xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

3d944c526977c961500124b5b555f2a9016560a1

14,812

py

Python

tests/test_caltrack_hourly.py

Morilor/eemeter

312525bb89119b877d0d905d45c167052b7275f5

[ "Apache-2.0" ]

161

2016-08-22T22:38:38.000Z

2022-03-24T10:04:05.000Z

tests/test_caltrack_hourly.py

Morilor/eemeter

312525bb89119b877d0d905d45c167052b7275f5

[ "Apache-2.0" ]

313

2016-09-12T05:36:28.000Z

2022-01-07T21:20:11.000Z

tests/test_caltrack_hourly.py

Morilor/eemeter

312525bb89119b877d0d905d45c167052b7275f5

[ "Apache-2.0" ]

58

2016-08-22T22:49:53.000Z

2022-01-18T12:18:07.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- """ Copyright 2014-2019 OpenEEmeter contributors Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import json import numpy as np import pandas as pd import pytest from eemeter.caltrack.hourly import ( caltrack_hourly_fit_feature_processor, caltrack_hourly_prediction_feature_processor, fit_caltrack_hourly_model_segment, fit_caltrack_hourly_model, ) from eemeter.features import ( compute_time_features, compute_temperature_features, compute_usage_per_day_feature, merge_features, ) @pytest.fixture def segmented_data(): index = pd.date_range(start="2017-01-01", periods=24, freq="H", tz="UTC") time_features = compute_time_features(index) segmented_data = pd.DataFrame( { "hour_of_week": time_features.hour_of_week, "temperature_mean": np.linspace(0, 100, 24), "meter_value": np.linspace(10, 70, 24), "weight": np.ones((24,)), }, index=index, ) return segmented_data @pytest.fixture def occupancy_lookup(): index = pd.Categorical(range(168)) occupancy = pd.Series([i % 2 == 0 for i in range(168)], index=index) return pd.DataFrame( {"dec-jan-feb-weighted": occupancy, "jan-feb-mar-weighted": occupancy} ) @pytest.fixture def occupied_temperature_bins(): bins = pd.Series([True, True, True], index=[30, 60, 90]) return pd.DataFrame({"dec-jan-feb-weighted": bins, "jan-feb-mar-weighted": bins}) @pytest.fixture def unoccupied_temperature_bins(): bins = pd.Series([False, True, True], index=[30, 60, 90]) return pd.DataFrame({"dec-jan-feb-weighted": bins, "jan-feb-mar-weighted": bins}) def test_caltrack_hourly_fit_feature_processor( segmented_data, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ): result = caltrack_hourly_fit_feature_processor( "dec-jan-feb-weighted", segmented_data, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ) assert list(result.columns) == [ "meter_value", "hour_of_week", "bin_0_occupied", "bin_1_occupied", "bin_2_occupied", "bin_3_occupied", "bin_0_unoccupied", "bin_1_unoccupied", "bin_2_unoccupied", "weight", ] assert result.shape == (24, 10) assert round(result.sum().sum(), 2) == 5916.0 def test_caltrack_hourly_prediction_feature_processor( segmented_data, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ): result = caltrack_hourly_prediction_feature_processor( "dec-jan-feb-weighted", segmented_data, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ) assert list(result.columns) == [ "hour_of_week", "bin_0_occupied", "bin_1_occupied", "bin_2_occupied", "bin_3_occupied", "bin_0_unoccupied", "bin_1_unoccupied", "bin_2_unoccupied", "weight", ] assert result.shape == (24, 9) assert round(result.sum().sum(), 2) == 4956.0 @pytest.fixture def segmented_design_matrices( segmented_data, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ): return { "dec-jan-feb-weighted": caltrack_hourly_fit_feature_processor( "dec-jan-feb-weighted", segmented_data, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ) } def test_fit_caltrack_hourly_model_segment(segmented_design_matrices): segment_name = "dec-jan-feb-weighted" segment_data = segmented_design_matrices[segment_name] segment_model = fit_caltrack_hourly_model_segment(segment_name, segment_data) assert segment_model.formula == ( "meter_value ~ C(hour_of_week) - 1 + bin_0_occupied" " + bin_1_occupied + bin_2_occupied + bin_3_occupied" " + bin_0_unoccupied + bin_1_unoccupied + bin_2_unoccupied" ) assert segment_model.segment_name == "dec-jan-feb-weighted" assert len(segment_model.model_params.keys()) == 31 assert segment_model.model is not None assert segment_model.warnings is not None prediction = segment_model.predict(segment_data) assert round(prediction.sum(), 2) == 960.0 @pytest.fixture def temps(): index = pd.date_range(start="2017-01-01", periods=24, freq="H", tz="UTC") temps = pd.Series(np.linspace(0, 100, 24), index=index) return temps def test_fit_caltrack_hourly_model( segmented_design_matrices, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, temps, ): segmented_model_results = fit_caltrack_hourly_model( segmented_design_matrices, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ) assert segmented_model_results.model.segment_models is not None assert str(segmented_model_results).startswith("CalTRACKHourlyModelResults") prediction = segmented_model_results.predict(temps.index, temps).result def test_serialize_caltrack_hourly_model( segmented_design_matrices, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, temps, ): segmented_model = fit_caltrack_hourly_model( segmented_design_matrices, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ) assert json.dumps(segmented_model.json()) @pytest.fixture def segmented_data_nans(): num_periods = 200 index = pd.date_range(start="2017-01-01", periods=num_periods, freq="H", tz="UTC") time_features = compute_time_features(index) segmented_data = pd.DataFrame( { "hour_of_week": time_features.hour_of_week, "temperature_mean": np.linspace(0, 100, num_periods), "meter_value": np.linspace(10, 70, num_periods), "weight": np.ones((num_periods,)), }, index=index, ) return segmented_data @pytest.fixture def occupancy_lookup_nans(): index = pd.Categorical(range(168)) occupancy = pd.Series([i % 2 == 0 for i in range(168)], index=index) occupancy_nans = pd.Series([np.nan for i in range(168)], index=index) return pd.DataFrame( { "dec-jan-feb-weighted": occupancy, "jan-feb-mar-weighted": occupancy, "apr-may-jun-weighted": occupancy_nans, } ) @pytest.fixture def temperature_bins_nans(): bins = pd.Series([True, True, True], index=[30, 60, 90]) bins_nans = pd.Series([False, False, False], index=[30, 60, 90]) return pd.DataFrame( { "dec-jan-feb-weighted": bins, "jan-feb-mar-weighted": bins, "apr-may-jun-weighted": bins_nans, } ) @pytest.fixture def segmented_design_matrices_nans( segmented_data_nans, occupancy_lookup_nans, temperature_bins_nans ): return { "dec-jan-feb-weighted": caltrack_hourly_fit_feature_processor( "dec-jan-feb-weighted", segmented_data_nans, occupancy_lookup_nans, temperature_bins_nans, temperature_bins_nans, ), "apr-may-jun-weighted": caltrack_hourly_fit_feature_processor( "apr-may-jun-weighted", segmented_data_nans, occupancy_lookup_nans, temperature_bins_nans, temperature_bins_nans, ), } def test_fit_caltrack_hourly_model_nans_less_than_week_predict( segmented_design_matrices_nans, occupancy_lookup_nans, temperature_bins_nans, temps_extended, temps, ): segmented_model_results = fit_caltrack_hourly_model( segmented_design_matrices_nans, occupancy_lookup_nans, temperature_bins_nans, temperature_bins_nans, ) assert segmented_model_results.model.segment_models is not None assert segmented_model_results.model.model_lookup["jan"].model is not None assert segmented_model_results.model.model_lookup["may"].model is not None assert segmented_model_results.model.model_lookup["may"].warnings == [] prediction = segmented_model_results.predict(temps.index, temps).result assert prediction.shape[0] == 24 assert prediction["predicted_usage"].sum().round() == 955.0 @pytest.fixture def segmented_data_nans_less_than_week(): num_periods = 4 index = pd.date_range(start="2017-01-01", periods=num_periods, freq="H", tz="UTC") time_features = compute_time_features(index) segmented_data = pd.DataFrame( { "hour_of_week": time_features.hour_of_week, "temperature_mean": np.linspace(0, 100, num_periods), "meter_value": np.linspace(10, 70, num_periods), "weight": np.ones((num_periods,)), }, index=index, ) return segmented_data @pytest.fixture def occupancy_lookup_nans_less_than_week(): index = pd.Categorical(range(168)) occupancy = pd.Series([i % 2 == 0 for i in range(168)], index=index) occupancy_nans_less_than_week = pd.Series([np.nan for i in range(168)], index=index) return pd.DataFrame( { "dec-jan-feb-weighted": occupancy, "jan-feb-mar-weighted": occupancy, "apr-may-jun-weighted": occupancy_nans_less_than_week, } ) @pytest.fixture def temperature_bins_nans_less_than_week(): bins = pd.Series([True, True, True], index=[30, 60, 90]) bins_nans_less_than_week = pd.Series([False, False, False], index=[30, 60, 90]) return pd.DataFrame( { "dec-jan-feb-weighted": bins, "jan-feb-mar-weighted": bins, "apr-may-jun-weighted": bins_nans_less_than_week, } ) @pytest.fixture def segmented_design_matrices_nans_less_than_week( segmented_data_nans_less_than_week, occupancy_lookup_nans_less_than_week, temperature_bins_nans_less_than_week, ): return { "dec-jan-feb-weighted": caltrack_hourly_fit_feature_processor( "dec-jan-feb-weighted", segmented_data_nans_less_than_week, occupancy_lookup_nans_less_than_week, temperature_bins_nans_less_than_week, temperature_bins_nans_less_than_week, ), "apr-may-jun-weighted": caltrack_hourly_fit_feature_processor( "apr-may-jun-weighted", segmented_data_nans_less_than_week, occupancy_lookup_nans_less_than_week, temperature_bins_nans_less_than_week, temperature_bins_nans_less_than_week, ), } @pytest.fixture def temps_extended(): index = pd.date_range(start="2017-01-01", periods=168, freq="H", tz="UTC") temps = pd.Series(1, index=index) return temps def test_fit_caltrack_hourly_model_nans_less_than_week_fit( segmented_design_matrices_nans_less_than_week, occupancy_lookup_nans_less_than_week, temperature_bins_nans_less_than_week, temps_extended, ): segmented_model_results = fit_caltrack_hourly_model( segmented_design_matrices_nans_less_than_week, occupancy_lookup_nans_less_than_week, temperature_bins_nans_less_than_week, temperature_bins_nans_less_than_week, ) assert segmented_model_results.model.segment_models is not None prediction = segmented_model_results.predict( temps_extended.index, temps_extended ).result assert prediction.shape[0] == 168 assert prediction.dropna().shape[0] == 4 @pytest.fixture def segmented_design_matrices_empty_models( segmented_data, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ): return { "dec-jan-feb-weighted": caltrack_hourly_fit_feature_processor( "dec-jan-feb-weighted", segmented_data[:0], occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ) } def test_predict_caltrack_hourly_model_empty_models( temps, segmented_design_matrices_empty_models, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ): segmented_model_results = fit_caltrack_hourly_model( segmented_design_matrices_empty_models, occupancy_lookup, occupied_temperature_bins, unoccupied_temperature_bins, ) assert segmented_model_results.model.segment_models is not None prediction = segmented_model_results.predict(temps.index, temps).result assert prediction.shape[0] == 24 assert prediction.dropna().shape[0] == 0 @pytest.fixture def occupancy_lookup_zeroes(): index = pd.Categorical(range(168)) occupancy = pd.Series([False] * 168, index=index) return pd.DataFrame( {"dec-jan-feb-weighted": occupancy, "jan-feb-mar-weighted": occupancy} ) @pytest.fixture def segmented_design_matrices_single_mode( segmented_data, occupancy_lookup_zeroes, occupied_temperature_bins, unoccupied_temperature_bins, ): return { "dec-jan-feb-weighted": caltrack_hourly_fit_feature_processor( "dec-jan-feb-weighted", segmented_data, occupancy_lookup_zeroes, occupied_temperature_bins, unoccupied_temperature_bins, ) } def test_fit_caltrack_hourly_model_segment_single_mode( segmented_design_matrices_single_mode ): segment_name = "dec-jan-feb-weighted" segment_data = segmented_design_matrices_single_mode[segment_name] segment_model = fit_caltrack_hourly_model_segment(segment_name, segment_data) assert segment_model.formula == ( "meter_value ~ C(hour_of_week) - 1 + bin_0_occupied + bin_1_occupied" " + bin_2_occupied + bin_3_occupied + bin_0_unoccupied + bin_1_unoccupied" " + bin_2_unoccupied" ) assert segment_model.segment_name == "dec-jan-feb-weighted" assert len(segment_model.model_params.keys()) == 31 assert segment_model.model is not None assert segment_model.warnings is not None prediction = segment_model.predict(segment_data) assert round(prediction.sum(), 2) == 960.0

31.052411

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0.786125

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0.802343

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null

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1

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null

0

6

3daddab9450165a26aaa1dfd0d06224e21bc8e0a

16,481

py

Python

test/programytest/extensions/scheduler/test_scheduler.py

cdoebler1/AIML2

ee692ec5ea3794cd1bc4cc8ec2a6b5e5c20a0d6a

[ "MIT" ]

345

2016-11-23T22:37:04.000Z

2022-03-30T20:44:44.000Z

test/programytest/extensions/scheduler/test_scheduler.py

MikeyBeez/program-y

00d7a0c7d50062f18f0ab6f4a041068e119ef7f0

[ "MIT" ]

275

2016-12-07T10:30:28.000Z

2022-02-08T21:28:33.000Z

test/programytest/extensions/scheduler/test_scheduler.py

VProgramMist/modified-program-y

f32efcafafd773683b3fe30054d5485fe9002b7d

[ "MIT" ]

159

2016-11-28T18:59:30.000Z

2022-03-20T18:02:44.000Z

import unittest from programy.extensions.scheduler.scheduler import SchedulerExtension from programytest.client import TestClient class SchedulerExtensionClient(TestClient): def __init__(self, mock_scheduler=None): self._mock_scheduler = mock_scheduler TestClient.__init__(self) def load_configuration(self, arguments): super(SchedulerExtensionClient, self).load_configuration(arguments) def load_scheduler(self): if self._mock_scheduler is not None: self._scheduler = self._mock_scheduler else: super(SchedulerExtensionClient, self).load_scheduler() class MockJob: def __init__(self, id, userid): self.args = [id, userid] @property def id(self): return self.args[0] class MockScheduler: def __init__(self): self._jobs = () def add_jobs(self, jobs): self._jobs = jobs def list_jobs(self): return self._jobs def pause_job (self, id): pass def resume_job (self, id): pass def stop_job (self, id): pass def schedule_every_n_seconds(self, userid, clientid, action, text, seconds): pass def schedule_every_n_minutes(self, userid, clientid, action, text, minutes): pass def schedule_every_n_hours(self, userid, clientid, action, text, hours): pass def schedule_every_n_days(self, userid, clientid, action, text, days): pass def schedule_every_n_weeks(self, userid, clientid, action, text, weeks): pass def schedule_every_n(self, userid, clientid, action, text, weeks=0, days=0, hours=0, minutes=0, seconds=0): pass def schedule_in_n_weeks(self, userid, clientid, action, text, weeks): pass def schedule_in_n_days(self, userid, clientid, action, text, days): pass def schedule_in_n_hours(self, userid, clientid, action, text, hours): pass def schedule_in_n_minutes(self, userid, clientid, action, text, minutes): pass def schedule_in_n_seconds(self, userid, clientid, action, text, seconds): pass class SchedulerExtensionTests(unittest.TestCase): # SCHEDULE IN|EVERY X SECS|MINS|HOURS|DAYS|WEEKS TEXT|SRAI TEXT ........... # PAUSE ALL|JOBID # RESUME ALL|JOBID # STOP ALL|JOBID # LIST def test_schedule_invalid(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() self.assertEquals("ERR", extension.execute(client_context, "OTHER")) self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE OTHER")) def test_schedule_in_invalid(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE IN")) self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE IN 10")) self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE IN 10 OTHER")) self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE IN 10 MINUTES OTHER")) self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE IN 10 MINUTES TEXT")) self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE IN 10 MINUTES SRAI")) def test_schedule_every_invalid(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE EVERY")) self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE EVER 10")) self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE EVER 10 OTHER")) self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE EVER 10 MINUTES OTHER")) self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE EVER 10 MINUTES TEXT")) self.assertEquals("ERR", extension.execute(client_context, "SCHEDULE EVER 10 MINUTES SRAI")) # IN XXXX def test_schedule_in_n_seconds(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE IN 10 SECONDS TEXT WAKEY WAKEY") self.assertEqual("OK", response) def test_schedule_in_n_minutes(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE IN 10 MINUTES TEXT WAKEY WAKEY") self.assertEqual("OK", response) def test_schedule_in_n_hours(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE IN 10 HOURS TEXT WAKEY WAKEY") self.assertEqual("OK", response) def test_schedule_in_n_days(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE IN 10 DAYS TEXT WAKEY WAKEY") self.assertEqual("OK", response) def test_schedule_in_n_weeks(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE IN 10 WEEKS TEXT WAKEY WAKEY") self.assertEqual("OK", response) # EVERY XXX def test_schedule_every_n_seconds(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE EVERY 10 SECONDS TEXT WAKEY WAKEY") self.assertEqual("OK", response) def test_schedule_every_n_minutes(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE EVERY 10 MINUTES TEXT WAKEY WAKEY") self.assertEqual("OK", response) def test_schedule_every_n_hours(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE EVERY 10 HOURS TEXT WAKEY WAKEY") self.assertEqual("OK", response) def test_schedule_every_n_days(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE EVERY 10 DAYS TEXT WAKEY WAKEY") self.assertEqual("OK", response) def test_schedule_every_n_weeks(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE EVERY 10 WEEKS TEXT WAKEY WAKEY") self.assertEqual("OK", response) # Other commands def test_pause_all(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE PAUSE ALL") self.assertEquals("OK", response) def test_pause_all_no_jobs(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE PAUSE ALL") self.assertEquals("ERR", response) def test_pause_job(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE PAUSE 1") self.assertEquals("OK", response) def test_pause_job_diff_id(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE PAUSE 2") self.assertEquals("ERR", response) def test_pause_job_no_userid(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid2")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE PAUSE 1") self.assertEquals("ERR", response) def test_pause_job_no_jobs(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE PAUSE 1") self.assertEquals("ERR", response) def test_resume_all(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE RESUME ALL") self.assertEquals("OK", response) def test_resume_all_no_jobs(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE RESUME ALL") self.assertEquals("ERR", response) def test_resume_job(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE RESUME 1") self.assertEquals("OK", response) def test_resume_job_diff_id(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE RESUME 2") self.assertEquals("ERR", response) def test_resume_job_no_userid(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid2")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE RESUME 1") self.assertEquals("ERR", response) def test_resume_job_no_jobs(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE RESUME 1") self.assertEquals("ERR", response) def test_stop_all(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE STOP ALL") self.assertEquals("OK", response) def test_stop_all_no_jobs(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE STOP ALL") self.assertEquals("ERR", response) def test_stop_job(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE STOP 1") self.assertEquals("OK", response) def test_stop_job_diff_id(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE STOP 2") self.assertEquals("ERR", response) def test_stop_job_no_userid(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid2")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE STOP 1") self.assertEquals("ERR", response) def test_stop_job_no_jobs(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE STOP 1") self.assertEquals("ERR", response) def test_list(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE LIST") self.assertEquals("OK <olist><item>1</item></olist>", response) def test_list_mulit_userids(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid"), 2: MockJob(2, "testid2"), 3: MockJob(3, "testid")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE LIST") self.assertEquals("OK <olist><item>1</item><item>3</item></olist>", response) def test_list_no_userid_jobs(self): client = SchedulerExtensionClient() client_context = client.create_client_context("testid") client_context.client._scheduler = MockScheduler() client_context.client._scheduler.add_jobs({1: MockJob(1, "testid2")}) extension = SchedulerExtension() response = extension.execute(client_context, "SCHEDULE LIST") self.assertEquals("ERR", response)

40.493857

127

0.696802

1,726

16,481

6.409618

0.052144

0.176263

0.121938

0.117961

0.911597

0.897135

0.888999

0.876797

0.869656

0.835578

0

0.007617

0.203446

16,481

406

128

40.593596

0.835085

0.009647

0

0.652459

0

0.093055

0.004414

0

0.147541

1

0.183607

false

0.045902

0.009836

0.006557

0.213115

0

null

0

1

0

null

0

6

9a8e7b31fad144ec998819e21cb8e9f6c82d9a34

2,449

py

Python

util/score_ctc.py

trinhtuanvubk/KWS-based-ASR

56ca095a903637ba92527fa3230bccd3357afa91

[ "MIT" ]

1

2022-03-16T07:01:00.000Z

util/score_ctc.py

trinhtuanvubk/KWS-based-ASR

56ca095a903637ba92527fa3230bccd3357afa91

[ "MIT" ]

null

util/score_ctc.py

trinhtuanvubk/KWS-based-ASR

56ca095a903637ba92527fa3230bccd3357afa91

[ "MIT" ]

null

# import nemo import nemo.collections.asr as nemo_asr import torch import numpy as np import torch.tensor # import math import util def score_stream(data,matrix_learned_phoneme,matrix_w): model_path = "./lightning_logs/version_7/checkpoints/epoch=2-step=21404.ckpt" asr_model = nemo_asr.models.EncDecCTCModel.load_from_checkpoint(checkpoint_path = model_path) # calculate score # files = [path] logprobs = [] # for fname, prob in zip(files, asr_model.transcribe(paths2audio_files = files , logprobs=1)) : # tensor_probs = (torch.exp(probs).numpy()).tolist() # tensor_probs = prob # print(tensor_probs) tensor_probs = asr_model.transcribe(data,logprobs=1) tensor_probs = np.exp(tensor_probs.numpy()) # print(tensor_probs) # print(np.max(tensor_probs,axis=1)) # print(type(tensor_probs[0])) # tensor_probs = [np.exp(i) for i in tensor_probs] for phoneme in matrix_learned_phoneme: probs = util.CTCforward(learned_phoneme = phoneme,matrix = tensor_probs) # print(probs) logprobs.append(np.log(probs)) # print(type(logprobs[0])) # score # score = sum([logprobs[i]*matrix_w[i]] for i in range(len(matrix_w))) score = sum([i*j for i,j in zip(logprobs,matrix_w)]) return score def score_ctc(path, matrix_learned_phoneme, matrix_w) : model_path = "./lightning_logs/version_7/checkpoints/epoch=2-step=21404.ckpt" asr_model = nemo_asr.models.EncDecCTCModel.load_from_checkpoint(checkpoint_path = model_path) # calculate score files = [path] logprobs = [] for fname, prob in zip(files, asr_model.transcribe(paths2audio_files = files , logprobs=1)) : # tensor_probs = (torch.exp(probs).numpy()).tolist() tensor_probs = prob # print(tensor_probs) tensor_probs = np.exp(tensor_probs.numpy()) # print(tensor_probs) # print(np.max(tensor_probs,axis=1)) # print(type(tensor_probs[0])) # tensor_probs = [np.exp(i) for i in tensor_probs] for phoneme in matrix_learned_phoneme: probs = util.CTCforward(learned_phoneme = phoneme,matrix = tensor_probs) # print(probs) logprobs.append(np.log(probs)) # print(type(logprobs[0])) # score # score = sum([logprobs[i]*matrix_w[i]] for i in range(len(matrix_w))) score = sum([i*j for i,j in zip(logprobs,matrix_w)]) return score

35.492754

99

0.670478

336

2,449

4.6875

0.193452

0.160635

0.050794

0.040635

0.892063

0

0.0129

0.208657

2,449

68

100

36.014706

0.799794

0.336056

0

0.62069

0

0.077597

0

1

0.068966

false

0

0.172414

0

0.310345

0

null

0

1

0

null

0

6

9aa3d99b8bf882af4f0e3614935b5995fa917b51

88

py

Python

autograd_cupy/sparse/sparse_jvps.py

ericmjl/autograd-cupy

493a90cabae42f9e0fdbea77cef758aff659604f

[ "MIT" ]

3

2018-08-03T00:11:17.000Z

2018-12-27T17:47:54.000Z

autograd_cupy/sparse/sparse_jvps.py

ericmjl/autograd-cupy

493a90cabae42f9e0fdbea77cef758aff659604f

[ "MIT" ]

null

autograd_cupy/sparse/sparse_jvps.py

ericmjl/autograd-cupy

493a90cabae42f9e0fdbea77cef758aff659604f

[ "MIT" ]

null

from autograd.extend import def_linear from .sparse_wrapper import dot def_linear(dot)

17.6

38

0.840909

14

88

5.071429

0.642857

0.253521

0

0.113636

88

4

39

22

0.910256

0

1

0

true

0

0.666667

0

0.666667

0

1

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null

1

0

1

0

null

0

1

0

1

0

1

0

6

9ab9435ec1f02262afd4f4bb84c025bded364f6d

75

py

Python

scpl/parser/__init__.py

jesopo/scpl

1fa5acfb468ab212276781fa1760bb5eda438c23

[ "MIT" ]

null

scpl/parser/__init__.py

jesopo/scpl

1fa5acfb468ab212276781fa1760bb5eda438c23

[ "MIT" ]

2

2021-11-15T11:12:14.000Z

2021-11-15T17:35:27.000Z

scpl/parser/__init__.py

jesopo/scpl

1fa5acfb468ab212276781fa1760bb5eda438c23

[ "MIT" ]

null

from .parser import * from .operands import * from .operators import *

18.75

24

0.706667

9

75

5.888889

0.555556

0.377358

0

0.213333

75

3

25

0.898305

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

9af9ff9ce17f38cb0bb39d7de4c3f27e10cfab06

41

py

Python

TOPSIS_Prakhar_101803126/__init__.py

PrakharJindal/Topsis-Pypi-Package

43a484d20aae5f4c8052295f432fafb6ba47aed4

[ "MIT" ]

null

TOPSIS_Prakhar_101803126/__init__.py

PrakharJindal/Topsis-Pypi-Package

43a484d20aae5f4c8052295f432fafb6ba47aed4

[ "MIT" ]

null

TOPSIS_Prakhar_101803126/__init__.py

PrakharJindal/Topsis-Pypi-Package

43a484d20aae5f4c8052295f432fafb6ba47aed4

[ "MIT" ]

null

from .topsis import CalculateTopsisScore

20.5

40

0.878049

4

41

9

1

0

0.097561

41

1

41

0.972973

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

b127ef316f1dd9b3d78f019706fc00e7bcca2096

67

py

Python

amocrm_asterisk_ng/telephony/impl/instances/asterisk_16/cdr_provider/query_handlers/__init__.py

iqtek/amocrn_asterisk_ng

429a8d0823b951c855a49c1d44ab0e05263c54dc

[ "MIT" ]

null

amocrm_asterisk_ng/telephony/impl/instances/asterisk_16/cdr_provider/query_handlers/__init__.py

iqtek/amocrn_asterisk_ng

429a8d0823b951c855a49c1d44ab0e05263c54dc

[ "MIT" ]

null

amocrm_asterisk_ng/telephony/impl/instances/asterisk_16/cdr_provider/query_handlers/__init__.py

iqtek/amocrn_asterisk_ng

429a8d0823b951c855a49c1d44ab0e05263c54dc

[ "MIT" ]

null

from .GetRecordFileUniqueIdQuery import GetRecordFileUniqueIdQuery

33.5

66

0.925373

4

67

15.5

0.75

0

0.059701

67

1

67

0.984127

0

1

0

true

0

1

0

1

0

1

0

1

null

0

1

0

null

0

1

0

1

0

1

0

6

b180c4c0a84ab038cab49981ad98faeffc5b12cb

106

py

Python

reqherd/webservice/crud/__init__.py

zthurman/reqherd

6b35c4f22d4e28c363f82a5f3331657f8244a589

[ "Apache-2.0" ]

null

reqherd/webservice/crud/__init__.py

zthurman/reqherd

6b35c4f22d4e28c363f82a5f3331657f8244a589

[ "Apache-2.0" ]

null

reqherd/webservice/crud/__init__.py

zthurman/reqherd

6b35c4f22d4e28c363f82a5f3331657f8244a589

[ "Apache-2.0" ]

null

from ..crud.sysreqs import sysreq from ..crud.softreqs import softreq from ..crud.hardreqs import hardreq

26.5

35

0.801887

15

106

5.666667

0.6

0.282353

0

0.113208

106

3

36

35.333333

0.904255

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

b184e119b4b603b4d9b7b4ce01a81fb46c2c80ea

2,534

py

Python

Zhangjiashan_vmd/projects/generate_samples.py

UnIcOrn7618/MonthlyRunoffForecastByAutoReg

2d66c628141f001e4ffb3dc3b7520a0f0f0ff239

[ "MIT" ]

2

2020-09-24T13:31:06.000Z

2020-11-11T09:08:16.000Z

Zhangjiashan_vmd/projects/generate_samples.py

UnIcOrn7618/MonthlyRunoffForecastByAutoReg

2d66c628141f001e4ffb3dc3b7520a0f0f0ff239

[ "MIT" ]

null

Zhangjiashan_vmd/projects/generate_samples.py

UnIcOrn7618/MonthlyRunoffForecastByAutoReg

2d66c628141f001e4ffb3dc3b7520a0f0f0ff239

[ "MIT" ]

1

2020-12-16T07:29:32.000Z

import os root_path = os.path.dirname(os.path.abspath("__file__")) from variables import variables import sys sys.path.append(root_path) from tools.samples_generator import gen_one_step_forecast_samples_triandev_test from tools.samples_generator import gen_multi_step_forecast_samples from tools.samples_generator import gen_one_step_forecast_samples gen_one_step_forecast_samples_triandev_test( station="Zhangjiashan", decomposer="vmd", lags_dict = variables['lags_dict'], input_columns=['IMF1','IMF2','IMF3','IMF4','IMF5','IMF6','IMF7',], output_column=['ORIG'], start=673, stop=792, test_len=120, ) for lead_time in [1,3,5,7,9]: gen_one_step_forecast_samples( station = "Zhangjiashan", decomposer="vmd", lags_dict = variables['lags_dict'], input_columns=['IMF1','IMF2','IMF3','IMF4','IMF5','IMF6','IMF7',], output_column=['ORIG'], start=553, stop=792, test_len=120, mode = 'PACF', lead_time =lead_time, ) for lead_time in [3,5,7,9]: gen_one_step_forecast_samples( station = "Zhangjiashan", decomposer="vmd", lags_dict = variables['lags_dict'], input_columns=['IMF1','IMF2','IMF3','IMF4','IMF5','IMF6','IMF7',], output_column=['ORIG'], start=553, stop=792, test_len=120, mode = 'Pearson', lead_time =lead_time, ) gen_multi_step_forecast_samples( station='Zhangjiashan', decomposer="vmd", lags_dict = variables['lags_dict'], columns=['IMF1','IMF2','IMF3','IMF4','IMF5','IMF6','IMF7',], start=553, stop=792, test_len=120, ) gen_one_step_forecast_samples( station = "Zhangjiashan", decomposer="vmd", lags_dict = variables['lags_dict'], input_columns=['IMF1','IMF2','IMF3','IMF4','IMF5','IMF6','IMF7',], output_column=['ORIG'], start=553, stop=792, test_len=120, mode = 'PACF', lead_time =1, n_components='mle', ) num_in_one = sum(variables['lags_dict'].values()) for n_components in range(num_in_one-16,num_in_one+1): gen_one_step_forecast_samples( station = "Zhangjiashan", decomposer="vmd", lags_dict = variables['lags_dict'], input_columns=['IMF1','IMF2','IMF3','IMF4','IMF5','IMF6','IMF7',], output_column=['ORIG'], start=553, stop=792, test_len=120, mode = 'PACF', lead_time =1, n_components=n_components, )

27.543478

79

0.624704

317

2,534

4.690852

0.208202

0.069939

0.114997

0.084734

0.829859

0.796907

0.774042

0.724277

0.70074

0

0.055781

0.221784

2,534

91

80

27.846154

0.698276

0

0.679012

0

0.146409

0

1

0

false

0

0.074074

0

0.074074

0

null

0

1

0

null

0

6

49351ddfde6e63ce6aa8591deb6001db57407d0c

24

py

Python

vk/types/events/__init__.py

Inzilkin/vk.py

969f01e666c877c1761c3629a100768f93de27eb

[ "MIT" ]

24

2019-09-13T15:30:09.000Z

2022-03-09T06:35:59.000Z

vk/types/events/__init__.py

Inzilkin/vk.py

969f01e666c877c1761c3629a100768f93de27eb

[ "MIT" ]

null

vk/types/events/__init__.py

Inzilkin/vk.py

969f01e666c877c1761c3629a100768f93de27eb

[ "MIT" ]

12

2019-09-13T15:30:31.000Z

2022-03-01T10:13:32.000Z

from . import community

12

23

0.791667

3

24

6.333333

1

0

0.166667

24

1

24

0.95

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

49734e2713a3c200dc972855cc36eeeba9ed7369

99

py

Python

src/textdata.py

little-quokka/py-quokka-block

d6593087c1f027af80c8968ac113c1ccb2cf7f55

[ "MIT" ]

null

src/textdata.py

little-quokka/py-quokka-block

d6593087c1f027af80c8968ac113c1ccb2cf7f55

[ "MIT" ]

8

2018-01-03T01:27:06.000Z

2018-01-03T01:32:33.000Z

src/textdata.py

little-quokka/py-quokka-block

d6593087c1f027af80c8968ac113c1ccb2cf7f55

[ "MIT" ]

null

from abstractdatapackage import AbstractDataPackage class TextData(AbstractDataPackage): pass

19.8

51

0.848485

8

99

10.5

0.75

0

0.121212

99

5

52

19.8

0.965517

0

1

0

true

0.333333

0

0.666667

0

1

0

1

null

0

1

0

null

0

1

0

6

497863b677cf4c4a60dc3b9419cf1a3b4b6583bc

9,835

py

Python

migrations/versions/9ff331ab950b_v0_1_0.py

BoostryJP/ibet-Prime

924e7f8da4f8feea0a572e8b5532e09bcdf2dc99

[ "Apache-2.0" ]

2

2021-08-19T12:35:25.000Z

2022-02-16T04:13:38.000Z

migrations/versions/9ff331ab950b_v0_1_0.py

BoostryJP/ibet-Prime

924e7f8da4f8feea0a572e8b5532e09bcdf2dc99

[ "Apache-2.0" ]

46

2021-09-02T03:22:05.000Z

2022-03-31T09:20:00.000Z

migrations/versions/9ff331ab950b_v0_1_0.py

BoostryJP/ibet-Prime

924e7f8da4f8feea0a572e8b5532e09bcdf2dc99

[ "Apache-2.0" ]

1

2021-11-17T23:18:27.000Z

"""v0.1.0 Revision ID: 9ff331ab950b Revises: Create Date: 2021-03-19 21:03:52.102757 """ from alembic import op import sqlalchemy as sa from app.database import get_db_schema # revision identifiers, used by Alembic. revision = '9ff331ab950b' down_revision = None branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table('account', sa.Column('created', sa.DateTime(), nullable=True), sa.Column('modified', sa.DateTime(), nullable=True), sa.Column('issuer_address', sa.String(length=42), nullable=False), sa.Column('keyfile', sa.JSON(), nullable=True), sa.Column('eoa_password', sa.String(length=2000), nullable=True), sa.Column('rsa_private_key', sa.String(length=8000), nullable=True), sa.Column('rsa_public_key', sa.String(length=2000), nullable=True), sa.Column('rsa_passphrase', sa.String(length=2000), nullable=True), sa.Column('rsa_status', sa.Integer(), nullable=True), sa.Column('is_deleted', sa.Boolean(), nullable=True), sa.PrimaryKeyConstraint('issuer_address') , schema=get_db_schema()) op.create_table('account_rsa_key_temporary', sa.Column('created', sa.DateTime(), nullable=True), sa.Column('modified', sa.DateTime(), nullable=True), sa.Column('issuer_address', sa.String(length=42), nullable=False), sa.Column('rsa_private_key', sa.String(length=8000), nullable=True), sa.Column('rsa_public_key', sa.String(length=2000), nullable=True), sa.Column('rsa_passphrase', sa.String(length=2000), nullable=True), sa.PrimaryKeyConstraint('issuer_address') , schema=get_db_schema()) op.create_table('bulk_transfer', sa.Column('created', sa.DateTime(), nullable=True), sa.Column('modified', sa.DateTime(), nullable=True), sa.Column('id', sa.Integer(), autoincrement=True, nullable=False), sa.Column('issuer_address', sa.String(length=42), nullable=False), sa.Column('upload_id', sa.String(length=36), nullable=True), sa.Column('token_address', sa.String(length=42), nullable=False), sa.Column('token_type', sa.String(length=40), nullable=False), sa.Column('from_address', sa.String(length=42), nullable=False), sa.Column('to_address', sa.String(length=42), nullable=False), sa.Column('amount', sa.Integer(), nullable=False), sa.Column('status', sa.Integer(), nullable=False), sa.PrimaryKeyConstraint('id') , schema=get_db_schema()) op.create_index(op.f('ix_bulk_transfer_issuer_address'), 'bulk_transfer', ['issuer_address'], unique=False, schema=get_db_schema()) op.create_index(op.f('ix_bulk_transfer_status'), 'bulk_transfer', ['status'], unique=False, schema=get_db_schema()) op.create_index(op.f('ix_bulk_transfer_upload_id'), 'bulk_transfer', ['upload_id'], unique=False, schema=get_db_schema()) op.create_table('bulk_transfer_upload', sa.Column('created', sa.DateTime(), nullable=True), sa.Column('modified', sa.DateTime(), nullable=True), sa.Column('upload_id', sa.String(length=36), nullable=False), sa.Column('issuer_address', sa.String(length=42), nullable=False), sa.Column('token_type', sa.String(length=40), nullable=False), sa.Column('status', sa.Integer(), nullable=False), sa.PrimaryKeyConstraint('upload_id') , schema=get_db_schema()) op.create_index(op.f('ix_bulk_transfer_upload_issuer_address'), 'bulk_transfer_upload', ['issuer_address'], unique=False, schema=get_db_schema()) op.create_index(op.f('ix_bulk_transfer_upload_status'), 'bulk_transfer_upload', ['status'], unique=False, schema=get_db_schema()) op.create_table('idx_personal_info', sa.Column('created', sa.DateTime(), nullable=True), sa.Column('modified', sa.DateTime(), nullable=True), sa.Column('id', sa.BigInteger(), autoincrement=True, nullable=False), sa.Column('account_address', sa.String(length=42), nullable=True), sa.Column('issuer_address', sa.String(length=42), nullable=True), sa.Column('personal_info', sa.JSON(), nullable=False), sa.PrimaryKeyConstraint('id') , schema=get_db_schema()) op.create_index(op.f('ix_idx_personal_info_account_address'), 'idx_personal_info', ['account_address'], unique=False, schema=get_db_schema()) op.create_index(op.f('ix_idx_personal_info_issuer_address'), 'idx_personal_info', ['issuer_address'], unique=False, schema=get_db_schema()) op.create_table('idx_personal_info_block_number', sa.Column('created', sa.DateTime(), nullable=True), sa.Column('modified', sa.DateTime(), nullable=True), sa.Column('id', sa.BigInteger(), autoincrement=True, nullable=False), sa.Column('latest_block_number', sa.BigInteger(), nullable=True), sa.PrimaryKeyConstraint('id') , schema=get_db_schema()) op.create_table('idx_position', sa.Column('created', sa.DateTime(), nullable=True), sa.Column('modified', sa.DateTime(), nullable=True), sa.Column('id', sa.BigInteger(), autoincrement=True, nullable=False), sa.Column('token_address', sa.String(length=42), nullable=True), sa.Column('account_address', sa.String(length=42), nullable=True), sa.Column('balance', sa.BigInteger(), nullable=True), sa.PrimaryKeyConstraint('id') , schema=get_db_schema()) op.create_index(op.f('ix_idx_position_account_address'), 'idx_position', ['account_address'], unique=False, schema=get_db_schema()) op.create_index(op.f('ix_idx_position_token_address'), 'idx_position', ['token_address'], unique=False, schema=get_db_schema()) op.create_table('idx_transfer', sa.Column('created', sa.DateTime(), nullable=True), sa.Column('modified', sa.DateTime(), nullable=True), sa.Column('id', sa.BigInteger(), autoincrement=True, nullable=False), sa.Column('transaction_hash', sa.String(length=66), nullable=True), sa.Column('token_address', sa.String(length=42), nullable=True), sa.Column('transfer_from', sa.String(length=42), nullable=True), sa.Column('transfer_to', sa.String(length=42), nullable=True), sa.Column('amount', sa.BigInteger(), nullable=True), sa.Column('block_timestamp', sa.DateTime(), nullable=True), sa.PrimaryKeyConstraint('id') , schema=get_db_schema()) op.create_index(op.f('ix_idx_transfer_token_address'), 'idx_transfer', ['token_address'], unique=False, schema=get_db_schema()) op.create_index(op.f('ix_idx_transfer_transaction_hash'), 'idx_transfer', ['transaction_hash'], unique=False, schema=get_db_schema()) op.create_index(op.f('ix_idx_transfer_transfer_from'), 'idx_transfer', ['transfer_from'], unique=False, schema=get_db_schema()) op.create_index(op.f('ix_idx_transfer_transfer_to'), 'idx_transfer', ['transfer_to'], unique=False, schema=get_db_schema()) op.create_table('token', sa.Column('created', sa.DateTime(), nullable=True), sa.Column('modified', sa.DateTime(), nullable=True), sa.Column('id', sa.Integer(), autoincrement=True, nullable=False), sa.Column('type', sa.String(length=40), nullable=False), sa.Column('tx_hash', sa.String(length=66), nullable=False), sa.Column('issuer_address', sa.String(length=42), nullable=True), sa.Column('token_address', sa.String(length=42), nullable=True), sa.Column('abi', sa.JSON(), nullable=False), sa.PrimaryKeyConstraint('id') , schema=get_db_schema()) op.create_table('tx_management', sa.Column('created', sa.DateTime(), nullable=True), sa.Column('modified', sa.DateTime(), nullable=True), sa.Column('tx_from', sa.String(length=42), nullable=False), sa.PrimaryKeyConstraint('tx_from') , schema=get_db_schema()) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.drop_table('tx_management', schema=get_db_schema()) op.drop_table('token', schema=get_db_schema()) op.drop_index(op.f('ix_idx_transfer_transfer_to'), table_name='idx_transfer', schema=get_db_schema()) op.drop_index(op.f('ix_idx_transfer_transfer_from'), table_name='idx_transfer', schema=get_db_schema()) op.drop_index(op.f('ix_idx_transfer_transaction_hash'), table_name='idx_transfer', schema=get_db_schema()) op.drop_index(op.f('ix_idx_transfer_token_address'), table_name='idx_transfer', schema=get_db_schema()) op.drop_table('idx_transfer', schema=get_db_schema()) op.drop_index(op.f('ix_idx_position_token_address'), table_name='idx_position', schema=get_db_schema()) op.drop_index(op.f('ix_idx_position_account_address'), table_name='idx_position', schema=get_db_schema()) op.drop_table('idx_position', schema=get_db_schema()) op.drop_table('idx_personal_info_block_number', schema=get_db_schema()) op.drop_index(op.f('ix_idx_personal_info_issuer_address'), table_name='idx_personal_info', schema=get_db_schema()) op.drop_index(op.f('ix_idx_personal_info_account_address'), table_name='idx_personal_info', schema=get_db_schema()) op.drop_table('idx_personal_info', schema=get_db_schema()) op.drop_index(op.f('ix_bulk_transfer_upload_status'), table_name='bulk_transfer_upload', schema=get_db_schema()) op.drop_index(op.f('ix_bulk_transfer_upload_issuer_address'), table_name='bulk_transfer_upload', schema=get_db_schema()) op.drop_table('bulk_transfer_upload', schema=get_db_schema()) op.drop_index(op.f('ix_bulk_transfer_upload_id'), table_name='bulk_transfer', schema=get_db_schema()) op.drop_index(op.f('ix_bulk_transfer_status'), table_name='bulk_transfer', schema=get_db_schema()) op.drop_index(op.f('ix_bulk_transfer_issuer_address'), table_name='bulk_transfer', schema=get_db_schema()) op.drop_table('bulk_transfer', schema=get_db_schema()) op.drop_table('account_rsa_key_temporary', schema=get_db_schema()) op.drop_table('account', schema=get_db_schema()) # ### end Alembic commands ###

61.086957

149

0.726894

1,396

9,835

4.846705

0.07808

0.081584

0.076411

0.115578

0.894177

0.874963

0.864617

0.843778

0.796482

0.72347

0

0.012815

0.103406

9,835

161

150

61.086957

0.754479

0.02786

0

0.451389

0

0.246588

0.094688

0

1

0.013889

false

0.020833

0

0.034722

0

null

0

1

0

null

0

6

772092ec6765810376e1feab85f3837c4d1bcc80

1,681

py

Python

random-images/WallpaperGenerator/test.py

dominicschaff/random

14a19b976a09c768ab8844b7cda237c17a92c9ae

[ "MIT" ]

null

random-images/WallpaperGenerator/test.py

dominicschaff/random

14a19b976a09c768ab8844b7cda237c17a92c9ae

[ "MIT" ]

null

random-images/WallpaperGenerator/test.py

dominicschaff/random

14a19b976a09c768ab8844b7cda237c17a92c9ae

[ "MIT" ]

null

from __future__ import division from math import radians as rad, pi, e from constants import * import functions import sys dr = DrawImage() dr.create() dr.plotRadians(functions.butterfly, start = 0, end = 10000, offset = (dr.width/2, dr.height/4), steps = 0.1, scale = 20, colour = (18,182,252), rotation = 180) print "Done: Butterfly" dr.plotRadians(functions.butterfly, start = 0, end = 10000, offset = (dr.width/2, dr.height/4*3), steps = 0.1, scale = 20, colour = (18,182,252), rotation = 0) print "Done: Butterfly" dr.plotRadians(functions.butterfly, start = 0, end = 10000, offset = (dr.width/4, dr.height/2), steps = 0.1, scale = 20, colour = (18,182,252), rotation = 180) print "Done: Butterfly" dr.plotRadians(functions.butterfly, start = 0, end = 10000, offset = (dr.width/4*3, dr.height/2), steps = 0.1, scale = 20, colour = (18,182,252), rotation = 180) print "Done: Butterfly" for i in drange(50,70.5,0.5): dr.plotRadians(functions.leaf, start = 0, end = 10000, offset = (dr.width/2, dr.height/2+25), steps = 0.1, scale = i, colour = (252,18,252), rotation = 270) dr.plotRadians(functions.leaf, start = 0, end = 10000, offset = (dr.width/2, dr.height/2+25), steps = 0.1, scale = i, colour = (252,18,252), rotation = 90) print "Done: Leaf:", i d2 = DrawImage() d2.open('image1.png') dr.addOver(d2) dr.save('image3.png')

23.676056

48

0.54075

221

1,681

4.095023

0.262443

0.086188

0.145856

0.092818

0.770166

0

0.130245

0.319453

1,681

71

49

23.676056

0.660839

0

0.692308

0

0.054102

0

null

0

0.076923

null

0.076923

0

null

0

1

0

null

0

1

0

6

772d89f1141a86458c1f48806e1b7d511a4d7d59

30,179

py

Python

python/trezorlib/tests/device_tests/test_msg_signtx_bcash.py

Kayuii/trezor-crypto

6556616681a4e2d7e18817e8692d4f6e041dee01

[ "MIT" ]

null

python/trezorlib/tests/device_tests/test_msg_signtx_bcash.py

Kayuii/trezor-crypto

6556616681a4e2d7e18817e8692d4f6e041dee01

[ "MIT" ]

1

2019-02-08T00:22:42.000Z

2019-02-13T09:41:54.000Z

python/trezorlib/tests/device_tests/test_msg_signtx_bcash.py

Kayuii/trezor-crypto

6556616681a4e2d7e18817e8692d4f6e041dee01

[ "MIT" ]

2

2019-02-07T23:57:09.000Z

2020-10-21T07:07:27.000Z

# This file is part of the Trezor project. # # Copyright (C) 2012-2018 SatoshiLabs and contributors # # This library is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License version 3 # as published by the Free Software Foundation. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the License along with this library. # If not, see <https://www.gnu.org/licenses/lgpl-3.0.html>. import pytest from trezorlib import btc, messages as proto from trezorlib.tools import H_, CallException, parse_path from ..support.ckd_public import deserialize from ..support.tx_cache import tx_cache from .common import TrezorTest TX_API = tx_cache("Bcash") class TestMsgSigntxBch(TrezorTest): def test_send_bch_change(self): self.setup_mnemonic_allallall() inp1 = proto.TxInputType( address_n=parse_path("44'/145'/0'/0/0"), # bitcoincash:qr08q88p9etk89wgv05nwlrkm4l0urz4cyl36hh9sv amount=1995344, prev_hash=bytes.fromhex( "bc37c28dfb467d2ecb50261387bf752a3977d7e5337915071bb4151e6b711a78" ), prev_index=0, script_type=proto.InputScriptType.SPENDADDRESS, ) out1 = proto.TxOutputType( address_n=parse_path("44'/145'/0'/1/0"), amount=1896050, script_type=proto.OutputScriptType.PAYTOADDRESS, ) out2 = proto.TxOutputType( address="bitcoincash:qr23ajjfd9wd73l87j642puf8cad20lfmqdgwvpat4", amount=73452, script_type=proto.OutputScriptType.PAYTOADDRESS, ) with self.client: self.client.set_expected_responses( [ proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.ButtonRequest(code=proto.ButtonRequestType.ConfirmOutput), proto.ButtonRequest(code=proto.ButtonRequestType.SignTx), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.TxRequest(request_type=proto.RequestType.TXFINISHED), ] ) _, serialized_tx = btc.sign_tx( self.client, "Bcash", [inp1], [out1, out2], prev_txes=TX_API ) assert ( serialized_tx.hex() == "0100000001781a716b1e15b41b07157933e5d777392a75bf87132650cb2e7d46fb8dc237bc000000006a473044022061aee4f17abe044d5df8c52c9ffd3b84e5a29743517e488b20ecf1ae0b3e4d3a02206bb84c55e407f3b684ff8d9bea0a3409cfd865795a19d10b3d3c31f12795c34a412103a020b36130021a0f037c1d1a02042e325c0cb666d6478c1afdcd9d913b9ef080ffffffff0272ee1c00000000001976a914b1401fce7e8bf123c88a0467e0ed11e3b9fbef5488acec1e0100000000001976a914d51eca49695cdf47e7f4b55507893e3ad53fe9d888ac00000000" ) def test_send_bch_nochange(self): self.setup_mnemonic_allallall() inp1 = proto.TxInputType( address_n=parse_path("44'/145'/0'/1/0"), # bitcoincash:qzc5q87w069lzg7g3gzx0c8dz83mn7l02scej5aluw amount=1896050, prev_hash=bytes.fromhex( "502e8577b237b0152843a416f8f1ab0c63321b1be7a8cad7bf5c5c216fcf062c" ), prev_index=0, script_type=proto.InputScriptType.SPENDADDRESS, ) inp2 = proto.TxInputType( address_n=parse_path("44'/145'/0'/0/1"), # bitcoincash:qr23ajjfd9wd73l87j642puf8cad20lfmqdgwvpat4 amount=73452, prev_hash=bytes.fromhex( "502e8577b237b0152843a416f8f1ab0c63321b1be7a8cad7bf5c5c216fcf062c" ), prev_index=1, script_type=proto.InputScriptType.SPENDADDRESS, ) out1 = proto.TxOutputType( address="bitcoincash:qq6wnnkrz7ykaqvxrx4hmjvayvzjzml54uyk76arx4", amount=1934960, script_type=proto.OutputScriptType.PAYTOADDRESS, ) with self.client: self.client.set_expected_responses( [ proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.ButtonRequest(code=proto.ButtonRequestType.ConfirmOutput), proto.ButtonRequest(code=proto.ButtonRequestType.SignTx), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest(request_type=proto.RequestType.TXFINISHED), ] ) _, serialized_tx = btc.sign_tx( self.client, "Bcash", [inp1, inp2], [out1], prev_txes=TX_API ) assert ( serialized_tx.hex() == "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" ) def test_send_bch_oldaddr(self): self.setup_mnemonic_allallall() inp1 = proto.TxInputType( address_n=parse_path("44'/145'/0'/1/0"), # bitcoincash:qzc5q87w069lzg7g3gzx0c8dz83mn7l02scej5aluw amount=1896050, prev_hash=bytes.fromhex( "502e8577b237b0152843a416f8f1ab0c63321b1be7a8cad7bf5c5c216fcf062c" ), prev_index=0, script_type=proto.InputScriptType.SPENDADDRESS, ) inp2 = proto.TxInputType( address_n=parse_path("44'/145'/0'/0/1"), # bitcoincash:qr23ajjfd9wd73l87j642puf8cad20lfmqdgwvpat4 amount=73452, prev_hash=bytes.fromhex( "502e8577b237b0152843a416f8f1ab0c63321b1be7a8cad7bf5c5c216fcf062c" ), prev_index=1, script_type=proto.InputScriptType.SPENDADDRESS, ) out1 = proto.TxOutputType( address="15pnEDZJo3ycPUamqP3tEDnEju1oW5fBCz", amount=1934960, script_type=proto.OutputScriptType.PAYTOADDRESS, ) with self.client: self.client.set_expected_responses( [ proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.ButtonRequest(code=proto.ButtonRequestType.ConfirmOutput), proto.ButtonRequest(code=proto.ButtonRequestType.SignTx), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest(request_type=proto.RequestType.TXFINISHED), ] ) _, serialized_tx = btc.sign_tx( self.client, "Bcash", [inp1, inp2], [out1], prev_txes=TX_API ) assert ( serialized_tx.hex() == "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" ) def test_attack_amount(self): self.setup_mnemonic_allallall() inp1 = proto.TxInputType( address_n=parse_path("44'/145'/0'/1/0"), # bitcoincash:qzc5q87w069lzg7g3gzx0c8dz83mn7l02scej5aluw amount=300, prev_hash=bytes.fromhex( "502e8577b237b0152843a416f8f1ab0c63321b1be7a8cad7bf5c5c216fcf062c" ), prev_index=0, script_type=proto.InputScriptType.SPENDADDRESS, ) inp2 = proto.TxInputType( address_n=parse_path("44'/145'/0'/0/1"), # bitcoincash:qr23ajjfd9wd73l87j642puf8cad20lfmqdgwvpat4 amount=70, prev_hash=bytes.fromhex( "502e8577b237b0152843a416f8f1ab0c63321b1be7a8cad7bf5c5c216fcf062c" ), prev_index=1, script_type=proto.InputScriptType.SPENDADDRESS, ) out1 = proto.TxOutputType( address="bitcoincash:qq6wnnkrz7ykaqvxrx4hmjvayvzjzml54uyk76arx4", amount=200, script_type=proto.OutputScriptType.PAYTOADDRESS, ) # test if passes without modifications with self.client: self.client.set_expected_responses( [ proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.ButtonRequest(code=proto.ButtonRequestType.ConfirmOutput), proto.ButtonRequest(code=proto.ButtonRequestType.SignTx), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest(request_type=proto.RequestType.TXFINISHED), ] ) btc.sign_tx(self.client, "Bcash", [inp1, inp2], [out1], prev_txes=TX_API) run_attack = True def attack_processor(msg): nonlocal run_attack if run_attack and msg.tx.inputs and msg.tx.inputs[0] == inp1: # 300 is lowered to 280 at the first run # the user confirms 280 but the transaction # is spending 300 => larger fee without the user knowing msg.tx.inputs[0].amount = 280 run_attack = False return msg # now fails self.client.set_filter(proto.TxAck, attack_processor) with self.client: self.client.set_expected_responses( [ proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.ButtonRequest(code=proto.ButtonRequestType.ConfirmOutput), proto.ButtonRequest(code=proto.ButtonRequestType.SignTx), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.Failure(), ] ) with pytest.raises(CallException) as exc: btc.sign_tx( self.client, "Bcash", [inp1, inp2], [out1], prev_txes=TX_API ) assert exc.value.args[0] in ( proto.FailureType.ProcessError, proto.FailureType.DataError, ) assert exc.value.args[1].endswith("Transaction has changed during signing") def test_attack_change_input(self): self.setup_mnemonic_allallall() inp1 = proto.TxInputType( address_n=parse_path("44'/145'/10'/0/0"), amount=1995344, prev_hash=bytes.fromhex( "bc37c28dfb467d2ecb50261387bf752a3977d7e5337915071bb4151e6b711a78" ), prev_index=0, script_type=proto.InputScriptType.SPENDADDRESS, ) out1 = proto.TxOutputType( address_n=parse_path("44'/145'/10'/1/0"), amount=1896050, script_type=proto.OutputScriptType.PAYTOADDRESS, ) out2 = proto.TxOutputType( address="bitcoincash:qr23ajjfd9wd73l87j642puf8cad20lfmqdgwvpat4", amount=73452, script_type=proto.OutputScriptType.PAYTOADDRESS, ) run_attack = False def attack_processor(msg): nonlocal run_attack if msg.tx.inputs and msg.tx.inputs[0] == inp1: if not run_attack: run_attack = True else: msg.tx.inputs[0].address_n[2] = H_(1) return msg self.client.set_filter(proto.TxAck, attack_processor) with self.client: self.client.set_expected_responses( [ proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.ButtonRequest(code=proto.ButtonRequestType.ConfirmOutput), proto.ButtonRequest(code=proto.ButtonRequestType.SignTx), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.Failure(code=proto.FailureType.ProcessError), ] ) with pytest.raises(CallException): btc.sign_tx( self.client, "Bcash", [inp1], [out1, out2], prev_txes=TX_API ) def test_send_bch_multisig_wrongchange(self): self.setup_mnemonic_allallall() xpubs = [] for n in map( lambda index: btc.get_public_node( self.client, parse_path("48'/145'/%d'" % index) ), range(1, 4), ): xpubs.append(n.xpub) def getmultisig(chain, nr, signatures=[b"", b"", b""], xpubs=xpubs): return proto.MultisigRedeemScriptType( nodes=[deserialize(xpub) for xpub in xpubs], address_n=[chain, nr], signatures=signatures, m=2, ) correcthorse = proto.HDNodeType( depth=1, fingerprint=0, child_num=0, chain_code=bytes.fromhex( "0000000000000000000000000000000000000000000000000000000000000000" ), public_key=bytes.fromhex( "0378d430274f8c5ec1321338151e9f27f4c676a008bdf8638d07c0b6be9ab35c71" ), ) sig = bytes.fromhex( "304402207274b5a4d15e75f3df7319a375557b0efba9b27bc63f9f183a17da95a6125c94022000efac57629f1522e2d3958430e2ef073b0706cfac06cce492651b79858f09ae" ) inp1 = proto.TxInputType( address_n=parse_path("48'/145'/1'/1/0"), multisig=getmultisig(1, 0, [b"", sig, b""]), # bitcoincash:pp6kcpkhua7789g2vyj0qfkcux3yvje7euhyhltn0a amount=24000, prev_hash=bytes.fromhex( "f68caf10df12d5b07a34601d88fa6856c6edcbf4d05ebef3486510ae1c293d5f" ), prev_index=1, script_type=proto.InputScriptType.SPENDMULTISIG, ) out1 = proto.TxOutputType( address_n=parse_path("48'/145'/1'/1/1"), multisig=proto.MultisigRedeemScriptType( pubkeys=[ proto.HDNodePathType(node=deserialize(xpubs[0]), address_n=[1, 1]), proto.HDNodePathType(node=correcthorse, address_n=[]), proto.HDNodePathType(node=correcthorse, address_n=[]), ], signatures=[b"", b"", b""], m=2, ), script_type=proto.OutputScriptType.PAYTOMULTISIG, amount=23000, ) with self.client: self.client.set_expected_responses( [ proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.ButtonRequest(code=proto.ButtonRequestType.ConfirmOutput), proto.ButtonRequest(code=proto.ButtonRequestType.SignTx), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest(request_type=proto.RequestType.TXFINISHED), ] ) (signatures1, serialized_tx) = btc.sign_tx( self.client, "Bcash", [inp1], [out1], prev_txes=TX_API ) assert ( signatures1[0].hex() == "304402201badcdcafef4855ed58621f95935efcbc72068510472140f4ec5e252faa0af93022003310a43488288f70aedee96a5af2643a255268a6858cda9ae3001ea5e3c7557" ) assert ( serialized_tx.hex() == "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" ) def test_send_bch_multisig_change(self): self.setup_mnemonic_allallall() xpubs = [] for n in map( lambda index: btc.get_public_node( self.client, parse_path("48'/145'/%d'" % index) ), range(1, 4), ): xpubs.append(n.xpub) def getmultisig(chain, nr, signatures=[b"", b"", b""], xpubs=xpubs): return proto.MultisigRedeemScriptType( nodes=[deserialize(xpub) for xpub in xpubs], address_n=[chain, nr], signatures=signatures, m=2, ) inp1 = proto.TxInputType( address_n=parse_path("48'/145'/3'/0/0"), multisig=getmultisig(0, 0), amount=48490, prev_hash=bytes.fromhex( "8b6db9b8ba24235d86b053ea2ccb484fc32b96f89c3c39f98d86f90db16076a0" ), prev_index=0, script_type=proto.InputScriptType.SPENDMULTISIG, ) out1 = proto.TxOutputType( address="bitcoincash:qqq8gx2j76nw4dfefumxmdwvtf2tpsjznusgsmzex9", amount=24000, script_type=proto.OutputScriptType.PAYTOADDRESS, ) out2 = proto.TxOutputType( address_n=parse_path("48'/145'/3'/1/0"), multisig=getmultisig(1, 0), script_type=proto.OutputScriptType.PAYTOMULTISIG, amount=24000, ) with self.client: self.client.set_expected_responses( [ proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.ButtonRequest(code=proto.ButtonRequestType.ConfirmOutput), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.ButtonRequest(code=proto.ButtonRequestType.SignTx), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.TxRequest(request_type=proto.RequestType.TXFINISHED), ] ) (signatures1, serialized_tx) = btc.sign_tx( self.client, "Bcash", [inp1], [out1, out2], prev_txes=TX_API ) assert ( signatures1[0].hex() == "3045022100a05f77bb39515c21c43e6c4ba401f39ed5d409dc3cfcd90f9a8345a08cc4bc8202205faf8f3b0775748278495324fdd60f370460452e4995e546450209ec4804a0f3" ) inp1 = proto.TxInputType( address_n=parse_path("48'/145'/1'/0/0"), multisig=getmultisig(0, 0, [b"", b"", signatures1[0]]), # bitcoincash:pqguz4nqq64jhr5v3kvpq4dsjrkda75hwy86gq0qzw amount=48490, prev_hash=bytes.fromhex( "8b6db9b8ba24235d86b053ea2ccb484fc32b96f89c3c39f98d86f90db16076a0" ), prev_index=0, script_type=proto.InputScriptType.SPENDMULTISIG, ) out2.address_n[2] = H_(1) with self.client: self.client.set_expected_responses( [ proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.ButtonRequest(code=proto.ButtonRequestType.ConfirmOutput), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.ButtonRequest(code=proto.ButtonRequestType.SignTx), proto.TxRequest( request_type=proto.RequestType.TXINPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=0), ), proto.TxRequest( request_type=proto.RequestType.TXOUTPUT, details=proto.TxRequestDetailsType(request_index=1), ), proto.TxRequest(request_type=proto.RequestType.TXFINISHED), ] ) (signatures1, serialized_tx) = btc.sign_tx( self.client, "Bcash", [inp1], [out1, out2], prev_txes=TX_API ) assert ( signatures1[0].hex() == "3044022006f239ef1f065a70873ab9d2c81a623a04ec7a37a0ec5299d3c585668f441f49022032b2f9ef13bc61230d14f6d79b9ad1bbebdf47b95e4757e9af1b1dcdf520d3ab" ) assert ( serialized_tx.hex() == "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" )

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Python

src/certipy/__init__.py

rlongio/certipy

901c3aa8f52814108b73ea000d91aec5fa8eca8d

[ "MIT" ]

null

src/certipy/__init__.py

rlongio/certipy

901c3aa8f52814108b73ea000d91aec5fa8eca8d

[ "MIT" ]

2

2021-01-06T06:47:01.000Z

2021-06-25T15:47:26.000Z

src/certipy/__init__.py

rlongio/certipy

901c3aa8f52814108b73ea000d91aec5fa8eca8d

[ "MIT" ]

null

from certipy.descriptors import *

17

33

0.823529

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624f5aadc27db776c78bd621727274f49c1aaee6

18,611

py

Python

tests/asgard/workers/autoscaler/test_autoscaler.py

rockerbacon/asgard-api

1c1eb19225ace4bbecb06b65b1b9c4ab131eb24a

[ "MIT" ]

3

2020-01-10T02:16:09.000Z

2020-02-19T18:42:37.000Z

tests/asgard/workers/autoscaler/test_autoscaler.py

b2wdigital/asgard-api

5444d81be33bf4af3c9cf5a2185c16ff10357034

[ "MIT" ]

13

2020-01-15T18:22:35.000Z

2021-03-31T19:21:54.000Z

tests/asgard/workers/autoscaler/test_autoscaler.py

rockerbacon/asgard-api

1c1eb19225ace4bbecb06b65b1b9c4ab131eb24a

[ "MIT" ]

6

2020-03-07T09:49:19.000Z

2021-07-25T03:14:10.000Z

from aioresponses import aioresponses from asynctest import TestCase from yarl import URL from asgard.conf import settings from asgard.workers.autoscaler.app import scale_all_apps from asgard.workers.autoscaler.asgard_cloudinterface import ( AsgardInterface as AsgardCloudInterface, ) from asgard.workers.autoscaler.periodicstatechecker import PeriodicStateChecker from asgard.workers.autoscaler.simple_decision_component import ( DecisionComponent, ) class AutoscalerTest(TestCase): async def test_scale_one_app(self): cloud_interface = AsgardCloudInterface() state_checker = PeriodicStateChecker(cloud_interface) decision_maker = DecisionComponent() with aioresponses() as rsps: stats_fixture = { "stats": { "type": "ASGARD", "errors": {}, "cpu_pct": "100", "ram_pct": "100", "cpu_thr_pct": "0", } } apps_fixture = { "apps": [ { "id": "/test_app1", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.3, "asgard.autoscale.mem": 0.8, "asgard.autoscale.ignore": "all", }, }, { "id": "/test_app2", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.1, "asgard.autoscale.mem": 0.1, "asgard.autoscale.ignore": "", }, }, ] } rsps.get( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload=apps_fixture, ) for app in apps_fixture["apps"]: rsps.get( f"{settings.ASGARD_API_ADDRESS}/apps{app['id']}/stats/avg-1min", status=200, payload=stats_fixture, ) rsps.put( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload={"deploymentId": "test", "version": "1.0"}, ) apps_stats = await state_checker.get_scalable_apps_stats() scaling_decision = decision_maker.decide_scaling_actions(apps_stats) await cloud_interface.apply_decisions(scaling_decision) scale_spy = rsps.requests.get( ("put", URL(f"{settings.ASGARD_API_ADDRESS}/v2/apps")) ) self.assertEqual(1, len(scaling_decision)) self.assertEqual(10, scaling_decision[0].mem) self.assertEqual("test_app2", scaling_decision[0].id) self.assertEqual(35, scaling_decision[0].cpu) self.assertIsNotNone(scale_spy) async def test_decide_to_scale_all_apps(self): cloud_interface = AsgardCloudInterface() state_checker = PeriodicStateChecker(cloud_interface) decision_maker = DecisionComponent() with aioresponses() as rsps: stats_fixture = { "stats": { "type": "ASGARD", "errors": {}, "cpu_pct": "100", "ram_pct": "100", "cpu_thr_pct": "0", } } apps_fixture = { "apps": [ { "id": "/test_app1", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.3, "asgard.autoscale.mem": 0.8, "asgard.autoscale.ignore": "cpu", }, }, { "id": "/test_app2", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.1, "asgard.autoscale.mem": 0.6, "asgard.autoscale.ignore": "mem", }, }, ] } rsps.get( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload=apps_fixture, ) for app in apps_fixture["apps"]: rsps.get( f"{settings.ASGARD_API_ADDRESS}/apps{app['id']}/stats/avg-1min", status=200, payload=stats_fixture, ) rsps.put( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload={"deploymentId": "test", "version": "1.0"}, ) apps_stats = await state_checker.get_scalable_apps_stats() scaling_decision = decision_maker.decide_scaling_actions(apps_stats) await cloud_interface.apply_decisions(scaling_decision) scale_spy = rsps.requests.get( ("put", URL(f"{settings.ASGARD_API_ADDRESS}/v2/apps")) ) self.assertEqual(len(apps_stats), len(scaling_decision)) self.assertEqual(1.25, scaling_decision[0].mem) self.assertEqual("test_app1", scaling_decision[0].id) self.assertEqual(None, scaling_decision[0].cpu) self.assertEqual("test_app2", scaling_decision[1].id) self.assertEqual(None, scaling_decision[1].mem) self.assertEqual(35, scaling_decision[1].cpu) self.assertIsNotNone(scale_spy) async def test_decide_to_scale_some_apps(self): cloud_interface = AsgardCloudInterface() state_checker = PeriodicStateChecker(cloud_interface) decision_maker = DecisionComponent() with aioresponses() as rsps: stats_fixture = { "stats": { "type": "ASGARD", "errors": {}, "cpu_pct": "100", "ram_pct": "100", "cpu_thr_pct": "0", } } apps_fixture = { "apps": [ { "id": "/test_app1", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.3, "asgard.autoscale.mem": 0.8, "asgard.autoscale.ignore": "all", }, }, { "id": "/test_app2", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.1, "asgard.autoscale.mem": 0.1, "asgard.autoscale.ignore": "", }, }, { "id": "/test_app3", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.5, "asgard.autoscale.mem": 0.7, "asgard.autoscale.ignore": "mem", }, }, ] } rsps.get( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload=apps_fixture, ) for app in apps_fixture["apps"]: rsps.get( f"{settings.ASGARD_API_ADDRESS}/apps{app['id']}/stats/avg-1min", status=200, payload=stats_fixture, ) rsps.put( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload={"deploymentId": "test", "version": "1.0"}, ) apps_stats = await state_checker.get_scalable_apps_stats() scaling_decision = decision_maker.decide_scaling_actions(apps_stats) await cloud_interface.apply_decisions(scaling_decision) scale_spy = rsps.requests.get( ("put", URL(f"{settings.ASGARD_API_ADDRESS}/v2/apps")) ) self.assertEqual(2, len(scaling_decision)) self.assertEqual(10, scaling_decision[0].mem) self.assertEqual("test_app2", scaling_decision[0].id) self.assertEqual(35, scaling_decision[0].cpu) self.assertEqual("test_app3", scaling_decision[1].id) self.assertEqual(None, scaling_decision[1].mem) self.assertEqual(7, scaling_decision[1].cpu) self.assertIsNotNone(scale_spy) async def test_decide_to_scale_no_apps(self): cloud_interface = AsgardCloudInterface() state_checker = PeriodicStateChecker(cloud_interface) decision_maker = DecisionComponent() with aioresponses() as rsps: stats_fixture = { "stats": { "type": "ASGARD", "errors": {}, "cpu_pct": "1", "ram_pct": "1", "cpu_thr_pct": "0", } } apps_fixture = { "apps": [ { "id": "/test_app1", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.3, "asgard.autoscale.mem": 0.8, "asgard.autoscale.ignore": "all", }, }, { "id": "/test_app2", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.1, "asgard.autoscale.mem": 0.1, "asgard.autoscale.ignore": "cpu,mem", }, }, ] } rsps.get( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload=apps_fixture, ) rsps.put( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload={"deploymentId": "test", "version": "1.0"}, ) for app in apps_fixture["apps"]: rsps.get( f"{settings.ASGARD_API_ADDRESS}/apps{app['id']}/stats/avg-1min", status=200, payload=stats_fixture, ) apps = await state_checker.get_scalable_apps_stats() scaling_decision = decision_maker.decide_scaling_actions(apps) await cloud_interface.apply_decisions(scaling_decision) scale_spy = rsps.requests.get( ("PUT", URL(f"{settings.ASGARD_API_ADDRESS}/v2/apps")) ) self.assertEqual(0, len(scaling_decision)) self.assertIsNone(scale_spy) async def test_does_not_scale_when_difference_less_than_5_percent(self): cloud_interface = AsgardCloudInterface() state_checker = PeriodicStateChecker(cloud_interface) decision_maker = DecisionComponent() with aioresponses() as rsps: stats_fixture = { "stats": { "type": "ASGARD", "errors": {}, "cpu_pct": "25.1", "ram_pct": "84.9", "cpu_thr_pct": "0", } } apps_fixture = { "apps": [ { "id": "/test_app1", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.3, "asgard.autoscale.mem": 0.8, }, } ] } rsps.get( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload=apps_fixture, ) rsps.put( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload={"deploymentId": "test", "version": "1.0"}, ) for app in apps_fixture["apps"]: rsps.get( f"{settings.ASGARD_API_ADDRESS}/apps{app['id']}/stats/avg-1min", status=200, payload=stats_fixture, ) apps_stats = await state_checker.get_scalable_apps_stats() scaling_decision = decision_maker.decide_scaling_actions(apps_stats) await cloud_interface.apply_decisions(scaling_decision) scale_spy = rsps.requests.get( ("PUT", URL(f"{settings.ASGARD_API_ADDRESS}/v2/apps")) ) self.assertEqual(0, len(scaling_decision)) self.assertEqual(1, len(apps_stats), "didn't fetch one app") self.assertEqual( 0, len(scaling_decision), "didn't make scaling decision" ) self.assertIsNone(scale_spy) async def test_scales_when_difference_more_than_5_percent(self): cloud_interface = AsgardCloudInterface() state_checker = PeriodicStateChecker(cloud_interface) decision_maker = DecisionComponent() with aioresponses() as rsps: stats_fixture = { "stats": { "type": "ASGARD", "errors": {}, "cpu_pct": "24.9", "ram_pct": "85.1", "cpu_thr_pct": "0", } } apps_fixture = { "apps": [ { "id": "/test_app1", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.3, "asgard.autoscale.mem": 0.8, }, } ] } rsps.get( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload=apps_fixture, ) rsps.put( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload={"deploymentId": "test", "version": "1.0"}, ) for app in apps_fixture["apps"]: rsps.get( f"{settings.ASGARD_API_ADDRESS}/apps{app['id']}/stats/avg-1min", status=200, payload=stats_fixture, ) apps_stats = await state_checker.get_scalable_apps_stats() scaling_decision = decision_maker.decide_scaling_actions(apps_stats) await cloud_interface.apply_decisions(scaling_decision) scale_spy = rsps.requests.get( ("put", URL(f"{settings.ASGARD_API_ADDRESS}/v2/apps")) ) self.assertEqual(1, len(apps_stats), "didn't fetch one app") self.assertEqual( 1, len(scaling_decision), "didn't make scaling decision" ) self.assertEqual( "test_app1", scaling_decision[0].id, "made decision for wrong app" ) self.assertEqual( 2.905, scaling_decision[0].cpu, "scaled cpu to incorrect value" ) self.assertEqual( 1.06375, scaling_decision[0].mem, "scaled memory to incorrect value" ) self.assertIsNotNone(scale_spy) async def test_worker_polling(self): with aioresponses() as rsps: stats_fixture = { "stats": { "type": "ASGARD", "errors": {}, "cpu_pct": "100", "ram_pct": "100", "cpu_thr_pct": "0", } } apps_fixture = { "apps": [ { "id": "/test_app1", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.3, "asgard.autoscale.mem": 0.8, "asgard.autoscale.ignore": "all", }, }, { "id": "/test_app2", "cpus": 3.5, "mem": 1.0, "labels": { "asgard.autoscale.cpu": 0.1, "asgard.autoscale.mem": 0.1, "asgard.autoscale.ignore": "", }, }, ] } body_fixture = [{"id": "test_app2", "mem": 10.0, "cpus": 35.0}] headers_fixture = { "Content-Type": "application/json", "Authorization": f"Token {settings.AUTOSCALER_AUTH_TOKEN}", } rsps.get( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload=apps_fixture, ) for app in apps_fixture["apps"]: rsps.get( f"{settings.ASGARD_API_ADDRESS}/apps{app['id']}/stats/avg-1min", status=200, payload=stats_fixture, ) rsps.put( f"{settings.ASGARD_API_ADDRESS}/v2/apps", status=200, payload={"deploymentId": "test", "version": "1.0"}, ) await scale_all_apps(None) scale_spy = rsps.requests.get( ("put", URL(f"{settings.ASGARD_API_ADDRESS}/v2/apps")) ) self.assertIsNotNone(scale_spy) self.assertEqual(body_fixture, scale_spy[0].kwargs.get("json"))

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62741ad09bb3e37ce9a5eed2a49e42a74de368ef

183

py

Python

app/cmuxovik/admin.py

artem343/cmuxovik

6f923f66ba47d0c513659c332fd8c89d21ea4abf

[ "MIT" ]

2

2020-03-31T18:01:55.000Z

2020-03-31T18:45:02.000Z

app/cmuxovik/admin.py

artem343/cmuxovik

6f923f66ba47d0c513659c332fd8c89d21ea4abf

[ "MIT" ]

35

2020-03-31T17:47:09.000Z

2022-03-12T00:22:54.000Z

app/cmuxovik/admin.py

artem343/cmuxovik

6f923f66ba47d0c513659c332fd8c89d21ea4abf

[ "MIT" ]

null

from django.contrib import admin from .models import Cmux, Tag, Author, Vote admin.site.register(Cmux) admin.site.register(Tag) admin.site.register(Author) admin.site.register(Vote)

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65905bfd4a48dc294e4630aaf88b314b42c4ecb4

98

py

Python

misago/misago/users/permissions/__init__.py

vascoalramos/misago-deployment

20226072138403108046c0afad9d99eb4163cedc

[ "MIT" ]

2

2021-03-06T21:06:13.000Z

2021-03-09T15:05:12.000Z

misago/users/permissions/__init__.py

HenryChenV/iJiangNan

68f156d264014939f0302222e16e3125119dd3e3

[ "MIT" ]

null

misago/users/permissions/__init__.py

HenryChenV/iJiangNan

68f156d264014939f0302222e16e3125119dd3e3

[ "MIT" ]

null

from .decorators import * from .delete import * from .moderation import * from .profiles import *

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1

0

1

0

1

0

6

02ec18dfc864d0a6c899ca80eaaffcc894cdf0dd

92

py

Python

test_ex1.py

assafine/IML.HUJI

b81b8beff05b5f120aa21a2f7fe90b4db95174f4

[ "MIT" ]

null

test_ex1.py

assafine/IML.HUJI

b81b8beff05b5f120aa21a2f7fe90b4db95174f4

[ "MIT" ]

null

test_ex1.py

assafine/IML.HUJI

b81b8beff05b5f120aa21a2f7fe90b4db95174f4

[ "MIT" ]

null

from IMLearn.learners import gaussian_estimators as ge def test_check(): assert 1==1

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0

6

f321e74e9db7a140ac368343c50ee96a580c20f5

158

py

Python

tlssecondopinion/views.py

MiWCryptAnalytics/tlssecondopinion

f1eebf753cc898ba546bf1371f3ce1ea848d17d6

[ "BSD-2-Clause" ]

null

tlssecondopinion/views.py

MiWCryptAnalytics/tlssecondopinion

f1eebf753cc898ba546bf1371f3ce1ea848d17d6

[ "BSD-2-Clause" ]

4

2017-04-13T02:51:42.000Z

2017-04-13T02:53:12.000Z

tlssecondopinion/views.py

MiWCryptAnalytics/tlssecondopinion

f1eebf753cc898ba546bf1371f3ce1ea848d17d6

[ "BSD-2-Clause" ]

null

from django.http import HttpResponseRedirect, HttpResponse from django.views.generic import View def index(request): return HttpResponseRedirect('scan')

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b84f811945d499d61f4cfa2c6c97c0f2b2f59b90

159

py

Python

web/forum/admin.py

borzunov/django-forum

37ee43327575e59a4f7e1fcaa9f3a1c0de08d2b3

[ "MIT" ]

null

web/forum/admin.py

borzunov/django-forum

37ee43327575e59a4f7e1fcaa9f3a1c0de08d2b3

[ "MIT" ]

null

web/forum/admin.py

borzunov/django-forum

37ee43327575e59a4f7e1fcaa9f3a1c0de08d2b3

[ "MIT" ]

null

from django.contrib import admin from .models import Section, Topic, Post admin.site.register(Section) admin.site.register(Topic) admin.site.register(Post)

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6

b86ac4a334151f71615d89701a5a23ee8fa3e500

46

py

Python

olivenodes/__init__.py

GordStephen/olivenodes

52fc2a1cc538da665c026f8c574db24add2d2b1b

[ "MIT" ]

null

olivenodes/__init__.py

GordStephen/olivenodes

52fc2a1cc538da665c026f8c574db24add2d2b1b

[ "MIT" ]

null

olivenodes/__init__.py

GordStephen/olivenodes

52fc2a1cc538da665c026f8c574db24add2d2b1b

[ "MIT" ]

null

from .graph import Graph from .nodes import *

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b86fbf8d8db90190972c4e419cdd67cbb59838e6

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py

Python

mlps/core/apeflow/interface/utils/__init__.py

seculayer/automl-mlps

80569909ec1c25db1ceafbb85b27d069d1a66aa3

[ "Apache-2.0" ]

null

mlps/core/apeflow/interface/utils/__init__.py

seculayer/automl-mlps

80569909ec1c25db1ceafbb85b27d069d1a66aa3

[ "Apache-2.0" ]

2

2022-03-31T07:39:59.000Z

2022-03-31T07:40:18.000Z

mlps/core/apeflow/interface/utils/__init__.py

seculayer/AutoAPE-mlps

80569909ec1c25db1ceafbb85b27d069d1a66aa3

[ "Apache-2.0" ]

1

2021-11-03T09:09:07.000Z

from . import gs, pytorch, tf

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6

b87439f8973b5e5d18727fc97759c6de6a5e3b66

35,743

py

Python

test/dataset_test.py

cs6ting/pytorch_geometric_temporal

c854cd6fb0998c528c3c564703f05eba7953ea65

[ "MIT" ]

1

2020-06-27T01:48:33.000Z

test/dataset_test.py

cs6ting/pytorch_geometric_temporal

c854cd6fb0998c528c3c564703f05eba7953ea65

[ "MIT" ]

null

test/dataset_test.py

cs6ting/pytorch_geometric_temporal

c854cd6fb0998c528c3c564703f05eba7953ea65

[ "MIT" ]

null

import numpy as np import networkx as nx from torch_geometric_temporal.signal import temporal_signal_split from torch_geometric_temporal.signal import StaticGraphTemporalSignal from torch_geometric_temporal.signal import DynamicGraphTemporalSignal from torch_geometric_temporal.signal import DynamicGraphStaticSignal from torch_geometric_temporal.signal import StaticHeteroGraphTemporalSignal from torch_geometric_temporal.signal import DynamicHeteroGraphTemporalSignal from torch_geometric_temporal.signal import DynamicHeteroGraphStaticSignal from torch_geometric_temporal.dataset import METRLADatasetLoader, PemsBayDatasetLoader from torch_geometric_temporal.dataset import ( ChickenpoxDatasetLoader, PedalMeDatasetLoader, WikiMathsDatasetLoader, EnglandCovidDatasetLoader, ) from torch_geometric_temporal.dataset import ( TwitterTennisDatasetLoader, MontevideoBusDatasetLoader, MTMDatasetLoader, ) from torch_geometric_temporal.dataset import ( WindmillOutputLargeDatasetLoader, WindmillOutputMediumDatasetLoader, WindmillOutputSmallDatasetLoader, ) def get_edge_array(n_count): return np.array([edge for edge in nx.gnp_random_graph(n_count, 0.1).edges()]).T def generate_signal(snapshot_count, n_count, feature_count, additional_features_keys=[]): edge_indices = [get_edge_array(n_count) for _ in range(snapshot_count)] edge_weights = [np.ones(edge_indices[t].shape[1]) for t in range(snapshot_count)] features = [ np.random.uniform(0, 1, (n_count, feature_count)) for _ in range(snapshot_count) ] if additional_features_keys: additional_features = { key: [np.random.uniform(0, 1, (n_count, feature_count)) for _ in range(snapshot_count) ] for key in additional_features_keys} return edge_indices, edge_weights, features, additional_features return edge_indices, edge_weights, features def generate_heterogeneous_signal(snapshot_count, n_count, feature_count, *additional_features_keys): edge_index_dicts = [{('author', 'writes', 'paper'): get_edge_array(n_count)} for _ in range(snapshot_count)] edge_weight_dicts = [{('author', 'writes', 'paper'): np.ones(edge_index_dicts[t][('author', 'writes', 'paper')].shape[1])} for t in range(snapshot_count)] feature_dicts = [{'author': np.random.uniform(0, 1, (n_count, feature_count)), 'paper': np.random.uniform(0, 1, (n_count, feature_count))} for _ in range(snapshot_count)] target_dicts = [{'author': np.random.uniform(0, 10, (n_count,)), 'paper': np.random.uniform(0, 10, (n_count,))} for _ in range(snapshot_count)] if additional_features_keys: additional_features = { key: [{'author': np.random.uniform(0, 1, (n_count, feature_count)), 'paper': np.random.uniform(0, 1, (n_count, feature_count))} for _ in range(snapshot_count)] for key in additional_features_keys} return edge_index_dicts, edge_weight_dicts, feature_dicts, target_dicts, additional_features return edge_index_dicts, edge_weight_dicts, feature_dicts, target_dicts def test_dynamic_graph_temporal_signal_real(): snapshot_count = 250 n_count = 100 feature_count = 32 edge_indices, edge_weights, features = generate_signal(250, 100, 32) targets = [np.random.uniform(0, 10, (n_count,)) for _ in range(snapshot_count)] dataset = DynamicGraphTemporalSignal(edge_indices, edge_weights, features, targets) for epoch in range(2): for snapshot in dataset: assert snapshot.edge_index.shape[0] == 2 assert snapshot.edge_index.shape[1] == snapshot.edge_attr.shape[0] assert snapshot.x.shape == (100, 32) assert snapshot.y.shape == (100,) targets = [ np.floor(np.random.uniform(0, 10, (n_count,))).astype(int) for _ in range(snapshot_count) ] dataset = DynamicGraphTemporalSignal(edge_indices, edge_weights, features, targets) for epoch in range(2): for snapshot in dataset: assert snapshot.edge_index.shape[0] == 2 assert snapshot.edge_index.shape[1] == snapshot.edge_attr.shape[0] assert snapshot.x.shape == (100, 32) assert snapshot.y.shape == (100,) def test_static_graph_temporal_signal(): dataset = StaticGraphTemporalSignal(None, None, [None, None], [None, None]) for snapshot in dataset: assert snapshot.edge_index is None assert snapshot.edge_attr is None assert snapshot.x is None assert snapshot.y is None def test_dynamic_graph_temporal_signal(): dataset = DynamicGraphTemporalSignal( [None, None], [None, None], [None, None], [None, None] ) for snapshot in dataset: assert snapshot.edge_index is None assert snapshot.edge_attr is None assert snapshot.x is None assert snapshot.y is None def test_static_graph_temporal_signal_typing(): dataset = StaticGraphTemporalSignal(None, None, [np.array([1])], [np.array([2])]) for snapshot in dataset: assert snapshot.edge_index is None assert snapshot.edge_attr is None assert snapshot.x.shape == (1,) assert snapshot.y.shape == (1,) def test_dynamic_graph_static_signal_typing(): dataset = DynamicGraphStaticSignal([None], [None], None, [None]) for snapshot in dataset: assert snapshot.edge_index is None assert snapshot.edge_attr is None assert snapshot.x is None assert snapshot.y is None def test_static_graph_temporal_signal_additional_attrs(): dataset = StaticGraphTemporalSignal(None, None, [None], [None], optional1=[np.array([1])], optional2=[np.array([2])]) assert dataset.additional_feature_keys == ["optional1", "optional2"] for snapshot in dataset: assert snapshot.optional1.shape == (1,) assert snapshot.optional2.shape == (1,) def test_dynamic_graph_static_signal_additional_attrs(): dataset = DynamicGraphStaticSignal([None], [None], None, [None], optional1=[np.array([1])], optional2=[np.array([2])]) assert dataset.additional_feature_keys == ["optional1", "optional2"] for snapshot in dataset: assert snapshot.optional1.shape == (1,) assert snapshot.optional2.shape == (1,) def test_dynamic_graph_temporal_signal_additional_attrs(): dataset = DynamicGraphTemporalSignal([None], [None], [None], [None], optional1=[np.array([1])], optional2=[np.array([2])]) assert dataset.additional_feature_keys == ["optional1", "optional2"] for snapshot in dataset: assert snapshot.optional1.shape == (1,) assert snapshot.optional2.shape == (1,) def test_static_hetero_graph_temporal_signal(): dataset = StaticHeteroGraphTemporalSignal(None, None, [None], [None]) for snapshot in dataset: assert len(snapshot.node_types) == 0 assert len(snapshot.node_stores) == 0 assert len(snapshot.edge_types) == 0 assert len(snapshot.edge_stores) == 0 def test_static_hetero_graph_temporal_signal_typing(): dataset = StaticHeteroGraphTemporalSignal(None, None, [{'author': np.array([1])}], [{'author': np.array([2])}]) for snapshot in dataset: assert snapshot.node_types[0] == 'author' assert snapshot.node_stores[0]['x'].shape == (1,) assert snapshot.node_stores[0]['y'].shape == (1,) assert len(snapshot.edge_types) == 0 def test_static_hetero_graph_temporal_signal_additional_attrs(): dataset = StaticHeteroGraphTemporalSignal(None, None, [None], [None], optional1=[{'author': np.array([1])}], optional2=[{'author': np.array([2])}], optional3=[None]) assert dataset.additional_feature_keys == ["optional1", "optional2", "optional3"] for snapshot in dataset: assert snapshot.node_stores[0]['optional1'].shape == (1,) assert snapshot.node_stores[0]['optional2'].shape == (1,) assert "optional3" not in list(dict(snapshot.node_stores[0]).keys()) def test_static_hetero_graph_temporal_signal_edges(): dataset = StaticHeteroGraphTemporalSignal({("author", "writes", "paper"): np.array([[0, 1], [1, 0]])}, {("author", "writes", "paper"): np.array([[0.1], [0.1]])}, [{"author": np.array([[0], [0]]), "paper": np.array([[0], [0], [0]])}, {"author": np.array([[0.1], [0.1]]), "paper": np.array([[0.1], [0.1], [0.1]])}], [None, None]) for snapshot in dataset: assert snapshot.edge_stores[0]['edge_index'].shape == (2, 2) assert snapshot.edge_stores[0]['edge_attr'].shape == (2, 1) assert snapshot.edge_stores[0]['edge_index'].shape[0] == snapshot.edge_stores[0]['edge_attr'].shape[0] def test_dynamic_hetero_graph_static_signal(): dataset = DynamicHeteroGraphStaticSignal([None], [None], None, [None]) for snapshot in dataset: assert len(snapshot.node_types) == 0 assert len(snapshot.node_stores) == 0 assert len(snapshot.edge_types) == 0 assert len(snapshot.edge_stores) == 0 def test_dynamic_hetero_graph_static_signal_typing(): dataset = DynamicHeteroGraphStaticSignal([None], [None], {'author': np.array([1])}, [{'author': np.array([2])}]) for snapshot in dataset: assert snapshot.node_types[0] == 'author' assert snapshot.node_stores[0]['x'].shape == (1,) assert snapshot.node_stores[0]['y'].shape == (1,) assert len(snapshot.edge_types) == 0 def test_dynamic_hetero_graph_static_signal_additional_attrs(): dataset = DynamicHeteroGraphStaticSignal([None], [None], None, [None], optional1=[{'author': np.array([1])}], optional2=[{'author': np.array([2])}], optional3=[None]) assert dataset.additional_feature_keys == ["optional1", "optional2", "optional3"] for snapshot in dataset: assert snapshot.node_stores[0]['optional1'].shape == (1,) assert snapshot.node_stores[0]['optional2'].shape == (1,) assert "optional3" not in list(dict(snapshot.node_stores[0]).keys()) def test_dynamic_hetero_graph_static_signal_edges(): dataset = DynamicHeteroGraphStaticSignal([{("author", "writes", "paper"): np.array([[0, 1], [1, 0]])}], [{("author", "writes", "paper"): np.array([[0.1], [0.1]])}], {"author": np.array([[0], [0]]), "paper": np.array([[0], [0], [0]])}, [None]) for snapshot in dataset: assert snapshot.edge_stores[0]['edge_index'].shape == (2, 2) assert snapshot.edge_stores[0]['edge_attr'].shape == (2, 1) assert snapshot.edge_stores[0]['edge_index'].shape[0] == snapshot.edge_stores[0]['edge_attr'].shape[0] def test_dynamic_hetero_graph_temporal_signal(): dataset = DynamicHeteroGraphTemporalSignal( [None, None], [None, None], [None, None], [None, None] ) for snapshot in dataset: assert len(snapshot.node_types) == 0 assert len(snapshot.node_stores) == 0 assert len(snapshot.edge_types) == 0 assert len(snapshot.edge_stores) == 0 def test_dynamic_hetero_graph_temporal_signal_typing(): dataset = DynamicHeteroGraphTemporalSignal([None], [None], [{'author': np.array([1])}], [{'author': np.array([2])}]) for snapshot in dataset: assert snapshot.node_types[0] == 'author' assert snapshot.node_stores[0]['x'].shape == (1,) assert snapshot.node_stores[0]['y'].shape == (1,) assert len(snapshot.edge_types) == 0 def test_dynamic_hetero_graph_temporal_signal_additional_attrs(): dataset = DynamicHeteroGraphTemporalSignal([None], [None], [None], [None], optional1=[{'author': np.array([1])}], optional2=[{'author': np.array([2])}], optional3=[None]) assert dataset.additional_feature_keys == ["optional1", "optional2", "optional3"] for snapshot in dataset: assert snapshot.node_stores[0]['optional1'].shape == (1,) assert snapshot.node_stores[0]['optional2'].shape == (1,) assert "optional3" not in list(dict(snapshot.node_stores[0]).keys()) def test_dynamic_hetero_graph_temporal_signal_edges(): dataset = DynamicHeteroGraphTemporalSignal([{("author", "writes", "paper"): np.array([[0, 1], [1, 0]])}], [{("author", "writes", "paper"): np.array([[0.1], [0.1]])}], [{"author": np.array([[0], [0]]), "paper": np.array([[0], [0], [0]])}], [None]) for snapshot in dataset: assert snapshot.edge_stores[0]['edge_index'].shape == (2, 2) assert snapshot.edge_stores[0]['edge_attr'].shape == (2, 1) assert snapshot.edge_stores[0]['edge_index'].shape[0] == snapshot.edge_stores[0]['edge_attr'].shape[0] def test_chickenpox(): loader = ChickenpoxDatasetLoader() dataset = loader.get_dataset() for epoch in range(3): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 102) assert snapshot.edge_attr.shape == (102,) assert snapshot.x.shape == (20, 4) assert snapshot.y.shape == (20,) def test_pedalme(): loader = PedalMeDatasetLoader() dataset = loader.get_dataset() for epoch in range(3): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 225) assert snapshot.edge_attr.shape == (225,) assert snapshot.x.shape == (15, 4) assert snapshot.y.shape == (15,) def test_wiki(): loader = WikiMathsDatasetLoader() dataset = loader.get_dataset() for epoch in range(1): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 27079) assert snapshot.edge_attr.shape == (27079,) assert snapshot.x.shape == (1068, 8) assert snapshot.y.shape == (1068,) def test_windmilllarge(): loader = WindmillOutputLargeDatasetLoader() dataset = loader.get_dataset() for epoch in range(2): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 101761) assert snapshot.edge_attr.shape == (101761,) assert snapshot.x.shape == (319, 8) assert snapshot.y.shape == (319,) def test_windmillsmall(): loader = WindmillOutputSmallDatasetLoader() dataset = loader.get_dataset() for epoch in range(2): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 121) assert snapshot.edge_attr.shape == (121,) assert snapshot.x.shape == (11, 8) assert snapshot.y.shape == (11,) def test_windmillmedium(): loader = WindmillOutputMediumDatasetLoader() dataset = loader.get_dataset() for epoch in range(2): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 676) assert snapshot.edge_attr.shape == (676,) assert snapshot.x.shape == (26, 8) assert snapshot.y.shape == (26,) def test_covid(): loader = EnglandCovidDatasetLoader() dataset = loader.get_dataset() for epoch in range(2): for snapshot in dataset: assert snapshot.edge_index.shape[0] == 2 assert snapshot.edge_attr.shape[0] == snapshot.edge_index.shape[1] assert snapshot.x.shape == (129, 8) assert snapshot.y.shape == (129,) def test_montevideobus(): loader = MontevideoBusDatasetLoader() dataset = loader.get_dataset() for epoch in range(1): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 690) assert snapshot.edge_attr.shape == (690,) assert snapshot.x.shape == (675, 4) assert snapshot.y.shape == (675,) def test_metrla(): loader = METRLADatasetLoader(raw_data_dir="/tmp/") dataset = loader.get_dataset() for epoch in range(2): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 1722) assert snapshot.edge_attr.shape == (1722,) assert snapshot.x.shape == (207, 2, 12) assert snapshot.y.shape == (207, 12) def test_metrla_task_generator(): loader = METRLADatasetLoader(raw_data_dir="/tmp/") dataset = loader.get_dataset(num_timesteps_in=6, num_timesteps_out=5) for epoch in range(2): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 1722) assert snapshot.edge_attr.shape == (1722,) assert snapshot.x.shape == (207, 2, 6) assert snapshot.y.shape == (207, 5) def test_pemsbay(): loader = PemsBayDatasetLoader(raw_data_dir="/tmp/") dataset = loader.get_dataset() for epoch in range(2): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 2694) assert snapshot.edge_attr.shape == (2694,) assert snapshot.x.shape == (325, 2, 12) assert snapshot.y.shape == (325, 2, 12) def test_pemsbay_task_generator(): loader = PemsBayDatasetLoader(raw_data_dir="/tmp/") dataset = loader.get_dataset(num_timesteps_in=6, num_timesteps_out=5) for epoch in range(2): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 2694) assert snapshot.edge_attr.shape == (2694,) assert snapshot.x.shape == (325, 2, 6) assert snapshot.y.shape == (325, 2, 5) def check_tennis_data(event_id, node_count, mode, edge_cnt): loader = TwitterTennisDatasetLoader(event_id, N=node_count, feature_mode=mode) dataset = loader.get_dataset() for epoch in range(3): i = 0 for snapshot in dataset: if node_count == 1000: assert snapshot.edge_index.shape == (2, edge_cnt[i]) assert snapshot.edge_attr.shape == (edge_cnt[i],) else: assert snapshot.edge_index.shape[1] <= edge_cnt[i] assert snapshot.edge_attr.shape[0] <= edge_cnt[i] if mode == "encoded": assert snapshot.x.shape == (node_count, 16) elif mode == "diagonal": assert snapshot.x.shape == (node_count, node_count) else: assert snapshot.x.shape == (node_count, 2) assert snapshot.y.shape == (node_count,) i += 1 def test_twitter_tennis_rg17(): edges_in_snapshots = [ 89, 61, 67, 283, 569, 515, 527, 262, 115, 85, 127, 315, 639, 841, 662, 341, 136, 108, 127, 257, 564, 664, 646, 424, 179, 82, 111, 250, 689, 897, 597, 352, 225, 109, 81, 305, 483, 816, 665, 310, 141, 145, 86, 285, 748, 703, 682, 341, 199, 102, 84, 327, 786, 776, 419, 208, 91, 78, 83, 263, 670, 880, 731, 361, 122, 68, 101, 269, 547, 673, 612, 221, 156, 99, 137, 262, 373, 368, 648, 288, 127, 62, 84, 319, 936, 889, 699, 291, 186, 83, 99, 191, 343, 502, 561, 283, 96, 92, 74, 178, 461, 720, 712, 279, 88, 41, 74, 137, 266, 664, 364, 167, 68, 59, 48, 178, 391, 815, 315, 189, ] check_tennis_data("rg17", 1000, None, edges_in_snapshots) check_tennis_data("rg17", 50, "diagonal", edges_in_snapshots) def test_twitter_tennis_uo17(): edges_in_snapshots = [ 88, 113, 273, 423, 718, 625, 640, 758, 434, 137, 289, 450, 625, 489, 336, 462, 284, 130, 188, 335, 523, 652, 584, 619, 452, 198, 206, 387, 464, 698, 601, 434, 279, 180, 162, 350, 613, 793, 474, 368, 231, 195, 152, 404, 591, 709, 642, 476, 413, 248, 160, 296, 521, 727, 725, 542, 200, 157, 268, 382, 638, 612, 640, 588, 250, 142, 142, 197, 341, 458, 395, 535, 256, 128, 180, 274, 732, 610, 632, 732, 481, 194, 206, 241, 287, 304, 376, 742, 196, 172, 117, 220, 311, 389, 610, 596, 165, 183, 183, 163, 406, 738, 464, 209, 103, 143, 115, 227, 203, 455, 638, 195, ] check_tennis_data("uo17", 1000, None, edges_in_snapshots) check_tennis_data("uo17", 200, "encoded", edges_in_snapshots) def test_mtm(): loader = MTMDatasetLoader() dataset = loader.get_dataset() for epoch in range(3): for snapshot in dataset: assert snapshot.edge_index.shape == (2, 19) assert snapshot.edge_attr.shape == (19,) assert snapshot.x.shape == (3, 21, 16) assert snapshot.y.shape == (16, 6) def test_discrete_train_test_split_static(): loader = ChickenpoxDatasetLoader() dataset = loader.get_dataset() train_dataset, test_dataset = temporal_signal_split(dataset, 0.8) for epoch in range(2): for snapshot in train_dataset: assert snapshot.edge_index.shape == (2, 102) assert snapshot.edge_attr.shape == (102,) assert snapshot.x.shape == (20, 4) assert snapshot.y.shape == (20,) for epoch in range(2): for snapshot in test_dataset: assert snapshot.edge_index.shape == (2, 102) assert snapshot.edge_attr.shape == (102,) assert snapshot.x.shape == (20, 4) assert snapshot.y.shape == (20,) def test_discrete_train_test_split_dynamic(): snapshot_count = 250 n_count = 100 feature_count = 32 edge_indices, edge_weights, features, additional_features = generate_signal( 250, 100, 32, ["optional1", "optional2"] ) targets = [np.random.uniform(0, 10, (n_count,)) for _ in range(snapshot_count)] dataset = DynamicGraphTemporalSignal( edge_indices, edge_weights, features, targets, **additional_features ) train_dataset, test_dataset = temporal_signal_split(dataset, 0.8) for epoch in range(2): for snapshot in test_dataset: assert snapshot.edge_index.shape[0] == 2 assert snapshot.edge_index.shape[1] == snapshot.edge_attr.shape[0] assert snapshot.x.shape == (100, 32) assert snapshot.y.shape == (100,) assert getattr(snapshot, "optional1").shape == (100, 32) assert getattr(snapshot, "optional2").shape == (100, 32) for epoch in range(2): for snapshot in train_dataset: assert snapshot.edge_index.shape[0] == 2 assert snapshot.edge_index.shape[1] == snapshot.edge_attr.shape[0] assert snapshot.x.shape == (100, 32) assert snapshot.y.shape == (100,) assert getattr(snapshot, "optional1").shape == (100, 32) assert getattr(snapshot, "optional2").shape == (100, 32) def test_train_test_split_dynamic_graph_static_signal(): snapshot_count = 250 n_count = 100 feature_count = 32 edge_indices, edge_weights, features, additional_features = generate_signal( 250, 100, 32, ["optional1", "optional2"] ) targets = [np.random.uniform(0, 10, (n_count,)) for _ in range(snapshot_count)] dataset = StaticGraphTemporalSignal( edge_indices[0], edge_weights[0], features, targets, **additional_features ) train_dataset, test_dataset = temporal_signal_split(dataset, 0.8) for epoch in range(2): for snapshot in test_dataset: assert snapshot.edge_index.shape[0] == 2 assert snapshot.edge_index.shape[1] == snapshot.edge_attr.shape[0] assert snapshot.x.shape == (100, 32) assert snapshot.y.shape == (100,) assert getattr(snapshot, "optional1").shape == (100, 32) assert getattr(snapshot, "optional2").shape == (100, 32) for epoch in range(2): for snapshot in train_dataset: assert snapshot.edge_index.shape[0] == 2 assert snapshot.edge_index.shape[1] == snapshot.edge_attr.shape[0] assert snapshot.x.shape == (100, 32) assert snapshot.y.shape == (100,) assert getattr(snapshot, "optional1").shape == (100, 32) assert getattr(snapshot, "optional2").shape == (100, 32) def test_discrete_train_test_split_dynamic_graph_static_signal(): snapshot_count = 250 n_count = 100 feature_count = 32 edge_indices, edge_weights, features, additional_features = generate_signal( 250, 100, 32, ["optional1", "optional2"] ) feature = features[0] targets = [np.random.uniform(0, 10, (n_count,)) for _ in range(snapshot_count)] dataset = DynamicGraphStaticSignal( edge_indices, edge_weights, feature, targets, **additional_features ) train_dataset, test_dataset = temporal_signal_split(dataset, 0.8) for epoch in range(2): for snapshot in test_dataset: assert snapshot.edge_index.shape[0] == 2 assert snapshot.edge_index.shape[1] == snapshot.edge_attr.shape[0] assert snapshot.x.shape == (100, 32) assert snapshot.y.shape == (100,) assert getattr(snapshot, "optional1").shape == (100, 32) assert getattr(snapshot, "optional2").shape == (100, 32) for epoch in range(2): for snapshot in train_dataset: assert snapshot.edge_index.shape[0] == 2 assert snapshot.edge_index.shape[1] == snapshot.edge_attr.shape[0] assert snapshot.x.shape == (100, 32) assert snapshot.y.shape == (100,) assert getattr(snapshot, "optional1").shape == (100, 32) assert getattr(snapshot, "optional2").shape == (100, 32) def test_train_test_split_dynamic_hetero_graph_temporal_signal(): snapshot_count = 250 n_count = 100 feature_count = 32 edge_index_dicts, edge_weight_dicts, feature_dicts, target_dicts, additional_feature_dicts = generate_heterogeneous_signal( snapshot_count, n_count, feature_count, "optional1", "optional2" ) dataset = DynamicHeteroGraphTemporalSignal( edge_index_dicts, edge_weight_dicts, feature_dicts, target_dicts, **additional_feature_dicts ) train_dataset, test_dataset = temporal_signal_split(dataset, 0.8) for epoch in range(2): for snapshot in test_dataset: assert len(snapshot.node_types) == 2 assert snapshot.node_types[0] == 'author' assert snapshot.node_types[1] == 'paper' assert snapshot.node_stores[0]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[0]['y'].shape == (n_count,) assert snapshot.node_stores[1]['y'].shape == (n_count,) assert len(snapshot.edge_types) == 1 assert snapshot.edge_types[0] == ('author', 'writes', 'paper') assert snapshot.edge_stores[0].edge_index.shape[0] == 2 assert snapshot.edge_stores[0].edge_index.shape[1] == snapshot.edge_stores[0].edge_attr.shape[0] assert snapshot.node_stores[1]['optional1'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['optional2'].shape == (n_count, feature_count) for epoch in range(2): for snapshot in train_dataset: assert len(snapshot.node_types) == 2 assert snapshot.node_types[0] == 'author' assert snapshot.node_types[1] == 'paper' assert snapshot.node_stores[0]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[0]['y'].shape == (n_count,) assert snapshot.node_stores[1]['y'].shape == (n_count,) assert len(snapshot.edge_types) == 1 assert snapshot.edge_types[0] == ('author', 'writes', 'paper') assert snapshot.edge_stores[0].edge_index.shape[0] == 2 assert snapshot.edge_stores[0].edge_index.shape[1] == snapshot.edge_stores[0].edge_attr.shape[0] assert snapshot.node_stores[1]['optional1'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['optional2'].shape == (n_count, feature_count) def test_train_test_split_static_hetero_graph_temporal_signal(): snapshot_count = 250 n_count = 100 feature_count = 32 edge_index_dicts, edge_weight_dicts, feature_dicts, target_dicts, additional_feature_dicts = generate_heterogeneous_signal( snapshot_count, n_count, feature_count, "optional1", "optional2" ) dataset = StaticHeteroGraphTemporalSignal( edge_index_dicts[0], edge_weight_dicts[0], feature_dicts, target_dicts, **additional_feature_dicts ) train_dataset, test_dataset = temporal_signal_split(dataset, 0.8) for epoch in range(2): for snapshot in test_dataset: assert len(snapshot.node_types) == 2 assert snapshot.node_types[0] == 'author' assert snapshot.node_types[1] == 'paper' assert snapshot.node_stores[0]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[0]['y'].shape == (n_count,) assert snapshot.node_stores[1]['y'].shape == (n_count,) assert len(snapshot.edge_types) == 1 assert snapshot.edge_types[0] == ('author', 'writes', 'paper') assert snapshot.edge_stores[0].edge_index.shape[0] == 2 assert snapshot.edge_stores[0].edge_index.shape[1] == snapshot.edge_stores[0].edge_attr.shape[0] assert snapshot.node_stores[1]['optional1'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['optional2'].shape == (n_count, feature_count) for epoch in range(2): for snapshot in train_dataset: assert len(snapshot.node_types) == 2 assert snapshot.node_types[0] == 'author' assert snapshot.node_types[1] == 'paper' assert snapshot.node_stores[0]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[0]['y'].shape == (n_count,) assert snapshot.node_stores[1]['y'].shape == (n_count,) assert len(snapshot.edge_types) == 1 assert snapshot.edge_types[0] == ('author', 'writes', 'paper') assert snapshot.edge_stores[0].edge_index.shape[0] == 2 assert snapshot.edge_stores[0].edge_index.shape[1] == snapshot.edge_stores[0].edge_attr.shape[0] assert snapshot.node_stores[1]['optional1'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['optional2'].shape == (n_count, feature_count) def test_train_test_split_dynamic_hetero_graph_static_signal(): snapshot_count = 250 n_count = 100 feature_count = 32 edge_index_dicts, edge_weight_dicts, feature_dicts, target_dicts, additional_feature_dicts = generate_heterogeneous_signal( snapshot_count, n_count, feature_count, "optional1", "optional2" ) dataset = DynamicHeteroGraphStaticSignal( edge_index_dicts, edge_weight_dicts, feature_dicts[0], target_dicts, **additional_feature_dicts ) train_dataset, test_dataset = temporal_signal_split(dataset, 0.8) for epoch in range(2): for snapshot in test_dataset: assert len(snapshot.node_types) == 2 assert snapshot.node_types[0] == 'author' assert snapshot.node_types[1] == 'paper' assert snapshot.node_stores[0]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[0]['y'].shape == (n_count,) assert snapshot.node_stores[1]['y'].shape == (n_count,) assert len(snapshot.edge_types) == 1 assert snapshot.edge_types[0] == ('author', 'writes', 'paper') assert snapshot.edge_stores[0].edge_index.shape[0] == 2 assert snapshot.edge_stores[0].edge_index.shape[1] == snapshot.edge_stores[0].edge_attr.shape[0] assert snapshot.node_stores[1]['optional1'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['optional2'].shape == (n_count, feature_count) for epoch in range(2): for snapshot in train_dataset: assert len(snapshot.node_types) == 2 assert snapshot.node_types[0] == 'author' assert snapshot.node_types[1] == 'paper' assert snapshot.node_stores[0]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['x'].shape == (n_count, feature_count) assert snapshot.node_stores[0]['y'].shape == (n_count,) assert snapshot.node_stores[1]['y'].shape == (n_count,) assert len(snapshot.edge_types) == 1 assert snapshot.edge_types[0] == ('author', 'writes', 'paper') assert snapshot.edge_stores[0].edge_index.shape[0] == 2 assert snapshot.edge_stores[0].edge_index.shape[1] == snapshot.edge_stores[0].edge_attr.shape[0] assert snapshot.node_stores[1]['optional1'].shape == (n_count, feature_count) assert snapshot.node_stores[1]['optional2'].shape == (n_count, feature_count)

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b8babb922debcc53d4eff231c9a6594f89d4ae65

111

py

Python

basic_examples/test_2_const.py

yurioliveira3/Python

02a3ea3bd44f93e51d5fc8b9cc017cf53e68266d

[ "MIT" ]

null

basic_examples/test_2_const.py

yurioliveira3/Python

02a3ea3bd44f93e51d5fc8b9cc017cf53e68266d

[ "MIT" ]

null

basic_examples/test_2_const.py

yurioliveira3/Python

02a3ea3bd44f93e51d5fc8b9cc017cf53e68266d

[ "MIT" ]

null

class A: def __init__(self): print("1") def __init__(self): print("2") a= A()

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b21d202ec481227d6aa61310ac31e8d5203dbd9e

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py

Python

src/infrastructure/clients/provider/xchange_api/exceptions.py

sdediego/forex-django-clean-architecture

915a8d844a8db5a40c726fe4cf9f6d50f7c95275

[ "MIT" ]

8

2021-11-09T16:43:38.000Z

2022-03-25T16:04:26.000Z

src/infrastructure/clients/provider/xchange_api/exceptions.py

sdediego/forex-django-clean-architecture

915a8d844a8db5a40c726fe4cf9f6d50f7c95275

[ "MIT" ]

null

src/infrastructure/clients/provider/xchange_api/exceptions.py

sdediego/forex-django-clean-architecture

915a8d844a8db5a40c726fe4cf9f6d50f7c95275

[ "MIT" ]

2

2021-11-16T21:17:31.000Z

2022-02-11T11:15:29.000Z

# coding: utf-8 from src.infrastructure.clients.provider.exceptions import ProviderDriverError class XChangeAPIDriverError(ProviderDriverError): pass

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b2588fcc26158f6f11a505faab691ec793b0b8ed

14,232

py

Python

polaris/polaris/tests/sep12/test_customer.py

Zagan202/django-polaris

62802ec1585b57cd34e99e3993f2ddff662b9aaf

[ "Apache-2.0" ]

null

polaris/polaris/tests/sep12/test_customer.py

Zagan202/django-polaris

62802ec1585b57cd34e99e3993f2ddff662b9aaf

[ "Apache-2.0" ]

null

polaris/polaris/tests/sep12/test_customer.py

Zagan202/django-polaris

62802ec1585b57cd34e99e3993f2ddff662b9aaf

[ "Apache-2.0" ]

null

from django.core.exceptions import ObjectDoesNotExist from unittest.mock import Mock, patch from urllib.parse import urlencode from polaris.tests.helpers import ( mock_check_auth_success, mock_check_auth_success_with_memo, ) from stellar_sdk.keypair import Keypair endpoint = "/kyc/customer" mock_success_integration = Mock( get=Mock(return_value={"status": "ACCEPTED"}), put=Mock(return_value="123"), ) @patch("polaris.sep12.customer.rci", mock_success_integration) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_put_success(client): response = client.put( endpoint, data={ "account": "test source address", "first_name": "Test", "email_address": "test@example.com", }, content_type="application/json", ) assert response.status_code == 202 assert response.json() == {"id": "123"} @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) @patch("polaris.sep12.customer.rci", mock_success_integration) def test_put_existing_id(client): response = client.put( endpoint, data={ "account": "test source address", "first_name": "Test", "email_address": "test@example.com", }, content_type="application/json", ) response = client.put( endpoint, data={ "id": response.json()["id"], "first_name": "Test2", "email_address": "test@example.com", }, content_type="application/json", ) assert response.status_code == 202 assert response.json() == {"id": "123"} mock_raise_bad_id_error = Mock(put=Mock(side_effect=ObjectDoesNotExist("bad id"))) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) @patch("polaris.sep12.customer.rci", mock_raise_bad_id_error) def test_bad_existing_id(client): response = client.put( endpoint, data={ "id": "notanid", "first_name": "Test2", "email_address": "test@example.com", }, content_type="application/json", ) assert response.status_code == 404 assert response.json()["error"] == "bad id" @patch("polaris.sep12.customer.rci", mock_success_integration) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_put_memo(client): response = client.put( endpoint, data={ "account": "test source address", "memo": "text memo", "memo_type": "text", "first_name": "Test", "email_address": "test@example.com", }, content_type="application/json", ) assert response.status_code == 202 assert response.json() == {"id": "123"} @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_put_bad_account(client): response = client.put( endpoint, data={ "account": "doesn't match mocked auth", "first_name": "Test", "email_address": "test@example.com", }, content_type="application/json", ) assert response.status_code == 403 assert "error" in response.json() def test_put_no_auth(client): response = client.put( endpoint, data={ "account": "doesn't match mocked auth", "first_name": "Test", "email_address": "test@example.com", }, content_type="application/json", ) assert response.status_code == 403 assert "error" in response.json() @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_put_bad_memo_type(client): response = client.put( endpoint, data={ "account": "test source address", "memo": "text memo", "memo_type": "not text", "first_name": "Test", "email_address": "test@example.com", }, content_type="application/json", ) assert response.status_code == 400 assert "error" in response.json() @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_put_bad_memo(client): response = client.put( endpoint, data={ "account": "test source address", "memo": 123, "memo_type": "text", "first_name": "Test", "email_address": "test@example.com", }, content_type="application/json", ) assert response.status_code == 400 assert "error" in response.json() @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_put_missing_memo(client): response = client.put( endpoint, data={ "account": "test source address", "memo_type": "text", "first_name": "Test", "email_address": "test@example.com", }, content_type="application/json", ) assert response.status_code == 400 assert "error" in response.json() @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_put_missing_memo_type(client): response = client.put( endpoint, data={ "account": "test source address", "memo": 123, "first_name": "Test", "email_address": "test@example.com", }, content_type="application/json", ) assert response.status_code == 400 assert "error" in response.json() mock_put = Mock(return_value="123") @patch("polaris.sep12.customer.rci.put", mock_put) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_sep9_params(client): response = client.put( endpoint, data={ "account": "test source address", "first_name": "Test", "email_address": "test@example.com", "not-a-sep9-param": 1, }, content_type="application/json", ) mock_put.assert_called_with( { "id": None, "memo": None, "memo_type": None, "account": "test source address", "first_name": "Test", "email_address": "test@example.com", } ) mock_put.reset_mock() assert response.status_code == 202 assert response.json() == {"id": "123"} mock_get_accepted = Mock(return_value={"status": "ACCEPTED", "id": "123"}) @patch("polaris.sep12.customer.rci.get", mock_get_accepted) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_get_accepted(client): response = client.get( endpoint + "?" + urlencode({"account": "test source address"}) ) assert response.status_code == 200 assert response.json() == {"status": "ACCEPTED", "id": "123"} @patch("polaris.sep12.customer.rci.get", Mock()) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_get_bad_auth(client): response = client.get(endpoint + "?" + urlencode({"account": "not a match"})) assert response.status_code == 403 assert "error" in response.json() def test_get_no_auth(client): response = client.get( endpoint + "?" + urlencode({"account": "test source address"}) ) assert response.status_code == 403 assert "error" in response.json() @patch("polaris.sep12.customer.rci", mock_success_integration) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_no_id_or_account(client): response = client.get(endpoint) assert response.status_code == 200 @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_get_bad_memo_type(client): response = client.get( endpoint + "?" + urlencode( { "account": "test source address", "memo": "text memo", "memo_type": "not text", } ), ) assert response.status_code == 400 assert "error" in response.json() @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_get_bad_memo(client): response = client.get( endpoint + "?" + urlencode( { "account": "test source address", "memo": "not a hash", "memo_type": "hash", } ), ) assert response.status_code == 400 assert "error" in response.json() @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_get_missing_memo(client): response = client.get( endpoint + "?" + urlencode({"account": "test source address", "memo_type": "text",}), ) assert response.status_code == 400 assert "error" in response.json() @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_get_missing_memo_type(client): response = client.get( endpoint + "?" + urlencode({"account": "test source address", "memo": "123"}) ) assert response.status_code == 400 assert "error" in response.json() @patch( "polaris.sep12.customer.rci.get", Mock( return_value={ "id": "123", "status": "NEEDS_INFO", "fields": { "email_address": { "description": "Email address of the user", "type": "string", } }, } ), ) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_valid_needs_info_response(client): response = client.get( endpoint + "?" + urlencode({"account": "test source address"}) ) assert response.status_code == 200 assert response.json() == { "id": "123", "status": "NEEDS_INFO", "fields": { "email_address": { "description": "Email address of the user", "type": "string", } }, } @patch( "polaris.sep12.customer.rci.get", Mock( return_value={ "status": "NEEDS_INFO", "fields": { "not a sep9 field": { "description": "good description", "type": "string", } }, } ), ) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_bad_field_needs_info(client): response = client.get( endpoint + "?" + urlencode({"account": "test source address"}) ) assert response.status_code == 500 @patch( "polaris.sep12.customer.rci.get", Mock( return_value={ "status": "NEEDS_INFO", "fields": {"email_address": {"description": "a description",}}, } ), ) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_missing_type_field_needs_info(client): response = client.get( endpoint + "?" + urlencode({"account": "test source address"}) ) assert response.status_code == 500 @patch( "polaris.sep12.customer.rci.get", Mock( return_value={ "status": "NEEDS_INFO", "fields": { "email_address": {"description": "a description", "unknown_field": True} }, } ), ) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_unknown_attr_needs_info(client): response = client.get( endpoint + "?" + urlencode({"account": "test source address"}) ) assert response.status_code == 500 @patch( "polaris.sep12.customer.rci.get", Mock( return_value={ "status": "NEEDS_INFO", "fields": {"email_address": {"type": "string"}}, } ), ) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_no_description_needs_info(client): response = client.get( endpoint + "?" + urlencode({"account": "test source address"}) ) assert response.status_code == 500 @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_delete_success(client): response = client.delete("/".join([endpoint, "test source address"])) assert response.status_code == 200 @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_bad_auth_delete(client): response = client.delete("/".join([endpoint, Keypair.random().public_key])) assert response.status_code == 404 @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) def test_bad_memo_delete(client): response = client.delete( "/".join([endpoint, "test source address"]), data={"memo": "not a valid hash memo", "memo_type": "hash"}, content_type="application/json", ) assert response.status_code == 400 assert "memo" in response.json()["error"] @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) @patch("polaris.sep12.customer.rci.delete") def test_delete_memo_customer(mock_delete, client): response = client.delete( "/".join([endpoint, "test source address"]), data={"memo": "test memo string", "memo_type": "text"}, content_type="application/json", ) assert response.status_code == 200 mock_delete.assert_called_with("test source address", "test memo string", "text") @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) @patch("polaris.sep12.customer.rci.delete") def test_delete_memo_customer_with_memo(mock_delete, client): response = client.delete( "/".join([endpoint, "test source address"]), data={"memo": "test memo string", "memo_type": "text"}, content_type="application/json", ) assert response.status_code == 200 mock_delete.assert_called_with("test source address", "test memo string", "text") mock_bad_delete = Mock(side_effect=ObjectDoesNotExist) @patch("polaris.sep10.utils.check_auth", mock_check_auth_success) @patch("polaris.sep12.customer.rci.delete", mock_bad_delete) def test_delete_memo_not_found(client): response = client.delete( "/".join([endpoint, "test source address"]), data={"memo": "test memo string", "memo_type": "text"}, content_type="application/json", ) assert response.status_code == 404 mock_bad_delete.assert_called_with( "test source address", "test memo string", "text" )

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6

b2637cfb0bf86764434a09bf9a4440835ecbd6fe

24

py

Python

speaksee/evaluation/spice/__init__.py

aimagelab/speaksee

63700a4062e2ae00132a5c77007604fdaf4bd00b

[ "BSD-3-Clause" ]

29

2019-02-28T05:29:53.000Z

2021-01-25T06:55:48.000Z

speaksee/evaluation/spice/__init__.py

aimagelab/speaksee

63700a4062e2ae00132a5c77007604fdaf4bd00b

[ "BSD-3-Clause" ]

2

2019-10-26T02:29:59.000Z

2021-01-15T13:58:53.000Z

speaksee/evaluation/spice/__init__.py

aimagelab/speaksee

63700a4062e2ae00132a5c77007604fdaf4bd00b

[ "BSD-3-Clause" ]

11

2019-03-12T08:43:09.000Z

2021-03-15T03:20:43.000Z

from .spice import Spice

24

0.833333

4

24

5

0.75

0

0.125

24

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1

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1

0

6

b2a29ee706126390fba24b52eeaceb6a50f97b1f

142

py

Python

info.py

NuCOS/nucosMQ

a66d25bb71eaaa176710ab8da820de90421760b3

[ "MIT" ]

1

2017-10-10T17:56:57.000Z

info.py

NuCOS/nucosObs

ff75a78efb7709cb57dfc91dab96d94c2c1d491b

[ "MIT" ]

1

2021-01-15T12:38:15.000Z

info.py

NuCOS/nucosCR

2fac4932603e00a615c73c73c58a156704ff4fa1

[ "MIT" ]

1

2018-04-08T07:56:22.000Z

from __future__ import print_function import sys import setuptools print ("VERSION: ",sys.version_info) print ("PATH: ", setuptools.__file__)

23.666667

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null

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1

0

1

0

6

a2592c3096510a48b7429c4a82edae9de7d5fe13

7,170

py

Python

quadpy/quadrilateral/__init__.py

whzup/quadpy

ca8bd2f9c5a4ae30dc85d8fb79217602bd42525e

[ "MIT" ]

null

quadpy/quadrilateral/__init__.py

whzup/quadpy

ca8bd2f9c5a4ae30dc85d8fb79217602bd42525e

[ "MIT" ]

null

quadpy/quadrilateral/__init__.py

whzup/quadpy

ca8bd2f9c5a4ae30dc85d8fb79217602bd42525e

[ "MIT" ]

null

from ..ncube import ncube_points as rectangle_points from ..ncube import transform from ._albrecht_collatz import ( albrecht_collatz_1, albrecht_collatz_2, albrecht_collatz_3, albrecht_collatz_4, ) from ._burnside import burnside from ._cohen_gismalla import cohen_gismalla_1, cohen_gismalla_2 from ._cools_haegemans_1985 import ( cools_haegemans_1985_1, cools_haegemans_1985_2, cools_haegemans_1985_3, ) from ._cools_haegemans_1988 import cools_haegemans_1988_1, cools_haegemans_1988_2 from ._dunavant import ( dunavant_00, dunavant_01, dunavant_02, dunavant_03, dunavant_04, dunavant_05, dunavant_06, dunavant_07, dunavant_08, dunavant_09, dunavant_10, ) from ._franke import ( franke_1, franke_2a, franke_2b, franke_3a, franke_3b, franke_3c, franke_5, franke_6, franke_8, ) from ._haegemans_piessens import haegemans_piessens from ._hammer_stroud import hammer_stroud_1_2, hammer_stroud_2_2, hammer_stroud_3_2 from ._irwin import irwin_1, irwin_2 from ._maxwell import maxwell from ._meister import meister from ._miller import miller from ._morrow_patterson import morrow_patterson_1, morrow_patterson_2 from ._phillips import phillips from ._piessens_haegemans import piessens_haegemans_1, piessens_haegemans_2 from ._product import product from ._rabinowitz_richter import ( rabinowitz_richter_1, rabinowitz_richter_2, rabinowitz_richter_3, rabinowitz_richter_4, rabinowitz_richter_5, rabinowitz_richter_6, ) from ._schmid import schmid_2, schmid_4, schmid_6 from ._sommariva import ( sommariva_01, sommariva_02, sommariva_03, sommariva_04, sommariva_05, sommariva_06, sommariva_07, sommariva_08, sommariva_09, sommariva_10, sommariva_11, sommariva_12, sommariva_13, sommariva_14, sommariva_15, sommariva_16, sommariva_17, sommariva_18, sommariva_19, sommariva_20, sommariva_21, sommariva_22, sommariva_23, sommariva_24, sommariva_25, sommariva_26, sommariva_27, sommariva_28, sommariva_29, sommariva_30, sommariva_31, sommariva_32, sommariva_33, sommariva_34, sommariva_35, sommariva_36, sommariva_37, sommariva_38, sommariva_39, sommariva_40, sommariva_41, sommariva_42, sommariva_43, sommariva_44, sommariva_45, sommariva_46, sommariva_47, sommariva_48, sommariva_49, sommariva_50, sommariva_51, sommariva_52, sommariva_53, sommariva_54, sommariva_55, ) from ._stroud import ( stroud_c2_1_1, stroud_c2_1_2, stroud_c2_3_1, stroud_c2_3_2, stroud_c2_3_3, stroud_c2_3_4, stroud_c2_3_5, stroud_c2_5_1, stroud_c2_5_2, stroud_c2_5_3, stroud_c2_5_4, stroud_c2_5_5, stroud_c2_5_6, stroud_c2_5_7, stroud_c2_7_1, stroud_c2_7_2, stroud_c2_7_3, stroud_c2_7_4, stroud_c2_7_5, stroud_c2_7_6, stroud_c2_9_1, stroud_c2_11_1, stroud_c2_11_2, stroud_c2_13_1, stroud_c2_15_1, stroud_c2_15_2, ) from ._tyler import tyler_1, tyler_2, tyler_3 from ._waldron import waldron from ._wissmann_becker import ( wissmann_becker_4_1, wissmann_becker_4_2, wissmann_becker_6_1, wissmann_becker_6_2, wissmann_becker_8_1, wissmann_becker_8_2, ) from ._witherden_vincent import ( witherden_vincent_01, witherden_vincent_03, witherden_vincent_05, witherden_vincent_07, witherden_vincent_09, witherden_vincent_11, witherden_vincent_13, witherden_vincent_15, witherden_vincent_17, witherden_vincent_19, witherden_vincent_21, ) __all__ = [ "albrecht_collatz_1", "albrecht_collatz_2", "albrecht_collatz_3", "albrecht_collatz_4", "burnside", "cohen_gismalla_1", "cohen_gismalla_2", "cools_haegemans_1985_1", "cools_haegemans_1985_2", "cools_haegemans_1985_3", "cools_haegemans_1988_1", "cools_haegemans_1988_2", "dunavant_00", "dunavant_01", "dunavant_02", "dunavant_03", "dunavant_04", "dunavant_05", "dunavant_06", "dunavant_07", "dunavant_08", "dunavant_09", "dunavant_10", "franke_1", "franke_2a", "franke_2b", "franke_3a", "franke_3b", "franke_3c", "franke_5", "franke_6", "franke_8", "hammer_stroud_1_2", "hammer_stroud_2_2", "hammer_stroud_3_2", "haegemans_piessens", "irwin_1", "irwin_2", "maxwell", "meister", "miller", "morrow_patterson_1", "morrow_patterson_2", "phillips", "piessens_haegemans_1", "piessens_haegemans_2", "rabinowitz_richter_1", "rabinowitz_richter_2", "rabinowitz_richter_3", "rabinowitz_richter_4", "rabinowitz_richter_5", "rabinowitz_richter_6", "schmid_2", "schmid_4", "schmid_6", "sommariva_01", "sommariva_02", "sommariva_03", "sommariva_04", "sommariva_05", "sommariva_06", "sommariva_07", "sommariva_08", "sommariva_09", "sommariva_10", "sommariva_11", "sommariva_12", "sommariva_13", "sommariva_14", "sommariva_15", "sommariva_16", "sommariva_17", "sommariva_18", "sommariva_19", "sommariva_20", "sommariva_21", "sommariva_22", "sommariva_23", "sommariva_24", "sommariva_25", "sommariva_26", "sommariva_27", "sommariva_28", "sommariva_29", "sommariva_30", "sommariva_31", "sommariva_32", "sommariva_33", "sommariva_34", "sommariva_35", "sommariva_36", "sommariva_37", "sommariva_38", "sommariva_39", "sommariva_40", "sommariva_41", "sommariva_42", "sommariva_43", "sommariva_44", "sommariva_45", "sommariva_46", "sommariva_47", "sommariva_48", "sommariva_49", "sommariva_50", "sommariva_51", "sommariva_52", "sommariva_53", "sommariva_54", "sommariva_55", "stroud_c2_1_1", "stroud_c2_1_2", "stroud_c2_3_1", "stroud_c2_3_2", "stroud_c2_3_3", "stroud_c2_3_4", "stroud_c2_3_5", "stroud_c2_5_1", "stroud_c2_5_2", "stroud_c2_5_3", "stroud_c2_5_4", "stroud_c2_5_5", "stroud_c2_5_6", "stroud_c2_5_7", "stroud_c2_7_1", "stroud_c2_7_2", "stroud_c2_7_3", "stroud_c2_7_4", "stroud_c2_7_5", "stroud_c2_7_6", "stroud_c2_9_1", "stroud_c2_11_1", "stroud_c2_11_2", "stroud_c2_13_1", "stroud_c2_15_1", "stroud_c2_15_2", "tyler_1", "tyler_2", "tyler_3", "waldron", "wissmann_becker_4_1", "wissmann_becker_4_2", "wissmann_becker_6_1", "wissmann_becker_6_2", "wissmann_becker_8_1", "wissmann_becker_8_2", "witherden_vincent_01", "witherden_vincent_03", "witherden_vincent_05", "witherden_vincent_07", "witherden_vincent_09", "witherden_vincent_11", "witherden_vincent_13", "witherden_vincent_15", "witherden_vincent_17", "witherden_vincent_19", "witherden_vincent_21", "product", # "transform", "rectangle_points", ]

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null

0

6

a2c07088af39cefb7cf0fa1759368002e597cf65

797

py

Python

trash/server/queue/main.py

josmejia2401/face_recognition_python

6155bfcb6e0dcb5cc3441ff3192ecf83fd1dcf1b

[ "MIT" ]

null

trash/server/queue/main.py

josmejia2401/face_recognition_python

6155bfcb6e0dcb5cc3441ff3192ecf83fd1dcf1b

[ "MIT" ]

null

trash/server/queue/main.py

josmejia2401/face_recognition_python

6155bfcb6e0dcb5cc3441ff3192ecf83fd1dcf1b

[ "MIT" ]

null

from multiprocessing.managers import BaseManager import queue queue = queue.Queue() class QueueManager(BaseManager): pass QueueManager.register('get_queue', callable=lambda:queue) m = QueueManager(address=('', 50000), authkey=b'abracadabra') s = m.get_server() s.serve_forever() #put from multiprocessing.managers import BaseManager class QueueManager(BaseManager): pass QueueManager.register('get_queue') m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra') m.connect() queue = m.get_queue() queue.put('hello') # get from multiprocessing.managers import BaseManager class QueueManager(BaseManager): pass QueueManager.register('get_queue') m = QueueManager(address=('foo.bar.org', 50000), authkey=b'abracadabra') m.connect() queue = m.get_queue() queue.get()

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797

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null

0

1

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6

a2d2b6c753772ad021e6eccc8b19f61d6d25d1ed

40

py

Python

brainframe_qt/ui/main_window/activities/identity_configuration/encoding_list/__init__.py

aotuai/brainframe-qt

082cfd0694e569122ff7c63e56dd0ec4b62d5bac

[ "BSD-3-Clause" ]

17

2021-02-11T18:19:22.000Z

2022-02-08T06:12:50.000Z

brainframe_qt/ui/main_window/activities/identity_configuration/encoding_list/__init__.py

aotuai/brainframe-qt

082cfd0694e569122ff7c63e56dd0ec4b62d5bac

[ "BSD-3-Clause" ]

80

2021-02-11T08:27:31.000Z

2021-10-13T21:33:22.000Z

brainframe_qt/ui/main_window/activities/identity_configuration/encoding_list/__init__.py

aotuai/brainframe-qt

082cfd0694e569122ff7c63e56dd0ec4b62d5bac

[ "BSD-3-Clause" ]

5

2021-02-12T09:51:34.000Z

2022-02-08T09:25:15.000Z

from .encoding_list import EncodingList

20

39

0.875

5

40

6.8

1

0

0.1

40

1

40

0.944444

0

1

0

true

0

1

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1

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null

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0

6

a75c625f0f2c3a2e3fe73fcf1c0dea8612223cb4

141

py

Python

src/simprocedure/UnConstraintRetValue.py

alikmli/HeapOverFlow-Detection

609082881af9788c4ef351754aecbb1e31eff475

[ "MIT" ]

null

src/simprocedure/UnConstraintRetValue.py

alikmli/HeapOverFlow-Detection

609082881af9788c4ef351754aecbb1e31eff475

[ "MIT" ]

null

src/simprocedure/UnConstraintRetValue.py

alikmli/HeapOverFlow-Detection

609082881af9788c4ef351754aecbb1e31eff475

[ "MIT" ]

null

import angr,claripy class ExeFunc(angr.SimProcedure): def run(*argv): pass #return claripy.BVS('UNConstrainRetValue',8)

20.142857

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0.673759

16

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5.9375

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141

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null

0

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0

1

0

6

a7bd6015290d947a1d8319b1cfe598a6b20a95cd

76

py

Python

src/ipynta/packaging/__init__.py

allanchua101/ipynta

861c36b1c2d675611fcd5ed478d658f8180d03af

[ "MIT" ]

null

src/ipynta/packaging/__init__.py

allanchua101/ipynta

861c36b1c2d675611fcd5ed478d658f8180d03af

[ "MIT" ]

null

src/ipynta/packaging/__init__.py

allanchua101/ipynta

861c36b1c2d675611fcd5ed478d658f8180d03af

[ "MIT" ]

null

from .tar_packager import TarPackager from .zip_packager import ZipPackager

25.333333

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null

0

1

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1

0

1

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6

a7cf0b21d2e981e8094886ebb46e37b5c00b54fb

12,394

py

Python

tests/unit/states/test_win_network.py

byteskeptical/salt

637fe0b04f38b2274191b005d73b3c6707d7f400

[ "Apache-2.0" ]

5

2018-05-01T20:51:14.000Z

2021-11-09T05:43:00.000Z

tests/unit/states/test_win_network.py

byteskeptical/salt

637fe0b04f38b2274191b005d73b3c6707d7f400

[ "Apache-2.0" ]

86

2017-01-27T11:54:46.000Z

2020-05-20T06:25:26.000Z

tests/unit/states/test_win_network.py

byteskeptical/salt

637fe0b04f38b2274191b005d73b3c6707d7f400

[ "Apache-2.0" ]

11

2017-01-26T19:36:29.000Z

2021-12-11T07:54:16.000Z

# -*- coding: utf-8 -*- ''' :codeauthor: Rahul Handay <rahulha@saltstack.com> ''' # Import Python Libs from __future__ import absolute_import, unicode_literals, print_function # Import Salt Testing Libs from tests.support.mixins import LoaderModuleMockMixin from tests.support.unit import TestCase, skipIf from tests.support.mock import ( MagicMock, patch, NO_MOCK, NO_MOCK_REASON ) # Import Salt Libs import salt.states.win_network as win_network @skipIf(NO_MOCK, NO_MOCK_REASON) class WinNetworkTestCase(TestCase, LoaderModuleMockMixin): ''' Validate the nftables state ''' def setup_loader_modules(self): return {win_network: {}} def test_managed_missing_parameters(self): ''' Test to ensure that the named interface is configured properly. ''' ret = {'name': 'salt', 'changes': {}, 'result': False, 'comment': 'dns_proto must be one of the following: static, dhcp\n' 'ip_proto must be one of the following: static, dhcp'} self.assertDictEqual(win_network.managed('salt'), ret) def test_managed_static_enabled_false(self): ret = {'name': 'salt', 'changes': {}, 'result': True, 'comment': 'Interface \'salt\' is up to date (already disabled)'} mock_false = MagicMock(return_value=False) with patch.dict(win_network.__salt__, {"ip.is_enabled": mock_false}): self.assertDictEqual( win_network.managed( 'salt', dns_proto='static', ip_proto='static', enabled=False), ret) def test_managed_test_true(self): ret = {'name': 'salt', 'changes': {}, 'result': False, 'comment': 'Failed to enable interface \'salt\' to make changes'} mock_false = MagicMock(return_value=False) with patch.dict(win_network.__salt__, {"ip.is_enabled": mock_false, "ip.enable": mock_false}), \ patch.dict(win_network.__opts__, {"test": False}): self.assertDictEqual( win_network.managed( 'salt', dns_proto='static', ip_proto='static'), ret) def test_managed_validate_errors(self): ret = {'name': 'salt', 'changes': {}, 'result': False, 'comment': 'The following SLS configuration errors were ' 'detected:\n' '- First Error\n' '- Second Error'} mock_true = MagicMock(return_value=True) mock_validate = MagicMock(return_value=['First Error', 'Second Error']) with patch.dict(win_network.__salt__, {"ip.is_enabled": mock_true}),\ patch.object(win_network, '_validate', mock_validate): self.assertDictEqual( win_network.managed( 'salt', dns_proto='static', ip_proto='static'), ret) def test_managed_get_current_config_failed(self): ret = {'name': 'salt', 'changes': {}, 'result': False, 'comment': 'Unable to get current configuration for interface ' '\'salt\''} mock_true = MagicMock(return_value=True) mock_false = MagicMock(return_value=False) mock_validate = MagicMock(return_value=[]) with patch.dict(win_network.__salt__, {'ip.is_enabled': mock_true, 'ip.get_interface': mock_false}), \ patch.object(win_network, '_validate', mock_validate): self.assertDictEqual( win_network.managed('salt', dns_proto='dhcp', ip_proto='dhcp'), ret) def test_managed_test_true_no_changes(self): ret = {'name': 'salt', 'changes': {}, 'result': True, 'comment': 'Interface \'salt\' is up to date'} mock_true = MagicMock(return_value=True) mock_validate = MagicMock(return_value=[]) mock_get_int = MagicMock(return_value={ 'DHCP enabled': 'yes', 'DNS servers configured through DHCP': '192.168.0.10'}) with patch.dict(win_network.__salt__, {'ip.is_enabled': mock_true, 'ip.get_interface': mock_get_int}), \ patch.dict(win_network.__opts__, {"test": True}), \ patch.object(win_network, '_validate', mock_validate): self.assertDictEqual( win_network.managed('salt', dns_proto='dhcp', ip_proto='dhcp'), ret) def test_managed_test_true_changes(self): ret = {'name': 'salt', 'changes': {}, 'result': None, 'comment': 'The following changes will be made to interface ' '\'salt\':\n' '- DNS protocol will be changed to: dhcp'} mock_true = MagicMock(return_value=True) mock_validate = MagicMock(return_value=[]) mock_get_int = MagicMock(return_value={ 'DHCP enabled': 'no', 'Statically Configured DNS Servers': '192.168.0.10'}) with patch.dict(win_network.__salt__, {'ip.is_enabled': mock_true, 'ip.get_interface': mock_get_int}), \ patch.dict(win_network.__opts__, {"test": True}), \ patch.object(win_network, '_validate', mock_validate): self.assertDictEqual( win_network.managed('salt', dns_proto='dhcp', ip_proto='dhcp'), ret) def test_managed_failed(self): ret = {'name': 'salt', 'changes': {}, 'result': False, 'comment': 'Failed to set desired configuration settings for ' 'interface \'salt\''} mock_true = MagicMock(return_value=True) mock_validate = MagicMock(return_value=[]) mock_get_int = MagicMock(return_value={ 'DHCP enabled': 'no', 'Statically Configured DNS Servers': '192.168.0.10'}) with patch.dict(win_network.__salt__, {'ip.is_enabled': mock_true, 'ip.get_interface': mock_get_int, 'ip.set_dhcp_dns': mock_true, 'ip.set_dhcp_ip': mock_true}), \ patch.dict(win_network.__opts__, {"test": False}), \ patch.object(win_network, '_validate', mock_validate): self.assertDictEqual( win_network.managed('salt', dns_proto='dhcp', ip_proto='dhcp'), ret) def test_managed(self): ret = {'name': 'salt', 'changes': { 'DHCP enabled': { 'new': 'yes', 'old': 'no'}, 'DNS servers configured through DHCP': { 'new': '192.168.0.10', 'old': ''}, 'Statically Configured DNS Servers': { 'new': '', 'old': '192.168.0.10' } }, 'result': True, 'comment': 'Successfully updated configuration for interface ' '\'salt\''} mock_true = MagicMock(return_value=True) mock_validate = MagicMock(return_value=[]) mock_get_int = MagicMock(side_effect=[ {'DHCP enabled': 'no', 'Statically Configured DNS Servers': '192.168.0.10'}, {'DHCP enabled': 'yes', 'DNS servers configured through DHCP': '192.168.0.10'}, ]) with patch.dict(win_network.__salt__, {'ip.is_enabled': mock_true, 'ip.get_interface': mock_get_int, 'ip.set_dhcp_dns': mock_true, 'ip.set_dhcp_ip': mock_true}), \ patch.dict(win_network.__opts__, {"test": False}), \ patch.object(win_network, '_validate', mock_validate): self.assertDictEqual( win_network.managed('salt', dns_proto='dhcp', ip_proto='dhcp'), ret) def test_managed_static_dns_clear(self): expected = {'name': 'salt', 'changes': { 'Statically Configured DNS Servers': { 'new': 'None', 'old': '192.168.0.10' } }, 'result': True, 'comment': 'Successfully updated configuration for ' 'interface \'salt\''} mock_true = MagicMock(return_value=True) mock_validate = MagicMock(return_value=[]) mock_get_int = MagicMock(side_effect=[ {'DHCP enabled': 'no', 'Statically Configured DNS Servers': '192.168.0.10'}, {'DHCP enabled': 'no', 'Statically Configured DNS Servers': 'None'}, ]) with patch.dict(win_network.__salt__, {'ip.is_enabled': mock_true, 'ip.get_interface': mock_get_int, 'ip.set_static_dns': mock_true}), \ patch.dict(win_network.__opts__, {"test": False}), \ patch.object(win_network, '_validate', mock_validate): ret = win_network.managed( 'salt', dns_proto='static', dns_servers=[], ip_proto='dhcp') self.assertDictEqual(ret, expected) def test_managed_static_dns(self): expected = {'name': 'salt', 'changes': { 'Statically Configured DNS Servers': { 'new': '192.168.0.10', 'old': 'None' } }, 'result': True, 'comment': 'Successfully updated configuration for ' 'interface \'salt\''} mock_true = MagicMock(return_value=True) mock_validate = MagicMock(return_value=[]) mock_get_int = MagicMock(side_effect=[ {'DHCP enabled': 'no', 'Statically Configured DNS Servers': 'None'}, {'DHCP enabled': 'no', 'Statically Configured DNS Servers': '192.168.0.10'}, ]) with patch.dict(win_network.__salt__, {'ip.is_enabled': mock_true, 'ip.get_interface': mock_get_int, 'ip.set_static_dns': mock_true}), \ patch.dict(win_network.__opts__, {"test": False}), \ patch.object(win_network, '_validate', mock_validate): ret = win_network.managed( 'salt', dns_proto='static', dns_servers=['192.168.0.10'], ip_proto='dhcp') self.assertDictEqual(ret, expected) def test_managed_static_dns_no_action(self): expected = {'name': 'salt', 'changes': {}, 'result': True, 'comment': 'Interface \'salt\' is up to date'} mock_true = MagicMock(return_value=True) mock_validate = MagicMock(return_value=[]) mock_get_int = MagicMock(return_value={ 'DHCP enabled': 'no', 'Statically Configured DNS Servers': '192.168.0.10' }) with patch.dict(win_network.__salt__, {'ip.is_enabled': mock_true, 'ip.get_interface': mock_get_int, 'ip.set_static_dns': mock_true}), \ patch.dict(win_network.__opts__, {"test": False}), \ patch.object(win_network, '_validate', mock_validate): # Don't pass dns_servers ret = win_network.managed('salt', dns_proto='static', ip_proto='dhcp') self.assertDictEqual(ret, expected) # Pass dns_servers=None ret = win_network.managed( 'salt', dns_proto='static', dns_servers=None, ip_proto='dhcp') self.assertDictEqual(ret, expected)

45.903704

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0

0.689362

0

0.210278

0

0.055319

1

0.055319

false

0

0.021277

0.004255

0.085106

0.004255

0

null

0

1

0

null

0

6

ac7037a0268860ccf3d9124c95e8246d6841d2d0

129

py

Python

my_script.py

antauren/test_pip

593d64bddc479ce7c29d0dbabc89db2cabc7975c

[ "MIT" ]

null

my_script.py

antauren/test_pip

593d64bddc479ce7c29d0dbabc89db2cabc7975c

[ "MIT" ]

null

my_script.py

antauren/test_pip

593d64bddc479ce7c29d0dbabc89db2cabc7975c

[ "MIT" ]

null

import utils2.math as math import utils2.strings.str_utils as str_utils print(math.add(10, 20)) print(str_utils.reverse("ABC"))

21.5

44

0.782946

23

129

4.26087

0.565217

0.244898

0

0.051282

0.093023

129

5

45

25.8

0.786325

0

0.023256

0

1

0

true

0

0.5

0

0.5

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

3bb5a9ab6a42ef01d97c72735ae4c897c39f3056

221

py

Python

exercises/level_0/list_min_max.py

eliranM98/python_course

d9431dd6c0f27fca8ca052cc2a821ed0b883136c

[ "MIT" ]

6

2019-03-29T06:14:53.000Z

2021-10-15T23:42:36.000Z

exercises/level_0/list_min_max.py

eliranM98/python_course

d9431dd6c0f27fca8ca052cc2a821ed0b883136c

[ "MIT" ]

4

2019-09-06T10:03:40.000Z

2022-03-11T23:30:55.000Z

exercises/level_0/list_min_max.py

eliranM98/python_course

d9431dd6c0f27fca8ca052cc2a821ed0b883136c

[ "MIT" ]

12

2019-06-20T19:34:52.000Z

2021-10-15T23:42:39.000Z

list1, list2 = [123, 567, 343, 611], [456, 700, 200] print("Max value element : ", max(list1)) print("Max value element : ", max(list2)) print("min value element : ", min(list1)) print("min value element : ", min(list2))

36.833333

52

0.647059

33

221

4.333333

0.424242

0.335664

0.181818

0.27972

0.643357

0

0.144385

0.153846

221

5

53

44.2

0.620321

0

0.361991

0

1

0

true

0

0.8

0

null

1

0

1

0

null

0

1

0

1

0

6

3bd4a5db1b22eab7389c8b3efdd005c7f0a915fb

187

py

Python

barbearia/agendamento/__init__.py

FabioMarquesArao/OPE_BARBEARIA

867e7d4b67d9d70b6056b2d817cd3d2561ca7131

[ "MIT" ]

null

barbearia/agendamento/__init__.py

FabioMarquesArao/OPE_BARBEARIA

867e7d4b67d9d70b6056b2d817cd3d2561ca7131

[ "MIT" ]

null

barbearia/agendamento/__init__.py

FabioMarquesArao/OPE_BARBEARIA

867e7d4b67d9d70b6056b2d817cd3d2561ca7131

[ "MIT" ]

null

from flask import Blueprint agendamento_bp = Blueprint("agendamento", __name__, static_folder="agendamento_static", template_folder="templates") from barbearia.agendamento import routes

37.4

116

0.839572

21

187

7.095238

0.619048

0.268456

0

0.080214

187

5

117

37.4

0.866279

0

0.202128

0

1

0

false

0

0.666667

0

0.666667

1

0

null

1

0

1

0

null

0

1

0

1

0

6

0233a17a70529d16664c718ccbbf7b91a46eb37a

31

py

Python

src/try.py

alelallele/learn_python_st

55b06efdf63135f3fff2c93508d25c5f4ae0db7e

[ "Apache-2.0" ]

null

src/try.py

alelallele/learn_python_st

55b06efdf63135f3fff2c93508d25c5f4ae0db7e

[ "Apache-2.0" ]

null

src/try.py

alelallele/learn_python_st

55b06efdf63135f3fff2c93508d25c5f4ae0db7e

[ "Apache-2.0" ]

null

print("Assalamualaikum Dunia")

15.5

30

0.806452

3

31

8.333333

1

0

0.064516

31

1

31

0.862069

0

0.677419

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

023cdccb156d5fe6eae8793ecbcb561d8a091508

75

py

Python

amocrm_asterisk_ng/telephony/impl/redirect_to_responsible/__init__.py

iqtek/amocrn_asterisk_ng

429a8d0823b951c855a49c1d44ab0e05263c54dc

[ "MIT" ]

null

amocrm_asterisk_ng/telephony/impl/redirect_to_responsible/__init__.py

iqtek/amocrn_asterisk_ng

429a8d0823b951c855a49c1d44ab0e05263c54dc

[ "MIT" ]

null

amocrm_asterisk_ng/telephony/impl/redirect_to_responsible/__init__.py

iqtek/amocrn_asterisk_ng

429a8d0823b951c855a49c1d44ab0e05263c54dc

[ "MIT" ]

null

from .RedirectToResponsibleComponent import RedirectToResponsibleComponent

37.5

74

0.933333

4

75

17.5

0.75

0

0.053333

75

1

75

0.985915

0

1

0

true

0

1

0

1

0

1

0

1

null

0

1

0

null

0

1

0

1

0

1

0

6

5a1d28b26acb95a59f3028a6c346dab08548f699

898

py

Python

src/python/pants/backend/codegen/protobuf/java/register.py

stuhood/pants

107b8335a03482516f64aefa98aadf9f5278b2ee

[ "Apache-2.0" ]

null

src/python/pants/backend/codegen/protobuf/java/register.py

stuhood/pants

107b8335a03482516f64aefa98aadf9f5278b2ee

[ "Apache-2.0" ]

null

src/python/pants/backend/codegen/protobuf/java/register.py

stuhood/pants

107b8335a03482516f64aefa98aadf9f5278b2ee

[ "Apache-2.0" ]

null

# Copyright 2016 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). """Generate Java targets from Protocol Buffers (Protobufs). See https://developers.google.com/protocol-buffers/. """ from pants.backend.codegen.protobuf.java.java_protobuf_library import ( JavaProtobufLibrary as JavaProtobufLibraryV1, ) from pants.backend.codegen.protobuf.java.protobuf_gen import ProtobufGen from pants.backend.codegen.protobuf.java.targets import JavaProtobufLibrary from pants.build_graph.build_file_aliases import BuildFileAliases from pants.goal.task_registrar import TaskRegistrar as task def build_file_aliases(): return BuildFileAliases(targets={"java_protobuf_library": JavaProtobufLibraryV1}) def register_goals(): task(name="protoc", action=ProtobufGen).install("gen") def targets2(): return [JavaProtobufLibrary]

32.071429

85

0.806236

107

898

6.654206

0.504673

0.063202

0.067416

0.09691

0.147472

0

0.011166

0.10245

898

27

86

33.259259

0.872208

0.265033

0

1

0

0.046012

0.032209

0

1

0.230769

true

0

0.384615

0.153846

0.769231

0

null

0

1

0

null

0

1

0

1

0

6

5a24642f5b7f32770c30b4c5d77704c6677f3f49

242

py

Python

app/codemirror/__init__.py

sappachok/django-anaconda

1ffd33ded759f622b6db23a3550a898b62350403

[ "MIT" ]

39

2015-03-22T21:57:28.000Z

2021-11-04T08:17:15.000Z

app/codemirror/__init__.py

sappachok/django-anaconda

1ffd33ded759f622b6db23a3550a898b62350403

[ "MIT" ]

67

2019-09-27T17:04:52.000Z

2022-03-21T22:16:23.000Z

app/codemirror/__init__.py

sappachok/django-datasci

1ffd33ded759f622b6db23a3550a898b62350403

[ "MIT" ]

17

2015-09-08T15:52:15.000Z

2020-02-28T03:20:02.000Z

# -*- coding: utf-8 -*- u""" Library for using `CodeMirror` in Django. """ from codemirror.fields import CodeMirrorField, CodeMirrorFormField from codemirror.utils import CodeMirrorJavascript from codemirror.widgets import CodeMirrorTextarea

30.25

66

0.801653

26

242

7.461538

0.730769

0.216495

0

0.00463

0.107438

242

7

67

34.571429

0.893519

0.264463

0

1

0

true

0

0.75

0

0.75

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

ce9f2ba1d839fbcf833b655e68da46871ddbf896

3,389

py

Python

tests/functional/test_config.py

koneksys/aras-oslc

92adb87b884014df5b82a1c5402592aabc916bc0

[ "MIT" ]

3

2021-03-19T22:25:51.000Z

2021-03-20T19:34:28.000Z

tests/functional/test_config.py

koneksys/aras-oslc

92adb87b884014df5b82a1c5402592aabc916bc0

[ "MIT" ]

null

tests/functional/test_config.py

koneksys/aras-oslc

92adb87b884014df5b82a1c5402592aabc916bc0

[ "MIT" ]

null

import logging from oslc_api.auth import login from oslc_api.auth.models import User log = logging.getLogger(__name__) def test_components(oslc_api, source_base_uri, access_token, item_values, mocker, load_item_types_test, load_items_test): @login.request_loader def load_user_from_request(request): return User(username='admin', access_token=access_token) item_type = item_values[0] config_id = item_values[1] if 'localhost' in source_base_uri: mocker.patch( 'oslc_api.aras.resources.load_item_types', return_value=load_item_types_test ) mocker.patch( 'oslc_api.aras.resources.load_items', return_value=load_items_test ) res = oslc_api.get_components(item_type) assert res is not None assert res.status_code == 200, 'The request was not successful' assert config_id.encode('ascii') in res.data, 'The response does not contain the config id' def test_component(oslc_api, source_base_uri, access_token, item_values, mocker, load_item_types_test, load_items_test, load_validate_configs_test): @login.request_loader def load_user_from_request(request): return User(username='admin', access_token=access_token) item_type = item_values[0] config_id = item_values[1] if 'localhost' in source_base_uri: mocker.patch( 'oslc_api.aras.resources.load_item_types', return_value=load_item_types_test ) mocker.patch( 'oslc_api.aras.resources.load_items', return_value=load_items_test ) mocker.patch( 'oslc_api.aras.resources.validate_config_id', return_value=load_validate_configs_test ) res = oslc_api.get_component(item_type, config_id) assert res is not None assert res.status_code == 200, 'The request was not successful' assert config_id.encode('ascii') in res.data, 'The response does not contain the config id' assert b'oslc_config:configurations' in res.data def test_configurations(oslc_api, source_base_uri, access_token, item_values, mocker, load_item_types_test, load_items_test, load_validate_configs_test, load_resource_shape_test): @login.request_loader def load_user_from_request(request): return User(username='admin', access_token=access_token) item_type = item_values[0] config_id = item_values[1] if 'localhost' in source_base_uri: mocker.patch( 'oslc_api.aras.resources.load_item_types', return_value=load_item_types_test ) mocker.patch( 'oslc_api.aras.resources.load_items', return_value=load_items_test ) mocker.patch( 'oslc_api.aras.resources.validate_config_id', return_value=load_resource_shape_test ) mocker.patch( 'oslc_api.aras.resources.load_streams', return_value=load_validate_configs_test ) res = oslc_api.get_configurations(item_type, config_id) assert res is not None assert res.status_code == 200, 'The request was not successful' assert config_id.encode('ascii') in res.data, 'The response does not contain the config id' assert b'rdfs:member' in res.data

32.902913

98

0.678961

451

3,389

4.751663

0.157428

0.05553

0.054596

0.075595

0.870742

0.864676

0.846477

0

0.005864

0.245205

3,389

102

99

33.22549

0.8319

0

0.658228

0

0.192387

0.107701

0

0.139241

1

0.075949

false

0

0.037975

0.151899

0

null

0

1

0

null

0

6

ceaacb2b94e8999fac50a224bbdd3dea062d7950

177

py

Python

app/main/error.py

IsaiahKe/Personal-Blog

5ec76513bb8710ba3c92c515fddf00f0b3dc8975

[ "MIT" ]

null

app/main/error.py

IsaiahKe/Personal-Blog

5ec76513bb8710ba3c92c515fddf00f0b3dc8975

[ "MIT" ]

null

app/main/error.py

IsaiahKe/Personal-Blog

5ec76513bb8710ba3c92c515fddf00f0b3dc8975

[ "MIT" ]

null

from flask import render_template from . import main @main.errorhandler(404) def notfound(): ''' error function ''' return render_template('notfound.html'),404

17.7

47

0.694915

21

177

5.761905

0.666667

0.231405

0

0.041958

0.19209

177

9

48

19.666667

0.804196

0.079096

0

0.088435

0

1

0.2

true

0

0.4

0

0.8

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

ceb1c880c1797da773391c2d5e7e2c5fe9d4761c

9,567

py

Python

idl2py/wcs/xyad.py

RapidLzj/idl2py

193051cd8d01db0d125b8975713b885ad521a992

[ "MIT" ]

null

idl2py/wcs/xyad.py

RapidLzj/idl2py

193051cd8d01db0d125b8975713b885ad521a992

[ "MIT" ]

null

idl2py/wcs/xyad.py

RapidLzj/idl2py

193051cd8d01db0d125b8975713b885ad521a992

[ "MIT" ]

null

""" By Dr Jie Zheng -Q, NAOC v1 2019-04-27 """ import numpy as np from..util import * def xyad(): pass #pro xyad, hdr, x, y, a, d, PRINT = print, GALACTIC = galactic, ALT = alt, $ # CELESTIAL = celestial, ECLIPTIC = ecliptic, PRECISION = precision #;+ #; NAME: #; XYAD #; PURPOSE: #; Use a FITS header to convert pixel (X,Y) to world coordinates #; EXPLANATION: #; Use astrometry in a FITS image header to compute world #; coordinates in decimal degrees from X and Y. #; #; If spherical coordinates (Calabretta & Greisen 2002, A&A, 395, 1077) are #; not present, then XYAD will still perform the transformation specified #; by the CD, CRVAL, and CRPIX keywords. #; CALLING SEQUENCE: #; XYAD, HDR ;Prompt for X and Y positions #; XYAD, HDR, X, Y, A, D, [ /PRINT, /Galactic, /Celestial, /Ecliptic, #; ALT =, PRECISION=] #; INPUTS: #; HDR - FITS Image header containing astrometry info #; #; OPTIONAL INPUTS: #; X - row position in pixels, scalar or vector #; Y - column position in pixels, scalar or vector #; #; X and Y should be in IDL convention, (first pixel is (0,0) where #; the integral value corresponds to the center of the pixel.) #; #; OPTIONAL OUTPUT: #; A - Output longitude in decimal DEGREES (for spherical coordinates), #; same number of elements as X and Y. For celestial #; coordinates, this is the Right ascension. #; D - Output latitude in decimal DEGREES. For celestial coordinates, #; this is the declination. #; OPTIONAL KEYWORD INPUT: #; ALT - single character 'A' through 'Z' or ' ' specifying an alternate #; astrometry system present in the FITS header. The default is #; to use the primary astrometry or ALT = ' '. If /ALT is set, #; then this is equivalent to ALT = 'A'. See Section 3.3 of #; Greisen & Calabretta (2002, A&A, 395, 1061) for information about #; alternate astrometry keywords. #; PRECISION - Integer scalar (0-4) specifying the number of digits #; displayed after the decimal of declination. The RA is #; automatically one digit more. See ADSTRING() for more info. #; Default value is 1, and the keyword is ignored if results are not #; displayed at the terminal #; /PRINT - If this keyword is set and non-zero, then results are displayed #; at the terminal.in both decimal and sexagesimal notation. #; #; The default for XYAD is to return the coordinate system present in #; in the FITS header. However, the following mutually exclusive #; keywords can be used to convert to a particular coordinate system: #; #; /CELESTIAL - Output is Right Ascension and declination #; /ECLIPTIC - Output is Ecliptic longitude and latitude #; /GALACTIC - Output is Galactic longitude and latitude #; Celestial & Ecliptic coords depend on the reference #; equinox, set to either B1950 (=FK4) or J2000 (=FK5,ICRS) #; according to the header or standard FITS WCS defaults. #; Note that astrometry at the sub-arcsec level requires #; fine distinctions that are not handled here. #; #; OPERATIONAL NOTES: #; If less than 5 parameters are supplied, or if the /PRINT keyword is #; set, then the computed astronomical coordinates are displayed at the #; terminal. #; #; If this procedure is to be used repeatedly with the same header, #; then it would be faster to use XY2AD. #; #; EXAMPLE: #; A FITS header, hdr, contains astrometric information in celestial #; coordinates. Find the RA and Dec corresponding to position X=23.3 #; Y = 100.2 on an image #; IDL> xyad, hdr, 23.3, 100.2 ;Displays results at the terminal #; To display the results in Galactic coordinates #; IDL> xyad, hdr, 23.3, 100.2, /GALACTIC #; #; PROCEDURES CALLED #; ADSTRING(), EULER, EXTAST, GET_EQUINOX(), GSSSXYAD, REPCHR(), XY2AD #; #; REVISION HISTORY: #; W. Landsman STX Jan, 1988 #; Use astrometry structure W. Landsman Jan, 1994 #; Recognize GSSS header W. Landsman June, 1994 #; Changed ADSTRING output format W. Landsman September 1995 #; Use vector call to ADSTRING() W. Landsman February 2000 #; Added ALT input keyword W. Landsman June 2003 #; Add precision keyword W. Landsman February 2004 #; Fix display if 'RA','DEC' reversed in CTYPE W. Landsman Feb. 2004 #; Handle display of NaN values W. Landsman May 2004 #; Work for non-spherical coordinate transformations W. Landsman Oct 2004 #; Fix output display units if ALT keyword used W. Landsman March 2005 #; More informative error message if no astrometry present W.L Nov 2007 #; Fix display when no equinox in header W.L. Dec 2007 #; Fix header display for noncelestial coords W.L. Jan 2008 #; Check for non-standard projections, set FK4 flag. J. P. Leahy Jul 2013 #;- # compile_opt idl2 # On_error,2 # # npar = N_params() # if ( npar EQ 0 ) then begin # print,'Syntax - XYAD, hdr, [x, y, a, d, /PRINT, Alt=, Precision=, ' # print,' /Galactic, /Celestial, /Ecliptic ]' # print,'HDR - FITS header (string array) containing astrometry' # print,'X,Y - Input X and Y positions (scalar or vector)' # print,'A,D - Output RA and Dec in decimal degrees' # return # endif # # extast, hdr, astr, noparams, ALT = alt ;Extract astrometry structure # # if ( noparams LT 0 ) then begin # if alt EQ '' then $ # message,'ERROR - No astrometry info in supplied FITS header' $ # else message, $ # 'ERROR - No alt=' + alt + ' astrometry info in supplied FITS header' # endif # # astr2 = TAG_EXIST(astr,'AXES') # # if ( npar lt 3 ) then read,'XYAD: Enter X and Y positions: ',x,y # # case strmid(astr.ctype[0],5,3) of # 'GSS': gsssxyad, astr, x, y, a, d # else: xy2ad, x, y, astr, a, d # endcase # titname = strmid(astr.ctype,0,4) # if (titname[0] EQ 'DEC-') || (titname[0] EQ 'ELAT') or $ # (titname[0] EQ 'GLAT') then titname = rotate(titname,2) # # eqnx = Get_Equinox(hdr,code) # IF astr2 THEN FK4 = STRMID(astr.RADECSYS,0,3) EQ 'FK4' ELSE $ # FK4 = eqnx EQ 1950 # # if keyword_set(GALACTIC) then begin # case titname[0] of # 'RA--': euler, a,d, select=1, FK4=fk4 # 'ELON': euler, a,d, select=5, FK4=fk4 # 'GLON': # else: MESSAGE, "doesn't know how to convert from "+titname # endcase # titname = ['GLON','GLAT'] # endif else if keyword_set(ECLIPTIC) then begin # case titname[0] of # 'RA--': euler, a, d, select=3, FK4=fk4 # 'ELON': # 'GLON': euler, a,d, select=6, FK4=fk4 # else: MESSAGE, "doesn't know how to convert from "+titname # endcase # titname = ['ELON','ELAT'] # endif else if keyword_set(CELESTIAL) then begin # case titname[0] of # 'RA--': # 'ELON': euler, a, d, select=4, FK4 = FK4 # 'GLON': euler, a,d, select=2, FK4 = FK4 # else: MESSAGE, "doesn't know how to convert from "+titname # endcase # titname = ['RA--','DEC-'] # endif # # if (npar lt 5) or keyword_set(PRINT) then begin # g = where( finite(d) and finite(a), Ng) # tit1= titname[0] # t1 = strpos(tit1,'-') # if t1 gt 0 then tit1 = strmid(tit1,0,t1) # tit2= titname[1] # t1 = strpos(tit2,'-') # if t1 gt 0 then tit2 = strmid(tit2,0,t1) # npts = N_elements(X) # spherical = strmid(astr.ctype[0],4,1) EQ '-' # fmt = '(2F8.2,2x,2F9.4,2x,A)' # if spherical then begin # # tit = ' X Y ' + tit1 + ' ' + tit2 # sexig = strmid(titname[0],0,4) EQ 'RA--' # if sexig then begin # # eqnx = code NE -1 ? '_' + string(eqnx,f='(I4)') : ' ' # tit += $ # ' ' + tit1 + eqnx + ' ' + tit2 + eqnx # if N_elements(precision) EQ 0 then precision = 1 # str = replicate(' --- --- ', Npts) # if Ng GT 0 then str[g] = adstring(a[g],d[g],precision) # endif else str = replicate('', npts) # print,tit # for i=0l, npts-1 do $ # print,FORMAT=fmt, float(x[i]), float(y[i]), a[i], d[i], str[i] # # endif else begin # unit1 = strtrim( sxpar( hdr, 'CUNIT1'+alt,count = N_unit1),2) # if N_unit1 EQ 0 then unit1 = '' # unit2 = strtrim( sxpar( hdr, 'CUNIT2'+alt,count = N_unit2),2) # if N_unit2 EQ 0 then unit2 = '' # print,' X Y ' + titname[0] + ' ' + titname[1] # if (N_unit1 GT 0) || (N_unit2 GT 0) then $ # print,unit1 ,unit2,f='(t23,a,t33,a)' # for i=0l, npts-1 do $ # print,FORMAT=fmt, float(x[i]), float(y[i]), a[i], d[i] # endelse # endif # # return # end

43.486364

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1,247

9,567

4.281476

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0.004495

0.005619

0.014609

0.16239

0.121933

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Python

py_client/aidm/__init__.py

sma-software/openviriato.algorithm-platform.py-client

73d4cf89aa6f4d02ab15b5504d92107848742325

[ "Apache-2.0" ]

2

2021-06-21T06:50:29.000Z

2021-06-30T15:58:02.000Z

py_client/aidm/__init__.py

sma-software/openviriato.algorithm-platform.py-client

73d4cf89aa6f4d02ab15b5504d92107848742325

[ "Apache-2.0" ]

null

py_client/aidm/__init__.py

sma-software/openviriato.algorithm-platform.py-client

73d4cf89aa6f4d02ab15b5504d92107848742325

[ "Apache-2.0" ]

null

from py_client.aidm.aidm_algorithm_classes import * from py_client.aidm.aidm_enum_classes import * from py_client.aidm.aidm_floating_point import * from py_client.aidm.aidm_link_classes import * from py_client.aidm.aidm_routing_edge_classes import * from py_client.aidm.aidm_routing_point_classes import * from py_client.aidm.aidm_table_cell_classes import * from py_client.aidm.aidm_table_classes import * from py_client.aidm.aidm_time_window_classes import * from py_client.aidm.aidm_track_closure_classes import * from py_client.aidm.aidm_train_classification_classes import * from py_client.aidm.aidm_train_path_node_classes import * from py_client.aidm.aidm_update_classes import * from py_client.aidm.aidm_termination_request import TerminationRequest, SignalType

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0cc2ef44ee606f3da56e31f6712a9da0b3ce9b60

5,712

py

Python

tests/test_engine/test_queries/test_queryop_comparsion_nin.py

jqueguiner/montydb

55bb3099fe110dbcd1ee24a71479fb0861d993a4

[ "BSD-3-Clause" ]

null

tests/test_engine/test_queries/test_queryop_comparsion_nin.py

jqueguiner/montydb

55bb3099fe110dbcd1ee24a71479fb0861d993a4

[ "BSD-3-Clause" ]

null

tests/test_engine/test_queries/test_queryop_comparsion_nin.py

jqueguiner/montydb

55bb3099fe110dbcd1ee24a71479fb0861d993a4

[ "BSD-3-Clause" ]

null

import pytest import re from montydb.errors import OperationFailure from montydb.types import bson_ as bson from ...conftest import skip_if_no_bson def count_documents(cursor, spec=None): return cursor.collection.count_documents(spec or {}) def test_qop_nin_1(monty_find, mongo_find): docs = [ {"a": 0}, {"a": 1} ] spec = {"a": {"$nin": [0]}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert count_documents(mongo_c, spec) == 1 assert count_documents(monty_c, spec) == count_documents(mongo_c, spec) assert next(mongo_c) == next(monty_c) def test_qop_nin_2(monty_find, mongo_find): docs = [ {"a": [1, 0]}, {"a": [1, 2]}, {"a": 3}, ] spec = {"a": {"$nin": [0, 2]}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert count_documents(mongo_c, spec) == 1 assert count_documents(monty_c, spec) == count_documents(mongo_c, spec) assert next(mongo_c) == next(monty_c) mongo_c.rewind() assert next(mongo_c)["_id"] == 2 def test_qop_nin_3(monty_find, mongo_find): docs = [ {"a": {"1": 5}}, {"a": [1, 2]}, {"a": 0}, ] spec = {"a.1": {"$nin": [5, 2]}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert count_documents(mongo_c, spec) == 1 assert count_documents(monty_c, spec) == count_documents(mongo_c, spec) assert next(mongo_c) == next(monty_c) mongo_c.rewind() assert next(mongo_c)["_id"] == 2 def test_qop_nin_4(monty_find, mongo_find): docs = [ {"a": {"b": 5}}, {"a": {"b": [2]}}, {"a": {"c": [2, 5]}}, ] spec = {"a.b": {"$nin": [5, 2]}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert count_documents(mongo_c, spec) == 1 assert count_documents(monty_c, spec) == count_documents(mongo_c, spec) assert next(mongo_c) == next(monty_c) mongo_c.rewind() assert next(mongo_c)["_id"] == 2 def test_qop_nin_5(monty_find, mongo_find): docs = [ {"a": {"b": [[0]]}}, {"a": {"b": [2]}}, {"a": {"b": 2}}, ] spec = {"a.b": {"$nin": [[2], [0]]}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert count_documents(mongo_c, spec) == 1 assert count_documents(monty_c, spec) == count_documents(mongo_c, spec) assert next(mongo_c) == next(monty_c) mongo_c.rewind() assert next(mongo_c)["_id"] == 2 def test_qop_nin_6(monty_find, mongo_find): docs = [ {"a": [{"b": 1}, {"b": 2}]}, {"a": [{"b": 3}, {"b": 4}]}, {"x": 5}, ] spec = {"a.b": {"$nin": [2]}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert count_documents(mongo_c, spec) == 2 assert count_documents(monty_c, spec) == count_documents(mongo_c, spec) for i in range(2): assert next(mongo_c) == next(monty_c) def test_qop_nin_7(monty_find, mongo_find): docs = [ {"a": [{"b": 1}, {"b": 2}]} ] spec = {"a.b": {"$nin": [True]}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert count_documents(mongo_c, spec) == 1 assert count_documents(monty_c, spec) == count_documents(mongo_c, spec) def test_qop_nin_8(monty_find, mongo_find): docs = [ {"a": [{"b": 1}]}, {"a": [{"x": 1}]}, ] spec = {"a.b": {"$nin": [None]}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert count_documents(mongo_c, spec) == 1 assert count_documents(monty_c, spec) == count_documents(mongo_c, spec) assert next(mongo_c) == next(monty_c) mongo_c.rewind() assert next(mongo_c)["_id"] == 0 @skip_if_no_bson def test_qop_nin_9(monty_find, mongo_find): docs = [ {"a": "banana"}, ] spec = {"a": {"$nin": [bson.Regex("^a")]}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert count_documents(mongo_c, spec) == 1 assert count_documents(monty_c, spec) == count_documents(mongo_c, spec) assert next(mongo_c) == next(monty_c) @skip_if_no_bson def test_qop_nin_10(monty_find, mongo_find): docs = [ {"a": [bson.Regex("*")]}, ] spec = {"a": {"$nin": [[bson.Regex("*")]]}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert count_documents(mongo_c, spec) == 0 assert count_documents(monty_c, spec) == count_documents(mongo_c, spec) def test_qop_nin_11(monty_find, mongo_find): docs = [ {"a": "banana"}, ] spec = {"a": {"$nin": [re.compile("^a")]}} monty_c = monty_find(docs, spec) mongo_c = mongo_find(docs, spec) assert count_documents(mongo_c, spec) == 1 assert count_documents(monty_c, spec) == count_documents(mongo_c, spec) assert next(mongo_c) == next(monty_c) @skip_if_no_bson def test_qop_nin_12(monty_find, mongo_find): docs = [ {"a": "apple"}, ] spec = {"a": {"$nin": [bson.Regex("*")]}} monty_c = monty_find(docs, spec) # Regular expression is invalid with pytest.raises(OperationFailure): next(monty_c) def test_qop_nin_13(monty_find, mongo_find): docs = [ {"a": 5}, ] spec = {"a": {"$nin": 5}} monty_c = monty_find(docs, spec) # $nin needs an array with pytest.raises(OperationFailure): next(monty_c) def test_qop_nin_14(monty_find, mongo_find): docs = [ {"a": 5}, ] spec = {"a": {"$nin": [5, {"$exists": 1}]}} monty_c = monty_find(docs, spec) # cannot nest $ under $nin with pytest.raises(OperationFailure): next(monty_c)

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0cca5d410b4e9598e7d598f136cddba5ed364266

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py

Python

pyBSE/pybse/__init__.py

GSavathrakis/dart_board

9430d97675d69e381b701499587a02fd71b02990

[ "MIT" ]

8

2017-12-04T22:32:25.000Z

2021-10-01T11:45:09.000Z

pyBSE/pybse/__init__.py

GSavathrakis/dart_board

9430d97675d69e381b701499587a02fd71b02990

[ "MIT" ]

2

2018-03-14T00:10:43.000Z

2021-05-02T18:51:11.000Z

pyBSE/pybse/__init__.py

GSavathrakis/dart_board

9430d97675d69e381b701499587a02fd71b02990

[ "MIT" ]

2

2018-07-17T23:00:01.000Z

2021-08-25T15:46:38.000Z

from .bse_wrapper import *

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py

Python

tests/clazz/packageA/packageB/module_b1.py

hiroki0525/autoload_module

f3e10dc02d0fd24b8caa872f8c71f8902dc44f83

[ "MIT" ]

10

2020-08-28T13:08:06.000Z

2021-12-21T12:03:05.000Z

tests/clazz/packageA/packageB/module_b1.py

hiroki0525/autoload_module

f3e10dc02d0fd24b8caa872f8c71f8902dc44f83

[ "MIT" ]

null

tests/clazz/packageA/packageB/module_b1.py

hiroki0525/autoload_module

f3e10dc02d0fd24b8caa872f8c71f8902dc44f83

[ "MIT" ]

null

from autoload import load_config from tests.clazz.testmodule import TestModule @load_config() class CustomModuleB1(TestModule): pass

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py

Python

src/asttrs/__init__.py

ryanchao2012/asttrs

b5e30ae6094f6b9d0504ca6b9c9a887df05a91c1

[ "MIT" ]

null

src/asttrs/__init__.py

ryanchao2012/asttrs

b5e30ae6094f6b9d0504ca6b9c9a887df05a91c1

[ "MIT" ]

null

src/asttrs/__init__.py

ryanchao2012/asttrs

b5e30ae6094f6b9d0504ca6b9c9a887df05a91c1

[ "MIT" ]

null

from ._ast import * # noqa

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6

0b828080493ab6a7a8f3b77302742b1202604f7b

25,545

py

Python

jaseci_core/jaseci/jac/jac_parse/jacLexer.py

panikingginoo12/jaseci

6659ab3a3edde865e2ff9a8dc6f2c0f98588d05b

[ "MIT" ]

null

jaseci_core/jaseci/jac/jac_parse/jacLexer.py

panikingginoo12/jaseci

6659ab3a3edde865e2ff9a8dc6f2c0f98588d05b

[ "MIT" ]

null

jaseci_core/jaseci/jac/jac_parse/jacLexer.py

panikingginoo12/jaseci

6659ab3a3edde865e2ff9a8dc6f2c0f98588d05b

[ "MIT" ]

null

# Generated from jac.g4 by ANTLR 4.9.2 from antlr4 import * from io import StringIO import sys if sys.version_info[1] > 5: from typing import TextIO else: from typing.io import TextIO def serializedATN(): with StringIO() as buf: buf.write("\3\u608b\ua72a\u8133\ub9ed\u417c\u3be7\u7786\u5964\2Z") buf.write("\u026b\b\1\4\2\t\2\4\3\t\3\4\4\t\4\4\5\t\5\4\6\t\6\4\7") buf.write("\t\7\4\b\t\b\4\t\t\t\4\n\t\n\4\13\t\13\4\f\t\f\4\r\t\r") buf.write("\4\16\t\16\4\17\t\17\4\20\t\20\4\21\t\21\4\22\t\22\4\23") buf.write("\t\23\4\24\t\24\4\25\t\25\4\26\t\26\4\27\t\27\4\30\t\30") buf.write("\4\31\t\31\4\32\t\32\4\33\t\33\4\34\t\34\4\35\t\35\4\36") buf.write("\t\36\4\37\t\37\4 \t \4!\t!\4\"\t\"\4#\t#\4$\t$\4%\t%") buf.write("\4&\t&\4\'\t\'\4(\t(\4)\t)\4*\t*\4+\t+\4,\t,\4-\t-\4.") buf.write("\t.\4/\t/\4\60\t\60\4\61\t\61\4\62\t\62\4\63\t\63\4\64") buf.write("\t\64\4\65\t\65\4\66\t\66\4\67\t\67\48\t8\49\t9\4:\t:") buf.write("\4;\t;\4<\t<\4=\t=\4>\t>\4?\t?\4@\t@\4A\tA\4B\tB\4C\t") 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buf.write("\61\2\2\u024e\u024f\3\2\2\2\u024f\u0250\bU\2\2\u0250\u00aa") buf.write("\3\2\2\2\u0251\u0252\7\61\2\2\u0252\u0253\7\61\2\2\u0253") buf.write("\u0257\3\2\2\2\u0254\u0256\n\7\2\2\u0255\u0254\3\2\2\2") buf.write("\u0256\u0259\3\2\2\2\u0257\u0255\3\2\2\2\u0257\u0258\3") buf.write("\2\2\2\u0258\u025a\3\2\2\2\u0259\u0257\3\2\2\2\u025a\u025b") buf.write("\bV\2\2\u025b\u00ac\3\2\2\2\u025c\u0260\7%\2\2\u025d\u025f") buf.write("\n\7\2\2\u025e\u025d\3\2\2\2\u025f\u0262\3\2\2\2\u0260") buf.write("\u025e\3\2\2\2\u0260\u0261\3\2\2\2\u0261\u0263\3\2\2\2") buf.write("\u0262\u0260\3\2\2\2\u0263\u0264\bW\2\2\u0264\u00ae\3") buf.write("\2\2\2\u0265\u0266\t\b\2\2\u0266\u0267\3\2\2\2\u0267\u0268") buf.write("\bX\2\2\u0268\u00b0\3\2\2\2\u0269\u026a\13\2\2\2\u026a") buf.write("\u00b2\3\2\2\2\22\2\u0171\u0177\u01cb\u0210\u0212\u0218") buf.write("\u021e\u0226\u022a\u0235\u023a\u0240\u0249\u0257\u0260") buf.write("\3\b\2\2") return buf.getvalue() class jacLexer(Lexer): atn = ATNDeserializer().deserialize(serializedATN()) decisionsToDFA = [ DFA(ds, i) for i, ds in enumerate(atn.decisionToState) ] T__0 = 1 T__1 = 2 T__2 = 3 T__3 = 4 T__4 = 5 T__5 = 6 T__6 = 7 KW_GRAPH = 8 KW_STRICT = 9 KW_DIGRAPH = 10 KW_SUBGRAPH = 11 KW_NODE = 12 KW_IGNORE = 13 KW_TAKE = 14 KW_SPAWN = 15 KW_WITH = 16 KW_ENTRY = 17 KW_EXIT = 18 KW_LENGTH = 19 KW_KEYS = 20 KW_CONTEXT = 21 KW_INFO = 22 KW_DETAILS = 23 KW_ACTIVITY = 24 COLON = 25 DBL_COLON = 26 COLON_OUT = 27 LBRACE = 28 RBRACE = 29 KW_EDGE = 30 KW_WALKER = 31 SEMI = 32 EQ = 33 PEQ = 34 MEQ = 35 TEQ = 36 DEQ = 37 CPY_EQ = 38 KW_AND = 39 KW_OR = 40 KW_IF = 41 KW_ELIF = 42 KW_ELSE = 43 KW_FOR = 44 KW_TO = 45 KW_BY = 46 KW_WHILE = 47 KW_CONTINUE = 48 KW_BREAK = 49 KW_DISENGAGE = 50 KW_SKIP = 51 KW_REPORT = 52 KW_DESTROY = 53 DEREF = 54 DOT = 55 NOT = 56 EE = 57 LT = 58 GT = 59 LTE = 60 GTE = 61 NE = 62 KW_IN = 63 KW_ANCHOR = 64 KW_HAS = 65 KW_PRIVATE = 66 COMMA = 67 KW_CAN = 68 PLUS = 69 MINUS = 70 MUL = 71 DIV = 72 MOD = 73 POW = 74 LPAREN = 75 RPAREN = 76 LSQUARE = 77 RSQUARE = 78 FLOAT = 79 STRING = 80 BOOL = 81 INT = 82 NAME = 83 COMMENT = 84 LINE_COMMENT = 85 PY_COMMENT = 86 WS = 87 ErrorChar = 88 channelNames = [ u"DEFAULT_TOKEN_CHANNEL", u"HIDDEN" ] modeNames = [ "DEFAULT_MODE" ] literalNames = [ "<INVALID>", "'version'", "'-->'", "'->'", "'<--'", "'<-'", "'<-->'", "'--'", "'graph'", "'strict'", "'digraph'", "'subgraph'", "'node'", "'ignore'", "'take'", "'spawn'", "'with'", "'entry'", "'exit'", "'length'", "'keys'", "'context'", "'info'", "'details'", "'activity'", "':'", "'::'", "'::>'", "'{'", "'}'", "'edge'", "'walker'", "';'", "'='", "'+='", "'-='", "'*='", "'/='", "':='", "'if'", "'elif'", "'else'", "'for'", "'to'", "'by'", "'while'", "'continue'", "'break'", "'disengage'", "'skip'", "'report'", "'destroy'", "'&'", "'.'", "'=='", "'<'", "'>'", "'<='", "'>='", "'!='", "'in'", "'anchor'", "'has'", "'private'", "','", "'can'", "'+'", "'-'", "'*'", "'/'", "'%'", "'^'", "'('", "')'", "'['", "']'" ] symbolicNames = [ "<INVALID>", "KW_GRAPH", "KW_STRICT", "KW_DIGRAPH", "KW_SUBGRAPH", "KW_NODE", "KW_IGNORE", "KW_TAKE", "KW_SPAWN", "KW_WITH", "KW_ENTRY", "KW_EXIT", "KW_LENGTH", "KW_KEYS", "KW_CONTEXT", "KW_INFO", "KW_DETAILS", "KW_ACTIVITY", "COLON", "DBL_COLON", "COLON_OUT", "LBRACE", "RBRACE", "KW_EDGE", "KW_WALKER", "SEMI", "EQ", "PEQ", "MEQ", "TEQ", "DEQ", "CPY_EQ", "KW_AND", "KW_OR", "KW_IF", "KW_ELIF", "KW_ELSE", "KW_FOR", "KW_TO", "KW_BY", "KW_WHILE", "KW_CONTINUE", "KW_BREAK", "KW_DISENGAGE", "KW_SKIP", "KW_REPORT", "KW_DESTROY", "DEREF", "DOT", "NOT", "EE", "LT", "GT", "LTE", "GTE", "NE", "KW_IN", "KW_ANCHOR", "KW_HAS", "KW_PRIVATE", "COMMA", "KW_CAN", "PLUS", "MINUS", "MUL", "DIV", "MOD", "POW", "LPAREN", "RPAREN", "LSQUARE", "RSQUARE", "FLOAT", "STRING", "BOOL", "INT", "NAME", "COMMENT", "LINE_COMMENT", "PY_COMMENT", "WS", "ErrorChar" ] ruleNames = [ "T__0", "T__1", "T__2", "T__3", "T__4", "T__5", "T__6", "KW_GRAPH", "KW_STRICT", "KW_DIGRAPH", "KW_SUBGRAPH", "KW_NODE", "KW_IGNORE", "KW_TAKE", "KW_SPAWN", "KW_WITH", "KW_ENTRY", "KW_EXIT", "KW_LENGTH", "KW_KEYS", "KW_CONTEXT", "KW_INFO", "KW_DETAILS", "KW_ACTIVITY", "COLON", "DBL_COLON", "COLON_OUT", "LBRACE", "RBRACE", "KW_EDGE", "KW_WALKER", "SEMI", "EQ", "PEQ", "MEQ", "TEQ", "DEQ", "CPY_EQ", "KW_AND", "KW_OR", "KW_IF", "KW_ELIF", "KW_ELSE", "KW_FOR", "KW_TO", "KW_BY", "KW_WHILE", "KW_CONTINUE", "KW_BREAK", "KW_DISENGAGE", "KW_SKIP", "KW_REPORT", "KW_DESTROY", "DEREF", "DOT", "NOT", "EE", "LT", "GT", "LTE", "GTE", "NE", "KW_IN", "KW_ANCHOR", "KW_HAS", "KW_PRIVATE", "COMMA", "KW_CAN", "PLUS", "MINUS", "MUL", "DIV", "MOD", "POW", "LPAREN", "RPAREN", "LSQUARE", "RSQUARE", "FLOAT", "STRING", "BOOL", "INT", "NAME", "COMMENT", "LINE_COMMENT", "PY_COMMENT", "WS", "ErrorChar" ] grammarFileName = "jac.g4" def __init__(self, input=None, output:TextIO = sys.stdout): super().__init__(input, output) self.checkVersion("4.9.2") self._interp = LexerATNSimulator(self, self.atn, self.decisionsToDFA, PredictionContextCache()) self._actions = None self._predicates = None

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e7eb1cc9b94fe8f97ab365303db26104068e08ec

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Python

duplicates/__init__.py

akcarsten/duplicates

b61b6f4bb562b21b3daf239cb0284b9c131f97c3

[ "MIT" ]

10

2021-01-11T14:53:28.000Z

2022-03-09T00:57:02.000Z

duplicates/__init__.py

akcarsten/duplicates

b61b6f4bb562b21b3daf239cb0284b9c131f97c3

[ "MIT" ]

1

2021-05-05T05:49:02.000Z

2021-05-10T03:25:41.000Z

duplicates/__init__.py

akcarsten/duplicates

b61b6f4bb562b21b3daf239cb0284b9c131f97c3

[ "MIT" ]

5

2021-06-05T05:30:17.000Z

2022-03-20T22:38:53.000Z

from .duplicates import *

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Python

ScanningTools/__init__.py

fincardona/ScanningTools.py

ecbd07b2535b3388bd66c7f9c738ec5367d1d05a

[ "MIT" ]

1

2018-10-09T10:31:56.000Z

ScanningTools/__init__.py

fincardona/ScanningTools.py

ecbd07b2535b3388bd66c7f9c738ec5367d1d05a

[ "MIT" ]

null

ScanningTools/__init__.py

fincardona/ScanningTools.py

ecbd07b2535b3388bd66c7f9c738ec5367d1d05a

[ "MIT" ]

null

from . import ScanningTools, Quaternions

20.5

40

0.829268

4

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0

0.121951

41

1

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1

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true

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1

0

1

0

1

0

6

b2b357070580aea5bfdf8d64e159d7282fb3c089

23,038

py

Python

src/dataset.py

atzberg/gmls-nets

d78e5b513b7dda8491f68e11dab730f106f86385

[ "BSD-3-Clause" ]

18

2019-09-17T18:58:26.000Z

2021-08-05T06:02:16.000Z

src/dataset.py

atzberg/gmls-nets

d78e5b513b7dda8491f68e11dab730f106f86385

[ "BSD-3-Clause" ]

null

src/dataset.py

atzberg/gmls-nets

d78e5b513b7dda8491f68e11dab730f106f86385

[ "BSD-3-Clause" ]

4

2019-11-16T04:02:07.000Z

2021-03-06T11:43:04.000Z

""" Collection of codes for generating some training data sets. """ # Authors: B.J. Gross and P.J. Atzberger # Website: http://atzberger.org/ import torch; import numpy as np; import pdb; class diffOp1(torch.utils.data.Dataset): r""" Generates samples of the form :math:`(u^{[i]},f^{[i]})` where :math:`f^{[i]} = L[u^{[i]}]`, where :math:`i` denotes the index of the sample. Stores data samples in the form :math:`(u,f)`. The samples of u are represented as a tensor of size [nsamples,nchannels,nx] and sample of f as a tensor of size [nsamples,nchannels,nx]. Note: For now, please use nx that is odd. In this initial implementation, we use a method based on conjugated flips with formula for the odd case which is slightly simpler than other case. """ def flipForFFT(self,u_k_part): r"""We flip as :math:`f_k = f_{N-k}`. Notice that only :math:`0,\ldots,N-1` entries stored. This is useful for constructing real-valued function representations from random coefficients. Real-valued function requires :math:`conj(f_k) = f_{N-k}`. We can use this flip to construct from random coefficients the term :math:`u_k = f_k + conj(flip(f_k))`, then above constraint is satisfied. Args: a (Tensor): 1d array to flip. Returns: Tensor: The flipped tensors symmetric under conjucation. """ nx = self.nx; uu = u_k_part[:,:,nx:0:-1]; vv = u_k_part[:,:,0]; vv = np.expand_dims(vv,2); uu_k_flip = np.concatenate([vv,uu],2); return uu_k_flip; def getComplex(self,a,b): j = np.complex(0,1); # create complex number (or use 1j). c = a + j*b; return c; def getRealImag(self,c): a = np.real(c); b = np.imag(c); return a,b; def computeLSymbol_ux(self): r"""Compute associated Fourier symbols for use under DFT for the operator L[u].""" nx = self.nx; vec_k1 = torch.zeros(nx); vec_k1_pp = torch.zeros(nx); vec_k_sq = torch.zeros(nx); L_symbol_real = torch.zeros(nx,dtype=torch.float32); L_symbol_imag = torch.zeros(nx,dtype=torch.float32); two_pi = 2.0*np.pi; #two_pi_i = two_pi*1j; # $2\pi{i}$, 1j = sqrt(-1) for i in range(0,nx): vec_k1[i] = i; if (vec_k1[i] < nx/2): vec_k1_p = vec_k1[i]; else: vec_k1_p = vec_k1[i] - nx; vec_k1_pp[i] = vec_k1_p; L_symbol_real[i] = 0.0; L_symbol_imag[i] = two_pi*vec_k1_p; L_hat = self.getComplex(L_symbol_real.numpy(),L_symbol_imag.numpy()); return L_hat, vec_k1_pp; def computeLSymbol_uxx(self): r"""Compute associated Fourier symbols for use under DFT for the operator L[u].""" nx = self.nx; vec_k1 = torch.zeros(nx); vec_k1_pp = torch.zeros(nx); vec_k_sq = torch.zeros(nx); L_symbol_real = torch.zeros(nx,dtype=torch.float32); L_symbol_imag = torch.zeros(nx,dtype=torch.float32); neg_four_pi_sq = -4.0*np.pi*np.pi; for i in range(0,nx): vec_k1[i] = i; vec_k_sq[i] = vec_k1[i]*vec_k1[i]; if (vec_k1[i] < nx/2): vec_k1_p = vec_k1[i]; else: vec_k1_p = vec_k1[i] - nx; vec_k1_pp[i] = vec_k1_p; vec_k_p_sq = vec_k1_p*vec_k1_p; L_symbol_real[i] = neg_four_pi_sq*vec_k_p_sq; L_symbol_imag[i] = 0.0; L_hat = self.getComplex(L_symbol_real.numpy(),L_symbol_imag.numpy()); return L_hat, vec_k1_pp; def computeCoeffActionL(self,u_hat,L_hat): r"""Computes the action of operator L used for data generation in Fourier space.""" u_k_real, u_k_imag = self.getRealImag(u_hat); L_symbol_real, L_symbol_imag = self.getRealImag(L_hat); f_k_real = L_symbol_real*u_k_real - L_symbol_imag*u_k_imag; #broadcast will distr over copies of u. f_k_imag = L_symbol_real*u_k_imag + L_symbol_imag*u_k_real; # Generate samples u and f using ifft f_hat = self.getComplex(f_k_real,f_k_imag); return f_hat; def computeActionL(self,u,L_hat): r"""Computes the action of operator L used for data generation.""" raise Exception('Currently this routine not debugged, need to test first.') if flag_verbose > 0: print("computeActionL(): WARNING: Not yet fully tested."); # perform FFT to get u_hat u_hat = np.fft.fft(u); # compute action of L_hat f_hat = self.computeCoeffActionL(u_hat,L_hat); # compute inverse FFT to get f f = np.fft.ifft(f_hat); return f; def __init__(self,op_type='uxx',op_params=None, gen_mode='exp1',gen_params={'alpha1':0.1}, num_samples=int(1e4),nchannels=1,nx=15, flag_verbose=0, **extra_params): r"""Setup for data generation. Args: op_type (str): The differential operator to sample. op_params (dict): The operator parameters. gen_mode (str): The mode for the data generator. gen_params (dict): The parameters for the given generator. num_samples (int): The number of samples to generate. nchannels (int): The number of channels. nx (int): The number of input sample points. flag_verbose (int): Level of reporting during calculations. extra_params (dict): Extra parameters for the sampler. For extra_params we have: noise_factor (float): The amount of noise to add to samples. scale_factor (float): A factor to scale magnitude of the samples. flagComputeL (bool): If the fourier symbol of operator should be computed. For generator modes we have: gen_mode == 'exp1': alpha1 (float): The decay rate. Note: For now, please use only nx that is odd. In this initial implementation, we use a method based on conjugated flips with formula for the odd case which is slightly simpler than other case. """ super(diffOp1, self).__init__(); if flag_verbose > 0: print("Generating the data samples which can take some time."); print("num_samples = %d"%num_samples); self.op_type=op_type; self.op_params=op_params; self.gen_mode=gen_mode; self.gen_params=gen_params; self.num_samples=num_samples; self.nchannels=nchannels; self.nx=nx; if (nx % 2 == 0): msg = "Not allowed yet to use nx that is even. "; msg += "For now, please just use nx that is odd given the flips currently used." raise Exception(msg); noise_factor=0;scale_factor=1.0;flagComputeL=False; # default values if 'noise_factor' in extra_params: noise_factor = extra_params['noise_factor']; if 'scale_factor' in extra_params: scale_factor = extra_params['scale_factor']; if 'flagComputeL' in extra_params: flagComputeL = extra_params['flagComputeL']; # Generate for the operator the Fourier symbols if self.op_type == 'ux' or self.op_type == 'u*ux' or self.op_type == 'ux*ux': L_hat, vec_k1_pp = self.computeLSymbol_ux(); elif self.op_type == 'uxx' or self.op_type == 'u*uxx' or self.op_type == 'uxx*uxx': L_hat, vec_k1_pp = self.computeLSymbol_uxx(); else: raise Exception("Unkonwn operator type."); if (flagComputeL): L_i = np.fft.ifft(L_hat); self.L_hat = L_hat; self.L_i = L_i; u = np.zeros(nx); i0 = int(nx/2); u[i0] = 1.0; self.G_i = self.computeActionL(u); # Generate random input function (want real-valued) # conj(u_k) = u_{N -k} needs to hold. u_k_real = np.random.randn(num_samples,nchannels,nx); u_k_imag = np.random.randn(num_samples,nchannels,nx); # scale modes to make smooth if gen_mode=='exp1': alpha1 = gen_params['alpha1']; factor_k = scale_factor*np.exp(-alpha1*vec_k1_pp**2); factor_k = factor_k.numpy(); else: raise Exception("Generation mode not recognized."); u_k_real = u_k_real*factor_k; # broadcast will apply over last two dimensions u_k_imag = u_k_imag*factor_k; # broadcast will apply over last two dimensions flag_debug = False; if flag_debug: if flag_verbose > 0: print("WARNING: debugging mode on."); u_k_real = 0.0*u_k_real; u_k_imag = 0.0*u_k_imag; u_k_real[0,0,1] = nx; u_k_imag[0,0,1] = 0; u_k_real[1,0,1] = 0; u_k_imag[1,0,1] = nx; u_k_real[2,0,1] = nx; u_k_imag[2,0,1] = nx; # flip modes for constructing rep of real-valued function u_k_real_flip = self.flipForFFT(u_k_real); u_k_imag_flip = self.flipForFFT(u_k_imag); u_k_real_p = 0.5*u_k_real + 0.5*u_k_real_flip; # make conjugate conj(u_k) = u_{N -k} u_k_imag_p = 0.5*u_k_imag - 0.5*u_k_imag_flip; # make conjugate conj(u_k) = u_{N -k} u_k_real_p = torch.from_numpy(u_k_real_p); u_k_imag_p = torch.from_numpy(u_k_imag_p); u_k_real_p = u_k_real_p.type(torch.float32); u_k_imag_p = u_k_imag_p.type(torch.float32); u_hat = self.getComplex(u_k_real_p.numpy(),u_k_imag_p.numpy()); f_hat = self.computeCoeffActionL(u_hat,L_hat); f_hat = f_hat; # target operator relation for PDEs later is Lu = -f, so f = -Lu. # Generate samples u and f, in 2d using ifft2. # ifft2 is broadcast over last two indices # perform inverse DFT to get u and f. u_i = np.fft.ifft(u_hat); f_i = np.fft.ifft(f_hat); if self.op_type == 'u*ux': f_i = u_i*f_i; elif self.op_type == 'ux*ux': f_i = f_i*f_i; elif self.op_type == 'u*uxx': f_i = u_i*f_i; elif self.op_type == 'uxx*uxx': f_i = f_i*f_i; self.samples_X = torch.from_numpy(np.real(u_i)).type(torch.float32); # only grab real part self.samples_Y = torch.from_numpy(np.real(f_i)).type(torch.float32); if noise_factor > 0: self.samples_Y += noise_factor*torch.randn(*self.samples_Y.shape); def __len__(self): return self.samples_X.size()[0]; def __getitem__(self,index): return self.samples_X[index],self.samples_Y[index]; def to(self,device): self.samples_X = self.samples_X.to(device); self.samples_Y = self.samples_Y.to(device); return self; class diffOp2(torch.utils.data.Dataset): r""" Generates samples of the form :math:`(u^{[i]},f^{[i]})` where :math:`f^{[i]} = L[u^{[i]}]`, where :math:`i` denotes the index of the sample. Stores data samples in the form :math:`(u,f)`. The samples of u are represented as a tensor of size [nsamples,nchannels,nx] and sample of f as a tensor of size [nsamples,nchannels,nx]. Note: For now, please use nx that is odd. In this initial implementation, we use a method based on conjugated flips with formula for the odd case which is slightly simpler than other case. """ def flipForFFT(self,u_k_part): r"""We flip as :math:`f_k = f_{N-k}`. Notice that only :math:`0,\ldots,N-1` entries stored. This is useful for constructing real-valued function representations from random coefficients. Real-valued function requires :math:`conj(f_k) = f_{N-k}`. We can use this flip to construct from random coefficients the term :math:`u_k = f_k + conj(flip(f_k))`, then above constraint is satisfied. Args: a (Tensor): 1d array to flip. Returns: Tensor: The flipped tensors symmetric under conjucation. """ nx = self.nx;ny = self.ny; u_k_part_row0 = u_k_part[:,:,0,:]; u_k_part_row0 = np.expand_dims(u_k_part_row0,2); u_k_part_ex = np.concatenate([u_k_part,u_k_part_row0],2); u_k_part_col0 = u_k_part_ex[:,:,:,0]; u_k_part_col0 = np.expand_dims(u_k_part_col0,3); u_k_part_ex = np.concatenate([u_k_part_ex,u_k_part_col0],3); u_k_part_ex_flip = np.flip(u_k_part_ex,2); u_k_part_ex_flip = np.flip(u_k_part_ex_flip,3); u_k_part_flip = np.delete(u_k_part_ex_flip,nx,2); u_k_part_flip = np.delete(u_k_part_flip,ny,3); return u_k_part_flip; def getComplex(self,a,b): j = np.complex(0,1); # create complex number (or use 1j). c = a + j*b; return c; def getRealImag(self,c): a = np.real(c); b = np.imag(c); return a,b; def computeLSymbol_laplacian_u(self): r"""Compute associated Fourier symbols for use under DFT for the operator L[u].""" num_dim = 1;nx=self.nx;ny=self.ny; vec_k1 = torch.zeros(nx,ny); vec_k2 = torch.zeros(nx,ny); vec_k1_pp = torch.zeros(nx,ny); vec_k2_pp = torch.zeros(nx,ny); vec_k_sq = torch.zeros(nx,ny); L_symbol_real = torch.zeros(nx,ny,dtype=torch.float32); L_symbol_imag = torch.zeros(nx,ny,dtype=torch.float32); neg_four_pi_sq = -4.0*np.pi*np.pi; for i in range(0,nx): for j in range(0,ny): vec_k1[i,j] = i; vec_k2[i,j] = j; vec_k_sq[i,j] = vec_k1[i,j]*vec_k1[i,j] + vec_k2[i,j]*vec_k2[i,j]; if (vec_k1[i,j] < nx/2): vec_k1_p = vec_k1[i,j]; else: vec_k1_p = vec_k1[i,j] - nx; if (vec_k2[i,j] < ny/2): vec_k2_p = vec_k2[i,j]; else: vec_k2_p = vec_k2[i,j] - ny; vec_k1_pp[i,j] = vec_k1_p; vec_k2_pp[i,j] = vec_k2_p; vec_k_p_sq = vec_k1_p*vec_k1_p + vec_k2_p*vec_k2_p; L_symbol_real[i,j] = neg_four_pi_sq*vec_k_p_sq; L_symbol_imag[i,j] = 0.0; L_hat = self.getComplex(L_symbol_real.numpy(),L_symbol_imag.numpy()); return L_hat, vec_k1_pp, vec_k2_pp; def computeLSymbol_grad_u(self): r"""Compute associated Fourier symbols for use under DFT for the operator L[u].""" num_dim = 2;nx=self.nx;ny=self.ny; vec_k1 = torch.zeros(nx,ny); vec_k2 = torch.zeros(nx,ny); vec_k1_pp = torch.zeros(nx,ny); vec_k2_pp = torch.zeros(nx,ny); vec_k_sq = torch.zeros(nx,ny); L_symbol_real = torch.zeros(num_dim,nx,ny,dtype=torch.float32); L_symbol_imag = torch.zeros(num_dim,nx,ny,dtype=torch.float32); two_pi = 2.0*np.pi; #two_pi_i = two_pi*1j; # $2\pi{i}$, 1j = sqrt(-1) for i in range(0,nx): for j in range(0,ny): vec_k1[i,j] = i; vec_k2[i,j] = j; vec_k_sq[i,j] = vec_k1[i,j]*vec_k1[i,j] + vec_k2[i,j]*vec_k2[i,j]; if (vec_k1[i,j] < nx/2): vec_k1_p = vec_k1[i,j]; else: vec_k1_p = vec_k1[i,j] - nx; if (vec_k2[i,j] < ny/2): vec_k2_p = vec_k2[i,j]; else: vec_k2_p = vec_k2[i,j] - ny; vec_k1_pp[i,j] = vec_k1_p; vec_k2_pp[i,j] = vec_k2_p; vec_k_p_sq = vec_k1_p*vec_k1_p + vec_k2_p*vec_k2_p; L_symbol_real[0,i,j] = 0.0; L_symbol_imag[0,i,j] = two_pi*vec_k1_p; L_symbol_real[1,i,j] = 0.0; L_symbol_imag[1,i,j] = two_pi*vec_k2_p; L_hat_0 = self.getComplex(L_symbol_real[0,:,:].numpy(),L_symbol_imag[0,:,:].numpy()); L_hat_1 = self.getComplex(L_symbol_real[1,:,:].numpy(),L_symbol_imag[1,:,:].numpy()); L_hat = np.stack((L_hat_0,L_hat_1)); return L_hat, vec_k1_pp, vec_k2_pp; def computeCoeffActionL(self,u_hat,L_hat): r"""Computes the action of operator L used for data generation in Fourier space.""" u_k_real, u_k_imag = self.getRealImag(u_hat); L_symbol_real, L_symbol_imag = self.getRealImag(L_hat); f_k_real = L_symbol_real*u_k_real - L_symbol_imag*u_k_imag; #broadcast will distr over copies of u. #f_k_real = -1.0*f_k_real; f_k_imag = L_symbol_real*u_k_imag + L_symbol_imag*u_k_real; #f_k_imag = -1.0*f_k_imag; # Generate samples u and f using ifft2. f_hat = self.getComplex(f_k_real,f_k_imag); return f_hat; def computeActionL(self,u,L_hat): r"""Computes the action of operator L used for data generation.""" raise Exception('Currently this routine not debugged, need to test first.') # perform FFT to get u_hat u_hat = np.fft.fft2(u); # compute action of L_hat f_hat = self.computeCoeffActionL(u_hat,L_hat); # compute inverse FFT to get f f = np.fft.ifft2(f_hat) return f; def __init__(self,op_type=r'\Delta{u}',op_params=None, gen_mode='exp1',gen_params={'alpha1':0.1}, num_samples=int(1e4),nchannels=1,nx=15,ny=15, flag_verbose=0, **extra_params): r"""Setup for data generation. Args: op_type (str): The differential operator to sample. op_params (dict): The operator parameters. gen_mode (str): The mode for the data generator. gen_params (dict): The parameters for the given generator. num_samples (int): The number of samples to generate. nchannels (int): The number of channels. nx (int): The number of input sample points in x-direction. ny (int): The number of input sample points in y- direction. flag_verbose (int): Level of reporting during calculations. extra_params (dict): Extra parameters for the sampler. For extra_params we have: noise_factor (float): The amount of noise to add to samples. scale_factor (float): A factor to scale magnitude of the samples. flagComputeL (bool): If the fourier symbol of operator should be computed. For generator modes we have: gen_mode == 'exp1': alpha1 (float): The decay rate. Note: For now, please use only nx that is odd. In this initial implementation, we use a method based on conjugated flips with formula for the odd case which is slightly simpler than other case. """ if flag_verbose > 0: print("Generating the data samples which can take some time."); print("num_samples = %d"%num_samples); self.op_type=op_type; self.op_params=op_params; self.gen_mode=gen_mode; self.gen_params=gen_params; self.num_samples=num_samples; self.nchannels=nchannels; self.nx=nx; self.ny=ny; if (nx % 2 == 0) or (ny % 2 == 0) or (nx != ny): # may be able to relax nx != ny (just for safety) msg = "Not allowed yet to use nx,ny that are even or unequal. "; msg += "For now, please just use nx,ny that is odd given the flips currently used." raise Exception(msg); noise_factor=0;scale_factor=1.0;flagComputeL=False; # default values if 'noise_factor' in extra_params: noise_factor = extra_params['noise_factor']; if 'scale_factor' in extra_params: scale_factor = extra_params['scale_factor']; if 'flagComputeL' in extra_params: flagComputeL = extra_params['flagComputeL']; # Generate for the operator the Fourier symbols flag_vv = 'null'; if self.op_type == r'\grad{u}' or self.op_type == r'u\grad{u}' or self.op_type == r'\grad{u}\cdot\grad{u}': L_hat, vec_k1_pp, vec_k2_pp = self.computeLSymbol_grad_u(); flag_vv = 'vector2'; elif self.op_type == r'\Delta{u}' or self.op_type == r'u\Delta{u}' or self.op_type == r'\Delta{u}*\Delta{u}': L_hat, vec_k1_pp, vec_k2_pp = self.computeLSymbol_laplacian_u(); flag_vv = 'scalar'; else: raise Exception("Unknown operator type."); if (flagComputeL): raise Exception("Currently not yet supported, the flagComputeL."); L_i = np.fft.ifft2(L_hat); self.L_hat = L_hat; self.L_i = L_i; u = np.zeros(nx,ny); i0 = int(nx/2); j0 = int(ny/2); u[i0,j0] = 1.0; self.G_i = self.computeActionL(u); # Generate random input function (want real-valued) # conj(u_k) = u_{N -k} needs to hold. u_k_real = np.random.randn(num_samples,nchannels,nx,ny); u_k_imag = np.random.randn(num_samples,nchannels,nx,ny); # scale modes to make smooth if gen_mode=='exp1': alpha1 = gen_params['alpha1']; factor_k = scale_factor*np.exp(-alpha1*(vec_k1_pp**2 + vec_k2_pp**2)); factor_k = factor_k.numpy(); else: raise Exception("Generation mode not recognized."); u_k_real = u_k_real*factor_k; # broadcast will apply over last two dimensions u_k_imag = u_k_imag*factor_k; # broadcast will apply over last two dimensions # flip modes for constructing rep of real-valued function u_k_real_flip = self.flipForFFT(u_k_real); u_k_imag_flip = self.flipForFFT(u_k_imag); u_k_real = 0.5*u_k_real + 0.5*u_k_real_flip; # make conjugate conj(u_k) = u_{N -k} u_k_imag = 0.5*u_k_imag - 0.5*u_k_imag_flip; # make conjugate conj(u_k) = u_{N -k} u_k_real = torch.from_numpy(u_k_real); u_k_imag = torch.from_numpy(u_k_imag); u_k_real = u_k_real.type(torch.float32); u_k_imag = u_k_imag.type(torch.float32); u_hat = self.getComplex(u_k_real.numpy(),u_k_imag.numpy()); if flag_vv == 'scalar': f_hat = self.computeCoeffActionL(u_hat,L_hat); elif flag_vv == 'vector2': f_hat_0 = self.computeCoeffActionL(u_hat,L_hat[0,:,:]); f_hat_1 = self.computeCoeffActionL(u_hat,L_hat[1,:,:]); f_hat = np.concatenate((f_hat_0,f_hat_1),-3); else: raise Exception("Unkonwn operator type."); # Generate samples u and f using ifft2. # ifft2 is broadcast over last two indices # perform inverse DFT to get u and f u_i = np.fft.ifft2(u_hat); if flag_vv == 'scalar': f_i = np.fft.ifft2(f_hat); elif flag_vv == 'vector2': f_i_0 = np.fft.ifft2(f_hat[:,0,:,:]); f_i_1 = np.fft.ifft2(f_hat[:,1,:,:]); f_i = np.stack((f_i_0,f_i_1),-3); else: raise Exception("Unkonwn operator type."); if self.op_type == r'\grad{u}': f_i = f_i; # nothing to do. elif self.op_type == r'u\grad{u}': f_i = u_i*f_i; # matches up by broadcast rules elif self.op_type == r'\grad{u}\cdot\grad{u}': f_i = np.sum(f_i**2,1); # sum on axis for channels, [batch,channel,nx,ny]. f_i = np.expand_dims(f_i,1); # keep in form [batch,1,nx,ny] elif self.op_type == r'\Delta{u}': f_i = f_i; # nothing to do. elif self.op_type == r'u\Delta{u}': f_i = u_i*f_i; elif self.op_type == r'\Delta{u}*\Delta{u}': f_i = f_i**2; else: raise Exception("Unkonwn operator type."); self.samples_X = torch.from_numpy(np.real(u_i)).type(torch.float32); # only grab real part self.samples_Y = torch.from_numpy(np.real(f_i)).type(torch.float32); if noise_factor > 0: self.samples_Y += noise_factor*torch.randn(*self.samples_Y.shape); def __len__(self): return self.samples_X.size()[0]; def __getitem__(self,index): return self.samples_X[index],self.samples_Y[index]; def to(self,device): self.samples_X = self.samples_X.to(device); self.samples_Y = self.samples_Y.to(device); return self;

36.510301

113

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23,038

3.465619

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null

0

6

6534aa15fe9e54affb901ef2b18a9190fe51c44f

224

py

Python

blurr/data/all.py

HenryDashwood/blurr

dececd4e706129694b25ee80c15dfb61ffadf9a9

[ "Apache-2.0" ]

null

blurr/data/all.py

HenryDashwood/blurr

dececd4e706129694b25ee80c15dfb61ffadf9a9

[ "Apache-2.0" ]

null

blurr/data/all.py

HenryDashwood/blurr

dececd4e706129694b25ee80c15dfb61ffadf9a9

[ "Apache-2.0" ]

null

from ..utils import * from .core import * from .question_answering import * from .token_classification import * from .text2text.core import * from .text2text.language_modeling import * from .text2text.summarization import *

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6

6545f00275d150f756fbd1778003e8a75c79ccd9

6,497

py

Python

tests/test_inventory_set.py

qhyou11/bridgy

887ff2b41d0d04ad469fb4838191a4a578597bdd

[ "MIT" ]

402

2017-08-09T19:27:49.000Z

2022-03-22T10:24:00.000Z

tests/test_inventory_set.py

qhyou11/bridgy

887ff2b41d0d04ad469fb4838191a4a578597bdd

[ "MIT" ]

33

2017-08-03T23:10:44.000Z

2020-12-16T03:29:33.000Z

tests/test_inventory_set.py

qhyou11/bridgy

887ff2b41d0d04ad469fb4838191a4a578597bdd

[ "MIT" ]

58

2017-11-19T21:22:45.000Z

2022-03-22T09:25:04.000Z

import os import mock import pytest import bridgy.inventory from bridgy.inventory import InventorySet, Instance from bridgy.inventory.aws import AwsInventory from bridgy.config import Config def get_aws_inventory(name): test_dir = os.path.dirname(os.path.abspath(__file__)) cache_dir = os.path.join(test_dir, 'aws_stubs') aws_obj = AwsInventory(name=name, cache_dir=cache_dir, access_key_id='access_key_id', secret_access_key='secret_access_key', session_token='session_token', region='region') return aws_obj def test_inventory_set(mocker): test_dir = os.path.dirname(os.path.abspath(__file__)) cache_dir = os.path.join(test_dir, 'aws_stubs') aws_obj = get_aws_inventory(name='aws') inventorySet = InventorySet() inventorySet.add(aws_obj) inventorySet.add(aws_obj) print(aws_obj.instances()) all_instances = inventorySet.instances() aws_instances = [ Instance(name=u'test-forms', address=u'devbox', aliases=(u'devbox', u'ip-172-31-8-185.us-west-2.compute.internal', u'i-e54cbaeb'), source='aws (aws)', container_id=None, type='VM'), Instance(name=u'devlab-forms', address=u'devbox', aliases=(u'devbox', u'ip-172-31-0-138.us-west-2.compute.internal', u'i-f7d726f9'), source='aws (aws)', container_id=None, type='VM'), Instance(name=u'test-account-svc', address=u'devbox', aliases=(u'devbox', u'ip-172-31-0-139.us-west-2.compute.internal', u'i-f4d726fa'), source='aws (aws)', container_id=None, type='VM'), Instance(name=u'devlab-pubsrv', address=u'devbox', aliases=(u'devbox', u'ip-172-31-0-142.us-west-2.compute.internal', u'i-f5d726fb'), source='aws (aws)', container_id=None, type='VM'), Instance(name=u'devlab-game-svc', address=u'devbox', aliases=(u'devbox', u'ip-172-31-0-140.us-west-2.compute.internal', u'i-f2d726fc'), source='aws (aws)', container_id=None, type='VM'), Instance(name=u'test-game-svc', address=u'devbox', aliases=(u'devbox', u'ip-172-31-0-141.us-west-2.compute.internal', u'i-f3d726fd'), source='aws (aws)', container_id=None, type='VM'), Instance(name=u'test-pubsrv', address=u'devbox', aliases=(u'devbox', u'ip-172-31-2-38.us-west-2.compute.internal', u'i-0f500447384e95942'), source='aws (aws)', container_id=None, type='VM'), Instance(name=u'test-pubsrv', address=u'devbox', aliases=(u'devbox', u'ip-172-31-2-39.us-west-2.compute.internal', u'i-0f500447384e95943'), source='aws (aws)', container_id=None, type='VM') ] expected_instances = aws_instances + aws_instances assert len(all_instances) == len(expected_instances) assert set(all_instances) == set(expected_instances) def test_inventory_set_filter_sources(mocker): test_dir = os.path.dirname(os.path.abspath(__file__)) cache_dir = os.path.join(test_dir, 'aws_stubs') inventorySet = InventorySet() inventorySet.add(get_aws_inventory(name='aws')) inventorySet.add(get_aws_inventory(name='awesome')) print(inventorySet.instances()) all_instances = inventorySet.instances(filter_sources='awesome') # aws_instances = [ # Instance(name='test-forms', address='devbox', aliases=('devbox', 'ip-172-31-8-185.us-west-2.compute.internal', 'i-e54cbaeb'), source='aws (aws)', container_id=None, type='VM'), # Instance(name='devlab-forms', address='devbox', aliases=('devbox', 'ip-172-31-0-138.us-west-2.compute.internal', 'i-f7d726f9'), source='aws (aws)', container_id=None, type='VM'), # Instance(name='test-account-svc', address='devbox', aliases=('devbox', 'ip-172-31-0-139.us-west-2.compute.internal', 'i-f4d726fa'), source='aws (aws)', container_id=None, type='VM'), # Instance(name='devlab-pubsrv', address='devbox', aliases=('devbox', 'ip-172-31-0-142.us-west-2.compute.internal', 'i-f5d726fb'), source='aws (aws)', container_id=None, type='VM'), # Instance(name='devlab-game-svc', address='devbox', aliases=('devbox', 'ip-172-31-0-140.us-west-2.compute.internal', 'i-f2d726fc'), source='aws (aws)', container_id=None, type='VM'), # Instance(name='test-game-svc', address='devbox', aliases=('devbox', 'ip-172-31-0-141.us-west-2.compute.internal', 'i-f3d726fd'), source='aws (aws)', container_id=None, type='VM'), # Instance(name='test-pubsrv', address='devbox', aliases=('devbox', 'ip-172-31-2-38.us-west-2.compute.internal', 'i-0f500447384e95942'), source='aws (aws)', container_id=None, type='VM'), # Instance(name='test-pubsrv', address='devbox', aliases=('devbox', 'ip-172-31-2-39.us-west-2.compute.internal', 'i-0f500447384e95943'), source='aws (aws)', container_id=None, type='VM') # ] awesome_instances = [ Instance(name='test-forms', address='devbox', aliases=('devbox', 'ip-172-31-8-185.us-west-2.compute.internal', 'i-e54cbaeb'), source='awesome (aws)', container_id=None, type='VM'), Instance(name='devlab-forms', address='devbox', aliases=('devbox', 'ip-172-31-0-138.us-west-2.compute.internal', 'i-f7d726f9'), source='awesome (aws)', container_id=None, type='VM'), Instance(name='test-account-svc', address='devbox', aliases=('devbox', 'ip-172-31-0-139.us-west-2.compute.internal', 'i-f4d726fa'), source='awesome (aws)', container_id=None, type='VM'), Instance(name='devlab-pubsrv', address='devbox', aliases=('devbox', 'ip-172-31-0-142.us-west-2.compute.internal', 'i-f5d726fb'), source='awesome (aws)', container_id=None, type='VM'), Instance(name='devlab-game-svc', address='devbox', aliases=('devbox', 'ip-172-31-0-140.us-west-2.compute.internal', 'i-f2d726fc'), source='awesome (aws)', container_id=None, type='VM'), Instance(name='test-game-svc', address='devbox', aliases=('devbox', 'ip-172-31-0-141.us-west-2.compute.internal', 'i-f3d726fd'), source='awesome (aws)', container_id=None, type='VM'), Instance(name='test-pubsrv', address='devbox', aliases=('devbox', 'ip-172-31-2-38.us-west-2.compute.internal', 'i-0f500447384e95942'), source='awesome (aws)', container_id=None, type='VM'), Instance(name='test-pubsrv', address='devbox', aliases=('devbox', 'ip-172-31-2-39.us-west-2.compute.internal', 'i-0f500447384e95943'), source='awesome (aws)', container_id=None, type='VM') ] assert len(all_instances) == len(awesome_instances) assert set(all_instances) == set(awesome_instances) all_instances = inventorySet.instances(filter_sources='bogus') assert len(all_instances) == 0

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1

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null

0

6

e8dae38169e57058281461b6150c04aef43d8d21

1,285

py

Python

challenge-20/test_solver.py

mauricioklein/algorithm-exercises

1be95762d000102795059255a0a0d2d21d4b67fc

[ "MIT" ]

3

2019-12-03T11:40:36.000Z

2020-06-28T19:39:51.000Z

challenge-20/test_solver.py

mauricioklein/algorithm-exercises

1be95762d000102795059255a0a0d2d21d4b67fc

[ "MIT" ]

null

challenge-20/test_solver.py

mauricioklein/algorithm-exercises

1be95762d000102795059255a0a0d2d21d4b67fc

[ "MIT" ]

null

import unittest from solver import ListNode class TestSolver(unittest.TestCase): def test_solver_iteratively(self): # Create nodes nodes = [ ListNode(4), ListNode(3), ListNode(2), ListNode(1) ] # Chain the nodes for i in range(len(nodes)-1): nodes[i].next = nodes[i+1] nodes[len(nodes)-1].next = None # Reverse the list head = nodes[0] head.reverseIteratively(head) # Verify node = nodes[len(nodes)-1] for i in range(1,5): self.assertEqual(node.val, i) node = node.next def test_solver_recursively(self): # Create nodes nodes = [ ListNode(4), ListNode(3), ListNode(2), ListNode(1) ] # Chain the nodes for i in range(len(nodes)-1): nodes[i].next = nodes[i+1] nodes[len(nodes)-1].next = None # Reverse the list head = nodes[0] head.reverseRecursively(head) # Verify node = nodes[len(nodes)-1] for i in range(1,5): self.assertEqual(node.val, i) node = node.next if __name__ == "__main__": unittest.main()

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null

0

1

0

1

0

null

0

6

3358dbdb86f277d5e708f3ec2c05b724de337198

19,413

py

Python

pyvkfft/fft.py

isuruf/pyvkfft

1cb234c55b9af6b5fd85fc2082572d428819779b

[ "MIT" ]

null

pyvkfft/fft.py

isuruf/pyvkfft

1cb234c55b9af6b5fd85fc2082572d428819779b

[ "MIT" ]

null

pyvkfft/fft.py

isuruf/pyvkfft

1cb234c55b9af6b5fd85fc2082572d428819779b

[ "MIT" ]

null

# -*- coding: utf-8 -*- # PyVkFFT # (c) 2021- : ESRF-European Synchrotron Radiation Facility # authors: # Vincent Favre-Nicolin, favre@esrf.fr __all__ = ['fftn', 'ifftn', 'rfftn', 'irfftn', 'vkfft_version', 'clear_vkfftapp_cache', 'has_pycuda', 'has_opencl', 'has_cupy'] from enum import Enum from functools import lru_cache import numpy as np from .base import complex32 from .config import FFT_CACHE_NB try: from .cuda import VkFFTApp as VkFFTApp_cuda, has_pycuda, has_cupy, vkfft_version if has_pycuda: import pycuda.gpuarray as cua if has_cupy: import cupy as cp except ImportError: has_cupy, has_pycuda = False, False try: from .opencl import VkFFTApp as VkFFTApp_cl, cla, vkfft_version has_opencl = True except ImportError: has_opencl = False class Backend(Enum): """ Backend language & library""" UNKNOWN = 0 PYCUDA = 1 PYOPENCL = 2 CUPY = 3 def _prepare_transform(src, dest, cl_queue, r2c=False): """ Determine the backend from the input data. Create the destination array if necessary. :param src: the source GPU array :param dest: the destination array. If None, a new GPU array is created. :param cl_queue: the opencl queue to use, or None :param r2c: if True, this is for an R2C transform, so adapt the destination array accordingly. :return: a tuple (backend, inplace, dest, cl_queue), also appending the destination dtype for an r2c transform. """ backend = Backend.UNKNOWN if r2c: if src.dtype in [np.float16, np.float32, np.float64]: sh = list(src.shape) sh[-1] = sh[-1] // 2 + 1 dtype = np.complex64 if src.dtype == np.float16: dtype = complex32 elif src.dtype == np.float64: dtype = np.complex128 else: sh = list(src.shape) sh[-1] = (sh[-1] - 1) * 2 dtype = np.float32 if src.dtype == complex32: dtype = np.float16 elif src.dtype == np.complex128: dtype = np.float64 else: sh, dtype = None, None if has_pycuda: if isinstance(src, cua.GPUArray): backend = Backend.PYCUDA # Must cast the gpudata to int as it can either be a DeviceAllocation object # or an int (e.g. when using a view of another array) src_ptr = int(src.gpudata) if dest is None: if r2c: dest = cua.empty(tuple(sh), dtype=dtype, allocator=src.allocator) else: dest = cua.empty_like(src) dest_ptr = int(dest.gpudata) if backend == Backend.UNKNOWN and has_opencl: if isinstance(src, cla.Array): backend = Backend.PYOPENCL src_ptr = src.data.int_ptr if dest is None: if r2c: dest = cla.empty(src.queue, tuple(sh), dtype=dtype, allocator=src.allocator) else: dest = cla.empty_like(src) dest_ptr = dest.data.int_ptr if cl_queue is None: cl_queue = src.queue if backend == Backend.UNKNOWN and has_cupy: if isinstance(src, cp.ndarray): backend = Backend.CUPY src_ptr = src.__cuda_array_interface__['data'][0] if dest is None: if r2c: dest = cp.empty(tuple(sh), dtype=dtype) else: dest = cp.empty_like(src) dest_ptr = dest.__cuda_array_interface__['data'][0] if backend == Backend.UNKNOWN: raise RuntimeError("Could note determine the type of GPU array supplied, or the " "corresponding backend is not installed " "(has_pycuda=%d, has_pyopencl=%d, has_cupy=%d)" % (has_pycuda, has_opencl, has_cupy)) inplace = dest_ptr == src_ptr if r2c: if inplace: dest = src.view(dtype=dtype) return backend, inplace, dest, cl_queue, dtype else: return backend, inplace, dest, cl_queue @lru_cache(maxsize=FFT_CACHE_NB) def _get_fft_app(backend, shape, dtype, inplace, ndim, axes, norm, cuda_stream, cl_queue): if backend in [Backend.PYCUDA, Backend.CUPY]: return VkFFTApp_cuda(shape, dtype, ndim=ndim, inplace=inplace, stream=cuda_stream, norm=norm, axes=axes) elif backend == Backend.PYOPENCL: return VkFFTApp_cl(shape, dtype, cl_queue, ndim=ndim, inplace=inplace, norm=norm, axes=axes) @lru_cache(maxsize=FFT_CACHE_NB) def _get_rfft_app(backend, shape, dtype, inplace, ndim, norm, cuda_stream, cl_queue): if backend in [Backend.PYCUDA, Backend.CUPY]: return VkFFTApp_cuda(shape, dtype, ndim=ndim, inplace=inplace, stream=cuda_stream, norm=norm, r2c=True) elif backend == Backend.PYOPENCL: return VkFFTApp_cl(shape, dtype, cl_queue, ndim=ndim, inplace=inplace, norm=norm, r2c=True) @lru_cache(maxsize=FFT_CACHE_NB) def _get_dct_app(backend, shape, dtype, inplace, ndim, norm, dct_type, cuda_stream, cl_queue): if backend in [Backend.PYCUDA, Backend.CUPY]: return VkFFTApp_cuda(shape, dtype, ndim=ndim, inplace=inplace, stream=cuda_stream, norm=norm, dct=dct_type) elif backend == Backend.PYOPENCL: return VkFFTApp_cl(shape, dtype, cl_queue, ndim=ndim, inplace=inplace, norm=norm, dct=dct_type) def fftn(src, dest=None, ndim=None, norm=1, axes=None, cuda_stream=None, cl_queue=None, return_scale=False): """ Perform a FFT on a GPU array, automatically creating the VkFFTApp and caching it for future re-use. :param src: the source pycuda.gpuarray.GPUArray or cupy.ndarray :param dest: the destination GPU array. If None, a new GPU array will be created and returned (using the source array allocator (pycuda, pyopencl) if available). If dest is the same array as src, an inplace transform is done. :param ndim: the number of dimensions (<=3) to use for the FFT. By default, uses the array dimensions. Can be smaller, e.g. ndim=2 for a 3D array to perform a batched 3D FFT on all the layers. The FFT is always performed along the last axes if the array's number of dimension is larger than ndim, i.e. on the x-axis for ndim=1, on the x and y axes for ndim=2. :param norm: if 0 (un-normalised), every transform multiplies the L2 norm of the array by the transform size. if 1 (the default) or "backward", the inverse transform divides the L2 norm by the array size, so FFT+iFFT will keep the array norm. if "ortho", each transform will keep the L2 norm, but that will involve an extra read & write operation. :param axes: a list or tuple of axes along which the transform is made. if None, the transform is done along the ndim fastest axes, or all axes if ndim is None. Not allowed for R2C transforms :param cuda_stream: the pycuda.driver.Stream or cupy.cuda.Stream to use for the transform. If None, the default one will be used :param cl_queue: the pyopencl.CommandQueue to be used. If None, the source array default queue will be used :param return_scale: if True, return the scale factor by which the result must be multiplied to keep its L2 norm after the transform :return: the destination array if return_scale is False, or (dest, scale) """ backend, inplace, dest, cl_queue = _prepare_transform(src, dest, cl_queue, False) app = _get_fft_app(backend, src.shape, src.dtype, inplace, ndim, axes, norm, cuda_stream, cl_queue) app.fft(src, dest) if return_scale: s = app.get_fft_scale() return dest, s return dest def ifftn(src, dest=None, ndim=None, norm=1, axes=None, cuda_stream=None, cl_queue=None, return_scale=False): """ Perform an inverse FFT on a GPU array, automatically creating the VkFFTApp and caching it for future re-use. :param src: the source pycuda.gpuarray.GPUArray or cupy.ndarray :param dest: the destination GPU array. If None, a new GPU array will be created and returned (using the source array allocator (pycuda, pyopencl) if available). If dest is the same array as src, an inplace transform is done. :param ndim: the number of dimensions (<=3) to use for the FFT. By default, uses the array dimensions. Can be smaller, e.g. ndim=2 for a 3D array to perform a batched 3D FFT on all the layers. The FFT is always performed along the last axes if the array's number of dimension is larger than ndim, i.e. on the x-axis for ndim=1, on the x and y axes for ndim=2. :param norm: if 0 (un-normalised), every transform multiplies the L2 norm of the array by the transform size. if 1 (the default) or "backward", the inverse transform divides the L2 norm by the array size, so FFT+iFFT will keep the array norm. if "ortho", each transform will keep the L2 norm, but that will involve an extra read & write operation. :param axes: a list or tuple of axes along which the transform is made. if None, the transform is done along the ndim fastest axes, or all axes if ndim is None. Not allowed for R2C transforms :param cuda_stream: the pycuda.driver.Stream or cupy.cuda.Stream to use for the transform. If None, the default one will be used :param cl_queue: the pyopencl.CommandQueue to be used. If None, the source array default queue will be used :param return_scale: if True, return the scale factor by which the result must be multiplied to keep its L2 norm after the transform :return: the destination array if return_scale is False, or (dest, scale) """ backend, inplace, dest, cl_queue = _prepare_transform(src, dest, cl_queue, False) app = _get_fft_app(backend, src.shape, src.dtype, inplace, ndim, axes, norm, cuda_stream, cl_queue) app.ifft(src, dest) if return_scale: s = app.get_fft_scale() return dest, s return dest def rfftn(src, dest=None, ndim=None, norm=1, cuda_stream=None, cl_queue=None, return_scale=False): """ Perform a real->complex transform on a GPU array, automatically creating the VkFFTApp and caching it for future re-use. For an out-of-place transform, the length of the destination last axis will be src.shape[-1]//2+1. For an in-place transform, if the src array has a shape (..., nx+2), the last two values along the last (X) axis are ignored, and the destination array will have a shape of (..., nx//2+1). :param src: the source pycuda.gpuarray.GPUArray or cupy.ndarray :param dest: the destination GPU array. If None, a new GPU array will be created and returned (using the source array allocator (pycuda, pyopencl) if available). If dest is the same array as src, an inplace transform is done. :param ndim: the number of dimensions (<=3) to use for the FFT. By default, uses the array dimensions. Can be smaller, e.g. ndim=2 for a 3D array to perform a batched 3D FFT on all the layers. The FFT is always performed along the last axes if the array's number of dimension is larger than ndim, i.e. on the x-axis for ndim=1, on the x and y axes for ndim=2. :param norm: if 0 (un-normalised), every transform multiplies the L2 norm of the array by the transform size. if 1 (the default) or "backward", the inverse transform divides the L2 norm by the array size, so FFT+iFFT will keep the array norm. if "ortho", each transform will keep the L2 norm, but that will involve an extra read & write operation. :param cuda_stream: the pycuda.driver.Stream or cupy.cuda.Stream to use for the transform. If None, the default one will be used :param cl_queue: the pyopencl.CommandQueue to be used. If None, the source array default queue will be used :param return_scale: if True, return the scale factor by which the result must be multiplied to keep its L2 norm after the transform :return: the destination array if return_scale is False, or (dest, scale). For an in-place transform, the returned value is a view of the array with the appropriate type. """ backend, inplace, dest, cl_queue, dtype = _prepare_transform(src, dest, cl_queue, True) app = _get_rfft_app(backend, src.shape, src.dtype, inplace, ndim, norm, cuda_stream, cl_queue) app.fft(src, dest) if return_scale: s = app.get_fft_scale() return dest.view(dtype=dtype), s return dest.view(dtype=dtype) def irfftn(src, dest=None, ndim=None, norm=1, cuda_stream=None, cl_queue=None, return_scale=False): """ Perform a complex->real transform on a GPU array, automatically creating the VkFFTApp and caching it for future re-use. For an out-of-place transform, the length of the destination last axis will be (src.shape[-1]-1)*2. For an in-place transform, if the src array has a shape (..., nx), the destination array will have a shape of (..., nx*2) but the last two vales along the last axis are used as buffer. :param src: the source pycuda.gpuarray.GPUArray or cupy.ndarray :param dest: the destination GPU array. If None, a new GPU array will be created and returned (using the source array allocator (pycuda, pyopencl) if available). If dest is the same array as src, an inplace transform is done. :param ndim: the number of dimensions (<=3) to use for the FFT. By default, uses the array dimensions. Can be smaller, e.g. ndim=2 for a 3D array to perform a batched 3D FFT on all the layers. The FFT is always performed along the last axes if the array's number of dimension is larger than ndim, i.e. on the x-axis for ndim=1, on the x and y axes for ndim=2. :param norm: if 0 (un-normalised), every transform multiplies the L2 norm of the array by the transform size. if 1 (the default) or "backward", the inverse transform divides the L2 norm by the array size, so FFT+iFFT will keep the array norm. if "ortho", each transform will keep the L2 norm, but that will involve an extra read & write operation. :param cuda_stream: the pycuda.driver.Stream or cupy.cuda.Stream to use for the transform. If None, the default one will be used :param cl_queue: the pyopencl.CommandQueue to be used. If None, the source array default queue will be used :param return_scale: if True, return the scale factor by which the result must be multiplied to keep its L2 norm after the transform :return: the destination array if return_scale is False, or (dest, scale) For an in-place transform, the returned value is a view of the array with the appropriate type. """ backend, inplace, dest, cl_queue, dtype = _prepare_transform(src, dest, cl_queue, True) app = _get_rfft_app(backend, dest.shape, dest.dtype, inplace, ndim, norm, cuda_stream, cl_queue) app.ifft(src, dest) if return_scale: s = app.get_fft_scale() return dest.view(dtype=dtype), s return dest.view(dtype=dtype) def dctn(src, dest=None, ndim=None, norm=1, dct_type=2, cuda_stream=None, cl_queue=None): """ Perform a real->real Direct Cosine Transform on a GPU array, automatically creating the VkFFTApp and caching it for future re-use. :param src: the source pycuda.gpuarray.GPUArray or cupy.ndarray :param dest: the destination GPU array. If None, a new GPU array will be created and returned (using the source array allocator (pycuda, pyopencl) if available). If dest is the same array as src, an inplace transform is done. :param ndim: the number of dimensions (<=3) to use for the FFT. By default, uses the array dimensions. Can be smaller, e.g. ndim=2 for a 3D array to perform a batched 3D FFT on all the layers. The FFT is always performed along the last axes if the array's number of dimension is larger than ndim, i.e. on the x-axis for ndim=1, on the x and y axes for ndim=2. :param norm: normalisation mode, either 0 (un-normalised) or 1 (the default, also available as "backward) which will normalise the inverse transform, so DCT+iDCT will keep the array norm. :param dct_type: the type of dct desired: 1, 2 (default), 3 or 4 :param cuda_stream: the pycuda.driver.Stream or cupy.cuda.Stream to use for the transform. If None, the default one will be used :param cl_queue: the pyopencl.CommandQueue to be used. If None, the source array default queue will be used :return: the destination array. """ backend, inplace, dest, cl_queue = _prepare_transform(src, dest, cl_queue, False) app = _get_dct_app(backend, src.shape, src.dtype, inplace, ndim, norm, dct_type, cuda_stream, cl_queue) app.fft(src, dest) return dest def idctn(src, dest=None, ndim=None, norm=1, dct_type=2, cuda_stream=None, cl_queue=None): """ Perform a real->real inverse Direct Cosine Transform on a GPU array, automatically creating the VkFFTApp and caching it for future re-use. :param src: the source pycuda.gpuarray.GPUArray or cupy.ndarray :param dest: the destination GPU array. If None, a new GPU array will be created and returned (using the source array allocator (pycuda, pyopencl) if available). If dest is the same array as src, an inplace transform is done. :param ndim: the number of dimensions (<=3) to use for the FFT. By default, uses the array dimensions. Can be smaller, e.g. ndim=2 for a 3D array to perform a batched 3D FFT on all the layers. The FFT is always performed along the last axes if the array's number of dimension is larger than ndim, i.e. on the x-axis for ndim=1, on the x and y axes for ndim=2. :param norm: normalisation mode, either 0 (un-normalised) or 1 (the default, also available as "backward) which will normalise the inverse transform, so DCT+iDCT will keep the array norm. :param dct_type: the type of dct desired: 2 (default), 3 or 4 :param cuda_stream: the pycuda.driver.Stream or cupy.cuda.Stream to use for the transform. If None, the default one will be used :param cl_queue: the pyopencl.CommandQueue to be used. If None, the source array default queue will be used :return: the destination array. """ backend, inplace, dest, cl_queue = _prepare_transform(src, dest, cl_queue, False) app = _get_dct_app(backend, src.shape, src.dtype, inplace, ndim, norm, dct_type, cuda_stream, cl_queue) app.ifft(src, dest) return dest def clear_vkfftapp_cache(): """ Remove all cached VkFFTApp""" _get_fft_app.cache_clear() _get_rfft_app.cache_clear()

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null

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null

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335f058bccdc187671e284b665d0a36b6d5cf372

8,060

py

Python

models/normalization.py

pkulwj1994/AdversarialConsistentScoreMatching

f439f242f004ce06382ed72f2aa7daf9c262abfa

[ "MIT" ]

119

2020-09-09T13:59:28.000Z

2022-03-17T17:04:10.000Z

models/normalization.py

pkulwj1994/AdversarialConsistentScoreMatching

f439f242f004ce06382ed72f2aa7daf9c262abfa

[ "MIT" ]

2

2020-11-13T03:26:22.000Z

2021-03-19T23:04:33.000Z

models/normalization.py

pkulwj1994/AdversarialConsistentScoreMatching

f439f242f004ce06382ed72f2aa7daf9c262abfa

[ "MIT" ]

19

2020-09-14T05:56:51.000Z

2021-12-28T15:53:34.000Z

import torch import torch.nn as nn def get_normalization(m_config, conditional=True): norm = m_config.normalization if conditional: if norm == 'NoneNorm': return ConditionalNoneNorm2d elif norm == 'InstanceNorm++': return ConditionalInstanceNorm2dPlus elif norm == 'InstanceNorm': return ConditionalInstanceNorm2d elif norm == 'BatchNorm': return ConditionalBatchNorm2d elif norm == 'VarianceNorm': return ConditionalVarianceNorm2d else: raise NotImplementedError("{} does not exist!".format(norm)) else: if norm == 'BatchNorm': return nn.BatchNorm2d elif norm == 'InstanceNorm': return nn.InstanceNorm2d elif norm == 'InstanceNorm++': return InstanceNorm2dPlus elif norm == 'VarianceNorm': return VarianceNorm2d elif norm == 'NoneNorm': return NoneNorm2d elif norm is None: return None else: raise NotImplementedError("{} does not exist!".format(norm)) class ConditionalBatchNorm2d(nn.Module): def __init__(self, num_features, num_classes, bias=True): super().__init__() self.num_features = num_features self.bias = bias self.bn = nn.BatchNorm2d(num_features, affine=False) if self.bias: self.embed = nn.Embedding(num_classes, num_features * 2) self.embed.weight.data[:, :num_features].uniform_() # Initialise scale at N(1, 0.02) self.embed.weight.data[:, num_features:].zero_() # Initialise bias at 0 else: self.embed = nn.Embedding(num_classes, num_features) self.embed.weight.data.uniform_() def forward(self, x, y): out = self.bn(x) if self.bias: gamma, beta = self.embed(y).chunk(2, dim=1) out = gamma.view(-1, self.num_features, 1, 1) * out + beta.view(-1, self.num_features, 1, 1) else: gamma = self.embed(y) out = gamma.view(-1, self.num_features, 1, 1) * out return out class ConditionalInstanceNorm2d(nn.Module): def __init__(self, num_features, num_classes, bias=True): super().__init__() self.num_features = num_features self.bias = bias self.instance_norm = nn.InstanceNorm2d(num_features, affine=False, track_running_stats=False) if bias: self.embed = nn.Embedding(num_classes, num_features * 2) self.embed.weight.data[:, :num_features].uniform_() # Initialise scale at N(1, 0.02) self.embed.weight.data[:, num_features:].zero_() # Initialise bias at 0 else: self.embed = nn.Embedding(num_classes, num_features) self.embed.weight.data.uniform_() def forward(self, x, y): h = self.instance_norm(x) if self.bias: gamma, beta = self.embed(y).chunk(2, dim=-1) out = gamma.view(-1, self.num_features, 1, 1) * h + beta.view(-1, self.num_features, 1, 1) else: gamma = self.embed(y) out = gamma.view(-1, self.num_features, 1, 1) * h return out class ConditionalVarianceNorm2d(nn.Module): def __init__(self, num_features, num_classes, bias=False): super().__init__() self.num_features = num_features self.bias = bias self.embed = nn.Embedding(num_classes, num_features) self.embed.weight.data.normal_(1, 0.02) def forward(self, x, y): f_vars = torch.var(x, dim=(2, 3), keepdim=True) h = x / torch.sqrt(f_vars + 1e-5) gamma = self.embed(y) out = gamma.view(-1, self.num_features, 1, 1) * h return out class VarianceNorm2d(nn.Module): def __init__(self, num_features, bias=False): super().__init__() self.num_features = num_features self.bias = bias self.alpha = nn.Parameter(torch.zeros(num_features)) self.alpha.data.normal_(1, 0.02) def forward(self, x): f_vars = torch.var(x, dim=(2, 3), keepdim=True) h = x / torch.sqrt(f_vars + 1e-5) out = self.alpha.view(-1, self.num_features, 1, 1) * h return out class ConditionalNoneNorm2d(nn.Module): def __init__(self, num_features, num_classes, bias=True): super().__init__() self.num_features = num_features self.bias = bias if bias: self.embed = nn.Embedding(num_classes, num_features * 2) self.embed.weight.data[:, :num_features].uniform_() # Initialise scale at N(1, 0.02) self.embed.weight.data[:, num_features:].zero_() # Initialise bias at 0 else: self.embed = nn.Embedding(num_classes, num_features) self.embed.weight.data.uniform_() def forward(self, x, y): if self.bias: gamma, beta = self.embed(y).chunk(2, dim=-1) out = gamma.view(-1, self.num_features, 1, 1) * x + beta.view(-1, self.num_features, 1, 1) else: gamma = self.embed(y) out = gamma.view(-1, self.num_features, 1, 1) * x return out # noinspection PyUnusedLocal class NoneNorm2d(nn.Module): def __init__(self, num_features, bias=True): super().__init__() @staticmethod def forward(x): return x class InstanceNorm2dPlus(nn.Module): def __init__(self, num_features, bias=True): super().__init__() self.num_features = num_features self.bias = bias self.instance_norm = nn.InstanceNorm2d(num_features, affine=False, track_running_stats=False) self.alpha = nn.Parameter(torch.zeros(num_features)) self.gamma = nn.Parameter(torch.zeros(num_features)) self.alpha.data.normal_(1, 0.02) self.gamma.data.normal_(1, 0.02) if bias: self.beta = nn.Parameter(torch.zeros(num_features)) def forward(self, x): means = torch.mean(x, dim=(2, 3)) m = torch.mean(means, dim=-1, keepdim=True) v = torch.var(means, dim=-1, keepdim=True) means = (means - m) / (torch.sqrt(v + 1e-5)) h = self.instance_norm(x) if self.bias: h = h + means[..., None, None] * self.alpha[..., None, None] out = self.gamma.view(-1, self.num_features, 1, 1) * h + self.beta.view(-1, self.num_features, 1, 1) else: h = h + means[..., None, None] * self.alpha[..., None, None] out = self.gamma.view(-1, self.num_features, 1, 1) * h return out class ConditionalInstanceNorm2dPlus(nn.Module): def __init__(self, num_features, num_classes, bias=True): super().__init__() self.num_features = num_features self.bias = bias self.instance_norm = nn.InstanceNorm2d(num_features, affine=False, track_running_stats=False) if bias: self.embed = nn.Embedding(num_classes, num_features * 3) self.embed.weight.data[:, :2 * num_features].normal_(1, 0.02) # Initialise scale at N(1, 0.02) self.embed.weight.data[:, 2 * num_features:].zero_() # Initialise bias at 0 else: self.embed = nn.Embedding(num_classes, 2 * num_features) self.embed.weight.data.normal_(1, 0.02) def forward(self, x, y): means = torch.mean(x, dim=(2, 3)) m = torch.mean(means, dim=-1, keepdim=True) v = torch.var(means, dim=-1, keepdim=True) means = (means - m) / (torch.sqrt(v + 1e-5)) h = self.instance_norm(x) if self.bias: gamma, alpha, beta = self.embed(y).chunk(3, dim=-1) h = h + means[..., None, None] * alpha[..., None, None] out = gamma.view(-1, self.num_features, 1, 1) * h + beta.view(-1, self.num_features, 1, 1) else: gamma, alpha = self.embed(y).chunk(2, dim=-1) h = h + means[..., None, None] * alpha[..., None, None] out = gamma.view(-1, self.num_features, 1, 1) * h return out

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null

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6

6856c6f0caf7be2b8f762fcf7db6f96ea6b3e2c0

22

py

Python

HangmanGame/views/__init__.py

github-675455/JogoDaForca

66b3aaae97c64c116f12d3a98c53bf0fc383bd63

[ "MIT" ]

null

HangmanGame/views/__init__.py

github-675455/JogoDaForca

66b3aaae97c64c116f12d3a98c53bf0fc383bd63

[ "MIT" ]

2

2018-08-29T03:34:02.000Z

2018-08-29T18:25:44.000Z

HangmanGame/views/__init__.py

github-675455/JogoDaForca

66b3aaae97c64c116f12d3a98c53bf0fc383bd63

[ "MIT" ]

null

from .Jogo import Jogo

22

0.818182

4

22

4.5

0.75

0

0.136364

22

1

22

0.947368

0

1

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1

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1

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null

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1

0

null

0

1

0

1

0

1

0

6

685ee02fbc19ee5a6b9d35f61855a706b51d9f2d

26

py

Python

hello_world.py

LarsPalmas/profile-rest-api2

5858a9342f762df01e5610fe090f8d27b8742d27

[ "MIT" ]

null

hello_world.py

LarsPalmas/profile-rest-api2

5858a9342f762df01e5610fe090f8d27b8742d27

[ "MIT" ]

8

2019-12-05T01:07:32.000Z

2022-02-10T11:52:03.000Z

hello_world.py

LarsPalmas/profile-rest-api2

5858a9342f762df01e5610fe090f8d27b8742d27

[ "MIT" ]

null

print("Hello World Eini!")

26

0.730769

4

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1

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1

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0.791667

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0.62963

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null

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0

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0

null

0

1

0

1

0

6

d79d48e6c1049bad0901797b24f08f246811fd3d

22

py

Python

src/psweep/__init__.py

elcorto/psweep

b1d372ba19f1d98744e04a1576211d51123272b1

[ "BSD-3-Clause" ]

6

2020-03-24T07:24:37.000Z

2021-07-29T07:18:59.000Z

src/psweep/__init__.py

elcorto/psweep

b1d372ba19f1d98744e04a1576211d51123272b1

[ "BSD-3-Clause" ]

2

2019-08-20T22:14:18.000Z

2022-03-11T09:16:59.000Z

src/psweep/__init__.py

elcorto/psweep

b1d372ba19f1d98744e04a1576211d51123272b1

[ "BSD-3-Clause" ]

1

2020-02-22T12:13:13.000Z

from .psweep import *

11

21

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3

22

5.333333

1

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0.181818

22

1

22

0.888889

0

1

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1

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1

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6

d7c4761da5e86d99296e44d4e2925878310fd719

98

py

Python

fornax/stages/prepare_environment/__init__.py

lwencel-priv/fornax

0f66a6284975bc5a2cfc3d38bc01ef6ad492e40e

[ "MIT" ]

null

fornax/stages/prepare_environment/__init__.py

lwencel-priv/fornax

0f66a6284975bc5a2cfc3d38bc01ef6ad492e40e

[ "MIT" ]

null

fornax/stages/prepare_environment/__init__.py

lwencel-priv/fornax

0f66a6284975bc5a2cfc3d38bc01ef6ad492e40e

[ "MIT" ]

null

"""Prepare environment stage package.""" from .prepare_environment import PrepareEnvironmentStage

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0

1

0

1

0

6

d7caadf0e5af43670a31ca342530fd496e1683fe

33

py

Python

painterAssistant/__init__.py

bartoszpogoda/academic-py-painter-assistant

2a2dff55e1d7b631f28d6492c5553a8e7ac5abc2

[ "MIT" ]

null

painterAssistant/__init__.py

bartoszpogoda/academic-py-painter-assistant

2a2dff55e1d7b631f28d6492c5553a8e7ac5abc2

[ "MIT" ]

null

painterAssistant/__init__.py

bartoszpogoda/academic-py-painter-assistant

2a2dff55e1d7b631f28d6492c5553a8e7ac5abc2

[ "MIT" ]

null

from . import paintCanCalculator

16.5

32

0.848485

3

33

9.333333

1

0

0.121212

33

1

33

0.965517

0

1

0

true

0

1

0

1

0

1

0

null

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0

null

0

1

0

1

0

1

0

6

d7f6d6b2a64adc2158779c58c330914da6b59f15

49

py

Python

microservices/svc/multiplier/handler/__init__.py

sato-mh/distributed-calculator

8d044084a0f70effe5264f3a726962e3ac8da7f5

[ "MIT" ]

null

microservices/svc/multiplier/handler/__init__.py

sato-mh/distributed-calculator

8d044084a0f70effe5264f3a726962e3ac8da7f5

[ "MIT" ]

null

microservices/svc/multiplier/handler/__init__.py

sato-mh/distributed-calculator

8d044084a0f70effe5264f3a726962e3ac8da7f5

[ "MIT" ]

null

from .multiplier import Multiplier # noqa: F401

24.5

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6

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6.333333

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0

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1

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1

0

6

cc19738fd831e6d3270cbd9b45609bcd503d9767

27

py

Python

scripts/post_process/__init__.py

AndAgio/Shallow2Deep

e42e9b3b11fdd2ec035144890a88e93a5154276f

[ "Apache-2.0" ]

null

scripts/post_process/__init__.py

AndAgio/Shallow2Deep

e42e9b3b11fdd2ec035144890a88e93a5154276f

[ "Apache-2.0" ]

2

2021-02-17T12:07:45.000Z

2021-02-17T12:16:21.000Z

scripts/post_process/__init__.py

AndAgio/Shallow2Deep

e42e9b3b11fdd2ec035144890a88e93a5154276f

[ "Apache-2.0" ]

null

from .process_log import *

13.5

26

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1

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1

0

1

0

6

cc2ea080861f80c4ae8ef63134f969e8e9f1745c

53,566

py

Python

__init__.py

SAM-tak/gen_rigidbodies

4cd8f81270dfc03e7705ace6912890ac00a0745a

[ "MIT" ]

7

2020-01-14T22:22:04.000Z

2022-01-30T06:00:39.000Z

__init__.py

SAM-tak/gen_rigidbodies

4cd8f81270dfc03e7705ace6912890ac00a0745a

[ "MIT" ]

null

__init__.py

SAM-tak/gen_rigidbodies

4cd8f81270dfc03e7705ace6912890ac00a0745a

[ "MIT" ]

null

import bpy from bpy.props import * import mathutils import math bl_info = { "name": "Generate rigid bodies from bone", "author": "SAM-tak, 12funkeys", "version": (1, 0, 0), "blender": (2, 80, 0), "location": "pose > Gen Rigid Bodies", "description": "Set rigid bodies and constraints easily", "warning": "", "support": "COMMUNITY", "wiki_url": "https://github.com/SAM-tak/gen_rigidbodies/wiki", "tracker_url": "https://github.com/SAM-tak/gen_rigidbodies", "category": "Rigging" } translation_dict = { "en_US" : { ("*", "Make Rigid Body Tools") : "Make Rigid Body Tools", ("*", "Gen Rigid Bodies") : "Gen Rigid Bodies", ("*", "Make Rigid Bodies") : "Make Rigid Bodies", ("*", "Add Passives") : "Add Passives", ("*", "Make passive rigid bodies aligned to selected bones") : "Make passive rigid bodies aligned to selected bones", ("*", "Add Actives") : "Add Actives", ("*", "Make active rigid bodies aligned to selected bones") : "Make active rigid bodies aligned to selected bones", ("*", "Add Joints") : "Add Joints", ("*", "Add Actives & Joints") : "Add Actives & Joints" }, "ja_JP" : { ("*", "Make Rigid Bodies Tools") : "選択ボーン", ("*", "Gen Rigid Bodies") : "剛体ツール", ("*", "Make Rigid Bodies") : "選択ボーン", ("*", "Add Passives") : "基礎剛体の作成‐ボーン追従", ("*", "Make passive rigid bodies aligned to selected bones") : "ボーンに追従する静的剛体を作成します", ("*", "Add Actives") : "基礎剛体の作成‐物理演算", ("*", "Make active rigid bodies aligned to selected bones") : "ボーンに追従する動的剛体を作成します", ("*", "Add Joints") : "基礎Jointの作成", ("*", "Add Actives & Joints") : "基礎剛体／連結Jointの作成" } } shapes = [ ('MESH', 'Mesh', 'Mesh'), ('CONVEX_HULL', 'Convex Hull', 'Convex Hull'), ('CONE', 'Cone', 'Cone'), ('CYLINDER', 'Cylinder', 'Cylinder'), ('CAPSULE', 'Capsule', 'Capsule'), ('SPHERE', 'Sphere', 'Sphere'), ('BOX', 'Box', 'Box') ] types = [ ('MOTOR', 'Motor', 'Motor'), ('GENERIC_SPRING', 'Generic Spring', 'Generic Spring'), ('GENERIC', 'Generic', 'Generic') ] ### Menus class PoseMenu(bpy.types.Menu): bl_idname = "GENRIGIDBODIES_MT_PoseSubMenuRoot" bl_label = "Gen Rigid Bodies" bl_description = "Make rigid bodies & constraint" def draw(self, context): self.layout.operator(AddPassiveOperator.bl_idname, icon='BONE_DATA') self.layout.operator(AddActiveOperator.bl_idname, icon='PHYSICS') self.layout.operator(AddJointOperator.bl_idname, icon='CONSTRAINT') self.layout.operator(AddActiveNJointOperator.bl_idname, icon='MOD_PHYSICS') @staticmethod def menu_fn(menu, context): menu.layout.separator() menu.layout.menu(PoseMenu.bl_idname, icon='MESH_ICOSPHERE') @classmethod def register(cls): bpy.app.translations.register(__name__, translation_dict) bpy.types.VIEW3D_MT_pose.append(cls.menu_fn) @classmethod def unregister(cls): bpy.types.VIEW3D_MT_pose.remove(cls.menu_fn) bpy.app.translations.unregister(__name__) class ObjectMenu(bpy.types.Menu): bl_idname = "GENRIGIDBODIES_MT_ObjectSubMenuRoot" bl_label = "Gen Rigid Bodies" bl_description = "Gen Rigid Bodies Utility" def draw(self, context): self.layout.operator(ReparentOrphanTrackObjectOperator.bl_idname) self.layout.operator(ForceCorrespondNameRBAndTrackObjectOperator.bl_idname) self.layout.operator(ConnectOperator.bl_idname, icon='MESH_ICOSPHERE') @staticmethod def menu_fn(menu, context): menu.layout.separator() menu.layout.menu(ObjectMenu.bl_idname) @classmethod def register(cls): bpy.types.VIEW3D_MT_object.append(cls.menu_fn) @classmethod def unregister(cls): bpy.types.VIEW3D_MT_object.remove(cls.menu_fn) ### user prop class UProp: rb_shape = EnumProperty( name='Shape', description='Choose Rigid Body Shape', items=shapes, #items=bpy.types.RigidBodyObject.collision_shape, #update=update_shape, default='CAPSULE' ) rb_dim = FloatVectorProperty( name = "Dimensions", description = "rigid body Dimensions XYZ", default = (1, 1, 1), subtype = 'XYZ', unit = 'NONE', min = 0, max = 5 ) rb_radius = FloatProperty( name = "Radius", description = "rigid body Collision Radius", default = 0.3, subtype = 'NONE', min = 0, max = 5 ) rb_length = FloatProperty( name = "Height", description = "rigid body Collision length", default = 1.0, subtype = 'NONE', min = 0, max = 5 ) rb_inset_capsule = BoolProperty( name='Inset Capsule', description='If shape type is capsule, decrement a length by radius to inscribe', default=False ) rb_mass = FloatProperty( name = "Mass", description = "rigid body mass", default = 1.0, subtype = 'NONE', min = 0.001 ) rb_friction = FloatProperty( name = "Friction", description = "rigid body friction", default = 0.5, subtype = 'NONE', min = 0, max = 1 ) rb_bounciness = FloatProperty( name = "Bounciness", description = "rigid body bounciness", default = 0.5, subtype = 'NONE', min = 0, max = 1 ) rb_translation = FloatProperty( name = "Translation", description = "rigid body translation", default = 0.5, subtype = 'NONE', min = 0, max = 1 ) rb_rotation = FloatProperty( name = "Rotation", description = "rigid body rotation", default = 0.5, subtype = 'NONE', min = 0, max = 1 ) rb_rootbody_passive = BoolProperty( name='Passive', description='Rigid Body Type Passive', default=True ) rb_add_pole_rootbody = BoolProperty( name='Add Pole Object', description='Add Pole Object', default=False ) rb_pole_rootbody_dim = FloatVectorProperty( name = "Pole Object Dimension", description = "Pole Object Dimension XYZ", default = (0.33, 0.33, 0.33), subtype = 'XYZ', unit = 'NONE', min = 0, max = 5 ) rb_rootbody_animated = BoolProperty( name='animated', description='Root Rigid Body sets animated', default=True ) jo_type = EnumProperty( name='Type', description='Choose Contstraint Type', items=types, default='GENERIC_SPRING' ) jo_size = FloatProperty( name = "joint Size", description = "joint Size", default = 0.33, subtype = 'NONE', min = 0.001, max = 1 ) jo_limit_lin_x = BoolProperty( name='X Axis', description='limit x', default=True, options={'ANIMATABLE'} ) jo_limit_lin_y = BoolProperty( name='Y Axis', description='limit y', default=True ) jo_limit_lin_z = BoolProperty( name='Z Axis', description='limit z', default=True ) jo_limit_lin_x_lower = FloatProperty( name = "Lower", description = "joint limit_lin_x_lower", default = 0, subtype = 'NONE' ) jo_limit_lin_y_lower = FloatProperty( name = "Lower", description = "joint limit_lin_y_lower", default = 0, subtype = 'NONE' ) jo_limit_lin_z_lower = FloatProperty( name = "Lower", description = "joint limit_lin_z_lower", default = 0, subtype = 'NONE' ) jo_limit_lin_x_upper = FloatProperty( name = "Upper", description = "joint limit_lin_x_upper", default = 0, subtype = 'NONE' ) jo_limit_lin_y_upper = FloatProperty( name = "Upper", description = "joint limit_lin_y_upper", default = 0, subtype = 'NONE' ) jo_limit_lin_z_upper = FloatProperty( name = "Upper", description = "joint limit_lin_z_upper", default = 0, subtype = 'NONE' ) jo_limit_ang_x = BoolProperty( name='X Angle', description='Angle limit x', default=True, options={'ANIMATABLE'} ) jo_limit_ang_y = BoolProperty( name='Y Angle', description='Angle limit y', default=True ) jo_limit_ang_z = BoolProperty( name='Z Angle', description='Angle limit z', default=True ) jo_limit_ang_x_lower = FloatProperty( name = "Lower", description = "joint limit_ang_x_lower", default = -0.785398, subtype = 'ANGLE' ) jo_limit_ang_y_lower = FloatProperty( name = "Lower", description = "joint limit_ang_y_lower", default = -0.785398, subtype = 'ANGLE' ) jo_limit_ang_z_lower = FloatProperty( name = "Lower", description = "joint limit_ang_z_lower", default = -0.785398, subtype = 'ANGLE' ) jo_limit_ang_x_upper = FloatProperty( name = "Upper", description = "joint limit_ang_x_upper", default = 0.785398, subtype = 'ANGLE' ) jo_limit_ang_y_upper = FloatProperty( name = "Upper", description = "joint limit_ang_y_upper", default = 0.785398, subtype = 'ANGLE' ) jo_limit_ang_z_upper = FloatProperty( name = "Upper", description = "joint limit_ang_z_upper", default = 0.785398, subtype = 'ANGLE' ) jo_use_spring_x = BoolProperty( name='X', description='use spring x', default=False ) jo_use_spring_y = BoolProperty( name='Y', description='use spring y', default=False ) jo_use_spring_z = BoolProperty( name='Z', description='use spring z', default=False ) jo_spring_stiffness_x = FloatProperty( name = "Stiffness", description = "Stiffness on the X Axis", default = 10.000, subtype = 'NONE', min = 0 ) jo_spring_stiffness_y = FloatProperty( name = "Stiffness", description = "Stiffness on the Y Axis", default = 10.000, subtype = 'NONE', min = 0 ) jo_spring_stiffness_z = FloatProperty( name = "Stiffness", description = "Stiffness on the Z Axis", default = 10.000, subtype = 'NONE', min = 0 ) jo_spring_damping_x = FloatProperty( name = "Damping X", description = "Damping on the X Axis", default = 0.5, subtype = 'NONE', min = 0, max = 1 ) jo_spring_damping_y = FloatProperty( name = "Damping Y", description = "Damping on the Y Axis", default = 0.5, subtype = 'NONE', min = 0, max = 1 ) jo_spring_damping_z = FloatProperty( name = "Damping Z", description = "Damping on the Z Axis", default = 0.5, subtype = 'NONE', min = 0, max = 1 ) jo_align_bone = BoolProperty( name='Align Joint To Bone', description='Set same rotation of bone to joint object', default=True ) ### Create Rigid Bodies On Bones class AddPassiveOperator(bpy.types.Operator): bl_idname = "genrigidbodies.addpassivejoint" bl_label = "Add Passives" bl_description = "Make passive rigid bodies aligned to selected bones" bl_options = {'REGISTER', 'UNDO'} ###instance UProp.rigidbody p_rb_shape : UProp.rb_shape p_rb_dim : UProp.rb_dim p_rb_radius : UProp.rb_radius p_rb_length : UProp.rb_length p_rb_inset_capsule : UProp.rb_inset_capsule p_rb_mass : UProp.rb_mass p_rb_friction : UProp.rb_friction p_rb_bounciness : UProp.rb_bounciness p_rb_translation : UProp.rb_translation p_rb_rotation : UProp.rb_rotation p_rb_rootbody_passive : UProp.rb_rootbody_passive p_rb_rootbody_animated : UProp.rb_rootbody_animated def draw(self, context): box = self.layout.box() box.prop(self, 'p_rb_shape') if self.p_rb_shape in ('CONE', 'CYLINDER', 'CAPSULE', 'SPHERE'): box.prop(self, 'p_rb_radius') box.prop(self, 'p_rb_length') if self.p_rb_shape == 'CAPSULE': box.prop(self, 'p_rb_inset_capsule') else: box.prop(self, 'p_rb_dim') box.prop(self, 'p_rb_mass') box.prop(self, 'p_rb_friction') box.prop(self, 'p_rb_bounciness') box.label(text="Damping:") box.prop(self, 'p_rb_translation') box.prop(self, 'p_rb_rotation') box.prop(self, 'p_rb_rootbody_passive') box.prop(self, 'p_rb_rootbody_animated') def execute(self, context): ###selected Armature ob = context.active_object #self.report({'INFO'}, ob.data) if len(context.selected_pose_bones) == 0: return {'FINISHED'} params = self for selected_bone in context.selected_pose_bones: #self.report({'INFO'}, str(selected_bone.vector[0])) ###Create Rigidbody Cube bpy.ops.mesh.primitive_cube_add(size=1, location=ob.matrix_world @ selected_bone.center) rc = context.active_object if rc is None: self.report({'INFO'}, 'Rigidboy creation Failded. Verify Rigidbody World exists and set current collection to Rigidbody World') return {'CANCELLED'} rc.name = "rb." + ob.name + '.' + selected_bone.name rc.rotation_mode = 'QUATERNION' rc.show_in_front = True rc.display.show_shadows = False rc.display_type = 'BOUNDS' rc.hide_render = True rc.cycles_visibility.transmission = False rc.cycles_visibility.camera = False rc.cycles_visibility.diffuse = False rc.cycles_visibility.scatter = False rc.cycles_visibility.shadow = False rc.cycles_visibility.glossy = False rc.show_bounds = True rc.display_bounds_type = params.p_rb_shape align_rb_ort_to_bone(rc, ob, selected_bone.name) ### Rigid Body Dimensions set_dimentions(context, params, selected_bone) ### Scale Apply bpy.ops.object.transform_apply(location=False, rotation=False, scale=True) ### Set Rigid Body bpy.ops.rigidbody.object_add() if params.p_rb_rootbody_passive == True: context.object.rigid_body.type = "PASSIVE" else: context.object.rigid_body.type = "ACTIVE" context.object.rigid_body.collision_shape = params.p_rb_shape context.object.rigid_body.kinematic = params.p_rb_rootbody_animated context.object.rigid_body.mass = params.p_rb_mass context.object.rigid_body.friction = params.p_rb_friction context.object.rigid_body.restitution = params.p_rb_bounciness context.object.rigid_body.linear_damping = params.p_rb_translation context.object.rigid_body.angular_damping = params.p_rb_rotation ### Child OF CoC = rc.constraints.new('CHILD_OF') CoC.name = 'Child_Of_' + selected_bone.name CoC.target = ob CoC.subtarget = selected_bone.name #without ops way to childof_set_inverse sub_target = bpy.data.objects[ob.name].pose.bones[selected_bone.name] #self.report({'INFO'}, str(sub_target)) CoC.inverse_matrix = (ob.matrix_world @ sub_target.matrix).inverted() rc.update_tag(refresh={'OBJECT'}) ###clear object select context.view_layer.objects.active = ob bpy.ops.object.mode_set(mode='OBJECT') bpy.ops.object.select_all(action='DESELECT') bpy.ops.object.mode_set(mode='POSE') bpy.ops.pose.select_all(action='DESELECT') self.report({'INFO'}, "OK") return {'FINISHED'} # class AddActiveOperator(bpy.types.Operator): bl_idname = "genrigidbodies.addactive" bl_label = "Add Actives" bl_description = "Make active rigid bodies aligned to selected bones" bl_options = {'REGISTER', 'UNDO'} tr_size = 0.25 ###instance UProp.rigidbody p_rb_shape : UProp.rb_shape p_rb_radius : UProp.rb_radius p_rb_length : UProp.rb_length p_rb_inset_capsule : UProp.rb_inset_capsule p_rb_dim : UProp.rb_dim p_rb_mass : UProp.rb_mass p_rb_friction : UProp.rb_friction p_rb_bounciness : UProp.rb_bounciness p_rb_translation : UProp.rb_translation p_rb_rotation : UProp.rb_rotation p_rb_rootbody_animated : UProp.rb_rootbody_animated def draw(self, context): box = self.layout.box() box.prop(self, 'p_rb_shape') if self.p_rb_shape in ('CONE', 'CYLINDER', 'CAPSULE', 'SPHERE'): box.prop(self, 'p_rb_radius') box.prop(self, 'p_rb_length') if self.p_rb_shape == 'CAPSULE': box.prop(self, 'p_rb_inset_capsule') else: box.prop(self, 'p_rb_dim') box.prop(self, 'p_rb_mass') box.prop(self, 'p_rb_friction') box.prop(self, 'p_rb_bounciness') box.prop(self, 'p_rb_translation') box.prop(self, 'p_rb_rotation') #box.prop(self, 'p_rb_rootbody_passive') box.prop(self, 'p_rb_rootbody_animated') ### def execute(self, context): ###selected Armature ob = context.active_object #self.report({'INFO'}, ob.data) spb = context.selected_pose_bones params = self bpy.ops.object.mode_set(mode='OBJECT') for selected_bone in spb: #self.report({'INFO'}, str(selected_bone.vector[0])) ###Create Rigidbody Cube bpy.ops.mesh.primitive_cube_add(size=1, location=ob.matrix_world @ selected_bone.center) rc = context.active_object if rc is None: self.report({'INFO'}, 'Rigidboy creation Failded. Verify Rigidbody World exists and set current collection to Rigidbody World') return {'CANCELLED'} rc.name = "rb." + ob.name + '.' + selected_bone.name rc.rotation_mode = 'QUATERNION' rc.show_in_front = True rc.display.show_shadows = False rc.display_type = 'BOUNDS' rc.hide_render = True rc.cycles_visibility.transmission = False rc.cycles_visibility.camera = False rc.cycles_visibility.diffuse = False rc.cycles_visibility.scatter = False rc.cycles_visibility.shadow = False rc.cycles_visibility.glossy = False rc.show_bounds = True rc.display_bounds_type = params.p_rb_shape align_rb_ort_to_bone(rc, ob, selected_bone.name) ### Rigid Body Dimensions set_dimentions(context, params, selected_bone) ### Scale Apply bpy.ops.object.transform_apply(location=False, rotation=False, scale=True) ### Set Rigid Body bpy.ops.rigidbody.object_add() context.object.rigid_body.type = "ACTIVE" context.object.rigid_body.collision_shape = params.p_rb_shape context.object.rigid_body.kinematic = params.p_rb_rootbody_animated context.object.rigid_body.mass = params.p_rb_mass context.object.rigid_body.friction = params.p_rb_friction context.object.rigid_body.restitution = params.p_rb_bounciness context.object.rigid_body.linear_damping = params.p_rb_translation context.object.rigid_body.angular_damping = params.p_rb_rotation ## Make Track offset point bpy.ops.object.empty_add(type='ARROWS') tr = context.active_object tr.name = "tr." + ob.name + "." + selected_bone.name tr.empty_display_size = selected_bone.length * self.tr_size tr.rotation_mode = 'QUATERNION' ### Align track object to bone align_obj_to_bone(tr, ob, selected_bone.name) tr.parent = rc tr.matrix_parent_inverse = rc.matrix_world.inverted() context.view_layer.objects.active = ob ### bone's use_connect turn to false bpy.ops.object.mode_set(mode='EDIT') for selected_bone in spb: ob.data.edit_bones[selected_bone.name].use_connect = False ### Set Copy Transform Constraint To Bone bpy.ops.object.mode_set(mode='POSE') for selected_bone in spb: tr = bpy.data.objects["tr." + ob.name + "." + selected_bone.name] #self.report({'INFO'}, str(rc.name)) con = selected_bone.constraints.new('COPY_TRANSFORMS') #self.report({'INFO'}, "info:" + str(CoC)) con.name = 'Copy Transforms Of ' + tr.name con.target = tr ### clear object select context.view_layer.objects.active = ob bpy.ops.object.mode_set(mode='OBJECT') bpy.ops.object.select_all(action='DESELECT') bpy.ops.object.mode_set(mode='POSE') bpy.ops.pose.select_all(action='DESELECT') self.report({'INFO'}, "OK") return {'FINISHED'} # class AddJointOperator(bpy.types.Operator): bl_idname = "genrigidbodies.addjoint" bl_label = "Add Joints" bl_description = "Make rigid body constraints on selected bones" bl_options = {'REGISTER', 'UNDO'} ###instance UProp.joint joint_type : UProp.jo_type joint_size : UProp.jo_size joint_align_bone : UProp.jo_align_bone joint_Axis_limit_x : UProp.jo_limit_lin_x joint_Axis_limit_y : UProp.jo_limit_lin_y joint_Axis_limit_z : UProp.jo_limit_lin_z joint_Axis_limit_x_lower : UProp.jo_limit_lin_x_lower joint_Axis_limit_y_lower : UProp.jo_limit_lin_y_lower joint_Axis_limit_z_lower : UProp.jo_limit_lin_z_lower joint_Axis_limit_x_upper : UProp.jo_limit_lin_x_upper joint_Axis_limit_y_upper : UProp.jo_limit_lin_y_upper joint_Axis_limit_z_upper : UProp.jo_limit_lin_z_upper joint_Angle_limit_x : UProp.jo_limit_ang_x joint_Angle_limit_y : UProp.jo_limit_ang_y joint_Angle_limit_z : UProp.jo_limit_ang_z joint_Angle_limit_x_lower : UProp.jo_limit_ang_x_lower joint_Angle_limit_y_lower : UProp.jo_limit_ang_y_lower joint_Angle_limit_z_lower : UProp.jo_limit_ang_z_lower joint_Angle_limit_x_upper : UProp.jo_limit_ang_x_upper joint_Angle_limit_y_upper : UProp.jo_limit_ang_y_upper joint_Angle_limit_z_upper : UProp.jo_limit_ang_z_upper joint_use_spring_x : UProp.jo_use_spring_x joint_use_spring_y : UProp.jo_use_spring_y joint_use_spring_z : UProp.jo_use_spring_z joint_spring_stiffness_x : UProp.jo_spring_stiffness_x joint_spring_stiffness_y : UProp.jo_spring_stiffness_y joint_spring_stiffness_z : UProp.jo_spring_stiffness_z joint_spring_damping_x : UProp.jo_spring_damping_x joint_spring_damping_y : UProp.jo_spring_damping_y joint_spring_damping_z : UProp.jo_spring_damping_z def draw(self, context): box = self.layout.box() box.prop(self, 'joint_type') box.prop(self, 'joint_size') box.prop(self, 'joint_align_bone') col = box.column(align=True) col.label(text="Limits:") row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Axis_limit_x', toggle=True) sub.prop(self, 'joint_Axis_limit_x_lower') sub.prop(self, 'joint_Axis_limit_x_upper') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Axis_limit_y', toggle=True) sub.prop(self, 'joint_Axis_limit_y_lower') sub.prop(self, 'joint_Axis_limit_y_upper') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Axis_limit_z', toggle=True) sub.prop(self, 'joint_Axis_limit_z_lower') sub.prop(self, 'joint_Axis_limit_z_upper') #col = self.layout.column(align=True) row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Angle_limit_x', toggle=True) sub.prop(self, 'joint_Angle_limit_x_lower') sub.prop(self, 'joint_Angle_limit_x_upper') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Angle_limit_y', toggle=True) sub.prop(self, 'joint_Angle_limit_y_lower') sub.prop(self, 'joint_Angle_limit_y_upper') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Angle_limit_z', toggle=True) sub.prop(self, 'joint_Angle_limit_z_lower') sub.prop(self, 'joint_Angle_limit_z_upper') #col = self.layout.column(align=True) col.label(text="Springs:") row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_use_spring_x', toggle=True) sub.prop(self, 'joint_spring_stiffness_x') sub.prop(self, 'joint_spring_damping_x') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_use_spring_y', toggle=True) sub.prop(self, 'joint_spring_stiffness_y') sub.prop(self, 'joint_spring_damping_y') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_use_spring_z', toggle=True) sub.prop(self, 'joint_spring_stiffness_z') sub.prop(self, 'joint_spring_damping_z') ### def execute(self, context): if context.scene.rigidbody_world is None: self.report({'INFO'}, 'Faild. Current scene has no Rigidbody World') return {'CANCELLED'} ###selected Armature ob = context.active_object #self.report({'INFO'}, ob.data) spb = context.selected_pose_bones ### Apply Object transform bpy.ops.object.mode_set(mode='OBJECT') params = self for selected_bone in spb: #self.report({'INFO'}, str(selected_bone.vector[0])) ###Create Empty Sphere bpy.ops.object.empty_add(type='ARROWS', location=ob.matrix_world @ selected_bone.matrix @ selected_bone.head) jc = context.active_object if jc is None: self.report({'INFO'}, 'Rigidboy creation Failded. Verify Rigidbody World exists and set current collection to Rigidbody World') return {'CANCELLED'} jc.name = "joint." + ob.name + "." + selected_bone.name jc.show_in_front = True jc.rotation_mode = 'QUATERNION' if params.joint_align_bone: align_obj_to_bone(jc, ob, selected_bone.name) ### Rigid Body Dimensions context.object.empty_display_size = selected_bone.length * params.joint_size ### Set Rigid Body Constraint bpy.ops.rigidbody.constraint_add() context.object.rigid_body_constraint.type = params.joint_type context.object.rigid_body_constraint.use_breaking = False context.object.rigid_body_constraint.use_override_solver_iterations = True context.object.rigid_body_constraint.breaking_threshold = 10 context.object.rigid_body_constraint.solver_iterations = 10 context.object.rigid_body_constraint.use_limit_lin_x = params.joint_Axis_limit_x context.object.rigid_body_constraint.use_limit_lin_y = params.joint_Axis_limit_y context.object.rigid_body_constraint.use_limit_lin_z = params.joint_Axis_limit_z context.object.rigid_body_constraint.limit_lin_x_lower = params.joint_Axis_limit_x_lower context.object.rigid_body_constraint.limit_lin_y_lower = params.joint_Axis_limit_y_lower context.object.rigid_body_constraint.limit_lin_z_lower = params.joint_Axis_limit_z_lower context.object.rigid_body_constraint.limit_lin_x_upper = params.joint_Axis_limit_x_upper context.object.rigid_body_constraint.limit_lin_y_upper = params.joint_Axis_limit_y_upper context.object.rigid_body_constraint.limit_lin_z_upper = params.joint_Axis_limit_z_upper context.object.rigid_body_constraint.use_limit_ang_x = params.joint_Angle_limit_x context.object.rigid_body_constraint.use_limit_ang_y = params.joint_Angle_limit_y context.object.rigid_body_constraint.use_limit_ang_z = params.joint_Angle_limit_z context.object.rigid_body_constraint.limit_ang_x_lower = params.joint_Angle_limit_x_lower context.object.rigid_body_constraint.limit_ang_y_lower = params.joint_Angle_limit_y_lower context.object.rigid_body_constraint.limit_ang_z_lower = params.joint_Angle_limit_z_lower context.object.rigid_body_constraint.limit_ang_x_upper = params.joint_Angle_limit_x_upper context.object.rigid_body_constraint.limit_ang_y_upper = params.joint_Angle_limit_y_upper context.object.rigid_body_constraint.limit_ang_z_upper = params.joint_Angle_limit_z_upper context.object.rigid_body_constraint.use_spring_x = params.joint_use_spring_x context.object.rigid_body_constraint.use_spring_y = params.joint_use_spring_y context.object.rigid_body_constraint.use_spring_z = params.joint_use_spring_z context.object.rigid_body_constraint.spring_stiffness_x = params.joint_spring_stiffness_x context.object.rigid_body_constraint.spring_stiffness_y = params.joint_spring_stiffness_y context.object.rigid_body_constraint.spring_stiffness_z = params.joint_spring_stiffness_z context.object.rigid_body_constraint.spring_damping_x = params.joint_spring_damping_x context.object.rigid_body_constraint.spring_damping_y = params.joint_spring_damping_y context.object.rigid_body_constraint.spring_damping_z = params.joint_spring_damping_z ###constraint.object if selected_bone.parent: rbname = "rb." + ob.name + "." + selected_bone.parent.name if rbname in context.view_layer.objects: context.object.rigid_body_constraint.object1 = context.view_layer.objects[rbname] rbname = "rb." + ob.name + "." + selected_bone.name if rbname in context.view_layer.objects: context.object.rigid_body_constraint.object2 = context.view_layer.objects[rbname] ###clear object select context.view_layer.objects.active = ob bpy.ops.object.mode_set(mode='OBJECT') bpy.ops.object.select_all(action='DESELECT') bpy.ops.object.mode_set(mode='POSE') bpy.ops.pose.select_all(action='DESELECT') self.report({'INFO'}, "OK") return {'FINISHED'} class AddActiveNJointOperator(bpy.types.Operator): bl_idname = "genrigidbodies.addactivenjoint" bl_label = "Add Actives & Joints" bl_description = "Make active rigid bodies & constraints" bl_options = {'REGISTER', 'UNDO'} tr_size = 0.5 ###instance UProp.rigidbody p_rb_shape : UProp.rb_shape p_rb_radius : UProp.rb_radius p_rb_length : UProp.rb_length p_rb_inset_capsule : UProp.rb_inset_capsule p_rb_dim : UProp.rb_dim p_rb_mass : UProp.rb_mass p_rb_friction : UProp.rb_friction p_rb_bounciness : UProp.rb_bounciness p_rb_translation : UProp.rb_translation p_rb_rotation : UProp.rb_rotation p_rb_add_pole_rootbody : UProp.rb_add_pole_rootbody p_rb_pole_rootbody_dim : UProp.rb_pole_rootbody_dim ###instance UProp.joint joint_type : UProp.jo_type joint_size : UProp.jo_size joint_align_bone : UProp.jo_align_bone joint_Axis_limit_x : UProp.jo_limit_lin_x joint_Axis_limit_y : UProp.jo_limit_lin_y joint_Axis_limit_z : UProp.jo_limit_lin_z joint_Axis_limit_x_lower : UProp.jo_limit_lin_x_lower joint_Axis_limit_y_lower : UProp.jo_limit_lin_y_lower joint_Axis_limit_z_lower : UProp.jo_limit_lin_z_lower joint_Axis_limit_x_upper : UProp.jo_limit_lin_x_upper joint_Axis_limit_y_upper : UProp.jo_limit_lin_y_upper joint_Axis_limit_z_upper : UProp.jo_limit_lin_z_upper joint_Angle_limit_x : UProp.jo_limit_ang_x joint_Angle_limit_y : UProp.jo_limit_ang_y joint_Angle_limit_z : UProp.jo_limit_ang_z joint_Angle_limit_x_lower : UProp.jo_limit_ang_x_lower joint_Angle_limit_y_lower : UProp.jo_limit_ang_y_lower joint_Angle_limit_z_lower : UProp.jo_limit_ang_z_lower joint_Angle_limit_x_upper : UProp.jo_limit_ang_x_upper joint_Angle_limit_y_upper : UProp.jo_limit_ang_y_upper joint_Angle_limit_z_upper : UProp.jo_limit_ang_z_upper joint_use_spring_x : UProp.jo_use_spring_x joint_use_spring_y : UProp.jo_use_spring_y joint_use_spring_z : UProp.jo_use_spring_z joint_spring_stiffness_x : UProp.jo_spring_stiffness_x joint_spring_stiffness_y : UProp.jo_spring_stiffness_y joint_spring_stiffness_z : UProp.jo_spring_stiffness_z joint_spring_damping_x : UProp.jo_spring_damping_x joint_spring_damping_y : UProp.jo_spring_damping_y joint_spring_damping_z : UProp.jo_spring_damping_z def draw(self, context): ###Rigid Body Object box = self.layout.box() box.prop(self, 'p_rb_shape') if self.p_rb_shape in ('CONE', 'CYLINDER', 'CAPSULE', 'SPHERE'): box.prop(self, 'p_rb_radius') box.prop(self, 'p_rb_length') if self.p_rb_shape == 'CAPSULE': box.prop(self, 'p_rb_inset_capsule') else: box.prop(self, 'p_rb_dim') box.prop(self, 'p_rb_mass') box.prop(self, 'p_rb_friction') box.prop(self, 'p_rb_bounciness') box.prop(self, 'p_rb_translation') box.prop(self, 'p_rb_rotation') #Joint Object box = self.layout.box() box.prop(self, 'joint_type') box.prop(self, 'joint_size') box.prop(self, 'joint_align_bone') box.prop(self, 'p_rb_add_pole_rootbody') col = box.column(align=True) col.label(text="Limits:") row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Axis_limit_x', toggle=True) sub.prop(self, 'joint_Axis_limit_x_lower') sub.prop(self, 'joint_Axis_limit_x_upper') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Axis_limit_y', toggle=True) sub.prop(self, 'joint_Axis_limit_y_lower') sub.prop(self, 'joint_Axis_limit_y_upper') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Axis_limit_z', toggle=True) sub.prop(self, 'joint_Axis_limit_z_lower') sub.prop(self, 'joint_Axis_limit_z_upper') #col = self.layout.column(align=True) row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Angle_limit_x', toggle=True) sub.prop(self, 'joint_Angle_limit_x_lower') sub.prop(self, 'joint_Angle_limit_x_upper') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Angle_limit_y', toggle=True) sub.prop(self, 'joint_Angle_limit_y_lower') sub.prop(self, 'joint_Angle_limit_y_upper') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_Angle_limit_z', toggle=True) sub.prop(self, 'joint_Angle_limit_z_lower') sub.prop(self, 'joint_Angle_limit_z_upper') #col = self.layout.column(align=True) col.label(text="Springs:") row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_use_spring_x', toggle=True) sub.prop(self, 'joint_spring_stiffness_x') sub.prop(self, 'joint_spring_damping_x') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_use_spring_y', toggle=True) sub.prop(self, 'joint_spring_stiffness_y') sub.prop(self, 'joint_spring_damping_y') row = col.row(align=True) sub = row.row(align=True) #sub.alignment = 'EXPAND' sub.prop(self, 'joint_use_spring_z', toggle=True) sub.prop(self, 'joint_spring_stiffness_z') sub.prop(self, 'joint_spring_damping_z') # def execute(self, context): ###selected Armature ob = context.active_object #self.report({'INFO'}, "ob:" + str(ob)) spb = context.selected_pose_bones bpy.ops.object.mode_set(mode='OBJECT') params = self rb_dict = {} ###Rigid Body Session for selected_bone in spb: #self.report({'INFO'}, str(selected_bone.vector[0])) ###Create Rigidbody Cube bpy.ops.mesh.primitive_cube_add(size=1, location=ob.matrix_world @ selected_bone.center) rc = context.active_object if rc is None: self.report({'INFO'}, 'Rigidbody creation Failded. Verify Rigidbody World exists and set current collection to Rigidbody World') return {'CANCELLED'} rc.name = "rb." + ob.name + "." + selected_bone.name rc.rotation_mode = 'QUATERNION' rc.show_in_front = True rc.display.show_shadows = False rc.display_type = 'BOUNDS' rc.hide_render = True rc.show_bounds = True rc.display_bounds_type = params.p_rb_shape rb_dict[selected_bone] = rc ### Aligh to Bone align_rb_ort_to_bone(rc, ob, selected_bone.name) ### Rigid Body Dimensions set_dimentions(context, params, selected_bone) ### Scale Apply bpy.ops.object.transform_apply(location=False, rotation=False, scale=True) ### Set Rigid Body bpy.ops.rigidbody.object_add() context.object.rigid_body.type = "ACTIVE" context.object.rigid_body.collision_shape = params.p_rb_shape context.object.rigid_body.mass = params.p_rb_mass context.object.rigid_body.friction = params.p_rb_friction context.object.rigid_body.restitution = params.p_rb_bounciness context.object.rigid_body.linear_damping = params.p_rb_translation context.object.rigid_body.angular_damping = params.p_rb_rotation ## Make Track offset point bpy.ops.object.empty_add(type='ARROWS') tr = context.active_object tr.name = "tr." + ob.name + "." + selected_bone.name tr.empty_display_size = selected_bone.length * params.joint_size * self.tr_size tr.rotation_mode = 'QUATERNION' ### Align track object to bone align_obj_to_bone(tr, ob, selected_bone.name) tr.parent = rc tr.matrix_parent_inverse = rc.matrix_world.inverted() if selected_bone.parent is not None and selected_bone.parent not in spb and selected_bone.parent not in rb_dict: if "rb." + ob.name + "." + selected_bone.parent.name in context.view_layer.objects: rb_dict[selected_bone.parent] = context.view_layer.objects["rb." + ob.name + "." + selected_bone.parent.name] elif params.p_rb_add_pole_rootbody: ###Create Rigidbody Cube bpy.ops.mesh.primitive_cube_add(size=1, location=ob.matrix_world @ selected_bone.matrix @ selected_bone.head) rc = context.active_object rc.name = "rb.pole." + ob.name + "." + selected_bone.parent.name rc.rotation_mode = 'QUATERNION' rc.show_in_front = True rc.display.show_shadows = False rc.hide_render = True rc.display_type = 'BOUNDS' rc.show_bounds = True rc.display_bounds_type = 'BOX' rb_dict[selected_bone.parent] = rc ### Rigid Body Dimensions context.object.dimensions = [ selected_bone.parent.length * params.p_rb_pole_rootbody_dim[0], selected_bone.parent.length * params.p_rb_pole_rootbody_dim[1], selected_bone.parent.length * params.p_rb_pole_rootbody_dim[2] ] ### Scale Apply bpy.ops.object.transform_apply(location=False, rotation=False, scale=True) ### Set Rigid Body bpy.ops.rigidbody.object_add() rc.rigid_body.type = "PASSIVE" rc.rigid_body.collision_shape = "BOX" #rc.rigid_body.collision_shape = params.p_rb_shape #rc.rigid_body.mass = params.p_rb_mass #rc.rigid_body.friction = params.p_rb_friction #rc.rigid_body.restitution = params.p_rb_bounciness #rc.rigid_body.linear_damping = params.p_rb_translation #rc.rigid_body.angular_damping = params.p_rb_rotation rc.rigid_body.kinematic = True ### Child OF CoC = rc.constraints.new('CHILD_OF') CoC.name = 'Child_Of_' + selected_bone.parent.name CoC.target = ob CoC.subtarget = selected_bone.parent.name #without ops way to childof_set_inverse sub_target = bpy.data.objects[ob.name].pose.bones[selected_bone.parent.name] #self.report({'INFO'}, str(sub_target)) CoC.inverse_matrix = (ob.matrix_world @ sub_target.matrix).inverted() #context.view_layer.update() print('Joint Session') ###Joint Session for selected_bone in spb: #self.report({'INFO'}, str(selected_bone.vector[0])) if selected_bone in rb_dict: ###Create Joint Empty bpy.ops.object.empty_add(type='ARROWS', location=ob.matrix_world @ selected_bone.matrix @ selected_bone.head) jc = context.active_object jc.name = "joint." + ob.name + "." + selected_bone.name jc.show_in_front = True jc.rotation_mode = 'QUATERNION' if params.joint_align_bone: align_obj_to_bone(jc, ob, selected_bone.name) ### Set Joint radius context.object.empty_display_size = selected_bone.length * params.joint_size ### Set Rigid Body Constraint bpy.ops.rigidbody.constraint_add() if selected_bone.parent in rb_dict: jc.rigid_body_constraint.object1 = rb_dict[selected_bone.parent] jc.rigid_body_constraint.object2 = rb_dict[selected_bone] jc.rigid_body_constraint.type = params.joint_type jc.rigid_body_constraint.use_breaking = False jc.rigid_body_constraint.use_override_solver_iterations = True jc.rigid_body_constraint.breaking_threshold = 10 jc.rigid_body_constraint.solver_iterations = 10 jc.rigid_body_constraint.use_limit_lin_x = params.joint_Axis_limit_x jc.rigid_body_constraint.use_limit_lin_y = params.joint_Axis_limit_y jc.rigid_body_constraint.use_limit_lin_z = params.joint_Axis_limit_z jc.rigid_body_constraint.limit_lin_x_lower = params.joint_Axis_limit_x_lower jc.rigid_body_constraint.limit_lin_y_lower = params.joint_Axis_limit_y_lower jc.rigid_body_constraint.limit_lin_z_lower = params.joint_Axis_limit_z_lower jc.rigid_body_constraint.limit_lin_x_upper = params.joint_Axis_limit_x_upper jc.rigid_body_constraint.limit_lin_y_upper = params.joint_Axis_limit_y_upper jc.rigid_body_constraint.limit_lin_z_upper = params.joint_Axis_limit_z_upper jc.rigid_body_constraint.use_limit_ang_x = params.joint_Angle_limit_x jc.rigid_body_constraint.use_limit_ang_y = params.joint_Angle_limit_y jc.rigid_body_constraint.use_limit_ang_z = params.joint_Angle_limit_z jc.rigid_body_constraint.limit_ang_x_lower = params.joint_Angle_limit_x_lower jc.rigid_body_constraint.limit_ang_y_lower = params.joint_Angle_limit_y_lower jc.rigid_body_constraint.limit_ang_z_lower = params.joint_Angle_limit_z_lower jc.rigid_body_constraint.limit_ang_x_upper = params.joint_Angle_limit_x_upper jc.rigid_body_constraint.limit_ang_y_upper = params.joint_Angle_limit_y_upper jc.rigid_body_constraint.limit_ang_z_upper = params.joint_Angle_limit_z_upper jc.rigid_body_constraint.use_spring_x = params.joint_use_spring_x jc.rigid_body_constraint.use_spring_y = params.joint_use_spring_y jc.rigid_body_constraint.use_spring_z = params.joint_use_spring_z jc.rigid_body_constraint.spring_stiffness_x = params.joint_spring_stiffness_x jc.rigid_body_constraint.spring_stiffness_y = params.joint_spring_stiffness_y jc.rigid_body_constraint.spring_stiffness_z = params.joint_spring_stiffness_z jc.rigid_body_constraint.spring_damping_x = params.joint_spring_damping_x jc.rigid_body_constraint.spring_damping_y = params.joint_spring_damping_y jc.rigid_body_constraint.spring_damping_z = params.joint_spring_damping_z context.view_layer.objects.active = ob ###bone's use_connect turn to false bpy.ops.object.mode_set(mode='EDIT') for selected_bone in spb: ob.data.edit_bones[selected_bone.name].use_connect = False ### Set Copy Transform Constraint To Bone bpy.ops.object.mode_set(mode='POSE') for selected_bone in spb: #bpy.ops.pose.armature_apply() ab = selected_bone tr = bpy.data.objects["tr." + ob.name + "." + selected_bone.name] #self.report({'INFO'}, str(rc.name)) con = ab.constraints.new('COPY_TRANSFORMS') #self.report({'INFO'}, "info:" + str(CoC)) con.name = 'Copy Transforms Of ' + tr.name con.target = tr ###clear object select context.view_layer.objects.active = ob bpy.ops.object.mode_set(mode='OBJECT') bpy.ops.object.select_all(action='DESELECT') bpy.ops.object.mode_set(mode='POSE') bpy.ops.pose.select_all(action='DESELECT') self.report({'INFO'}, "OK") return {'FINISHED'} class ReparentOrphanTrackObjectOperator(bpy.types.Operator): bl_idname = "genrigidbodies.reparent_orphan_track_object" bl_label = "Reparent Orphan Track Object" bl_description = "Parent unparented 'tr.' object to corresponding 'rb.' object by keep transforming parenting." bl_options = {'UNDO'} def execute(self, context): print(context.view_layer.objects) for i in context.selected_objects: if i.name.startswith("tr."): correspondName = 'rb' + i.name[2:] print(correspondName) if correspondName in context.view_layer.objects: print('parent') parentObject = context.view_layer.objects[correspondName] i.parent = parentObject i.matrix_parent_inverse = parentObject.matrix_world.inverted() return {'FINISHED'} class ForceCorrespondNameRBAndTrackObjectOperator(bpy.types.Operator): bl_idname = "genrigidbodies.force_correspond_name_rb_n_tr" bl_label = "Repair Corresponding" bl_description = "If 'tr.' object's parent 'rb.' object has non-corresponding name, rename it." bl_options = {'UNDO'} def execute(self, context): print(context.view_layer.objects) for i in context.selected_objects: if i.name.startswith("tr.") and i.parent and i.parent.name.startswith("rb."): correspondName = 'rb' + i.name[2:] print(correspondName) if correspondName != i.parent.name: print('rename') i.parent.name = correspondName return {'FINISHED'} class ConnectOperator(bpy.types.Operator): bl_idname = "genrigidbodies.connect" bl_label = "Connect Rigid Body Constraint" bl_description = "Set selected objects' 'Objects' paratemter of rigid body constraint to active object." bl_options = {'UNDO'} def execute(self, context): for i in context.selected_objects: if i != context.active_object and i.rigid_body_constraint: i.rigid_body_constraint.object1 = context.active_object return {'FINISHED'} # utils def set_dimentions(context, params, selected_bone): if params.p_rb_shape in ('CONE', 'CYLINDER', 'CAPSULE', 'SPHERE'): if params.p_rb_shape == 'CAPSULE' and not params.p_rb_inset_capsule: context.object.dimensions = [ selected_bone.length * params.p_rb_radius, selected_bone.length * params.p_rb_radius, selected_bone.length * (params.p_rb_length + params.p_rb_radius) ] else: context.object.dimensions = [ selected_bone.length * params.p_rb_radius, selected_bone.length * params.p_rb_radius, selected_bone.length * params.p_rb_length ] else: context.object.dimensions = [ selected_bone.length * params.p_rb_dim[0], selected_bone.length * params.p_rb_dim[2], selected_bone.length * params.p_rb_dim[1] ] def align_obj_to_bone(obj, armature, bone_name): bone = armature.data.bones[bone_name] mat = armature.matrix_world @ bone.matrix_local obj.location = mat.to_translation() obj.rotation_mode = 'QUATERNION' obj.rotation_quaternion = mat.to_quaternion() def align_rb_ort_to_bone(obj, armature, bone_name): bone = armature.data.bones[bone_name] mat = armature.matrix_world @ bone.matrix_local @ mathutils.Matrix.Rotation(math.radians(-90.0), 4, 'X') obj.rotation_mode = 'QUATERNION' obj.rotation_quaternion = mat.to_quaternion() # add menu register, unregister = bpy.utils.register_classes_factory(( AddPassiveOperator, AddActiveOperator, AddJointOperator, AddActiveNJointOperator, ReparentOrphanTrackObjectOperator, ForceCorrespondNameRBAndTrackObjectOperator, ConnectOperator, PoseMenu, ObjectMenu, ))

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Python

tests/utmp.py

jleaniz/dtformats

03c29442c6a98bd4998314fca7274572ea848a84

[ "Apache-2.0" ]

61

2017-08-30T11:13:17.000Z

2022-03-24T20:45:18.000Z

tests/utmp.py

jleaniz/dtformats

03c29442c6a98bd4998314fca7274572ea848a84

[ "Apache-2.0" ]

12

2017-05-01T10:22:49.000Z

2022-02-11T05:51:18.000Z

tests/utmp.py

jleaniz/dtformats

03c29442c6a98bd4998314fca7274572ea848a84

[ "Apache-2.0" ]

19

2018-08-16T09:32:07.000Z

2021-11-19T17:14:02.000Z

# -*- coding: utf-8 -*- """Tests for utmp files.""" import unittest from dtformats import utmp from tests import test_lib class LinuxLibc6UtmpFileTest(test_lib.BaseTestCase): """Linux libc6 utmp file tests.""" # pylint: disable=protected-access def testDebugPrintEntry(self): """Tests the _DebugPrintEntry function.""" output_writer = test_lib.TestOutputWriter() test_file = utmp.LinuxLibc6UtmpFile(output_writer=output_writer) data_type_map = test_file._GetDataTypeMap('linux_libc6_utmp_entry') entry = data_type_map.CreateStructureValues( ip_address=test_file._EMPTY_IP_ADDRESS, exit_status=5, hostname=b'host', microseconds=8, pid=2, session=6, terminal=b'vty', terminal_identifier=3, termination_status=4, timestamp=7, type=1, unknown1=b'unknown', username=b'user') test_file._DebugPrintEntry(entry) def testDecodeString(self): """Tests the _DecodeString function.""" test_file = utmp.LinuxLibc6UtmpFile() string = test_file._DecodeString(b'test\x00') self.assertEqual(string, 'test') def testReadEntries(self): """Tests the _ReadEntries function.""" output_writer = test_lib.TestOutputWriter() test_file = utmp.LinuxLibc6UtmpFile(output_writer=output_writer) test_file_path = self._GetTestFilePath(['utmp-linux_libc6']) self._SkipIfPathNotExists(test_file_path) with open(test_file_path, 'rb') as file_object: test_file._ReadEntries(file_object) def testReadFileObject(self): """Tests the ReadFileObject.""" output_writer = test_lib.TestOutputWriter() test_file = utmp.LinuxLibc6UtmpFile(debug=True, output_writer=output_writer) test_file_path = self._GetTestFilePath(['utmp-linux_libc6']) self._SkipIfPathNotExists(test_file_path) test_file.Open(test_file_path) class MacOSXUtmpxFileTest(test_lib.BaseTestCase): """Mac OS X 10.5 utmpx file tests.""" # pylint: disable=protected-access def testDebugPrintEntry(self): """Tests the _DebugPrintEntry function.""" output_writer = test_lib.TestOutputWriter() test_file = utmp.MacOSXUtmpxFile(output_writer=output_writer) data_type_map = test_file._GetDataTypeMap('macosx_utmpx_entry') entry = data_type_map.CreateStructureValues( hostname=b'host', microseconds=1, pid=2, terminal=b'vty', terminal_identifier=3, timestamp=4, type=5, unknown1=6, unknown2=b'unknown', username=b'user') test_file._DebugPrintEntry(entry) def testDecodeString(self): """Tests the _DecodeString function.""" test_file = utmp.MacOSXUtmpxFile() string = test_file._DecodeString(b'test\x00') self.assertEqual(string, 'test') def testReadEntries(self): """Tests the _ReadEntries function.""" output_writer = test_lib.TestOutputWriter() test_file = utmp.MacOSXUtmpxFile(output_writer=output_writer) test_file_path = self._GetTestFilePath(['utmpx-macosx10.5']) self._SkipIfPathNotExists(test_file_path) with open(test_file_path, 'rb') as file_object: test_file._ReadEntries(file_object) def testReadFileObject(self): """Tests the ReadFileObject.""" output_writer = test_lib.TestOutputWriter() test_file = utmp.MacOSXUtmpxFile(debug=True, output_writer=output_writer) test_file_path = self._GetTestFilePath(['utmpx-macosx10.5']) self._SkipIfPathNotExists(test_file_path) test_file.Open(test_file_path) if __name__ == '__main__': unittest.main()

28.555556

80

0.712618

412

3,598

5.915049

0.237864

0.101764

0.059089

0.046779

0.808781

0.748872

0.73533

0

0.01355

0.179544

3,598

125

81

28.784

0.811992

0.119789

0

0.657895

0

0.05661

0.007076

0

0.026316

1

0.105263

false

0

0.039474

0

0.171053

0

null

0

1

0

null

0

6

04051ffeeaeb6bc8d951d79951e14ed8c0725a58

40

py

Python

hnms/__init__.py

microsoft/hnms

c7368cd9079fe576a61cdf4e1872b326485f2464

[ "MIT" ]

30

2020-05-26T01:33:05.000Z

2020-10-21T23:50:31.000Z

hnms/__init__.py

microsoft/hnms

c7368cd9079fe576a61cdf4e1872b326485f2464

[ "MIT" ]

1

2020-05-31T12:18:09.000Z

2020-05-31T14:09:05.000Z

hnms/__init__.py

microsoft/hnms

c7368cd9079fe576a61cdf4e1872b326485f2464

[ "MIT" ]

5

2020-05-26T02:11:47.000Z

2021-11-10T08:33:32.000Z

from .multi_hnms import MultiHNMS, HNMS

20

39

0.825

6

40

5.333333

0.833333

0

0.125

40

1

40

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

041a9fa62dc55ae70593d44254261599b82add98

341

py

Python

pipeline/__init__.py

cnwarden/mico2

017c52ef4626649d162904f247f21eec768fafc3

[ "MIT" ]

null

pipeline/__init__.py

cnwarden/mico2

017c52ef4626649d162904f247f21eec768fafc3

[ "MIT" ]

null

pipeline/__init__.py

cnwarden/mico2

017c52ef4626649d162904f247f21eec768fafc3

[ "MIT" ]

null

# coding:utf-8 import elasticsearch import pykafka from pipeline.pipeline_manager import PipelineManager from pipeline.pipelines import ESPipeline, KafkaPipeline, StorePipeline, SimplePipeline, SaveToDictPipeline __all__ = ['PipelineManager', 'ESPipeline', 'KafkaPipeline', 'StorePipeline', 'SimplePipeline', 'SaveToDictPipeline']

37.888889

118

0.809384

29

341

9.344828

0.586207

0.088561

0.265683

0.369004

0.501845

0

0.003279

0.105572

341

8

119

42.625

0.885246

0.035191

0

0.260188

0

1

0

false

0

0.8

0

0.8

0

1

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null

0

1

0

1

0

null

0

1

0

1

0

6

04362d1c0bc89f03b2612adaea14f8dfb97bce44

2,069

py

Python

groupdocs_comparison_cloud/models/__init__.py

groupdocs-comparison-cloud/groupdocs-comparison-cloud-python

f970b22fae7a791d07b756c2d418217fd368c289

[ "MIT" ]

null

groupdocs_comparison_cloud/models/__init__.py

groupdocs-comparison-cloud/groupdocs-comparison-cloud-python

f970b22fae7a791d07b756c2d418217fd368c289

[ "MIT" ]

null

groupdocs_comparison_cloud/models/__init__.py

groupdocs-comparison-cloud/groupdocs-comparison-cloud-python

f970b22fae7a791d07b756c2d418217fd368c289

[ "MIT" ]

1

2021-02-02T18:41:48.000Z

# coding: utf-8 # flake8: noqa from __future__ import absolute_import # import models from groupdocs_comparison_cloud.models.apply_revisions_options import ApplyRevisionsOptions from groupdocs_comparison_cloud.models.change_info import ChangeInfo from groupdocs_comparison_cloud.models.comparison_options import ComparisonOptions from groupdocs_comparison_cloud.models.diagram_master_setting import DiagramMasterSetting from groupdocs_comparison_cloud.models.disc_usage import DiscUsage from groupdocs_comparison_cloud.models.error import Error from groupdocs_comparison_cloud.models.error_details import ErrorDetails from groupdocs_comparison_cloud.models.file_info import FileInfo from groupdocs_comparison_cloud.models.file_versions import FileVersions from groupdocs_comparison_cloud.models.files_list import FilesList from groupdocs_comparison_cloud.models.files_upload_result import FilesUploadResult from groupdocs_comparison_cloud.models.format import Format from groupdocs_comparison_cloud.models.formats_result import FormatsResult from groupdocs_comparison_cloud.models.info_result import InfoResult from groupdocs_comparison_cloud.models.items_style import ItemsStyle from groupdocs_comparison_cloud.models.link import Link from groupdocs_comparison_cloud.models.metadata import Metadata from groupdocs_comparison_cloud.models.object_exist import ObjectExist from groupdocs_comparison_cloud.models.page_info import PageInfo from groupdocs_comparison_cloud.models.rectangle import Rectangle from groupdocs_comparison_cloud.models.revision_info import RevisionInfo from groupdocs_comparison_cloud.models.settings import Settings from groupdocs_comparison_cloud.models.size import Size from groupdocs_comparison_cloud.models.storage_exist import StorageExist from groupdocs_comparison_cloud.models.storage_file import StorageFile from groupdocs_comparison_cloud.models.style_change_info import StyleChangeInfo from groupdocs_comparison_cloud.models.file_version import FileVersion from groupdocs_comparison_cloud.models.updates_options import UpdatesOptions

59.114286

91

0.908652

261

2,069

6.873563

0.260536

0.202899

0.358974

0.437012

0.556299

0.19621

0

0.00103

0.061382

2,069

34

92

60.852941

0.92276

0.019333

0

1

0

true

0

1

0

1

0

null

1

0

null

0

1

0

1

0

1

0

6

044fcca08ab99ca3809d45e924f55259da622082

30

py

Python

Grapple/__init__.py

elctrc/grapple

0131bd63711a0695b2fa5f17464655083404b97f

[ "Apache-2.0" ]

3

2021-06-16T15:49:57.000Z

2021-09-01T16:52:15.000Z

Grapple/__init__.py

elctrc/grapple

0131bd63711a0695b2fa5f17464655083404b97f

[ "Apache-2.0" ]

null

Grapple/__init__.py

elctrc/grapple

0131bd63711a0695b2fa5f17464655083404b97f

[ "Apache-2.0" ]

null

from .grapple import HayLoader

30

0.866667

4

30

6.5

1

0

0.1

30

1

30

0.962963

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

f08ed7656c5c84be93bc864aec551a09b31e4dd3

164

py

Python

emulator/script2.py

mace84/script-languages

d586cbe212bbb4efbfb39e095183729c65489360

[ "MIT" ]

6

2019-01-09T11:55:15.000Z

2021-06-25T19:52:42.000Z

emulator/script2.py

mace84/script-languages

d586cbe212bbb4efbfb39e095183729c65489360

[ "MIT" ]

65

2018-12-12T08:40:38.000Z

2022-02-28T09:19:45.000Z

emulator/script2.py

mace84/script-languages

d586cbe212bbb4efbfb39e095183729c65489360

[ "MIT" ]

9

2018-11-23T08:59:09.000Z

2020-02-04T12:56:35.000Z

#input_column: b,string,VARCHAR(100),100,None,None #input_type: SET #output_column: b,string,VARCHAR(100),100,None,None #output_type: EMITS #!/bin/bash ls -l /tmp

20.5

51

0.75

29

164

4.103448

0.551724

0.117647

0.218487

0.336134

0.571429

0

0.07947

0.079268

164

7

52

23.428571

0.708609

0.865854

0

1

0

true

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

6

f0fd8f98ada3234e49c76eb4884461094bb94f54

93

py

Python

terrascript/vcd/__init__.py

hugovk/python-terrascript

08fe185904a70246822f5cfbdc9e64e9769ec494

[ "BSD-2-Clause" ]

4

2022-02-07T21:08:14.000Z

2022-03-03T04:41:28.000Z

terrascript/vcd/__init__.py

hugovk/python-terrascript

08fe185904a70246822f5cfbdc9e64e9769ec494

[ "BSD-2-Clause" ]

null

terrascript/vcd/__init__.py

hugovk/python-terrascript

08fe185904a70246822f5cfbdc9e64e9769ec494

[ "BSD-2-Clause" ]

2

2022-02-06T01:49:42.000Z

2022-02-08T14:15:00.000Z

# terrascript/vcd/__init__.py import terrascript class vcd(terrascript.Provider): pass

13.285714

32

0.774194

11

93

6.181818

0.727273

0

0.139785

93

6

33

15.5

0.85

0.290323

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

9bd15d570c4edfc4bfb31a2706ea18aa04efa9f5

137

py

Python

tests/job_scrapper.py

DannyMcwaves/ATS

91327ce15b4c4ea2fffebf02562cb8095b7983ec

[ "BSD-3-Clause" ]

null

tests/job_scrapper.py

DannyMcwaves/ATS

91327ce15b4c4ea2fffebf02562cb8095b7983ec

[ "BSD-3-Clause" ]

4

2020-06-05T17:38:46.000Z

2022-03-02T14:54:30.000Z

tests/job_scrapper.py

DannyMcwaves/ATS

91327ce15b4c4ea2fffebf02562cb8095b7983ec

[ "BSD-3-Clause" ]

null

from job_scraper import run url = 'https://stackoverflow.com/jobs/139474/full-stack-developer-with-a-passion-for-borderguru' run(url)

19.571429

96

0.781022

21

137

5.047619

0.904762

0.113208

0

0.047619

0.080292

137

6

97

22.833333

0.793651

0

0.333333

0.647059

0

1

0

false

0.333333

0

0.333333

0

1

0

null

0

1

0

1

0

null

0

1

0

6

ac969f51247bccae56dbcd467866fade7d7c0225

334

py

Python

Beta/Never gonna give you up.py

mwk0408/codewars_solutions

9b4f502b5f159e68024d494e19a96a226acad5e5

[ "MIT" ]

6

2020-09-03T09:32:25.000Z

2020-12-07T04:10:01.000Z

Beta/Never gonna give you up.py

mwk0408/codewars_solutions

9b4f502b5f159e68024d494e19a96a226acad5e5

[ "MIT" ]

1

2021-12-13T15:30:21.000Z

Beta/Never gonna give you up.py

mwk0408/codewars_solutions

9b4f502b5f159e68024d494e19a96a226acad5e5

[ "MIT" ]

null

def music(numbers): s="Never gonna give you up\nNever gonna let you down\nNever gonna run around and desert you\nNever gonna make you cry\nNever gonna say goodbye\nNever gonna tell a lie and hurt you".split("\n") return [s[val].replace("Never gonna", "NEVER GONNA") if index%2 else s[val] for index, val in enumerate(numbers)]

111.333333

196

0.739521

60

334

4.116667

0.6

0.222672

0

0.003546

0.155689

334

3

197

111.333333

0.87234

0

0.333333

0.597015

0

1

0.333333

false

0

0.666667

0

null

1

0

1

0

1

0

1

0

null

0

1

0

1

0

6

ac9e0e0b5801506d8f955bb2b8721ba557314363

27

py

Python

hello.py

Feister31/Election-Analysis

5884c906bcc12bcc682f0ed930d72f06a2a090d8

[ "MIT" ]

null

hello.py

Feister31/Election-Analysis

5884c906bcc12bcc682f0ed930d72f06a2a090d8

[ "MIT" ]

null

hello.py

Feister31/Election-Analysis

5884c906bcc12bcc682f0ed930d72f06a2a090d8

[ "MIT" ]

null

print("election_analysis")

13.5

26

0.814815

3

27

7

1

0

0.037037

27

1

27

0.807692

0

0.62963

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

acc0b6df2b6aceb61444b8085229d0462e37573d

879

py

Python

terrascript/digitalocean/d.py

vutsalsinghal/python-terrascript

3b9fb5ad77453d330fb0cd03524154a342c5d5dc

[ "BSD-2-Clause" ]

null

terrascript/digitalocean/d.py

vutsalsinghal/python-terrascript

3b9fb5ad77453d330fb0cd03524154a342c5d5dc

[ "BSD-2-Clause" ]

null

terrascript/digitalocean/d.py

vutsalsinghal/python-terrascript

3b9fb5ad77453d330fb0cd03524154a342c5d5dc

[ "BSD-2-Clause" ]

null

# terrascript/digitalocean/d.py import terrascript class digitalocean_certificate(terrascript.Data): pass class digitalocean_database_cluster(terrascript.Data): pass class digitalocean_domain(terrascript.Data): pass class digitalocean_droplet(terrascript.Data): pass class digitalocean_droplet_snapshot(terrascript.Data): pass class digitalocean_floating_ip(terrascript.Data): pass class digitalocean_image(terrascript.Data): pass class digitalocean_kubernetes_cluster(terrascript.Data): pass class digitalocean_loadbalancer(terrascript.Data): pass class digitalocean_record(terrascript.Data): pass class digitalocean_ssh_key(terrascript.Data): pass class digitalocean_tag(terrascript.Data): pass class digitalocean_volume_snapshot(terrascript.Data): pass class digitalocean_volume(terrascript.Data): pass

18.702128

56

0.796359

96

879

7.083333

0.25

0.35

0.391176

0.458824

0.770588

0.452941

0

0.135381

879

46

57

19.108696

0.894737

0.032992

0

0.482759

0

1

0

true

0.482759

0.034483

0

0.517241

0

null

1

0

null

0

1

0

1

0

6

ace5700a6e1a8a4f7b4738cf6ee5f0df89d47cf7

42

py

Python

content/usr/src/app/examples/env.py

jerenius/Tahtoprobe

bce3cc439d2d63897ecbffeec820d637dc4cdb46

[ "MIT" ]

null

content/usr/src/app/examples/env.py

jerenius/Tahtoprobe

bce3cc439d2d63897ecbffeec820d637dc4cdb46

[ "MIT" ]

null

content/usr/src/app/examples/env.py

jerenius/Tahtoprobe

bce3cc439d2d63897ecbffeec820d637dc4cdb46

[ "MIT" ]

null

import os print(os.environ['mqttbroker'])

14

31

0.761905

6

42

5.333333

0.833333

0

0.071429

42

2

32

21

0.820513

0

0.238095

0

1

0

true

0

0.5

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

aced9056be53d5cb3ab9b218adb0c1684e092e11

5,429

py

Python

tests/unit/testActionRules/testActionRules.py

KIZI/actionrules

227e021fa60ce40a1492322fe9bec35f0469e19c

[ "MIT" ]

8

2019-10-11T09:49:20.000Z

2022-03-21T23:23:55.000Z

tests/unit/testActionRules/testActionRules.py

hhl60492/actionrules

cdd1f58b44278e033d2eed7c603938e29368c9fa

[ "MIT" ]

15

2019-12-29T20:14:36.000Z

2021-12-10T13:16:00.000Z

tests/unit/testActionRules/testActionRules.py

KIZI/actionrules

227e021fa60ce40a1492322fe9bec35f0469e19c

[ "MIT" ]

7

2019-10-10T15:51:36.000Z

2022-03-23T00:33:30.000Z

import unittest import pandas as pd from actionrules.actionRules import ActionRules from actionrules.desiredState import DesiredState class TestActionRules(unittest.TestCase): def setUp(self): self.actionRulesDiscoveryEmptyNotNan = ActionRules([pd.DataFrame()], [pd.DataFrame()], [pd.DataFrame()], DesiredState(), [pd.Series()], [pd.Series()]) self.actionRulesDiscoveryEmptyNan = ActionRules([pd.DataFrame()], [pd.DataFrame()], [pd.DataFrame()], DesiredState(), [pd.Series()], [pd.Series()], True) def test_is_action_couple_when_stable_candidate_not_nan_same_values(self): result = self.actionRulesDiscoveryEmptyNotNan._is_action_couple('0', '0', "stable") #(bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (True, ('0',), False) self.assertEqual(expected, result) def test_is_action_couple_when_not_stable_candidate_not_nan_different_values(self): result = self.actionRulesDiscoveryEmptyNotNan._is_action_couple('0', '1', "stable") #(bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (False, None, True) self.assertEqual(expected, result) def test_is_action_couple_when_not_stable_candidate_not_nan_missing_value(self): result = self.actionRulesDiscoveryEmptyNotNan._is_action_couple('nan', '1', "stable") # (bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (False, None, True) self.assertEqual(expected, result) def test_is_action_couple_when_not_flexible_candidate_not_nan_same_values(self): result = self.actionRulesDiscoveryEmptyNotNan._is_action_couple('0', '0', "flexible") #(bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (False, None, True) self.assertEqual(expected, result) def test_is_action_couple_when_flexible_candidate_not_nan_different_values(self): result = self.actionRulesDiscoveryEmptyNotNan._is_action_couple('0', '1', "flexible") #(bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (True, ('0', '1'), False) self.assertEqual(expected, result) def test_is_action_couple_when_not_flexible_candidate_not_nan_missing_value(self): result = self.actionRulesDiscoveryEmptyNotNan._is_action_couple('nan', '1', "flexible") # (bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (False, None, True) self.assertEqual(expected, result) def test_is_action_couple_when_stable_candidate_nan_same_values(self): result = self.actionRulesDiscoveryEmptyNan._is_action_couple('0', '0', "stable") #(bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (True, ('0',), False) self.assertEqual(expected, result) def test_is_action_couple_when_not_stable_candidate_nan_different_values(self): result = self.actionRulesDiscoveryEmptyNan._is_action_couple('0', '1', "stable") #(bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (False, None, True) self.assertEqual(expected, result) def test_is_action_couple_when_stable_candidate_nan_missing_value(self): result = self.actionRulesDiscoveryEmptyNan._is_action_couple('nan', '1', "stable") # (bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (True, ('1*',), False) self.assertEqual(expected, result) def test_is_action_couple_when_not_flexible_candidate_nan_same_values(self): result = self.actionRulesDiscoveryEmptyNan._is_action_couple('0', '0', "flexible") #(bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (False, None, True) self.assertEqual(expected, result) def test_is_action_couple_when_flexible_candidate_nan_different_values(self): result = self.actionRulesDiscoveryEmptyNan._is_action_couple('0', '1', "flexible") #(bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (True, ('0', '1'), False) self.assertEqual(expected, result) def test_is_action_couple_when_flexible_candidate_nan_missing_value(self): result = self.actionRulesDiscoveryEmptyNan._is_action_couple('nan', '1', "flexible") # (bool is_action_pair, (before, after) action_pair, bool break_rule) expected = (True, ('None', '1'), False) self.assertEqual(expected, result) def test_get_uplift(self): result = self.actionRulesDiscoveryEmptyNan._get_uplift(0.2, 0.8, 0.8) expected = 0.15 self.assertAlmostEqual(expected, result) if __name__ == '__main__': unittest.main()

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null

0

1

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null

0

6

acedd7a0944d8784bf933d66fe77b0849856dd14

1,083

py

Python

gQuant/plugins/cusignal_plugin/setup.py

t-triobox/gQuant

6ee3ba104ce4c6f17a5755e7782298902d125563

[ "Apache-2.0" ]

null

gQuant/plugins/cusignal_plugin/setup.py

t-triobox/gQuant

6ee3ba104ce4c6f17a5755e7782298902d125563

[ "Apache-2.0" ]

null

gQuant/plugins/cusignal_plugin/setup.py

t-triobox/gQuant

6ee3ba104ce4c6f17a5755e7782298902d125563

[ "Apache-2.0" ]

null

''' Greenflow Cusignal Plugin ''' from setuptools import setup, find_packages setup( name='greenflow_cusignal_plugin', version='1.0', description='greenflow cusignal plugin - RAPIDS Cusignal Nodes for Greenflow', # noqa: E501 install_requires=["greenflow", "cusignal"], packages=find_packages(include=['greenflow_cusignal_plugin', 'greenflow_cusignal_plugin.*']), entry_points={ 'greenflow.plugin': [ 'greenflow_cusignal_plugin = greenflow_cusignal_plugin', 'greenflow_cusignal_plugin.convolution = greenflow_cusignal_plugin.convolution', # noqa: E501 'greenflow_cusignal_plugin.filtering = greenflow_cusignal_plugin.filtering', # noqa: E501 'greenflow_cusignal_plugin.gensig = greenflow_cusignal_plugin.gensig', # noqa: E501 'greenflow_cusignal_plugin.spectral_analysis = greenflow_cusignal_plugin.spectral_analysis', # noqa: E501 'greenflow_cusignal_plugin.windows = greenflow_cusignal_plugin.windows' # noqa: E501 ], } )

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acf5088785c6f06655057edb0c495d78fce0fca9

33

py

Python

tests/__init__.py

lakshayarora476/TSIClient

8d911d8beac3259d0fe86446e6526c1c8d53b74f

[ "MIT" ]

null

tests/__init__.py

lakshayarora476/TSIClient

8d911d8beac3259d0fe86446e6526c1c8d53b74f

[ "MIT" ]

null

tests/__init__.py

lakshayarora476/TSIClient

8d911d8beac3259d0fe86446e6526c1c8d53b74f

[ "MIT" ]

null

from TSIClient import TSIClient

16.5

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null

0

1

0

1

0

1

0

6

4a16fce57e525d7542a7b15a19451f6a8ffc1df0

304

py

Python

tests/data/project1/file1.py

Polyconseil/check-oldies

0d0d9632281d14f652e71ac2c0db3b0cbf9b089c

[ "BSD-3-Clause" ]

4

2020-10-27T16:18:57.000Z

2020-12-01T10:58:19.000Z

tests/data/project1/file1.py

Polyconseil/check-oldies

0d0d9632281d14f652e71ac2c0db3b0cbf9b089c

[ "BSD-3-Clause" ]

1

2020-11-18T14:04:10.000Z

2020-11-18T15:29:44.000Z

tests/data/project1/file1.py

Polyconseil/check-oldies

0d0d9632281d14f652e71ac2c0db3b0cbf9b089c

[ "BSD-3-Clause" ]

null

# TIMEBOMB: report me a = 1 # TIMEBOMB (jsmith): report me # TIMEBOMB: do not report me (pragma). # no-check-fixmes # TIMEBOMB(jsmith - 2020-04-25): report me a = "TIMEBOMB" # do not report me (within a string) a = "TIMEBOMB" # do not report me (within a string) # TIMEBOMB - FEWTURE-BOOM: report me

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1

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null

0

1

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6

4a1833f2e874f31cd4232fbe5bda65f63de3b0ac

43

py

Python

src/audisto_exporter/__init__.py

ZeitOnline/audisto_exporter

9d1b1771c9ec38f0c512f4736b97fd7f3432e904

[ "BSD-3-Clause" ]

null

src/audisto_exporter/__init__.py

ZeitOnline/audisto_exporter

9d1b1771c9ec38f0c512f4736b97fd7f3432e904

[ "BSD-3-Clause" ]

1

2021-06-24T11:32:59.000Z

src/audisto_exporter/__init__.py

ZeitOnline/audisto_exporter

9d1b1771c9ec38f0c512f4736b97fd7f3432e904

[ "BSD-3-Clause" ]

null

from audisto_exporter.exporter import main

21.5

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null

0

1

0

1

0

1

0

6

4a254d47f70fe89c5643e5985dd52d55f47dfd33

42

py

Python

hpvm/projects/predtuner/predtuner/approxes/__init__.py

vzyrianov/hpvm-autograd

521cc3b684531548aea75f9fe3cc673aaa4a2e90

[ "Apache-2.0" ]

null

hpvm/projects/predtuner/predtuner/approxes/__init__.py

vzyrianov/hpvm-autograd

521cc3b684531548aea75f9fe3cc673aaa4a2e90

[ "Apache-2.0" ]

null

hpvm/projects/predtuner/predtuner/approxes/__init__.py

vzyrianov/hpvm-autograd

521cc3b684531548aea75f9fe3cc673aaa4a2e90

[ "Apache-2.0" ]

null

from .approxes import get_knobs_from_file

21

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null

0

1

0

1

0

1

0

6

c59362cab4594afa05e3f2674aeb5ede17f7bfc4

25

py

Python

recport/__init__.py

CircleOnCircles/recport

371f8af612f7a0787eab9267ffe65f372c7badb2

[ "MIT" ]

null

recport/__init__.py

CircleOnCircles/recport

371f8af612f7a0787eab9267ffe65f372c7badb2

[ "MIT" ]

null

recport/__init__.py

CircleOnCircles/recport

371f8af612f7a0787eab9267ffe65f372c7badb2

[ "MIT" ]

1

2020-02-03T13:52:22.000Z

from .portfolio import *

12.5

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null

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1

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1

0

1

0

6

681919366bd3448b7c6281a35f618ace8e1ef4be

2,462

py

Python

tests/system/action/meeting/test_replace_projector_id.py

MJJojo97/openslides-backend

af0d1edb0070e352d46f285a1ba0bbe3702d49ae

[ "MIT" ]

null

tests/system/action/meeting/test_replace_projector_id.py

MJJojo97/openslides-backend

af0d1edb0070e352d46f285a1ba0bbe3702d49ae

[ "MIT" ]

19

2021-11-22T16:25:54.000Z

2021-11-25T13:38:13.000Z

tests/system/action/meeting/test_replace_projector_id.py

MJJojo97/openslides-backend

af0d1edb0070e352d46f285a1ba0bbe3702d49ae

[ "MIT" ]

null

from tests.system.action.base import BaseActionTestCase class MeetingReplaceProjectorIdTest(BaseActionTestCase): def setUp(self) -> None: super().setUp() self.set_models( { "meeting/1": { "default_projector_$_id": ["motion"], "default_projector_$motion_id": 11, "reference_projector_id": 20, "is_active_in_organization_id": 1, }, "projector/11": { "used_as_default_$motion_in_meeting_id": 1, "used_as_default_$_in_meeting_id": ["motion"], }, "projector/20": { "used_as_reference_projector_meeting_id": 1, }, } ) def test_replacing(self) -> None: response = self.request( "meeting.replace_projector_id", {"id": 1, "projector_id": 11} ) self.assert_status_code(response, 200) meeting = self.get_model("meeting/1") assert meeting.get("default_projector_$_id") == ["motion"] assert meeting.get("default_projector_$motion_id") == 20 assert meeting.get("reference_projector_id") == 20 projector_11 = self.get_model("projector/11") assert projector_11.get("used_as_default_$motion_in_meeting_id") is None projector_20 = self.get_model("projector/20") assert projector_20.get("used_as_reference_projector_meeting_id") == 1 assert projector_20.get("used_as_default_$motion_in_meeting_id") == 1 assert projector_20.get("used_as_default_$_in_meeting_id") == ["motion"] def test_no_replacing(self) -> None: response = self.request( "meeting.replace_projector_id", {"id": 1, "projector_id": 12} ) self.assert_status_code(response, 200) meeting = self.get_model("meeting/1") assert meeting.get("default_projector_$_id") == ["motion"] assert meeting.get("default_projector_$motion_id") == 11 assert meeting.get("reference_projector_id") == 20 projector_11 = self.get_model("projector/11") assert projector_11.get("used_as_default_$motion_in_meeting_id") == 1 assert projector_11.get("used_as_default_$_in_meeting_id") == ["motion"] projector_20 = self.get_model("projector/20") assert projector_20.get("used_as_reference_projector_meeting_id") == 1

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null

0

1

0

null

0

6

a85ace768f4d863824637747325b058794211789

2,882

py

Python

karp/tests/integration/test_sql_uow.py

spraakbanken/karp-backend-v6-tmp

e5b78157bd999df18c188973ae2a337015b6f35d

[ "MIT" ]

1

2021-12-08T15:33:42.000Z

karp/tests/integration/test_sql_uow.py

spraakbanken/karp-backend-v6-tmp

e5b78157bd999df18c188973ae2a337015b6f35d

[ "MIT" ]

null

karp/tests/integration/test_sql_uow.py

spraakbanken/karp-backend-v6-tmp

e5b78157bd999df18c188973ae2a337015b6f35d

[ "MIT" ]

null

import pytest from karp.domain import model from karp.infrastructure.sql import sql_unit_of_work from karp.utility import unique_id def random_resource() -> model.Resource: return model.Resource( entity_id=unique_id.make_unique_id(), resource_id="abc", name="ABC", config={"fields": {}}, message="added", ) def random_entry(resource_id: str = None) -> model.Entry: return model.Entry( entity_id=unique_id.make_unique_id(), entry_id="abc..1", resource_id=resource_id or "abc", body={"id": "abc..1"}, message="added", ) class TestSqlResourceUnitOfWork: def test_rolls_back_uncommitted_work_by_default(self, sqlite_session_factory): uow = sql_unit_of_work.SqlResourceUnitOfWork(sqlite_session_factory) with uow: resource = random_resource() uow.resources.put(resource) new_session = sqlite_session_factory() rows = list(new_session.execute('SELECT * FROM "resources"')) assert rows == [] def test_rolls_back_on_error(self, sqlite_session_factory): class MyException(Exception): pass uow = sql_unit_of_work.SqlResourceUnitOfWork(sqlite_session_factory) with pytest.raises(MyException): with uow: resource = random_resource() uow.resources.put(resource) raise MyException() new_session = sqlite_session_factory() rows = list(new_session.execute('SELECT * FROM "resources"')) assert rows == [] class TestSqlEntryUnitOfWork: def test_rolls_back_uncommitted_work_by_default(self, sqlite_session_factory): uow = sql_unit_of_work.SqlEntryUnitOfWork( {"resource_id": "abc", "table_name": "abc"}, resource_config={"resource_id": "abc", "config": {}}, session_factory=sqlite_session_factory, ) with uow: entry = random_entry(resource_id="abc") uow.entries.put(entry) new_session = sqlite_session_factory() rows = list(new_session.execute('SELECT * FROM "resources"')) assert rows == [] def test_rolls_back_on_error(self, sqlite_session_factory): class MyException(Exception): pass uow = sql_unit_of_work.SqlEntryUnitOfWork( {"resource_id": "abc", "table_name": "abc"}, resource_config={"resource_id": "abc", "config": {}}, session_factory=sqlite_session_factory, ) with pytest.raises(MyException): with uow: entry = random_entry(resource_id="abc") uow.entries.put(entry) raise MyException() new_session = sqlite_session_factory() rows = list(new_session.execute('SELECT * FROM "resources"')) assert rows == []

32.75

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0

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0

1

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1

0

null

0

6

a86c86de616a09799680ced1a9ed9952c4d86b29

38

py

Python

src/automagic_imaging/scripts/__init__.py

univ-of-utah-marriott-library-apple/radmind_auto_image_creator

84ede339c7e060068bba91d627d10d7d15fc743e

[ "MIT" ]

2

2015-06-25T05:33:23.000Z

2018-03-04T06:11:54.000Z

src/automagic_imaging/scripts/__init__.py

univ-of-utah-marriott-library-apple/radmind_auto_image_creator

84ede339c7e060068bba91d627d10d7d15fc743e

[ "MIT" ]

null

src/automagic_imaging/scripts/__init__.py

univ-of-utah-marriott-library-apple/radmind_auto_image_creator

84ede339c7e060068bba91d627d10d7d15fc743e

[ "MIT" ]

null

import logger, parse_options, radmind

19

37

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5

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null

0

1

0

1

0

1

0

6

a8b2d188a08bbe1de71b93b1c3c0339bf1b59b6a

29

py

Python

plugins/pelican_alias/__init__.py

fferegrino/yet-another-blog-migration

1e7e95768af0d86d0a890b4582ef70c44b995e8e

[ "Apache-2.0" ]

null

plugins/pelican_alias/__init__.py

fferegrino/yet-another-blog-migration

1e7e95768af0d86d0a890b4582ef70c44b995e8e

[ "Apache-2.0" ]

36

2019-04-30T22:01:52.000Z

2019-08-15T18:01:36.000Z

plugins/pelican_alias/__init__.py

fferegrino/yet-another-blog-migration

1e7e95768af0d86d0a890b4582ef70c44b995e8e

[ "Apache-2.0" ]

null

from .pelican_alias import *

14.5

28

0.793103

4

29

5.5

1

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1

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0.88

0

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1

0

null

0

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null

0

1

0

1

0

1

0

6

a8d3ffefb6a36b0e99d1e3b83f06a466e6e4b38a

535

py

Python

tests/response/test_generate_link_response.py

jeremydeanlakey/lakey-finicity-python

f0b5ae6febb9337f0e28731f631b726fca940d2c

[ "MIT" ]

1

2021-02-09T14:44:55.000Z

tests/response/test_generate_link_response.py

jeremydeanlakey/lakey-finicity-python

f0b5ae6febb9337f0e28731f631b726fca940d2c

[ "MIT" ]

null

tests/response/test_generate_link_response.py

jeremydeanlakey/lakey-finicity-python

f0b5ae6febb9337f0e28731f631b726fca940d2c

[ "MIT" ]

1

2022-01-26T18:09:33.000Z

DOCS_EXAMPLE_GENERATE_LINK_RESPONSE = { "link": "https://connect.lakey_finicity.com?analytics=google%3AUA-123456789-1&consumerId=1cb21a38d006a384cf0376d12f2ddfef&customerId=12345678&partnerId=12345678921234&redirectUri=https%3A%2F%2Fwww.lakey_finicity.com&signature=b5fd21d087c06d0a7442b6fa85e7added988b057ab11717b7e37f650878b2dd2&timestamp=1564070902134&type=voa&webhook=https%3A%2F%2Facme-lending.com/webhook&webhookContentType=application%2Fjson&webhookData=%7B%22value1%22%3A%22123456789%22%2C%22value2%22%3A%2201Mar19%22%7D" }

133.75

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7.491803

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0

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null

0

6

a8d551833bc2154a534b7f5f037dac6d48c89659

603

py

Python

cancer-immune/EMEWS-scripts/python/stats.py

rheiland/PhysiCell-EMEWS-2

ec6ae7dab314b839f46a152ce9f5905155012d48

[ "BSD-3-Clause" ]

null

cancer-immune/EMEWS-scripts/python/stats.py

rheiland/PhysiCell-EMEWS-2

ec6ae7dab314b839f46a152ce9f5905155012d48

[ "BSD-3-Clause" ]

null

cancer-immune/EMEWS-scripts/python/stats.py

rheiland/PhysiCell-EMEWS-2

ec6ae7dab314b839f46a152ce9f5905155012d48

[ "BSD-3-Clause" ]

2

2019-05-24T02:42:11.000Z

2021-07-12T12:19:46.000Z

import statistics import builtins def min(vals): fl = [v for x in vals for v in x if v != 9999999999] if len(fl) == 0: return -1 return builtins.min(fl) def max(vals): fl = [v for x in vals for v in x if v != 9999999999] if len(fl) == 0: return -1 return builtins.max(fl) def mean(vals): fl = [v for x in vals for v in x if v != 9999999999] if len(fl) == 0: return -1 return statistics.mean(fl) def std(vals): fl = [v for x in vals for v in x if v != 9999999999] if len(fl) == 0: return -1 return statistics.pstdev(fl)

22.333333

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null

0

1

0

6

763e28bdaae93c07326b7b64c69db34d0ba6e1fc

6,336

py

Python

starry/_core/ops/integration.py

shashankdholakia/starry

5619cc9823651a69f1230ead8fc87eb75a9d682e

[ "MIT" ]

null

starry/_core/ops/integration.py

shashankdholakia/starry

5619cc9823651a69f1230ead8fc87eb75a9d682e

[ "MIT" ]

null

starry/_core/ops/integration.py

shashankdholakia/starry

5619cc9823651a69f1230ead8fc87eb75a9d682e

[ "MIT" ]

null

# -*- coding: utf-8 -*- from ...compat import Apply, Op, tt import numpy as np __all__ = ["sTOp", "rTReflectedOp", "sTReflectedOp"] class sTOp(Op): def __init__(self, func, N): self.func = func self.N = N self._grad_op = sTGradientOp(self) def make_node(self, *inputs): inputs = [tt.as_tensor_variable(i) for i in inputs] outputs = [tt.TensorType(inputs[-1].dtype, (False, False))()] return Apply(self, inputs, outputs) def infer_shape(self, *args): shapes = args[-1] return [shapes[0] + (tt.as_tensor(self.N),)] def R_op(self, inputs, eval_points): if eval_points[0] is None: return eval_points return self.grad(inputs, eval_points) def perform(self, node, inputs, outputs): outputs[0][0] = self.func(*inputs) def grad(self, inputs, gradients): return self._grad_op(*(inputs + gradients)) class sTGradientOp(Op): def __init__(self, base_op): self.base_op = base_op def make_node(self, *inputs): inputs = [tt.as_tensor_variable(i) for i in inputs] outputs = [i.type() for i in inputs[:-1]] return Apply(self, inputs, outputs) def infer_shape(self, *args): shapes = args[-1] return shapes[:-1] def perform(self, node, inputs, outputs): bb, br = self.base_op.func(*inputs) outputs[0][0] = np.reshape(bb, np.shape(inputs[0])) outputs[1][0] = np.reshape(br, np.shape(inputs[1])) class rTReflectedOp(Op): def __init__(self, func, N): self.func = func self.N = N self._grad_op = rTReflectedGradientOp(self) def make_node(self, *inputs): inputs = [tt.as_tensor_variable(i) for i in inputs] outputs = [ tt.TensorType(inputs[-1].dtype, (False, False))(), tt.TensorType(inputs[-1].dtype, (False, False))(), tt.TensorType(inputs[-1].dtype, (False, False))(), ] return Apply(self, inputs, outputs) def infer_shape(self, *args): shapes = args[-1] return [ shapes[0] + (tt.as_tensor(self.N),), shapes[0] + (tt.as_tensor(self.N),), shapes[0] + (tt.as_tensor(self.N),), ] def R_op(self, inputs, eval_points): if eval_points[0] is None: return eval_points return self.grad(inputs, eval_points) def perform(self, node, inputs, outputs): (b, sigr) = inputs rT, ddb, ddsigr = self.func(b, sigr) outputs[0][0] = rT outputs[1][0] = ddb outputs[2][0] = ddsigr def grad(self, inputs, gradients): results = self(*inputs) grad = self._grad_op(*(inputs + results + [gradients[0]])) return grad class rTReflectedGradientOp(Op): def __init__(self, base_op): self.base_op = base_op def make_node(self, *inputs): inputs = [tt.as_tensor_variable(i) for i in inputs] outputs = [i.type() for i in inputs[:2]] return Apply(self, inputs, outputs) def infer_shape(self, *args): shapes = args[-1] return shapes[:2] def perform(self, node, inputs, outputs): b, sigr, rT, ddb, ddsigr, brT = inputs bb = (brT * ddb).sum(-1) bsigr = (brT * ddsigr).sum() outputs[0][0] = np.reshape(bb, np.shape(b)) outputs[1][0] = np.array(np.reshape(bsigr, np.shape(sigr))) class sTReflectedOp(Op): def __init__(self, func, N): self.func = func self.N = N self._grad_op = sTReflectedGradientOp(self) def make_node(self, *inputs): inputs = [tt.as_tensor_variable(i) for i in inputs] outputs = [ tt.TensorType(inputs[-1].dtype, (False, False))(), tt.TensorType(inputs[-1].dtype, (False, False))(), tt.TensorType(inputs[-1].dtype, (False, False))(), tt.TensorType(inputs[-1].dtype, (False, False))(), tt.TensorType(inputs[-1].dtype, (False, False))(), tt.TensorType(inputs[-1].dtype, (False, False))(), ] return Apply(self, inputs, outputs) def infer_shape(self, *args): shapes = args[-1] return [ shapes[0] + (tt.as_tensor(self.N),), shapes[0] + (tt.as_tensor(self.N),), shapes[0] + (tt.as_tensor(self.N),), shapes[0] + (tt.as_tensor(self.N),), shapes[0] + (tt.as_tensor(self.N),), shapes[0] + (tt.as_tensor(self.N),), ] def R_op(self, inputs, eval_points): if eval_points[0] is None: return eval_points return self.grad(inputs, eval_points) def perform(self, node, inputs, outputs): b, theta, bo, ro, sigr = inputs sT, ddb, ddtheta, ddbo, ddro, ddsigr = self.func( b, theta, bo, ro, sigr ) outputs[0][0] = sT outputs[1][0] = ddb outputs[2][0] = ddtheta outputs[3][0] = ddbo outputs[4][0] = ddro outputs[5][0] = ddsigr def grad(self, inputs, gradients): results = self(*inputs) grad = self._grad_op(*(inputs + results + [gradients[0]])) return grad class sTReflectedGradientOp(Op): def __init__(self, base_op): self.base_op = base_op def make_node(self, *inputs): inputs = [tt.as_tensor_variable(i) for i in inputs] outputs = [i.type() for i in inputs[:5]] return Apply(self, inputs, outputs) def infer_shape(self, *args): shapes = args[-1] return shapes[:5] def perform(self, node, inputs, outputs): ( b, theta, bo, ro, sigr, sT, ddb, ddtheta, ddbo, ddro, ddsigr, bsT, ) = inputs bb = (bsT * ddb).sum(-1) btheta = (bsT * ddtheta).sum(-1) bbo = (bsT * ddbo).sum(-1) bro = (bsT * ddro).sum() bsigr = (bsT * ddsigr).sum() outputs[0][0] = np.reshape(bb, np.shape(b)) outputs[1][0] = np.reshape(btheta, np.shape(theta)) outputs[2][0] = np.reshape(bbo, np.shape(bo)) outputs[3][0] = np.array(np.reshape(bro, np.shape(ro))) outputs[4][0] = np.array(np.reshape(bsigr, np.shape(sigr)))

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6,336

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0.353293

0

null

0

1

0

null

0

6

767a3ccb69f855fe3fdb99e127c48479410a52ae

399

py

Python

tests/test_models.py

softformance/django-facebook-photo-api

0750140f322a195d69e7fb64c8792efe3f75f073

[ "MIT" ]

null

tests/test_models.py

softformance/django-facebook-photo-api

0750140f322a195d69e7fb64c8792efe3f75f073

[ "MIT" ]

null

tests/test_models.py

softformance/django-facebook-photo-api

0750140f322a195d69e7fb64c8792efe3f75f073

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ test_Django-Facebook-photo-api ------------ Tests for `Django-Facebook-photo-api` models module. """ from django.test import TestCase from django_facebook_photo_api import models class TestDjango_facebook_photo_api(TestCase): def setUp(self): pass def test_something(self): pass def tearDown(self): pass

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0.202335

0.249027

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399

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null

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1

0

1

0

6

767c925602ef009b0d9a443b436a4c5d856ed7ef

11,860

py

Python

plgx-esp/tests/test_functional/test_logging.py

eclecticiq/eiq-er-ce

ebb12d5c4e0ee144f8166576924b8ce8dc5dfc94

[ "MIT" ]

null

plgx-esp/tests/test_functional/test_logging.py

eclecticiq/eiq-er-ce

ebb12d5c4e0ee144f8166576924b8ce8dc5dfc94

[ "MIT" ]

null

plgx-esp/tests/test_functional/test_logging.py

eclecticiq/eiq-er-ce

ebb12d5c4e0ee144f8166576924b8ce8dc5dfc94

[ "MIT" ]

2

2021-11-12T10:25:02.000Z

2022-03-30T06:33:52.000Z

import datetime as dt import gzip import io import json from flask import url_for from polylogyx.db.models import ResultLog import time class TestLogging: def test_bad_post_request(self, node, testapp): resp = testapp.post(url_for("api.logger"), {"foo": "bar"}, expect_errors=True) assert not resp.normal_body def test_missing_node_key(self, node, testapp): resp = testapp.post_json( url_for("api.logger"), {"foo": "bar"}, expect_errors=True ) assert not resp.normal_body # assert resp.json == {'node_invalid': True} def test_status_log_created_for_node(self, node, testapp): data = { "line": 1, "message": "This is a test of the emergency broadcast system.", "severity": 1, "filename": "foobar.cpp", } assert not node.status_logs.count() resp = testapp.post_json( url_for("api.logger"), { "node_key": node.node_key, "data": [data], "log_type": "status", }, extra_environ=dict(REMOTE_ADDR="127.0.0.2"), expect_errors=True, ) assert node.status_logs.count() assert node.status_logs[0].line == data["line"] assert node.status_logs[0].message == data["message"] assert node.status_logs[0].severity == data["severity"] assert node.status_logs[0].filename == data["filename"] assert node.last_ip == "127.0.0.2" def test_status_log_created_for_node_put(self, node, testapp): data = { "line": 1, "message": "This is a test of the emergency broadcast system.", "severity": 1, "filename": "foobar.cpp", } assert not node.status_logs.count() resp = testapp.put_json( url_for("api.logger"), { "node_key": node.node_key, "data": [data], "log_type": "status", }, extra_environ=dict(REMOTE_ADDR="127.0.0.2"), expect_errors=True, ) assert node.status_logs.count() assert node.status_logs[0].line == data["line"] assert node.status_logs[0].message == data["message"] assert node.status_logs[0].severity == data["severity"] assert node.status_logs[0].filename == data["filename"] assert node.last_ip == "127.0.0.2" def test_status_log_created_for_node_when_gzipped(self, node, testapp): data = { "line": 1, "message": "This is a test of the emergency broadcast system.", "severity": 1, "filename": "foobar.cpp", } assert not node.status_logs.count() fileobj = io.BytesIO() gzf = gzip.GzipFile(fileobj=fileobj, mode="wb") gzf.write( json.dumps( { "node_key": node.node_key, "data": [data], "log_type": "status", } ).encode("utf-8") ) gzf.close() resp = testapp.post( url_for("api.logger"), fileobj.getvalue(), headers={"Content-Encoding": "gzip", "Content-Type": "application/json"}, extra_environ=dict(REMOTE_ADDR="127.0.0.2"), expect_errors=True, ) assert node.status_logs.count() assert node.status_logs[0].line == data["line"] assert node.status_logs[0].message == data["message"] assert node.status_logs[0].severity == data["severity"] assert node.status_logs[0].filename == data["filename"] assert node.last_ip == "127.0.0.2" def test_no_status_log_created_when_data_is_empty(self, node, testapp,celery_worker): assert not node.status_logs.count() resp = testapp.post_json( url_for("api.logger"), { "node_key": node.node_key, "data": [], "log_type": "status", }, extra_environ=dict(REMOTE_ADDR="127.0.0.2"), expect_errors=True, ) assert not node.status_logs.count() assert node.last_ip == "127.0.0.2" def test_result_log_created_for_node(self,testapp,db,node,celery_worker): now = dt.datetime.utcnow() data = [ { "diffResults": { "added": [ { "name": "osqueryd", "path": "/usr/local/bin/osqueryd", "pid": "97830", } ], "removed": [ { "name": "osqueryd", "path": "/usr/local/bin/osqueryd", "pid": "97650", } ], }, "name": "processes", "hostIdentifier": "hostname.local", "calendarTime": "%s %s" % (now.ctime(), "UTC"), "unixTime": now.strftime("%s"), } ] assert not node.result_logs.count() resp = testapp.post_json( url_for("api.logger"), { "node_key": node.node_key, "data": data, "log_type": "result", }, extra_environ=dict(REMOTE_ADDR="127.0.0.2"), expect_errors=True, ) time.sleep(5) assert node.result_logs.count() == 2 assert node.last_ip == "127.0.0.2" added = ResultLog.query.filter(ResultLog.node==node).filter(ResultLog.action=="added").first() removed = ResultLog.query.filter(ResultLog.node==node).filter(ResultLog.action=="removed").first() assert added.name == data[0]["name"] assert added.columns == data[0]["diffResults"]["added"][0] assert removed.name == data[0]["name"] assert removed.columns == data[0]["diffResults"]["removed"][0] def test_no_result_log_created_when_data_is_empty(self, node, testapp): assert not node.result_logs.count() resp = testapp.post_json( url_for("api.logger"), { "node_key": node.node_key, "data": [], "log_type": "result", }, extra_environ=dict(REMOTE_ADDR="127.0.0.2"), expect_errors=True, ) assert not node.result_logs.count() # assert node.last_ip == "127.0.0.2" def test_result_event_format(self,testapp,db,node,celery_worker): now = dt.datetime.utcnow() calendarTime = "%s %s" % (now.ctime(), "UTC") unixTime = now.strftime("%s") data = [ { "action": "added", "columns": { "name": "osqueryd", "path": "/usr/local/bin/osqueryd", "pid": "97830", }, "name": "osquery", "hostIdentifier": "hostname.local", "calendarTime": calendarTime, "unixTime": unixTime, }, { "action": "removed", "columns": { "name": "osqueryd", "path": "/usr/local/bin/osqueryd", "pid": "97830", }, "name": "osquery", "hostIdentifier": "hostname.local", "calendarTime": calendarTime, "unixTime": unixTime, }, { "action": "added", "columns": { "name": "osqueryd", "path": "/usr/local/bin/osqueryd", "pid": "97830", }, "name": "processes", "hostIdentifier": "hostname.local", "calendarTime": calendarTime, "unixTime": unixTime, }, { "action": "removed", "columns": { "name": "osqueryd", "path": "/usr/local/bin/osqueryd", "pid": "97830", }, "name": "processes", "hostIdentifier": "hostname.local", "calendarTime": calendarTime, "unixTime": unixTime, }, ] assert not node.result_logs.count() resp = testapp.post_json( url_for("api.logger"), { "node_key": node.node_key, "data": data, "log_type": "result", }, extra_environ=dict(REMOTE_ADDR="127.0.0.2"), expect_errors=True, ) time.sleep(5) assert node.result_logs.count() == 4 assert node.last_ip == "127.0.0.2" added = ResultLog.query.filter(ResultLog.node==node).filter(ResultLog.action=="added").count() removed = ResultLog.query.filter(ResultLog.node==node).filter(ResultLog.action=="removed").count() assert added == 2 assert removed == 2 def test_heterogeneous_result_format(self,testapp,db,node,celery_worker): now = dt.datetime.utcnow() calendarTime = "%s %s" % (now.ctime(), "UTC") unixTime = now.strftime("%s") data = [ { "action": "removed", "columns": { "name": "osqueryd", "path": "/usr/local/bin/osqueryd", "pid": "97830", }, "name": "processes", "hostIdentifier": "hostname.local", "calendarTime": calendarTime, "unixTime": unixTime, }, { "diffResults": { "added": [ { "name": "osqueryd", "path": "/usr/local/bin/osqueryd", "pid": "97830", } ], "removed": [ { "name": "osqueryd", "path": "/usr/local/bin/osqueryd", "pid": "97650", } ], }, "name": "processes", "hostIdentifier": "hostname.local", "calendarTime": calendarTime, "unixTime": unixTime, }, { "calendarTime": calendarTime, "unixTime": unixTime, "action": "snapshot", "snapshot": [ {"parent": "0", "path": "/sbin/launchd", "pid": "1"}, {"parent": "1", "path": "/usr/sbin/syslogd", "pid": "51"}, {"parent": "1", "path": "/usr/libexec/UserEventAgent", "pid": "52"}, {"parent": "1", "path": "/usr/libexec/kextd", "pid": "54"}, ], "name": "process_snapshot", "name": "file_events", "hostIdentifier": "hostname.local", }, ] assert not node.result_logs.count() resp = testapp.post_json( url_for("api.logger"), { "node_key": node.node_key, "data": data, "log_type": "result", }, extra_environ=dict(REMOTE_ADDR="127.0.0.2"), expect_errors=True, ) time.sleep(10) assert node.result_logs.count() == 7 assert node.last_ip == "127.0.0.2"

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null

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6

7696a576f92f3e242bcfaf5fa51c1343f1aaa4d7

231

py

Python

doac/exceptions/invalid_client.py

EE/doac

ffc26fe8222e61cadbaa138b7e36d749de663e68

[ "MIT" ]

19

2015-01-02T12:16:59.000Z

2018-10-10T14:56:03.000Z

doac/exceptions/invalid_client.py

EE/doac

ffc26fe8222e61cadbaa138b7e36d749de663e68

[ "MIT" ]

2

2015-05-28T17:29:34.000Z

2016-05-24T15:50:30.000Z

doac/exceptions/invalid_client.py

EE/doac

ffc26fe8222e61cadbaa138b7e36d749de663e68

[ "MIT" ]

10

2015-03-03T10:37:44.000Z

2018-10-10T14:56:10.000Z

from .base import InvalidClient class ClientDoesNotExist(InvalidClient): reason = "The client was malformed or invalid." class ClientSecretNotValid(InvalidClient): reason = "The client secret was malformed or invalid."

23.1

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null

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1

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6

76a91d830647a56c5c9c2cc5585274603655152f

187

py

Python

tests/conftest.py

arne-cl/discoursegraphs

4e14688e19c980ac9bbac75ff1bf5d751ef44ac3

[ "BSD-3-Clause" ]

41

2015-02-20T00:35:39.000Z

2022-03-15T13:54:13.000Z

tests/conftest.py

arne-cl/discoursegraphs

4e14688e19c980ac9bbac75ff1bf5d751ef44ac3

[ "BSD-3-Clause" ]

68

2015-01-09T18:07:38.000Z

2021-10-06T16:30:43.000Z

tests/conftest.py

arne-cl/discoursegraphs

4e14688e19c980ac9bbac75ff1bf5d751ef44ac3

[ "BSD-3-Clause" ]

8

2015-02-20T00:35:48.000Z

2021-10-30T14:09:03.000Z

from discoursegraphs.corpora import pcc def pytest_namespace(): """these objects/variables are available to all tests in the test suite""" return {'maz_1423': pcc['maz-1423']}

23.375

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0

1

0

1

0

6

4f4cf462380fbc20db6f843ec67d6921e87dff07

203

py

Python

mksc/feature/values/__init__.py

HelloCoyen/mksc2

ede038b87b7a46c2872ac9ae744c4dbfe5d6fe48

[ "MIT" ]

null

mksc/feature/values/__init__.py

HelloCoyen/mksc2

ede038b87b7a46c2872ac9ae744c4dbfe5d6fe48

[ "MIT" ]

null

mksc/feature/values/__init__.py

HelloCoyen/mksc2

ede038b87b7a46c2872ac9ae744c4dbfe5d6fe48

[ "MIT" ]

null

from .abnormal import fix_abnormal_value from .missing import fix_missing_value from .normalization import normalization from .scale import fix_scaling from .standard import fix_standard, logarithmetics

33.833333

50

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0

1

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1

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6

96d84256259e44d892215cc82e4e515b4941110a

26,300

py

Python

saas/add_env.py

kerven88/opsany-paas

78b83d0b6a46f3e70226ca99992d736b2af0af72

[ "Apache-2.0" ]

null

saas/add_env.py

kerven88/opsany-paas

78b83d0b6a46f3e70226ca99992d736b2af0af72

[ "Apache-2.0" ]

null

saas/add_env.py

kerven88/opsany-paas

78b83d0b6a46f3e70226ca99992d736b2af0af72

[ "Apache-2.0" ]

null

""" mysql-connector==2.2.9 SQLAlchemy==1.4.22 """ import os import sys import datetime import configparser from sqlalchemy import Column, DateTime, ForeignKey, String, create_engine, Index from sqlalchemy.dialects.mysql import INTEGER, LONGTEXT, SMALLINT, TINYINT from sqlalchemy.orm import relationship, sessionmaker from sqlalchemy.ext.declarative import declarative_base from urllib import parse # change dir to install os.chdir('../install') # testify file if exists if not os.path.exists('install.config'): sys.exit('install config is not exists.') read_install_config = configparser.ConfigParser() try: read_install_config.read('install.config') config_dict = dict(read_install_config) except Exception as e: print(e) sys.exit('file context is wrong.') def replace_str(data): if not data: return None return data.replace("\"", "").replace("\'", "") MYSQL_SERVER_IP = replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP", "127.0.0.1")) MYSQL_ROOT_PASSWORD = replace_str(config_dict.get("mysql").get("MYSQL_ROOT_PASSWORD", "OpsAny@2020")) try: db = create_engine("mysql+mysqlconnector://root:{}@{}/opsany_paas".format(parse.quote_plus(MYSQL_ROOT_PASSWORD), MYSQL_SERVER_IP)) Base = declarative_base(db) def to_dict(self): return {c.name: getattr(self, c.name, None) for c in self.__table__.columns} Base.to_dict = to_dict except Exception as e: print("Script error: {}".format(str(e))) sys.exit('connect sql is failed. Please check mysql server!') envs = [ { "app_code": "cmdb", "env": [ # CMDB count 8 {"key": "UPLOAD_PATH", "value": replace_str(config_dict.get('opsany_saas').get("UPLOAD_PATH")), "env_scope": "all", "intro": "uploads path"}, {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_CMDB_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "MONGO_HOST", "value": replace_str(config_dict.get('mongodb').get("MONGO_SERVER_IP")), "env_scope": "all", "intro": "mongo host"}, {"key": "MONGO_PORT", "value": replace_str(config_dict.get('mongodb').get("MONGO_PORT")), "env_scope": "all", "intro": "mongo port"}, {"key": "MONGO_PASSWORD", "value": replace_str(config_dict.get('mongodb').get("MONGO_CMDB_PASSWORD")), "env_scope": "all", "intro": "mongo password"}, # {"key": "DEFAULT_USER_ICON", "value": read_install_config.get("DEFAULT_USER_ICON"), "env_scope": "all", "intro": "user default icon"}, ] },{ "app_code": "cmp", "env": [ # CMP count 7 {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_CMP_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "MONGO_HOST", "value": replace_str(config_dict.get('mongodb').get("MONGO_SERVER_IP")), "env_scope": "all", "intro": "mongo host"}, {"key": "MONGO_PORT", "value": replace_str(config_dict.get('mongodb').get("MONGO_PORT")), "env_scope": "all", "intro": "mongo port"}, {"key": "MONGO_PASSWORD", "value": replace_str(config_dict.get('mongodb').get("MONGO_CMP_PASSWORD")), "env_scope": "all", "intro": "mongo password"}, # {"key": "DEFAULT_USER_ICON", "value": read_install_config.get("DEFAULT_USER_ICON"), "env_scope": "all", "intro": "user default icon"}, ] },{ "app_code": "job", "env": [ # JOB count 10 {"key": "UPLOAD_PATH", "value": replace_str(config_dict.get('opsany_saas').get("UPLOAD_PATH")), "env_scope": "all", "intro": "uploads path"}, {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_JOB_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "FILE_ROOT", "value": replace_str(config_dict.get('opsany_saas').get("FILE_ROOT")), "env_scope": "all", "intro": "Salt file root"}, {"key": "PILLAR_ROOT", "value": replace_str(config_dict.get('opsany_saas').get("PILLAR_ROOT")), "env_scope": "all", "intro": "Salt pillar root"}, {"key": "MONGO_HOST", "value": replace_str(config_dict.get('mongodb').get("MONGO_SERVER_IP")), "env_scope": "all", "intro": "mongo host"}, {"key": "MONGO_PORT", "value": replace_str(config_dict.get('mongodb').get("MONGO_PORT")), "env_scope": "all", "intro": "mongo port"}, {"key": "MONGO_PASSWORD", "value": replace_str(config_dict.get('mongodb').get("MONGO_JOB_PASSWORD")), "env_scope": "all", "intro": "mongo password"}, {"key": "REDIS_HOST", "value": replace_str(config_dict.get("redis").get("REDIS_SERVER_IP")), "env_scope": "all", "intro": "redis host"}, {"key": "REDIS_PORT", "value": replace_str(config_dict.get("redis").get("REDIS_PORT")), "env_scope": "all", "intro": "redis port"}, {"key": "REDIS_PASSWORD", "value": replace_str(config_dict.get("redis").get("REDIS_SERVER_PASSWORD")), "env_scope": "all", "intro": "redis password"}, # {"key": "DEFAULT_USER_ICON", "value": read_install_config.get("DEFAULT_USER_ICON"), "env_scope": "all", "intro": "user default icon"}, ] },{ "app_code": "workbench", "env": [ # WORKBENCH count 7 {"key": "UPLOAD_PATH", "value": replace_str(config_dict.get('opsany_saas').get("UPLOAD_PATH")), "env_scope": "all", "intro": "uploads path"}, {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_WORKBENCH_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "MONGO_HOST", "value": replace_str(config_dict.get('mongodb').get("MONGO_SERVER_IP")), "env_scope": "all", "intro": "mongo host"}, {"key": "MONGO_PORT", "value": replace_str(config_dict.get('mongodb').get("MONGO_PORT")), "env_scope": "all", "intro": "mongo port"}, {"key": "MONGO_PASSWORD", "value": replace_str(config_dict.get('mongodb').get("MONGO_WORKBENCH_PASSWORD")), "env_scope": "all", "intro": "mongo password"}, ] },{ "app_code": "rbac", "env": [ # RBAC count 4 {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_RBAC_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "UPLOAD_PATH", "value": replace_str(config_dict.get('opsany_saas').get("UPLOAD_PATH")), "env_scope": "all", "intro": "uploads path"}, ] },{ "app_code": "monitor", "env": [ # MONITOR count 10 {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_MONITOR_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "MONGO_HOST", "value": replace_str(config_dict.get('mongodb').get("MONGO_SERVER_IP")), "env_scope": "all", "intro": "mongo host"}, {"key": "MONGO_PORT", "value": replace_str(config_dict.get('mongodb').get("MONGO_PORT")), "env_scope": "all", "intro": "mongo port"}, {"key": "MONGO_PASSWORD", "value": replace_str(config_dict.get('mongodb').get("MONGO_MONITOR_PASSWORD")), "env_scope": "all", "intro": "mongo password"}, {"key": "ELASTIC_SEARCH_USERNAME", "value": replace_str(config_dict.get('elasticsearch').get("ELASTIC_SEARCH_USERNAME")), "env_scope": "all", "intro": "es username"}, {"key": "ES_PASSWORD", "value": replace_str(config_dict.get('elasticsearch').get("ES_PASSWORD")), "env_scope": "all", "intro": "es password"}, {"key": "ES_SERVER_IP", "value": replace_str(config_dict.get('elasticsearch').get("ES_SERVER_IP")), "env_scope": "all", "intro": "es host"}, {"key": "ELASTIC_PORT", "value": replace_str(config_dict.get('elasticsearch').get("ELASTIC_PORT")), "env_scope": "all", "intro": "es port"}, {"key": "ELASTIC_SEARCH_INDEX", "value": replace_str(config_dict.get('elasticsearch').get("ELASTIC_SEARCH_INDEX")), "env_scope": "all", "intro": "es index"}, {"key": "UPLOAD_PATH", "value": replace_str(config_dict.get('opsany_saas').get("UPLOAD_PATH")), "env_scope": "all", "intro": "uploads path"}, ] },{ "app_code": "control", "env": [ # CONTROL count 13 {"key": "UPLOAD_PATH", "value": replace_str(config_dict.get('opsany_saas').get("UPLOAD_PATH")), "env_scope": "all", "intro": "uploads path"}, {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_CONTROL_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "MONGO_HOST", "value": replace_str(config_dict.get('mongodb').get("MONGO_SERVER_IP")), "env_scope": "all", "intro": "mongo host"}, {"key": "MONGO_PORT", "value": replace_str(config_dict.get('mongodb').get("MONGO_PORT")), "env_scope": "all", "intro": "mongo port"}, {"key": "MONGO_PASSWORD", "value": replace_str(config_dict.get('mongodb').get("MONGO_CONTROL_PASSWORD")), "env_scope": "all", "intro": "mongo password"}, {"key": "REDIS_HOST", "value": replace_str(config_dict.get("redis").get("REDIS_SERVER_IP")), "env_scope": "all", "intro": "redis host"}, {"key": "REDIS_PORT", "value": replace_str(config_dict.get("redis").get("REDIS_PORT")), "env_scope": "all", "intro": "redis port"}, {"key": "REDIS_PASSWORD", "value": replace_str(config_dict.get("redis").get("REDIS_SERVER_PASSWORD")), "env_scope": "all", "intro": "redis password"}, {"key": "ROSTER_FILE_URL", "value": replace_str(config_dict.get('opsany_saas').get("ROSTER_FILE_URL")), "env_scope": "all", "intro": "roster file path"}, {"key": "SALT_SSH_FILE_URL", "value": replace_str(config_dict.get('opsany_saas').get("SALT_SSH_FILE_URL")), "env_scope": "all", "intro": "salt ssh file path"}, {"key": "ANSIBLE_HOST_KEY_CHECKING", "value": replace_str(config_dict.get("opsany_saas").get("ANSIBLE_HOST_KEY_CHECKING")), "env_scope": "all", "intro": "ansible vs host checking"}, # {"key": "DEFAULT_USER_ICON", "value": read_install_config.get("DEFAULT_USER_ICON"), "env_scope": "all", "intro": "user default icon"}, ] },{ "app_code": "devops", "env": [ # devops count 8 {"key": "UPLOAD_PATH", "value": replace_str(config_dict.get('opsany_saas').get("UPLOAD_PATH")), "env_scope": "all", "intro": "uploads path"}, {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_DEVOPS_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "MONGO_HOST", "value": replace_str(config_dict.get('mongodb').get("MONGO_SERVER_IP")), "env_scope": "all", "intro": "mongo host"}, {"key": "MONGO_PORT", "value": replace_str(config_dict.get('mongodb').get("MONGO_PORT")), "env_scope": "all", "intro": "mongo port"}, {"key": "MONGO_PASSWORD", "value": replace_str(config_dict.get('mongodb').get("MONGO_DEVOPS_PASSWORD")), "env_scope": "all", "intro": "mongo password"}, # {"key": "DEFAULT_USER_ICON", "value": read_install_config.get("DEFAULT_USER_ICON"), "env_scope": "all", "intro": "user default icon"}, ] },{ "app_code": "bastion", "env": [ # bastion count 8 {"key": "UPLOAD_PATH", "value": replace_str(config_dict.get('opsany_saas').get("UPLOAD_PATH")), "env_scope": "all", "intro": "uploads path"}, {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_BASTION_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "REDIS_HOST", "value": replace_str(config_dict.get("redis").get("REDIS_SERVER_IP")), "env_scope": "all", "intro": "redis host"}, {"key": "REDIS_PORT", "value": replace_str(config_dict.get("redis").get("REDIS_PORT")), "env_scope": "all", "intro": "redis port"}, {"key": "REDIS_PASSWORD", "value": replace_str(config_dict.get("redis").get("REDIS_SERVER_PASSWORD")), "env_scope": "all", "intro": "redis password"}, {"key": "TERMINAL_TIMEOUT", "value": replace_str(config_dict.get("redis").get("TERMINAL_TIMEOUT")), "env_scope": "all", "intro": "terminal timeout"}, ] }, { "app_code": "deploy", "env": [ # devops count 8 {"key": "UPLOAD_PATH", "value": replace_str(config_dict.get('opsany_saas').get("UPLOAD_PATH")), "env_scope": "all", "intro": "uploads path"}, {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_DEVOPS_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "MONGO_HOST", "value": replace_str(config_dict.get('mongodb').get("MONGO_SERVER_IP")), "env_scope": "all", "intro": "mongo host"}, {"key": "MONGO_PORT", "value": replace_str(config_dict.get('mongodb').get("MONGO_PORT")), "env_scope": "all", "intro": "mongo port"}, {"key": "MONGO_PASSWORD", "value": replace_str(config_dict.get('mongodb').get("MONGO_DEVOPS_PASSWORD")), "env_scope": "all", "intro": "mongo password"}, # {"key": "DEFAULT_USER_ICON", "value": read_install_config.get("DEFAULT_USER_ICON"), "env_scope": "all", "intro": "user default icon"}, ] }, { "app_code": "pipeline", "env": [ # pipeline count 8 {"key": "UPLOAD_PATH", "value": replace_str(config_dict.get('opsany_saas').get("UPLOAD_PATH")), "env_scope": "all", "intro": "uploads path"}, {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_DEVOPS_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "MONGO_HOST", "value": replace_str(config_dict.get('mongodb').get("MONGO_SERVER_IP")), "env_scope": "all", "intro": "mongo host"}, {"key": "MONGO_PORT", "value": replace_str(config_dict.get('mongodb').get("MONGO_PORT")), "env_scope": "all", "intro": "mongo port"}, {"key": "MONGO_PASSWORD", "value": replace_str(config_dict.get('mongodb').get("MONGO_DEVOPS_PASSWORD")), "env_scope": "all", "intro": "mongo password"}, # {"key": "DEFAULT_USER_ICON", "value": read_install_config.get("DEFAULT_USER_ICON"), "env_scope": "all", "intro": "user default icon"}, ] }, { "app_code": "repo", "env": [ # repo count 8 {"key": "UPLOAD_PATH", "value": replace_str(config_dict.get('opsany_saas').get("UPLOAD_PATH")), "env_scope": "all", "intro": "uploads path"}, {"key": "MYSQL_PASSWORD", "value": replace_str(config_dict.get('mysql').get("MYSQL_OPSANY_DEVOPS_PASSWORD")), "env_scope": "all", "intro": "mysql password"}, {"key": "MYSQL_HOST", "value": replace_str(config_dict.get('mysql').get("MYSQL_SERVER_IP")), "env_scope": "all", "intro": "mysql host"}, {"key": "MYSQL_PORT", "value": replace_str(config_dict.get('mysql').get("MYSQL_PORT")), "env_scope": "all", "intro": "mysql port"}, {"key": "MONGO_HOST", "value": replace_str(config_dict.get('mongodb').get("MONGO_SERVER_IP")), "env_scope": "all", "intro": "mongo host"}, {"key": "MONGO_PORT", "value": replace_str(config_dict.get('mongodb').get("MONGO_PORT")), "env_scope": "all", "intro": "mongo port"}, {"key": "MONGO_PASSWORD", "value": replace_str(config_dict.get('mongodb').get("MONGO_DEVOPS_PASSWORD")), "env_scope": "all", "intro": "mongo password"}, # {"key": "DEFAULT_USER_ICON", "value": read_install_config.get("DEFAULT_USER_ICON"), "env_scope": "all", "intro": "user default icon"}, ] } ] class PaasApptag(Base): __tablename__ = 'paas_apptags' id = Column(INTEGER(11), primary_key=True) name = Column(String(20), nullable=False, unique=True) code = Column(String(30), nullable=False, unique=True) index = Column(INTEGER(11), nullable=False) class PaasApp(Base): __tablename__ = 'paas_app' id = Column(INTEGER(11), primary_key=True) name = Column(String(20), nullable=False, unique=True) code = Column(String(30), nullable=False, unique=True) introduction = Column(LONGTEXT, nullable=False) creater = Column(String(20), nullable=False) created_date = Column(DateTime, index=True) state = Column(SMALLINT(6), nullable=False) is_already_test = Column(TINYINT(1), nullable=False) is_already_online = Column(TINYINT(1), nullable=False) first_test_time = Column(DateTime, index=True) first_online_time = Column(DateTime, index=True) language = Column(String(50)) auth_token = Column(String(36)) tags_id = Column(ForeignKey('paas_apptags.id'), index=True) deploy_token = Column(LONGTEXT) is_use_celery = Column(TINYINT(1), nullable=False) is_use_celery_beat = Column(TINYINT(1), nullable=False) is_saas = Column(TINYINT(1), nullable=False) logo = Column(String(100)) tags = relationship('PaasApptag') class EngineApp(Base): __tablename__ = 'engine_apps' id = Column(INTEGER(11), primary_key=True) name = Column(String(20), nullable=False) logo = Column(String(100), nullable=False) app_code = Column(String(100), nullable=False, unique=True) app_lang = Column(String(100), nullable=False) app_type = Column(String(100), nullable=False) is_active = Column(TINYINT(1), nullable=False) created_at = Column(DateTime, nullable=False) updated_at = Column(DateTime, nullable=False) class EngineAppEnv(Base): __tablename__ = 'engine_app_envs' id = Column(INTEGER(11), primary_key=True) mode = Column(String(200), nullable=False) key = Column(String(200), nullable=False) value = Column(String(200), nullable=False) created_at = Column(DateTime, nullable=False) updated_at = Column(DateTime, nullable=False) bk_app_id = Column(ForeignKey('engine_apps.id'), nullable=False, index=True) bk_app = relationship('EngineApp') class PaasAppEnvvar(Base): __tablename__ = 'paas_app_envvars' __table_args__ = ( Index('paas_app_envvars_app_code_36685348c7256adf_uniq', 'app_code', 'mode', 'name', unique=True), ) id = Column(INTEGER(11), primary_key=True) app_code = Column(String(30), nullable=False) mode = Column(String(20), nullable=False) name = Column(String(50), nullable=False) value = Column(String(1024), nullable=False) intro = Column(LONGTEXT) class AddEnv: def __init__(self): cursor = sessionmaker(bind=db) self.session = cursor() self.envs = envs def add_env(self): for env in self.envs: app = self.session.query(PaasApp).filter(PaasApp.code==env.get("app_code")).first() if app: env_list = env.get("env") for env_dict in env_list: key = env_dict.get("key") value = env_dict.get("value") env_scope = "prod" env_query = self.session.query(EngineAppEnv).filter( EngineAppEnv.bk_app_id==app.id, EngineAppEnv.key==key ).first() if not env_query: create_query = EngineAppEnv(mode=env_scope, key=key, value=value, created_at=datetime.datetime.now(), updated_at=datetime.datetime.now(), bk_app_id=app.id ) self.session.add(create_query) self.session.commit() print("For {} create env info: key={} value={}".format(env.get("app_code"), key, value)) else: self.session.query(EngineAppEnv).filter( EngineAppEnv.id==env_query.id).update({ "mode": env_scope, "key": key, "value": value, "updated_at": datetime.datetime.now(), "bk_app_id": app.id }) self.session.commit() print("For {} update env info: key={} value={}".format(env.get("app_code"), key, value)) def add_env_v2(self): for env in self.envs: app_code = env.get("app_code") env_list = env.get("env") for env_dict in env_list: env_query = self.session.query(PaasAppEnvvar).filter( PaasAppEnvvar.app_code==app_code, PaasAppEnvvar.name==env_dict.get("key") ).first() if not env_query: create_query = PaasAppEnvvar(app_code=app_code, name=env_dict.get("key", ""), value=env_dict.get("value", ""), mode=env_dict.get("env_scope", "all"), intro=env_dict.get("intro", ""), ) self.session.add(create_query) self.session.commit() print("For {} create env info: key={} value={}".format(app_code, env_dict.get("key"), env_dict.get("value"))) else: self.session.query(PaasAppEnvvar).filter( PaasAppEnvvar.id==env_query.id).update({ "mode": env_dict.get("env_scope", "all"), "name": env_dict.get("key", ""), "value": env_dict.get("value", ""), "intro": env_dict.get("intro", ""), "app_code": app_code, }) self.session.commit() print("For {} update env info: key={} value={}".format(app_code, env_dict.get("key"), env_dict.get("value"))) if __name__ == '__main__': AddEnv().add_env_v2() print("ENV INPUT IS DONE, SUCCESS.")

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96e207eb8a118e7b80e898bcd7a442641ebdb0f6

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Python

blog/tests/test_views.py

robml/django_diy_blog

b03d92ccc1208408d0fb907271390741bc9bb101

[ "BSD-3-Clause" ]

null

blog/tests/test_views.py

robml/django_diy_blog

b03d92ccc1208408d0fb907271390741bc9bb101

[ "BSD-3-Clause" ]

5

2021-03-19T00:25:40.000Z

2021-09-22T18:39:14.000Z

blog/tests/test_views.py

robml/django_diy_blog

b03d92ccc1208408d0fb907271390741bc9bb101

[ "BSD-3-Clause" ]

null

from django.test import TestCase from django.urls import reverse, reverse_lazy from django.contrib.auth.models import User from blog.models import Blog, BlogAuthor class IndexTest(TestCase): def test_view_url_exists_at_desired_location(self): response = self.client.get('/blog/') self.assertEqual(response.status_code,200) def test_view_url_accessible_by_name(self): response = self.client.get(reverse('index')) self.assertEqual(response.status_code,200) def test_view_uses_correct_template(self): response = self.client.get(reverse('index')) self.assertEqual(response.status_code,200) self.assertTemplateUsed(response, 'index.html') def test_view_uses_correct_dr_evil_values(self): response = self.client.get(reverse('index')) self.assertTrue('num_blogs_dr_evil' in response.context) real_count = Blog.objects.filter(author__name__username__iexact='dr_evil').count() self.assertEqual(response.context['num_blogs_dr_evil'],real_count) class BlogAuthorListViewTest(TestCase): @classmethod def setUpTestData(cls): # Create a user num_users = 13 for test_user_id in range(num_users): test_user_id=str(test_user_id) test_user = User.objects.create_user(username='testuser'+test_user_id,password='testuser'+test_user_id) test_user.save() BlogAuthor.objects.create(name=test_user,bio='user#'+test_user_id) def test_view_url_exists_at_desired_location(self): response = self.client.get('/blog/bloggers/') self.assertEqual(response.status_code,200) def test_view_url_accessible_by_name(self): response = self.client.get(reverse('blogauthor-list')) self.assertEqual(response.status_code,200) def test_view_uses_correct_template(self): response = self.client.get(reverse('blogauthor-list')) self.assertEqual(response.status_code,200) self.assertTemplateUsed(response, 'blog/blogauthor_list.html') def test_pagination_is_five(self): response = self.client.get(reverse('blogauthor-list')) self.assertEqual(response.status_code,200) self.assertTrue('is_paginated' in response.context) self.assertTrue(response.context['is_paginated'] == True) self.assertTrue(len(response.context['blogauthor_list'])==5) class BlogListViewTest(TestCase): @classmethod def setUpTestData(cls): # Create a user num_users = 13 for test_user_id in range(num_users): test_user_id=str(test_user_id) test_user = User.objects.create_user(username='testuser'+test_user_id,password='testuser'+test_user_id) test_user.save() author = BlogAuthor.objects.create(name=test_user,bio='user#'+test_user_id) Blog.objects.create(author=author,title="post by user#"+test_user_id,description="test desc") def test_view_url_exists_at_desired_location(self): response = self.client.get('/blog/all/') self.assertEqual(response.status_code,200) def test_view_url_accessible_by_name(self): response = self.client.get(reverse('blog-list')) self.assertEqual(response.status_code,200) def test_view_uses_correct_template(self): response = self.client.get(reverse('blog-list')) self.assertEqual(response.status_code,200) self.assertTemplateUsed(response, 'blog/blog_list.html') def test_pagination_is_five(self): response = self.client.get(reverse('blog-list')) self.assertEqual(response.status_code,200) self.assertTrue('is_paginated' in response.context) self.assertTrue(response.context['is_paginated'] == True) self.assertTrue(len(response.context['blog_list'])==5) class BlogAuthorDetailViewTest(TestCase): @classmethod def setUpTestData(cls): test_user = User.objects.create_user(username='testuser1',password='testuser1') test_user.save() BlogAuthor.objects.create(name=test_user,bio='user1') def test_view_url_exists_at_desired_location(self): id = BlogAuthor.objects.get(id=1).id response = self.client.get('/blog/bloggers/'+str(id)) self.assertEqual(response.status_code,200) def test_view_url_accessible_by_name(self): id = BlogAuthor.objects.get(id=1).id response = self.client.get(reverse('blogauthor-detail',args=[str(id)])) self.assertEqual(response.status_code,200) def test_view_uses_correct_template(self): id = BlogAuthor.objects.get(id=1).id response = self.client.get(reverse('blogauthor-detail',args=[str(id)])) self.assertEqual(response.status_code,200) self.assertTemplateUsed(response, 'blog/blogauthor_detail.html') class BlogDetailViewTest(TestCase): @classmethod def setUpTestData(cls): test_user = User.objects.create_user(username='testuser1',password='testuser1') test_user.save() author = BlogAuthor.objects.create(name=test_user,bio='user1') Blog.objects.create(author=author,title="post by user1",description="test desc") def test_view_url_exists_at_desired_location(self): id = Blog.objects.get(id=1).id response = self.client.get('/blog/'+str(id)) self.assertEqual(response.status_code,301) # Getting a 301 instead of a 200 def test_view_url_accessible_by_name(self): id = Blog.objects.get(id=1).id response = self.client.get(reverse('blog-detail',args=[str(id)])) self.assertEqual(response.status_code,200) def test_view_uses_correct_template(self): id = Blog.objects.get(id=1).id response = self.client.get(reverse('blog-detail',args=[str(id)])) self.assertEqual(response.status_code,200) self.assertTemplateUsed(response, 'blog/blog_detail.html') # Notes: the test below is already secured on the form and model tests # HOWEVER: the self.client.get yields a 404 with the current syntax, and a NoReverseMatch when used with reverse # I leave this as an exercise if testing the View of New comments is crucial to you, best of luck, Rob """ class NewCommentViewTest(TestCase): def setUp(self): # Create a user test_user1 = User.objects.create_user(username='testuser1', password='1X<ISRUkw+tuK') test_user2 = User.objects.create_user(username='testuser2', password='2HJ1vRV0Z&3iD') test_user1.save() test_user2.save() author = BlogAuthor.objects.create(name=test_user1,bio='user1') Blog.objects.create(author=author,title="post by user1",description="test desc") def test_redirect_if_not_logged_in(self): id = Blog.objects.get(id=1).id response = self.client.get('blog/'+str(id)+'/create') # Manually check redirect (Can't use assertRedirect, because the redirect URL is unpredictable) self.assertEqual(response.status_code, 302) self.assertTrue(response.url.startswith('/accounts/login/')) def test_logged_in(self): id = Blog.objects.get(id=1).id login = self.client.login(username='testuser2', password='2HJ1vRV0Z&3iD') response = self.client.get('blog/'+str(id)+'/create') # Check that it lets us login self.assertEqual(response.status_code, 200) def test_uses_correct_template(self): id = Blog.objects.get(id=1).id login = self.client.login(username='testuser2', password='2HJ1vRV0Z&3iD') response = self.client.get('blog/'+str(id)+'/create') self.assertEqual(response.status_code, 200) # Check we used correct template self.assertTemplateUsed(response, 'blog/comment_form.html') """

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