.get('cl_cov', [.8]) # repeat if not equal to subject length if len(cl_index) != n_subjects: cl_index = [cl_index] * n_subjects if len(cl_cov) != n_subjects: cl_cov = [cl_cov] * n_subjects # now generate the data x, y, roi = [], [], [] for n_s in range(n_subjects): # re-inject the indices and covariance kwargs['cl_index'] = cl_index[n_s] kwargs['cl_cov'] = cl_cov[n_s] # generate the data of a single subject _x, _y, _roi, times = sim_local_cd_ss(random_state=n_s, **kwargs) # merge data x += [_x] y += [_y] roi += [_roi] return x, y, roi, times def sim_local_cd_ss(n_conditions=2, n_epochs=10, n_times=100, n_roi=1, cl_index=[40, 60], cl_cov=[.8], random_state=None): """Single-subject simulations for computing local MI (CD). This function can be used for simulating local representations of mutual information between a continuous and a discret variable (CD) for a single subject. Parameters ---------- n_conditions : int | 2 Number of conditions n_epochs : int | 30 Number of trials n_times : int | 100 Number of time points n_roi : int | 1 Number of ROI cl_index : array_like | [40, 60] Sample indices where the clusters are located. Should be an array of shape (n_clusters, 2) cl_cov : array_like | [.8] Covariance level between the data and the regressor variable. Should be an array of shape (n_clusters,) random_state : int | None Random state (use it for reproducibility) Returns ------- x : array_like Data array of shape (n_epochs, n_channels, n_times) y : array_like Condition array of shape (n_epochs,) roi : array_like Array of ROI names of shape (n_roi,) times : array_like Time vector of shape (n_times,) """ random_state = np.random.randint(100) if not isinstance( random_state, int) else random_state rnd = np.random.RandomState(random_state) # ------------------------------------------------------------------------- # Pick random n_roi roi = np.array([f"roi_{k}" for k in range(n_roi)]) # ------------------------------------------------------------------------- # check cluster types cl_index, cl_cov = np.atleast_2d(cl_index), np.asarray(cl_cov) assert (cl_index.shape[-1] == 2) and (cl_cov.ndim == 1) if cl_index.shape[0] == 1: cl_index = np.tile(cl_index, (n_roi, 1)) if cl_cov.shape[0] == 1: cl_cov = np.repeat(cl_cov, n_roi) assert (cl_index.shape == (n_roi, 2)) and (cl_cov.shape == (n_roi,)) # ------------------------------------------------------------------------- # linearly spaced values taken from a gaussian distribution res = 100 pick_up = np.linspace(0, res - 1, n_conditions).astype(int) values = np.sort(rnd.randn(res))[pick_up] # regressor variable y_regr = np.repeat(values, np.round(n_epochs, n_conditions)) y_regr = rnd.permutation(y_regr)[0:n_epochs] # condition variable _, y = np.unique(y_regr, return_inverse=True) y_regr = y_regr.reshape(-1, 1) x = rnd.randn(n_epochs, n_roi, n_times) # ------------------------------------------------------------------------- # Introduce a correlation between the data and the regressor for num, (idx, cov) in enumerate(zip(cl_index, cl_cov)): # define correlation strength t_len = idx[1] - idx[0] epsilon = np.sqrt((1. - cov ** 2) / cov ** 2) # Generate noise rnd_noise = np.random.RandomState(random_state + num + 1) noise = epsilon * rnd_noise.randn(n_epochs, t_len) x[:, num, idx[0]:idx[1]] = y_regr + noise times = np.arange(n_times) return x, y.astype(int), roi, times """ ############################################################################### I(C; C | D) ############################################################################### - MI between two continuous variables conditioned by a discret variable - Single / Multi subjects simulations """ def sim_local_ccd_ms(n_subjects, **kwargs): """Multi-subjects simulations for computing local MI (CCD). This function can be used for simulating local representations of mutual information between two continuous variables conditioned by a third discret one (CCD) across multiple subjects. Parameters ---------- n_subjects : int Number of subjects kwargs : dict | {} Additional arguments are send to the function :func:`sim_local_ccd_ss` Returns ------- x : list List length n_subjects composed of data arrays each one with a shape of (n_epochs, n_channels, n_times) y : list List of length n_subjects composed of regressor arrays each one with a shape of (n_epochs) z : array_like Condition array of shape (n_epochs,) roi : list List of length n_subjects composed of roi arrays each one with a shape of (n_roi) times : array_like Time vector """ n_c = kwargs.get('n_conditions', 2) if 'n_conditions' in list(kwargs.keys()): kwargs.pop('n_conditions') x, y, roi, times = sim_local_cc_ms(n_subjects, **kwargs) n_e = len(y[0]) z = [np.random.randint(0, n_c, (n_e,)) for k in range(n_subjects)] return x, y, z, roi, times def sim_local_ccd_ss(n_epochs=10, n_times=100, n_roi=1, n_conditions=2, cl_index=[40, 60], cl_cov=[.8], random_state=None): """Single-subject simulations for computing local MI (CC). This function can be used for simulating local representations of mutual information between two continuous variables conditioned by a third discret one (CCD) for a single subject. Parameters ---------- n_epochs : int | 30 Number of trials n_times : int | 100 Number of time points n_roi : int | 1 Number of ROI n_conditions : int | 2 Number of conditions cl_index : array_like | [40, 60] Sample indices where the clusters are located. Should be an array of shape (n_clusters, 2) cl_cov : array_like | [.8] Covariance level between the data and the regressor variable. Should be an array of shape (n_clusters,) random_state : int | None Random state (use it for reproducibility) Returns ------- x : array_like Data array of shape (n_epochs, n_channels, n_times) y : array_like Regressor array of shape (n_epochs,) z : array_like Condition array of shape (n_epochs,) roi : array_like Array of ROI names of shape (n_roi,) times : array_like Time vector of shape (n_times,) """ x, y, roi, times = sim_local_cc_ss( n_epochs=n_epochs, n_times=n_times, n_roi=n_roi, cl_index=cl_index, cl_cov=cl_cov, random_state=random_state) z = np.random.randint(0, n_conditions, (n_epochs,)) return x, y, z, roi, times

35.557841

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1,890

13,832

4.028042

0.103175

0.03494

0.022068

0.023906

0.883357

0.867595

0.850256

0.817943

0.812032

0.796795

0

0.0147

0.257374

13,832

388

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35.649485

0.726441

0.502024

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0.119266

0

null

0

1

0

null

0

6

6bd3ca0cad733c32f5d86cb834a679ac4561669b

178

py

Python

python/8kyu/sort_and_star.py

Sigmanificient/codewars

b34df4bf55460d312b7ddf121b46a707b549387a

[ "MIT" ]

3

2021-06-08T01:57:13.000Z

2021-06-26T10:52:47.000Z

python/8kyu/sort_and_star.py

Sigmanificient/codewars

b34df4bf55460d312b7ddf121b46a707b549387a

[ "MIT" ]

null

python/8kyu/sort_and_star.py

Sigmanificient/codewars

b34df4bf55460d312b7ddf121b46a707b549387a

[ "MIT" ]

2

2021-06-10T21:20:13.000Z

2021-06-30T10:13:26.000Z

"""Kata url: https://www.codewars.com/kata/57cfdf34902f6ba3d300001e.""" from typing import List def two_sort(array: List[str]) -> str: return '***'.join(sorted(array)[0])

22.25

71

0.685393

24

178

5.041667

0.833333

0

0.101911

0.117978

178

7

72

25.428571

0.66879

0.365169

0

0.028037

0

1

0.333333

false

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0.333333

1

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1

0

null

0

1

0

null

0

1

0

1

0

6

6beceb207208ae3ace01806f4b04047a7539c555

33

py

Python

object_detection2/data/__init__.py

vghost2008/wml

d0c5a1da6c228e321ae59a563e9ac84aa66266ff

[ "MIT" ]

6

2019-12-10T17:18:56.000Z

2022-03-01T01:00:35.000Z

object_detection2/data/__init__.py

vghost2008/wml

d0c5a1da6c228e321ae59a563e9ac84aa66266ff

[ "MIT" ]

2

2021-08-25T16:16:01.000Z

2022-02-10T05:21:19.000Z

object_detection2/data/__init__.py

vghost2008/wml

d0c5a1da6c228e321ae59a563e9ac84aa66266ff

[ "MIT" ]

2

2019-12-07T09:57:35.000Z

2021-09-06T04:58:10.000Z

from . import buildin_dataprocess

33

0.878788

4

33

7

1

0

0.090909

33

1

33

0.933333

0

1

0

true

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1

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null

0

1

0

null

0

1

0

1

0

1

0

6

d40d04ebf5316f8b1731bf9cd0ea41ec32233b6a

29,646

py

Python

pybind/slxos/v16r_1_00b/mpls_state/statistics_oam/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

null

pybind/slxos/v16r_1_00b/mpls_state/statistics_oam/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

null

pybind/slxos/v16r_1_00b/mpls_state/statistics_oam/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

[ "Apache-2.0" ]

1

2021-11-05T22:15:42.000Z

from operator import attrgetter import pyangbind.lib.xpathhelper as xpathhelper from pyangbind.lib.yangtypes import RestrictedPrecisionDecimalType, RestrictedClassType, TypedListType from pyangbind.lib.yangtypes import YANGBool, YANGListType, YANGDynClass, ReferenceType from pyangbind.lib.base import PybindBase from decimal import Decimal from bitarray import bitarray import __builtin__ import return_codes class statistics_oam(PybindBase): """ This class was auto-generated by the PythonClass plugin for PYANG from YANG module brocade-mpls-operational - based on the path /mpls-state/statistics-oam. Each member element of the container is represented as a class variable - with a specific YANG type. YANG Description: OAM packet statistics """ __slots__ = ('_pybind_generated_by', '_path_helper', '_yang_name', '_rest_name', '_extmethods', '__usr_ping_count','__usr_traceroute_count','__echo_req_sent_count','__echo_req_received_count','__echo_req_timeout_count','__echo_resp_sent_count','__echo_resp_received_count','__return_codes',) _yang_name = 'statistics-oam' _rest_name = 'statistics-oam' _pybind_generated_by = 'container' def __init__(self, *args, **kwargs): path_helper_ = kwargs.pop("path_helper", None) if path_helper_ is False: self._path_helper = False elif path_helper_ is not None and isinstance(path_helper_, xpathhelper.YANGPathHelper): self._path_helper = path_helper_ elif hasattr(self, "_parent"): path_helper_ = getattr(self._parent, "_path_helper", False) self._path_helper = path_helper_ else: self._path_helper = False extmethods = kwargs.pop("extmethods", None) if extmethods is False: self._extmethods = False elif extmethods is not None and isinstance(extmethods, dict): self._extmethods = extmethods elif hasattr(self, "_parent"): extmethods = getattr(self._parent, "_extmethods", None) self._extmethods = extmethods else: self._extmethods = False self.__echo_req_timeout_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-timeout-count", rest_name="echo-req-timeout-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) self.__usr_traceroute_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="usr-traceroute-count", rest_name="usr-traceroute-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) self.__return_codes = YANGDynClass(base=YANGListType("number",return_codes.return_codes, yang_name="return-codes", rest_name="return-codes", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='number', extensions={u'tailf-common': {u'callpoint': u'mpls-statistics-oam-retcode', u'cli-suppress-show-path': None}}), is_container='list', yang_name="return-codes", rest_name="return-codes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'callpoint': u'mpls-statistics-oam-retcode', u'cli-suppress-show-path': None}}, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='list', is_config=False) self.__echo_resp_received_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-resp-received-count", rest_name="echo-resp-received-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) self.__echo_req_sent_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-sent-count", rest_name="echo-req-sent-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) self.__echo_req_received_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-received-count", rest_name="echo-req-received-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) self.__echo_resp_sent_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-resp-sent-count", rest_name="echo-resp-sent-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) self.__usr_ping_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="usr-ping-count", rest_name="usr-ping-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) load = kwargs.pop("load", None) if args: if len(args) > 1: raise TypeError("cannot create a YANG container with >1 argument") all_attr = True for e in self._pyangbind_elements: if not hasattr(args[0], e): all_attr = False break if not all_attr: raise ValueError("Supplied object did not have the correct attributes") for e in self._pyangbind_elements: nobj = getattr(args[0], e) if nobj._changed() is False: continue setmethod = getattr(self, "_set_%s" % e) if load is None: setmethod(getattr(args[0], e)) else: setmethod(getattr(args[0], e), load=load) def _path(self): if hasattr(self, "_parent"): return self._parent._path()+[self._yang_name] else: return [u'mpls-state', u'statistics-oam'] def _rest_path(self): if hasattr(self, "_parent"): if self._rest_name: return self._parent._rest_path()+[self._rest_name] else: return self._parent._rest_path() else: return [u'mpls-state', u'statistics-oam'] def _get_usr_ping_count(self): """ Getter method for usr_ping_count, mapped from YANG variable /mpls_state/statistics_oam/usr_ping_count (uint32) YANG Description: Count of user initiated ping requests """ return self.__usr_ping_count def _set_usr_ping_count(self, v, load=False): """ Setter method for usr_ping_count, mapped from YANG variable /mpls_state/statistics_oam/usr_ping_count (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_usr_ping_count is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_usr_ping_count() directly. YANG Description: Count of user initiated ping requests """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="usr-ping-count", rest_name="usr-ping-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """usr_ping_count must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="usr-ping-count", rest_name="usr-ping-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False)""", }) self.__usr_ping_count = t if hasattr(self, '_set'): self._set() def _unset_usr_ping_count(self): self.__usr_ping_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="usr-ping-count", rest_name="usr-ping-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) def _get_usr_traceroute_count(self): """ Getter method for usr_traceroute_count, mapped from YANG variable /mpls_state/statistics_oam/usr_traceroute_count (uint32) YANG Description: Count of user initiated traceroute requests """ return self.__usr_traceroute_count def _set_usr_traceroute_count(self, v, load=False): """ Setter method for usr_traceroute_count, mapped from YANG variable /mpls_state/statistics_oam/usr_traceroute_count (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_usr_traceroute_count is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_usr_traceroute_count() directly. YANG Description: Count of user initiated traceroute requests """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="usr-traceroute-count", rest_name="usr-traceroute-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """usr_traceroute_count must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="usr-traceroute-count", rest_name="usr-traceroute-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False)""", }) self.__usr_traceroute_count = t if hasattr(self, '_set'): self._set() def _unset_usr_traceroute_count(self): self.__usr_traceroute_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="usr-traceroute-count", rest_name="usr-traceroute-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) def _get_echo_req_sent_count(self): """ Getter method for echo_req_sent_count, mapped from YANG variable /mpls_state/statistics_oam/echo_req_sent_count (uint32) YANG Description: Count of MPLS Echo requests sent """ return self.__echo_req_sent_count def _set_echo_req_sent_count(self, v, load=False): """ Setter method for echo_req_sent_count, mapped from YANG variable /mpls_state/statistics_oam/echo_req_sent_count (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_echo_req_sent_count is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_echo_req_sent_count() directly. YANG Description: Count of MPLS Echo requests sent """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-sent-count", rest_name="echo-req-sent-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """echo_req_sent_count must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-sent-count", rest_name="echo-req-sent-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False)""", }) self.__echo_req_sent_count = t if hasattr(self, '_set'): self._set() def _unset_echo_req_sent_count(self): self.__echo_req_sent_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-sent-count", rest_name="echo-req-sent-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) def _get_echo_req_received_count(self): """ Getter method for echo_req_received_count, mapped from YANG variable /mpls_state/statistics_oam/echo_req_received_count (uint32) YANG Description: Count of MPLS Echo requests received """ return self.__echo_req_received_count def _set_echo_req_received_count(self, v, load=False): """ Setter method for echo_req_received_count, mapped from YANG variable /mpls_state/statistics_oam/echo_req_received_count (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_echo_req_received_count is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_echo_req_received_count() directly. YANG Description: Count of MPLS Echo requests received """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-received-count", rest_name="echo-req-received-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """echo_req_received_count must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-received-count", rest_name="echo-req-received-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False)""", }) self.__echo_req_received_count = t if hasattr(self, '_set'): self._set() def _unset_echo_req_received_count(self): self.__echo_req_received_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-received-count", rest_name="echo-req-received-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) def _get_echo_req_timeout_count(self): """ Getter method for echo_req_timeout_count, mapped from YANG variable /mpls_state/statistics_oam/echo_req_timeout_count (uint32) YANG Description: Count of MPLS Echo requests timedout """ return self.__echo_req_timeout_count def _set_echo_req_timeout_count(self, v, load=False): """ Setter method for echo_req_timeout_count, mapped from YANG variable /mpls_state/statistics_oam/echo_req_timeout_count (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_echo_req_timeout_count is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_echo_req_timeout_count() directly. YANG Description: Count of MPLS Echo requests timedout """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-timeout-count", rest_name="echo-req-timeout-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """echo_req_timeout_count must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-timeout-count", rest_name="echo-req-timeout-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False)""", }) self.__echo_req_timeout_count = t if hasattr(self, '_set'): self._set() def _unset_echo_req_timeout_count(self): self.__echo_req_timeout_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-req-timeout-count", rest_name="echo-req-timeout-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) def _get_echo_resp_sent_count(self): """ Getter method for echo_resp_sent_count, mapped from YANG variable /mpls_state/statistics_oam/echo_resp_sent_count (uint32) YANG Description: Count of MPLS Echo responses sent """ return self.__echo_resp_sent_count def _set_echo_resp_sent_count(self, v, load=False): """ Setter method for echo_resp_sent_count, mapped from YANG variable /mpls_state/statistics_oam/echo_resp_sent_count (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_echo_resp_sent_count is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_echo_resp_sent_count() directly. YANG Description: Count of MPLS Echo responses sent """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-resp-sent-count", rest_name="echo-resp-sent-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """echo_resp_sent_count must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-resp-sent-count", rest_name="echo-resp-sent-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False)""", }) self.__echo_resp_sent_count = t if hasattr(self, '_set'): self._set() def _unset_echo_resp_sent_count(self): self.__echo_resp_sent_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-resp-sent-count", rest_name="echo-resp-sent-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) def _get_echo_resp_received_count(self): """ Getter method for echo_resp_received_count, mapped from YANG variable /mpls_state/statistics_oam/echo_resp_received_count (uint32) YANG Description: Count of MPLS Echo responses received """ return self.__echo_resp_received_count def _set_echo_resp_received_count(self, v, load=False): """ Setter method for echo_resp_received_count, mapped from YANG variable /mpls_state/statistics_oam/echo_resp_received_count (uint32) If this variable is read-only (config: false) in the source YANG file, then _set_echo_resp_received_count is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_echo_resp_received_count() directly. YANG Description: Count of MPLS Echo responses received """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-resp-received-count", rest_name="echo-resp-received-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """echo_resp_received_count must be of a type compatible with uint32""", 'defined-type': "uint32", 'generated-type': """YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-resp-received-count", rest_name="echo-resp-received-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False)""", }) self.__echo_resp_received_count = t if hasattr(self, '_set'): self._set() def _unset_echo_resp_received_count(self): self.__echo_resp_received_count = YANGDynClass(base=RestrictedClassType(base_type=long, restriction_dict={'range': ['0..4294967295']}, int_size=32), is_leaf=True, yang_name="echo-resp-received-count", rest_name="echo-resp-received-count", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='uint32', is_config=False) def _get_return_codes(self): """ Getter method for return_codes, mapped from YANG variable /mpls_state/statistics_oam/return_codes (list) YANG Description: OAM packet statistics return code """ return self.__return_codes def _set_return_codes(self, v, load=False): """ Setter method for return_codes, mapped from YANG variable /mpls_state/statistics_oam/return_codes (list) If this variable is read-only (config: false) in the source YANG file, then _set_return_codes is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_return_codes() directly. YANG Description: OAM packet statistics return code """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=YANGListType("number",return_codes.return_codes, yang_name="return-codes", rest_name="return-codes", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='number', extensions={u'tailf-common': {u'callpoint': u'mpls-statistics-oam-retcode', u'cli-suppress-show-path': None}}), is_container='list', yang_name="return-codes", rest_name="return-codes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'callpoint': u'mpls-statistics-oam-retcode', u'cli-suppress-show-path': None}}, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='list', is_config=False) except (TypeError, ValueError): raise ValueError({ 'error-string': """return_codes must be of a type compatible with list""", 'defined-type': "list", 'generated-type': """YANGDynClass(base=YANGListType("number",return_codes.return_codes, yang_name="return-codes", rest_name="return-codes", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='number', extensions={u'tailf-common': {u'callpoint': u'mpls-statistics-oam-retcode', u'cli-suppress-show-path': None}}), is_container='list', yang_name="return-codes", rest_name="return-codes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'callpoint': u'mpls-statistics-oam-retcode', u'cli-suppress-show-path': None}}, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='list', is_config=False)""", }) self.__return_codes = t if hasattr(self, '_set'): self._set() def _unset_return_codes(self): self.__return_codes = YANGDynClass(base=YANGListType("number",return_codes.return_codes, yang_name="return-codes", rest_name="return-codes", parent=self, is_container='list', user_ordered=False, path_helper=self._path_helper, yang_keys='number', extensions={u'tailf-common': {u'callpoint': u'mpls-statistics-oam-retcode', u'cli-suppress-show-path': None}}), is_container='list', yang_name="return-codes", rest_name="return-codes", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'callpoint': u'mpls-statistics-oam-retcode', u'cli-suppress-show-path': None}}, namespace='urn:brocade.com:mgmt:brocade-mpls-operational', defining_module='brocade-mpls-operational', yang_type='list', is_config=False) usr_ping_count = __builtin__.property(_get_usr_ping_count) usr_traceroute_count = __builtin__.property(_get_usr_traceroute_count) echo_req_sent_count = __builtin__.property(_get_echo_req_sent_count) echo_req_received_count = __builtin__.property(_get_echo_req_received_count) echo_req_timeout_count = __builtin__.property(_get_echo_req_timeout_count) echo_resp_sent_count = __builtin__.property(_get_echo_resp_sent_count) echo_resp_received_count = __builtin__.property(_get_echo_resp_received_count) return_codes = __builtin__.property(_get_return_codes) _pyangbind_elements = {'usr_ping_count': usr_ping_count, 'usr_traceroute_count': usr_traceroute_count, 'echo_req_sent_count': echo_req_sent_count, 'echo_req_received_count': echo_req_received_count, 'echo_req_timeout_count': echo_req_timeout_count, 'echo_resp_sent_count': echo_resp_sent_count, 'echo_resp_received_count': echo_resp_received_count, 'return_codes': return_codes, }

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null

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null

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6

2e17319608f88884574f4d9f2eec350031f2d290

20

py

Python

pywork/py1.py

infinityman8/pythonwork-uni

8ba7f341573f3031710d1bf4d91849508aa81bf8

[ "MIT" ]

null

pywork/py1.py

infinityman8/pythonwork-uni

8ba7f341573f3031710d1bf4d91849508aa81bf8

[ "MIT" ]

null

pywork/py1.py

infinityman8/pythonwork-uni

8ba7f341573f3031710d1bf4d91849508aa81bf8

[ "MIT" ]

null

x=4 y=5 a=3(x+y)

5

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1

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null

0

6

2e352d4498a933b27cc6dc7695b09136bb4e78ce

2,716

py

Python

src/pytorch_yard/avalanche/scenarios.py

karolpiczak/pytorch-yard

1bf2515ffdf63365af87dffecc0e393b4a24ec0f

[ "MIT" ]

null

src/pytorch_yard/avalanche/scenarios.py

karolpiczak/pytorch-yard

1bf2515ffdf63365af87dffecc0e393b4a24ec0f

[ "MIT" ]

null

src/pytorch_yard/avalanche/scenarios.py

karolpiczak/pytorch-yard

1bf2515ffdf63365af87dffecc0e393b4a24ec0f

[ "MIT" ]

null

from typing import Any, Tuple, cast import torch import torch.utils.data from avalanche.benchmarks.generators.benchmark_generators import nc_benchmark from avalanche.benchmarks.scenarios.new_classes.nc_scenario import NCScenario def incremental_task( train: torch.utils.data.Dataset[torch.Tensor], test: torch.utils.data.Dataset[torch.Tensor], transform: Any, n_experiences: int, n_classes: int, ) -> Tuple[NCScenario, int]: """ Incremental task setup. Task labels are provided, classes from `0` to `n_classes` split over `n_experiences` (without remapping). Most commonly used with a multi-head setup, where each head is trained on a different experience. """ benchmark = nc_benchmark( train_dataset=cast(Any, train), test_dataset=cast(Any, test), n_experiences=n_experiences, task_labels=True, fixed_class_order=range(n_classes), class_ids_from_zero_in_each_exp=True, train_transform=transform, eval_transform=transform, ) n_output_classes = n_classes // n_experiences return benchmark, n_output_classes def incremental_domain( train: torch.utils.data.Dataset[torch.Tensor], test: torch.utils.data.Dataset[torch.Tensor], transform: Any, n_experiences: int, n_classes: int, ) -> Tuple[NCScenario, int]: """ Incremental domain setup. No task labels, classes are remapped to `0, ..., effective_n_classes`, where `effective_n_classes` is the number of classes per single experience. """ benchmark = nc_benchmark( train_dataset=cast(Any, train), test_dataset=cast(Any, test), n_experiences=n_experiences, task_labels=False, fixed_class_order=range(n_classes), class_ids_from_zero_in_each_exp=True, train_transform=transform, eval_transform=transform, ) n_output_classes = n_classes // n_experiences return benchmark, n_output_classes def incremental_class( train: torch.utils.data.Dataset[torch.Tensor], test: torch.utils.data.Dataset[torch.Tensor], transform: Any, n_experiences: int, n_classes: int, ) -> Tuple[NCScenario, int]: """ Incremental class setup. No task labels, classes from `0` to `n_classes` split over `n_experiences` (without remapping). """ benchmark = nc_benchmark( train_dataset=cast(Any, train), test_dataset=cast(Any, test), n_experiences=n_experiences, task_labels=False, fixed_class_order=range(n_classes), train_transform=transform, eval_transform=transform, ) n_output_classes = n_classes return benchmark, n_output_classes

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0.001401

0.211708

2,716

95

110

28.589474

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0

null

0

1

0

1

0

null

0

6

2e39a457a24758f095aeb213ba1555d1c57cdc96

36

py

Python

core/__init__.py

KJook/KJSerial

b362d2a968b60732241214acffb846d93edc3d3f

[ "MIT" ]

1

2022-03-18T05:46:54.000Z

core/__init__.py

KJook/KJSerial

b362d2a968b60732241214acffb846d93edc3d3f

[ "MIT" ]

null

core/__init__.py

KJook/KJSerial

b362d2a968b60732241214acffb846d93edc3d3f

[ "MIT" ]

1

2022-03-22T02:46:48.000Z

from .s import getPortList, myserial

36

0.833333

5

36

6

1

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0.111111

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1

0

1

0

1

0

6

2e6985c41102764af81fb1c8d486c4ef6ad10277

26

py

Python

environment/__init__.py

mbed92/soft-grip

4399a4ab719bf29303769de33977a037624d864d

[ "MIT" ]

5

2020-01-19T08:55:55.000Z

2021-07-08T13:12:24.000Z

environment/__init__.py

mbed92/soft-grip

4399a4ab719bf29303769de33977a037624d864d

[ "MIT" ]

null

environment/__init__.py

mbed92/soft-grip

4399a4ab719bf29303769de33977a037624d864d

[ "MIT" ]

1

2020-06-28T08:20:33.000Z

from .manenv import ManEnv

26

0.846154

4

26

5.5

0.75

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0.115385

26

1

26

0.956522

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null

0

1

0

1

0

1

0

6

2e8523ba350a4bfdeff9803111fe3876e7501841

100

py

Python

src/gsc/utils.py

nguyen-ngoc-thach/gitlab-search-command-tools

ead603b1139c5ddf2f6b963bda0a5b0b384fac67

[ "Apache-2.0" ]

8

2021-12-19T12:03:59.000Z

2022-03-15T12:03:51.000Z

src/gsc/utils.py

nguyen-ngoc-thach/git-search-command

ead603b1139c5ddf2f6b963bda0a5b0b384fac67

[ "Apache-2.0" ]

null

src/gsc/utils.py

nguyen-ngoc-thach/git-search-command

ead603b1139c5ddf2f6b963bda0a5b0b384fac67

[ "Apache-2.0" ]

null

import re def is_valid_environment_name(name: str): return re.match("^[A-Za-z0-9_-]*$", name)

16.666667

45

0.67

17

100

3.705882

0.823529

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0.023256

0.14

100

5

46

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1

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6

5cf7f080c5d2d781faa0a7ba7fdb5db5d208471b

3,982

py

Python

lane_detection_utils/lane_args_utils.py

syeda27/MonoRARP

71415d9fc71bc636ac1f5de1a90f033b4e519538

[ "MIT" ]

2

2020-07-22T07:05:01.000Z

2021-11-27T13:28:03.000Z

lane_detection_utils/lane_args_utils.py

syeda27/MonoRARP

71415d9fc71bc636ac1f5de1a90f033b4e519538

[ "MIT" ]

null

lane_detection_utils/lane_args_utils.py

syeda27/MonoRARP

71415d9fc71bc636ac1f5de1a90f033b4e519538

[ "MIT" ]

null

""" There are so many variables related to the lane detector, that I think it makes sense to create a set of classes for them... """ import numpy as np class scan_region_output_args: def __init__(self): #Initializing vectors to be used for collection of the lines inside the region self.rx1 = np.zeros(100) self.rx2 = np.zeros(100) self.ry1 = np.zeros(100) self.ry2 = np.zeros(100) #Initializing vector for angle collection self.angles = np.zeros(100) self.count_angles_per_region = 0 def print(self): print( self.rx1, self.rx2, self.ry1, self.angles, self.count_angles_per_region ) def initialize_lane_detector_members(lane_detector_object): lane_detector_object.mux_lane_vec_previous = np.zeros(40) lane_detector_object.muy_lane_vec_previous = np.zeros(40) lane_detector_object.base_ptx_lane_vec_previous = np.zeros(40) lane_detector_object.base_pty_lane_vec_previous = np.zeros(40) lane_detector_object.mux_lane_vec_aggregated = np.zeros(40) lane_detector_object.muy_lane_vec_aggregated = np.zeros(40) lane_detector_object.base_ptx_lane_vec_aggregated = np.zeros(40) lane_detector_object.base_pty_lane_vec_aggregated = np.zeros(40) lane_detector_object.count_lanes_average_vec = 0 lane_detector_object.mux_lane_vec_average = np.zeros(4000) lane_detector_object.muy_lane_vec_average = np.zeros(4000) lane_detector_object.base_ptx_lane_vec_average = np.zeros(4000) lane_detector_object.base_pty_lane_vec_average = np.zeros(4000) lane_detector_object.count_lanes_average_vec2 = 0 lane_detector_object.mux_lane_vec_average2 = np.zeros(4000) lane_detector_object.muy_lane_vec_average2 = np.zeros(4000) lane_detector_object.base_ptx_lane_vec_average2 = np.zeros(4000) lane_detector_object.base_pty_lane_vec_average2 = np.zeros(4000) lane_detector_object.count_lane_group1 = 0 lane_detector_object.count_lane_group2 = 0 lane_detector_object.white_mark_hit = 0 lane_detector_object.count_road_nomark = 0 lane_detector_object.capture_frameindex_for_speed = 0 lane_detector_object.frameindex_for_speed_previous = 0 lane_detector_object.frameindex_for_speed = 0 lane_detector_object.count_scanned_lines_reverse_for_speed_previous = 0 lane_detector_object.count_scanned_lines_reverse_for_speed = 0 lane_detector_object.white_mark_hit_1 = 0 lane_detector_object.count_road_nomark_1 = 0 lane_detector_object.capture_frameindex_for_speed_1 = 0 lane_detector_object.frameindex_for_speed_previous_1 = 0 lane_detector_object.frameindex_for_speed_1 = 0 lane_detector_object.count_scanned_lines_reverse_for_speed_previous_1 = 0 lane_detector_object.count_scanned_lines_reverse_for_speed_1 = 0 lane_detector_object.base_ptx_lane_vec_final1 = 0 lane_detector_object.base_pty_lane_vec_final1 = 0 lane_detector_object.mux_lane_vec_final1 = 0 lane_detector_object.muy_lane_vec_final1 = 0 lane_detector_object.base_ptx_lane_vec_final2 = 0 lane_detector_object.base_pty_lane_vec_final2 = 0 lane_detector_object.mux_lane_vec_final2 = 0 lane_detector_object.muy_lane_vec_final2 = 0 lane_detector_object.mux_lane_vec_final1_previous = 0 lane_detector_object.muy_lane_vec_final1_previous = 0 lane_detector_object.base_ptx_lane_vec_final1_previous = 0 lane_detector_object.base_pty_lane_vec_final1_previous = 0 lane_detector_object.mux_lane_vec_final2_previous = 0 lane_detector_object.muy_lane_vec_final2_previous = 0 lane_detector_object.base_ptx_lane_vec_final2_previous = 0 lane_detector_object.base_pty_lane_vec_final2_previous = 0 lane_detector_object.x1_lane_group1 = 0 lane_detector_object.x1_lane_group2 = 0 lane_detector_object.initial_frame_was_processed_flag = 0 lane_detector_object.first_reading_available_flag = 0

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null

1

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null

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6

cf1838dd66d05579fc3ee4e65a14791d302ec69e

24,059

py

Python

kgcnn/layers/conv/attention.py

the16thpythonist/gcnn_keras

27d794095b684333d93149c825d84b85df8c30ff

[ "MIT" ]

47

2021-03-10T10:15:42.000Z

2022-03-14T00:53:40.000Z

kgcnn/layers/conv/attention.py

the16thpythonist/gcnn_keras

27d794095b684333d93149c825d84b85df8c30ff

[ "MIT" ]

36

2021-05-06T15:06:51.000Z

2022-03-02T13:06:16.000Z

kgcnn/layers/conv/attention.py

the16thpythonist/gcnn_keras

27d794095b684333d93149c825d84b85df8c30ff

[ "MIT" ]

11

2021-04-05T02:14:27.000Z

2022-03-02T03:25:52.000Z

import tensorflow as tf # import tensorflow.keras as ks from kgcnn.layers.base import GraphBaseLayer from kgcnn.layers.gather import GatherNodesIngoing, GatherNodesOutgoing, GatherState from kgcnn.layers.modules import DenseEmbedding, ActivationEmbedding, LazyConcatenate from kgcnn.layers.pooling import PoolingNodes from kgcnn.layers.pooling import PoolingNodesAttention, PoolingLocalEdgesAttention @tf.keras.utils.register_keras_serializable(package='kgcnn', name='AttentionHeadGAT') class AttentionHeadGAT(GraphBaseLayer): r"""Computes the attention head according to `GAT <https://arxiv.org/abs/1710.10903>`_ . The attention coefficients are computed by :math:`a_{ij} = \sigma(a^T W n_i || W n_j)`, optionally by :math:`a_{ij} = \sigma( W n_i || W n_j || e_{ij})` with edges :math:`e_{ij}`. The attention is obtained by :math:`\alpha_{ij} = \text{softmax}_j (a_{ij})`. And the messages are pooled by :math:`m_i = \sum_j \alpha_{ij} W n_j`. If the graph has no self-loops, they must be added beforehand or use external skip connections. And optionally passed through an activation :math:`h_i = \sigma(\sum_j \alpha_{ij} W n_j)`. An edge is defined by index tuple :math:`(i, j)` with the direction of the connection from :math:`j` to :math:`i`. Args: units (int): Units for the linear trafo of node features before attention. use_edge_features (bool): Append edge features to attention computation. Default is False. use_final_activation (bool): Whether to apply the final activation for the output. has_self_loops (bool): If the graph has self-loops. Not used here. Default is True. activation (str): Activation. Default is {"class_name": "kgcnn>leaky_relu", "config": {"alpha": 0.2}}, use_bias (bool): Use bias. Default is True. kernel_regularizer: Kernel regularization. Default is None. bias_regularizer: Bias regularization. Default is None. activity_regularizer: Activity regularization. Default is None. kernel_constraint: Kernel constrains. Default is None. bias_constraint: Bias constrains. Default is None. kernel_initializer: Initializer for kernels. Default is 'glorot_uniform'. bias_initializer: Initializer for bias. Default is 'zeros'. """ def __init__(self, units, use_edge_features=False, use_final_activation=True, has_self_loops=True, activation='kgcnn>leaky_relu', use_bias=True, kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, kernel_initializer='glorot_uniform', bias_initializer='zeros', **kwargs): """Initialize layer.""" super(AttentionHeadGAT, self).__init__(**kwargs) self.use_edge_features = use_edge_features self.use_final_activation = use_final_activation self.has_self_loops = has_self_loops self.units = int(units) self.use_bias = use_bias kernel_args = {"kernel_regularizer": kernel_regularizer, "activity_regularizer": activity_regularizer, "bias_regularizer": bias_regularizer, "kernel_constraint": kernel_constraint, "bias_constraint": bias_constraint, "kernel_initializer": kernel_initializer, "bias_initializer": bias_initializer} self.lay_linear_trafo = DenseEmbedding(units, activation="linear", use_bias=use_bias, **kernel_args) self.lay_alpha = DenseEmbedding(1, activation=activation, use_bias=False, **kernel_args) self.lay_gather_in = GatherNodesIngoing() self.lay_gather_out = GatherNodesOutgoing() self.lay_concat = LazyConcatenate(axis=-1) self.lay_pool_attention = PoolingLocalEdgesAttention() if self.use_final_activation: self.lay_final_activ = ActivationEmbedding(activation=activation) def build(self, input_shape): """Build layer.""" super(AttentionHeadGAT, self).build(input_shape) def call(self, inputs, **kwargs): """Forward pass. Args: inputs (list): of [node, edges, edge_indices] - nodes (tf.RaggedTensor): Node embeddings of shape (batch, [N], F) - edges (tf.RaggedTensor): Edge or message embeddings of shape (batch, [M], F) - edge_indices (tf.RaggedTensor): Edge indices referring to nodes of shape (batch, [M], 2) Returns: tf.RaggedTensor: Embedding tensor of pooled edge attentions for each node. """ node, edge, edge_index = inputs w_n = self.lay_linear_trafo(node, **kwargs) wn_in = self.lay_gather_in([w_n, edge_index], **kwargs) wn_out = self.lay_gather_out([w_n, edge_index], **kwargs) if self.use_edge_features: e_ij = self.lay_concat([wn_in, wn_out, edge], **kwargs) else: e_ij = self.lay_concat([wn_in, wn_out], **kwargs) a_ij = self.lay_alpha(e_ij, **kwargs) # Should be dimension (batch*None,1) h_i = self.lay_pool_attention([node, wn_out, a_ij, edge_index], **kwargs) if self.use_final_activation: h_i = self.lay_final_activ(h_i, **kwargs) return h_i def get_config(self): """Update layer config.""" config = super(AttentionHeadGAT, self).get_config() config.update({"use_edge_features": self.use_edge_features, "use_bias": self.use_bias, "units": self.units, "has_self_loops": self.has_self_loops, "use_final_activation": self.use_final_activation}) conf_sub = self.lay_alpha.get_config() for x in ["kernel_regularizer", "activity_regularizer", "bias_regularizer", "kernel_constraint", "bias_constraint", "kernel_initializer", "bias_initializer", "activation"]: config.update({x: conf_sub[x]}) return config @tf.keras.utils.register_keras_serializable(package='kgcnn', name='AttentionHeadGATV2') class AttentionHeadGATV2(GraphBaseLayer): r"""Computes the modified attention head according to `GATv2 <https://arxiv.org/pdf/2105.14491.pdf>`_ . The attention coefficients are computed by :math:`a_{ij} = a^T \sigma( W [n_i || n_j] )`, optionally by :math:`a_{ij} = a^T \sigma( W [n_i || n_j || e_{ij}] )` with edges :math:`e_{ij}`. The attention is obtained by :math:`\alpha_{ij} = \text{softmax}_j (a_{ij})`. And the messages are pooled by :math:`m_i = \sum_j \alpha_{ij} e_{ij}`. If the graph has no self-loops, they must be added beforehand or use external skip connections. And optionally passed through an activation :math:`h_i = \sigma(\sum_j \alpha_{ij} e_{ij})`. An edge is defined by index tuple :math:`(i, j)` with the direction of the connection from :math:`j` to :math:`i`. Args: units (int): Units for the linear trafo of node features before attention. use_edge_features (bool): Append edge features to attention computation. Default is False. use_final_activation (bool): Whether to apply the final activation for the output. has_self_loops (bool): If the graph has self-loops. Not used here. Default is True. activation (str): Activation. Default is {"class_name": "kgcnn>leaky_relu", "config": {"alpha": 0.2}}, use_bias (bool): Use bias. Default is True. kernel_regularizer: Kernel regularization. Default is None. bias_regularizer: Bias regularization. Default is None. activity_regularizer: Activity regularization. Default is None. kernel_constraint: Kernel constrains. Default is None. bias_constraint: Bias constrains. Default is None. kernel_initializer: Initializer for kernels. Default is 'glorot_uniform'. bias_initializer: Initializer for bias. Default is 'zeros'. """ def __init__(self, units, use_edge_features=False, use_final_activation=True, has_self_loops=True, activation='kgcnn>leaky_relu', use_bias=True, kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, kernel_initializer='glorot_uniform', bias_initializer='zeros', **kwargs): """Initialize layer.""" super(AttentionHeadGATV2, self).__init__(**kwargs) self.use_edge_features = use_edge_features self.use_final_activation = use_final_activation self.has_self_loops = has_self_loops self.units = int(units) self.use_bias = use_bias kernel_args = {"kernel_regularizer": kernel_regularizer, "activity_regularizer": activity_regularizer, "bias_regularizer": bias_regularizer, "kernel_constraint": kernel_constraint, "bias_constraint": bias_constraint, "kernel_initializer": kernel_initializer, "bias_initializer": bias_initializer} self.lay_linear_trafo = DenseEmbedding(units, activation="linear", use_bias=use_bias, **kernel_args) self.lay_alpha_activation = DenseEmbedding(units, activation=activation, use_bias=use_bias, **kernel_args) self.lay_alpha = DenseEmbedding(1, activation="linear", use_bias=False, **kernel_args) self.lay_gather_in = GatherNodesIngoing() self.lay_gather_out = GatherNodesOutgoing() self.lay_concat = LazyConcatenate(axis=-1) self.lay_pool_attention = PoolingLocalEdgesAttention() if self.use_final_activation: self.lay_final_activ = ActivationEmbedding(activation=activation) def build(self, input_shape): """Build layer.""" super(AttentionHeadGATV2, self).build(input_shape) def call(self, inputs, **kwargs): """Forward pass. Args: inputs (list): of [node, edges, edge_indices] - nodes (tf.RaggedTensor): Node embeddings of shape (batch, [N], F) - edges (tf.RaggedTensor): Edge or message embeddings of shape (batch, [M], F) - edge_indices (tf.RaggedTensor): Edge indices referring to nodes of shape (batch, [M], 2) Returns: tf.RaggedTensor: Embedding tensor of pooled edge attentions for each node. """ node, edge, edge_index = inputs w_n = self.lay_linear_trafo(node, **kwargs) n_in = self.lay_gather_in([node, edge_index], **kwargs) n_out = self.lay_gather_out([node, edge_index], **kwargs) wn_out = self.lay_gather_out([w_n, edge_index], **kwargs) if self.use_edge_features: e_ij = self.lay_concat([n_in, n_out, edge], **kwargs) else: e_ij = self.lay_concat([n_in, n_out], **kwargs) a_ij = self.lay_alpha_activation(e_ij, **kwargs) a_ij = self.lay_alpha(a_ij, **kwargs) h_i = self.lay_pool_attention([node, wn_out, a_ij, edge_index], **kwargs) if self.use_final_activation: h_i = self.lay_final_activ(h_i, **kwargs) return h_i def get_config(self): """Update layer config.""" config = super(AttentionHeadGATV2, self).get_config() config.update({"use_edge_features": self.use_edge_features, "use_bias": self.use_bias, "units": self.units, "has_self_loops": self.has_self_loops, "use_final_activation": self.use_final_activation}) conf_sub = self.lay_alpha_activation.get_config() for x in ["kernel_regularizer", "activity_regularizer", "bias_regularizer", "kernel_constraint", "bias_constraint", "kernel_initializer", "bias_initializer", "activation"]: config.update({x: conf_sub[x]}) return config @tf.keras.utils.register_keras_serializable(package='kgcnn', name='AttentiveHeadFP') class AttentiveHeadFP(GraphBaseLayer): r"""Computes the attention head for `Attentive FP <https://doi.org/10.1021/acs.jmedchem.9b00959>`_ model. The attention coefficients are computed by :math:`a_{ij} = \sigma_1( W_1 [h_i || h_j] )`. The initial representation :math:`h_i` and :math:`h_j` must be calculated beforehand. The attention is obtained by :math:`\alpha_{ij} = \text{softmax}_j (a_{ij})`. And finally pooled for context :math:`C_i = \sigma_2(\sum_j \alpha_{ij} W_2 h_j)`. An edge is defined by index tuple :math:`(i, j)` with the direction of the connection from :math:`j` to :math:`i`. Args: units (int): Units for the linear trafo of node features before attention. use_edge_features (bool): Append edge features to attention computation. Default is False. activation (str): Activation. Default is {"class_name": "kgcnn>leaky_relu", "config": {"alpha": 0.2}}. activation_context (str): Activation function for context. Default is "elu". use_bias (bool): Use bias. Default is True. kernel_regularizer: Kernel regularization. Default is None. bias_regularizer: Bias regularization. Default is None. activity_regularizer: Activity regularization. Default is None. kernel_constraint: Kernel constrains. Default is None. bias_constraint: Bias constrains. Default is None. kernel_initializer: Initializer for kernels. Default is 'glorot_uniform'. bias_initializer: Initializer for bias. Default is 'zeros'. """ def __init__(self, units, use_edge_features=False, activation='kgcnn>leaky_relu', activation_context="elu", use_bias=True, kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, kernel_initializer='glorot_uniform', bias_initializer='zeros', **kwargs): """Initialize layer.""" super(AttentiveHeadFP, self).__init__(**kwargs) self.use_edge_features = use_edge_features self.units = int(units) self.use_bias = use_bias kernel_args = {"kernel_regularizer": kernel_regularizer, "activity_regularizer": activity_regularizer, "bias_regularizer": bias_regularizer, "kernel_constraint": kernel_constraint, "bias_constraint": bias_constraint, "kernel_initializer": kernel_initializer, "bias_initializer": bias_initializer} self.lay_linear_trafo = DenseEmbedding(units, activation="linear", use_bias=use_bias, **kernel_args) self.lay_alpha_activation = DenseEmbedding(units, activation=activation, use_bias=use_bias, **kernel_args) self.lay_alpha = DenseEmbedding(1, activation="linear", use_bias=False, **kernel_args) self.lay_gather_in = GatherNodesIngoing() self.lay_gather_out = GatherNodesOutgoing() self.lay_concat = LazyConcatenate(axis=-1) self.lay_pool_attention = PoolingLocalEdgesAttention() self.lay_final_activ = ActivationEmbedding(activation=activation_context) if use_edge_features: self.lay_fc1 = DenseEmbedding(units, activation=activation, use_bias=use_bias, **kernel_args) self.lay_fc2 = DenseEmbedding(units, activation=activation, use_bias=use_bias, **kernel_args) self.lay_concat_edge = LazyConcatenate(axis=-1) def build(self, input_shape): """Build layer.""" super(AttentiveHeadFP, self).build(input_shape) def call(self, inputs, **kwargs): """Forward pass. Args: inputs (list): of [node, edges, edge_indices] - nodes (tf.RaggedTensor): Node embeddings of shape (batch, [N], F) - edges (tf.RaggedTensor): Edge or message embeddings of shape (batch, [M], F) - edge_indices (tf.RaggedTensor): Edge indices referring to nodes of shape (batch, [M], 2) Returns: tf.RaggedTensor: Hidden tensor of pooled edge attentions for each node. """ node, edge, edge_index = inputs if self.use_edge_features: n_in = self.lay_gather_in([node, edge_index], **kwargs) n_out = self.lay_gather_out([node, edge_index], **kwargs) n_in = self.lay_fc1(n_in, **kwargs) n_out = self.lay_concat_edge([n_out, edge], **kwargs) n_out = self.lay_fc2(n_out, **kwargs) else: n_in = self.lay_gather_in([node, edge_index], **kwargs) n_out = self.lay_gather_out([node, edge_index], **kwargs) wn_out = self.lay_linear_trafo(n_out, **kwargs) e_ij = self.lay_concat([n_in, n_out], **kwargs) e_ij = self.lay_alpha_activation(e_ij, **kwargs) # Maybe uses GAT original definition. # a_ij = e_ij a_ij = self.lay_alpha(e_ij, **kwargs) # Should be dimension (batch,None,1) not fully clear in original paper. n_i = self.lay_pool_attention([node, wn_out, a_ij, edge_index], **kwargs) out = self.lay_final_activ(n_i, **kwargs) return out def get_config(self): """Update layer config.""" config = super(AttentiveHeadFP, self).get_config() config.update({"use_edge_features": self.use_edge_features, "use_bias": self.use_bias, "units": self.units}) conf_sub = self.lay_alpha_activation.get_config() for x in ["kernel_regularizer", "activity_regularizer", "bias_regularizer", "kernel_constraint", "bias_constraint", "kernel_initializer", "bias_initializer", "activation"]: config.update({x: conf_sub[x]}) conf_context = self.lay_final_activ.get_config() config.update({"activation_context": conf_context["activation"]}) return config @tf.keras.utils.register_keras_serializable(package='kgcnn', name='PoolingNodesAttentive') class PoolingNodesAttentive(GraphBaseLayer): r"""Computes the attentive pooling for node embeddings for `Attentive FP <https://doi.org/10.1021/acs.jmedchem.9b00959>`_ model. Args: units (int): Units for the linear trafo of node features before attention. pooling_method(str): Initial pooling before iteration. Default is "sum". depth (int): Number of iterations for graph embedding. Default is 3. activation (str): Activation. Default is {"class_name": "kgcnn>leaky_relu", "config": {"alpha": 0.2}}. activation_context (str): Activation function for context. Default is "elu". use_bias (bool): Use bias. Default is True. kernel_regularizer: Kernel regularization. Default is None. bias_regularizer: Bias regularization. Default is None. activity_regularizer: Activity regularization. Default is None. kernel_constraint: Kernel constrains. Default is None. bias_constraint: Bias constrains. Default is None. kernel_initializer: Initializer for kernels. Default is 'glorot_uniform'. bias_initializer: Initializer for bias. Default is 'zeros'. """ def __init__(self, units, depth=3, pooling_method="sum", activation='kgcnn>leaky_relu', activation_context="elu", use_bias=True, kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, kernel_initializer='glorot_uniform', bias_initializer='zeros', recurrent_activation='sigmoid', recurrent_initializer='orthogonal', recurrent_regularizer=None, recurrent_constraint=None, dropout=0.0, recurrent_dropout=0.0, reset_after=True, **kwargs): """Initialize layer.""" super(PoolingNodesAttentive, self).__init__(**kwargs) self.pooling_method = pooling_method self.depth = depth self.units = int(units) kernel_args = {"use_bias": use_bias, "kernel_regularizer": kernel_regularizer, "activity_regularizer": activity_regularizer, "bias_regularizer": bias_regularizer, "kernel_constraint": kernel_constraint, "bias_constraint": bias_constraint, "kernel_initializer": kernel_initializer, "bias_initializer": bias_initializer} gru_args = {"recurrent_activation": recurrent_activation, "use_bias": use_bias, "kernel_initializer": kernel_initializer, "recurrent_initializer": recurrent_initializer, "bias_initializer": bias_initializer, "kernel_regularizer": kernel_regularizer, "recurrent_regularizer": recurrent_regularizer, "bias_regularizer": bias_regularizer, "kernel_constraint": kernel_constraint, "recurrent_constraint": recurrent_constraint, "bias_constraint": bias_constraint, "dropout": dropout, "recurrent_dropout": recurrent_dropout, "reset_after": reset_after} self.lay_linear_trafo = DenseEmbedding(units, activation="linear", **kernel_args) self.lay_alpha = DenseEmbedding(1, activation=activation, **kernel_args) self.lay_gather_s = GatherState() self.lay_concat = LazyConcatenate(axis=-1) self.lay_pool_start = PoolingNodes(pooling_method=self.pooling_method) self.lay_pool_attention = PoolingNodesAttention() self.lay_final_activ = ActivationEmbedding(activation=activation_context) self.lay_gru = tf.keras.layers.GRUCell(units=units, activation="tanh", **gru_args) def build(self, input_shape): """Build layer.""" super(PoolingNodesAttentive, self).build(input_shape) def call(self, inputs, **kwargs): """Forward pass. Args: inputs: nodes - nodes (tf.RaggedTensor): Node features of shape (batch, [N], F) Returns: tf.Tensor: Hidden tensor of pooled node attentions of shape (batch, F). """ node = inputs h = self.lay_pool_start(node, **kwargs) wn = self.lay_linear_trafo(node, **kwargs) for _ in range(self.depth): hv = self.lay_gather_s([h, node], **kwargs) ev = self.lay_concat([hv, node], **kwargs) av = self.lay_alpha(ev, **kwargs) cont = self.lay_pool_attention([wn, av], **kwargs) cont = self.lay_final_activ(cont, **kwargs) h, _ = self.lay_gru(cont, h, **kwargs) out = h return out def get_config(self): """Update layer config.""" config = super(PoolingNodesAttentive, self).get_config() config.update({"units": self.units, "depth": self.depth, "pooling_method": self.pooling_method}) conf_sub = self.lay_alpha.get_config() for x in ["kernel_regularizer", "activity_regularizer", "bias_regularizer", "kernel_constraint", "bias_constraint", "kernel_initializer", "bias_initializer", "activation", "use_bias"]: config.update({x: conf_sub[x]}) conf_context = self.lay_final_activ.get_config() config.update({"activation_context": conf_context["activation"]}) conf_gru = self.lay_gru.get_config() for x in ["recurrent_activation", "recurrent_initializer", "recurrent_regularizer", "recurrent_constraint", "dropout", "recurrent_dropout", "reset_after"]: config.update({x: conf_gru[x]}) return config

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null

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6

cf1cf7524a2c06bc22de20e8dfef11835b0184e6

68

py

Python

app/handlers/private/__init__.py

s-klimov/meal_bo

f74898c179a8551c8ec8df147aabc659496c610e

[ "MIT" ]

1

2022-02-20T06:16:01.000Z

app/handlers/private/__init__.py

s-klimov/meal_bot

f74898c179a8551c8ec8df147aabc659496c610e

[ "MIT" ]

null

app/handlers/private/__init__.py

s-klimov/meal_bot

f74898c179a8551c8ec8df147aabc659496c610e

[ "MIT" ]

null

from .start import * from .mealtime import * from .barcode import *

17

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6

d859b67e8cfb846781768f9c494950d50174353a

184

py

Python

src/onevision/cv/imgproc/shape/__init__.py

phlong3105/onevision

90552b64df7213e7fbe23c80ffd8a89583289433

[ "MIT" ]

2

2022-03-28T09:46:38.000Z

2022-03-28T14:12:32.000Z

src/onevision/cv/imgproc/shape/__init__.py

phlong3105/onevision

90552b64df7213e7fbe23c80ffd8a89583289433

[ "MIT" ]

null

src/onevision/cv/imgproc/shape/__init__.py

phlong3105/onevision

90552b64df7213e7fbe23c80ffd8a89583289433

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ """ from __future__ import annotations from .anchor import * from .box import * from .box_convert import * from .distance import *

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6

d872bbaefeeb88ae8d049c5721e279ae29a15333

41

py

Python

droput_authentication/droput_auth/controller/__init__.py

hosein-yousefii/DROPUT

99a714f03a92b14228a3691ca6568ece0f0ea48c

[ "Apache-2.0" ]

2

2022-03-17T08:08:07.000Z

2022-03-17T21:38:54.000Z

droput_authentication/droput_auth/controller/__init__.py

hosein-yousefii/DROPUT

99a714f03a92b14228a3691ca6568ece0f0ea48c

[ "Apache-2.0" ]

null

droput_authentication/droput_auth/controller/__init__.py

hosein-yousefii/DROPUT

99a714f03a92b14228a3691ca6568ece0f0ea48c

[ "Apache-2.0" ]

null

from droput_auth.controller import apiv1

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6

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py

Python

chupacabra_server/app/tests/tic_tac_toe/test_tic_tac_toe.py

lopez86/chupacabra

4f40eb770b57bfc01b68013b24c523d7056e4f5b

[ "MIT" ]

null

chupacabra_server/app/tests/tic_tac_toe/test_tic_tac_toe.py

lopez86/chupacabra

4f40eb770b57bfc01b68013b24c523d7056e4f5b

[ "MIT" ]

null

chupacabra_server/app/tests/tic_tac_toe/test_tic_tac_toe.py

lopez86/chupacabra

4f40eb770b57bfc01b68013b24c523d7056e4f5b

[ "MIT" ]

null

import unittest import arrow from chupacabra_client.protos.game_structs_pb2 import ( Coordinate, Coordinates, GamePieceMove, Move, PlayerInfo ) import numpy as np from tic_tac_toe import tic_tac_toe_game class TestTicTacToeGame(unittest.TestCase): def test__init(self): with self.assertRaises(AssertionError): tic_tac_toe_game.TicTacToeInternalState('', [], [], 0, 0) with self.assertRaises(AssertionError): tic_tac_toe_game.TicTacToeInternalState( '1', [], [PlayerInfo(), PlayerInfo()], 0, 0 ) with self.assertRaises(AssertionError): tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [], 0, 0 ) with self.assertRaises(AssertionError): tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], 0, 0, board=[1, 2, 3] ) with self.assertRaises(AssertionError): tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], 0, 0, board=np.zeros([3, 3], dtype=np.float32) ) with self.assertRaises(AssertionError): tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], 0, 0, board=np.zeros([2, 2], dtype=np.int8) ) with self.assertRaises(AssertionError): tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], 0, 0, mode='Illegal mode' ) with self.assertRaises(AssertionError): tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], 0, 0, turn=2 ) state = tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], 0, 0, turn=None, winner=1, board=np.zeros([3, 3], dtype=np.int8) ) self.assertEqual(1, state.winner) self.assertEqual(0, state.turn) def test_serialize_state(self): state = tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], 5, 6, ) serialized = tic_tac_toe_game.serialize_state(state) deserialized = tic_tac_toe_game.deserialize_state(serialized) self.assertEqual('1', deserialized.id) self.assertEqual(['1', '2'], deserialized.player_ids) self.assertEqual(6, deserialized.game_expiration_time) self.assertEqual(5, deserialized.turn_expiration_time) def test__validate_game_state(self): expiration_time = arrow.utcnow().timestamp + 3600 players = [ PlayerInfo(username='player1'), PlayerInfo(username='player2') ] player_ids = ['1', '2'] state = tic_tac_toe_game.TicTacToeInternalState( 'a', player_ids, players, expiration_time, expiration_time, turn=0) validated, message = tic_tac_toe_game._validate_game_state(state, '1') self.assertTrue(validated) self.assertEqual('', message) state = tic_tac_toe_game.TicTacToeInternalState( 'a', player_ids, players, expiration_time, expiration_time, turn=0) validated, message = tic_tac_toe_game._validate_game_state(state, '2') self.assertFalse(validated) self.assertEqual(tic_tac_toe_game.CANNOT_MOVE_MESSAGE, message) state = tic_tac_toe_game.TicTacToeInternalState( 'a', player_ids, players, expiration_time, expiration_time, turn=0, mode=tic_tac_toe_game.FINISHED_MODE ) validated, message = tic_tac_toe_game._validate_game_state(state, '2') self.assertFalse(validated) self.assertEqual(tic_tac_toe_game.NOT_IN_PLAY_MODE_MESSAGE, message) def test__validate_and_extract_coordinates(self): # A good move move = Move( piece_moves=[ GamePieceMove( locations=[ Coordinates( values=[ Coordinate(name='x', value=0), Coordinate(name='y', value=1) ] ) ] ) ] ) coordinates, message = tic_tac_toe_game._validate_and_extract_coordinates(move) expected_coordinates = { 'x': 0, 'y': 1 } self.assertEqual(expected_coordinates, coordinates) self.assertEqual('', message) move = Move( piece_moves=[ GamePieceMove( locations=[ Coordinates( values=[ Coordinate(name='x', value=5), Coordinate(name='y', value=1) ] ) ] ) ] ) coordinates, message = tic_tac_toe_game._validate_and_extract_coordinates(move) self.assertEqual({}, coordinates) self.assertEqual(tic_tac_toe_game.ILLEGAL_MOVE_MESSAGE, message) move = Move( piece_moves=[ GamePieceMove( locations=[ Coordinates( values=[ Coordinate(name='x', value=0), ] ) ] ) ] ) coordinates, message = tic_tac_toe_game._validate_and_extract_coordinates(move) self.assertEqual({}, coordinates) self.assertEqual(tic_tac_toe_game.ILLEGAL_MOVE_MESSAGE, message) move = Move( piece_moves=[ GamePieceMove( locations=[ Coordinates( values=[ Coordinate(name='x', value=1), Coordinate(name='y', value=1), Coordinate(name='z', value=0) ] ) ] ) ] ) coordinates, message = tic_tac_toe_game._validate_and_extract_coordinates(move) self.assertEqual({}, coordinates) self.assertEqual(tic_tac_toe_game.ILLEGAL_MOVE_MESSAGE, message) move = Move( piece_moves=[ GamePieceMove( locations=[ Coordinates( values=[ Coordinate(name='x', value=5), Coordinate(name='z', value=1) ] ) ] ) ] ) coordinates, message = tic_tac_toe_game._validate_and_extract_coordinates(move) self.assertEqual({}, coordinates) self.assertEqual(tic_tac_toe_game.ILLEGAL_MOVE_MESSAGE, message) move = Move( piece_moves=[ GamePieceMove( locations=[ Coordinates( values=[ Coordinate(name='x', value=0), Coordinate(name='y', value=1) ] ), ] * 2 ) ] ) coordinates, message = tic_tac_toe_game._validate_and_extract_coordinates(move) self.assertEqual({}, coordinates) self.assertEqual(tic_tac_toe_game.ILLEGAL_MOVE_MESSAGE, message) move = Move( piece_moves=[ GamePieceMove( locations=[ Coordinates( values=[ Coordinate(name='x', value=0), Coordinate(name='y', value=1) ] ), ] ) ] * 2 ) coordinates, message = tic_tac_toe_game._validate_and_extract_coordinates(move) self.assertEqual({}, coordinates) self.assertEqual(tic_tac_toe_game.ILLEGAL_MOVE_MESSAGE, message) def test__check_for_game_over(self): board = np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0]]) game_over, winner = tic_tac_toe_game._check_for_game_over(board) self.assertEqual(game_over, False) self.assertEqual(winner, -1) board = np.array([[1, -1, 1], [-1, 0, 1], [0, 0, -1]]) game_over, winner = tic_tac_toe_game._check_for_game_over(board) self.assertEqual(game_over, False) self.assertEqual(winner, -1) # Games with winners (may not necessarily be actual valid states) board = np.array([[1, 1, 1], [0, -1, 0], [-1, 0, -1]]) game_over, winner = tic_tac_toe_game._check_for_game_over(board) self.assertEqual(game_over, True) self.assertEqual(winner, 0) board = np.array([[0, 1, -1], [0, 1, 0], [-1, 1, 0]]) game_over, winner = tic_tac_toe_game._check_for_game_over(board) self.assertEqual(game_over, True) self.assertEqual(winner, 0) board = np.array([[0, -1, 0], [0, -1, 1], [1, -1, 0]]) game_over, winner = tic_tac_toe_game._check_for_game_over(board) self.assertEqual(game_over, True) self.assertEqual(winner, 1) board = np.array([[-1, 0, 1], [0, 1, 0], [1, -1, 0]]) game_over, winner = tic_tac_toe_game._check_for_game_over(board) self.assertEqual(game_over, True) self.assertEqual(winner, 0) # A tie board = np.array([[1, -1, 1], [1, -1, 1], [-1, 1, -1]]) game_over, winner = tic_tac_toe_game._check_for_game_over(board) self.assertEqual(game_over, True) self.assertEqual(winner, -1) def test_make_move(self): good_time = arrow.utcnow().timestamp + 3600 state = tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], 0, 0, turn=0 ) move = Move( piece_moves=[ GamePieceMove( locations=[ Coordinates( values=[ Coordinate(name='x', value=0), Coordinate(name='y', value=0) ] ), ] ) ] ) result = tic_tac_toe_game.make_move( state, move, '3' ) self.assertEqual((tic_tac_toe_game.CANNOT_MOVE_MESSAGE, None), result) result = tic_tac_toe_game.make_move( state, move, '1' ) self.assertEqual(np.sum(state.board), np.sum(result[1].board)) self.assertEqual(tic_tac_toe_game.FINISHED_MODE, result[1].mode) # Good turn time, bad game time state = tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], good_time, 0, turn=0 ) result = tic_tac_toe_game.make_move( state, move, '1' ) self.assertEqual(np.sum(state.board), np.sum(result[1].board)) self.assertEqual(tic_tac_toe_game.FINISHED_MODE, result[1].mode) state = tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], good_time, good_time, turn=0 ) message, new_state = tic_tac_toe_game.make_move( state, move, '1' ) self.assertEqual( 0, np.sum( np.array( [[1, 0, 0], [0, 0, 0], [0, 0, 0]], dtype=np.int8 ) - new_state.board ) ) bad_move = Move( piece_moves=[ GamePieceMove( locations=[ Coordinates( values=[ Coordinate(name='x', value=0), Coordinate(name='z', value=0) ] ), ] ) ] ) _, new_state = tic_tac_toe_game.make_move( state, bad_move, '1' ) self.assertIsNone(new_state) state = tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], good_time, good_time, turn=0, board=np.array( [[1, 0, 0], [0, 0, 0], [0, 0, 0]], dtype=np.int8 ) ) _, new_state = tic_tac_toe_game.make_move( state, move, '1' ) self.assertIsNone(new_state) state = tic_tac_toe_game.TicTacToeInternalState( '1', ['1', '2'], [PlayerInfo(), PlayerInfo()], good_time, good_time, turn=0, board=np.array( [[0, 1, 1], [0, 0, 0], [0, 0, 0]], dtype=np.int8 ) ) _, new_state = tic_tac_toe_game.make_move( state, move, '1' ) self.assertEqual(tic_tac_toe_game.FINISHED_MODE, new_state.mode) self.assertEqual(0, new_state.winner)

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1

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0

0.029197

0

null

0

1

0

null

0

6

d8ee37f6824e7aeda4d362ee6e6415e7389842a6

158

py

Python

misago/users/serializers/__init__.py

HenryChenV/iJiangNan

68f156d264014939f0302222e16e3125119dd3e3

[ "MIT" ]

1

2017-07-25T03:04:36.000Z

misago/users/serializers/__init__.py

HenryChenV/iJiangNan

68f156d264014939f0302222e16e3125119dd3e3

[ "MIT" ]

null

misago/users/serializers/__init__.py

HenryChenV/iJiangNan

68f156d264014939f0302222e16e3125119dd3e3

[ "MIT" ]

null

from .ban import * from .moderation import * from .options import * from .rank import * from .user import * from .auth import * from .usernamechange import *

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158

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1

0

1

0

1

0

6

2b3ab9ed13c04ed37dd0536218b0e4f13cb3cea3

544

py

Python

utils.py

taufikxu/Tools

ca693967197cf64444c39064b5db9fa5911676e0

[ "MIT" ]

2

2020-07-07T01:39:42.000Z

2021-09-06T03:46:05.000Z

utils.py

taufikxu/Tools

ca693967197cf64444c39064b5db9fa5911676e0

[ "MIT" ]

null

utils.py

taufikxu/Tools

ca693967197cf64444c39064b5db9fa5911676e0

[ "MIT" ]

null

import sys from tqdm import tqdm from tqdm import trange def xrange(iters, prefix=None, Epoch=None, **kwargs): if Epoch is not None and prefix is None: prefix = "Epoch " + str(Epoch) return trange(int(iters), file=sys.stdout, leave=False, dynamic_ncols=True, desc=prefix, **kwargs) def range_iterator(iters, prefix=None, Epoch=None, **kwargs): if Epoch is not None and prefix is None: prefix = "Epoch " + str(Epoch) return tqdm(iters, file=sys.stdout, leave=False, dynamic_ncols=True, desc=prefix, **kwargs)

34

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544

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36.266667

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0

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0

null

0

1

0

6

2b5de1b4dcab807ff21112a0ea3a32773b16d82c

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py

Python

imagespawner/__init__.py

accre/jupyter-imagespawner

ecc18455b2475b095f649e4a3cd057785c3a04da

[ "BSD-3-Clause" ]

null

imagespawner/__init__.py

accre/jupyter-imagespawner

ecc18455b2475b095f649e4a3cd057785c3a04da

[ "BSD-3-Clause" ]

null

imagespawner/__init__.py

accre/jupyter-imagespawner

ecc18455b2475b095f649e4a3cd057785c3a04da

[ "BSD-3-Clause" ]

null

from .imagespawner import MarathonImageChooserSpawner

27

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54

12.25

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0.98

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1

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1

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1

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1

0

null

0

1

0

1

0

1

0

6

2b66f458102e8fefe058c40d80dc33c21875168c

86

py

Python

src/data/__init__.py

salosyatov/football_stat

a8cb68cd648f65f8dbb383b8795cbd8b0dbac5d3

[ "FTL" ]

null

src/data/__init__.py

salosyatov/football_stat

a8cb68cd648f65f8dbb383b8795cbd8b0dbac5d3

[ "FTL" ]

null

src/data/__init__.py

salosyatov/football_stat

a8cb68cd648f65f8dbb383b8795cbd8b0dbac5d3

[ "FTL" ]

null

from .cache_images import cache_images from .make_dataset import split_train_val_data

28.666667

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0.883721

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86

5

0.714286

0.314286

0

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43

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0

null

0

1

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1

0

1

0

6

99431f67fba8398ed31ef7a279c692ddc14e1c3a

18

py

Python

models/__init__.py

x-zho14/VisionPermutator

e825c8aecb277cad71e9b23a58b0d565b3ac78eb

[ "MIT" ]

142

2021-06-23T15:11:11.000Z

2022-03-27T13:26:49.000Z

models/__init__.py

x-zho14/VisionPermutator

e825c8aecb277cad71e9b23a58b0d565b3ac78eb

[ "MIT" ]

7

2021-07-20T03:32:59.000Z

2021-11-18T07:40:46.000Z

models/__init__.py

x-zho14/VisionPermutator

e825c8aecb277cad71e9b23a58b0d565b3ac78eb

[ "MIT" ]

20

2021-06-25T03:09:02.000Z

2022-02-14T06:51:26.000Z

from .vip import *

18

0.722222

3

18

4.333333

1

0

0.166667

18

1

18

0.866667

0

1

0

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1

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null

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1

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1

0

1

0

6

996355fa8cf9215c4f2b68e4cd7bcb6beddc27ad

139

py

Python

library/lib_study/145_frameworks_shlex.py

gottaegbert/penter

8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d

[ "MIT" ]

13

2020-01-04T07:37:38.000Z

2021-08-31T05:19:58.000Z

library/lib_study/145_frameworks_shlex.py

gottaegbert/penter

8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d

[ "MIT" ]

3

2020-06-05T22:42:53.000Z

2020-08-24T07:18:54.000Z

library/lib_study/145_frameworks_shlex.py

gottaegbert/penter

8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d

[ "MIT" ]

9

2020-10-19T04:53:06.000Z

2021-08-31T05:20:01.000Z

import shlex # 3.8 print(shlex.join(['echo', '-n', 'Multiple words'])) import shlex, subprocess subprocess.Popen(shlex.split('ls -l /'))

19.857143

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139

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0.75

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0.115108

139

6

58

23.166667

0.747967

0.395683

0

0.08642

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null

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1

0

1

0

1

0

6

9990944ee57b4da1272372e46210ae6fc3dac7d4

42

py

Python

models/__init__.py

Lanping-Tech/Enhanced-VIT

90a0516f3b6f926d758f1f72b09ab20b60f722ea

[ "Apache-2.0" ]

null

models/__init__.py

Lanping-Tech/Enhanced-VIT

90a0516f3b6f926d758f1f72b09ab20b60f722ea

[ "Apache-2.0" ]

null

models/__init__.py

Lanping-Tech/Enhanced-VIT

90a0516f3b6f926d758f1f72b09ab20b60f722ea

[ "Apache-2.0" ]

null

from .vit import ViT from .resvit import *

21

0.761905

7

42

4.571429

0.571429

0

0.166667

42

2

21

0.914286

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

99935a5d4f968a4b441568350faddf9c099b7f5d

49

py

Python

ddf_utils/model/__init__.py

semio/ddf_utils

e10c4cb6dc7722415a5863579a552cc7b7e3668d

[ "MIT" ]

2

2016-11-23T12:28:15.000Z

2019-03-04T16:06:25.000Z

ddf_utils/model/__init__.py

semio/ddf_utils

e10c4cb6dc7722415a5863579a552cc7b7e3668d

[ "MIT" ]

124

2016-07-14T13:39:41.000Z

2021-12-24T01:45:23.000Z

ddf_utils/model/__init__.py

semio/ddf_utils

e10c4cb6dc7722415a5863579a552cc7b7e3668d

[ "MIT" ]

1

2016-11-30T23:42:56.000Z

from .ddf import DDF from .package import DDFcsv

16.333333

27

0.795918

8

49

4.875

0.625

0

0.163265

49

2

28

24.5

0.95122

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1

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true

0

1

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1

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1

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1

0

null

0

1

0

1

0

1

0

6

99a63fa91495ded0ecb4bc0dbc8e92070b4ea199

105

py

Python

components/zerodop/GPUgeo2rdr/__init__.py

vincentschut/isce2

1557a05b7b6a3e65abcfc32f89c982ccc9b65e3c

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

1,133

2022-01-07T21:24:57.000Z

2022-01-07T21:33:08.000Z

components/zerodop/GPUgeo2rdr/__init__.py

vincentschut/isce2

1557a05b7b6a3e65abcfc32f89c982ccc9b65e3c

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

276

2019-02-10T07:18:28.000Z

2022-03-31T21:45:55.000Z

components/zerodop/GPUgeo2rdr/__init__.py

vincentschut/isce2

1557a05b7b6a3e65abcfc32f89c982ccc9b65e3c

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

235

2019-02-10T05:00:53.000Z

2022-03-18T07:37:24.000Z

#!/usr/bin/env python def createGeo2rdr(): from .GPUgeo2rdr import PyGeo2rdr return PyGeo2rdr()

17.5

37

0.714286

12

105

6.25

0.916667

0

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0.180952

105

5

38

21

0.825581

0.190476

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1

0.333333

true

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null

0

1

0

1

0

1

0

6

41d7e9d736891a3dfc9a495779130c14ae930706

38

py

Python

convnet_web/handlers/__init__.py

tech-team/convnet

ee401c29349e163a95a868304e120de215158e37

[ "MIT" ]

null

convnet_web/handlers/__init__.py

tech-team/convnet

ee401c29349e163a95a868304e120de215158e37

[ "MIT" ]

null

convnet_web/handlers/__init__.py

tech-team/convnet

ee401c29349e163a95a868304e120de215158e37

[ "MIT" ]

null

from pages import * from api import *

12.666667

19

0.736842

6

38

4.666667

0.666667

0

0.210526

38

2

20

19

0.933333

0

1

0

true

0

1

0

1

0

1

0

null

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1

0

null

0

1

0

1

0

1

0

6

41dfb215c38c25ef73e517eea3417e70e53c95a4

61

py

Python

alento_bot/core_module/core_cog/__init__.py

alentoghostflame/StupidAlentoBot

c024bfb79a9ecb0d9fda5ddc4e361a0cb878baba

[ "MIT" ]

1

2021-12-12T02:50:20.000Z

alento_bot/core_module/core_cog/__init__.py

alentoghostflame/StupidAlentoBot

c024bfb79a9ecb0d9fda5ddc4e361a0cb878baba

[ "MIT" ]

17

2020-02-07T23:40:36.000Z

2020-12-22T16:38:44.000Z

alento_bot/core_module/core_cog/__init__.py

alentoghostflame/StupidAlentoBot

c024bfb79a9ecb0d9fda5ddc4e361a0cb878baba

[ "MIT" ]

null

from alento_bot.core_module.core_cog.core_cog import CoreCog

30.5

60

0.885246

11

61

4.545455

0.727273

0.28

0

0.065574

61

1

61

0.877193

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

41fc02c2426cd4aba597ba25b93495425c31f5e6

43

py

Python

adlib/utils/validation.py

xyvivian/adlib

79a93baa8aa542080bbf55734168eb89317df83c

[ "MIT" ]

null

adlib/utils/validation.py

xyvivian/adlib

79a93baa8aa542080bbf55734168eb89317df83c

[ "MIT" ]

null

adlib/utils/validation.py

xyvivian/adlib

79a93baa8aa542080bbf55734168eb89317df83c

[ "MIT" ]

null

from typing import List import numpy as np

14.333333

23

0.813953

8

43

4.375

0.875

0

0.186047

43

2

24

21.5

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

513898b33cf50a40d2d3ced0cf4b02f0098f184c

42

py

Python

beauty_bot/database_management/__init__.py

blue945u/beauty_bot

ddf56cd759b0b838d602dcb3c6a5c83df19eb3c0

[ "MIT" ]

null

beauty_bot/database_management/__init__.py

blue945u/beauty_bot

ddf56cd759b0b838d602dcb3c6a5c83df19eb3c0

[ "MIT" ]

null

beauty_bot/database_management/__init__.py

blue945u/beauty_bot

ddf56cd759b0b838d602dcb3c6a5c83df19eb3c0

[ "MIT" ]

null

from .data_base_tool import PixnetDatabase

42

0.904762

6

42

6

1

0

0.071429

42

1

42

0.923077

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

515f7ff6e17f2e79e6202817e2bae7bf78e7a9c6

126

py

Python

Pacotes/pacote_v1.py

VictorMello1993/CursoPythonUdemy

d3e2e542a7c3d3f9635f2b88d0e75ab4fa84236d

[ "MIT" ]

null

Pacotes/pacote_v1.py

VictorMello1993/CursoPythonUdemy

d3e2e542a7c3d3f9635f2b88d0e75ab4fa84236d

[ "MIT" ]

4

2021-04-08T21:54:09.000Z

2022-02-10T14:35:13.000Z

Pacotes/pacote_v1.py

VictorMello1993/CursoPythonUdemy

d3e2e542a7c3d3f9635f2b88d0e75ab4fa84236d

[ "MIT" ]

null

# Importando um módulo criado no pacote 'pacote1' from pacote1 import modulo1 print(type(modulo1)) print(modulo1.soma(2, 3))

25.2

49

0.769841

19

126

5.105263

0.789474

0.247423

0

0.063636

0.126984

126

5

50

25.2

0.818182

0.373016

0

1

0

true

0

0.333333

0

0.333333

0.666667

1

0

null

1

0

1

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null

0

1

0

1

0

1

0

6

5a9eaf81b1ea47c9f768b4adbb931a0ee4b90e1d

27,326

py

Python

tests/open_alchemy/schemas/artifacts/property_/test_relationship.py

MihailMiller/OpenAlchemy

55b751c58ca50706ebc46262f50addb7dec34278

[ "Apache-2.0" ]

40

2019-11-05T06:50:35.000Z

2022-03-09T01:34:57.000Z

tests/open_alchemy/schemas/artifacts/property_/test_relationship.py

MihailMiller/OpenAlchemy

55b751c58ca50706ebc46262f50addb7dec34278

[ "Apache-2.0" ]

178

2019-11-03T04:10:38.000Z

2022-03-31T00:07:17.000Z

tests/open_alchemy/schemas/artifacts/property_/test_relationship.py

MihailMiller/OpenAlchemy

55b751c58ca50706ebc46262f50addb7dec34278

[ "Apache-2.0" ]

17

2019-11-04T07:22:46.000Z

2022-03-23T05:29:49.000Z

"""Tests for retrieving artifacts for a relationship property.""" import functools import pytest from open_alchemy import types from open_alchemy.schemas import artifacts GET_TESTS = [ pytest.param( True, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "required", True, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="required True", ), pytest.param( False, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "required", False, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="required False", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "type", types.PropertyType.RELATIONSHIP, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="property type", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "sub_type", types.RelationshipType.MANY_TO_ONE, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="sub type many-to-one", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-uselist": False, } }, "sub_type", types.RelationshipType.ONE_TO_ONE, artifacts.types.OneToOneRelationshipPropertyArtifacts, id="sub type one-to-one", ), pytest.param( None, {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "sub_type", types.RelationshipType.ONE_TO_MANY, artifacts.types.OneToManyRelationshipPropertyArtifacts, id="sub type one-to-many", ), pytest.param( None, {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-secondary": "secondary_1", } }, "sub_type", types.RelationshipType.MANY_TO_MANY, artifacts.types.ManyToManyRelationshipPropertyArtifacts, id="sub type many-to-many", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "parent", "RefSchema", artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="parent many-to-one", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-uselist": False, } }, "parent", "RefSchema", artifacts.types.OneToOneRelationshipPropertyArtifacts, id="parent one-to-one", ), pytest.param( None, {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "parent", "RefSchema", artifacts.types.OneToManyRelationshipPropertyArtifacts, id="parent one-to-many", ), pytest.param( None, {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-secondary": "secondary_1", } }, "parent", "RefSchema", artifacts.types.ManyToManyRelationshipPropertyArtifacts, id="parent many-to-many", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "array", "items": {"$ref": "#/components/schemas/RefRefSchema"}, }, "RefRefSchema": {"type": "object"}, }, "parent", "RefRefSchema", artifacts.types.OneToManyRelationshipPropertyArtifacts, id="$ref items one-to-many", ), pytest.param( None, { "allOf": [ {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}} ] }, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "parent", "RefSchema", artifacts.types.OneToManyRelationshipPropertyArtifacts, id="allOf items one-to-many", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "array", "items": {"$ref": "#/components/schemas/RefRefSchema"}, }, "RefRefSchema": {"type": "object", "x-secondary": "secondary_1"}, }, "parent", "RefRefSchema", artifacts.types.ManyToManyRelationshipPropertyArtifacts, id="$ref items one-to-many", ), pytest.param( None, { "allOf": [ {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}} ] }, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-secondary": "secondary_1", } }, "parent", "RefSchema", artifacts.types.ManyToManyRelationshipPropertyArtifacts, id="allOf items one-to-many", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "schema", {"type": "object", "x-de-$ref": "RefSchema"}, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="schema many-to-one", ), pytest.param( None, { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"description": "description 1"}, ] }, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "description": "description 2", } }, "schema", {"type": "object", "x-de-$ref": "RefSchema", "description": "description 1"}, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="schema description prefer local many-to-one", ), pytest.param( None, {"allOf": [{"$ref": "#/components/schemas/RefSchema"}, {"nullable": True}]}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "nullable": False, } }, "schema", {"type": "object", "x-de-$ref": "RefSchema", "nullable": True}, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="schema nullable prefer local many-to-one", ), pytest.param( None, {"allOf": [{"$ref": "#/components/schemas/RefSchema"}, {"writeOnly": True}]}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "writeOnly": False, } }, "schema", {"type": "object", "x-de-$ref": "RefSchema", "writeOnly": True}, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="schema writeOnly prefer local many-to-one", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-uselist": False, } }, "schema", {"type": "object", "x-de-$ref": "RefSchema"}, artifacts.types.OneToOneRelationshipPropertyArtifacts, id="schema one-to-one", ), pytest.param( None, {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "schema", {"type": "array", "items": {"type": "object", "x-de-$ref": "RefSchema"}}, artifacts.types.OneToManyRelationshipPropertyArtifacts, id="schema one-to-many", ), pytest.param( None, { "allOf": [ {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, {"description": "description 1"}, ] }, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "description": "description 2", } }, "schema", { "type": "array", "items": {"type": "object", "x-de-$ref": "RefSchema"}, "description": "description 1", }, artifacts.types.OneToManyRelationshipPropertyArtifacts, id="schema description one-to-many", ), pytest.param( None, { "allOf": [ {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, {"writeOnly": True}, ] }, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "writeOnly": False, } }, "schema", { "type": "array", "items": {"type": "object", "x-de-$ref": "RefSchema"}, "writeOnly": True, }, artifacts.types.OneToManyRelationshipPropertyArtifacts, id="schema writeOnly one-to-many", ), pytest.param( None, {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-secondary": "secondary_1", } }, "schema", {"type": "array", "items": {"type": "object", "x-de-$ref": "RefSchema"}}, artifacts.types.ManyToManyRelationshipPropertyArtifacts, id="schema many-to-many", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "backref_property", None, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="backref undefined", ), pytest.param( None, { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"x-backref": "backref_1"}, ] }, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "backref_property", "backref_1", artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="backref many-to-one", ), pytest.param( None, { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"x-backref": "backref_1"}, ] }, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-backref": "backref_2", } }, "backref_property", "backref_1", artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="backref prefer local many-to-one", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-backref": "backref_1", "x-uselist": False, } }, "backref_property", "backref_1", artifacts.types.OneToOneRelationshipPropertyArtifacts, id="backref one-to-one", ), pytest.param( None, {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-backref": "backref_1", } }, "backref_property", "backref_1", artifacts.types.OneToManyRelationshipPropertyArtifacts, id="backref one-to-many", ), pytest.param( None, {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, { "RefSchema": { "type": "object", "x-backref": "backref_1", "x-secondary": "secondary_1", } }, "backref_property", "backref_1", artifacts.types.ManyToManyRelationshipPropertyArtifacts, id="backref many-to-many", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "kwargs", None, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="kwargs undefined", ), pytest.param( None, { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"x-kwargs": {"key_1": "value 1"}}, ] }, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "kwargs", {"key_1": "value 1"}, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="kwargs many-to-one", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-kwargs": {"key_2": "value 2"}, } }, "kwargs", None, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="kwargs on parent many-to-one", ), pytest.param( None, { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"x-kwargs": {"key_1": "value 1"}}, ] }, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-uselist": False, } }, "kwargs", {"key_1": "value 1"}, artifacts.types.OneToOneRelationshipPropertyArtifacts, id="kwargs one-to-one", ), pytest.param( None, { "type": "array", "items": { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"x-kwargs": {"key_1": "value 1"}}, ] }, }, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "kwargs", {"key_1": "value 1"}, artifacts.types.OneToManyRelationshipPropertyArtifacts, id="kwargs one-to-many", ), pytest.param( None, { "type": "array", "items": { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"x-kwargs": {"key_1": "value 1"}}, ] }, }, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-secondary": "secondary_1", } }, "kwargs", {"key_1": "value 1"}, artifacts.types.ManyToManyRelationshipPropertyArtifacts, id="kwargs many-to-many", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "write_only", None, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="writeOnly undefined", ), pytest.param( None, {"allOf": [{"$ref": "#/components/schemas/RefSchema"}, {"writeOnly": True}]}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "write_only", True, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="writeOnly many-to-one", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "writeOnly": True, } }, "write_only", None, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="writeOnly many-to-one skip_ref", ), pytest.param( None, {"allOf": [{"$ref": "#/components/schemas/RefSchema"}, {"writeOnly": False}]}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-uselist": False, } }, "write_only", False, artifacts.types.OneToOneRelationshipPropertyArtifacts, id="writeOnly one-to-one", ), pytest.param( None, { "writeOnly": True, "type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}, }, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "write_only", True, artifacts.types.OneToManyRelationshipPropertyArtifacts, id="writeOnly one-to-many", ), pytest.param( None, { "writeOnly": True, "type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}, }, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-secondary": "secondary_1", } }, "write_only", True, artifacts.types.ManyToManyRelationshipPropertyArtifacts, id="writeOnly many-to-many", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "description", None, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="description undefined", ), pytest.param( None, { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"description": "description 1"}, ] }, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "description", "description 1", artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="description many-to-one", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "description": "description 1", } }, "description", None, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="description many-to-one skip_ref", ), pytest.param( None, { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"description": "description 2"}, ] }, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-uselist": False, } }, "description", "description 2", artifacts.types.OneToOneRelationshipPropertyArtifacts, id="description one-to-one", ), pytest.param( None, { "description": "description 1", "type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}, }, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "description", "description 1", artifacts.types.OneToManyRelationshipPropertyArtifacts, id="description one-to-many", ), pytest.param( None, { "description": "description 1", "type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}, }, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-secondary": "secondary_1", } }, "description", "description 1", artifacts.types.ManyToManyRelationshipPropertyArtifacts, id="description many-to-many", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "foreign_key", "ref_schema.id", artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="foreign key many-to-one", ), pytest.param( None, { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"x-foreign-key-column": "name"}, ] }, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "foreign_key", "ref_schema.name", artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="foreign key set many-to-one", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-uselist": False, } }, "foreign_key", "ref_schema.id", artifacts.types.OneToOneRelationshipPropertyArtifacts, id="foreign key one-to-one", ), pytest.param( None, {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "foreign_key", "schema.id", artifacts.types.OneToManyRelationshipPropertyArtifacts, id="foreign key one-to-many", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "foreign_key_property", "ref_schema_id", artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="foreign key property many-to-one", ), pytest.param( None, { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"x-foreign-key-column": "name"}, ] }, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "foreign_key_property", "ref_schema_name", artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="foreign key property set many-to-one", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-uselist": False, } }, "foreign_key_property", "ref_schema_id", artifacts.types.OneToOneRelationshipPropertyArtifacts, id="foreign key property one-to-one", ), pytest.param( None, {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "foreign_key_property", "schema_ref_schema_id", artifacts.types.OneToManyRelationshipPropertyArtifacts, id="foreign key property one-to-many", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "nullable", None, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="nullable undefined", ), pytest.param( None, {"allOf": [{"$ref": "#/components/schemas/RefSchema"}, {"nullable": True}]}, {"RefSchema": {"type": "object", "x-tablename": "ref_schema"}}, "nullable", True, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="nullable many-to-one", ), pytest.param( None, {"$ref": "#/components/schemas/RefSchema"}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "nullable": True, } }, "nullable", True, artifacts.types.ManyToOneRelationshipPropertyArtifacts, id="nullable many-to-one on reference", ), pytest.param( None, {"allOf": [{"$ref": "#/components/schemas/RefSchema"}, {"nullable": False}]}, { "RefSchema": { "type": "object", "x-tablename": "ref_schema", "x-uselist": False, } }, "nullable", False, artifacts.types.OneToOneRelationshipPropertyArtifacts, id="nullable one-to-one", ), pytest.param( None, {"type": "array", "items": {"$ref": "#/components/schemas/RefSchema"}}, {"RefSchema": {"type": "object", "x-secondary": "secondary_1"}}, "secondary", "secondary_1", artifacts.types.ManyToManyRelationshipPropertyArtifacts, id="secondary many-to-many", ), pytest.param( None, { "type": "array", "items": { "allOf": [ {"$ref": "#/components/schemas/RefSchema"}, {"x-secondary": "secondary_1"}, ] }, }, {"RefSchema": {"type": "object", "x-secondary": "secondary_2"}}, "secondary", "secondary_1", artifacts.types.ManyToManyRelationshipPropertyArtifacts, id="secondary prefer local many-to-many", ), ] @pytest.mark.parametrize( "required, schema, schemas, key, expected_value, expected_type", GET_TESTS ) @pytest.mark.schemas @pytest.mark.artifacts def test_get(required, schema, schemas, key, expected_value, expected_type): """ GIVEN schema, schemas, key and expected value WHEN get is called with the schema and schemas THEN the returned artifacts has the expected value behind the key. """ parent_schema = {"x-tablename": "schema"} property_name = "ref_schema" returned_artifacts = artifacts.property_.relationship.get( schemas, parent_schema, property_name, schema, required ) assert isinstance(returned_artifacts, expected_type) value = functools.reduce(getattr, key.split("."), returned_artifacts) assert value == expected_value

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87

0.490632

2,074

27,326

6.386692

0.043394

0.053601

0.058131

0.135739

0.885626

0.794957

0.768836

0.726634

0.668126

0.608712

0

0.003254

0.347727

27,326

890

88

30.703371

0.739901

0.008014

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0.702055

0

0.325541

0.071128

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0.002283

1

0.001142

false

0

0.004566

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0.005708

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null

0

1

0

1

0

1

0

null

0

6

851a22f82e9633c51f3d7b27611c5e475d15b154

212

py

Python

app_survey/admin.py

MorganFrenk/survey_API

9172f00666c8788be5c0856157542d7eb76d112c

[ "MIT" ]

1

2021-08-15T16:35:27.000Z

app_survey/admin.py

MorganFrenk/survey_API

9172f00666c8788be5c0856157542d7eb76d112c

[ "MIT" ]

4

2021-08-19T09:30:45.000Z

2021-08-19T12:23:36.000Z

app_survey/admin.py

MorganFrenk/survey_API

9172f00666c8788be5c0856157542d7eb76d112c

[ "MIT" ]

null

from django.contrib import admin from app_survey.models import Answer, Choice, Question, Survey admin.site.register(Survey) admin.site.register(Question) admin.site.register(Choice) admin.site.register(Answer)

23.555556

62

0.820755

30

212

5.766667

0.433333

0.208092

0.393064

0.265896

0

0.080189

212

8

63

26.5

0.887179

0

1

0

true

0

0.333333

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0.333333

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null

1

0

1

0

null

0

1

0

1

0

6

51799f844f911b1c5139663e3f7b9804832779bb

4,558

py

Python

tests/test_sensor.py

kubawolanin/Home-Assistant-Mail-And-Packages

6e1b43683d4e0a386724dfcd14ce653968ce6557

[ "MIT" ]

2

2022-01-13T18:55:56.000Z

2022-01-14T20:56:19.000Z

tests/test_sensor.py

kubawolanin/Home-Assistant-Mail-And-Packages

6e1b43683d4e0a386724dfcd14ce653968ce6557

[ "MIT" ]

4

2022-01-13T08:34:58.000Z

2022-02-20T11:17:31.000Z

tests/test_sensor.py

kubawolanin/Home-Assistant-Mail-And-Packages

6e1b43683d4e0a386724dfcd14ce653968ce6557

[ "MIT" ]

2

2022-01-13T16:47:21.000Z

2022-02-07T12:43:58.000Z

""" Test Mail and Packages Sensor """ from pytest_homeassistant_custom_component.common import MockConfigEntry from custom_components.mail_and_packages.const import DOMAIN from tests.const import FAKE_CONFIG_DATA_NO_RND async def test_sensor(hass, mock_update): entry = MockConfigEntry( domain=DOMAIN, title="imap.test.email", data=FAKE_CONFIG_DATA_NO_RND, ) entry.add_to_hass(hass) assert await hass.config_entries.async_setup(entry.entry_id) await hass.async_block_till_done() assert "mail_and_packages" in hass.config.components # Check for mail_updated sensor reporting value from test data state = hass.states.get("sensor.mail_updated") assert state assert state.state == "2022-01-06T12:14:38+00:00" # Make sure the rest of the sensors are importing our test data state = hass.states.get("sensor.mail_usps_mail") assert state assert state.state == "6" assert state.attributes["image"] == "mail_today.gif" state = hass.states.get("sensor.mail_usps_delivered") assert state assert state.state == "3" state = hass.states.get("sensor.mail_usps_delivering") assert state assert state.state == "3" assert state.attributes["tracking_#"] == ["92123456789012345"] state = hass.states.get("sensor.mail_usps_packages") assert state assert state.state == "3" state = hass.states.get("sensor.mail_ups_delivered") assert state assert state.state == "1" state = hass.states.get("sensor.mail_ups_delivering") assert state assert state.state == "1" assert state.attributes["tracking_#"] == ["1Z123456789"] state = hass.states.get("sensor.mail_ups_packages") assert state assert state.state == "1" state = hass.states.get("sensor.mail_fedex_delivered") assert state assert state.state == "0" state = hass.states.get("sensor.mail_fedex_delivering") assert state assert state.state == "2" assert state.attributes["tracking_#"] == ["1234567890"] state = hass.states.get("sensor.mail_fedex_packages") assert state assert state.state == "2" state = hass.states.get("sensor.mail_fedex_packages") assert state assert state.state == "2" state = hass.states.get("sensor.mail_amazon_packages") assert state assert state.state == "7" assert state.attributes["order"] == ["#123-4567890"] state = hass.states.get("sensor.mail_amazon_packages_delivered") assert state assert state.state == "2" state = hass.states.get("sensor.mail_dhl_delivered") assert state assert state.state == "0" state = hass.states.get("sensor.mail_dhl_delivering") assert state assert state.state == "1" assert state.attributes["tracking_#"] == ["1234567890"] state = hass.states.get("sensor.mail_dhl_packages") assert state assert state.state == "2" state = hass.states.get("sensor.mail_auspost_delivered") assert state assert state.state == "2" state = hass.states.get("sensor.mail_auspost_delivering") assert state assert state.state == "1" state = hass.states.get("sensor.mail_auspost_packages") assert state assert state.state == "3" state = hass.states.get("sensor.mail_poczta_polska_delivering") assert state assert state.state == "1" state = hass.states.get("sensor.mail_poczta_polska_packages") assert state assert state.state == "1" state = hass.states.get("sensor.mail_inpost_pl_delivered") assert state assert state.state == "2" state = hass.states.get("sensor.mail_inpost_pl_delivering") assert state assert state.state == "1" state = hass.states.get("sensor.mail_inpost_pl_packages") assert state assert state.state == "3" state = hass.states.get("sensor.mail_dpd_com_pl_delivered") assert state assert state.state == "2" state = hass.states.get("sensor.mail_dpd_com_pl_delivering") assert state assert state.state == "1" state = hass.states.get("sensor.mail_dpd_com_pl_packages") assert state assert state.state == "3" state = hass.states.get("sensor.mail_gls_delivered") assert state assert state.state == "2" state = hass.states.get("sensor.mail_gls_delivering") assert state assert state.state == "1" state = hass.states.get("sensor.mail_gls_packages") assert state assert state.state == "3" state = hass.states.get("sensor.mail_packages_delivered") assert state assert state.state == "7"

28.848101

72

0.689557

601

4,558

5.051581

0.161398

0.253623

0.158103

0.189723

0.791502

0.761199

0.720685

0.658762

0.606719

0.600791

0

0.028804

0.192628

4,558

157

73

29.031847

0.796196

0.033787

0

0.573913

0

0.250682

0.203822

0

0.626087

1

0

false

0

0.026087

0

0.026087

0

null

1

0

1

0

1

0

1

0

null

0

1

0

6

51c0d0c1544a17bf3745338c9729dee771cd6d78

179,923

py

Python

ambari-server/src/test/python/stacks/2.5/common/test_stack_advisor.py

gcxtx/ambari

133d9c4661b21182482c25f96c3f0bf0a9740a9f

[ "Apache-2.0" ]

1

2021-05-06T06:24:04.000Z

ambari-server/src/test/python/stacks/2.5/common/test_stack_advisor.py

gcxtx/ambari

133d9c4661b21182482c25f96c3f0bf0a9740a9f

[ "Apache-2.0" ]

null

ambari-server/src/test/python/stacks/2.5/common/test_stack_advisor.py

gcxtx/ambari

133d9c4661b21182482c25f96c3f0bf0a9740a9f

[ "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. ''' import json import os import socket from unittest import TestCase from mock.mock import patch, MagicMock class TestHDP25StackAdvisor(TestCase): def setUp(self): import imp self.maxDiff = None self.testDirectory = os.path.dirname(os.path.abspath(__file__)) stackAdvisorPath = os.path.join(self.testDirectory, '../../../../../main/resources/stacks/stack_advisor.py') hdp206StackAdvisorPath = os.path.join(self.testDirectory, '../../../../../main/resources/stacks/HDP/2.0.6/services/stack_advisor.py') hdp21StackAdvisorPath = os.path.join(self.testDirectory, '../../../../../main/resources/stacks/HDP/2.1/services/stack_advisor.py') hdp22StackAdvisorPath = os.path.join(self.testDirectory, '../../../../../main/resources/stacks/HDP/2.2/services/stack_advisor.py') hdp23StackAdvisorPath = os.path.join(self.testDirectory, '../../../../../main/resources/stacks/HDP/2.3/services/stack_advisor.py') hdp24StackAdvisorPath = os.path.join(self.testDirectory, '../../../../../main/resources/stacks/HDP/2.4/services/stack_advisor.py') hdp25StackAdvisorPath = os.path.join(self.testDirectory, '../../../../../main/resources/stacks/HDP/2.5/services/stack_advisor.py') hdp25StackAdvisorClassName = 'HDP25StackAdvisor' with open(stackAdvisorPath, 'rb') as fp: imp.load_module('stack_advisor', fp, stackAdvisorPath, ('.py', 'rb', imp.PY_SOURCE)) with open(hdp206StackAdvisorPath, 'rb') as fp: imp.load_module('stack_advisor_impl', fp, hdp206StackAdvisorPath, ('.py', 'rb', imp.PY_SOURCE)) with open(hdp21StackAdvisorPath, 'rb') as fp: imp.load_module('stack_advisor_impl', fp, hdp21StackAdvisorPath, ('.py', 'rb', imp.PY_SOURCE)) with open(hdp22StackAdvisorPath, 'rb') as fp: imp.load_module('stack_advisor_impl', fp, hdp22StackAdvisorPath, ('.py', 'rb', imp.PY_SOURCE)) with open(hdp23StackAdvisorPath, 'rb') as fp: imp.load_module('stack_advisor_impl', fp, hdp23StackAdvisorPath, ('.py', 'rb', imp.PY_SOURCE)) with open(hdp24StackAdvisorPath, 'rb') as fp: imp.load_module('stack_advisor_impl', fp, hdp24StackAdvisorPath, ('.py', 'rb', imp.PY_SOURCE)) with open(hdp25StackAdvisorPath, 'rb') as fp: stack_advisor_impl = imp.load_module('stack_advisor_impl', fp, hdp25StackAdvisorPath, ('.py', 'rb', imp.PY_SOURCE)) clazz = getattr(stack_advisor_impl, hdp25StackAdvisorClassName) self.stackAdvisor = clazz() # substitute method in the instance self.get_system_min_uid_real = self.stackAdvisor.get_system_min_uid self.stackAdvisor.get_system_min_uid = self.get_system_min_uid_magic # setup for 'test_recommendYARNConfigurations' self.hosts = { "items": [ { "Hosts": { "cpu_count": 6, "total_mem": 50331648, "disk_info": [ {"mountpoint": "/"}, {"mountpoint": "/dev/shm"}, {"mountpoint": "/vagrant"}, {"mountpoint": "/"}, {"mountpoint": "/dev/shm"}, {"mountpoint": "/vagrant"} ], "public_host_name": "c6401.ambari.apache.org", "host_name": "c6401.ambari.apache.org" }, }, { "Hosts": { "cpu_count": 6, "total_mem": 50331648, "disk_info": [ {"mountpoint": "/"}, {"mountpoint": "/dev/shm"}, {"mountpoint": "/vagrant"}, {"mountpoint": "/"}, {"mountpoint": "/dev/shm"}, {"mountpoint": "/vagrant"} ], "public_host_name": "c6402.ambari.apache.org", "host_name": "c6402.ambari.apache.org" }, }, { "Hosts": { "cpu_count": 6, "total_mem": 50331648, "disk_info": [ {"mountpoint": "/"}, {"mountpoint": "/dev/shm"}, {"mountpoint": "/vagrant"}, {"mountpoint": "/"}, {"mountpoint": "/dev/shm"}, {"mountpoint": "/vagrant"} ], "public_host_name": "c6403.ambari.apache.org", "host_name": "c6403.ambari.apache.org" }, }, { "Hosts": { "cpu_count": 6, "total_mem": 50331648, "disk_info": [ {"mountpoint": "/"}, {"mountpoint": "/dev/shm"}, {"mountpoint": "/vagrant"}, {"mountpoint": "/"}, {"mountpoint": "/dev/shm"}, {"mountpoint": "/vagrant"} ], "public_host_name": "c6404.ambari.apache.org", "host_name": "c6404.ambari.apache.org" }, }, { "Hosts": { "cpu_count": 6, "total_mem": 50331648, "disk_info": [ {"mountpoint": "/"}, {"mountpoint": "/dev/shm"}, {"mountpoint": "/vagrant"}, {"mountpoint": "/"}, {"mountpoint": "/dev/shm"}, {"mountpoint": "/vagrant"} ], "public_host_name": "c6405.ambari.apache.org", "host_name": "c6405.ambari.apache.org" }, } ] } self.clusterData = { "cpu": 4, "mapMemory": 3000, "amMemory": 2000, "reduceMemory": 2056, "containers": 3, "ramPerContainer": 256 } # Expected config outputs. # Expected capacity-scheduler with 'llap' (size:20) and 'default' queue at root level. self.expected_capacity_scheduler_llap_queue_size_20 = { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=80\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=80\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=20\n' 'yarn.scheduler.capacity.root.llap.capacity=20\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } } # Expected capacity-scheduler with 'llap' (size:40) and 'default' queue at root level. self.expected_capacity_scheduler_llap_queue_size_40 = { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } } # Expected capacity-scheduler with 'llap' state = STOPPED, cap = 0 % and 'default' queue cap to 100%. self.expected_capacity_scheduler_llap_Stopped_size_0 = { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=100\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=100\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=STOPPED\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=0\n' 'yarn.scheduler.capacity.root.llap.capacity=0\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } } # Expected capacity-scheduler with only 'default' queue. self.expected_capacity_scheduler_with_default_queue_only = { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.root.queues=default\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=100\n' "yarn.scheduler.capacity.root.default.maximum-capacity=100\n" 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' } } # Expected capacity-scheduler as empty. self.expected_capacity_scheduler_empty = { "properties": { } } # Expected 'hive_interactive_site' with (1). 'hive.llap.daemon.queue.name' set to 'llap' queue, and # (2). 'hive.llap.daemon.queue.name' property_attributes set to : default and llap. self.expected_hive_interactive_site_llap = { "hive-interactive-site": { "properties": { "hive.llap.daemon.queue.name": "llap" }, "property_attributes": { "hive.llap.daemon.queue.name": { "entries": [ { "value": "default", "label": "default" }, { "value": "llap", "label": "llap" } ] } } } } # Expected 'hive_interactive_site' with (1). 'hive.llap.daemon.queue.name' set to 'default' queue, and # (2). 'hive.llap.daemon.queue.name' property_attributes set to : default. self.expected_hive_interactive_site_default = { "hive-interactive-site": { "properties": { "hive.llap.daemon.queue.name": "default" }, "property_attributes": { "hive.llap.daemon.queue.name": { "entries": [ { "value": "default", "label": "default" } ] } } } } # Expected 'hive_interactive_site' when no modifications are done. self.expected_hive_interactive_site_empty = { "hive-interactive-site": { "properties": { } } } # Expected 'hive_interactive_site' when no modifications are done. self.expected_hive_interactive_env_empty = { "hive-interactive-env": { "properties": { } } } self.expected_hive_interactive_site_only_memory = { "hive-interactive-site": { "properties": { 'hive.llap.daemon.yarn.container.mb': '341' } } } # Expected 'hive_interactive_env' with 'llap_queue_capacity' set to 20. self.expected_llap_queue_capacity_20 = '20' # Expected 'hive_interactive_env' with 'llap_queue_capacity' set to 40. self.expected_llap_queue_capacity_40 = '40' # expected vals. self.expected_visibility_false = {'visible': 'false'} self.expected_visibility_true = {'visible': 'true'} def load_json(self, filename): file = os.path.join(self.testDirectory, filename) with open(file, 'rb') as f: data = json.load(f) return data def prepareHosts(self, hostsNames): hosts = { "items": [] } for hostName in hostsNames: nextHost = {"Hosts":{"host_name" : hostName}} hosts["items"].append(nextHost) return hosts @patch('__builtin__.open') @patch('os.path.exists') def get_system_min_uid_magic(self, exists_mock, open_mock): class MagicFile(object): def read(self): return """ #test line UID_MIN 200 UID_MIN 500 """ def __exit__(self, exc_type, exc_val, exc_tb): pass def __enter__(self): return self exists_mock.return_value = True open_mock.return_value = MagicFile() return self.get_system_min_uid_real() def __getHosts(self, componentsList, componentName): return [component["StackServiceComponents"] for component in componentsList if component["StackServiceComponents"]["component_name"] == componentName][0] def test_getComponentLayoutValidations_one_hsi_host(self): hosts = self.load_json("host-3-hosts.json") services = self.load_json("services-normal-his-2-hosts.json") validations = self.stackAdvisor.getComponentLayoutValidations(services, hosts) expected = {'component-name': 'HIVE_SERVER_INTERACTIVE', 'message': 'Between 0 and 1 HiveServer2 Interactive components should be installed in cluster.', 'type': 'host-component', 'level': 'ERROR'} self.assertEquals(validations[0], expected) def test_validateYarnConfigurations(self): properties = {'enable_hive_interactive': 'true', 'hive_server_interactive_host': 'c6401.ambari.apache.org', 'hive.tez.container.size': '2048'} recommendedDefaults = {'enable_hive_interactive': 'true', "hive_server_interactive_host": "c6401.ambari.apache.org"} configurations = { "hive-interactive-env": { "properties": {'enable_hive_interactive': 'true', "hive_server_interactive_host": "c6401.ambari.apache.org"} }, "hive-site": { "properties": {"hive.security.authorization.enabled": "true", 'hive.tez.java.opts': '-server -Djava.net.preferIPv4Stack=true'} }, "hive-env": { "properties": {"hive_security_authorization": "None"} }, "yarn-site": { "properties": {"yarn.resourcemanager.work-preserving-recovery.enabled": "false"} } } services = self.load_json("services-normal-his-valid.json") res_expected = [ {'config-type': 'yarn-site', 'message': 'While enabling HIVE_SERVER_INTERACTIVE it is recommended that you enable work preserving restart in YARN.', 'type': 'configuration', 'config-name': 'yarn.resourcemanager.work-preserving-recovery.enabled', 'level': 'WARN'} ] res = self.stackAdvisor.validateYarnConfigurations(properties, recommendedDefaults, configurations, services, {}) self.assertEquals(res, res_expected) pass def test_validateHiveConfigurations(self): properties = {'enable_hive_interactive': 'true', 'hive_server_interactive_host': 'c6401.ambari.apache.org', 'hive.tez.container.size': '2048'} recommendedDefaults = {'enable_hive_interactive': 'true', "hive_server_interactive_host": "c6401.ambari.apache.org"} configurations = { "hive-interactive-env": { "properties": {'enable_hive_interactive': 'true', 'hive_server_interactive_host': 'c6401.ambari.apache.org'} }, "hive-site": { "properties": {"hive.security.authorization.enabled": "true", 'hive.tez.java.opts': '-server -Djava.net.preferIPv4Stack=true'} }, "hive-env": { "properties": {"hive_security_authorization": "None"} }, "yarn-site": { "properties": {"yarn.resourcemanager.work-preserving-recovery.enabled": "true"} } } configurations2 = { "hive-interactive-env": { "properties": {'enable_hive_interactive': 'false'} }, "hive-site": { "properties": {"hive.security.authorization.enabled": "true", 'hive.tez.java.opts': '-server -Djava.net.preferIPv4Stack=true'} }, "hive-env": { "properties": {"hive_security_authorization": "None"} }, "yarn-site": { "properties": {"yarn.resourcemanager.work-preserving-recovery.enabled": "true"} } } configurations3 = { "hive-interactive-env": { "properties": {'enable_hive_interactive': 'true', "hive_server_interactive_host": "c6402.ambari.apache.org"} }, "hive-site": { "properties": {"hive.security.authorization.enabled": "true", 'hive.tez.java.opts': '-server -Djava.net.preferIPv4Stack=true'} }, "hive-env": { "properties": {"hive_security_authorization": "None"} }, "yarn-site": { "properties": {"yarn.resourcemanager.work-preserving-recovery.enabled": "true"} } } services = self.load_json("services-normal-his-valid.json") res_expected = [ ] # the above error is not what we are checking for - just to keep test happy without having to test res = self.stackAdvisor.validateHiveInteractiveEnvConfigurations(properties, recommendedDefaults, configurations, services, {}) self.assertEquals(res, res_expected) res_expected = [ {'config-type': 'hive-interactive-env', 'message': 'HIVE_SERVER_INTERACTIVE requires enable_hive_interactive in hive-interactive-env set to true.', 'type': 'configuration', 'config-name': 'enable_hive_interactive', 'level': 'ERROR'}, {'config-type': 'hive-interactive-env', 'message': 'HIVE_SERVER_INTERACTIVE requires hive_server_interactive_host in hive-interactive-env set to its host name.', 'type': 'configuration', 'config-name': 'hive_server_interactive_host', 'level': 'ERROR'} ] res = self.stackAdvisor.validateHiveInteractiveEnvConfigurations(properties, recommendedDefaults, configurations2, services, {}) self.assertEquals(res, res_expected) res_expected = [ {'config-type': 'hive-interactive-env', 'message': 'HIVE_SERVER_INTERACTIVE requires hive_server_interactive_host in hive-interactive-env set to its host name.', 'type': 'configuration', 'config-name': 'hive_server_interactive_host', 'level': 'ERROR'} ] res = self.stackAdvisor.validateHiveInteractiveEnvConfigurations(properties, recommendedDefaults, configurations3, services, {}) self.assertEquals(res, res_expected) pass # Tests related to 'recommendYARNConfigurations()' # Test 1 : (1). Only default queue exists in capacity-scheduler (2). enable_hive_interactive' is 'On' and # 'llap_queue_capacity is 0. def test_recommendYARNConfigurations_create_llap_queue_1(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] }, } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'', u'type': u'', u'name': u'' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": "yarn.scheduler.capacity.root.queues=default\n" "yarn.scheduler.capacity.root.default.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.state=RUNNING\n" "yarn.scheduler.capacity.root.default.maximum-capacity=100\n" "yarn.scheduler.capacity.root.default.capacity=100\n" "yarn.scheduler.capacity.root.default.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.capacity=100\n" "yarn.scheduler.capacity.root.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.accessible-node-labels=*\n" "yarn.scheduler.capacity.node-locality-delay=40\n" "yarn.scheduler.capacity.maximum-applications=10000\n" "yarn.scheduler.capacity.maximum-am-resource-percent=1\n" "yarn.scheduler.capacity.queue-mappings-override.enable=false\n" } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'0' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "682", "yarn.nodemanager.resource.memory-mb": "10240" } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name':'default' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "hive-site": { 'properties': { 'hive.tez.container.size': '341' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertEquals(configurations['hive-interactive-site']['properties']['hive.llap.daemon.queue.name'], self.expected_hive_interactive_site_llap['hive-interactive-site']['properties']['hive.llap.daemon.queue.name']) self.assertEquals(configurations['hive-interactive-site']['property_attributes']['hive.llap.daemon.queue.name'], self.expected_hive_interactive_site_llap['hive-interactive-site']['property_attributes']['hive.llap.daemon.queue.name']) self.assertEquals(configurations['hive-interactive-env']['properties']['llap_queue_capacity'], self.expected_llap_queue_capacity_20) cap_sched_output_dict = convertToDict(configurations['capacity-scheduler']['properties']['capacity-scheduler']) cap_sched_expected_dict = convertToDict(self.expected_capacity_scheduler_llap_queue_size_20['properties']['capacity-scheduler']) self.assertEqual(cap_sched_output_dict, cap_sched_expected_dict) # Test 2: (1). Only default queue exists in capacity-scheduler (2). enable_hive_interactive' is 'On' and # 'llap_queue_capacity is 40. def test_recommendYARNConfigurations_create_llap_queue_2(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'', u'type': u'', u'name': u'' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": "yarn.scheduler.capacity.root.queues=default\n" "yarn.scheduler.capacity.root.default.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.state=RUNNING\n" "yarn.scheduler.capacity.root.default.maximum-capacity=100\n" "yarn.scheduler.capacity.root.default.capacity=100\n" "yarn.scheduler.capacity.root.default.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.capacity=100\n" "yarn.scheduler.capacity.root.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.accessible-node-labels=*\n" "yarn.scheduler.capacity.node-locality-delay=40\n" "yarn.scheduler.capacity.maximum-applications=10000\n" "yarn.scheduler.capacity.maximum-am-resource-percent=1\n" "yarn.scheduler.capacity.queue-mappings-override.enable=false\n" } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'40' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "682", "yarn.nodemanager.resource.memory-mb": "2048" } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name':'default', } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "hive-site": { 'properties': { 'hive.tez.container.size': '341' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertEquals(configurations['hive-interactive-site']['properties']['hive.llap.daemon.queue.name'], self.expected_hive_interactive_site_llap['hive-interactive-site']['properties']['hive.llap.daemon.queue.name']) self.assertEquals(configurations['hive-interactive-site']['property_attributes']['hive.llap.daemon.queue.name'], self.expected_hive_interactive_site_llap['hive-interactive-site']['property_attributes']['hive.llap.daemon.queue.name']) self.assertTrue('llap_queue_capacity' not in configurations['hive-interactive-env']['properties']) cap_sched_output_dict = convertToDict(configurations['capacity-scheduler']['properties']['capacity-scheduler']) cap_sched_expected_dict = convertToDict(self.expected_capacity_scheduler_llap_queue_size_40['properties']['capacity-scheduler']) self.assertEqual(cap_sched_output_dict, cap_sched_expected_dict) # Test 3: (1). 'llap' (0%) and 'default' (100%) queues exists at leaf level in capacity-scheduler # (2). llap is state = STOPPED, (3). llap_queue_capacity = 0, and (4). enable_hive_interactive' is 'ON'. # Expected : llap queue state = RUNNING, llap_queue_capacity = 20 def test_recommendYARNConfigurations_update_llap_queue_1(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'off', u'type': u'hive-interactive-env', u'name': u'enable_hive_interactive' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": "yarn.scheduler.capacity.root.accessible-node-labels=*\n" "yarn.scheduler.capacity.root.capacity=100\n" "yarn.scheduler.capacity.root.queues=default,llap\n" "yarn.scheduler.capacity.maximum-applications=10000\n" "yarn.scheduler.capacity.root.default.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.state=RUNNING\n" "yarn.scheduler.capacity.maximum-am-resource-percent=1\n" "yarn.scheduler.capacity.root.default.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.capacity=100\n" "yarn.scheduler.capacity.root.acl_administer_queue=*\n" "yarn.scheduler.capacity.node-locality-delay=40\n" "yarn.scheduler.capacity.queue-mappings-override.enable=false\n" "yarn.scheduler.capacity.root.llap.user-limit-factor=1\n" "yarn.scheduler.capacity.root.llap.state=STOPPED\n" "yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.llap.maximum-capacity=0\n" "yarn.scheduler.capacity.root.default.maximum-capacity=100\n" "yarn.scheduler.capacity.root.llap.capacity=0\n" "yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n" "yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n" "yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1\n" } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'0' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "341", "yarn.nodemanager.resource.memory-mb": "20000", "yarn.nodemanager.resource.cpu-vcores": '1' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name':'llap', 'hive.server2.tez.sessions.per.default.queue' : '1' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "hive-site": { 'properties': { 'hive.tez.container.size': '341' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertEquals(configurations['hive-interactive-site']['properties']['hive.llap.daemon.queue.name'], self.expected_hive_interactive_site_llap['hive-interactive-site']['properties']['hive.llap.daemon.queue.name']) self.assertEquals(configurations['hive-interactive-site']['property_attributes']['hive.llap.daemon.queue.name'], self.expected_hive_interactive_site_llap['hive-interactive-site']['property_attributes']['hive.llap.daemon.queue.name']) self.assertEquals(configurations['hive-interactive-env']['properties']['llap_queue_capacity'], self.expected_llap_queue_capacity_20) cap_sched_output_dict = convertToDict(configurations['capacity-scheduler']['properties']['capacity-scheduler']) cap_sched_expected_dict = convertToDict(self.expected_capacity_scheduler_llap_queue_size_20['properties']['capacity-scheduler']) self.assertEqual(cap_sched_output_dict, cap_sched_expected_dict) # Test 4: (1). 'llap' (20%) and 'default' (80%) queues exists at leaf level in capacity-scheduler # (2). llap is state = STOPPED, (3). llap_queue_capacity = 40, and (4). enable_hive_interactive' is 'ON'. # Expected : llap state goes RUNNING. def test_recommendYARNConfigurations_update_llap_queue_2(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'', u'type': u'', u'name': u'' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": "yarn.scheduler.capacity.root.accessible-node-labels=*\n" "yarn.scheduler.capacity.root.capacity=100\n" "yarn.scheduler.capacity.root.queues=default,llap\n" "yarn.scheduler.capacity.maximum-applications=10000\n" "yarn.scheduler.capacity.root.default.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.state=RUNNING\n" "yarn.scheduler.capacity.maximum-am-resource-percent=1\n" "yarn.scheduler.capacity.root.default.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.capacity=80\n" "yarn.scheduler.capacity.root.acl_administer_queue=*\n" "yarn.scheduler.capacity.node-locality-delay=40\n" "yarn.scheduler.capacity.queue-mappings-override.enable=false\n" "yarn.scheduler.capacity.root.llap.user-limit-factor=1\n" "yarn.scheduler.capacity.root.llap.state=RUNNING\n" "yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.llap.maximum-capacity=20\n" "yarn.scheduler.capacity.root.default.maximum-capacity=80\n" "yarn.scheduler.capacity.root.llap.capacity=20\n" "yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n" "yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n" "yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1\n" } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'40' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name':'llap' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "341", "yarn.nodemanager.resource.memory-mb": "20000", "yarn.nodemanager.resource.cpu-vcores": '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "hive-site": { 'properties': { 'hive.tez.container.size': '341' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertEquals(configurations['hive-interactive-site']['properties']['hive.llap.daemon.queue.name'], self.expected_hive_interactive_site_llap['hive-interactive-site']['properties']['hive.llap.daemon.queue.name']) self.assertEquals(configurations['hive-interactive-site']['property_attributes']['hive.llap.daemon.queue.name'], self.expected_hive_interactive_site_llap['hive-interactive-site']['property_attributes']['hive.llap.daemon.queue.name']) self.assertTrue('llap_queue_capacity' not in configurations['hive-interactive-env']['properties']) cap_sched_output_dict = convertToDict(configurations['capacity-scheduler']['properties']['capacity-scheduler']) cap_sched_expected_dict = convertToDict(self.expected_capacity_scheduler_llap_queue_size_40['properties']['capacity-scheduler']) self.assertEqual(cap_sched_output_dict, cap_sched_expected_dict) # Test 5: (1). 'llap' (20%) and 'default' (60%) queues exists at leaf level in capacity-scheduler # (2). llap is state = RUNNING, (3). llap_queue_capacity = 40, and (4). enable_hive_interactive' is 'ON'. # Expected : Existing llap queue's capacity in capacity-scheduler set to 40. def test_recommendYARNConfigurations_update_llap_queue_3(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'', u'type': u'', u'name': u'' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": "yarn.scheduler.capacity.root.accessible-node-labels=*\n" "yarn.scheduler.capacity.root.capacity=100\n" "yarn.scheduler.capacity.root.queues=default,llap\n" "yarn.scheduler.capacity.maximum-applications=10000\n" "yarn.scheduler.capacity.root.default.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.state=RUNNING\n" "yarn.scheduler.capacity.maximum-am-resource-percent=1\n" "yarn.scheduler.capacity.root.default.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.capacity=80\n" "yarn.scheduler.capacity.root.acl_administer_queue=*\n" "yarn.scheduler.capacity.node-locality-delay=40\n" "yarn.scheduler.capacity.queue-mappings-override.enable=false\n" "yarn.scheduler.capacity.root.llap.user-limit-factor=1\n" "yarn.scheduler.capacity.root.llap.state=RUNNING\n" "yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.llap.maximum-capacity=20\n" "yarn.scheduler.capacity.root.default.maximum-capacity=80\n" "yarn.scheduler.capacity.root.llap.capacity=20\n" "yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n" "yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n" "yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1\n" } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'40' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name':'llap' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "341", "yarn.nodemanager.resource.memory-mb": "20000", "yarn.nodemanager.resource.cpu-vcores": '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "hive-site": { 'properties': { 'hive.tez.container.size': '341' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertEquals(configurations['hive-interactive-site']['properties']['hive.llap.daemon.queue.name'], self.expected_hive_interactive_site_llap['hive-interactive-site']['properties']['hive.llap.daemon.queue.name']) self.assertEquals(configurations['hive-interactive-site']['property_attributes']['hive.llap.daemon.queue.name'], self.expected_hive_interactive_site_llap['hive-interactive-site']['property_attributes']['hive.llap.daemon.queue.name']) self.assertTrue('llap_queue_capacity' not in configurations['hive-interactive-env']['properties']) cap_sched_output_dict = convertToDict(configurations['capacity-scheduler']['properties']['capacity-scheduler']) cap_sched_expected_dict = convertToDict(self.expected_capacity_scheduler_llap_queue_size_40['properties']['capacity-scheduler']) self.assertEqual(cap_sched_output_dict, cap_sched_expected_dict) # Test 6: (1). Only default queue exists in capacity-scheduler (2). enable_hive_interactive' is 'Off' and # 'llap_queue_capacity is 0. # Expected : No changes def test_recommendYARNConfigurations_no_update_to_llap_queue_1(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'', u'type': u'', u'name': u'' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": "yarn.scheduler.capacity.root.queues=default\n" "yarn.scheduler.capacity.root.default.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.state=RUNNING\n" "yarn.scheduler.capacity.root.default.maximum-capacity=100\n" "yarn.scheduler.capacity.root.default.capacity=100\n" "yarn.scheduler.capacity.root.default.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.capacity=100\n" "yarn.scheduler.capacity.root.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.accessible-node-labels=*\n" "yarn.scheduler.capacity.node-locality-delay=40\n" "yarn.scheduler.capacity.maximum-applications=10000\n" "yarn.scheduler.capacity.maximum-am-resource-percent=1\n" "yarn.scheduler.capacity.queue-mappings-override.enable=false\n" } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'false', 'llap_queue_capacity':'0' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "682", "yarn.nodemanager.resource.memory-mb": "2048" } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } }, "hive-env": { 'properties': { 'hive_user': 'hive' } } } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertTrue('hive.llap.daemon.queue.name' not in configurations['hive-interactive-site']['properties']) self.assertTrue('property_attributes' not in configurations['hive-interactive-site']) self.assertTrue('hive-interactive-env' not in configurations) self.assertEquals(configurations['capacity-scheduler']['properties'],self.expected_capacity_scheduler_empty['properties']) # Test 7: (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'off'. # Expected : 'default' queue set to Size 100, 'llap' queue state set to STOPPED and sized to 0. def test_recommendYARNConfigurations_llap_queue_set_to_stopped_1(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'', u'type': u'', u'name': u'' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": "yarn.scheduler.capacity.root.accessible-node-labels=*\n" "yarn.scheduler.capacity.root.capacity=100\n" "yarn.scheduler.capacity.root.queues=default,llap\n" "yarn.scheduler.capacity.maximum-applications=10000\n" "yarn.scheduler.capacity.root.default.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.state=RUNNING\n" "yarn.scheduler.capacity.maximum-am-resource-percent=1\n" "yarn.scheduler.capacity.root.default.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.capacity=80\n" "yarn.scheduler.capacity.root.acl_administer_queue=*\n" "yarn.scheduler.capacity.node-locality-delay=40\n" "yarn.scheduler.capacity.queue-mappings-override.enable=false\n" "yarn.scheduler.capacity.root.llap.user-limit-factor=1\n" "yarn.scheduler.capacity.root.llap.state=RUNNING\n" "yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.llap.maximum-capacity=20\n" "yarn.scheduler.capacity.root.default.maximum-capacity=100\n" "yarn.scheduler.capacity.root.llap.capacity=20\n" "yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n" "yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n" "yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1\n" } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'false' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name':'default' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "682", "yarn.nodemanager.resource.memory-mb": "2048" }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } }, }, "hive-env": { 'properties': { 'hive_user': 'hive' } } } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertEquals(configurations['hive-interactive-site']['properties']['hive.llap.daemon.queue.name'], self.expected_hive_interactive_site_default['hive-interactive-site']['properties']['hive.llap.daemon.queue.name']) self.assertFalse('property_attributes' in configurations['hive-interactive-site']) self.assertFalse('hive-interactive-env' in configurations) cap_sched_output_dict = convertToDict(configurations['capacity-scheduler']['properties']['capacity-scheduler']) cap_sched_expected_dict = convertToDict(self.expected_capacity_scheduler_llap_Stopped_size_0['properties']['capacity-scheduler']) self.assertEqual(cap_sched_output_dict, cap_sched_expected_dict) # Test 8: (1). More than 2 queues at leaf level exists in capacity-scheduler (no queue is named 'llap') # (2). enable_hive_interactive' is 'off'. # Expected : No changes. def test_recommendYARNConfigurations_no_update_to_llap_queue_2(self): services= { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'', u'type': u'', u'name': u'' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": "yarn.scheduler.capacity.maximum-am-resource-percent=0.2\n" "yarn.scheduler.capacity.maximum-applications=10000\n" "yarn.scheduler.capacity.node-locality-delay=40\n" "yarn.scheduler.capacity.queue-mappings-override.enable=false\n" "yarn.scheduler.capacity.resource-calculator=org.apache.hadoop.yarn.util.resource.DefaultResourceCalculator\n" "yarn.scheduler.capacity.root.accessible-node-labels=*\n" "yarn.scheduler.capacity.root.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.capacity=100\n" "yarn.scheduler.capacity.root.default.a.a1.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.default.a.a1.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.a.a1.capacity=75\n" "yarn.scheduler.capacity.root.default.a.a1.maximum-capacity=100\n" "yarn.scheduler.capacity.root.default.a.a1.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.default.a.a1.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.default.a.a1.state=RUNNING\n" "yarn.scheduler.capacity.root.default.a.a1.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.a.a2.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.default.a.a2.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.a.a2.capacity=25\n" "yarn.scheduler.capacity.root.default.a.a2.maximum-capacity=25\n" "yarn.scheduler.capacity.root.default.a.a2.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.default.a.a2.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.default.a.a2.state=RUNNING\n" "yarn.scheduler.capacity.root.default.a.a2.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.a.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.default.a.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.a.capacity=50\n" "yarn.scheduler.capacity.root.default.a.maximum-capacity=100\n" "yarn.scheduler.capacity.root.default.a.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.default.a.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.default.a.queues=a1,a2\n" "yarn.scheduler.capacity.root.default.a.state=RUNNING\n" "yarn.scheduler.capacity.root.default.a.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.b.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.default.b.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.b.capacity=50\n" "yarn.scheduler.capacity.root.default.b.maximum-capacity=50\n" "yarn.scheduler.capacity.root.default.b.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.default.b.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.default.b.state=RUNNING\n" "yarn.scheduler.capacity.root.default.b.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.capacity=100\n" "yarn.scheduler.capacity.root.default.maximum-capacity=100\n" "yarn.scheduler.capacity.root.default.queues=a,b\n" "yarn.scheduler.capacity.root.default.state=RUNNING\n" "yarn.scheduler.capacity.root.default.user-limit-factor=1\n" "yarn.scheduler.capacity.root.queues=default" } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'false', 'llap_queue_capacity':'0' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } }, "hive-env": { 'properties': { 'hive_user': 'hive' } } } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertEquals(configurations['hive-interactive-site']['properties'], self.expected_hive_interactive_site_empty['hive-interactive-site']['properties']) self.assertEquals(configurations['capacity-scheduler']['properties'], self.expected_capacity_scheduler_empty['properties']) self.assertFalse('hive-interactive-env' in configurations) # Test 9: (1). More than 2 queues at leaf level exists in capacity-scheduler (one queue is named 'llap') # (2). enable_hive_interactive' is 'off'. # Expected : No changes. def test_recommendYARNConfigurations_no_update_to_llap_queue_3(self): services= { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'', u'type': u'', u'name': u'' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": "yarn.scheduler.capacity.maximum-am-resource-percent=0.2\n" "yarn.scheduler.capacity.maximum-applications=10000\n" "yarn.scheduler.capacity.node-locality-delay=40\n" "yarn.scheduler.capacity.queue-mappings-override.enable=false\n" "yarn.scheduler.capacity.resource-calculator=org.apache.hadoop.yarn.util.resource.DefaultResourceCalculator\n" "yarn.scheduler.capacity.root.accessible-node-labels=*\n" "yarn.scheduler.capacity.root.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.capacity=100\n" "yarn.scheduler.capacity.root.default.a.a1.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.default.a.a1.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.a.a1.capacity=75\n" "yarn.scheduler.capacity.root.default.a.a1.maximum-capacity=100\n" "yarn.scheduler.capacity.root.default.a.a1.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.default.a.a1.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.default.a.a1.state=RUNNING\n" "yarn.scheduler.capacity.root.default.a.a1.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.a.llap.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.default.a.llap.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.a.llap.capacity=25\n" "yarn.scheduler.capacity.root.default.a.llap.maximum-capacity=25\n" "yarn.scheduler.capacity.root.default.a.llap.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.default.a.llap.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.default.a.llap.state=RUNNING\n" "yarn.scheduler.capacity.root.default.a.llap.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.a.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.default.a.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.a.capacity=50\n" "yarn.scheduler.capacity.root.default.a.maximum-capacity=100\n" "yarn.scheduler.capacity.root.default.a.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.default.a.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.default.a.queues=a1,llap\n" "yarn.scheduler.capacity.root.default.a.state=RUNNING\n" "yarn.scheduler.capacity.root.default.a.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.b.acl_administer_queue=*\n" "yarn.scheduler.capacity.root.default.b.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.b.capacity=50\n" "yarn.scheduler.capacity.root.default.b.maximum-capacity=50\n" "yarn.scheduler.capacity.root.default.b.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.default.b.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.default.b.state=RUNNING\n" "yarn.scheduler.capacity.root.default.b.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.capacity=100\n" "yarn.scheduler.capacity.root.default.maximum-capacity=100\n" "yarn.scheduler.capacity.root.default.queues=a,b\n" "yarn.scheduler.capacity.root.default.state=RUNNING\n" "yarn.scheduler.capacity.root.default.user-limit-factor=1\n" "yarn.scheduler.capacity.root.queues=default" } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'false', 'llap_queue_capacity':'0' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } } } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertEquals(configurations['hive-interactive-site']['properties'], self.expected_hive_interactive_site_empty['hive-interactive-site']['properties']) self.assertEquals(configurations['capacity-scheduler']['properties'], self.expected_capacity_scheduler_empty['properties']) self.assertFalse('hive-interactive-env' in configurations) # Test 10: (1). 'llap' (Cap: 0%, State: STOPPED) and 'default' (100%) queues exists at leaf level # in capacity-scheduler # (2). enable_hive_interactive' is 'off'. # Expected : No changes. def test_recommendYARNConfigurations_no_update_to_llap_queue_4(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'', u'type': u'', u'name': u'' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": "yarn.scheduler.capacity.root.accessible-node-labels=*\n" "yarn.scheduler.capacity.root.capacity=100\n" "yarn.scheduler.capacity.root.queues=default,llap\n" "yarn.scheduler.capacity.maximum-applications=10000\n" "yarn.scheduler.capacity.root.default.user-limit-factor=1\n" "yarn.scheduler.capacity.root.default.state=RUNNING\n" "yarn.scheduler.capacity.maximum-am-resource-percent=1\n" "yarn.scheduler.capacity.root.default.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.capacity=100\n" "yarn.scheduler.capacity.root.acl_administer_queue=*\n" "yarn.scheduler.capacity.node-locality-delay=40\n" "yarn.scheduler.capacity.queue-mappings-override.enable=false\n" "yarn.scheduler.capacity.root.llap.user-limit-factor=1\n" "yarn.scheduler.capacity.root.llap.state=STOPPED\n" "yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n" "yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n" "yarn.scheduler.capacity.root.llap.maximum-capacity=0\n" "yarn.scheduler.capacity.root.default.maximum-capacity=100\n" "yarn.scheduler.capacity.root.llap.capacity=0\n" "yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n" "yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n" "yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1\n" } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'false' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } } } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertEquals(configurations['hive-interactive-site']['properties'], self.expected_hive_interactive_site_empty['hive-interactive-site']['properties']) self.assertEquals(configurations['capacity-scheduler']['properties'], self.expected_capacity_scheduler_empty['properties']) self.assertFalse('hive-interactive-env' in configurations) # Test 11: YARN service with : (1). 'capacity scheduler' having 'llap' (state:stopped) and 'default' queue at # root level and (2). 'enable_hive_interactive' is ON and (3). 'hive.llap.daemon.queue.name' == 'default' def test_recommendYARNConfigurations_no_update_to_llap_queue_5(self): services_15 = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6403.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "changed-configurations": [ { u'old_value': u'0', u'type': u'hive-interactive-env', u'name': u'llap_queue_capacity' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=STOPPED\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'40' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'default', 'hive.server2.tez.sessions.per.default.queue': '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "341", "yarn.nodemanager.resource.memory-mb": "4096", "yarn.nodemanager.resource.cpu-vcores": '1' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } }, "hive-site": { 'properties': { 'hive.tez.container.size': '341' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services_15, self.hosts) # Check output self.assertEquals(configurations['capacity-scheduler']['properties'], self.expected_capacity_scheduler_empty['properties']) self.assertEquals(configurations['hive-interactive-site']['properties'], self.expected_hive_interactive_site_only_memory['hive-interactive-site']['properties']) self.assertEquals(configurations['hive-interactive-env']['properties'], self.expected_hive_interactive_env_empty['hive-interactive-env']['properties']) self.assertEquals(configurations['hive-interactive-env']['property_attributes']['llap_queue_capacity'], self.expected_visibility_false) # Test 12: capacity-scheduler not present as input in services. # Expected : No changes. def test_recommendYARNConfigurations_no_update_to_llap_queue_5(self): services= { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'', u'type': u'', u'name': u'' } ], "configurations": { "capacity-scheduler": { "properties": { } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'false', 'llap_queue_capacity':'0' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } } } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertEquals(configurations['capacity-scheduler']['properties'], self.expected_capacity_scheduler_empty['properties']) self.assertFalse('hive-interactive-env' in configurations) self.assertEquals(configurations['hive-interactive-site']['properties'], self.expected_hive_interactive_site_empty['hive-interactive-site']['properties']) # Test 13: capacity-scheduler malformed as input in services. # Expected : No changes. def test_recommendYARNConfigurations_no_update_to_llap_queue_6(self): services= { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] } ] } ], "changed-configurations": [ { u'old_value': u'', u'type': u'', u'name': u'' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": "yarn.scheduler.capacity.root.default.a.a1.acl_submit_applications=*\n" "yarn.scheduler.capacity.root.default.a.a1.capacity=75\n" "yarn.scheduler.capacity.root.default.a.a1.maximum-capacity=100\n" } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'false', 'llap_queue_capacity':'0' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } } } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) # Check output self.assertEquals(configurations['capacity-scheduler']['properties'], self.expected_capacity_scheduler_empty['properties']) self.assertFalse('hive-interactive-env' in configurations) self.assertEquals(configurations['hive-interactive-site']['properties'], self.expected_hive_interactive_site_empty['hive-interactive-site']['properties']) # Test 14 : (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'OFF' and (3). configuration change detected for 'enable_hive_interactive' # Expected : Configurations values not recommended for llap related configs. def test_recommendYARNConfigurations_llap_configs_not_updated_1(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6403.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "changed-configurations": [ { u'old_value': u'false', u'type': u'hive-interactive-env', u'name': u'enable_hive_interactive' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'false', 'llap_queue_capacity':'40' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'llap', 'hive.server2.tez.sessions.per.default.queue': '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "341", "yarn.nodemanager.resource.memory-mb": "4096", "yarn.nodemanager.resource.cpu-vcores": '1' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } } } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) cap_sched_output_dict = convertToDict(configurations['capacity-scheduler']['properties']['capacity-scheduler']) cap_sched_expected_dict = convertToDict(self.expected_capacity_scheduler_llap_Stopped_size_0['properties']['capacity-scheduler']) self.assertEqual(cap_sched_output_dict, cap_sched_expected_dict) self.assertEquals(configurations['hive-interactive-site']['properties'], self.expected_hive_interactive_site_default['hive-interactive-site']['properties']) self.assertTrue('hive-interactive-env' not in configurations) self.assertTrue('property_attributes' not in configurations) # Test 15 : (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'OFF' and (3). configuration change NOT detected for 'enable_hive_interactive' # Expected : No changes. def test_recommendYARNConfigurations_llap_configs_not_updated_2(self): services_18 = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6403.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=STOPPED\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'false', 'llap_queue_capacity':'40' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'llap', 'hive.server2.tez.sessions.per.default.queue': '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "341", "yarn.nodemanager.resource.memory-mb": "4096", "yarn.nodemanager.resource.cpu-vcores": '1' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } } } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services_18, self.hosts) self.assertEquals(configurations['capacity-scheduler']['properties'], self.expected_capacity_scheduler_empty['properties']) self.assertEquals(configurations['hive-interactive-site']['properties'], self.expected_hive_interactive_site_empty['hive-interactive-site']['properties']) self.assertTrue('hive-interactive-env' not in configurations) self.assertTrue('property_attributes' not in configurations) ####################### 'One Node Manager' cluster - tests for calculating llap configs ################ # Test 16: (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'on' and (3). configuration change detected for 'llap_queue_capacity' # Expected : Configurations values recommended for llap related configs. def test_recommendYARNConfigurations_one_node_manager_llap_configs_updated_1(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6403.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "changed-configurations": [ { u'old_value': u'0', u'type': u'hive-interactive-env', u'name': u'llap_queue_capacity' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=80\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=20\n' 'yarn.scheduler.capacity.root.llap.capacity=20\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'21' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'llap', 'hive.server2.tez.sessions.per.default.queue': '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "512", "yarn.nodemanager.resource.memory-mb": "10240", "yarn.nodemanager.resource.cpu-vcores": '1' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "512" } }, "hive-site": { 'properties': { 'hive.tez.container.size': '512' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) self.assertEqual(configurations['hive-interactive-site']['properties']['hive.server2.tez.sessions.per.default.queue'], '1') self.assertEquals(configurations['hive-interactive-site']['property_attributes']['hive.server2.tez.sessions.per.default.queue'], {'minimum': '1', 'maximum': '32'}) self.assertEqual(configurations['hive-interactive-env']['properties']['num_llap_nodes'], '1') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.yarn.container.mb'], '1536') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.num.executors'], '1') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.memory.size'], '1024') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.enabled'], 'true') self.assertEqual(configurations['hive-interactive-env']['properties']['llap_heap_size'], '409') self.assertEqual(configurations['hive-interactive-env']['properties']['slider_am_container_size'], '512') # Test 17: (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'on' and (3). configuration change detected for 'enable_hive_interactive' # Expected : Configurations values recommended for llap related configs. def test_recommendYARNConfigurations_one_node_manager_llap_configs_updated_2(self): # Services 16: YARN service with : (1). 'capacity scheduler' having 'llap' and 'default' queue at root level and # (2). 'enable_hive_interactive' is ON and (3). configuration change detected for 'enable_hive_interactive' services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6403.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "changed-configurations": [ { u'old_value': u'false', u'type': u'hive-interactive-env', u'name': u'enable_hive_interactive' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'41' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'llap', 'hive.server2.tez.sessions.per.default.queue': '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "341", "yarn.nodemanager.resource.memory-mb": "10240", "yarn.nodemanager.resource.cpu-vcores": '1' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } }, "hive-site": { 'properties': { 'hive.tez.container.size': '341' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) self.assertEqual(configurations['hive-interactive-site']['properties']['hive.server2.tez.sessions.per.default.queue'], '3') self.assertEquals(configurations['hive-interactive-site']['property_attributes']['hive.server2.tez.sessions.per.default.queue'], {'minimum': '1', 'maximum': '32'}) self.assertEqual(configurations['hive-interactive-env']['properties']['num_llap_nodes'], '1') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.yarn.container.mb'], '3069') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.num.executors'], '1') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.memory.size'], '2728') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.enabled'], 'true') self.assertEqual(configurations['hive-interactive-env']['properties']['llap_heap_size'], '272') self.assertEqual(configurations['hive-interactive-env']['properties']['slider_am_container_size'], '341') # Test 18: (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'on' and (3). configuration change detected for 'hive.server2.tez.sessions.per.default.queue' # Expected : Configurations values recommended for llap related configs. def test_recommendYARNConfigurations_one_node_manager_llap_configs_updated_3(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6403.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "changed-configurations": [ { u'old_value': u'1', u'type': u'hive-interactive-site', u'name': u'hive.server2.tez.sessions.per.default.queue' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'41', 'num_llap_nodes': 1 } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'llap', 'hive.server2.tez.sessions.per.default.queue': '2', } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "1024", "yarn.nodemanager.resource.memory-mb": "51200", "yarn.nodemanager.resource.cpu-vcores": '1' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "1024" } }, "hive-site": { 'properties': { 'hive.tez.container.size': '1024' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) self.assertTrue('hive.server2.tez.sessions.per.default.queue' not in configurations['hive-interactive-site']['properties']) self.assertTrue('hive.server2.tez.sessions.per.default.queue' not in configurations['hive-interactive-site']['property_attributes']) self.assertEqual(configurations['hive-interactive-env']['properties']['num_llap_nodes'], '1') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.yarn.container.mb'], '18432') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.num.executors'], '1') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.memory.size'], '17408') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.enabled'], 'true') self.assertEqual(configurations['hive-interactive-env']['properties']['llap_heap_size'], '819') self.assertEqual(configurations['hive-interactive-env']['properties']['slider_am_container_size'], '1024') ####################### 'Three Node Managers' cluster - tests for calculating llap configs ################ # Test 19: (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'on' and (3). configuration change detected for 'llap_queue_capacity' # Expected : Configurations values recommended for llap related configs. def test_recommendYARNConfigurations_three_node_manager_llap_configs_updated_1(self): # Services 20: YARN service with : (1). 'capacity scheduler' having 'llap' and 'default' queue at root level and # (2). 'enable_hive_interactive' is ON and (3). configuration change detected for 'llap_queue_capacity' # 3 node managers and yarn.nodemanager.resource.memory-mb": "40960" services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org", "c6402.ambari.apache.org", "c6403.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6401.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "changed-configurations": [ { u'old_value': u'55', u'type': u'hive-interactive-env', u'name': u'llap_queue_capacity' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'90' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'llap', 'hive.server2.tez.sessions.per.default.queue': '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "2048", "yarn.nodemanager.resource.memory-mb": "40960", "yarn.nodemanager.resource.cpu-vcores": '4' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "1024" } }, "hive-site": { 'properties': { 'hive.tez.container.size': '1024' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) self.assertEqual(configurations['hive-interactive-site']['properties']['hive.server2.tez.sessions.per.default.queue'], '13') self.assertEquals(configurations['hive-interactive-site']['property_attributes']['hive.server2.tez.sessions.per.default.queue'], {'minimum': '1', 'maximum': '32'}) self.assertEqual(configurations['hive-interactive-env']['properties']['num_llap_nodes'], '2') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.yarn.container.mb'], '40960') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.num.executors'], '4') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.memory.size'], '36864') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.enabled'], 'true') self.assertEqual(configurations['hive-interactive-env']['properties']['llap_heap_size'], '3276') self.assertEqual(configurations['hive-interactive-env']['properties']['slider_am_container_size'], '1024') # Test 20: (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'on' and (3). configuration change detected for 'enable_hive_interactive' # Expected : Configurations values recommended for llap related configs. def test_recommendYARNConfigurations_three_node_manager_llap_configs_updated_2(self): # 3 node managers and yarn.nodemanager.resource.memory-mb": "12288" services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org", "c6402.ambari.apache.org", "c6403.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6401.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "changed-configurations": [ { u'old_value': u'false', u'type': u'hive-interactive-env', u'name': u'enable_hive_interactive' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'100' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'llap', 'hive.server2.tez.sessions.per.default.queue': '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "341", "yarn.nodemanager.resource.memory-mb": "12288", "yarn.nodemanager.resource.cpu-vcores": '3' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "1024" } }, "hive-site": { 'properties': { 'hive.tez.container.size': '1024' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) self.assertEqual(configurations['hive-interactive-site']['properties']['hive.server2.tez.sessions.per.default.queue'], '6') self.assertEquals(configurations['hive-interactive-site']['property_attributes']['hive.server2.tez.sessions.per.default.queue'], {'minimum': '1', 'maximum': '32'}) self.assertEqual(configurations['hive-interactive-env']['properties']['num_llap_nodes'], '2') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.yarn.container.mb'], '12276') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.num.executors'], '3') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.memory.size'], '9204') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.enabled'], 'true') self.assertEqual(configurations['hive-interactive-env']['properties']['llap_heap_size'], '2457') self.assertEqual(configurations['hive-interactive-env']['properties']['slider_am_container_size'], '341') # Test 21: (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'on' and (3). configuration change detected for 'hive.server2.tez.sessions.per.default.queue' # Expected : Configurations values recommended for llap related configs. def test_recommendYARNConfigurations_three_node_manager_llap_configs_updated_3(self): # 3 node managers and yarn.nodemanager.resource.memory-mb": "204800" services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org", "c6402.ambari.apache.org", "c6403.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6401.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "changed-configurations": [ { u'old_value': u'2', u'type': u'hive-interactive-site', u'name': u'hive.server2.tez.sessions.per.default.queue' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'50' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'llap', 'hive.server2.tez.sessions.per.default.queue': '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "2048", "yarn.nodemanager.resource.memory-mb": "204800", "yarn.nodemanager.resource.cpu-vcores": '3' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "1024" } }, "hive-site": { 'properties': { 'hive.tez.container.size': '1024' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) self.assertEqual(configurations['hive-interactive-env']['properties']['num_llap_nodes'], '1') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.yarn.container.mb'], '204800') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.num.executors'], '3') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.memory.size'], '201728') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.enabled'], 'true') self.assertEqual(configurations['hive-interactive-env']['properties']['llap_heap_size'], '2457') self.assertEqual(configurations['hive-interactive-env']['properties']['slider_am_container_size'], '1024') ####################### 'Five Node Managers' cluster - tests for calculating llap configs ################ # Test 22: (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'on' and (3). configuration change detected for 'llap_queue_capacity' # Expected : Configurations values recommended for llap related configs. def test_recommendYARNConfigurations_five_node_manager_llap_configs_updated_1(self): services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org", "c6402.ambari.apache.org", "c6403.ambari.apache.org", "c6404.ambari.apache.org", "c6405.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6401.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "changed-configurations": [ { u'old_value': u'55', u'type': u'hive-interactive-env', u'name': u'llap_queue_capacity' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'90' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'llap', 'hive.server2.tez.sessions.per.default.queue': '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "3072", "yarn.nodemanager.resource.memory-mb": "40960", "yarn.nodemanager.resource.cpu-vcores": '4' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "1024" } }, "hive-site": { 'properties': { 'hive.tez.container.size': '1024' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) self.assertEqual(configurations['hive-interactive-site']['properties']['hive.server2.tez.sessions.per.default.queue'], '15') self.assertEquals(configurations['hive-interactive-site']['property_attributes']['hive.server2.tez.sessions.per.default.queue'], {'minimum': '1', 'maximum': '32'}) self.assertEqual(configurations['hive-interactive-env']['properties']['num_llap_nodes'], '3') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.yarn.container.mb'], '39936') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.num.executors'], '4') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.memory.size'], '35840') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.enabled'], 'true') self.assertEqual(configurations['hive-interactive-env']['properties']['llap_heap_size'], '3276') self.assertEqual(configurations['hive-interactive-env']['properties']['slider_am_container_size'], '1024') # Test 23: (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'on' and (3). configuration change detected for 'enable_hive_interactive' # Expected : Configurations values recommended for llap related configs. def test_recommendYARNConfigurations_five_node_manager_llap_configs_updated_2(self): # 3 node managers and yarn.nodemanager.resource.memory-mb": "12288" services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org", "c6402.ambari.apache.org", "c6403.ambari.apache.org", "c6404.ambari.apache.org", "c6405.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6401.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "changed-configurations": [ { u'old_value': u'false', u'type': u'hive-interactive-env', u'name': u'enable_hive_interactive' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'100' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'llap', 'hive.server2.tez.sessions.per.default.queue': '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "341", "yarn.nodemanager.resource.memory-mb": "204800", "yarn.nodemanager.resource.cpu-vcores": '10' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "341" } }, "hive-site": { 'properties': { 'hive.tez.container.size': '341' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) self.assertEqual(configurations['hive-interactive-site']['properties']['hive.server2.tez.sessions.per.default.queue'], '32') self.assertEquals(configurations['hive-interactive-site']['property_attributes']['hive.server2.tez.sessions.per.default.queue'], {'minimum': '1', 'maximum': '32'}) self.assertEqual(configurations['hive-interactive-env']['properties']['num_llap_nodes'], '4') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.yarn.container.mb'], '204600') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.num.executors'], '10') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.memory.size'], '201190') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.enabled'], 'true') self.assertEqual(configurations['hive-interactive-env']['properties']['llap_heap_size'], '2728') self.assertEqual(configurations['hive-interactive-env']['properties']['slider_am_container_size'], '341') # Test 24: (1). 'default' and 'llap' (State : RUNNING) queue exists at root level in capacity-scheduler, and # (2). enable_hive_interactive' is 'on' and (3). configuration change detected for 'hive.server2.tez.sessions.per.default.queue' # Expected : Configurations values recommended for llap related configs. def test_recommendYARNConfigurations_five_node_manager_llap_configs_updated_3(self): # 3 node managers and yarn.nodemanager.resource.memory-mb": "204800" services = { "services": [{ "StackServices": { "service_name": "YARN", }, "Versions": { "stack_version": "2.5" }, "components": [ { "StackServiceComponents": { "component_name": "NODEMANAGER", "hostnames": ["c6401.ambari.apache.org", "c6402.ambari.apache.org", "c6403.ambari.apache.org", "c6404.ambari.apache.org", "c6405.ambari.apache.org"] } } ] }, { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE", "StackServices": { "service_name": "HIVE", "service_version": "1.2.1.2.5", "stack_name": "HDP", "stack_version": "2.5" }, "components": [ { "href": "/api/v1/stacks/HDP/versions/2.5/services/HIVE/components/HIVE_SERVER_INTERACTIVE", "StackServiceComponents": { "advertise_version": "true", "bulk_commands_display_name": "", "bulk_commands_master_component_name": "", "cardinality": "0-1", "component_category": "MASTER", "component_name": "HIVE_SERVER_INTERACTIVE", "custom_commands": ["RESTART_LLAP"], "decommission_allowed": "false", "display_name": "HiveServer2 Interactive", "has_bulk_commands_definition": "false", "is_client": "false", "is_master": "true", "reassign_allowed": "false", "recovery_enabled": "false", "service_name": "HIVE", "stack_name": "HDP", "stack_version": "2.5", "hostnames": ["c6401.ambari.apache.org"] }, "dependencies": [] }, { "StackServiceComponents": { "advertise_version": "true", "cardinality": "1+", "component_category": "SLAVE", "component_name": "NODEMANAGER", "display_name": "NodeManager", "is_client": "false", "is_master": "false", "hostnames": [ "c6401.ambari.apache.org" ] }, "dependencies": [] }, ] } ], "changed-configurations": [ { u'old_value': u'3', u'type': u'hive-interactive-site', u'name': u'hive.server2.tez.sessions.per.default.queue' } ], "configurations": { "capacity-scheduler": { "properties": { "capacity-scheduler": 'yarn.scheduler.capacity.root.default.maximum-capacity=60\n' 'yarn.scheduler.capacity.root.accessible-node-labels=*\n' 'yarn.scheduler.capacity.root.capacity=100\n' 'yarn.scheduler.capacity.root.queues=default,llap\n' 'yarn.scheduler.capacity.maximum-applications=10000\n' 'yarn.scheduler.capacity.root.default.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.default.state=RUNNING\n' 'yarn.scheduler.capacity.maximum-am-resource-percent=1\n' 'yarn.scheduler.capacity.root.default.acl_submit_applications=*\n' 'yarn.scheduler.capacity.root.default.capacity=60\n' 'yarn.scheduler.capacity.root.acl_administer_queue=*\n' 'yarn.scheduler.capacity.node-locality-delay=40\n' 'yarn.scheduler.capacity.queue-mappings-override.enable=false\n' 'yarn.scheduler.capacity.root.llap.user-limit-factor=1\n' 'yarn.scheduler.capacity.root.llap.state=RUNNING\n' 'yarn.scheduler.capacity.root.llap.ordering-policy=fifo\n' 'yarn.scheduler.capacity.root.llap.minimum-user-limit-percent=100\n' 'yarn.scheduler.capacity.root.llap.maximum-capacity=40\n' 'yarn.scheduler.capacity.root.llap.capacity=40\n' 'yarn.scheduler.capacity.root.llap.acl_submit_applications=hive\n' 'yarn.scheduler.capacity.root.llap.acl_administer_queue=hive\n' 'yarn.scheduler.capacity.root.llap.maximum-am-resource-percent=1' } }, "hive-interactive-env": { 'properties': { 'enable_hive_interactive': 'true', 'llap_queue_capacity':'50' } }, "hive-interactive-site": { 'properties': { 'hive.llap.daemon.queue.name': 'llap', 'hive.server2.tez.sessions.per.default.queue': '1' } }, "hive-env": { 'properties': { 'hive_user': 'hive' } }, "yarn-site": { "properties": { "yarn.scheduler.minimum-allocation-mb": "2048", "yarn.nodemanager.resource.memory-mb": "204800", "yarn.nodemanager.resource.cpu-vcores": '3' } }, "tez-interactive-site": { "properties": { "tez.am.resource.memory.mb": "1024" } }, "hive-site": { 'properties': { 'hive.tez.container.size': '1024' } }, } } configurations = { } self.stackAdvisor.recommendYARNConfigurations(configurations, self.clusterData, services, self.hosts) self.assertEqual(configurations['hive-interactive-env']['properties']['num_llap_nodes'], '2') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.yarn.container.mb'], '204800') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.daemon.num.executors'], '3') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.memory.size'], '201728') self.assertEqual(configurations['hive-interactive-site']['properties']['hive.llap.io.enabled'], 'true') self.assertEqual(configurations['hive-interactive-env']['properties']['llap_heap_size'], '2457') self.assertEqual(configurations['hive-interactive-env']['properties']['slider_am_container_size'], '1024') def test_recommendAtlasConfigurations(self): self.maxDiff = None configurations = { "application-properties": { "properties": { "atlas.graph.index.search.solr.zookeeper-url": "" } }, "logsearch-solr-env": { "properties": { "logsearch_solr_znode": "/logsearch" } } } clusterData = { "cpu": 4, "mapMemory": 3000, "amMemory": 2000, "reduceMemory": 2056, "containers": 3, "ramPerContainer": 256 } expected = { 'application-properties': { 'properties': { 'atlas.graph.index.search.solr.zookeeper-url': '{{solr_zookeeper_url}}', } }, "logsearch-solr-env": { "properties": { "logsearch_solr_znode": "/logsearch" } } } services = { "services": [ { "href": "/api/v1/stacks/HDP/versions/2.2/services/ATLAS", "StackServices": { "service_name": "LOGSEARCH", "service_version": "2.6.0.2.2", "stack_name": "HDP", "stack_version": "2.3" }, "components": [ { "StackServiceComponents": { "advertise_version": "false", "cardinality": "1", "component_category": "MASTER", "component_name": "LOGSEARCH_SOLR", "display_name": "solr", "is_client": "false", "is_master": "true", "hostnames": [] }, "dependencies": [] } ] }, ], "configurations": { "application-properties": { "properties": { "atlas.graph.index.search.solr.zookeeper-url": "" } }, "logsearch-solr-env": { "properties": { "logsearch_solr_znode": "/logsearch" } } }, "changed-configurations": [ ] } hosts = { "items" : [ { "href" : "/api/v1/hosts/c6401.ambari.apache.org", "Hosts" : { "cpu_count" : 1, "host_name" : "c6401.ambari.apache.org", "os_arch" : "x86_64", "os_type" : "centos6", "ph_cpu_count" : 1, "public_host_name" : "c6401.ambari.apache.org", "rack_info" : "/default-rack", "total_mem" : 1922680 } } ] } self.stackAdvisor.recommendAtlasConfigurations(configurations, clusterData, services, hosts) self.assertEquals(configurations, expected) services['ambari-server-properties'] = {'java.home': '/usr/jdk64/jdk1.7.3_23'} self.stackAdvisor.recommendAtlasConfigurations(configurations, clusterData, services, hosts) self.assertEquals(configurations, expected) """ Helper method to convert string of key-values to dict. """ def convertToDict(properties): capacitySchedulerProperties = dict() properties = str(properties).split('\n') if properties: for property in properties: key, sep, value = property.partition("=") if key: capacitySchedulerProperties[key] = value return capacitySchedulerProperties

42.275141

268

0.533523

16,163

179,923

5.802821

0.030564

0.08455

0.132326

0.132294

0.949739

0.946903

0.936764

0.928565

0.925963

0.919459

0

0.02197

0.33088

179,923

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269

42.285076

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0.480059

0.319905

0

0.036502

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0.009716

false

0.000788

0.001576

0.000788

0.013655

0

null

0

1

0

null

0

6

cf8c586e6631f46b42cb5ed9d74ef74c9c030dd8

35

py

Python

discord/webhook/sync.py

Harukomaze/disnake

541f5c9623a02be894cd1015dbb344070700cb87

[ "MIT" ]

null

discord/webhook/sync.py

Harukomaze/disnake

541f5c9623a02be894cd1015dbb344070700cb87

[ "MIT" ]

null

discord/webhook/sync.py

Harukomaze/disnake

541f5c9623a02be894cd1015dbb344070700cb87

[ "MIT" ]

null

from disnake.webhook.sync import *

17.5

34

0.8

5

35

5.6

1

0

0.114286

35

1

35

0.903226

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

cfe0253c203b0b4ef21e89f0fb0e0ab7a7c7c51b

512

py

Python

testdata/testfile.py

viswaraavi/Introspect

2884786afbae0399d049fdca90c68ea46846d581

[ "MIT" ]

2

2016-08-13T20:52:37.000Z

2018-11-13T20:08:14.000Z

testdata/testfile.py

viswaraavi/Introspect

2884786afbae0399d049fdca90c68ea46846d581

[ "MIT" ]

null

testdata/testfile.py

viswaraavi/Introspect

2884786afbae0399d049fdca90c68ea46846d581

[ "MIT" ]

null

class A(object): def __init__(self,boo): self.boo=boo def a(self): pass def b(self): pass class B(object): def __init__(self,boo): pass def c(self): pass def d(self): pass class c(object): def __init__(self,boo): pass def e(self): pass def f(self): pass class D(A,B): def __init__(self,boo): pass def g(self): pass def b(self): pass

12.487805

27

0.457031

67

512

3.253731

0.208955

0.293578

0.201835

0.256881

0.619266

0.527523

0.247706

0

0.435547

512

40

28

12.8

0.754325

0

0.607143

0

1

0.428571

false

0.392857

0

0.571429

0

null

1

0

null

0

1

0

1

0

1

0

6

5c66f7bae2354a4448866e4302f7da5eeeaea35c

134

py

Python

conf/script/src/build_system/cmd/setup/_priv/cli/__init__.py

benoit-dubreuil/template-repo-cpp-full-ecosystem

f506dd5e2a61cdd311b6a6a4be4abc59567b4b20

[ "MIT" ]

null

conf/script/src/build_system/cmd/setup/_priv/cli/__init__.py

benoit-dubreuil/template-repo-cpp-full-ecosystem

f506dd5e2a61cdd311b6a6a4be4abc59567b4b20

[ "MIT" ]

113

2021-02-15T19:22:36.000Z

2021-05-07T15:17:42.000Z

conf/script/src/build_system/cmd/setup/_priv/cli/__init__.py

benoit-dubreuil/template-repo-cpp-full-ecosystem

f506dd5e2a61cdd311b6a6a4be4abc59567b4b20

[ "MIT" ]

null

from .colorize import * from .compiler_env import * from .compiler_shell_env import * from .meson import * from .target_info import *

22.333333

33

0.776119

19

134

5.263158

0.473684

0.4

0.36

0

0.149254

134

5

34

26.8

0.877193

0

1

0

true

0

1

0

1

0

1

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null

1

0

1

0

null

0

1

0

1

0

6

5ccb22f7c34198947919605140d97c08d0be927b

163

py

Python

Math/check_if_prime_number.py

IshGill/Leetcode-Guides

90b0f8e69e558926b3d47c988c663b9a4d1c845c

[ "Unlicense" ]

6

2021-02-08T08:00:45.000Z

2021-09-29T11:08:40.000Z

Math/check_if_prime_number.py

IshGill/Leetcode-Guides

90b0f8e69e558926b3d47c988c663b9a4d1c845c

[ "Unlicense" ]

11

2021-02-19T08:56:32.000Z

2021-03-22T04:52:33.000Z

Math/check_if_prime_number.py

IshGill/Leetcode-Guides

90b0f8e69e558926b3d47c988c663b9a4d1c845c

[ "Unlicense" ]

3

2021-02-20T12:03:36.000Z

2021-03-22T13:19:30.000Z

def checkPrime(n): return "{} is not prime".format(n) if len([i for i in range(2, n) if n % i == 0]) >= 1 else "{} is prime".format(n) print(checkPrime(7))

40.75

120

0.588957

31

163

3.096774

0.645161

0.229167

0.25

0

0.031008

0.208589

163

4

121

40.75

0.713178

0

0.161491

0

1

0.333333

false

0

0.333333

0.666667

0.333333

0

null

1

0

1

0

null

0

1

0

1

0

6

7a8448be4215444012a4250d1db2376f4b847cab

170

py

Python

cobra/screen/base.py

emersonmx/cobra-pycurses

bbe99832df4128eb93ae4af4881b56d638006fc5

[ "MIT" ]

null

cobra/screen/base.py

emersonmx/cobra-pycurses

bbe99832df4128eb93ae4af4881b56d638006fc5

[ "MIT" ]

null

cobra/screen/base.py

emersonmx/cobra-pycurses

bbe99832df4128eb93ae4af4881b56d638006fc5

[ "MIT" ]

null

class Screen(object): def show(self): pass def hide(self): pass def dispose(self): pass def update(self, delta): pass

12.142857

28

0.511765

20

170

4.35

0.55

0.275862

0.37931

0

0.394118

170

13

29

13.076923

0.84466

0

0.444444

0

1

0.444444

false

0.444444

0

0.555556

0

1

0

null

1

0

null

0

1

0

1

0

1

0

6

8faf2e2c62cd18ba9901ab9f606eca1c53b7b867

208

py

Python

src/eascheduler/errors/errors.py

spacemanspiff2007/eascheduler

849fe8f43b7bbcb8db3e76c0dda2811eb935cf39

[ "Apache-2.0" ]

null

src/eascheduler/errors/errors.py

spacemanspiff2007/eascheduler

849fe8f43b7bbcb8db3e76c0dda2811eb935cf39

[ "Apache-2.0" ]

3

2021-04-08T11:02:31.000Z

2022-02-14T06:07:56.000Z

src/eascheduler/errors/errors.py

spacemanspiff2007/eascheduler

849fe8f43b7bbcb8db3e76c0dda2811eb935cf39

[ "Apache-2.0" ]

null

class JobAlreadyCanceledException(Exception): pass class UnknownWeekdayError(Exception): pass class FirstRunInThePastError(Exception): pass class BoundaryFunctionError(Exception): pass

13

45

0.774038

16

208

10.0625

0.4375

0.322981

0.335404

0

0.168269

208

15

46

13.866667

0.930636

0

0.5

0

1

0

true

0.5

0

0.5

0

1

0

1

null

1

0

null

0

1

0

6

8fcff00d6088575fd3843a74f877f9ba25a8c311

25

py

Python

guildreader/__init__.py

redmoogle/jsonreader

b37db693a1f382661c44cf756e5ac7a6a3953010

[ "MIT" ]

null

guildreader/__init__.py

redmoogle/jsonreader

b37db693a1f382661c44cf756e5ac7a6a3953010

[ "MIT" ]

null

guildreader/__init__.py

redmoogle/jsonreader

b37db693a1f382661c44cf756e5ac7a6a3953010

[ "MIT" ]

1

2021-04-13T15:09:58.000Z

from .jsonreader import *

25

0.8

3

25

6.666667

1

0

0.12

25

1

25

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

8fd334bd36faa5b25f78339294796b4573e916f8

769

py

Python

misc/first_fit.py

Cryptonite-MIT/Write-ups

d0daa4516aa524f56225357bc46020c4a33db198

[ "MIT" ]

null

misc/first_fit.py

Cryptonite-MIT/Write-ups

d0daa4516aa524f56225357bc46020c4a33db198

[ "MIT" ]

null

misc/first_fit.py

Cryptonite-MIT/Write-ups

d0daa4516aa524f56225357bc46020c4a33db198

[ "MIT" ]

2

2021-10-01T19:40:55.000Z

2021-10-01T19:41:40.000Z

from pwn import * r = remote("chal.imaginaryctf.org", 42003) # for i in range(0,7): r.recvuntil('1: Malloc\n2: Free\n3: Fill a\n4: System b\n> ') r.sendline("1") r.recvuntil("What do I malloc?\n(1) a\n(2) b\n>> ") r.sendline("1") r.recvuntil("1: Malloc\n2: Free\n3: Fill a\n4: System b\n> ") r.sendline("3") r.recvuntil(">> ") r.sendline("/bin/sh") r.recvuntil("1: Malloc\n2: Free\n3: Fill a\n4: System b\n> ") r.sendline("2") r.recvuntil("What do I free?\n(1) a\n(2) b\n>> ") r.sendline("1") r.recvuntil("1: Malloc\n2: Free\n3: Fill a\n4: System b\n> ") r.sendline("1") r.recvuntil("What do I malloc?\n(1) a\n(2) b\n>> ") r.sendline("2") r.recvuntil("1: Malloc\n2: Free\n3: Fill a\n4: System b\n> ") r.sendline("4") r.sendline("whoami") print(r.recvline()) r.close()

29.576923

61

0.629389

157

769

3.082803

0.248408

0.18595

0.049587

0.181818

0.747934

0.733471

0.708678

0

0.060294

0.115735

769

25

62

30.76

0.651471

0.026008

0

0.521739

0

0.51004

0.028112

0

1

0

false

0

0.043478

0

0.043478

0

null

0

1

0

1

0

null

0

6

8fe787b361aae25e4cd41f49281fcfece810ee59

73

py

Python

parcels/compilation/__init__.py

noemieplanat/Copy-parcels-master

21f053b81a9ccdaa5d8ee4f7efd6f01639b83bfc

[ "MIT" ]

202

2017-07-24T23:22:38.000Z

2022-03-22T15:33:46.000Z

parcels/compilation/__init__.py

noemieplanat/Copy-parcels-master

21f053b81a9ccdaa5d8ee4f7efd6f01639b83bfc

[ "MIT" ]

538

2017-06-21T08:04:43.000Z

2022-03-31T14:36:45.000Z

parcels/compilation/__init__.py

noemieplanat/Copy-parcels-master

21f053b81a9ccdaa5d8ee4f7efd6f01639b83bfc

[ "MIT" ]

94

2017-07-05T10:28:55.000Z

2022-03-23T19:46:23.000Z

from .codegenerator import * # noqa from .codecompiler import * # noqa

24.333333

36

0.726027

8

73

6.625

0.625

0.377358

0

0.191781

73

2

37

36.5

0.898305

0.123288

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

8f018c130e62a4cfb313d1e3169db60e67bb0598

36

py

Python

number.py

Jonting416/cs3240-labdemo

11e71e2d034fe9863ee950699ad6352ba276e966

[ "MIT" ]

null

number.py

Jonting416/cs3240-labdemo

11e71e2d034fe9863ee950699ad6352ba276e966

[ "MIT" ]

null

number.py

Jonting416/cs3240-labdemo

11e71e2d034fe9863ee950699ad6352ba276e966

[ "MIT" ]

null

def number(num): return num + 5

12

18

0.611111

6

36

3.666667

0.833333

0

0.038462

0.277778

36

2

19

18

0.807692

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

8f27f01e065f5ace76f6d3b5e5da76e906df0973

79

py

Python

Setup.py

FedDragon1/MCFS

8aa4144c206502c16278a4b5b6e825f8ddf5b1d1

[ "MIT" ]

1

2022-02-24T02:15:10.000Z

Setup.py

FedDragon1/MCFS

8aa4144c206502c16278a4b5b6e825f8ddf5b1d1

[ "MIT" ]

null

Setup.py

FedDragon1/MCFS

8aa4144c206502c16278a4b5b6e825f8ddf5b1d1

[ "MIT" ]

null

from os import system system("pip install svg.path") system("pip install kivy")

26.333333

30

0.772152

13

79

4.692308

0.692308

0.295082

0.52459

0

0.113924

79

3

31

26.333333

0.871429

0

0.45

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

1

0

6

8f479a26ef9aae86d134953cac93046801d90e8c

122

py

Python

abc/124/a/answer.py

TakuyaNoguchi/atcoder

d079402e6fe9c9aaf3a6fc9272331ee71fc497da

[ "MIT" ]

null

abc/124/a/answer.py

TakuyaNoguchi/atcoder

d079402e6fe9c9aaf3a6fc9272331ee71fc497da

[ "MIT" ]

null

abc/124/a/answer.py

TakuyaNoguchi/atcoder

d079402e6fe9c9aaf3a6fc9272331ee71fc497da

[ "MIT" ]

null

A, B = map(int, input().split()) if A == B: print(A + B) elif A > B: print(A + A - 1) else: print(B + B - 1)

13.555556

32

0.45082

24

122

2.291667

0.458333

0.145455

0.254545

0.290909

0

0.02439

0.327869

122

8

33

15.25

0.646341

0

1

0

true

0

0.428571

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

8f5c30b28542e374fd1f9133a3becfa45fb3d4ce

1,481

py

Python

terrascript/vcd/r.py

vutsalsinghal/python-terrascript

3b9fb5ad77453d330fb0cd03524154a342c5d5dc

[ "BSD-2-Clause" ]

null

terrascript/vcd/r.py

vutsalsinghal/python-terrascript

3b9fb5ad77453d330fb0cd03524154a342c5d5dc

[ "BSD-2-Clause" ]

null

terrascript/vcd/r.py

vutsalsinghal/python-terrascript

3b9fb5ad77453d330fb0cd03524154a342c5d5dc

[ "BSD-2-Clause" ]

null

# terrascript/vcd/r.py import terrascript class vcd_network(terrascript.Resource): pass class vcd_network_routed(terrascript.Resource): pass class vcd_network_direct(terrascript.Resource): pass class vcd_network_isolated(terrascript.Resource): pass class vcd_vapp_network(terrascript.Resource): pass class vcd_vapp(terrascript.Resource): pass class vcd_firewall_rules(terrascript.Resource): pass class vcd_dnat(terrascript.Resource): pass class vcd_snat(terrascript.Resource): pass class vcd_edgegateway(terrascript.Resource): pass class vcd_edgegateway_vpn(terrascript.Resource): pass class vcd_vapp_vm(terrascript.Resource): pass class vcd_org(terrascript.Resource): pass class vcd_org_vdc(terrascript.Resource): pass class vcd_org_user(terrascript.Resource): pass class vcd_catalog(terrascript.Resource): pass class vcd_catalog_item(terrascript.Resource): pass class vcd_catalog_media(terrascript.Resource): pass class vcd_inserted_media(terrascript.Resource): pass class vcd_independent_disk(terrascript.Resource): pass class vcd_external_network(terrascript.Resource): pass class vcd_lb_service_monitor(terrascript.Resource): pass class vcd_lb_server_pool(terrascript.Resource): pass class vcd_lb_app_profile(terrascript.Resource): pass class vcd_lb_app_rule(terrascript.Resource): pass class vcd_lb_virtual_server(terrascript.Resource): pass

17.843373

51

0.781904

186

1,481

5.956989

0.209677

0.187726

0.539711

0.631769

0.818592

0.706679

0.064982

0

0.145172

1,481

82

52

18.060976

0.875197

0.013504

0

0.490566

0

1

0

true

0.490566

0.018868

0

0.509434

0

null

0

1

0

null

0

1

0

6

8f5e972efdad8c613c937586d6c013992ec4f437

139

py

Python

__init__.py

vitorpp0/unitsmod

82307ca1b5cabdc931ab37813784804ab0d567db

[ "MIT" ]

null

__init__.py

vitorpp0/unitsmod

82307ca1b5cabdc931ab37813784804ab0d567db

[ "MIT" ]

null

__init__.py

vitorpp0/unitsmod

82307ca1b5cabdc931ab37813784804ab0d567db

[ "MIT" ]

null

import unitsmod.convertDimension as convertDimension import unitsmod.database as database import unitsmod.dimensionClass as dimensionClass

34.75

52

0.892086

15

139

8.266667

0.4

0.33871

0

0.086331

139

3

53

46.333333

0.976378

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

8f7d7d3cc5a7331cfb2f611c52c455dae64c8702

144

py

Python

tests/fixtures/color.py

bcurnow/rfid-security-svc

d3806cb74d3d0cc2623ea425230dc8781ba4d8b4

[ "Apache-2.0" ]

null

tests/fixtures/color.py

bcurnow/rfid-security-svc

d3806cb74d3d0cc2623ea425230dc8781ba4d8b4

[ "Apache-2.0" ]

null

tests/fixtures/color.py

bcurnow/rfid-security-svc

d3806cb74d3d0cc2623ea425230dc8781ba4d8b4

[ "Apache-2.0" ]

null

import pytest from rfidsecuritysvc.model.color import Color @pytest.fixture(scope='session') def default_color(): return Color(0xABCDEF)

16

45

0.777778

18

144

6.166667

0.722222

0

0.007937

0.125

144

8

46

18

0.873016

0

0.048611

0

0.055556

0

1

0.2

true

0

0.4

0.2

0.8

0

1

0

null

0

1

0

null

0

1

0

1

0

6

56aee59ab2c2b4c41fa5c8444707e5bc9d8cfcf1

2,255

py

Python

pycmc/charts/applemusic.py

RomeoDespres/pycmc

7f9abb0e8c076f0cd85f78ce66d3da4a3f1b52ee

[ "MIT" ]

23

2020-05-19T13:19:19.000Z

2022-02-23T12:38:19.000Z

pycmc/charts/applemusic.py

RomeoDespres/pycmc

7f9abb0e8c076f0cd85f78ce66d3da4a3f1b52ee

[ "MIT" ]

9

2020-05-14T17:00:14.000Z

2021-02-08T05:55:41.000Z

pycmc/charts/applemusic.py

RomeoDespres/pycmc

7f9abb0e8c076f0cd85f78ce66d3da4a3f1b52ee

[ "MIT" ]

2

2020-12-03T16:33:33.000Z

2021-04-28T01:03:29.000Z

from .. import utilities APPLE_MUSIC_CHARTS_URL = f"/charts/applemusic" FRIDAY = 4 def tracks(date, country="US", genre="All Genres"): """ Query the charts/applemusic/tracks endpoint for the given date. https://api.chartmetric.com/api/charts/applemusic/tracks **Parameters** - `date`: string date in ISO format %Y-%m-%d - `country`: string country code, e.g. 'US' - `genre`: string genre (see CM docs) **Returns** list of dictionary of tracks on AppleMusic charts """ params = { "date": date, "country_code": country, "genre": genre, "type": "daily", "offset": 0, } urlhandle = f"{APPLE_MUSIC_CHARTS_URL}/tracks" data = utilities.RequestData(urlhandle, params) return utilities.RequestGet(data)["data"] def albums(date, country="US", genre="All Genres"): """ Query the charts/applemusic/albums endpoint for the given date. https://api.chartmetric.com/api/charts/applemusic/albums **Parameters** - `date`: string date in ISO format %Y-%m-%d - `country`: string country code, e.g. 'US' - `genre`: string genre (see CM docs) **Returns** A list of dictionary of albums on AppleMusic charts. """ urlhandle = f"{APPLE_MUSIC_CHARTS_URL}/albums" params = { "date": date, "country_code": country, "genre": genre, } data = utilities.RequestData(urlhandle, params) return utilities.RequestGet(data)["data"] def videos(date, country="US", genre="All Genres"): """ Query the charts/applemusic/videos endpoint for the given date. https://api.chartmetric.com/api/charts/applemusic/videos **Parameters** - `date`: string date in ISO format %Y-%m-%d - `country`: string country code, e.g. 'US' - `genre`: string genre (see CM docs) **Returns** A list of dictionary of videos on AppleMusic charts. """ urlhandle = f"{APPLE_MUSIC_CHARTS_URL}/videos" params = { "date": date, "country_code": country, "genre": genre, } data = utilities.RequestData(urlhandle, params) return utilities.RequestGet(data)["data"]

24.51087

67

0.607539

267

2,255

5.074906

0.224719

0.082657

0.047232

0.056089

0.847232

0.82583

0.794834

0.725461

0

0.001196

0.258537

2,255

91

68

24.78022

0.809211

0.474945

0

0.5625

0

0.224858

0.088235

0

1

0.09375

false

0

0.03125

0

0.21875

0

null

0

1

0

null

0

6

56d8a78508548ee10bba38fa26e090eb5949e13a

33

py

Python

module/functions/__init__.py

Nz-zero/Insira

562e0a1ccb38e99177f7f0861e5fded99bc1cfd0

[ "MIT" ]

null

module/functions/__init__.py

Nz-zero/Insira

562e0a1ccb38e99177f7f0861e5fded99bc1cfd0

[ "MIT" ]

null

module/functions/__init__.py

Nz-zero/Insira

562e0a1ccb38e99177f7f0861e5fded99bc1cfd0

[ "MIT" ]

null

from .dataprep import Data_prep

16.5

32

0.818182

5

33

5.2

1

0

0.151515

33

1

33

0.928571

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

a422e1dc8144852ba0697e35ee337c87c72a3854

36

py

Python

tests/test_fastfantasy.py

kevin-persaud-davis/fastfantasy

90a45e4a49baa2108b29989cc05c23ca4fa5314b

[ "MIT" ]

null

tests/test_fastfantasy.py

kevin-persaud-davis/fastfantasy

90a45e4a49baa2108b29989cc05c23ca4fa5314b

[ "MIT" ]

null

tests/test_fastfantasy.py

kevin-persaud-davis/fastfantasy

90a45e4a49baa2108b29989cc05c23ca4fa5314b

[ "MIT" ]

null

from fastfantasy import fastfantasy

18

35

0.888889

4

36

8

0.75

0

0.111111

36

1

36

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

a4385c51bc7ed4f28f97803ff0ef71379c984e35

152

py

Python

example/services/library.py

TheCaptainCat/flasque

d42deb57572084f513202a32c460186700ce8e0b

[ "MIT" ]

3

2019-10-25T12:21:28.000Z

2020-09-11T13:43:32.000Z

example/services/library.py

TheCaptainCat/bolinette

d42deb57572084f513202a32c460186700ce8e0b

[ "MIT" ]

null

example/services/library.py

TheCaptainCat/bolinette

d42deb57572084f513202a32c460186700ce8e0b

[ "MIT" ]

null

from bolinette.data import service, Service from example.entities import Library @service("library") class LibraryService(Service[Library]): ...

16.888889

43

0.763158

17

152

6.823529

0.588235

0.241379

0

0.131579

152

8

44

19

0.878788

0

0.046053

0

1

0

true

0

0.4

0

0.6

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

a43b1104130b003687e6f13000445f1003a036c9

57

py

Python

avalonbot/__init__.py

AvantiShri/avalon-bot

20916ce670084f27eeaed35a6e44507e9ecf229d

[ "MIT" ]

null

avalonbot/__init__.py

AvantiShri/avalon-bot

20916ce670084f27eeaed35a6e44507e9ecf229d

[ "MIT" ]

null

avalonbot/__init__.py

AvantiShri/avalon-bot

20916ce670084f27eeaed35a6e44507e9ecf229d

[ "MIT" ]

null

from . import cards from . import game from . import bot

14.25

19

0.736842

9

57

4.666667

0.555556

0.714286

0

0.210526

57

3

20

19

0.933333

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

a4415d7e6eb2a1d6fc57fc3bd0ed10f7f8c0927a

24

py

Python

elastico/__init__.py

klorenz/python-elastico

9a39e6cfe33d3081cc52424284c19e9698343006

[ "MIT" ]

null

elastico/__init__.py

klorenz/python-elastico

9a39e6cfe33d3081cc52424284c19e9698343006

[ "MIT" ]

null

elastico/__init__.py

klorenz/python-elastico

9a39e6cfe33d3081cc52424284c19e9698343006

[ "MIT" ]

null

from . import pyaml_ext

12

23

0.791667

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6

a4506b05ad0b6ebb26334d6a3a9b8a4cb578ada8

28

py

Python

eddl/backend/__init__.py

salvacarrion/pyeddl

56d1e4378844d12c064f168f4541900684079c4b

[ "MIT" ]

null

eddl/backend/__init__.py

salvacarrion/pyeddl

56d1e4378844d12c064f168f4541900684079c4b

[ "MIT" ]

null

eddl/backend/__init__.py

salvacarrion/pyeddl

56d1e4378844d12c064f168f4541900684079c4b

[ "MIT" ]

null

from .eddl_backend import *

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6

f12775fd5a8342524d1cfb232339eac47b3b3c99

20,754

py

Python

tests/ut/python/parallel/test_stridedslice.py

httpsgithu/mindspore

c29d6bb764e233b427319cb89ba79e420f1e2c64

[ "Apache-2.0" ]

1

2022-02-23T09:13:43.000Z

tests/ut/python/parallel/test_stridedslice.py

949144093/mindspore

c29d6bb764e233b427319cb89ba79e420f1e2c64

[ "Apache-2.0" ]

null

tests/ut/python/parallel/test_stridedslice.py

949144093/mindspore

c29d6bb764e233b427319cb89ba79e420f1e2c64

[ "Apache-2.0" ]

null

# Copyright 2020 Huawei 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 numpy as np import pytest import mindspore as ms from mindspore import context, Tensor, Parameter from mindspore.common.api import _cell_graph_executor from mindspore.nn import Cell, TrainOneStepCell, Momentum from mindspore.ops import operations as P from parallel.utils.utils import ParallelValidator class Net(Cell): def __init__(self, weight, w2, begin, end, strides, strategy1=None, strategy2=None, is_parameter=True, begin_mask=0, end_mask=0, ellipsis_mask=0, new_axis_mask=0, shrink_axis_mask=0): super().__init__() self.mul = P.Mul().shard(strategy1) self.strided_slice = P.StridedSlice(begin_mask=begin_mask, end_mask=end_mask, ellipsis_mask=ellipsis_mask, new_axis_mask=new_axis_mask, shrink_axis_mask=shrink_axis_mask).shard(strategy2) if is_parameter: self.weight = Parameter(weight, "w1") else: self.weight = weight self.mul2 = P.Mul() self.weight2 = Parameter(w2, "w2") self.begin = begin self.end = end self.strides = strides def construct(self, x, b): out = self.strided_slice(self.weight, self.begin, self.end, self.strides) out = self.mul(x, out) out = self.mul2(out, self.weight2) return out class Net2(Cell): def __init__(self, weight2, begin, end, strides, strategy1=None, strategy2=None, begin_mask=0, end_mask=0, ellipsis_mask=0, new_axis_mask=0, shrink_axis_mask=0): super().__init__() self.mul = P.Mul().shard(strategy1) self.strided_slice = P.StridedSlice(begin_mask=begin_mask, end_mask=end_mask, ellipsis_mask=ellipsis_mask, new_axis_mask=new_axis_mask, shrink_axis_mask=shrink_axis_mask).shard(strategy2) self.weight2 = Parameter(weight2, "w2") self.begin = begin self.end = end self.strides = strides def construct(self, x, b): out = self.mul(x, self.weight2) out = self.strided_slice(out, self.begin, self.end, self.strides) return out _x1 = Tensor(np.ones([128, 64, 1]), dtype=ms.float32) _x2 = Tensor(np.ones([1, 64, 32, 32]), dtype=ms.float32) _x3 = Tensor(np.ones([64, 32]), dtype=ms.float32) _w1 = Tensor(np.ones([256, 64, 32]), dtype=ms.float32) _w2 = Tensor(np.ones([128, 64, 1]), dtype=ms.float32) _w3 = Tensor(np.ones([1, 64, 32, 32]), dtype=ms.float32) _b1 = Tensor(np.ones([128, 64, 32]), dtype=ms.float32) _b2 = Tensor(np.ones([1, 64, 32, 32]), dtype=ms.float32) def compile_net(net, _x1, _b1): optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9) train_net = TrainOneStepCell(net, optimizer) train_net.set_auto_parallel() train_net.set_train() _cell_graph_executor.compile(train_net, _x1, _b1) context.reset_auto_parallel_context() def compile_net_utils(net: Cell, *inputs): net.set_auto_parallel() net.set_train() phase, _ = _cell_graph_executor.compile(net, *inputs, auto_parallel_mode=True) context.reset_auto_parallel_context() return phase def test_stridedslice_no_fully_fetch_split_error(): context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((2, 2, 2), (2, 2, 2)) strategy2 = ((2, 2, 2),) net = Net(_w1, _w2, (0, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=True) with pytest.raises(RuntimeError): compile_net(net, _x1, _b1) def test_stridedslice_strides_no_1_split_error(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with strides no 1 split in semi auto parallel. Expectation: compile error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((2, 2, 2), (2, 2, 2)) strategy2 = ((1, 2, 2),) net = Net(_w1, _w2, (0, 0, 0), (128, 64, 32), (1, 1, 2), strategy1, strategy2, is_parameter=True) with pytest.raises(RuntimeError): compile_net(net, _x1, _b1) def test_stridedslice_begin_size_smaller(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with begin size is smaller in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 1), (1, 4, 2)) strategy2 = ((1, 4, 2),) net = Net(_w1, _w2, (0, 0), (128, 64), (1, 1), strategy1, strategy2, is_parameter=True) compile_net(net, _x1, _b1) def test_stridedslice_parameter(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice of parameter in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 1), (1, 4, 2)) strategy2 = ((1, 4, 2),) net = Net(_w1, _w2, (0, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=True) compile_net(net, _x1, _b1) def test_stridedslice_begin_mask_no_0_split_parameter(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with begin mask no 0 split in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 1), (1, 4, 2)) strategy2 = ((1, 4, 2),) net = Net(_w1, _w2, (0, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=True, begin_mask=1) compile_net(net, _x1, _b1) def test_stridedslice_end_mask_no_0_parameter(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with end mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 1), (1, 4, 2)) strategy2 = ((1, 4, 2),) net = Net(_w1, _w2, (127, 0, 0), (128, 63, 32), (1, 1, 1), strategy1, strategy2, is_parameter=True, begin_mask=1, end_mask=2) compile_net(net, _x1, _b1) def test_stridedslice_ellipsis_mask_no_0_parameter(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with ellipsis mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 1), (1, 4, 2)) strategy2 = ((1, 4, 2),) net = Net(_w1, _w2, (127, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=True, begin_mask=1, end_mask=2, ellipsis_mask=4) compile_net(net, _x1, _b1) def test_stridedslice_new_axis_mask_no_0_parameter(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with new axis mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 2, 1), (1, 4, 2, 1)) strategy2 = ((1, 1, 4),) net = Net(_w1, _w3, (0, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=True, new_axis_mask=1) compile_net(net, _x2, _b2) def test_stridedslice_shrink_axis_mask_no_0_parameter(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with shrink axis mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 2), (1, 2)) strategy2 = ((1, 4, 1),) net = Net(_w1, _w2, (0, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=True, shrink_axis_mask=1) compile_net(net, _x3, _b1) def test_stridedslice_tensor(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice of tensor in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 1), (1, 4, 2)) strategy2 = ((1, 4, 2),) net = Net(_w1, _w2, (0, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=False) compile_net(net, _x1, _b1) def test_stridedslice_begin_mask_no_0_tensor(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with begin mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 1), (1, 4, 2)) strategy2 = ((1, 4, 2),) net = Net(_w1, _w2, (127, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=False, begin_mask=1) compile_net(net, _x1, _b1) def test_stridedslice_end_mask_no_0_tensor(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with end mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 1), (1, 4, 2)) strategy2 = ((1, 4, 2),) net = Net(_w1, _w2, (0, 0, 0), (128, 63, 32), (1, 1, 1), strategy1, strategy2, is_parameter=False, end_mask=2) compile_net(net, _x1, _b1) def test_stridedslice_ellipsis_mask_no_0_tensor(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with ellipsis mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 1), (1, 4, 2)) strategy2 = ((1, 4, 2),) net = Net(_w1, _w2, (127, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=False, begin_mask=1, end_mask=2, ellipsis_mask=4) compile_net(net, _x1, _b1) def test_stridedslice_new_axis_mask_no_0_tensor(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with new axis mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 2, 1), (1, 4, 2, 1)) strategy2 = ((1, 1, 4),) net = Net(_w1, _w3, (0, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=False, new_axis_mask=1) compile_net(net, _x2, _b2) def test_stridedslice_shrink_axis_mask_no_0_tensor(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with shrink axis mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 2), (1, 2)) strategy2 = ((1, 4, 1),) net = Net(_w1, _w2, (0, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=False, shrink_axis_mask=1) compile_net(net, _x3, _b1) def test_stridedslice_parameter_no_full_split(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with no full split in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 1), (1, 4, 2)) strategy2 = ((1, 2, 2),) net = Net(_w1, _w2, (0, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=True) compile_net(net, _x1, _b1) def test_stridedslice_output(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice of output in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 8, 1), (1, 8, 1)) strategy2 = ((1, 8, 1),) net = Net2(_w2, (0, 0, 0), (64, 64, 1), (1, 1, 1), strategy1, strategy2) compile_net(net, _x1, _b1) def test_stridedslice_begin_mask_no_0_output(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with begin mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 8, 1), (1, 8, 1)) strategy2 = ((1, 8, 1),) net = Net2(_w2, (61, 0, 0), (64, 64, 1), (1, 1, 1), strategy1, strategy2, begin_mask=1) compile_net(net, _x1, _b1) def test_stridedslice_end_mask_no_0_output(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with end mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 8, 1), (1, 8, 1)) strategy2 = ((1, 8, 1),) net = Net2(_w2, (0, 0, 0), (64, 63, 1), (1, 1, 1), strategy1, strategy2, end_mask=2) compile_net(net, _x1, _b1) def test_stridedslice_ellipsis_mask_no_0_output(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with ellipsis mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 8, 1), (1, 8, 1)) strategy2 = ((1, 8, 1),) net = Net2(_w2, (63, 0, 0), (64, 63, 1), (1, 1, 1), strategy1, strategy2, begin_mask=1, end_mask=2, ellipsis_mask=4) compile_net(net, _x1, _b1) def test_stridedslice_new_axis_mask_no_0_output(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with new axis mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 8, 1), (1, 8, 1)) strategy2 = ((8, 1, 1),) net = Net2(_w2, (0, 0, 0), (64, 64, 1), (1, 1, 1), strategy1, strategy2, new_axis_mask=1) compile_net(net, _x1, _b1) def test_stridedslice_shrink_axis_mask_no_0_output(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with shrink axis mask no 0 in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 8, 1), (1, 8, 1)) strategy2 = ((1, 8, 1),) net = Net2(_w2, (0, 0, 0), (64, 64, 1), (1, 1, 1), strategy1, strategy2, shrink_axis_mask=1) compile_net(net, _x1, _b1) def test_stridedslice_output_no_full_split(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with no full split in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 8, 1), (1, 8, 1)) strategy2 = ((1, 4, 1),) net = Net2(_w2, (0, 0, 0), (64, 64, 1), (1, 1, 1), strategy1, strategy2) compile_net(net, _x1, _b1) def test_stridedslice_no_strategy(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with no strategy in semi auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 8, 1), (1, 8, 1)) strategy2 = None net = Net2(_w2, (0, 0, 0), (128, 64, 1), (1, 1, 1), strategy1, strategy2) compile_net(net, _x1, _b1) def test_stridedslice_begin_mask_no_0_no_strategy(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with begin mask no 0 in auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 8, 1), (1, 8, 1)) strategy2 = None net = Net2(_w2, (127, 0, 0), (128, 64, 1), (1, 1, 1), strategy1, strategy2, begin_mask=1) compile_net(net, _x1, _b1) def test_stridedslice_auto_parallel(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice in auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=8, global_rank=0) net = Net2(_w2, (0, 0, 0), (32, 64, 1), (1, 1, 1)) compile_net(net, _x1, _b1) def test_stridedslice_begin_mask_no_0_auto_parallel(): """ Feature: distribute operator stridedslice in auto parallel mode. Description: test stridedslice with begin mask no 0 in auto parallel. Expectation: compile done without error. """ context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=8, global_rank=0) net = Net2(_w2, (29, 0, 0), (32, 64, 1), (1, 1, 1), begin_mask=1) compile_net(net, _x1, _b1) def test_stridedslice_layout(): """ Features: StridedSlice Description: validate layout and structure Expectation: No raise RuntimeError """ context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0) strategy1 = ((1, 4, 1), (1, 4, 2)) strategy2 = ((1, 4, 2),) net = Net(_w1, _w2, (127, 0, 0), (128, 64, 32), (1, 1, 1), strategy1, strategy2, is_parameter=True, begin_mask=1, end_mask=2, ellipsis_mask=4) phase = compile_net_utils(net, _x1, _b1) validator = ParallelValidator(net, phase) # check layout features_expect_layout = ([4, 2], [-1, 1, 0], [256, 16, 16], 0, True, '') assert validator.check_parameter_layout('w1', features_expect_layout) # check attrs roi_expect_attrs = {'begin_mask': 1, 'end_mask': 2, 'ellipsis_mask': 4} assert validator.check_node_attrs('StridedSlice-1', roi_expect_attrs) # check inputs roi_expect_inputs = ['Load-0', 'out((127, 0, 0))', 'out((128, 64, 32))', 'out((1, 1, 1))'] assert validator.check_node_inputs('StridedSlice-1', roi_expect_inputs) # check sub_graph sub_graph = { 'StridedSlice-1': ['Load-0', 'out((127, 0, 0))', 'out((128, 64, 32))', 'out((1, 1, 1))'], 'Mul-0': ['Reshape-1', 'StridedSlice-1'], 'AllGather-2': ['Reshape-2'], 'Split-1': ['AllGather-2'], 'TupleGetItem-3': ['Split-1', 0], 'TupleGetItem-4': ['Split-1', 1], 'TupleGetItem-5': ['Split-1', 2], 'TupleGetItem-6': ['Split-1', 3], 'MakeTuple-2': ['TupleGetItem-3', 'TupleGetItem-4', 'TupleGetItem-5', 'TupleGetItem-6'], 'Concat-1': ['MakeTuple-2'] } assert validator.check_graph_structure(sub_graph)

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0.104656

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0

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null

0

6

f18833ab2e03af35fc67a4690feb71c126f206a0

11,971

py

Python

src/jengaapi/send_money_services.py

MainaKamau92/JengaAPIPythonWrapper

b48682fc045e74c19d674ea83f905f7c5d55230b

[ "BSD-2-Clause" ]

null

src/jengaapi/send_money_services.py

MainaKamau92/JengaAPIPythonWrapper

b48682fc045e74c19d674ea83f905f7c5d55230b

[ "BSD-2-Clause" ]

null

src/jengaapi/send_money_services.py

MainaKamau92/JengaAPIPythonWrapper

b48682fc045e74c19d674ea83f905f7c5d55230b

[ "BSD-2-Clause" ]

null

import json import requests from . import BASE_URL from .exceptions import handle_response, generate_reference class SendMoneyService: def __init__(self, token): self.token = token self.headers = { 'Content-Type': 'application/json', 'Authorization': self.token } self.reference_no = generate_reference() @staticmethod def _generate_payload_source(country_code, source_name, source_account_number): return dict( countryCode=country_code, name=source_name, accountNumber=source_account_number ) @staticmethod def _generate_payload_destination(country_code, destination_name): return dict( type=None, countryCode=country_code, name=destination_name, ) @staticmethod def _generate_payload_transfer(transfer_amount, currency_code, reference_no, transfer_date, description): return dict( type=None, amount=str(transfer_amount), currencyCode=currency_code, reference=reference_no, date=transfer_date.strftime("%Y-%m-%d"), description=description ) @staticmethod def _send_request(headers, payload): url = BASE_URL + f'transaction/v2/remittance' response = requests.post(url, headers=headers, data=json.dumps(payload)) formatted_response = handle_response(response) return formatted_response @staticmethod def _redundant_params(kwargs): country_code = kwargs.get("country_code") source_name = kwargs.get("source_name") source_account_number = kwargs.get("source_account_number") destination_name = kwargs.get("destination_name") transfer_amount = kwargs.get("transfer_amount") currency_code = kwargs.get("currency_code") reference_no = kwargs.get("reference_no") transfer_date = kwargs.get("transfer_date") description = kwargs.get("description") return (country_code, source_name, source_account_number, destination_name, transfer_amount, currency_code, reference_no, transfer_date, description) def send_within_equity(self, signature, **kwargs): destination_account_number = kwargs.get("destination_account_number") (country_code, source_name, source_account_number, destination_name, transfer_amount, currency_code, reference_no, transfer_date, description) = self._redundant_params(kwargs) payload_destination = self._generate_payload_destination(country_code, destination_name) payload_source = self._generate_payload_source(country_code, source_name, source_account_number) payload_transfer = self._generate_payload_transfer(transfer_amount, currency_code, reference_no, transfer_date, description) self.headers["signature"] = signature payload_destination["type"] = "bank" payload_destination["accountNumber"] = destination_account_number payload_transfer["type"] = "InternalFundsTransfer" payload = dict(source=payload_source, destination=payload_destination, transfer=payload_transfer) return self._send_request(headers=self.headers, payload=payload) def send_to_mobile_wallets(self, signature, **kwargs): wallet_name = kwargs.get("wallet_name") destination_mobile_number = kwargs.get("destination_mobile_number") (country_code, source_name, source_account_number, destination_name, transfer_amount, currency_code, reference_no, transfer_date, description) = self._redundant_params(kwargs) payload_destination = self._generate_payload_destination(country_code, destination_name) payload_source = self._generate_payload_source(country_code, source_name, source_account_number) payload_transfer = self._generate_payload_transfer(transfer_amount, currency_code, reference_no, transfer_date, description) self.headers["signature"] = signature payload_destination["type"] = "mobile" payload_destination["mobileNumber"] = destination_mobile_number payload_destination["walletName"] = wallet_name payload_transfer["type"] = "MobileWallet" payload = dict(source=payload_source, destination=payload_destination, transfer=payload_transfer) return self._send_request(headers=self.headers, payload=payload) def send_rtgs(self, signature, **kwargs): destination_account_number = kwargs.get("destination_account_number") bank_code = kwargs.get("bank_code") (country_code, source_name, source_account_number, destination_name, transfer_amount, currency_code, reference_no, transfer_date, description) = self._redundant_params(kwargs) payload_destination = self._generate_payload_destination(country_code, destination_name) payload_source = self._generate_payload_source(country_code, source_name, source_account_number) payload_transfer = self._generate_payload_transfer(transfer_amount, currency_code, reference_no, transfer_date, description) self.headers["signature"] = signature payload_destination["type"] = "bank" payload_destination["bankCode"] = bank_code payload_destination["accountNumber"] = destination_account_number payload_transfer["type"] = "RTGS" payload = dict(source=payload_source, destination=payload_destination, transfer=payload_transfer) return self._send_request(headers=self.headers, payload=payload) def send_swift(self, signature, **kwargs): bank_bic = kwargs.get('bank_bic') address_line = kwargs.get('address_line') charge_option = kwargs.get('charge_option') destination_account_number = kwargs.get('destination_account_number') (country_code, source_name, source_account_number, destination_name, transfer_amount, currency_code, reference_no, transfer_date, description) = self._redundant_params(kwargs) payload_destination = self._generate_payload_destination(country_code, destination_name) payload_source = self._generate_payload_source(country_code, source_name, source_account_number) payload_transfer = self._generate_payload_transfer(transfer_amount, currency_code, reference_no, transfer_date, description) self.headers["signature"] = signature payload_destination["type"] = "bank" payload_destination["bankBic"] = bank_bic payload_destination["accountNumber"] = destination_account_number payload_destination["addressline1"] = address_line payload_transfer["type"] = "SWIFT" payload_transfer["chargeOption"] = charge_option payload = dict(source=payload_source, destination=payload_destination, transfer=payload_transfer) return self._send_request(headers=self.headers, payload=payload) def send_eft(self, signature, **kwargs): bank_code = kwargs.get('bank_code') branch_code = kwargs.get('branch_code') destination_account_number = kwargs.get('destination_account_number') # signature = API.signature((self.reference_no, self.source_account_number, # destination_account_number, self.transfer_amount, # bank_code)) (country_code, source_name, source_account_number, destination_name, transfer_amount, currency_code, reference_no, transfer_date, description) = self._redundant_params(kwargs) payload_destination = self._generate_payload_destination(country_code, destination_name) payload_source = self._generate_payload_source(country_code, source_name, source_account_number) payload_transfer = self._generate_payload_transfer(transfer_amount, currency_code, reference_no, transfer_date, description) self.headers["signature"] = signature payload_destination["type"] = "bank" payload_destination["bankCode"] = bank_code payload_destination["branchCode"] = branch_code payload_destination["accountNumber"] = destination_account_number payload_transfer["type"] = "EFT" payload = dict(source=payload_source, destination=payload_destination, transfer=payload_transfer) return self._send_request(headers=self.headers, payload=payload) def send_pesalink_to_bank_account(self, signature, **kwargs): bank_code = kwargs.get('bank_code') mobile_number = kwargs.get('mobile_number') destination_account_number = kwargs.get('destination_account_number') # signature = API.signature((self.transfer_amount, self.currency_code, self.reference_no, # self.destination_name, self.source_account_number)) (country_code, source_name, source_account_number, destination_name, transfer_amount, currency_code, reference_no, transfer_date, description) = self._redundant_params(kwargs) payload_destination = self._generate_payload_destination(country_code, destination_name) payload_source = self._generate_payload_source(country_code, source_name, source_account_number) payload_transfer = self._generate_payload_transfer(transfer_amount, currency_code, reference_no, transfer_date, description) self.headers["signature"] = signature payload_destination["type"] = "bank" payload_destination["bankCode"] = bank_code payload_destination["mobileNumber"] = mobile_number payload_destination["accountNumber"] = destination_account_number payload_transfer["type"] = "PesaLink" payload = dict(source=payload_source, destination=payload_destination, transfer=payload_transfer) return self._send_request(headers=self.headers, payload=payload) def send_pesalink_to_mobile_number(self, signature, **kwargs): destination_mobile_number = kwargs.get("destination_mobile_number") bank_code = kwargs.get("bank_code") # signature = API.signature((self.transfer_amount, self.currency_code, # self.reference_no, self.destination_name, # self.source_account_number)) (country_code, source_name, source_account_number, destination_name, transfer_amount, currency_code, reference_no, transfer_date, description) = self._redundant_params(kwargs) payload_destination = self._generate_payload_destination(country_code, destination_name) payload_source = self._generate_payload_source(country_code, source_name, source_account_number) payload_transfer = self._generate_payload_transfer(transfer_amount, currency_code, reference_no, transfer_date, description) self.headers["signature"] = signature payload_destination["type"] = "mobile" payload_destination["bankCode"] = bank_code payload_destination["mobileNumber"] = destination_mobile_number payload = dict(source=payload_source, destination=payload_destination, transfer=payload_transfer) return self._send_request(headers=self.headers, payload=payload)

52.047826

115

0.681564

1,182

11,971

6.5

0.076142

0.105428

0.054406

0.046466

0.78524

0.77704

0.748275

0.72719

0.698816

0

0.00022

0.24008

11,971

229

116

52.275109

0.844344

0.045944

0

0.631016

1

0

0.075885

0.021644

0

1

0.069519

false

0

0.02139

0.016043

0.160428

0

null

0

1

0

1

0

null

0

6

2d01d24333ce1d97700190a60ce6a9d6089a21f9

2,356

py

Python

tests/test_watcher.py

FXTD-ODYSSEY/pyuiw

9613d0ff3cc1187a0aa854ce17fd14245751d969

[ "MIT" ]

null

tests/test_watcher.py

FXTD-ODYSSEY/pyuiw

9613d0ff3cc1187a0aa854ce17fd14245751d969

[ "MIT" ]

null

tests/test_watcher.py

FXTD-ODYSSEY/pyuiw

9613d0ff3cc1187a0aa854ce17fd14245751d969

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ """ # Import future modules from __future__ import absolute_import from __future__ import division from __future__ import print_function # Import built-in modules from pathlib import Path import subprocess from textwrap import dedent import time # Import third-party modules import pytest __author__ = "timmyliang" __email__ = "820472580@qq.com" __date__ = "2021-11-28 20:13:19" def test_watch_files(runner, get_ui): custom, custom_py = get_ui("custom") blank, blank_py = get_ui("blank") basic, basic_py = get_ui("basic") blank_button, blank_button_py = get_ui("blank_button") args = ["-w", custom, blank, basic] process = runner(args, subprocess.Popen) time.sleep(3) assert custom_py.is_file() assert blank_py.is_file() assert basic_py.is_file() with open(blank_py, encoding="utf8") as f: before_py = f.read() with open(blank_button, encoding="utf8") as f: button_content = f.read() with open(blank, encoding="utf8") as f: content = f.read() with open(blank, "w", encoding="utf8") as f: f.write(button_content) time.sleep(2) with open(blank_py, encoding="utf8") as f: after_py = f.read() assert before_py != after_py process.terminate() with open(blank, "w", encoding="utf8") as f: f.write(content) def test_watch_dir_and_exclude(runner, get_ui, UI_DIR): custom, custom_py = get_ui("custom") blank, blank_py = get_ui("blank") basic, basic_py = get_ui("basic") blank_button, blank_button_py = get_ui("blank_button") args = ["-w", str(UI_DIR), "-e", "*custom*"] process = runner(args, subprocess.Popen) time.sleep(3) assert not custom_py.is_file() assert blank_py.is_file() assert basic_py.is_file() with open(blank_py, encoding="utf8") as f: before_py = f.read() with open(blank_button, encoding="utf8") as f: button_content = f.read() with open(blank, encoding="utf8") as f: content = f.read() with open(blank, "w", encoding="utf8") as f: f.write(button_content) time.sleep(2) with open(blank_py, encoding="utf8") as f: after_py = f.read() assert before_py != after_py process.terminate() with open(blank, "w", encoding="utf8") as f: f.write(content)

24.040816

58

0.652801

344

2,356

4.215116

0.218023

0.066207

0.107586

0.124138

0.728276

0.662069

0

0.021657

0.216044

2,356

97

59

24.28866

0.7634

0.039898

0

0.730159

0

0.074255

0

0.126984

1

0.031746

false

0

0.126984

0

0.15873

0.015873

0

null

0

1

0

1

0

null

0

6

2d0a1a263077e01c5cffaa0a1b194e86edf80b30

35

py

Python

branch_test1_1.py

11pikachu/starter-workflows

c007143a1d9853f2a8b98bff385fd8dcb6f3af6e

[ "MIT" ]

null

branch_test1_1.py

11pikachu/starter-workflows

c007143a1d9853f2a8b98bff385fd8dcb6f3af6e

[ "MIT" ]

null

branch_test1_1.py

11pikachu/starter-workflows

c007143a1d9853f2a8b98bff385fd8dcb6f3af6e

[ "MIT" ]

1

2020-05-20T05:58:03.000Z

print('branch test1 first commit')

17.5

34

0.771429

5

35

5.4

1

0

0.032258

0.114286

35

1

35

0.83871

0

0.714286

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6