xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

14aff0f5078b8248cb7469fa7cbfb6729d443577

166

py

Python

data_structures/queue/conftest.py

seattlechem/data-structures-and-algorithms

376e465c0a5529ea7c5c4e972a9852b6340251ff

[ "MIT" ]

null

data_structures/queue/conftest.py

seattlechem/data-structures-and-algorithms

376e465c0a5529ea7c5c4e972a9852b6340251ff

[ "MIT" ]

null

data_structures/queue/conftest.py

seattlechem/data-structures-and-algorithms

376e465c0a5529ea7c5c4e972a9852b6340251ff

[ "MIT" ]

null

from .queue import Queue import pytest @pytest.fixture def empty_queue(): return Queue() @pytest.fixture def small_queue(): return Queue([1, 2, 3, 4, 5])

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py

Python

barmat/volume_integrals.py

FaustinCarter/barmat

753725cda1c807afe4eacb385f1ab794579c100c

[ "MIT" ]

4

2018-04-23T20:54:01.000Z

2021-06-10T17:22:02.000Z

barmat/volume_integrals.py

FaustinCarter/barmat

753725cda1c807afe4eacb385f1ab794579c100c

[ "MIT" ]

3

2017-03-23T16:13:18.000Z

2021-06-10T17:03:55.000Z

barmat/volume_integrals.py

FaustinCarter/barmat

753725cda1c807afe4eacb385f1ab794579c100c

[ "MIT" ]

1

2021-06-10T17:23:09.000Z

# coding=utf-8 from __future__ import division import math as ma import numba @numba.jit("float64(float64, float64, float64)", nopython=True) def intR(a, b, x): r"""Calculate the R integral from Popel divided by x, (x = q*L0, L0 = zero-temp London depth). Parameters ---------- a : float b : float x : float Returns ------- r : float The R integral from Popel, divided by x. Note ---- See R. Pöpel (1989), doi: 10.1063/1.343622 for more details.""" z2 = a**2+b**2 if x == 0: r = b/(3.0*z2) #This is really r/x #for small x elif x < 0.01*ma.sqrt(z2): r = b/(3.0*z2) #This is really r/x #for large x elif x > 100*ma.sqrt(z2): r = (ma.pi*(1+(b**2-a**2)/x**2)/4-b/x)/x #This is really r/x #in between x else: #calculate all the terms of r r = (1/x**2)*(-0.5*b*x+0.25*a*b*ma.log((z2+x**2+2*a*x)/(z2+x**2-2*a*x))+ 0.25*(x**2+b**2-a**2)*ma.atan2(2*b*x,(z2-x**2)))/x #This is really r/x return r @numba.jit("float64(float64, float64, float64)", nopython=True) def intS(a, b, x): r"""Calculate the R integral from Popel divided by x, (x = q*L0, L0 = zero-temp London depth). Parameters ---------- a : float b : float x : float Returns ------- s : float The S integral from Popel, divided by x. Note ---- See R. Pöpel (1989), doi: 10.1063/1.343622 for more details.""" z2 = a**2+b**2 if x == 0: s = a/(3.0*z2) #This is really s/x #for small x elif x < 0.01*ma.sqrt(z2): s = a/(3.0*z2) #This is really s/x #for large x elif x > 100*ma.sqrt(z2): s = (a/x - a*b*ma.pi/(2*x**2))/x #This is really s/x #in between x else: #calculate all the terms of s s = (1/x**2)*(0.5*(a*x)+ 0.125*(x**2+b**2-a**2)*ma.log((z2+x**2+2*a*x)/(z2+x**2-2*a*x))- 0.5*b*a*ma.atan2(2*b*x,(z2-x**2)))/x #This is really s/x return s

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14b7ea420a3998a704d99ff49d3edee44f4da77f

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py

Python

rabbitmqalert/tests/test_argumentsparser.py

mdcatapult/rabbitmq-alert

cf0f83942084b471129010f3069089d58b2ac314

[ "BSD-3-Clause" ]

72

2016-06-02T13:27:33.000Z

2022-02-23T09:06:34.000Z

rabbitmqalert/tests/test_argumentsparser.py

mdcatapult/rabbitmq-alert

cf0f83942084b471129010f3069089d58b2ac314

[ "BSD-3-Clause" ]

24

2015-12-07T17:34:28.000Z

2022-01-25T05:46:59.000Z

rabbitmqalert/tests/test_argumentsparser.py

mdcatapult/rabbitmq-alert

cf0f83942084b471129010f3069089d58b2ac314

[ "BSD-3-Clause" ]

35

2016-06-29T10:14:28.000Z

2021-11-18T09:09:57.000Z

#! /usr/bin/python2 # -*- coding: utf8 -*- from collections import namedtuple import mock import unittest from rabbitmqalert import argumentsparser from rabbitmqalert.models import argument from rabbitmqalert import rabbitmqalert class ArgumentsParserTestCase(unittest.TestCase): def setUp(self): argumentsparser.os_real = argumentsparser.os argumentsparser.apiclient.ApiClient_real = argumentsparser.apiclient.ApiClient argumentsparser.argument.Argument_real = argumentsparser.argument.Argument argumentsparser.argument.Argument.files_have_group_real = argumentsparser.argument.Argument.files_have_group argumentsparser.argument.ConfigParser.ConfigParser_real = argumentsparser.argument.ConfigParser.ConfigParser argumentsparser.argument.os_real = argumentsparser.argument.os rabbitmqalert.argparse_real = rabbitmqalert.argparse def tearDown(self): argumentsparser.os = argumentsparser.os_real argumentsparser.apiclient.ApiClient = argumentsparser.apiclient.ApiClient_real argumentsparser.argument.Argument = argumentsparser.argument.Argument_real argumentsparser.argument.Argument.files_have_group = argumentsparser.argument.Argument.files_have_group_real argumentsparser.argument.ConfigParser.ConfigParser = argumentsparser.argument.ConfigParser.ConfigParser_real argumentsparser.argument.os = argumentsparser.argument.os_real rabbitmqalert.argparse = rabbitmqalert.argparse_real def test_parse_calls_get_value_for_every_group_argument(self): logger = mock.MagicMock() # setup the argparse argument parser with fake cli arguments rabbitmqalert.argparse._sys.argv = ['rabbitmqalert.py'] + self.arguments_dict_to_list(self.construct_arguments()) argparse_parser = rabbitmqalert.setup_arguments() argumentsparser.argument.Argument = mock.MagicMock() argumentsparser.apiclient.ApiClient.get_queues = mock.MagicMock() parser = argumentsparser.ArgumentsParser(logger) parser.validate = mock.MagicMock() parser.format_conditions = mock.MagicMock() parser.parse(argparse_parser) # count the number of arguments group_arguments_count = 0 for group in argparse_parser._action_groups: for group_argument in group._group_actions: group_arguments_count += 1 argumentsparser.argument.Argument.get_value.call_count == group_arguments_count def test_parse_returns_discovered_queues_when_argument_set(self): logger = mock.MagicMock() # edit the cli arguments to look like queues discovery was requested arguments = self.construct_arguments() arguments["--queues-discovery"] = True arguments_list = self.arguments_dict_to_list(arguments) # setup the argparse argument parser with fake cli arguments rabbitmqalert.argparse._sys.argv = ['rabbitmqalert.py'] + arguments_list argparse_parser = rabbitmqalert.setup_arguments() argumentsparser.apiclient.ApiClient.get_queues = mock.MagicMock(return_value=["foo-queue", "bar-queue"]) parser = argumentsparser.ArgumentsParser(logger) parser.validate = mock.MagicMock() parser.format_conditions = mock.MagicMock() parser.parse(argparse_parser) # create a copy of the arguments in the form they would look like after parsing them (behore calling validate) arguments_dict = vars(argparse_parser.parse_args(arguments_list)) arguments_dict["server_queues"] = ["foo-queue", "bar-queue"] arguments_dict["email_to"] = arguments_dict["email_to"].split(",") arguments_dict["help"] = None arguments_dict["queue_conditions"] = dict() arguments_dict["email_ssl"] = False argumentsparser.apiclient.ApiClient.get_queues.assert_called_once() parser.validate.assert_called_once_with(arguments_dict) def test_parse_returns_emails_split(self): logger = mock.MagicMock() # edit the cli arguments to look like multiple email address were given arguments = self.construct_arguments() arguments["--email-to"] = "foo-email-to,bar-email-to" arguments_list = self.arguments_dict_to_list(arguments) # setup the argparse argument parser with fake cli arguments rabbitmqalert.argparse._sys.argv = ['rabbitmqalert.py'] + arguments_list argparse_parser = rabbitmqalert.setup_arguments() parser = argumentsparser.ArgumentsParser(logger) parser.validate = mock.MagicMock() parser.format_conditions = mock.MagicMock() parser.parse(argparse_parser) # create a copy of the arguments in the form they would look like after parsing them (behore calling validate) arguments_dict = vars(argparse_parser.parse_args(arguments_list)) arguments_dict["server_queues"] = arguments_dict["server_queues"].split(",") arguments_dict["email_to"] = arguments_dict["email_to"].split(",") arguments_dict["help"] = None arguments_dict["queue_conditions"] = dict() arguments_dict["server_queues_discovery"] = False arguments_dict["email_ssl"] = False parser.validate.assert_called_once_with(arguments_dict) def test_parse_skips_queue_conditions_when_non_standard_groups_do_not_exist(self): logger = mock.MagicMock() argumentsparser.argument.Argument.files_have_group = mock.MagicMock(return_value=False) arguments_list = self.arguments_dict_to_list(self.construct_arguments()) # setup the argparse argument parser with fake cli arguments rabbitmqalert.argparse._sys.argv = ['rabbitmqalert.py'] + arguments_list argparse_parser = rabbitmqalert.setup_arguments() parser = argumentsparser.ArgumentsParser(logger) parser.validate = mock.MagicMock() parser.format_conditions = mock.MagicMock() parser.parse(argparse_parser) # create a copy of the arguments in the form they would look like after parsing them (behore calling validate) arguments_dict = vars(argparse_parser.parse_args(arguments_list)) arguments_dict["server_queues"] = arguments_dict["server_queues"].split(",") arguments_dict["email_to"] = arguments_dict["email_to"].split(",") arguments_dict["help"] = None arguments_dict["queue_conditions"] = dict() arguments_dict["server_queues_discovery"] = False arguments_dict["email_ssl"] = False # checks for non-standard group for queue specific conditions argumentsparser.argument.Argument.files_have_group.assert_called_once_with("Conditions:foo-queue") # validate called with empty queue_conditions parser.validate.assert_called_once_with(arguments_dict) def test_parse_constructs_queue_conditions_when_non_standard_groups_exist(self): logger = mock.MagicMock() argumentsparser.argument.Argument.files_have_group = mock.MagicMock(return_value=True) arguments_dict = self.construct_arguments() arguments_dict["--queues"] = "foo-queue,bar-queue" arguments_list = self.arguments_dict_to_list(arguments_dict) # setup the argparse argument parser with fake cli arguments rabbitmqalert.argparse._sys.argv = ['rabbitmqalert.py'] + arguments_list argparse_parser = rabbitmqalert.setup_arguments() parser = argumentsparser.ArgumentsParser(logger) parser.validate = mock.MagicMock() parser.format_conditions = mock.MagicMock() parser.parse(argparse_parser) # create a copy of the arguments in the form they would look like after parsing them (behore calling validate) arguments_dict = vars(argparse_parser.parse_args(arguments_list)) arguments_dict["server_queues"] = arguments_dict["server_queues"].split(",") arguments_dict["email_to"] = arguments_dict["email_to"].split(",") arguments_dict["help"] = None arguments_dict["server_queues_discovery"] = False arguments_dict["email_ssl"] = False arguments_dict["queue_conditions"] = { "foo-queue": { "conditions_total_queue_size": 40, "conditions_ready_queue_size": 20, "conditions_queue_consumers_connected": 52, "conditions_unack_queue_size": 30 }, "bar-queue": { "conditions_total_queue_size": 40, "conditions_ready_queue_size": 20, "conditions_queue_consumers_connected": 52, "conditions_unack_queue_size": 30 } } # checks for non-standard group for queue specific conditions argumentsparser.argument.Argument.files_have_group.assert_any_call("Conditions:foo-queue") argumentsparser.argument.Argument.files_have_group.assert_any_call("Conditions:bar-queue") # validate called with empty queue_conditions parser.validate.assert_called_once_with(arguments_dict) def test_parse_returns_merged_arguments_and_conditions(self): logger = mock.MagicMock() arguments = self.construct_arguments() arguments_list = self.arguments_dict_to_list(arguments) # setup the argparse argument parser with fake cli arguments rabbitmqalert.argparse._sys.argv = ['rabbitmqalert.py'] + arguments_list argparse_parser = rabbitmqalert.setup_arguments() parser = argumentsparser.ArgumentsParser(logger) result = parser.parse(argparse_parser) # create a copy of the arguments in the form they would look like after parsing them arguments_dict = vars(argparse_parser.parse_args(arguments_list)) arguments_dict["server_queues"] = arguments_dict["server_queues"].split(",") arguments_dict["email_to"] = arguments_dict["email_to"].split(",") arguments_dict["help"] = None arguments_dict["server_queues_discovery"] = False arguments_dict["email_ssl"] = False arguments_dict["queue_conditions"] = dict() arguments_dict = dict(arguments_dict.items() + parser.format_conditions(arguments_dict).items()) self.assertEquals(arguments_dict, result) def test_validate_exits_when_required_argument_is_missing(self): logger = mock.MagicMock() arguments = self.construct_arguments() del arguments["--host"] arguments_list = self.arguments_dict_to_list(arguments) rabbitmqalert.argparse._sys.argv = ['rabbitmqalert.py'] + arguments_list argparse_parser = rabbitmqalert.setup_arguments() parser = argumentsparser.ArgumentsParser(logger) arguments_dict = vars(argparse_parser.parse_args(arguments_list)) with self.assertRaises(SystemExit) as ex: parser.validate(arguments_dict) self.assertEqual(ex.exception.code, 1) logger.error.assert_called_once_with("Required argument not defined: host") def test_validate_does_not_exit_when_all_required_arguments_exist(self): logger = mock.MagicMock() arguments = self.construct_arguments() arguments_list = self.arguments_dict_to_list(arguments) rabbitmqalert.argparse._sys.argv = ['rabbitmqalert.py'] + arguments_list argparse_parser = rabbitmqalert.setup_arguments() parser = argumentsparser.ArgumentsParser(logger) arguments_dict = vars(argparse_parser.parse_args(arguments_list)) parser.validate(arguments_dict) logger.error.assert_not_called() def test_format_conditions_returns_generic_and_queue_conditions(self): logger = mock.MagicMock() arguments = self.construct_arguments() arguments_list = self.arguments_dict_to_list(arguments) # setup the argparse argument parser with fake cli arguments rabbitmqalert.argparse._sys.argv = ['rabbitmqalert.py'] + arguments_list argparse_parser = rabbitmqalert.setup_arguments() arguments_dict = vars(argparse_parser.parse_args(arguments_list)) arguments_dict["server_queues"] = ["foo-queue"] arguments_dict["email_to"] = arguments_dict["email_to"].split(",") arguments_dict["help"] = None arguments_dict["queue_conditions"] = dict() parser = argumentsparser.ArgumentsParser(logger) results = parser.format_conditions(arguments_dict) self.assertTrue("conditions" in results) self.assertTrue("generic_conditions" in results) # generic conditions self.assertEquals(arguments_dict["conditions_consumers_connected"], results["generic_conditions"]["conditions_consumers_connected"]) self.assertEquals(arguments_dict["conditions_open_connections"], results["generic_conditions"]["conditions_open_connections"]) self.assertEquals(arguments_dict["conditions_nodes_running"], results["generic_conditions"]["conditions_nodes_running"]) self.assertEquals(arguments_dict["conditions_node_memory_used"], results["generic_conditions"]["conditions_node_memory_used"]) # queue conditions self.assertEquals(arguments_dict["conditions_ready_queue_size"], results["conditions"]["foo-queue"]["conditions_ready_queue_size"]) self.assertEquals(arguments_dict["conditions_unack_queue_size"], results["conditions"]["foo-queue"]["conditions_unack_queue_size"]) self.assertEquals(arguments_dict["conditions_total_queue_size"], results["conditions"]["foo-queue"]["conditions_total_queue_size"]) self.assertEquals(arguments_dict["conditions_queue_consumers_connected"], results["conditions"]["foo-queue"]["conditions_queue_consumers_connected"]) def test_format_conditions_returns_queue_conditions_when_exist(self): logger = mock.MagicMock() arguments = self.construct_arguments() arguments_list = self.arguments_dict_to_list(arguments) # setup the argparse argument parser with fake cli arguments rabbitmqalert.argparse._sys.argv = ['rabbitmqalert.py'] + arguments_list argparse_parser = rabbitmqalert.setup_arguments() arguments_dict = vars(argparse_parser.parse_args(arguments_list)) arguments_dict["server_queues"] = ["foo-queue", "bar-queue"] arguments_dict["email_to"] = arguments_dict["email_to"].split(",") arguments_dict["help"] = None arguments_dict["queue_conditions"] = { "foo-queue": { "conditions_total_queue_size": 40, "conditions_ready_queue_size": 20, "conditions_queue_consumers_connected": 52, "conditions_unack_queue_size": 30 }, "bar-queue": { "conditions_total_queue_size": 40, "conditions_ready_queue_size": 20, "conditions_queue_consumers_connected": 52, "conditions_unack_queue_size": 30 } } parser = argumentsparser.ArgumentsParser(logger) results = parser.format_conditions(arguments_dict) self.assertTrue("conditions" in results) self.assertTrue("generic_conditions" in results) # generic conditions self.assertEquals(arguments_dict["conditions_consumers_connected"], results["generic_conditions"]["conditions_consumers_connected"]) self.assertEquals(arguments_dict["conditions_open_connections"], results["generic_conditions"]["conditions_open_connections"]) self.assertEquals(arguments_dict["conditions_nodes_running"], results["generic_conditions"]["conditions_nodes_running"]) self.assertEquals(arguments_dict["conditions_node_memory_used"], results["generic_conditions"]["conditions_node_memory_used"]) # queue conditions self.assertTrue(arguments_dict["conditions_ready_queue_size"], results["conditions"]["foo-queue"]["conditions_ready_queue_size"]) self.assertEquals(arguments_dict["conditions_unack_queue_size"], results["conditions"]["foo-queue"]["conditions_unack_queue_size"]) self.assertEquals(arguments_dict["conditions_total_queue_size"], results["conditions"]["foo-queue"]["conditions_total_queue_size"]) self.assertEquals(arguments_dict["conditions_queue_consumers_connected"], results["conditions"]["foo-queue"]["conditions_queue_consumers_connected"]) self.assertTrue(arguments_dict["conditions_ready_queue_size"], results["conditions"]["bar-queue"]["conditions_ready_queue_size"]) self.assertEquals(arguments_dict["conditions_unack_queue_size"], results["conditions"]["bar-queue"]["conditions_unack_queue_size"]) self.assertEquals(arguments_dict["conditions_total_queue_size"], results["conditions"]["bar-queue"]["conditions_total_queue_size"]) self.assertEquals(arguments_dict["conditions_queue_consumers_connected"], results["conditions"]["bar-queue"]["conditions_queue_consumers_connected"]) @staticmethod def construct_arguments(): return { "--config-file": None, "--scheme": "foo-scheme", "--host": "foo-host", "--port": "foo-port", "--host-alias": "bar-host", "--username": "foo-username", "--password": "foo-password", "--vhost": "foo-vhost", "--queues": "foo-queue", "--queues-discovery": False, "--check-rate": "10", "--ready-queue-size": "20", "--unacknowledged-queue-size": "30", "--total-queue-size": "40", "--queue-consumers-connected": "52", "--consumers-connected": "50", "--open-connections": "51", "--nodes-running": "60", "--node-memory-used": "70", "--email-to": "foo-email-to", "--email-from": "foo-email-from", "--email-subject": "foo-email-subject", "--email-server": "foo-email-server", "--email-password": "foo-email-password", "--email-ssl": False, "--slack-url": "foo-slack-url", "--slack-channel": "foo-slack-channel", "--slack-username": "foo-slack-username", "--telegram-bot-id": "foo-telegram-bot-id", "--telegram-channel": "foo-telegram-channel" } @staticmethod def arguments_dict_to_list(dict): result = [] for key, value in dict.iteritems(): if value not in [False, None]: result.append(key) # arguments of store_true or store_false action must not have a value result.append(value) if type(value) is not bool else None return result if __name__ == "__main__": unittest.main()

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210d97708e948defc016011d23120873587d7f47

28

py

Python

segmentation_models_pytorch/transunet/__init__.py

PhilippMarquardt/segmentation_models.pytorch

8a884bdf7a0c92a2eb4f5d85120a83cd13b08a06

[ "MIT" ]

null

segmentation_models_pytorch/transunet/__init__.py

PhilippMarquardt/segmentation_models.pytorch

8a884bdf7a0c92a2eb4f5d85120a83cd13b08a06

[ "MIT" ]

null

segmentation_models_pytorch/transunet/__init__.py

PhilippMarquardt/segmentation_models.pytorch

8a884bdf7a0c92a2eb4f5d85120a83cd13b08a06

[ "MIT" ]

null

from .model import TransUnet

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21148063577ce42922990fc414643ad210d8f4a4

95

py

Python

Hello1.py

jkirkish/DojoAssignments

3eb6e08132977af9d25449254a2caeb40f53c394

[ "Adobe-Glyph", "FSFAP" ]

null

Hello1.py

jkirkish/DojoAssignments

3eb6e08132977af9d25449254a2caeb40f53c394

[ "Adobe-Glyph", "FSFAP" ]

null

Hello1.py

jkirkish/DojoAssignments

3eb6e08132977af9d25449254a2caeb40f53c394

[ "Adobe-Glyph", "FSFAP" ]

null

name = "Jelly" name = "Hello" print (5+5) print ("Joseph",name) print("5",5) print("Me")

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dcd90aa7dd1df367e933dd00d51dd35eca42c005

64

py

Python

onix/views/__init__.py

jesuejunior/stone

e55d3d9a555a1bd0f8655b7684652187cd1f5d4b

[ "BSD-3-Clause" ]

3

2016-06-16T22:47:42.000Z

2019-10-13T15:29:16.000Z

onix/views/__init__.py

jesuejunior/stone

e55d3d9a555a1bd0f8655b7684652187cd1f5d4b

[ "BSD-3-Clause" ]

1

2021-06-10T18:22:23.000Z

onix/views/__init__.py

jesuejunior/stone

e55d3d9a555a1bd0f8655b7684652187cd1f5d4b

[ "BSD-3-Clause" ]

null

from .home import * from .block import * from .material import *

21.333333

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dcf18a2399e4f4cc092b7775baf685b002a4f9e4

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py

Python

cg_openmm/__init__.py

garrettameek/cg_openmm

5ea52c9e6e2990953bdbcfa14f4e61a7d7efae7c

[ "MIT" ]

null

cg_openmm/__init__.py

garrettameek/cg_openmm

5ea52c9e6e2990953bdbcfa14f4e61a7d7efae7c

[ "MIT" ]

null

cg_openmm/__init__.py

garrettameek/cg_openmm

5ea52c9e6e2990953bdbcfa14f4e61a7d7efae7c

[ "MIT" ]

null

from . import build from . import simulation from . import utilities

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0d2781e79e44af2b0967bd184d59ce1c4089c670

189

py

Python

technologies/app/jupyter/jupyter-base/tests/python3_lib_test.py

EtienneSIG/technologies

b143d814c3500c545a508e1965a7560e6aed90e6

[ "Apache-2.0" ]

null

technologies/app/jupyter/jupyter-base/tests/python3_lib_test.py

EtienneSIG/technologies

b143d814c3500c545a508e1965a7560e6aed90e6

[ "Apache-2.0" ]

null

technologies/app/jupyter/jupyter-base/tests/python3_lib_test.py

EtienneSIG/technologies

b143d814c3500c545a508e1965a7560e6aed90e6

[ "Apache-2.0" ]

null

# Manual tests ... import sys print(sys.executable) print(sys.version) print(sys.version_info) ### FIXME find a way to test those installs # - from hdfs.hfile import Hfile # - import hdf5

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0d35b5cc887897bb17dde3020cb668d62c69864c

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py

Python

test_macro/fors/__init__.py

kerryeon/test-macro

a65f12d7f6f1a679070e974f2abacfed7634c2c6

[ "MIT" ]

null

test_macro/fors/__init__.py

kerryeon/test-macro

a65f12d7f6f1a679070e974f2abacfed7634c2c6

[ "MIT" ]

null

test_macro/fors/__init__.py

kerryeon/test-macro

a65f12d7f6f1a679070e974f2abacfed7634c2c6

[ "MIT" ]

null

from .recorder import Recorder

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b4aab581710d19724934ed8e7167357503e062b3

4,334

py

Python

resources/dot_PyCharm/system/python_stubs/-762174762/PySide/QtGui/QGraphicsGridLayout.py

basepipe/developer_onboarding

05b6a776f8974c89517868131b201f11c6c2a5ad

[ "MIT" ]

1

2020-04-20T02:27:20.000Z

resources/dot_PyCharm/system/python_stubs/cache/8cdc475d469a13122bc4bc6c3ac1c215d93d5f120f5cc1ef33a8f3088ee54d8e/PySide/QtGui/QGraphicsGridLayout.py

basepipe/developer_onboarding

05b6a776f8974c89517868131b201f11c6c2a5ad

[ "MIT" ]

null

resources/dot_PyCharm/system/python_stubs/cache/8cdc475d469a13122bc4bc6c3ac1c215d93d5f120f5cc1ef33a8f3088ee54d8e/PySide/QtGui/QGraphicsGridLayout.py

basepipe/developer_onboarding

05b6a776f8974c89517868131b201f11c6c2a5ad

[ "MIT" ]

null

# encoding: utf-8 # module PySide.QtGui # from C:\Python27\lib\site-packages\PySide\QtGui.pyd # by generator 1.147 # no doc # imports import PySide.QtCore as __PySide_QtCore import Shiboken as __Shiboken from QGraphicsLayout import QGraphicsLayout class QGraphicsGridLayout(QGraphicsLayout): # no doc def addItem(self, *args, **kwargs): # real signature unknown pass def alignment(self, *args, **kwargs): # real signature unknown pass def columnAlignment(self, *args, **kwargs): # real signature unknown pass def columnCount(self, *args, **kwargs): # real signature unknown pass def columnMaximumWidth(self, *args, **kwargs): # real signature unknown pass def columnMinimumWidth(self, *args, **kwargs): # real signature unknown pass def columnPreferredWidth(self, *args, **kwargs): # real signature unknown pass def columnSpacing(self, *args, **kwargs): # real signature unknown pass def columnStretchFactor(self, *args, **kwargs): # real signature unknown pass def count(self, *args, **kwargs): # real signature unknown pass def horizontalSpacing(self, *args, **kwargs): # real signature unknown pass def invalidate(self, *args, **kwargs): # real signature unknown pass def itemAt(self, *args, **kwargs): # real signature unknown pass def removeAt(self, *args, **kwargs): # real signature unknown pass def removeItem(self, *args, **kwargs): # real signature unknown pass def rowAlignment(self, *args, **kwargs): # real signature unknown pass def rowCount(self, *args, **kwargs): # real signature unknown pass def rowMaximumHeight(self, *args, **kwargs): # real signature unknown pass def rowMinimumHeight(self, *args, **kwargs): # real signature unknown pass def rowPreferredHeight(self, *args, **kwargs): # real signature unknown pass def rowSpacing(self, *args, **kwargs): # real signature unknown pass def rowStretchFactor(self, *args, **kwargs): # real signature unknown pass def setAlignment(self, *args, **kwargs): # real signature unknown pass def setColumnAlignment(self, *args, **kwargs): # real signature unknown pass def setColumnFixedWidth(self, *args, **kwargs): # real signature unknown pass def setColumnMaximumWidth(self, *args, **kwargs): # real signature unknown pass def setColumnMinimumWidth(self, *args, **kwargs): # real signature unknown pass def setColumnPreferredWidth(self, *args, **kwargs): # real signature unknown pass def setColumnSpacing(self, *args, **kwargs): # real signature unknown pass def setColumnStretchFactor(self, *args, **kwargs): # real signature unknown pass def setGeometry(self, *args, **kwargs): # real signature unknown pass def setHorizontalSpacing(self, *args, **kwargs): # real signature unknown pass def setRowAlignment(self, *args, **kwargs): # real signature unknown pass def setRowFixedHeight(self, *args, **kwargs): # real signature unknown pass def setRowMaximumHeight(self, *args, **kwargs): # real signature unknown pass def setRowMinimumHeight(self, *args, **kwargs): # real signature unknown pass def setRowPreferredHeight(self, *args, **kwargs): # real signature unknown pass def setRowSpacing(self, *args, **kwargs): # real signature unknown pass def setRowStretchFactor(self, *args, **kwargs): # real signature unknown pass def setSpacing(self, *args, **kwargs): # real signature unknown pass def setVerticalSpacing(self, *args, **kwargs): # real signature unknown pass def sizeHint(self, *args, **kwargs): # real signature unknown pass def verticalSpacing(self, *args, **kwargs): # real signature unknown pass def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(S, *more): # real signature unknown; restored from __doc__ """ T.__new__(S, ...) -> a new object with type S, a subtype of T """ pass

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b4ee9baafc61f7aeebcb34aa9f83f7509b1347a8

82

py

Python

TermTk/TTkTestWidgets/__init__.py

UltraStudioLTD/pyTermTk

a1e96b0e7f43906b9fda0b16f19f427919a055c2

[ "MIT" ]

1

2022-02-28T16:33:25.000Z

TermTk/TTkTestWidgets/__init__.py

UltraStudioLTD/pyTermTk

a1e96b0e7f43906b9fda0b16f19f427919a055c2

[ "MIT" ]

null

TermTk/TTkTestWidgets/__init__.py

UltraStudioLTD/pyTermTk

a1e96b0e7f43906b9fda0b16f19f427919a055c2

[ "MIT" ]

null

from .logviewer import * from .testwidget import * from .testwidgetsizes import *

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6

b4fdd6858ddb174637892f661e3766ac5c8a0236

188

py

Python

classification.py

oushu1zhangxiangxuan1/learn-tensorflow

e83f8633fcbfd428ee3495b18b75ca78c7a25331

[ "Apache-2.0" ]

null

classification.py

oushu1zhangxiangxuan1/learn-tensorflow

e83f8633fcbfd428ee3495b18b75ca78c7a25331

[ "Apache-2.0" ]

null

classification.py

oushu1zhangxiangxuan1/learn-tensorflow

e83f8633fcbfd428ee3495b18b75ca78c7a25331

[ "Apache-2.0" ]

null

import tensorflow as tf from tensorlfow.examples.tutorials.mnist import input_data xs = tf.placeholder(tf.float32, [None, 784]) ys = tf.placeholder(tf.float32, [None, 10]) prediction =

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37050b12c1f2e0d5211ff2641cce046d21598b08

240

py

Python

trio_asyncio/__init__.py

ProvoK/trio-asyncio

8098e93a63eedf7188545cbda45e54c0bcdd85fc

[ "Apache-2.0", "MIT" ]

null

trio_asyncio/__init__.py

ProvoK/trio-asyncio

8098e93a63eedf7188545cbda45e54c0bcdd85fc

[ "Apache-2.0", "MIT" ]

null

trio_asyncio/__init__.py

ProvoK/trio-asyncio

8098e93a63eedf7188545cbda45e54c0bcdd85fc

[ "Apache-2.0", "MIT" ]

null

# This code implements basic asyncio compatibility from ._version import __version__ # noqa from .base import * # noqa from .loop import * # noqa from .util import * # noqa from .async_ import * # noqa from .adapter import * # noqa

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1

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6

2ea43309241365712afcb36edd2684632cfc7a85

8,051

py

Python

algs14_hashtable/hashtable_linked_sorted.py

zhubaiyuan/learning-algorithms

ea9ee674878d535a9e9987c0d948c0357e0ed4da

[ "MIT" ]

null

algs14_hashtable/hashtable_linked_sorted.py

zhubaiyuan/learning-algorithms

ea9ee674878d535a9e9987c0d948c0357e0ed4da

[ "MIT" ]

null

algs14_hashtable/hashtable_linked_sorted.py

zhubaiyuan/learning-algorithms

ea9ee674878d535a9e9987c0d948c0357e0ed4da

[ "MIT" ]

null

from algs14_hashtable.entry import LinkedEntry class SortedLinkedListsHashtable: """ Hashtable using array of M linked lists where keys appear in sorted order. """ def __init__(self, M=10): self.table = [None] * M if M < 1: raise ValueError('Hashtable storage must be at least 1.') self.M = M self.N = 0 def __len__(self): return self.N def get(self, k): """ Retrieve value associated with key, k. STOP when entry is bigger than key. """ # First place it could be hc = hash(k) % self.M entry = self.table[hc] while entry: # Doesn't exist since keys in sorted order if entry.key > k: return None if entry.key == k: return entry.value entry = entry.next # Couldn't find return None def put(self, k, v): """ Associate value, v, with the key, k. """ # First place it could be hc = hash(k) % self.M entry = self.table[hc] if entry is None: self.N += 1 self.table[hc] = LinkedEntry(k, v, self.table[hc]) return prev = None while entry: # Can insert since we didn't find if entry.key > k: self.N += 1 # new First if prev is None: self.table[hc] = LinkedEntry(k, v, entry) else: prev.next = LinkedEntry(k, v, entry) return # Overwrite if already here if entry.key == k: entry.value = v return prev, entry = entry, entry.next # If we get here, key is largest among all, so append to end prev.next = LinkedEntry(k, v) self.N += 1 def remove(self, k): """ Remove (k,v) entry associated with k. """ # First place it could be hc = hash(k) % self.M entry = self.table[hc] prev = None while entry: if entry.key == k: if prev: prev.next = entry.next else: self.table[hc] = entry.next self.N -= 1 return entry.value prev, entry = entry, entry.next # Nothing was removed return None def __iter__(self): """ Generate all (k, v) tuples for entries in all linked lists table. """ for entry in self.table: while entry: yield (entry.key, entry.value) entry = entry.next def evaluate_hashtable_sorted_chains(output=True, decimals=4): """ Evaluate performance of separate chaining Hashtable with sorted entries. """ import timeit from common.table import DataTable print('Best Case Build Time') tbl = DataTable([8, 20, 20, 20], ['M', 'Open Addressing', 'Separate Chaining', 'Sorted Chains'], output=output, decimals=decimals) for size in [214129, 524287, 999983]: timing_oa = min(timeit.repeat(stmt=''' ht = OpenHashtable({}) for w in reversed(words[:160564]): ht.put(w,w)'''.format(size), setup=''' from algs14_hashtable.hashtable_open import OpenHashtable from resources.english import english_words words = english_words()''', repeat=7, number=5))/5 timing_sc = min(timeit.repeat(stmt=''' ht = LinkedHashtable({}) for w in reversed(words[:160564]): ht.put(w,w)'''.format(size), setup=''' from algs14_hashtable.hashtable_linked import LinkedHashtable from resources.english import english_words words = english_words()''', repeat=7, number=5))/5 timing_sorted = min(timeit.repeat(stmt=''' ht = SortedLinkedListsHashtable({}) for w in reversed(words[:160564]): ht.put(w,w)'''.format(size), setup=''' from algs14_hashtable.hashtable_linked_sorted import SortedLinkedListsHashtable from resources.english import english_words words = english_words()''', repeat=7, number=5))/5 tbl.row([size, timing_oa, timing_sc, timing_sorted]) print('Worst Case Build Time') tbl = DataTable([8, 20, 20, 20], ['M', 'Open Addressing', 'Separate Chaining', 'Sorted Chains'], output=output, decimals=decimals) for size in [214129, 524287, 999983]: timing_oa = min(timeit.repeat(stmt=''' ht = OpenHashtable({}) for w in words[:160564]: ht.put(w,w)'''.format(size), setup=''' from algs14_hashtable.hashtable_open import OpenHashtable from resources.english import english_words words = english_words()''', repeat=7, number=5))/5 timing_sc = min(timeit.repeat(stmt=''' ht = LinkedHashtable({}) for w in words[:160564]: ht.put(w,w)'''.format(size), setup=''' from algs14_hashtable.hashtable_linked import LinkedHashtable from resources.english import english_words words = english_words()''', repeat=7, number=5))/5 timing_sorted = min(timeit.repeat(stmt=''' ht = SortedLinkedListsHashtable({}) for w in words[:160564]: ht.put(w,w)'''.format(size), setup=''' from algs14_hashtable.hashtable_linked_sorted import SortedLinkedListsHashtable from resources.english import english_words words = english_words()''', repeat=7, number=5))/5 tbl.row([size, timing_oa, timing_sc, timing_sorted]) print('Search First Half') tbl = DataTable([8, 20, 20, 20], ['M', 'Open Addressing', 'Separate Chaining', 'Sorted Chains'], output=output, decimals=decimals) for size in [214129, 524287, 999983]: search_oa = min(timeit.repeat(stmt=''' for w in words[:160564]: ht.get(w)''', setup=''' from algs14_hashtable.hashtable_open import OpenHashtable from resources.english import english_words words = english_words() ht = OpenHashtable({}) for w in words[:160564]: ht.put(w,w)'''.format(size), repeat=7, number=5))/5 search_sc = min(timeit.repeat(stmt=''' for w in words[:160564]: ht.get(w)''', setup=''' from algs14_hashtable.hashtable_linked import LinkedHashtable from resources.english import english_words words = english_words() ht = LinkedHashtable({}) for w in words[:160564]: ht.put(w,w)'''.format(size), repeat=7, number=5))/5 search_sorted = min(timeit.repeat(stmt=''' for w in words[:160564]: ht.get(w)''', setup=''' from algs14_hashtable.hashtable_linked_sorted import SortedLinkedListsHashtable from resources.english import english_words words = english_words() ht = SortedLinkedListsHashtable({}) for w in words[:160564]: ht.put(w,w)'''.format(size), repeat=7, number=5))/5 tbl.row([size, search_oa, search_sc, search_sorted]) print('Search Back Half') tbl = DataTable([8, 20, 20, 20], ['M', 'Open Addressing', 'Separate Chaining', 'Sorted Chains'], output=output, decimals=decimals) for size in [214129, 524287, 999983]: search_oa = min(timeit.repeat(stmt=''' for w in words[160564:]: ht.get(w)''', setup=''' from algs14_hashtable.hashtable_open import OpenHashtable from resources.english import english_words words = english_words() ht = OpenHashtable({}) for w in words[:160564]: ht.put(w,w)'''.format(size), repeat=7, number=5))/5 search_sc = min(timeit.repeat(stmt=''' for w in words[160564:]: ht.get(w)''', setup=''' from algs14_hashtable.hashtable_linked import LinkedHashtable from resources.english import english_words words = english_words() ht = LinkedHashtable({}) for w in words[:160564]: ht.put(w,w)'''.format(size), repeat=7, number=5))/5 search_sorted = min(timeit.repeat(stmt=''' for w in words[160564:]: ht.get(w)''', setup=''' from algs14_hashtable.hashtable_linked_sorted import SortedLinkedListsHashtable from resources.english import english_words words = english_words() ht = SortedLinkedListsHashtable({}) for w in words[:160564]: ht.put(w,w)'''.format(size), repeat=7, number=5))/5 tbl.row([size, search_oa, search_sc, search_sorted])

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2ea7bdc15084fd23b19cd3a6bcb6311df50cfdd9

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py

Python

PyBambooHR/__init__.py

zoni/PyBambooHR

a6536501c6dacb3a6b2bc48297925ce0dd499bee

[ "MIT" ]

null

PyBambooHR/__init__.py

zoni/PyBambooHR

a6536501c6dacb3a6b2bc48297925ce0dd499bee

[ "MIT" ]

null

PyBambooHR/__init__.py

zoni/PyBambooHR

a6536501c6dacb3a6b2bc48297925ce0dd499bee

[ "MIT" ]

null

from .PyBambooHR import PyBambooHR

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1

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6

2ec7bd616998921f665afcca6b9687c543f49ad7

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py

Python

tests/emulated_modules/sample_2.py

alisaifee/hiro

e93551b575c10729766b077bb1a79b1f87436a4e

[ "MIT" ]

5

2017-03-16T06:55:38.000Z

2021-04-07T15:42:23.000Z

tests/emulated_modules/sample_2.py

alisaifee/hiro

e93551b575c10729766b077bb1a79b1f87436a4e

[ "MIT" ]

8

2017-01-12T12:26:58.000Z

2020-05-26T02:20:57.000Z

tests/emulated_modules/sample_2.py

alisaifee/hiro

e93551b575c10729766b077bb1a79b1f87436a4e

[ "MIT" ]

4

2016-06-20T11:32:14.000Z

2019-06-27T07:14:44.000Z

import datetime import time from . import sub_module_2 __all__ = ["datetime", "time", "sub_module_2"]

14.857143

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2ee2644e73489fdecbc5d67baf80a77ce15a3d3c

108

py

Python

app/database/models/__init__.py

statar/chat_app_backend

f964c77395d400df47af3dbb663951e0c718636c

[ "MIT" ]

null

app/database/models/__init__.py

statar/chat_app_backend

f964c77395d400df47af3dbb663951e0c718636c

[ "MIT" ]

null

app/database/models/__init__.py

statar/chat_app_backend

f964c77395d400df47af3dbb663951e0c718636c

[ "MIT" ]

null

# src/database/models/__init__.py from .user import * from .user_actions import * # to do remove class

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1

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6

2c0cf66e015204e34e79f95b9b8faa61d5ed2422

74

py

Python

test/__init__.py

toogy/pendigits-hmm

03382e1457941714439d40b67e53eaf117fe4d08

[ "MIT" ]

null

test/__init__.py

toogy/pendigits-hmm

03382e1457941714439d40b67e53eaf117fe4d08

[ "MIT" ]

null

test/__init__.py

toogy/pendigits-hmm

03382e1457941714439d40b67e53eaf117fe4d08

[ "MIT" ]

null

import os import sys sys.path.insert(1, os.path.join(sys.path[0], '..'))

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1

0

6

25ace007eb41f7540d88eb4d9d9c2f7774d2ccda

41

py

Python

deepracing_py/deepracing/exceptions/__init__.py

linklab-uva/deepracing

fc25c47658277df029e7399d295d97a75fe85216

[ "Apache-2.0" ]

11

2020-06-29T15:21:37.000Z

2021-04-12T00:42:26.000Z

deepracing_py/deepracing/exceptions/__init__.py

linklab-uva/deepracing

fc25c47658277df029e7399d295d97a75fe85216

[ "Apache-2.0" ]

null

deepracing_py/deepracing/exceptions/__init__.py

linklab-uva/deepracing

fc25c47658277df029e7399d295d97a75fe85216

[ "Apache-2.0" ]

4

2019-01-23T23:36:57.000Z

2021-07-02T00:18:37.000Z

class DeepRacingException(Exception): ...

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null

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6

25bcdb887b2b6508495bb4a5590b435282354564

44

py

Python

Mundo 3/ex111/utilidadescev/__init__.py

RafaelSdm/Curso-de-Python

ae933ba80ee00ad5160bd5d05cf4b21007943fd4

[ "MIT" ]

1

2021-03-10T21:53:38.000Z

Mundo 3/ex112/utilidadescev/__init__.py

RafaelSdm/Curso-de-Python

ae933ba80ee00ad5160bd5d05cf4b21007943fd4

[ "MIT" ]

null

Mundo 3/ex112/utilidadescev/__init__.py

RafaelSdm/Curso-de-Python

ae933ba80ee00ad5160bd5d05cf4b21007943fd4

[ "MIT" ]

null

from ex111.utilidadescev import moeda, dado

44

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0

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6

25d6c3e6fa7a63921e9c6c46cac0f6c0f4a47fce

777

py

Python

app/urls.py

thexdesk/ESPN-API

debaf328d385c688f90dbb96703244f87da3c100

[ "MIT" ]

null

app/urls.py

thexdesk/ESPN-API

debaf328d385c688f90dbb96703244f87da3c100

[ "MIT" ]

3

2020-06-05T17:12:59.000Z

2021-06-10T18:09:18.000Z

app/urls.py

thexdesk/ESPN-API

debaf328d385c688f90dbb96703244f87da3c100

[ "MIT" ]

1

2020-02-09T08:17:18.000Z

from django.conf.urls import url from . import views urlpatterns = [ url(r'^(?P<leagueId>[0-9]+)/(?P<year>[0-9]+)/teams/$', views.getTeams), url(r'^(?P<leagueId>[0-9]+)/(?P<year>[0-9]+)/teams/(?P<teamId>[0-9]+)/$', views.getTeam), url(r'^(?P<leagueId>[0-9]+)/(?P<year>[0-9]+)/power-rankings/$', views.getPowerRankings), url(r'^(?P<leagueId>[0-9]+)/(?P<year>[0-9]+)/scoreboard/$', views.getScoreboard), url(r'^(?P<leagueId>[0-9]+)/teams/$', views.getTeams), url(r'^(?P<leagueId>[0-9]+)/teams/(?P<teamId>[0-9]+)/$', views.getTeam), url(r'^(?P<leagueId>[0-9]+)/teams/(?P<teamId>[0-9]+)/history/$', views.getTeamHistory), url(r'^(?P<leagueId>[0-9]+)/power-rankings/$', views.getPowerRankings), url(r'^(?P<leagueId>[0-9]+)/scoreboard/$', views.getScoreboard), ]

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null

0

6

d349b3c3a757a1de1806a79e04ae9cb4d1476671

35

py

Python

opensenate/parliamentarians/__init__.py

g0ulartleo/opendata-senado

091d060d55d49f844d192baa1c0aef1aa039f1c0

[ "MIT" ]

null

opensenate/parliamentarians/__init__.py

g0ulartleo/opendata-senado

091d060d55d49f844d192baa1c0aef1aa039f1c0

[ "MIT" ]

null

opensenate/parliamentarians/__init__.py

g0ulartleo/opendata-senado

091d060d55d49f844d192baa1c0aef1aa039f1c0

[ "MIT" ]

null

from .senator import SenatorClient

17.5

34

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1

35

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null

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1

0

1

0

6

d36c69306b1f6cccfb85b59f8fe15a647e6867a7

214

py

Python

defining_classes/demo.py

Minkov/python-oop-2020-02

d2acb1504c1a135cded2ae6ff42acccb303d9ab1

[ "MIT" ]

2

2020-02-27T18:34:45.000Z

2020-10-25T17:34:15.000Z

defining_classes/demo.py

Minkov/python-oop-2020-02

d2acb1504c1a135cded2ae6ff42acccb303d9ab1

[ "MIT" ]

null

defining_classes/demo.py

Minkov/python-oop-2020-02

d2acb1504c1a135cded2ae6ff42acccb303d9ab1

[ "MIT" ]

null

from math import pi class Circle: def __init__(self, radius): self.radius = radius def area(self): return self.radius * self.radius * pi c = Circle(5) print(c.__dict__) print(c.area())

14.266667

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1

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null

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1

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6

d38a4bf8ce92fcdac6b2fdce750c0f27939d21eb

6,804

py

Python

tests/initsync/data_report_initsync_summary.py

iagcl/data_pipeline

b9b965d43a4261357e417f4eeee5d8b7d2dfd858

[ "Apache-2.0" ]

16

2017-10-31T21:43:26.000Z

2019-08-11T08:49:06.000Z

tests/initsync/data_report_initsync_summary.py

iagcl/data_pipeline

b9b965d43a4261357e417f4eeee5d8b7d2dfd858

[ "Apache-2.0" ]

1

2017-11-01T06:25:56.000Z

tests/initsync/data_report_initsync_summary.py

iagcl/data_pipeline

b9b965d43a4261357e417f4eeee5d8b7d2dfd858

[ "Apache-2.0" ]

9

2017-10-30T05:23:15.000Z

2022-02-17T03:53:09.000Z

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. # import collections import data_pipeline.constants.const as const TestCase = collections.namedtuple('TestCase', "description input_all_table_results expected_subject expected_total_count expected_status expected_min_lsn expected_max_lsn expected_run_id expected_mailing_list") tests=[ TestCase( description="Single table success", input_all_table_results={ 'tableA': (123, const.SUCCESS, const.INITSYNCEXTRACT, "foo") }, expected_total_count=1, expected_status=const.SUCCESS, expected_min_lsn=123, expected_max_lsn=123, expected_run_id=1, expected_subject='myprofile InitSync SUCCESS', expected_mailing_list=set(['someone@gmail.com']), ), TestCase( description="Single table success, extractlsn disabled", input_all_table_results={ 'tableA': (None, const.SUCCESS, const.INITSYNCEXTRACT, "foo") }, expected_total_count=1, expected_status=const.SUCCESS, expected_min_lsn=None, expected_max_lsn=None, expected_run_id=1, expected_subject='myprofile InitSync SUCCESS', expected_mailing_list=set(['someone@gmail.com']), ), TestCase( description="Single table error", input_all_table_results={ 'tableA': (123, const.ERROR, const.INITSYNCEXTRACT, "foo") }, expected_total_count=1, expected_status=const.ERROR, expected_min_lsn=123, expected_max_lsn=123, expected_run_id=1, expected_subject='myprofile InitSync ERROR', expected_mailing_list=set(['someone@gmail.com', 'someone@error.com']), ), TestCase( description="Three table success", input_all_table_results={ 'tableA': (123, const.SUCCESS, const.INITSYNCEXTRACT, "foo"), 'tableB': (123, const.SUCCESS, const.INITSYNCEXTRACT, "foo"), 'tableC': (123, const.SUCCESS, const.INITSYNCEXTRACT, "foo"), }, expected_total_count=3, expected_status=const.SUCCESS, expected_min_lsn=123, expected_max_lsn=123, expected_run_id=1, expected_subject='myprofile InitSync SUCCESS', expected_mailing_list=set(['someone@gmail.com']), ), TestCase( description="Three table error", input_all_table_results={ 'tableA': (123, const.ERROR, const.INITSYNCEXTRACT, "foo"), 'tableB': (123, const.ERROR, const.INITSYNCEXTRACT, "foo"), 'tableC': (123, const.ERROR, const.INITSYNCEXTRACT, "foo"), }, expected_total_count=3, expected_status=const.ERROR, expected_min_lsn=123, expected_max_lsn=123, expected_run_id=1, expected_subject='myprofile InitSync ERROR', expected_mailing_list=set(['someone@gmail.com', 'someone@error.com']), ), TestCase( description="Error on last table resulting in warning", input_all_table_results={ 'tableA': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableB': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableC': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableD': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableE': (123, const.ERROR, const.INITSYNCAPPLY, "foo"), }, expected_total_count=5, expected_status=const.WARNING, expected_min_lsn=123, expected_max_lsn=123, expected_run_id=1, expected_subject='myprofile InitSync WARNING (4 out of 5)', expected_mailing_list=set(['someone@gmail.com', 'someone@error.com']), ), TestCase( description="Error on second last table resulting in warning", input_all_table_results={ 'tableA': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableB': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableC': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableD': (123, const.ERROR, const.INITSYNCAPPLY, "foo"), 'tableE': (123, const.SUCCESS, const.INITSYNC, "foo"), }, expected_total_count=5, expected_status=const.WARNING, expected_min_lsn=123, expected_max_lsn=123, expected_run_id=1, expected_subject='myprofile InitSync WARNING (4 out of 5)', expected_mailing_list=set(['someone@gmail.com', 'someone@error.com']), ), TestCase( description="Error on first table resulting in warning", input_all_table_results={ 'tableA': (123, const.ERROR, const.INITSYNCAPPLY, "foo"), 'tableB': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableC': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableD': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableE': (123, const.SUCCESS, const.INITSYNC, "foo"), }, expected_total_count=5, expected_status=const.WARNING, expected_min_lsn=123, expected_max_lsn=123, expected_run_id=1, expected_subject='myprofile InitSync WARNING (4 out of 5)', expected_mailing_list=set(['someone@gmail.com', 'someone@error.com']), ), TestCase( description="Error on middle table resulting in warning", input_all_table_results={ 'tableA': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableB': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableC': (123, const.ERROR, const.INITSYNCAPPLY, "foo"), 'tableD': (123, const.SUCCESS, const.INITSYNC, "foo"), 'tableE': (123, const.SUCCESS, const.INITSYNC, "foo"), }, expected_total_count=5, expected_status=const.WARNING, expected_min_lsn=123, expected_max_lsn=123, expected_run_id=1, expected_subject='myprofile InitSync WARNING (4 out of 5)', expected_mailing_list=set(['someone@gmail.com', 'someone@error.com']), ), ]

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null

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1

0

null

0

6

d3997bdf79040050d8c8df1e6fd35c04b1a7fa9d

146

py

Python

mysite/polls/views.py

cs-fullstack-fall-2018/django-intro1-RoyzellW

1e011df68e9d2533a55be83b3b0c3a82ee854a8e

[ "Apache-2.0" ]

null

mysite/polls/views.py

cs-fullstack-fall-2018/django-intro1-RoyzellW

1e011df68e9d2533a55be83b3b0c3a82ee854a8e

[ "Apache-2.0" ]

null

mysite/polls/views.py

cs-fullstack-fall-2018/django-intro1-RoyzellW

1e011df68e9d2533a55be83b3b0c3a82ee854a8e

[ "Apache-2.0" ]

null

from django.shortcuts import render # Create your views here. def index(request): return HttpResponse("This is broken, try something else.")

24.333333

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1

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6

4cb6c57c0f7a17520a9ed625c51ba885556b15bd

7,236

py

Python

tests/callbacks/test_torch_scheduler.py

Ddaniela13/torchbearer

89c2724b76f3a85065ea79598aece4b2c3c5f7fb

[ "MIT" ]

null

tests/callbacks/test_torch_scheduler.py

Ddaniela13/torchbearer

89c2724b76f3a85065ea79598aece4b2c3c5f7fb

[ "MIT" ]

null

tests/callbacks/test_torch_scheduler.py

Ddaniela13/torchbearer

89c2724b76f3a85065ea79598aece4b2c3c5f7fb

[ "MIT" ]

null

from unittest import TestCase from mock import patch, Mock import torchbearer from torchbearer.callbacks import TorchScheduler, LambdaLR, StepLR, MultiStepLR, ExponentialLR, CosineAnnealingLR,\ ReduceLROnPlateau class TestTorchScheduler(TestCase): def test_torch_scheduler_on_batch_with_monitor(self): state = {torchbearer.EPOCH: 1, torchbearer.METRICS: {'test': 101}, torchbearer.OPTIMIZER: 'optimizer'} mock_scheduler = Mock() mock_scheduler.return_value = mock_scheduler torch_scheduler = TorchScheduler(lambda opt: mock_scheduler(opt), monitor='test', step_on_batch=True) torch_scheduler.on_start(state) mock_scheduler.assert_called_once_with('optimizer') mock_scheduler.reset_mock() torch_scheduler.on_start_training(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() torch_scheduler.on_sample(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() torch_scheduler.on_step_training(state) mock_scheduler.step.assert_called_once_with(101) mock_scheduler.reset_mock() torch_scheduler.on_end_epoch(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() def test_torch_scheduler_on_epoch_with_monitor(self): state = {torchbearer.EPOCH: 1, torchbearer.METRICS: {'test': 101}, torchbearer.OPTIMIZER: 'optimizer'} mock_scheduler = Mock() mock_scheduler.return_value = mock_scheduler torch_scheduler = TorchScheduler(lambda opt: mock_scheduler(opt), monitor='test', step_on_batch=False) torch_scheduler.on_start(state) mock_scheduler.assert_called_once_with('optimizer') mock_scheduler.reset_mock() torch_scheduler.on_start_training(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() torch_scheduler.on_sample(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() torch_scheduler.on_step_training(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() torch_scheduler.on_end_epoch(state) mock_scheduler.step.assert_called_once_with(101, epoch=1) mock_scheduler.reset_mock() def test_torch_scheduler_on_batch_no_monitor(self): state = {torchbearer.EPOCH: 1, torchbearer.OPTIMIZER: 'optimizer'} mock_scheduler = Mock() mock_scheduler.return_value = mock_scheduler torch_scheduler = TorchScheduler(lambda opt: mock_scheduler(opt), monitor=None, step_on_batch=True) torch_scheduler.on_start(state) mock_scheduler.assert_called_once_with('optimizer') mock_scheduler.reset_mock() torch_scheduler.on_start_training(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() torch_scheduler.on_sample(state) mock_scheduler.step.assert_called_once_with() mock_scheduler.reset_mock() torch_scheduler.on_step_training(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() torch_scheduler.on_end_epoch(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() def test_torch_scheduler_on_epoch_no_monitor(self): state = {torchbearer.EPOCH: 1, torchbearer.OPTIMIZER: 'optimizer'} mock_scheduler = Mock() mock_scheduler.return_value = mock_scheduler torch_scheduler = TorchScheduler(lambda opt: mock_scheduler(opt), monitor=None, step_on_batch=False) torch_scheduler.on_start(state) mock_scheduler.assert_called_once_with('optimizer') mock_scheduler.reset_mock() torch_scheduler.on_start_training(state) mock_scheduler.step.assert_called_once_with(epoch=1) mock_scheduler.reset_mock() torch_scheduler.on_sample(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() torch_scheduler.on_step_training(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() torch_scheduler.on_end_epoch(state) mock_scheduler.assert_not_called() mock_scheduler.reset_mock() class TestLambdaLR(TestCase): @patch('torch.optim.lr_scheduler.LambdaLR') def test_lambda_lr(self, lr_mock): state = {torchbearer.OPTIMIZER: 'optimizer'} scheduler = LambdaLR(0.1, last_epoch=-4, step_on_batch='batch') scheduler.on_start(state) lr_mock.assert_called_once_with('optimizer', 0.1, last_epoch=-4) self.assertTrue(scheduler._step_on_batch == 'batch') class TestStepLR(TestCase): @patch('torch.optim.lr_scheduler.StepLR') def test_lambda_lr(self, lr_mock): state = {torchbearer.OPTIMIZER: 'optimizer'} scheduler = StepLR(10, gamma=0.4, last_epoch=-4, step_on_batch='batch') scheduler.on_start(state) lr_mock.assert_called_once_with('optimizer', 10, gamma=0.4, last_epoch=-4) self.assertTrue(scheduler._step_on_batch == 'batch') class TestMultiStepLR(TestCase): @patch('torch.optim.lr_scheduler.MultiStepLR') def test_lambda_lr(self, lr_mock): state = {torchbearer.OPTIMIZER: 'optimizer'} scheduler = MultiStepLR(10, gamma=0.4, last_epoch=-4, step_on_batch='batch') scheduler.on_start(state) lr_mock.assert_called_once_with('optimizer', 10, gamma=0.4, last_epoch=-4) self.assertTrue(scheduler._step_on_batch == 'batch') class TestExponentialLR(TestCase): @patch('torch.optim.lr_scheduler.ExponentialLR') def test_lambda_lr(self, lr_mock): state = {torchbearer.OPTIMIZER: 'optimizer'} scheduler = ExponentialLR(0.4, last_epoch=-4, step_on_batch='batch') scheduler.on_start(state) lr_mock.assert_called_once_with('optimizer', 0.4, last_epoch=-4) self.assertTrue(scheduler._step_on_batch == 'batch') class TestCosineAnnealingLR(TestCase): @patch('torch.optim.lr_scheduler.CosineAnnealingLR') def test_lambda_lr(self, lr_mock): state = {torchbearer.OPTIMIZER: 'optimizer'} scheduler = CosineAnnealingLR(4, eta_min=10, last_epoch=-4, step_on_batch='batch') scheduler.on_start(state) lr_mock.assert_called_once_with('optimizer', 4, eta_min=10, last_epoch=-4) self.assertTrue(scheduler._step_on_batch == 'batch') class TestReduceLROnPlateau(TestCase): @patch('torch.optim.lr_scheduler.ReduceLROnPlateau') def test_lambda_lr(self, lr_mock): state = {torchbearer.OPTIMIZER: 'optimizer'} scheduler = ReduceLROnPlateau(monitor='test', mode='max', factor=0.2, patience=100, verbose=True, threshold=10, threshold_mode='thresh', cooldown=5, min_lr=0.1, eps=1e-4, step_on_batch='batch') scheduler.on_start(state) lr_mock.assert_called_once_with('optimizer', mode='max', factor=0.2, patience=100, verbose=True, threshold=10, threshold_mode='thresh', cooldown=5, min_lr=0.1, eps=1e-4) self.assertTrue(scheduler._step_on_batch == 'batch') self.assertTrue(scheduler._monitor == 'test')

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0

null

0

1

0

null

0

6

4ce147c505ab00aaa9c2199911991ce54819aa27

3,394

py

Python

tests/unit_tests/test_michelson/test_repl/test_chest.py

m-kus/pytezos

dfb7e34a4ca24b5cf40541900c5f761c61571996

[ "MIT" ]

null

tests/unit_tests/test_michelson/test_repl/test_chest.py

m-kus/pytezos

dfb7e34a4ca24b5cf40541900c5f761c61571996

[ "MIT" ]

null

tests/unit_tests/test_michelson/test_repl/test_chest.py

m-kus/pytezos

dfb7e34a4ca24b5cf40541900c5f761c61571996

[ "MIT" ]

null

from unittest import TestCase, skip from pytezos.contract.interface import ContractInterface source = """ storage (bytes); parameter (pair (chest_key) (chest)); code { UNPAIR; DIP {DROP}; UNPAIR; DIIP {PUSH nat 1000}; OPEN_CHEST; IF_LEFT { # successful case NIL operation; PAIR ; } { IF { # first type of failure PUSH bytes 0x01; NIL operation; PAIR; } { # second type of failure PUSH bytes 0x00; NIL operation; PAIR; } } } """ chest_key = bytes.fromhex( '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') chest = bytes.fromhex( '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') @skip class OpenChestTestCase(TestCase): def test_open_chest(self): ci = ContractInterface.from_michelson(source) ci.call(chest_key, chest).interpret()

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4ce720597fdb62dfff722e3c7d80c43be3dfe355

2,164

py

Python

blender/2.79/scripts/addons/add_curve_sapling/presets/japanese_maple.py

uzairakbar/bpy2.79

3a3e0004ac6783c4e4b89d939e4432de99026a85

[ "MIT" ]

2

2019-11-27T09:05:42.000Z

2020-02-20T01:25:23.000Z

add_curve_sapling/presets/japanese_maple.py

1-MillionParanoidTterabytes/blender-addons-master

acc8fc23a38e6e89099c3e5079bea31ce85da06a

[ "Unlicense" ]

null

add_curve_sapling/presets/japanese_maple.py

1-MillionParanoidTterabytes/blender-addons-master

acc8fc23a38e6e89099c3e5079bea31ce85da06a

[ "Unlicense" ]

4

2020-02-19T20:02:26.000Z

2022-02-11T18:47:56.000Z

{'leafScaleT': -0.5, 'shapeS': '10', 'scaleV': 2.0, 'resU': 4, 'boneStep': (1, 1, 1, 1), 'af3': 4.0, 'baseSize': 0.4000000059604645, 'prunePowerLow': 0.0010000000474974513, 'leafRotateV': 0.0, 'rootFlare': 1.0, 'customShape': (0.699999988079071, 1.0, 0.20000000298023224, 0.800000011920929), 'attractOut': (0.0, 0.75, 0.25, 0.0), 'useArm': False, 'branches': (0, 50, 10, 16), 'leafDownAngle': 45.0, 'length': (1.0, 0.30000001192092896, 0.5, 0.20000000298023224), 'segSplits': (0.25, 0.4000000059604645, 0.5, 0.0), 'makeMesh': False, 'curveV': (400.0, 150.0, 100.0, 0.0), 'curveBack': (0.0, 0.0, 0.0, 0.0), 'af1': 1.0, 'closeTip': False, 'frameRate': 1.0, 'leafangle': -10.0, 'af2': 1.0, 'rMode': 'rotate', 'leafScaleV': 0.0, 'rotateV': (15.0, 0.0, 0.0, 0.0), 'useParentAngle': False, 'taperCrown': 0.0, 'minRadius': 0.001500000013038516, 'splitAngleV': (5.0, 5.0, 0.0, 0.0), 'scaleV0': 0.10000000149011612, 'bevel': True, 'leafDownAngleV': 10.0, 'previewArm': False, 'showLeaves': True, 'ratioPower': 1.25, 'handleType': '0', 'branchDist': 1.0, 'leafScaleX': 0.20000000298023224, 'prune': False, 'splitHeight': 0.30000001192092896, 'baseSplits': 2, 'baseSize_s': 0.25, 'downAngle': (90.0, 90.0, 30.0, 30.0), 'bevelRes': 1, 'leafAnim': False, 'loopFrames': 0, 'lengthV': (0.0, 0.0, 0.0, 0.0), 'gust': 1.0, 'downAngleV': (0.0, 90.0, 15.0, 10.0), 'leafRotate': 137.5, 'wind': 1.0, 'leaves': -5, 'curve': (0.0, -20.0, -20.0, 0.0), 'radiusTweak': (1.0, 1.0, 1.0, 1.0), 'pruneRatio': 1.0, 'pruneBase': 0.30000001192092896, 'armAnim': False, 'splitBias': 0.0, 'rotate': (99.5, 137.5, 137.5, 137.5), 'armLevels': 2, 'scale': 6.0, 'prunePowerHigh': 0.5, 'nrings': 0, 'splitByLen': True, 'leafShape': 'hex', 'splitAngle': (15.0, 20.0, 25.0, 0.0), 'ratio': 0.019999999552965164, 'scale0': 1.0, 'autoTaper': True, 'pruneWidth': 0.4000000059604645, 'leafScale': 0.17000000178813934, 'seed': 0, 'curveRes': (16, 5, 3, 1), 'horzLeaves': True, 'useOldDownAngle': False, 'levels': 4, 'pruneWidthPeak': 0.6000000238418579, 'attractUp': (0.0, -0.3499999940395355, -0.20000000298023224, 0.0), 'taper': (1.0, 1.0, 1.0, 1.0), 'leafDist': '6', 'gustF': 0.07500000298023224, 'shape': '8'}

2,164

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0

1

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1

0

null

0

1

0

6

e2635abc229517d1d5fec156db782537421fce5a

12,331

py

Python

test/orm/test_session_state_change.py

petit87/sqlalchemy

67d674bd63ca36ac32b23f96e2b19e9dac6b0863

[ "MIT" ]

null

test/orm/test_session_state_change.py

petit87/sqlalchemy

67d674bd63ca36ac32b23f96e2b19e9dac6b0863

[ "MIT" ]

null

test/orm/test_session_state_change.py

petit87/sqlalchemy

67d674bd63ca36ac32b23f96e2b19e9dac6b0863

[ "MIT" ]

1

2022-02-28T20:16:29.000Z

from sqlalchemy import exc as sa_exc from sqlalchemy.orm import state_changes from sqlalchemy.testing import eq_ from sqlalchemy.testing import expect_raises_message from sqlalchemy.testing import fixtures class StateTestChange(state_changes._StateChangeState): a = 1 b = 2 c = 3 class StateMachineTest(fixtures.TestBase): def test_single_change(self): """test single method that declares and invokes a state change""" _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.b ) def move_to_b(self): self._state = StateTestChange.b m = Machine() eq_(m._state, _NO_CHANGE) m.move_to_b() eq_(m._state, StateTestChange.b) def test_single_incorrect_change(self): """test single method that declares a state change but changes to the wrong state.""" _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.b ) def move_to_b(self): self._state = StateTestChange.c m = Machine() eq_(m._state, _NO_CHANGE) with expect_raises_message( sa_exc.IllegalStateChangeError, r"Method 'move_to_b' " r"caused an unexpected state change to <StateTestChange.c: 3>", ): m.move_to_b() def test_single_failed_to_change(self): """test single method that declares a state change but didn't do the change.""" _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.b ) def move_to_b(self): pass m = Machine() eq_(m._state, _NO_CHANGE) with expect_raises_message( sa_exc.IllegalStateChangeError, r"Method 'move_to_b' failed to change state " "to <StateTestChange.b: 2> as " "expected", ): m.move_to_b() def test_change_from_sub_method_with_declaration(self): """test successful state change by one method calling another that does the change. """ _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.b ) def _inner_move_to_b(self): self._state = StateTestChange.b @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.b ) def move_to_b(self): with self._expect_state(StateTestChange.b): self._inner_move_to_b() m = Machine() eq_(m._state, _NO_CHANGE) m.move_to_b() eq_(m._state, StateTestChange.b) def test_method_and_sub_method_no_change(self): """test methods that declare the state should not change""" _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): @state_changes._StateChange.declare_states( (StateTestChange.a,), _NO_CHANGE ) def _inner_do_nothing(self): pass @state_changes._StateChange.declare_states( (StateTestChange.a,), _NO_CHANGE ) def do_nothing(self): self._inner_do_nothing() m = Machine() eq_(m._state, _NO_CHANGE) m._state = StateTestChange.a m.do_nothing() eq_(m._state, StateTestChange.a) def test_method_w_no_change_illegal_inner_change(self): _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.c ) def _inner_move_to_c(self): self._state = StateTestChange.c @state_changes._StateChange.declare_states( (StateTestChange.a,), _NO_CHANGE ) def do_nothing(self): self._inner_move_to_c() m = Machine() eq_(m._state, _NO_CHANGE) m._state = StateTestChange.a with expect_raises_message( sa_exc.IllegalStateChangeError, r"Method '_inner_move_to_c' can't be called here; " r"method 'do_nothing' is already in progress and this " r"would cause an unexpected state change to " "<StateTestChange.c: 3>", ): m.do_nothing() eq_(m._state, StateTestChange.a) def test_change_from_method_sub_w_no_change(self): """test methods that declare the state should not change""" _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): @state_changes._StateChange.declare_states( (StateTestChange.a,), _NO_CHANGE ) def _inner_do_nothing(self): pass @state_changes._StateChange.declare_states( (StateTestChange.a,), StateTestChange.b ) def move_to_b(self): self._inner_do_nothing() self._state = StateTestChange.b m = Machine() eq_(m._state, _NO_CHANGE) m._state = StateTestChange.a m.move_to_b() eq_(m._state, StateTestChange.b) def test_invalid_change_from_declared_sub_method_with_declaration(self): """A method uses _expect_state() to call a sub-method, which must declare that state as its destination if no exceptions are raised. """ _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): # method declares StateTestChange.c so can't be called under # expect_state(StateTestChange.b) @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.c ) def _inner_move_to_c(self): self._state = StateTestChange.c @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.b ) def move_to_b(self): with self._expect_state(StateTestChange.b): self._inner_move_to_c() m = Machine() eq_(m._state, _NO_CHANGE) with expect_raises_message( sa_exc.IllegalStateChangeError, r"Cant run operation '_inner_move_to_c' here; will move " r"to state <StateTestChange.c: 3> where we are " "expecting <StateTestChange.b: 2>", ): m.move_to_b() def test_invalid_change_from_invalid_sub_method_with_declaration(self): """A method uses _expect_state() to call a sub-method, which must declare that state as its destination if no exceptions are raised. Test an error is raised if the sub-method doesn't change to the correct state. """ _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): # method declares StateTestChange.b, but is doing the wrong # change, so should fail under expect_state(StateTestChange.b) @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.b ) def _inner_move_to_c(self): self._state = StateTestChange.c @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.b ) def move_to_b(self): with self._expect_state(StateTestChange.b): self._inner_move_to_c() m = Machine() eq_(m._state, _NO_CHANGE) with expect_raises_message( sa_exc.IllegalStateChangeError, r"While method 'move_to_b' was running, method " r"'_inner_move_to_c' caused an unexpected state change " "to <StateTestChange.c: 3>", ): m.move_to_b() def test_invalid_prereq_state(self): _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.b ) def move_to_b(self): self._state = StateTestChange.b @state_changes._StateChange.declare_states( (StateTestChange.c,), "d" ) def move_to_d(self): self._state = "d" m = Machine() eq_(m._state, _NO_CHANGE) m.move_to_b() eq_(m._state, StateTestChange.b) with expect_raises_message( sa_exc.IllegalStateChangeError, r"Can't run operation 'move_to_d' when " "Session is in state <StateTestChange.b: 2>", ): m.move_to_d() def test_declare_only(self): _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): @state_changes._StateChange.declare_states( state_changes._StateChangeStates.ANY, StateTestChange.b ) def _inner_move_to_b(self): self._state = StateTestChange.b def move_to_b(self): with self._expect_state(StateTestChange.b): self._move_to_b() m = Machine() eq_(m._state, _NO_CHANGE) with expect_raises_message( AssertionError, "Unexpected call to _expect_state outside of " "state-changing method", ): m.move_to_b() def test_sibling_calls_maintain_correct_state(self): _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): @state_changes._StateChange.declare_states( state_changes._StateChangeStates.ANY, StateTestChange.c ) def move_to_c(self): self._state = StateTestChange.c @state_changes._StateChange.declare_states( state_changes._StateChangeStates.ANY, _NO_CHANGE ) def do_nothing(self): pass m = Machine() m.do_nothing() eq_(m._state, _NO_CHANGE) m.move_to_c() eq_(m._state, StateTestChange.c) def test_change_from_sub_method_requires_declaration(self): """A method can't call another state-changing method without using _expect_state() to allow the state change to occur. """ _NO_CHANGE = state_changes._StateChangeStates.NO_CHANGE class Machine(state_changes._StateChange): @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.b ) def _inner_move_to_b(self): self._state = StateTestChange.b @state_changes._StateChange.declare_states( (StateTestChange.a, _NO_CHANGE), StateTestChange.b ) def move_to_b(self): self._inner_move_to_b() m = Machine() with expect_raises_message( sa_exc.IllegalStateChangeError, r"Method '_inner_move_to_b' can't be called here; " r"method 'move_to_b' is already in progress and this would " r"cause an unexpected state change to <StateTestChange.b: 2>", ): m.move_to_b()

35.536023

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5.115356

0.098457

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0.115628

0.0948

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0.797472

0.768026

0.757254

0.740305

0

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0.312465

12,331

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35.638728

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0.086692

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0.694656

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0.083176

0.007922

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1

0.137405

false

0.015267

0.019084

0

0.225191

0

null

0

1

0

null

0

6

e26452fe4d62f2442629588e7aeb574618c3bc8c

46

py

Python

examples/restAPI/my_project/config/settings/local.py

emilioag/django_rest_coreapi_schema

9b95f01311f0ba3f936762ba19c96c8a94f1f91f

[ "MIT" ]

null

examples/restAPI/my_project/config/settings/local.py

emilioag/django_rest_coreapi_schema

9b95f01311f0ba3f936762ba19c96c8a94f1f91f

[ "MIT" ]

3

2020-06-05T16:39:19.000Z

2021-06-10T18:06:23.000Z

examples/restAPI/my_project/config/settings/local.py

emilioag/django_rest_coreapi_schema

9b95f01311f0ba3f936762ba19c96c8a94f1f91f

[ "MIT" ]

null

from .base import * print("Settings: LOCAL")

11.5

24

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6

46

5.333333

1

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0.152174

46

3

25

15.333333

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null

0

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0

1

0

1

0

6

e29d9438f2046b1b8603b9ad5110651fb9a06d8a

9,143

py

Python

packages/task-scheduler/task_scheduler/routes/tasks/test_tasks.py

baviera08/romi-dashboard

ac3a15014ad3c3bdac523a6550934a06653cfba1

[ "Apache-2.0" ]

null

packages/task-scheduler/task_scheduler/routes/tasks/test_tasks.py

baviera08/romi-dashboard

ac3a15014ad3c3bdac523a6550934a06653cfba1

[ "Apache-2.0" ]

1

2020-12-01T20:25:32.000Z

packages/task-scheduler/task_scheduler/routes/tasks/test_tasks.py

baviera08/romi-dashboard

ac3a15014ad3c3bdac523a6550934a06653cfba1

[ "Apache-2.0" ]

null

# import asyncio # import concurrent.futures # from rmf_task_msgs.msg import TaskSummary as RmfTaskSummary # from rmf_task_msgs.msg import TaskType as RmfTaskType # from rmf_task_msgs.srv import CancelTask as RmfCancelTask # from rmf_task_msgs.srv import SubmitTask as RmfSubmitTask # from ...models import CancelTask, CleanTaskDescription, SubmitTask, TaskSummary # from ...models import tortoise_models as ttm # from ..test_fixtures import RouteFixture # class TestTasksRoute(RouteFixture): # def test_submit_task_request(self): # # create a submit task request message # task = SubmitTask( # task_type=RmfTaskType.TYPE_CLEAN, # start_time=0, # description=CleanTaskDescription(cleaning_zone="zone_2"), # priority=0, # ) # fut = self.host_service_one( # RmfSubmitTask, "submit_task", RmfSubmitTask.Response(success=True) # ) # resp = self.session.post(f"{self.base_url}/tasks/submit_task", data=task.json()) # self.assertEqual(resp.status_code, 200) # ros_received: RmfSubmitTask.Request = fut.result(3) # self.assertEqual(ros_received.requester, "rmf_server") # def test_cancel_task_request(self): # cancel_task = CancelTask(task_id="test_task") # fut = self.host_service_one( # RmfCancelTask, "cancel_task", RmfCancelTask.Response(success=True) # ) # resp = self.session.post( # f"{self.base_url}/tasks/cancel_task", data=cancel_task.json() # ) # self.assertEqual(resp.status_code, 200) # received: RmfCancelTask.Request = fut.result(3) # self.assertEqual(received.task_id, "test_task") # def test_cancel_task_failure(self): # cancel_task = CancelTask(task_id="test_task") # fut = self.host_service_one( # RmfCancelTask, # "cancel_task", # RmfCancelTask.Response(success=False, message="test error"), # ) # resp = self.session.post( # f"{self.base_url}/tasks/cancel_task", data=cancel_task.json() # ) # self.assertEqual(resp.status_code, 500) # fut.result(3) # self.assertEqual(resp.json()["detail"], "test error") # def test_query_tasks(self): # dataset = [ # TaskSummary( # task_id="task_1", # fleet_name="fleet_1", # submission_time={"sec": 1000, "nanosec": 0}, # start_time={"sec": 2000, "nanosec": 0}, # end_time={"sec": 3000, "nanosec": 0}, # robot_name="robot_1", # state=RmfTaskSummary.STATE_COMPLETED, # task_profile={ # "description": { # "task_type": {"type": RmfTaskType.TYPE_LOOP}, # "priority": {"value": 0}, # } # }, # ), # TaskSummary( # task_id="task_2", # fleet_name="fleet_2", # submission_time={"sec": 4000, "nanosec": 0}, # start_time={"sec": 5000, "nanosec": 0}, # end_time={"sec": 6000, "nanosec": 0}, # robot_name="robot_2", # state=RmfTaskSummary.STATE_ACTIVE, # task_profile={ # "description": { # "task_type": {"type": RmfTaskType.TYPE_DELIVERY}, # "priority": {"value": 1}, # } # }, # ), # ] # fut = concurrent.futures.Future() # async def save_data(): # fut.set_result( # await asyncio.gather( # *(ttm.TaskSummary.save_pydantic(data) for data in dataset) # ) # ) # self.server.app.wait_ready() # self.server.app.loop.create_task(save_data()) # fut.result() # resp = self.session.get(f"{self.base_url}/tasks?task_id=task_1,task_2") # self.assertEqual(resp.status_code, 200) # resp_json = resp.json() # items = resp_json["items"] # self.assertEqual(len(items), 2) # resp = self.session.get(f"{self.base_url}/tasks?fleet_name=fleet_1") # self.assertEqual(resp.status_code, 200) # resp_json = resp.json() # items = resp_json["items"] # self.assertEqual(len(items), 1) # self.assertEqual(items[0]["task_summary"]["task_id"], "task_1") # self.assertEqual(items[0]["task_summary"]["fleet_name"], "fleet_1") # resp = self.session.get(f"{self.base_url}/tasks?robot_name=robot_1") # self.assertEqual(resp.status_code, 200) # resp_json = resp.json() # items = resp_json["items"] # self.assertEqual(len(items), 1) # self.assertEqual(items[0]["task_summary"]["task_id"], "task_1") # self.assertEqual(items[0]["task_summary"]["robot_name"], "robot_1") # resp = self.session.get(f"{self.base_url}/tasks?state=completed") # self.assertEqual(resp.status_code, 200) # resp_json = resp.json() # items = resp_json["items"] # self.assertEqual(len(items), 1) # self.assertEqual(items[0]["task_summary"]["task_id"], "task_1") # self.assertEqual( # items[0]["task_summary"]["state"], RmfTaskSummary.STATE_COMPLETED # ) # resp = self.session.get(f"{self.base_url}/tasks?task_type=loop") # self.assertEqual(resp.status_code, 200) # resp_json = resp.json() # items = resp_json["items"] # self.assertEqual(len(items), 1) # self.assertEqual(items[0]["task_summary"]["task_id"], "task_1") # self.assertEqual( # items[0]["task_summary"]["task_profile"]["description"]["task_type"][ # "type" # ], # RmfTaskType.TYPE_LOOP, # ) # resp = self.session.get(f"{self.base_url}/tasks?priority=0") # self.assertEqual(resp.status_code, 200) # resp_json = resp.json() # items = resp_json["items"] # self.assertEqual(len(items), 1) # self.assertEqual(items[0]["task_summary"]["task_id"], "task_1") # resp = self.session.get(f"{self.base_url}/tasks?submission_time_since=4000") # self.assertEqual(resp.status_code, 200) # resp_json = resp.json() # items = resp_json["items"] # self.assertEqual(len(items), 1) # self.assertEqual(items[0]["task_summary"]["task_id"], "task_2") # resp = self.session.get(f"{self.base_url}/tasks?start_time_since=5000") # self.assertEqual(resp.status_code, 200) # resp_json = resp.json() # items = resp_json["items"] # self.assertEqual(len(items), 1) # self.assertEqual(items[0]["task_summary"]["task_id"], "task_2") # resp = self.session.get(f"{self.base_url}/tasks?end_time_since=6000") # self.assertEqual(resp.status_code, 200) # resp_json = resp.json() # items = resp_json["items"] # self.assertEqual(len(items), 1) # self.assertEqual(items[0]["task_summary"]["task_id"], "task_2") # # test no match # resp = self.session.get( # f"{self.base_url}/tasks?fleet_name=fleet_1&start_time_since=5000" # ) # self.assertEqual(resp.status_code, 200) # resp_json = resp.json() # items = resp_json["items"] # self.assertEqual(len(items), 0) # # no query returns everything # resp = self.session.get(f"{self.base_url}/tasks") # self.assertEqual(resp.status_code, 200) # resp_json = resp.json() # items = resp_json["items"] # self.assertEqual(len(items), 2) # def test_get_task_summary(self): # dataset = [ # TaskSummary( # task_id="task_1", # fleet_name="fleet_1", # submission_time={"sec": 1000, "nanosec": 0}, # start_time={"sec": 2000, "nanosec": 0}, # end_time={"sec": 3000, "nanosec": 0}, # robot_name="robot_1", # state=RmfTaskSummary.STATE_COMPLETED, # task_profile={ # "description": { # "task_type": {"type": RmfTaskType.TYPE_LOOP}, # "priority": {"value": 0}, # } # }, # ), # ] # fut = concurrent.futures.Future() # async def save_data(): # fut.set_result( # await asyncio.gather( # *(ttm.TaskSummary.save_pydantic(data) for data in dataset) # ) # ) # self.server.app.wait_ready() # self.server.app.loop.create_task(save_data()) # fut.result() # resp = self.session.get(f"{self.base_url}/tasks/task_1/summary") # self.assertEqual(200, resp.status_code) # resp_json = resp.json() # self.assertEqual("task_1", resp_json["task_id"])

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0.552116

998

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0.130381

0.059189

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0.73139

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e2b581f33f97ed0ca005f6c01b0c8ee8c995b201

10,030

py

Python

zerver/webhooks/cofazure/view.py

CatarinaSMorais/zulip

e943d717b84291397328bd4dc578c04eed21885e

[ "Apache-2.0" ]

1

2021-08-10T07:31:27.000Z

zerver/webhooks/cofazure/view.py

CatarinaSMorais/zulip

e943d717b84291397328bd4dc578c04eed21885e

[ "Apache-2.0" ]

1

2021-08-05T14:46:02.000Z

zerver/webhooks/cofazure/view.py

CatarinaSMorais/zulip

e943d717b84291397328bd4dc578c04eed21885e

[ "Apache-2.0" ]

1

2021-08-05T14:27:13.000Z

# Webhooks for external integrations. from typing import Any, Dict, Iterable from django.http import HttpRequest, HttpResponse from zerver.decorator import webhook_view from zerver.lib.request import REQ, has_request_variables from zerver.lib.response import json_success from zerver.lib.webhooks.common import check_send_webhook_message from zerver.models import UserProfile from zerver.lib.webhooks.bodyfunctions import BuildandRelease as br from zerver.lib.webhooks.bodyfunctions import code as cd from zerver.lib.webhooks.bodyfunctions import pipelines as pl from zerver.lib.webhooks.bodyfunctions import workitems as wk """ Mapeamento do eventtype devolvido pelo GIT A cada eventtype está a associada uma função que devolve o body e o topic da mensagem a publicar As funcoes encontram-se num outro ficheiro chamado bodyfunctions """ EVENT_FUNCTION_MAPPER:Dict[str, Dict[str, Any]] ={ "ms.vss-release.deployment-started-event": {"Function":br.release_deployment_started_body, "Active":True}, "build.complete": {"Function": br.build_completed_body, "Active": True}, "ms.vss-release.release-abandoned-event": {"Function": br.release_abandoned_body, "Active": True}, "ms.vss-release.release-created-event": {"Function": br.release_created_body, "Active": True}, "ms.vss-release.deployment-approval-completed-event": {"Function": br.release_deployment_approval_completed_body, "Active": True}, "ms.vss-release.deployment-approval-pending-event": {"Function": br.release_deployment_approval_pending_body, "Active": True}, "git.pullrequest.merged": {"Function": cd.pull_request_merged_body, "Active": True}, "git.pullrequest.updated": {"Function": cd.pull_request_updated_body, "Active": True}, "tfvc.checkin": {"Function": cd.checkin_body, "Active": True}, "git.push": {"Function": cd.push_body, "Active": True}, "git.pullrequest.created": {"Function": cd.pull_request_created_body, "Active": True}, "ms.vss-pipelines.run-state-changed-event": {"Function": pl.run_state_changed_body, "Active": True}, "ms.vss-pipelinechecks-events.approval-completed": {"Function": pl.run_stage_approval_completed_body, "Active": True}, "ms.vss-pipelinechecks-events.approval-pending": {"Function": pl.run_stage_waiting_for_approval_body, "Active": True}, "ms.vss-pipelines.stage-state-changed-event": {"Function": pl.run_stage_state_changed_body, "Active": True}, "workitem.restored": {"Function": wk.work_item_restored_body, "Active": True}, "workitem.updated": {"Function": wk.work_item_updated_body, "Active": True}, "workitem.commented": {"Function": wk.work_item_commented_body, "Active": True}, "workitem.created": {"Function": wk.work_item_created_body, "Active": True}, "workitem.deleted": {"Function": wk.work_item_deleted_body, "Active": True} } @webhook_view('CofAzure') @has_request_variables def api_cofazure_webhook( request: HttpRequest, user_profile: UserProfile, payload: Dict[str, Iterable[Dict[str, Any]]]=REQ(argument_type='body'), ) -> HttpResponse: event = payload['eventType'] if event is None: # Helper.log_unsupported(event) return json_success() # Retira a função a executrar da lista configurada mais acima body_function = EVENT_FUNCTION_MAPPER[event]['Functions'] # construct the body of the message body = '' # try to add the Wikipedia article of the day body_template = 'Nova mensagem do azure : {detailedMessage}' body += body_template.format(detailedMessage=payload['detailedMessage']['text']) topic = payload['eventType'] # send the message check_send_webhook_message(request, user_profile, topic, body) return json_success() """ from typing import Any, Callable, Dict, Iterable from django.http import HttpRequest, HttpResponse from zerver.decorator import log_exception_to_webhook_logger, webhook_view from zerver.lib.request import REQ, has_request_variables from zerver.lib.response import json_success from zerver.lib.webhooks.common import check_send_webhook_message from zerver.models import UserProfile from zerver.lib.webhooks.bodyfunctions import BuildandRelease as br from zerver.lib.webhooks.bodyfunctions import code as cd from zerver.lib.webhooks.bodyfunctions import pipelines as pl from zerver.lib.webhooks.bodyfunctions import workitems as wk class Helper: def __init__( self, payload: Dict[str, Iterable[Dict[str, Any]]], include_title: bool, ) -> None: self.payload = payload self.include_title = include_title def log_unsupported(self, event: str) -> None: summary = f"The '{event}' event isn't currently supported by the cofazure webhook" log_exception_to_webhook_logger( summary=summary, unsupported_event=True, ) """ """ Mapeamento do eventtype devolvido pelo GIT A cada eventtype está a associada uma função que devolve o body e o topic da mensagem a publicar As funcoes encontram-se num outro ficheiro chamado bodyfunctions """ """ EVENT_FUNCTION_MAPPER:Dict[str, Dict[str, Any]] ={ "ms.vss-release.deployment-started-event": {"Function":br.release_deployment_started_body, "Active":True}, "build.complete": {"Function": br.build_completed_body, "Active": True}, "ms.vss-release.release-abandoned-event": {"Function": br.release_abandoned_body, "Active": True}, "ms.vss-release.release-created-event": {"Function": br.release_created_body, "Active": True}, "ms.vss-release.deployment-approval-completed-event": {"Function": br.release_deployment_approval_completed_body, "Active": True}, "ms.vss-release.deployment-approval-pending-event": {"Function": br.release_deployment_approval_pending_body, "Active": True}, "git.pullrequest.merged": {"Function": cd.pull_request_merged_body, "Active": True}, "git.pullrequest.updated": {"Function": cd.pull_request_updated_body, "Active": True}, "tfvc.checkin": {"Function": cd.checkin_body, "Active": True}, "git.push": {"Function": cd.push_body, "Active": True}, "git.pullrequest.created": {"Function": cd.pull_request_created_body, "Active": True}, "ms.vss-pipelines.run-state-changed-event": {"Function": pl.run_state_changed_body, "Active": True}, "ms.vss-pipelinechecks-events.approval-completed": {"Function": pl.run_stage_approval_completed_body, "Active": True}, "ms.vss-pipelinechecks-events.approval-pending": {"Function": pl.run_stage_waiting_for_approval_body, "Active": True}, "ms.vss-pipelines.stage-state-changed-event": {"Function": pl.run_stage_state_changed_body, "Active": True}, "workitem.restored": {"Function": wk.work_item_restored_body, "Active": True}, "workitem.updated": {"Function": wk.work_item_updated_body, "Active": True}, "workitem.commented": {"Function": wk.work_item_commented_body, "Active": True}, "workitem.created": {"Function": wk.work_item_created_body, "Active": True}, "workitem.deleted": {"Function": wk.work_item_deleted_body, "Active": True}, } @webhook_view('cofazure') @has_request_variables def api_cofazure_webhook( request: HttpRequest, user_profile: UserProfile, payload: Dict[str, Iterable[Dict[str, Any]]] = REQ(argument_type='body'), ) -> HttpResponse: # Retira o json que vem no body o valor do atributo eventType try: event = payload["eventType"] # Valida se o evento vem preenchido if event is None: # Helper.log_unsupported(event) return json_success() # Retira a função a executrar da lista configurada mais acima body_function = EVENT_FUNCTION_MAPPER[event]["Functions"] # Valida se existe função para o evento pretendido if body_function is None: # Helper.log_unsupported(event) return json_success() function_state = EVENT_FUNCTION_MAPPER[event]["Active"] if function_state == False: return json_success() # cria o objecto para passar para a função e atribui á variavel payload o conteudo do json do GIT helper = Helper(payload=payload, include_title="", ) # executa a função para obter o topic e o body topic, body = body_function(helper) # publica na stream uma mensagem com o topic e o body obtidos check_send_webhook_message(request, user_profile, topic, body) return json_success() except: return json_success() """

45.590909

117

0.615354

1,088

10,030

5.488971

0.171875

0.066979

0.093771

0.042867

0.834896

0.821835

0.816477

0.808439

0

0.282951

10,030

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0

null

0

1

0

null

0

6

2c8231bfc1a04590d8a38e2d4a7095b5409d69c8

156

py

Python

macOS/Cut.py

bliles/autokey-macos

c8d44b83f6d4117b9430ede0c0aec81f72d9feab

[ "MIT" ]

38

2019-04-06T01:20:26.000Z

2022-02-22T03:02:40.000Z

macOS/Cut.py

bliles/autokey-macos

c8d44b83f6d4117b9430ede0c0aec81f72d9feab

[ "MIT" ]

null

macOS/Cut.py

bliles/autokey-macos

c8d44b83f6d4117b9430ede0c0aec81f72d9feab

[ "MIT" ]

8

2019-04-06T01:20:34.000Z

2022-03-31T14:10:04.000Z

if window.get_active_class() != 'gnome-terminal-server.Gnome-terminal': keyboard.send_keys("<ctrl>+x") else: keyboard.send_keys("<ctrl>+<shift>+c")

31.2

71

0.698718

22

156

4.772727

0.727273

0.247619

0.304762

0.380952

0

0.096154

156

4

72

39

0.744681

0

0.384615

0.230769

0

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true

0

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null

1

0

1

0

null

0

1

0

6

2c93c382e0baa98d3b3365c60b22b56a464cb1af

191,137

py

Python

sdk/python/pulumi_kubernetes_ingress_nginx/_inputs.py

joeduffy/pulumi-kubernetes-ingress-nginx

efc5b9b67efa2c4348869e3038c3c3725ef28915

[ "Apache-2.0" ]

5

2021-11-16T18:59:37.000Z

2022-03-28T07:44:12.000Z

sdk/python/pulumi_kubernetes_ingress_nginx/_inputs.py

joeduffy/pulumi-kubernetes-ingress-nginx

efc5b9b67efa2c4348869e3038c3c3725ef28915

[ "Apache-2.0" ]

2

2021-12-07T08:40:42.000Z

2021-12-22T13:00:27.000Z

sdk/python/pulumi_kubernetes_ingress_nginx/_inputs.py

joeduffy/pulumi-kubernetes-ingress-nginx

efc5b9b67efa2c4348869e3038c3c3725ef28915

[ "Apache-2.0" ]

1

2022-03-18T13:37:08.000Z

# coding=utf-8 # *** WARNING: this file was generated by Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from . import _utilities import pulumi_kubernetes __all__ = [ 'AutoscalingBehaviorScalingPolicyArgs', 'AutoscalingBehaviorScalingArgs', 'AutoscalingBehaviorArgs', 'AutoscalingTemplatePodsMetricArgs', 'AutoscalingTemplatePodsTargetArgs', 'AutoscalingTemplatePodsArgs', 'AutoscalingTemplateArgs', 'AutoscalingArgs', 'ContollerAdmissionWebhooksArgs', 'ControllerAdmissionWebhooksCreateSecretJobArgs', 'ControllerAdmissionWebhooksPatchWebhbookJobArgs', 'ControllerAdmissionWebhooksPatchArgs', 'ControllerAdmissionWebhooksServiceArgs', 'ControllerCustomTemplateArgs', 'ControllerDefaultBackendServiceArgs', 'ControllerDefaultBackendArgs', 'ControllerHostPortPortsArgs', 'ControllerHostPortArgs', 'ControllerImageArgs', 'ControllerIngressClassResourceArgs', 'ControllerMetricsPrometheusRulesArgs', 'ControllerMetricsServiceMonitorArgs', 'ControllerMetricsServiceArgs', 'ControllerMetricsArgs', 'ControllerPodSecurityPolicyArgs', 'ControllerPortArgs', 'ControllerPublishServiceArgs', 'ControllerRBACArgs', 'ControllerRollingUpdateArgs', 'ControllerScopeArgs', 'ControllerServiceAccountArgs', 'ControllerServiceInternalArgs', 'ControllerServiceNodePortsArgs', 'ControllerServiceArgs', 'ControllerTcpArgs', 'ControllerUdpArgs', 'ControllerUpdateStrategyArgs', 'ControllerArgs', 'KedaScaledObjectArgs', 'KedaTriggerArgs', 'KedaArgs', 'ReleaseArgs', 'RepositoryOptsArgs', ] @pulumi.input_type class AutoscalingBehaviorScalingPolicyArgs: def __init__(__self__, *, period_seconds: Optional[pulumi.Input[int]] = None, type: Optional[pulumi.Input[str]] = None, value: Optional[pulumi.Input[int]] = None): if period_seconds is not None: pulumi.set(__self__, "period_seconds", period_seconds) if type is not None: pulumi.set(__self__, "type", type) if value is not None: pulumi.set(__self__, "value", value) @property @pulumi.getter(name="periodSeconds") def period_seconds(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "period_seconds") @period_seconds.setter def period_seconds(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "period_seconds", value) @property @pulumi.getter def type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "type") @type.setter def type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "type", value) @property @pulumi.getter def value(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "value") @value.setter def value(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "value", value) @pulumi.input_type class AutoscalingBehaviorScalingArgs: def __init__(__self__, *, policies: Optional[pulumi.Input[Sequence[pulumi.Input['AutoscalingBehaviorScalingPolicyArgs']]]] = None, stabilization_window_seconds: Optional[pulumi.Input[int]] = None): if policies is not None: pulumi.set(__self__, "policies", policies) if stabilization_window_seconds is not None: pulumi.set(__self__, "stabilization_window_seconds", stabilization_window_seconds) @property @pulumi.getter def policies(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['AutoscalingBehaviorScalingPolicyArgs']]]]: return pulumi.get(self, "policies") @policies.setter def policies(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['AutoscalingBehaviorScalingPolicyArgs']]]]): pulumi.set(self, "policies", value) @property @pulumi.getter(name="stabilizationWindowSeconds") def stabilization_window_seconds(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "stabilization_window_seconds") @stabilization_window_seconds.setter def stabilization_window_seconds(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "stabilization_window_seconds", value) @pulumi.input_type class AutoscalingBehaviorArgs: def __init__(__self__, *, scale_down: Optional[pulumi.Input['AutoscalingBehaviorScalingArgs']] = None, scale_up: Optional[pulumi.Input['AutoscalingBehaviorScalingArgs']] = None): if scale_down is not None: pulumi.set(__self__, "scale_down", scale_down) if scale_up is not None: pulumi.set(__self__, "scale_up", scale_up) @property @pulumi.getter(name="scaleDown") def scale_down(self) -> Optional[pulumi.Input['AutoscalingBehaviorScalingArgs']]: return pulumi.get(self, "scale_down") @scale_down.setter def scale_down(self, value: Optional[pulumi.Input['AutoscalingBehaviorScalingArgs']]): pulumi.set(self, "scale_down", value) @property @pulumi.getter(name="scaleUp") def scale_up(self) -> Optional[pulumi.Input['AutoscalingBehaviorScalingArgs']]: return pulumi.get(self, "scale_up") @scale_up.setter def scale_up(self, value: Optional[pulumi.Input['AutoscalingBehaviorScalingArgs']]): pulumi.set(self, "scale_up", value) @pulumi.input_type class AutoscalingTemplatePodsMetricArgs: def __init__(__self__, *, name: Optional[pulumi.Input[str]] = None): if name is not None: pulumi.set(__self__, "name", name) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @pulumi.input_type class AutoscalingTemplatePodsTargetArgs: def __init__(__self__, *, average_value: Optional[pulumi.Input[str]] = None, type: Optional[pulumi.Input[str]] = None): if average_value is not None: pulumi.set(__self__, "average_value", average_value) if type is not None: pulumi.set(__self__, "type", type) @property @pulumi.getter(name="averageValue") def average_value(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "average_value") @average_value.setter def average_value(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "average_value", value) @property @pulumi.getter def type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "type") @type.setter def type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "type", value) @pulumi.input_type class AutoscalingTemplatePodsArgs: def __init__(__self__, *, metric: Optional[pulumi.Input['AutoscalingTemplatePodsMetricArgs']] = None, target: Optional[pulumi.Input['AutoscalingTemplatePodsTargetArgs']] = None): if metric is not None: pulumi.set(__self__, "metric", metric) if target is not None: pulumi.set(__self__, "target", target) @property @pulumi.getter def metric(self) -> Optional[pulumi.Input['AutoscalingTemplatePodsMetricArgs']]: return pulumi.get(self, "metric") @metric.setter def metric(self, value: Optional[pulumi.Input['AutoscalingTemplatePodsMetricArgs']]): pulumi.set(self, "metric", value) @property @pulumi.getter def target(self) -> Optional[pulumi.Input['AutoscalingTemplatePodsTargetArgs']]: return pulumi.get(self, "target") @target.setter def target(self, value: Optional[pulumi.Input['AutoscalingTemplatePodsTargetArgs']]): pulumi.set(self, "target", value) @pulumi.input_type class AutoscalingTemplateArgs: def __init__(__self__, *, pods: Optional[pulumi.Input['AutoscalingTemplatePodsArgs']] = None, type: Optional[pulumi.Input[str]] = None): if pods is not None: pulumi.set(__self__, "pods", pods) if type is not None: pulumi.set(__self__, "type", type) @property @pulumi.getter def pods(self) -> Optional[pulumi.Input['AutoscalingTemplatePodsArgs']]: return pulumi.get(self, "pods") @pods.setter def pods(self, value: Optional[pulumi.Input['AutoscalingTemplatePodsArgs']]): pulumi.set(self, "pods", value) @property @pulumi.getter def type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "type") @type.setter def type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "type", value) @pulumi.input_type class AutoscalingArgs: def __init__(__self__, *, annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, controller_autoscaling_behavior: Optional[pulumi.Input['AutoscalingBehaviorArgs']] = None, enabled: Optional[pulumi.Input[bool]] = None, max_replicas: Optional[pulumi.Input[int]] = None, min_replicas: Optional[pulumi.Input[int]] = None, target_cpu_utilization_percentage: Optional[pulumi.Input[int]] = None, target_memory_utilization_percentage: Optional[pulumi.Input[int]] = None): if annotations is not None: pulumi.set(__self__, "annotations", annotations) if controller_autoscaling_behavior is not None: pulumi.set(__self__, "controller_autoscaling_behavior", controller_autoscaling_behavior) if enabled is not None: pulumi.set(__self__, "enabled", enabled) if max_replicas is not None: pulumi.set(__self__, "max_replicas", max_replicas) if min_replicas is not None: pulumi.set(__self__, "min_replicas", min_replicas) if target_cpu_utilization_percentage is not None: pulumi.set(__self__, "target_cpu_utilization_percentage", target_cpu_utilization_percentage) if target_memory_utilization_percentage is not None: pulumi.set(__self__, "target_memory_utilization_percentage", target_memory_utilization_percentage) @property @pulumi.getter def annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: return pulumi.get(self, "annotations") @annotations.setter def annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "annotations", value) @property @pulumi.getter(name="controllerAutoscalingBehavior") def controller_autoscaling_behavior(self) -> Optional[pulumi.Input['AutoscalingBehaviorArgs']]: return pulumi.get(self, "controller_autoscaling_behavior") @controller_autoscaling_behavior.setter def controller_autoscaling_behavior(self, value: Optional[pulumi.Input['AutoscalingBehaviorArgs']]): pulumi.set(self, "controller_autoscaling_behavior", value) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter(name="maxReplicas") def max_replicas(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "max_replicas") @max_replicas.setter def max_replicas(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "max_replicas", value) @property @pulumi.getter(name="minReplicas") def min_replicas(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "min_replicas") @min_replicas.setter def min_replicas(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "min_replicas", value) @property @pulumi.getter(name="targetCPUUtilizationPercentage") def target_cpu_utilization_percentage(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "target_cpu_utilization_percentage") @target_cpu_utilization_percentage.setter def target_cpu_utilization_percentage(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "target_cpu_utilization_percentage", value) @property @pulumi.getter(name="targetMemoryUtilizationPercentage") def target_memory_utilization_percentage(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "target_memory_utilization_percentage") @target_memory_utilization_percentage.setter def target_memory_utilization_percentage(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "target_memory_utilization_percentage", value) @pulumi.input_type class ContollerAdmissionWebhooksArgs: def __init__(__self__, *, annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, certificate: Optional[pulumi.Input[str]] = None, create_secret_job: Optional[pulumi.Input['ControllerAdmissionWebhooksCreateSecretJobArgs']] = None, enabled: Optional[pulumi.Input[bool]] = None, existing_psp: Optional[pulumi.Input[str]] = None, failure_policy: Optional[pulumi.Input[str]] = None, key: Optional[pulumi.Input[str]] = None, namespace_selector: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, object_selector: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, patch: Optional[pulumi.Input['ControllerAdmissionWebhooksPatchArgs']] = None, patch_webhook_job: Optional[pulumi.Input['ControllerAdmissionWebhooksPatchWebhbookJobArgs']] = None, port: Optional[pulumi.Input[int]] = None, service: Optional[pulumi.Input['ControllerAdmissionWebhooksServiceArgs']] = None, timeout_seconds: Optional[pulumi.Input[int]] = None): """ :param pulumi.Input[str] existing_psp: Use an existing PSP instead of creating one. """ if annotations is not None: pulumi.set(__self__, "annotations", annotations) if certificate is not None: pulumi.set(__self__, "certificate", certificate) if create_secret_job is not None: pulumi.set(__self__, "create_secret_job", create_secret_job) if enabled is not None: pulumi.set(__self__, "enabled", enabled) if existing_psp is not None: pulumi.set(__self__, "existing_psp", existing_psp) if failure_policy is not None: pulumi.set(__self__, "failure_policy", failure_policy) if key is not None: pulumi.set(__self__, "key", key) if namespace_selector is not None: pulumi.set(__self__, "namespace_selector", namespace_selector) if object_selector is not None: pulumi.set(__self__, "object_selector", object_selector) if patch is not None: pulumi.set(__self__, "patch", patch) if patch_webhook_job is not None: pulumi.set(__self__, "patch_webhook_job", patch_webhook_job) if port is not None: pulumi.set(__self__, "port", port) if service is not None: pulumi.set(__self__, "service", service) if timeout_seconds is not None: pulumi.set(__self__, "timeout_seconds", timeout_seconds) @property @pulumi.getter def annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "annotations") @annotations.setter def annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "annotations", value) @property @pulumi.getter def certificate(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "certificate") @certificate.setter def certificate(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "certificate", value) @property @pulumi.getter(name="createSecretJob") def create_secret_job(self) -> Optional[pulumi.Input['ControllerAdmissionWebhooksCreateSecretJobArgs']]: return pulumi.get(self, "create_secret_job") @create_secret_job.setter def create_secret_job(self, value: Optional[pulumi.Input['ControllerAdmissionWebhooksCreateSecretJobArgs']]): pulumi.set(self, "create_secret_job", value) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter(name="existingPsp") def existing_psp(self) -> Optional[pulumi.Input[str]]: """ Use an existing PSP instead of creating one. """ return pulumi.get(self, "existing_psp") @existing_psp.setter def existing_psp(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "existing_psp", value) @property @pulumi.getter(name="failurePolicy") def failure_policy(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "failure_policy") @failure_policy.setter def failure_policy(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "failure_policy", value) @property @pulumi.getter def key(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "key") @key.setter def key(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "key", value) @property @pulumi.getter(name="namespaceSelector") def namespace_selector(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "namespace_selector") @namespace_selector.setter def namespace_selector(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "namespace_selector", value) @property @pulumi.getter(name="objectSelector") def object_selector(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "object_selector") @object_selector.setter def object_selector(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "object_selector", value) @property @pulumi.getter def patch(self) -> Optional[pulumi.Input['ControllerAdmissionWebhooksPatchArgs']]: return pulumi.get(self, "patch") @patch.setter def patch(self, value: Optional[pulumi.Input['ControllerAdmissionWebhooksPatchArgs']]): pulumi.set(self, "patch", value) @property @pulumi.getter(name="patchWebhookJob") def patch_webhook_job(self) -> Optional[pulumi.Input['ControllerAdmissionWebhooksPatchWebhbookJobArgs']]: return pulumi.get(self, "patch_webhook_job") @patch_webhook_job.setter def patch_webhook_job(self, value: Optional[pulumi.Input['ControllerAdmissionWebhooksPatchWebhbookJobArgs']]): pulumi.set(self, "patch_webhook_job", value) @property @pulumi.getter def port(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "port") @port.setter def port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "port", value) @property @pulumi.getter def service(self) -> Optional[pulumi.Input['ControllerAdmissionWebhooksServiceArgs']]: return pulumi.get(self, "service") @service.setter def service(self, value: Optional[pulumi.Input['ControllerAdmissionWebhooksServiceArgs']]): pulumi.set(self, "service", value) @property @pulumi.getter(name="timeoutSeconds") def timeout_seconds(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "timeout_seconds") @timeout_seconds.setter def timeout_seconds(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "timeout_seconds", value) @pulumi.input_type class ControllerAdmissionWebhooksCreateSecretJobArgs: def __init__(__self__, *, resources: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']] = None): if resources is not None: pulumi.set(__self__, "resources", resources) @property @pulumi.getter def resources(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']]: return pulumi.get(self, "resources") @resources.setter def resources(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']]): pulumi.set(self, "resources", value) @pulumi.input_type class ControllerAdmissionWebhooksPatchWebhbookJobArgs: def __init__(__self__, *, resources: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']] = None): if resources is not None: pulumi.set(__self__, "resources", resources) @property @pulumi.getter def resources(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']]: return pulumi.get(self, "resources") @resources.setter def resources(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']]): pulumi.set(self, "resources", value) @pulumi.input_type class ControllerAdmissionWebhooksPatchArgs: def __init__(__self__, *, enabled: Optional[pulumi.Input[bool]] = None, image: Optional[pulumi.Input['ControllerImageArgs']] = None, node_selector: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, pod_annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, priority_class_name: Optional[pulumi.Input[str]] = None, run_as_user: Optional[pulumi.Input[int]] = None, tolerations: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.TolerationArgs']]]] = None): """ :param pulumi.Input[str] priority_class_name: Provide a priority class name to the webhook patching job. """ if enabled is not None: pulumi.set(__self__, "enabled", enabled) if image is not None: pulumi.set(__self__, "image", image) if node_selector is not None: pulumi.set(__self__, "node_selector", node_selector) if pod_annotations is not None: pulumi.set(__self__, "pod_annotations", pod_annotations) if priority_class_name is not None: pulumi.set(__self__, "priority_class_name", priority_class_name) if run_as_user is not None: pulumi.set(__self__, "run_as_user", run_as_user) if tolerations is not None: pulumi.set(__self__, "tolerations", tolerations) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter def image(self) -> Optional[pulumi.Input['ControllerImageArgs']]: return pulumi.get(self, "image") @image.setter def image(self, value: Optional[pulumi.Input['ControllerImageArgs']]): pulumi.set(self, "image", value) @property @pulumi.getter(name="nodeSelector") def node_selector(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: return pulumi.get(self, "node_selector") @node_selector.setter def node_selector(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "node_selector", value) @property @pulumi.getter(name="podAnnotations") def pod_annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "pod_annotations") @pod_annotations.setter def pod_annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "pod_annotations", value) @property @pulumi.getter(name="priorityClassName") def priority_class_name(self) -> Optional[pulumi.Input[str]]: """ Provide a priority class name to the webhook patching job. """ return pulumi.get(self, "priority_class_name") @priority_class_name.setter def priority_class_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "priority_class_name", value) @property @pulumi.getter(name="runAsUser") def run_as_user(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "run_as_user") @run_as_user.setter def run_as_user(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "run_as_user", value) @property @pulumi.getter def tolerations(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.TolerationArgs']]]]: return pulumi.get(self, "tolerations") @tolerations.setter def tolerations(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.TolerationArgs']]]]): pulumi.set(self, "tolerations", value) @pulumi.input_type class ControllerAdmissionWebhooksServiceArgs: def __init__(__self__, *, annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, cluster_ip: Optional[pulumi.Input[str]] = None, external_ips: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, load_balancer_ips: Optional[pulumi.Input[str]] = None, load_balancer_source_ranges: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, service_port: Optional[pulumi.Input[int]] = None, type: Optional[pulumi.Input[str]] = None): if annotations is not None: pulumi.set(__self__, "annotations", annotations) if cluster_ip is not None: pulumi.set(__self__, "cluster_ip", cluster_ip) if external_ips is not None: pulumi.set(__self__, "external_ips", external_ips) if load_balancer_ips is not None: pulumi.set(__self__, "load_balancer_ips", load_balancer_ips) if load_balancer_source_ranges is not None: pulumi.set(__self__, "load_balancer_source_ranges", load_balancer_source_ranges) if service_port is not None: pulumi.set(__self__, "service_port", service_port) if type is not None: pulumi.set(__self__, "type", type) @property @pulumi.getter def annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "annotations") @annotations.setter def annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "annotations", value) @property @pulumi.getter(name="clusterIP") def cluster_ip(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "cluster_ip") @cluster_ip.setter def cluster_ip(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "cluster_ip", value) @property @pulumi.getter(name="externalIPs") def external_ips(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: return pulumi.get(self, "external_ips") @external_ips.setter def external_ips(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "external_ips", value) @property @pulumi.getter(name="loadBalancerIPs") def load_balancer_ips(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "load_balancer_ips") @load_balancer_ips.setter def load_balancer_ips(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "load_balancer_ips", value) @property @pulumi.getter(name="loadBalancerSourceRanges") def load_balancer_source_ranges(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: return pulumi.get(self, "load_balancer_source_ranges") @load_balancer_source_ranges.setter def load_balancer_source_ranges(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "load_balancer_source_ranges", value) @property @pulumi.getter(name="servicePort") def service_port(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "service_port") @service_port.setter def service_port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "service_port", value) @property @pulumi.getter def type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "type") @type.setter def type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "type", value) @pulumi.input_type class ControllerCustomTemplateArgs: def __init__(__self__, *, config_map_key: Optional[pulumi.Input[str]] = None, config_map_name: Optional[pulumi.Input[str]] = None): if config_map_key is not None: pulumi.set(__self__, "config_map_key", config_map_key) if config_map_name is not None: pulumi.set(__self__, "config_map_name", config_map_name) @property @pulumi.getter(name="configMapKey") def config_map_key(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "config_map_key") @config_map_key.setter def config_map_key(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "config_map_key", value) @property @pulumi.getter(name="configMapName") def config_map_name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "config_map_name") @config_map_name.setter def config_map_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "config_map_name", value) @pulumi.input_type class ControllerDefaultBackendServiceArgs: def __init__(__self__, *, annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, cluster_ip: Optional[pulumi.Input[str]] = None, external_ips: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, load_balancer_ip: Optional[pulumi.Input[str]] = None, load_balancer_source_ranges: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, service_port: Optional[pulumi.Input[int]] = None, type: Optional[pulumi.Input[str]] = None): """ :param pulumi.Input[Sequence[pulumi.Input[str]]] external_ips: List of IP addresses at which the default backend service is available. Ref: https://kubernetes.io/docs/user-guide/services/#external-ips """ if annotations is not None: pulumi.set(__self__, "annotations", annotations) if cluster_ip is not None: pulumi.set(__self__, "cluster_ip", cluster_ip) if external_ips is not None: pulumi.set(__self__, "external_ips", external_ips) if load_balancer_ip is not None: pulumi.set(__self__, "load_balancer_ip", load_balancer_ip) if load_balancer_source_ranges is not None: pulumi.set(__self__, "load_balancer_source_ranges", load_balancer_source_ranges) if service_port is not None: pulumi.set(__self__, "service_port", service_port) if type is not None: pulumi.set(__self__, "type", type) @property @pulumi.getter def annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: return pulumi.get(self, "annotations") @annotations.setter def annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "annotations", value) @property @pulumi.getter(name="clusterIP") def cluster_ip(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "cluster_ip") @cluster_ip.setter def cluster_ip(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "cluster_ip", value) @property @pulumi.getter(name="externalIPs") def external_ips(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ List of IP addresses at which the default backend service is available. Ref: https://kubernetes.io/docs/user-guide/services/#external-ips """ return pulumi.get(self, "external_ips") @external_ips.setter def external_ips(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "external_ips", value) @property @pulumi.getter(name="loadBalancerIP") def load_balancer_ip(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "load_balancer_ip") @load_balancer_ip.setter def load_balancer_ip(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "load_balancer_ip", value) @property @pulumi.getter(name="loadBalancerSourceRanges") def load_balancer_source_ranges(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: return pulumi.get(self, "load_balancer_source_ranges") @load_balancer_source_ranges.setter def load_balancer_source_ranges(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "load_balancer_source_ranges", value) @property @pulumi.getter(name="servicePort") def service_port(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "service_port") @service_port.setter def service_port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "service_port", value) @property @pulumi.getter def type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "type") @type.setter def type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "type", value) @pulumi.input_type class ControllerDefaultBackendArgs: def __init__(__self__, *, affinity: Optional[pulumi.Input['pulumi_kubernetes.core.v1.AffinityArgs']] = None, autoscaling: Optional[pulumi.Input['AutoscalingArgs']] = None, enabled: Optional[pulumi.Input[bool]] = None, existing_psp: Optional[pulumi.Input[str]] = None, extra_args: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, extra_envs: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.EnvVarArgs']]]] = None, extra_volume_mounts: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeMountArgs']]]] = None, extra_volumes: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeArgs']]]] = None, image: Optional[pulumi.Input['ControllerImageArgs']] = None, liveness_probe: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']] = None, min_available: Optional[pulumi.Input[int]] = None, name: Optional[pulumi.Input[str]] = None, node_selector: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, pod_annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, pod_labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, pod_security_context: Optional[pulumi.Input['pulumi_kubernetes.core.v1.PodSecurityContextArgs']] = None, port: Optional[pulumi.Input[int]] = None, priority_class_name: Optional[pulumi.Input[str]] = None, readiness_probe: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']] = None, replica_count: Optional[pulumi.Input[int]] = None, resources: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']] = None, service: Optional[pulumi.Input['ControllerDefaultBackendServiceArgs']] = None, service_account: Optional[pulumi.Input['ControllerServiceAccountArgs']] = None, tolerations: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.TolerationArgs']]]] = None): """ :param pulumi.Input[str] existing_psp: Use an existing PSP instead of creating one. :param pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeMountArgs']]] extra_volume_mounts: Additional volumeMounts to the default backend container. - name: copy-portal-skins mountPath: /var/lib/lemonldap-ng/portal/skins :param pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeArgs']]] extra_volumes: Additional volumes to the default backend pod. - name: copy-portal-skins emptyDir: {} :param pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs'] liveness_probe: Liveness probe values for default backend. Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] node_selector: Node labels for default backend pod assignment Ref: https://kubernetes.io/docs/user-guide/node-selection/. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] pod_annotations: Annotations to be added to default backend pods. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] pod_labels: labels to add to the pod container metadata :param pulumi.Input['pulumi_kubernetes.core.v1.PodSecurityContextArgs'] pod_security_context: Security Context policies for controller pods. See https://kubernetes.io/docs/tasks/administer-cluster/sysctl-cluster/ for notes on enabling and using sysctls. :param pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs'] readiness_probe: Readiness probe values for default backend. Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes. :param pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.TolerationArgs']]] tolerations: Node tolerations for server scheduling to nodes with taints. Ref: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/ """ if affinity is not None: pulumi.set(__self__, "affinity", affinity) if autoscaling is not None: pulumi.set(__self__, "autoscaling", autoscaling) if enabled is not None: pulumi.set(__self__, "enabled", enabled) if existing_psp is not None: pulumi.set(__self__, "existing_psp", existing_psp) if extra_args is not None: pulumi.set(__self__, "extra_args", extra_args) if extra_envs is not None: pulumi.set(__self__, "extra_envs", extra_envs) if extra_volume_mounts is not None: pulumi.set(__self__, "extra_volume_mounts", extra_volume_mounts) if extra_volumes is not None: pulumi.set(__self__, "extra_volumes", extra_volumes) if image is not None: pulumi.set(__self__, "image", image) if liveness_probe is not None: pulumi.set(__self__, "liveness_probe", liveness_probe) if min_available is not None: pulumi.set(__self__, "min_available", min_available) if name is not None: pulumi.set(__self__, "name", name) if node_selector is not None: pulumi.set(__self__, "node_selector", node_selector) if pod_annotations is not None: pulumi.set(__self__, "pod_annotations", pod_annotations) if pod_labels is not None: pulumi.set(__self__, "pod_labels", pod_labels) if pod_security_context is not None: pulumi.set(__self__, "pod_security_context", pod_security_context) if port is not None: pulumi.set(__self__, "port", port) if priority_class_name is not None: pulumi.set(__self__, "priority_class_name", priority_class_name) if readiness_probe is not None: pulumi.set(__self__, "readiness_probe", readiness_probe) if replica_count is not None: pulumi.set(__self__, "replica_count", replica_count) if resources is not None: pulumi.set(__self__, "resources", resources) if service is not None: pulumi.set(__self__, "service", service) if service_account is not None: pulumi.set(__self__, "service_account", service_account) if tolerations is not None: pulumi.set(__self__, "tolerations", tolerations) @property @pulumi.getter def affinity(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.AffinityArgs']]: return pulumi.get(self, "affinity") @affinity.setter def affinity(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.AffinityArgs']]): pulumi.set(self, "affinity", value) @property @pulumi.getter def autoscaling(self) -> Optional[pulumi.Input['AutoscalingArgs']]: return pulumi.get(self, "autoscaling") @autoscaling.setter def autoscaling(self, value: Optional[pulumi.Input['AutoscalingArgs']]): pulumi.set(self, "autoscaling", value) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter(name="existingPsp") def existing_psp(self) -> Optional[pulumi.Input[str]]: """ Use an existing PSP instead of creating one. """ return pulumi.get(self, "existing_psp") @existing_psp.setter def existing_psp(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "existing_psp", value) @property @pulumi.getter(name="extraArgs") def extra_args(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "extra_args") @extra_args.setter def extra_args(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "extra_args", value) @property @pulumi.getter(name="extraEnvs") def extra_envs(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.EnvVarArgs']]]]: return pulumi.get(self, "extra_envs") @extra_envs.setter def extra_envs(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.EnvVarArgs']]]]): pulumi.set(self, "extra_envs", value) @property @pulumi.getter(name="extraVolumeMounts") def extra_volume_mounts(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeMountArgs']]]]: """ Additional volumeMounts to the default backend container. - name: copy-portal-skins mountPath: /var/lib/lemonldap-ng/portal/skins """ return pulumi.get(self, "extra_volume_mounts") @extra_volume_mounts.setter def extra_volume_mounts(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeMountArgs']]]]): pulumi.set(self, "extra_volume_mounts", value) @property @pulumi.getter(name="extraVolumes") def extra_volumes(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeArgs']]]]: """ Additional volumes to the default backend pod. - name: copy-portal-skins emptyDir: {} """ return pulumi.get(self, "extra_volumes") @extra_volumes.setter def extra_volumes(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeArgs']]]]): pulumi.set(self, "extra_volumes", value) @property @pulumi.getter def image(self) -> Optional[pulumi.Input['ControllerImageArgs']]: return pulumi.get(self, "image") @image.setter def image(self, value: Optional[pulumi.Input['ControllerImageArgs']]): pulumi.set(self, "image", value) @property @pulumi.getter(name="livenessProbe") def liveness_probe(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']]: """ Liveness probe values for default backend. Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes. """ return pulumi.get(self, "liveness_probe") @liveness_probe.setter def liveness_probe(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']]): pulumi.set(self, "liveness_probe", value) @property @pulumi.getter(name="minAvailable") def min_available(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "min_available") @min_available.setter def min_available(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "min_available", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="nodeSelector") def node_selector(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ Node labels for default backend pod assignment Ref: https://kubernetes.io/docs/user-guide/node-selection/. """ return pulumi.get(self, "node_selector") @node_selector.setter def node_selector(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "node_selector", value) @property @pulumi.getter(name="podAnnotations") def pod_annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ Annotations to be added to default backend pods. """ return pulumi.get(self, "pod_annotations") @pod_annotations.setter def pod_annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "pod_annotations", value) @property @pulumi.getter(name="podLabels") def pod_labels(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ labels to add to the pod container metadata """ return pulumi.get(self, "pod_labels") @pod_labels.setter def pod_labels(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "pod_labels", value) @property @pulumi.getter(name="podSecurityContext") def pod_security_context(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.PodSecurityContextArgs']]: """ Security Context policies for controller pods. See https://kubernetes.io/docs/tasks/administer-cluster/sysctl-cluster/ for notes on enabling and using sysctls. """ return pulumi.get(self, "pod_security_context") @pod_security_context.setter def pod_security_context(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.PodSecurityContextArgs']]): pulumi.set(self, "pod_security_context", value) @property @pulumi.getter def port(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "port") @port.setter def port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "port", value) @property @pulumi.getter(name="priorityClassName") def priority_class_name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "priority_class_name") @priority_class_name.setter def priority_class_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "priority_class_name", value) @property @pulumi.getter(name="readinessProbe") def readiness_probe(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']]: """ Readiness probe values for default backend. Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes. """ return pulumi.get(self, "readiness_probe") @readiness_probe.setter def readiness_probe(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']]): pulumi.set(self, "readiness_probe", value) @property @pulumi.getter(name="replicaCount") def replica_count(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "replica_count") @replica_count.setter def replica_count(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "replica_count", value) @property @pulumi.getter def resources(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']]: return pulumi.get(self, "resources") @resources.setter def resources(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']]): pulumi.set(self, "resources", value) @property @pulumi.getter def service(self) -> Optional[pulumi.Input['ControllerDefaultBackendServiceArgs']]: return pulumi.get(self, "service") @service.setter def service(self, value: Optional[pulumi.Input['ControllerDefaultBackendServiceArgs']]): pulumi.set(self, "service", value) @property @pulumi.getter(name="serviceAccount") def service_account(self) -> Optional[pulumi.Input['ControllerServiceAccountArgs']]: return pulumi.get(self, "service_account") @service_account.setter def service_account(self, value: Optional[pulumi.Input['ControllerServiceAccountArgs']]): pulumi.set(self, "service_account", value) @property @pulumi.getter def tolerations(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.TolerationArgs']]]]: """ Node tolerations for server scheduling to nodes with taints. Ref: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/ """ return pulumi.get(self, "tolerations") @tolerations.setter def tolerations(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.TolerationArgs']]]]): pulumi.set(self, "tolerations", value) @pulumi.input_type class ControllerHostPortPortsArgs: def __init__(__self__, *, http: Optional[pulumi.Input[int]] = None, https: Optional[pulumi.Input[int]] = None): if http is not None: pulumi.set(__self__, "http", http) if https is not None: pulumi.set(__self__, "https", https) @property @pulumi.getter def http(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "http") @http.setter def http(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "http", value) @property @pulumi.getter def https(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "https") @https.setter def https(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "https", value) @pulumi.input_type class ControllerHostPortArgs: def __init__(__self__, *, enabled: Optional[pulumi.Input[bool]] = None, ports: Optional[pulumi.Input['ControllerHostPortPortsArgs']] = None): if enabled is not None: pulumi.set(__self__, "enabled", enabled) if ports is not None: pulumi.set(__self__, "ports", ports) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter def ports(self) -> Optional[pulumi.Input['ControllerHostPortPortsArgs']]: return pulumi.get(self, "ports") @ports.setter def ports(self, value: Optional[pulumi.Input['ControllerHostPortPortsArgs']]): pulumi.set(self, "ports", value) @pulumi.input_type class ControllerImageArgs: def __init__(__self__, *, allow_privilege_escalation: Optional[pulumi.Input[bool]] = None, digest: Optional[pulumi.Input[str]] = None, image: Optional[pulumi.Input[str]] = None, pull_policy: Optional[pulumi.Input[str]] = None, read_only_root_filesystem: Optional[pulumi.Input[bool]] = None, registry: Optional[pulumi.Input[str]] = None, repository: Optional[pulumi.Input[str]] = None, run_as_non_root: Optional[pulumi.Input[bool]] = None, run_as_user: Optional[pulumi.Input[str]] = None, tag: Optional[pulumi.Input[str]] = None): """ :param pulumi.Input[str] repository: for backwards compatibility consider setting the full image url via the repository value below use *either* current default registry/image or repository format or installing will fail. """ if allow_privilege_escalation is not None: pulumi.set(__self__, "allow_privilege_escalation", allow_privilege_escalation) if digest is not None: pulumi.set(__self__, "digest", digest) if image is not None: pulumi.set(__self__, "image", image) if pull_policy is not None: pulumi.set(__self__, "pull_policy", pull_policy) if read_only_root_filesystem is not None: pulumi.set(__self__, "read_only_root_filesystem", read_only_root_filesystem) if registry is not None: pulumi.set(__self__, "registry", registry) if repository is not None: pulumi.set(__self__, "repository", repository) if run_as_non_root is not None: pulumi.set(__self__, "run_as_non_root", run_as_non_root) if run_as_user is not None: pulumi.set(__self__, "run_as_user", run_as_user) if tag is not None: pulumi.set(__self__, "tag", tag) @property @pulumi.getter(name="allowPrivilegeEscalation") def allow_privilege_escalation(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "allow_privilege_escalation") @allow_privilege_escalation.setter def allow_privilege_escalation(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "allow_privilege_escalation", value) @property @pulumi.getter def digest(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "digest") @digest.setter def digest(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "digest", value) @property @pulumi.getter def image(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "image") @image.setter def image(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "image", value) @property @pulumi.getter(name="pullPolicy") def pull_policy(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "pull_policy") @pull_policy.setter def pull_policy(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "pull_policy", value) @property @pulumi.getter(name="readOnlyRootFilesystem") def read_only_root_filesystem(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "read_only_root_filesystem") @read_only_root_filesystem.setter def read_only_root_filesystem(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "read_only_root_filesystem", value) @property @pulumi.getter def registry(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "registry") @registry.setter def registry(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "registry", value) @property @pulumi.getter def repository(self) -> Optional[pulumi.Input[str]]: """ for backwards compatibility consider setting the full image url via the repository value below use *either* current default registry/image or repository format or installing will fail. """ return pulumi.get(self, "repository") @repository.setter def repository(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "repository", value) @property @pulumi.getter(name="runAsNonRoot") def run_as_non_root(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "run_as_non_root") @run_as_non_root.setter def run_as_non_root(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "run_as_non_root", value) @property @pulumi.getter(name="runAsUser") def run_as_user(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "run_as_user") @run_as_user.setter def run_as_user(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "run_as_user", value) @property @pulumi.getter def tag(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "tag") @tag.setter def tag(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "tag", value) @pulumi.input_type class ControllerIngressClassResourceArgs: def __init__(__self__, *, controller_value: Optional[pulumi.Input[str]] = None, default: Optional[pulumi.Input[bool]] = None, enabled: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None, parameters: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None): """ :param pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]] parameters: Parameters is a link to a custom resource containing additional configuration for the controller. This is optional if the controller does not require extra parameters. """ if controller_value is not None: pulumi.set(__self__, "controller_value", controller_value) if default is not None: pulumi.set(__self__, "default", default) if enabled is not None: pulumi.set(__self__, "enabled", enabled) if name is not None: pulumi.set(__self__, "name", name) if parameters is not None: pulumi.set(__self__, "parameters", parameters) @property @pulumi.getter(name="controllerValue") def controller_value(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "controller_value") @controller_value.setter def controller_value(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "controller_value", value) @property @pulumi.getter def default(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "default") @default.setter def default(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "default", value) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter def parameters(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: """ Parameters is a link to a custom resource containing additional configuration for the controller. This is optional if the controller does not require extra parameters. """ return pulumi.get(self, "parameters") @parameters.setter def parameters(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "parameters", value) @pulumi.input_type class ControllerMetricsPrometheusRulesArgs: def __init__(__self__, *, additional_labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, enabled: Optional[pulumi.Input[bool]] = None, namespace: Optional[pulumi.Input[str]] = None, rules: Optional[pulumi.Input[Sequence[pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None): if additional_labels is not None: pulumi.set(__self__, "additional_labels", additional_labels) if enabled is not None: pulumi.set(__self__, "enabled", enabled) if namespace is not None: pulumi.set(__self__, "namespace", namespace) if rules is not None: pulumi.set(__self__, "rules", rules) @property @pulumi.getter(name="additionalLabels") def additional_labels(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "additional_labels") @additional_labels.setter def additional_labels(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "additional_labels", value) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter def namespace(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "namespace") @namespace.setter def namespace(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "namespace", value) @property @pulumi.getter def rules(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "rules") @rules.setter def rules(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "rules", value) @pulumi.input_type class ControllerMetricsServiceMonitorArgs: def __init__(__self__, *, additional_labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, enabled: Optional[pulumi.Input[bool]] = None, honor_labels: Optional[pulumi.Input[bool]] = None, job_label: Optional[pulumi.Input[str]] = None, metric_relabelings: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, namespace: Optional[pulumi.Input[str]] = None, namespace_selector: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, scrape_interval: Optional[pulumi.Input[str]] = None, target_labels: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None): """ :param pulumi.Input[str] job_label: The label to use to retrieve the job name from. """ if additional_labels is not None: pulumi.set(__self__, "additional_labels", additional_labels) if enabled is not None: pulumi.set(__self__, "enabled", enabled) if honor_labels is not None: pulumi.set(__self__, "honor_labels", honor_labels) if job_label is not None: pulumi.set(__self__, "job_label", job_label) if metric_relabelings is not None: pulumi.set(__self__, "metric_relabelings", metric_relabelings) if namespace is not None: pulumi.set(__self__, "namespace", namespace) if namespace_selector is not None: pulumi.set(__self__, "namespace_selector", namespace_selector) if scrape_interval is not None: pulumi.set(__self__, "scrape_interval", scrape_interval) if target_labels is not None: pulumi.set(__self__, "target_labels", target_labels) @property @pulumi.getter(name="additionalLabels") def additional_labels(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "additional_labels") @additional_labels.setter def additional_labels(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "additional_labels", value) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter(name="honorLabels") def honor_labels(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "honor_labels") @honor_labels.setter def honor_labels(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "honor_labels", value) @property @pulumi.getter(name="jobLabel") def job_label(self) -> Optional[pulumi.Input[str]]: """ The label to use to retrieve the job name from. """ return pulumi.get(self, "job_label") @job_label.setter def job_label(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "job_label", value) @property @pulumi.getter(name="metricRelabelings") def metric_relabelings(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: return pulumi.get(self, "metric_relabelings") @metric_relabelings.setter def metric_relabelings(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "metric_relabelings", value) @property @pulumi.getter def namespace(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "namespace") @namespace.setter def namespace(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "namespace", value) @property @pulumi.getter(name="namespaceSelector") def namespace_selector(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "namespace_selector") @namespace_selector.setter def namespace_selector(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "namespace_selector", value) @property @pulumi.getter(name="scrapeInterval") def scrape_interval(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "scrape_interval") @scrape_interval.setter def scrape_interval(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "scrape_interval", value) @property @pulumi.getter(name="targetLabels") def target_labels(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: return pulumi.get(self, "target_labels") @target_labels.setter def target_labels(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "target_labels", value) @pulumi.input_type class ControllerMetricsServiceArgs: def __init__(__self__, *, annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, cluster_ip: Optional[pulumi.Input[str]] = None, external_ips: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, external_traffic_policy: Optional[pulumi.Input[str]] = None, load_balancer_ips: Optional[pulumi.Input[str]] = None, load_balancer_source_ranges: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, node_port: Optional[pulumi.Input[str]] = None, service_port: Optional[pulumi.Input[int]] = None, type: Optional[pulumi.Input[str]] = None): if annotations is not None: pulumi.set(__self__, "annotations", annotations) if cluster_ip is not None: pulumi.set(__self__, "cluster_ip", cluster_ip) if external_ips is not None: pulumi.set(__self__, "external_ips", external_ips) if external_traffic_policy is not None: pulumi.set(__self__, "external_traffic_policy", external_traffic_policy) if load_balancer_ips is not None: pulumi.set(__self__, "load_balancer_ips", load_balancer_ips) if load_balancer_source_ranges is not None: pulumi.set(__self__, "load_balancer_source_ranges", load_balancer_source_ranges) if node_port is not None: pulumi.set(__self__, "node_port", node_port) if service_port is not None: pulumi.set(__self__, "service_port", service_port) if type is not None: pulumi.set(__self__, "type", type) @property @pulumi.getter def annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: return pulumi.get(self, "annotations") @annotations.setter def annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "annotations", value) @property @pulumi.getter(name="clusterIP") def cluster_ip(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "cluster_ip") @cluster_ip.setter def cluster_ip(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "cluster_ip", value) @property @pulumi.getter(name="externalIPs") def external_ips(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: return pulumi.get(self, "external_ips") @external_ips.setter def external_ips(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "external_ips", value) @property @pulumi.getter(name="externalTrafficPolicy") def external_traffic_policy(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "external_traffic_policy") @external_traffic_policy.setter def external_traffic_policy(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "external_traffic_policy", value) @property @pulumi.getter(name="loadBalancerIPs") def load_balancer_ips(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "load_balancer_ips") @load_balancer_ips.setter def load_balancer_ips(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "load_balancer_ips", value) @property @pulumi.getter(name="loadBalancerSourceRanges") def load_balancer_source_ranges(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: return pulumi.get(self, "load_balancer_source_ranges") @load_balancer_source_ranges.setter def load_balancer_source_ranges(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "load_balancer_source_ranges", value) @property @pulumi.getter(name="nodePort") def node_port(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "node_port") @node_port.setter def node_port(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "node_port", value) @property @pulumi.getter(name="servicePort") def service_port(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "service_port") @service_port.setter def service_port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "service_port", value) @property @pulumi.getter def type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "type") @type.setter def type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "type", value) @pulumi.input_type class ControllerMetricsArgs: def __init__(__self__, *, enabled: Optional[pulumi.Input[bool]] = None, port: Optional[pulumi.Input[int]] = None, prometheus_rule: Optional[pulumi.Input['ControllerMetricsPrometheusRulesArgs']] = None, service: Optional[pulumi.Input['ControllerMetricsServiceArgs']] = None, service_monitor: Optional[pulumi.Input['ControllerMetricsServiceMonitorArgs']] = None): """ :param pulumi.Input[int] port: if this port is changed, change healthz-port: in extraArgs: accordingly. """ if enabled is not None: pulumi.set(__self__, "enabled", enabled) if port is not None: pulumi.set(__self__, "port", port) if prometheus_rule is not None: pulumi.set(__self__, "prometheus_rule", prometheus_rule) if service is not None: pulumi.set(__self__, "service", service) if service_monitor is not None: pulumi.set(__self__, "service_monitor", service_monitor) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter def port(self) -> Optional[pulumi.Input[int]]: """ if this port is changed, change healthz-port: in extraArgs: accordingly. """ return pulumi.get(self, "port") @port.setter def port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "port", value) @property @pulumi.getter(name="prometheusRule") def prometheus_rule(self) -> Optional[pulumi.Input['ControllerMetricsPrometheusRulesArgs']]: return pulumi.get(self, "prometheus_rule") @prometheus_rule.setter def prometheus_rule(self, value: Optional[pulumi.Input['ControllerMetricsPrometheusRulesArgs']]): pulumi.set(self, "prometheus_rule", value) @property @pulumi.getter def service(self) -> Optional[pulumi.Input['ControllerMetricsServiceArgs']]: return pulumi.get(self, "service") @service.setter def service(self, value: Optional[pulumi.Input['ControllerMetricsServiceArgs']]): pulumi.set(self, "service", value) @property @pulumi.getter(name="serviceMonitor") def service_monitor(self) -> Optional[pulumi.Input['ControllerMetricsServiceMonitorArgs']]: return pulumi.get(self, "service_monitor") @service_monitor.setter def service_monitor(self, value: Optional[pulumi.Input['ControllerMetricsServiceMonitorArgs']]): pulumi.set(self, "service_monitor", value) @pulumi.input_type class ControllerPodSecurityPolicyArgs: def __init__(__self__, *, enabled: Optional[pulumi.Input[bool]] = None): if enabled is not None: pulumi.set(__self__, "enabled", enabled) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @pulumi.input_type class ControllerPortArgs: def __init__(__self__, *, http: Optional[pulumi.Input[int]] = None, https: Optional[pulumi.Input[int]] = None): if http is not None: pulumi.set(__self__, "http", http) if https is not None: pulumi.set(__self__, "https", https) @property @pulumi.getter def http(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "http") @http.setter def http(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "http", value) @property @pulumi.getter def https(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "https") @https.setter def https(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "https", value) @pulumi.input_type class ControllerPublishServiceArgs: def __init__(__self__, *, enabled: Optional[pulumi.Input[bool]] = None, path_override: Optional[pulumi.Input[str]] = None): """ :param pulumi.Input[str] path_override: Allows overriding of the publish service to bind to. Must be <namespace>/<service_name>. """ if enabled is not None: pulumi.set(__self__, "enabled", enabled) if path_override is not None: pulumi.set(__self__, "path_override", path_override) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter(name="pathOverride") def path_override(self) -> Optional[pulumi.Input[str]]: """ Allows overriding of the publish service to bind to. Must be <namespace>/<service_name>. """ return pulumi.get(self, "path_override") @path_override.setter def path_override(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "path_override", value) @pulumi.input_type class ControllerRBACArgs: def __init__(__self__, *, create: Optional[pulumi.Input[bool]] = None, scope: Optional[pulumi.Input[bool]] = None): if create is not None: pulumi.set(__self__, "create", create) if scope is not None: pulumi.set(__self__, "scope", scope) @property @pulumi.getter def create(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "create") @create.setter def create(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "create", value) @property @pulumi.getter def scope(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "scope") @scope.setter def scope(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "scope", value) @pulumi.input_type class ControllerRollingUpdateArgs: def __init__(__self__, *, max_unavailable: Optional[pulumi.Input[int]] = None): if max_unavailable is not None: pulumi.set(__self__, "max_unavailable", max_unavailable) @property @pulumi.getter(name="maxUnavailable") def max_unavailable(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "max_unavailable") @max_unavailable.setter def max_unavailable(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "max_unavailable", value) @pulumi.input_type class ControllerScopeArgs: def __init__(__self__, *, enabled: Optional[pulumi.Input[bool]] = None, namespace: Optional[pulumi.Input[str]] = None): if enabled is not None: pulumi.set(__self__, "enabled", enabled) if namespace is not None: pulumi.set(__self__, "namespace", namespace) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter def namespace(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "namespace") @namespace.setter def namespace(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "namespace", value) @pulumi.input_type class ControllerServiceAccountArgs: def __init__(__self__, *, automount_service_account_token: Optional[pulumi.Input[bool]] = None, create: Optional[pulumi.Input[bool]] = None, name: Optional[pulumi.Input[str]] = None): if automount_service_account_token is not None: pulumi.set(__self__, "automount_service_account_token", automount_service_account_token) if create is not None: pulumi.set(__self__, "create", create) if name is not None: pulumi.set(__self__, "name", name) @property @pulumi.getter(name="automountServiceAccountToken") def automount_service_account_token(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "automount_service_account_token") @automount_service_account_token.setter def automount_service_account_token(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "automount_service_account_token", value) @property @pulumi.getter def create(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "create") @create.setter def create(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "create", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @pulumi.input_type class ControllerServiceInternalArgs: def __init__(__self__, *, annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, enabled: Optional[pulumi.Input[bool]] = None, external_traffic_policy: Optional[pulumi.Input[str]] = None, labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, load_balancer_ips: Optional[pulumi.Input[str]] = None, load_balancer_source_ranges: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None): """ :param pulumi.Input[str] external_traffic_policy: Set external traffic policy to: "Local" to preserve source IP on providers supporting it. Ref: https://kubernetes.io/docs/tutorials/services/source-ip/#source-ip-for-services-with-typeloadbalancer :param pulumi.Input[Sequence[pulumi.Input[str]]] load_balancer_source_ranges: Restrict access For LoadBalancer service. Defaults to 0.0.0.0/0. """ if annotations is not None: pulumi.set(__self__, "annotations", annotations) if enabled is not None: pulumi.set(__self__, "enabled", enabled) if external_traffic_policy is not None: pulumi.set(__self__, "external_traffic_policy", external_traffic_policy) if labels is not None: pulumi.set(__self__, "labels", labels) if load_balancer_ips is not None: pulumi.set(__self__, "load_balancer_ips", load_balancer_ips) if load_balancer_source_ranges is not None: pulumi.set(__self__, "load_balancer_source_ranges", load_balancer_source_ranges) @property @pulumi.getter def annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "annotations") @annotations.setter def annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "annotations", value) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter(name="externalTrafficPolicy") def external_traffic_policy(self) -> Optional[pulumi.Input[str]]: """ Set external traffic policy to: "Local" to preserve source IP on providers supporting it. Ref: https://kubernetes.io/docs/tutorials/services/source-ip/#source-ip-for-services-with-typeloadbalancer """ return pulumi.get(self, "external_traffic_policy") @external_traffic_policy.setter def external_traffic_policy(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "external_traffic_policy", value) @property @pulumi.getter def labels(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "labels") @labels.setter def labels(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "labels", value) @property @pulumi.getter(name="loadBalancerIPs") def load_balancer_ips(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "load_balancer_ips") @load_balancer_ips.setter def load_balancer_ips(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "load_balancer_ips", value) @property @pulumi.getter(name="loadBalancerSourceRanges") def load_balancer_source_ranges(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ Restrict access For LoadBalancer service. Defaults to 0.0.0.0/0. """ return pulumi.get(self, "load_balancer_source_ranges") @load_balancer_source_ranges.setter def load_balancer_source_ranges(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "load_balancer_source_ranges", value) @pulumi.input_type class ControllerServiceNodePortsArgs: def __init__(__self__, *, http: Optional[pulumi.Input[str]] = None, https: Optional[pulumi.Input[str]] = None, tcp: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, udp: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None): if http is not None: pulumi.set(__self__, "http", http) if https is not None: pulumi.set(__self__, "https", https) if tcp is not None: pulumi.set(__self__, "tcp", tcp) if udp is not None: pulumi.set(__self__, "udp", udp) @property @pulumi.getter def http(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "http") @http.setter def http(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "http", value) @property @pulumi.getter def https(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "https") @https.setter def https(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "https", value) @property @pulumi.getter def tcp(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "tcp") @tcp.setter def tcp(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "tcp", value) @property @pulumi.getter def udp(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "udp") @udp.setter def udp(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "udp", value) @pulumi.input_type class ControllerServiceArgs: def __init__(__self__, *, annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, cluster_ip: Optional[pulumi.Input[str]] = None, enable_http: Optional[pulumi.Input[bool]] = None, enable_https: Optional[pulumi.Input[bool]] = None, enabled: Optional[pulumi.Input[bool]] = None, external_ips: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, external_traffic_policy: Optional[pulumi.Input[str]] = None, health_check_node_port: Optional[pulumi.Input[int]] = None, internal: Optional[pulumi.Input['ControllerServiceInternalArgs']] = None, labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, load_balancer_ips: Optional[pulumi.Input[str]] = None, load_balancer_source_ranges: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, node_ports: Optional[pulumi.Input['ControllerServiceNodePortsArgs']] = None, ports: Optional[pulumi.Input['ControllerPortArgs']] = None, session_affinity: Optional[pulumi.Input[str]] = None, target_ports: Optional[pulumi.Input['ControllerPortArgs']] = None, type: Optional[pulumi.Input[str]] = None): """ :param pulumi.Input[Sequence[pulumi.Input[str]]] external_ips: List of IP addresses at which the controller services are available Ref: https://kubernetes.io/docs/user-guide/services/#external-ips :param pulumi.Input[str] external_traffic_policy: Set external traffic policy to: "Local" to preserve source IP on providers supporting it. Ref: https://kubernetes.io/docs/tutorials/services/source-ip/#source-ip-for-services-with-typeloadbalancer :param pulumi.Input[int] health_check_node_port: specifies the health check node port (numeric port number) for the service. If healthCheckNodePort isn’t specified, the service controller allocates a port from your cluster’s NodePort range. Ref: https://kubernetes.io/docs/tasks/access-application-cluster/create-external-load-balancer/#preserving-the-client-source-ip :param pulumi.Input['ControllerServiceInternalArgs'] internal: Enables an additional internal load balancer (besides the external one). Annotations are mandatory for the load balancer to come up. Varies with the cloud service. :param pulumi.Input[str] session_affinity: Must be either "None" or "ClientIP" if set. Kubernetes will default to "None". Ref: https://kubernetes.io/docs/concepts/services-networking/service/#virtual-ips-and-service-proxies """ if annotations is not None: pulumi.set(__self__, "annotations", annotations) if cluster_ip is not None: pulumi.set(__self__, "cluster_ip", cluster_ip) if enable_http is not None: pulumi.set(__self__, "enable_http", enable_http) if enable_https is not None: pulumi.set(__self__, "enable_https", enable_https) if enabled is not None: pulumi.set(__self__, "enabled", enabled) if external_ips is not None: pulumi.set(__self__, "external_ips", external_ips) if external_traffic_policy is not None: pulumi.set(__self__, "external_traffic_policy", external_traffic_policy) if health_check_node_port is not None: pulumi.set(__self__, "health_check_node_port", health_check_node_port) if internal is not None: pulumi.set(__self__, "internal", internal) if labels is not None: pulumi.set(__self__, "labels", labels) if load_balancer_ips is not None: pulumi.set(__self__, "load_balancer_ips", load_balancer_ips) if load_balancer_source_ranges is not None: pulumi.set(__self__, "load_balancer_source_ranges", load_balancer_source_ranges) if node_ports is not None: pulumi.set(__self__, "node_ports", node_ports) if ports is not None: pulumi.set(__self__, "ports", ports) if session_affinity is not None: pulumi.set(__self__, "session_affinity", session_affinity) if target_ports is not None: pulumi.set(__self__, "target_ports", target_ports) if type is not None: pulumi.set(__self__, "type", type) @property @pulumi.getter def annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "annotations") @annotations.setter def annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "annotations", value) @property @pulumi.getter(name="clusterIP") def cluster_ip(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "cluster_ip") @cluster_ip.setter def cluster_ip(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "cluster_ip", value) @property @pulumi.getter(name="enableHttp") def enable_http(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enable_http") @enable_http.setter def enable_http(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enable_http", value) @property @pulumi.getter(name="enableHttps") def enable_https(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enable_https") @enable_https.setter def enable_https(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enable_https", value) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter(name="externalIPs") def external_ips(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ List of IP addresses at which the controller services are available Ref: https://kubernetes.io/docs/user-guide/services/#external-ips """ return pulumi.get(self, "external_ips") @external_ips.setter def external_ips(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "external_ips", value) @property @pulumi.getter(name="externalTrafficPolicy") def external_traffic_policy(self) -> Optional[pulumi.Input[str]]: """ Set external traffic policy to: "Local" to preserve source IP on providers supporting it. Ref: https://kubernetes.io/docs/tutorials/services/source-ip/#source-ip-for-services-with-typeloadbalancer """ return pulumi.get(self, "external_traffic_policy") @external_traffic_policy.setter def external_traffic_policy(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "external_traffic_policy", value) @property @pulumi.getter(name="healthCheckNodePort") def health_check_node_port(self) -> Optional[pulumi.Input[int]]: """ specifies the health check node port (numeric port number) for the service. If healthCheckNodePort isn’t specified, the service controller allocates a port from your cluster’s NodePort range. Ref: https://kubernetes.io/docs/tasks/access-application-cluster/create-external-load-balancer/#preserving-the-client-source-ip """ return pulumi.get(self, "health_check_node_port") @health_check_node_port.setter def health_check_node_port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "health_check_node_port", value) @property @pulumi.getter def internal(self) -> Optional[pulumi.Input['ControllerServiceInternalArgs']]: """ Enables an additional internal load balancer (besides the external one). Annotations are mandatory for the load balancer to come up. Varies with the cloud service. """ return pulumi.get(self, "internal") @internal.setter def internal(self, value: Optional[pulumi.Input['ControllerServiceInternalArgs']]): pulumi.set(self, "internal", value) @property @pulumi.getter def labels(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "labels") @labels.setter def labels(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "labels", value) @property @pulumi.getter(name="loadBalancerIPs") def load_balancer_ips(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "load_balancer_ips") @load_balancer_ips.setter def load_balancer_ips(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "load_balancer_ips", value) @property @pulumi.getter(name="loadBalancerSourceRanges") def load_balancer_source_ranges(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: return pulumi.get(self, "load_balancer_source_ranges") @load_balancer_source_ranges.setter def load_balancer_source_ranges(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "load_balancer_source_ranges", value) @property @pulumi.getter(name="nodePorts") def node_ports(self) -> Optional[pulumi.Input['ControllerServiceNodePortsArgs']]: return pulumi.get(self, "node_ports") @node_ports.setter def node_ports(self, value: Optional[pulumi.Input['ControllerServiceNodePortsArgs']]): pulumi.set(self, "node_ports", value) @property @pulumi.getter def ports(self) -> Optional[pulumi.Input['ControllerPortArgs']]: return pulumi.get(self, "ports") @ports.setter def ports(self, value: Optional[pulumi.Input['ControllerPortArgs']]): pulumi.set(self, "ports", value) @property @pulumi.getter(name="sessionAffinity") def session_affinity(self) -> Optional[pulumi.Input[str]]: """ Must be either "None" or "ClientIP" if set. Kubernetes will default to "None". Ref: https://kubernetes.io/docs/concepts/services-networking/service/#virtual-ips-and-service-proxies """ return pulumi.get(self, "session_affinity") @session_affinity.setter def session_affinity(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "session_affinity", value) @property @pulumi.getter(name="targetPorts") def target_ports(self) -> Optional[pulumi.Input['ControllerPortArgs']]: return pulumi.get(self, "target_ports") @target_ports.setter def target_ports(self, value: Optional[pulumi.Input['ControllerPortArgs']]): pulumi.set(self, "target_ports", value) @property @pulumi.getter def type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "type") @type.setter def type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "type", value) @pulumi.input_type class ControllerTcpArgs: def __init__(__self__, *, annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, config_map_namespace: Optional[pulumi.Input[str]] = None): """ :param pulumi.Input[Mapping[str, pulumi.Input[str]]] annotations: Annotations to be added to the tcp config configmap. """ if annotations is not None: pulumi.set(__self__, "annotations", annotations) if config_map_namespace is not None: pulumi.set(__self__, "config_map_namespace", config_map_namespace) @property @pulumi.getter def annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ Annotations to be added to the tcp config configmap. """ return pulumi.get(self, "annotations") @annotations.setter def annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "annotations", value) @property @pulumi.getter(name="configMapNamespace") def config_map_namespace(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "config_map_namespace") @config_map_namespace.setter def config_map_namespace(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "config_map_namespace", value) @pulumi.input_type class ControllerUdpArgs: def __init__(__self__, *, annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, config_map_namespace: Optional[pulumi.Input[str]] = None): """ :param pulumi.Input[Mapping[str, pulumi.Input[str]]] annotations: Annotations to be added to the udp config configmap. """ if annotations is not None: pulumi.set(__self__, "annotations", annotations) if config_map_namespace is not None: pulumi.set(__self__, "config_map_namespace", config_map_namespace) @property @pulumi.getter def annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ Annotations to be added to the udp config configmap. """ return pulumi.get(self, "annotations") @annotations.setter def annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "annotations", value) @property @pulumi.getter(name="configMapNamespace") def config_map_namespace(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "config_map_namespace") @config_map_namespace.setter def config_map_namespace(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "config_map_namespace", value) @pulumi.input_type class ControllerUpdateStrategyArgs: def __init__(__self__, *, rolling_update: Optional[pulumi.Input['ControllerRollingUpdateArgs']] = None, type: Optional[pulumi.Input[str]] = None): if rolling_update is not None: pulumi.set(__self__, "rolling_update", rolling_update) if type is not None: pulumi.set(__self__, "type", type) @property @pulumi.getter(name="rollingUpdate") def rolling_update(self) -> Optional[pulumi.Input['ControllerRollingUpdateArgs']]: return pulumi.get(self, "rolling_update") @rolling_update.setter def rolling_update(self, value: Optional[pulumi.Input['ControllerRollingUpdateArgs']]): pulumi.set(self, "rolling_update", value) @property @pulumi.getter def type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "type") @type.setter def type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "type", value) @pulumi.input_type class ControllerArgs: def __init__(__self__, *, add_headers: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, admission_webhooks: Optional[pulumi.Input['ContollerAdmissionWebhooksArgs']] = None, affinity: Optional[pulumi.Input['pulumi_kubernetes.core.v1.AffinityArgs']] = None, allow_snippet_annotations: Optional[pulumi.Input[bool]] = None, annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, autoscaling: Optional[pulumi.Input['AutoscalingArgs']] = None, autoscaling_template: Optional[pulumi.Input[Sequence[pulumi.Input['AutoscalingTemplateArgs']]]] = None, config: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, config_annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, config_map_namespace: Optional[pulumi.Input[str]] = None, container_name: Optional[pulumi.Input[str]] = None, container_port: Optional[pulumi.Input['ControllerPortArgs']] = None, custom_template: Optional[pulumi.Input['ControllerCustomTemplateArgs']] = None, dns_config: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, dns_policy: Optional[pulumi.Input[str]] = None, election_id: Optional[pulumi.Input[str]] = None, enable_mimalloc: Optional[pulumi.Input[bool]] = None, existing_psp: Optional[pulumi.Input[str]] = None, extra_args: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, extra_containers: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.ContainerArgs']]]] = None, extra_envs: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.EnvVarArgs']]]] = None, extra_init_containers: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.ContainerArgs']]]] = None, extra_volume_mounts: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeMountArgs']]]] = None, extra_volumes: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeArgs']]]] = None, health_check_path: Optional[pulumi.Input[str]] = None, heath_check_host: Optional[pulumi.Input[str]] = None, host_network: Optional[pulumi.Input[bool]] = None, host_port: Optional[pulumi.Input['ControllerHostPortArgs']] = None, hostname: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, image: Optional[pulumi.Input['ControllerImageArgs']] = None, ingress_class_by_name: Optional[pulumi.Input[bool]] = None, ingress_class_resource: Optional[pulumi.Input['ControllerIngressClassResourceArgs']] = None, keda: Optional[pulumi.Input['KedaArgs']] = None, kind: Optional[pulumi.Input[str]] = None, lifecycle: Optional[pulumi.Input['pulumi_kubernetes.core.v1.LifecycleArgs']] = None, liveness_probe: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']] = None, maxmind_license_key: Optional[pulumi.Input[str]] = None, metrics: Optional[pulumi.Input['ControllerMetricsArgs']] = None, min_available: Optional[pulumi.Input[int]] = None, min_ready_seconds: Optional[pulumi.Input[int]] = None, name: Optional[pulumi.Input[str]] = None, node_selector: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, pod_annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, pod_labels: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, pod_security_context: Optional[pulumi.Input['pulumi_kubernetes.core.v1.PodSecurityContextArgs']] = None, priority_class_name: Optional[pulumi.Input[str]] = None, proxy_set_headers: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, publish_service: Optional[pulumi.Input['ControllerPublishServiceArgs']] = None, readiness_probe: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']] = None, replica_count: Optional[pulumi.Input[int]] = None, report_node_internal_ip: Optional[pulumi.Input[bool]] = None, resources: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']] = None, scope: Optional[pulumi.Input['ControllerScopeArgs']] = None, service: Optional[pulumi.Input['ControllerServiceArgs']] = None, startup_probe: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']] = None, sysctls: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, tcp: Optional[pulumi.Input['ControllerTcpArgs']] = None, terminate_grace_period_seconds: Optional[pulumi.Input[int]] = None, tolerations: Optional[pulumi.Input['pulumi_kubernetes.core.v1.TolerationArgs']] = None, topology_spread_constraints: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.TopologySpreadConstraintArgs']]]] = None, udp: Optional[pulumi.Input['ControllerUdpArgs']] = None, update_strategy: Optional[pulumi.Input['ControllerUpdateStrategyArgs']] = None, watch_ingress_without_class: Optional[pulumi.Input[bool]] = None): """ :param pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]] add_headers: Will add custom headers before sending response traffic to the client according to: https://kubernetes.github.io/ingress-nginx/user-guide/nginx-configuration/configmap/#add-headers. :param pulumi.Input['pulumi_kubernetes.core.v1.AffinityArgs'] affinity: Affinity and anti-affinity Ref: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/#affinity-and-anti-affinity. :param pulumi.Input[bool] allow_snippet_annotations: This configuration defines if Ingress Controller should allow users to set their own *-snippet annotations, otherwise this is forbidden / dropped when users add those annotations. Global snippets in ConfigMap are still respected. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] annotations: Annotations to be added to the controller Deployment or DaemonSet. :param pulumi.Input['AutoscalingArgs'] autoscaling: Mutually exclusive with keda autoscaling. :param pulumi.Input[Sequence[pulumi.Input['AutoscalingTemplateArgs']]] autoscaling_template: Custom or additional autoscaling metrics ref: https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/#support-for-custom-metrics :param pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]] config: Will add custom configuration options to Nginx https://kubernetes.github.io/ingress-nginx/user-guide/nginx-configuration/configmap/. :param pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]] config_annotations: Annotations to be added to the controller config configuration configmap. :param pulumi.Input[str] config_map_namespace: Allows customization of the configmap / nginx-configmap namespace. :param pulumi.Input[str] container_name: Configures the controller container name. :param pulumi.Input['ControllerPortArgs'] container_port: Configures the ports the nginx-controller listens on. :param pulumi.Input['ControllerCustomTemplateArgs'] custom_template: Override NGINX template. :param pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]] dns_config: Optionally customize the pod dnsConfig. :param pulumi.Input[str] dns_policy: Optionally change this to ClusterFirstWithHostNet in case you have 'hostNetwork: true'. By default, while using host network, name resolution uses the host's DNS. If you wish nginx-controller to keep resolving names inside the k8s network, use ClusterFirstWithHostNet. :param pulumi.Input[str] election_id: Election ID to use for status update. :param pulumi.Input[bool] enable_mimalloc: Enable mimalloc as a drop-in replacement for malloc. ref: https://github.com/microsoft/mimalloc. :param pulumi.Input[str] existing_psp: Use an existing PSP instead of creating one. :param pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]] extra_args: Additional command line arguments to pass to nginx-ingress-controller E.g. to specify the default SSL certificate you can use `default-ssl-certificate: "<namespace>/<secret_name>"`. :param pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.ContainerArgs']]] extra_containers: Additional containers to be added to the controller pod. See https://github.com/lemonldap-ng-controller/lemonldap-ng-controller as example. :param pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.EnvVarArgs']]] extra_envs: Additional environment variables to set. :param pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.ContainerArgs']]] extra_init_containers: Containers, which are run before the app containers are started. - name: init-myservice image: busybox command: ['sh', '-c', 'until nslookup myservice; do echo waiting for myservice; sleep 2; done;'] :param pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeMountArgs']]] extra_volume_mounts: Additional volumeMounts to the controller main container. - name: copy-portal-skins mountPath: /var/lib/lemonldap-ng/portal/skins :param pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeArgs']]] extra_volumes: Additional volumes to the controller pod. - name: copy-portal-skins emptyDir: {} :param pulumi.Input[str] health_check_path: Path of the health check endpoint. All requests received on the port defined by the healthz-port parameter are forwarded internally to this path. :param pulumi.Input[str] heath_check_host: Address to bind the health check endpoint. It is better to set this option to the internal node address if the ingress nginx controller is running in the hostNetwork: true mode. :param pulumi.Input[bool] host_network: Required for use with CNI based kubernetes installations (such as ones set up by kubeadm), since CNI and hostport don't mix yet. Can be deprecated once https://github.com/kubernetes/kubernetes/issues/23920 is merged. :param pulumi.Input['ControllerHostPortArgs'] host_port: Use host ports 80 and 443. Disabled by default. :param pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]] hostname: Optionally customize the pod hostname. :param pulumi.Input[bool] ingress_class_by_name: Process IngressClass per name (additionally as per spec.controller). :param pulumi.Input['ControllerIngressClassResourceArgs'] ingress_class_resource: This section refers to the creation of the IngressClass resource. IngressClass resources are supported since k8s >= 1.18 and required since k8s >= 1.19 :param pulumi.Input['KedaArgs'] keda: Mutually exclusive with hpa autoscaling. :param pulumi.Input[str] kind: DaemonSet or Deployment. :param pulumi.Input['pulumi_kubernetes.core.v1.LifecycleArgs'] lifecycle: Improve connection draining when ingress controller pod is deleted using a lifecycle hook: With this new hook, we increased the default terminationGracePeriodSeconds from 30 seconds to 300, allowing the draining of connections up to five minutes. If the active connections end before that, the pod will terminate gracefully at that time. To effectively take advantage of this feature, the Configmap feature worker-shutdown-timeout new value is 240s instead of 10s. :param pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs'] liveness_probe: Liveness probe values Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes. :param pulumi.Input[str] maxmind_license_key: Maxmind license key to download GeoLite2 Databases https://blog.maxmind.com/2019/12/18/significant-changes-to-accessing-and-using-geolite2-databases. :param pulumi.Input[int] min_ready_seconds: minReadySeconds to avoid killing pods before we are ready. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] node_selector: Node labels for controller pod assignment Ref: https://kubernetes.io/docs/user-guide/node-selection/. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] pod_annotations: Annotations to be added to controller pods. :param pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]] pod_labels: labels to add to the pod container metadata. :param pulumi.Input['pulumi_kubernetes.core.v1.PodSecurityContextArgs'] pod_security_context: Security Context policies for controller pods. :param pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]] proxy_set_headers: Will add custom headers before sending traffic to backends according to https://github.com/kubernetes/ingress-nginx/tree/main/docs/examples/customization/custom-headers. :param pulumi.Input['ControllerPublishServiceArgs'] publish_service: Allows customization of the source of the IP address or FQDN to report in the ingress status field. By default, it reads the information provided by the service. If disable, the status field reports the IP address of the node or nodes where an ingress controller pod is running. :param pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs'] readiness_probe: Readiness probe values Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes. :param pulumi.Input[bool] report_node_internal_ip: Bare-metal considerations via the host network https://kubernetes.github.io/ingress-nginx/deploy/baremetal/#via-the-host-network Ingress status was blank because there is no Service exposing the NGINX Ingress controller in a configuration using the host network, the default --publish-service flag used in standard cloud setups does not apply. :param pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs'] resources: Define requests resources to avoid probe issues due to CPU utilization in busy nodes ref: https://github.com/kubernetes/ingress-nginx/issues/4735#issuecomment-551204903 Ideally, there should be no limits. https://engineering.indeedblog.com/blog/2019/12/cpu-throttling-regression-fix/ :param pulumi.Input['ControllerScopeArgs'] scope: Limit the scope of the controller. :param pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs'] startup_probe: Startup probe values Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes. :param pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]] sysctls: See https://kubernetes.io/docs/tasks/administer-cluster/sysctl-cluster/ for notes on enabling and using sysctls. :param pulumi.Input['ControllerTcpArgs'] tcp: Allows customization of the tcp-services-configmap. :param pulumi.Input[int] terminate_grace_period_seconds: How long to wait for the drain of connections. :param pulumi.Input['pulumi_kubernetes.core.v1.TolerationArgs'] tolerations: Node tolerations for server scheduling to nodes with taints Ref: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/. :param pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.TopologySpreadConstraintArgs']]] topology_spread_constraints: Topology spread constraints rely on node labels to identify the topology domain(s) that each Node is in. Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-topology-spread-constraints/. :param pulumi.Input['ControllerUpdateStrategyArgs'] update_strategy: The update strategy to apply to the Deployment or DaemonSet. :param pulumi.Input[bool] watch_ingress_without_class: Process Ingress objects without ingressClass annotation/ingressClassName field. Overrides value for --watch-ingress-without-class flag of the controller binary. Defaults to false. """ if add_headers is not None: pulumi.set(__self__, "add_headers", add_headers) if admission_webhooks is not None: pulumi.set(__self__, "admission_webhooks", admission_webhooks) if affinity is not None: pulumi.set(__self__, "affinity", affinity) if allow_snippet_annotations is not None: pulumi.set(__self__, "allow_snippet_annotations", allow_snippet_annotations) if annotations is not None: pulumi.set(__self__, "annotations", annotations) if autoscaling is not None: pulumi.set(__self__, "autoscaling", autoscaling) if autoscaling_template is not None: pulumi.set(__self__, "autoscaling_template", autoscaling_template) if config is not None: pulumi.set(__self__, "config", config) if config_annotations is not None: pulumi.set(__self__, "config_annotations", config_annotations) if config_map_namespace is not None: pulumi.set(__self__, "config_map_namespace", config_map_namespace) if container_name is not None: pulumi.set(__self__, "container_name", container_name) if container_port is not None: pulumi.set(__self__, "container_port", container_port) if custom_template is not None: pulumi.set(__self__, "custom_template", custom_template) if dns_config is not None: pulumi.set(__self__, "dns_config", dns_config) if dns_policy is not None: pulumi.set(__self__, "dns_policy", dns_policy) if election_id is not None: pulumi.set(__self__, "election_id", election_id) if enable_mimalloc is not None: pulumi.set(__self__, "enable_mimalloc", enable_mimalloc) if existing_psp is not None: pulumi.set(__self__, "existing_psp", existing_psp) if extra_args is not None: pulumi.set(__self__, "extra_args", extra_args) if extra_containers is not None: pulumi.set(__self__, "extra_containers", extra_containers) if extra_envs is not None: pulumi.set(__self__, "extra_envs", extra_envs) if extra_init_containers is not None: pulumi.set(__self__, "extra_init_containers", extra_init_containers) if extra_volume_mounts is not None: pulumi.set(__self__, "extra_volume_mounts", extra_volume_mounts) if extra_volumes is not None: pulumi.set(__self__, "extra_volumes", extra_volumes) if health_check_path is not None: pulumi.set(__self__, "health_check_path", health_check_path) if heath_check_host is not None: pulumi.set(__self__, "heath_check_host", heath_check_host) if host_network is not None: pulumi.set(__self__, "host_network", host_network) if host_port is not None: pulumi.set(__self__, "host_port", host_port) if hostname is not None: pulumi.set(__self__, "hostname", hostname) if image is not None: pulumi.set(__self__, "image", image) if ingress_class_by_name is not None: pulumi.set(__self__, "ingress_class_by_name", ingress_class_by_name) if ingress_class_resource is not None: pulumi.set(__self__, "ingress_class_resource", ingress_class_resource) if keda is not None: pulumi.set(__self__, "keda", keda) if kind is not None: pulumi.set(__self__, "kind", kind) if lifecycle is not None: pulumi.set(__self__, "lifecycle", lifecycle) if liveness_probe is not None: pulumi.set(__self__, "liveness_probe", liveness_probe) if maxmind_license_key is not None: pulumi.set(__self__, "maxmind_license_key", maxmind_license_key) if metrics is not None: pulumi.set(__self__, "metrics", metrics) if min_available is not None: pulumi.set(__self__, "min_available", min_available) if min_ready_seconds is not None: pulumi.set(__self__, "min_ready_seconds", min_ready_seconds) if name is not None: pulumi.set(__self__, "name", name) if node_selector is not None: pulumi.set(__self__, "node_selector", node_selector) if pod_annotations is not None: pulumi.set(__self__, "pod_annotations", pod_annotations) if pod_labels is not None: pulumi.set(__self__, "pod_labels", pod_labels) if pod_security_context is not None: pulumi.set(__self__, "pod_security_context", pod_security_context) if priority_class_name is not None: pulumi.set(__self__, "priority_class_name", priority_class_name) if proxy_set_headers is not None: pulumi.set(__self__, "proxy_set_headers", proxy_set_headers) if publish_service is not None: pulumi.set(__self__, "publish_service", publish_service) if readiness_probe is not None: pulumi.set(__self__, "readiness_probe", readiness_probe) if replica_count is not None: pulumi.set(__self__, "replica_count", replica_count) if report_node_internal_ip is not None: pulumi.set(__self__, "report_node_internal_ip", report_node_internal_ip) if resources is not None: pulumi.set(__self__, "resources", resources) if scope is not None: pulumi.set(__self__, "scope", scope) if service is not None: pulumi.set(__self__, "service", service) if startup_probe is not None: pulumi.set(__self__, "startup_probe", startup_probe) if sysctls is not None: pulumi.set(__self__, "sysctls", sysctls) if tcp is not None: pulumi.set(__self__, "tcp", tcp) if terminate_grace_period_seconds is not None: pulumi.set(__self__, "terminate_grace_period_seconds", terminate_grace_period_seconds) if tolerations is not None: pulumi.set(__self__, "tolerations", tolerations) if topology_spread_constraints is not None: pulumi.set(__self__, "topology_spread_constraints", topology_spread_constraints) if udp is not None: pulumi.set(__self__, "udp", udp) if update_strategy is not None: pulumi.set(__self__, "update_strategy", update_strategy) if watch_ingress_without_class is not None: pulumi.set(__self__, "watch_ingress_without_class", watch_ingress_without_class) @property @pulumi.getter(name="addHeaders") def add_headers(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: """ Will add custom headers before sending response traffic to the client according to: https://kubernetes.github.io/ingress-nginx/user-guide/nginx-configuration/configmap/#add-headers. """ return pulumi.get(self, "add_headers") @add_headers.setter def add_headers(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "add_headers", value) @property @pulumi.getter(name="admissionWebhooks") def admission_webhooks(self) -> Optional[pulumi.Input['ContollerAdmissionWebhooksArgs']]: return pulumi.get(self, "admission_webhooks") @admission_webhooks.setter def admission_webhooks(self, value: Optional[pulumi.Input['ContollerAdmissionWebhooksArgs']]): pulumi.set(self, "admission_webhooks", value) @property @pulumi.getter def affinity(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.AffinityArgs']]: """ Affinity and anti-affinity Ref: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/#affinity-and-anti-affinity. """ return pulumi.get(self, "affinity") @affinity.setter def affinity(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.AffinityArgs']]): pulumi.set(self, "affinity", value) @property @pulumi.getter(name="allowSnippetAnnotations") def allow_snippet_annotations(self) -> Optional[pulumi.Input[bool]]: """ This configuration defines if Ingress Controller should allow users to set their own *-snippet annotations, otherwise this is forbidden / dropped when users add those annotations. Global snippets in ConfigMap are still respected. """ return pulumi.get(self, "allow_snippet_annotations") @allow_snippet_annotations.setter def allow_snippet_annotations(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "allow_snippet_annotations", value) @property @pulumi.getter def annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ Annotations to be added to the controller Deployment or DaemonSet. """ return pulumi.get(self, "annotations") @annotations.setter def annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "annotations", value) @property @pulumi.getter def autoscaling(self) -> Optional[pulumi.Input['AutoscalingArgs']]: """ Mutually exclusive with keda autoscaling. """ return pulumi.get(self, "autoscaling") @autoscaling.setter def autoscaling(self, value: Optional[pulumi.Input['AutoscalingArgs']]): pulumi.set(self, "autoscaling", value) @property @pulumi.getter(name="autoscalingTemplate") def autoscaling_template(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['AutoscalingTemplateArgs']]]]: """ Custom or additional autoscaling metrics ref: https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/#support-for-custom-metrics """ return pulumi.get(self, "autoscaling_template") @autoscaling_template.setter def autoscaling_template(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['AutoscalingTemplateArgs']]]]): pulumi.set(self, "autoscaling_template", value) @property @pulumi.getter def config(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: """ Will add custom configuration options to Nginx https://kubernetes.github.io/ingress-nginx/user-guide/nginx-configuration/configmap/. """ return pulumi.get(self, "config") @config.setter def config(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "config", value) @property @pulumi.getter(name="configAnnotations") def config_annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: """ Annotations to be added to the controller config configuration configmap. """ return pulumi.get(self, "config_annotations") @config_annotations.setter def config_annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "config_annotations", value) @property @pulumi.getter(name="configMapNamespace") def config_map_namespace(self) -> Optional[pulumi.Input[str]]: """ Allows customization of the configmap / nginx-configmap namespace. """ return pulumi.get(self, "config_map_namespace") @config_map_namespace.setter def config_map_namespace(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "config_map_namespace", value) @property @pulumi.getter(name="containerName") def container_name(self) -> Optional[pulumi.Input[str]]: """ Configures the controller container name. """ return pulumi.get(self, "container_name") @container_name.setter def container_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "container_name", value) @property @pulumi.getter(name="containerPort") def container_port(self) -> Optional[pulumi.Input['ControllerPortArgs']]: """ Configures the ports the nginx-controller listens on. """ return pulumi.get(self, "container_port") @container_port.setter def container_port(self, value: Optional[pulumi.Input['ControllerPortArgs']]): pulumi.set(self, "container_port", value) @property @pulumi.getter(name="customTemplate") def custom_template(self) -> Optional[pulumi.Input['ControllerCustomTemplateArgs']]: """ Override NGINX template. """ return pulumi.get(self, "custom_template") @custom_template.setter def custom_template(self, value: Optional[pulumi.Input['ControllerCustomTemplateArgs']]): pulumi.set(self, "custom_template", value) @property @pulumi.getter(name="dnsConfig") def dns_config(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: """ Optionally customize the pod dnsConfig. """ return pulumi.get(self, "dns_config") @dns_config.setter def dns_config(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "dns_config", value) @property @pulumi.getter(name="dnsPolicy") def dns_policy(self) -> Optional[pulumi.Input[str]]: """ Optionally change this to ClusterFirstWithHostNet in case you have 'hostNetwork: true'. By default, while using host network, name resolution uses the host's DNS. If you wish nginx-controller to keep resolving names inside the k8s network, use ClusterFirstWithHostNet. """ return pulumi.get(self, "dns_policy") @dns_policy.setter def dns_policy(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "dns_policy", value) @property @pulumi.getter(name="electionID") def election_id(self) -> Optional[pulumi.Input[str]]: """ Election ID to use for status update. """ return pulumi.get(self, "election_id") @election_id.setter def election_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "election_id", value) @property @pulumi.getter(name="enableMimalloc") def enable_mimalloc(self) -> Optional[pulumi.Input[bool]]: """ Enable mimalloc as a drop-in replacement for malloc. ref: https://github.com/microsoft/mimalloc. """ return pulumi.get(self, "enable_mimalloc") @enable_mimalloc.setter def enable_mimalloc(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enable_mimalloc", value) @property @pulumi.getter(name="existingPsp") def existing_psp(self) -> Optional[pulumi.Input[str]]: """ Use an existing PSP instead of creating one. """ return pulumi.get(self, "existing_psp") @existing_psp.setter def existing_psp(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "existing_psp", value) @property @pulumi.getter(name="extraArgs") def extra_args(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: """ Additional command line arguments to pass to nginx-ingress-controller E.g. to specify the default SSL certificate you can use `default-ssl-certificate: "<namespace>/<secret_name>"`. """ return pulumi.get(self, "extra_args") @extra_args.setter def extra_args(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "extra_args", value) @property @pulumi.getter(name="extraContainers") def extra_containers(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.ContainerArgs']]]]: """ Additional containers to be added to the controller pod. See https://github.com/lemonldap-ng-controller/lemonldap-ng-controller as example. """ return pulumi.get(self, "extra_containers") @extra_containers.setter def extra_containers(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.ContainerArgs']]]]): pulumi.set(self, "extra_containers", value) @property @pulumi.getter(name="extraEnvs") def extra_envs(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.EnvVarArgs']]]]: """ Additional environment variables to set. """ return pulumi.get(self, "extra_envs") @extra_envs.setter def extra_envs(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.EnvVarArgs']]]]): pulumi.set(self, "extra_envs", value) @property @pulumi.getter(name="extraInitContainers") def extra_init_containers(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.ContainerArgs']]]]: """ Containers, which are run before the app containers are started. - name: init-myservice image: busybox command: ['sh', '-c', 'until nslookup myservice; do echo waiting for myservice; sleep 2; done;'] """ return pulumi.get(self, "extra_init_containers") @extra_init_containers.setter def extra_init_containers(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.ContainerArgs']]]]): pulumi.set(self, "extra_init_containers", value) @property @pulumi.getter(name="extraVolumeMounts") def extra_volume_mounts(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeMountArgs']]]]: """ Additional volumeMounts to the controller main container. - name: copy-portal-skins mountPath: /var/lib/lemonldap-ng/portal/skins """ return pulumi.get(self, "extra_volume_mounts") @extra_volume_mounts.setter def extra_volume_mounts(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeMountArgs']]]]): pulumi.set(self, "extra_volume_mounts", value) @property @pulumi.getter(name="extraVolumes") def extra_volumes(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeArgs']]]]: """ Additional volumes to the controller pod. - name: copy-portal-skins emptyDir: {} """ return pulumi.get(self, "extra_volumes") @extra_volumes.setter def extra_volumes(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.VolumeArgs']]]]): pulumi.set(self, "extra_volumes", value) @property @pulumi.getter(name="healthCheckPath") def health_check_path(self) -> Optional[pulumi.Input[str]]: """ Path of the health check endpoint. All requests received on the port defined by the healthz-port parameter are forwarded internally to this path. """ return pulumi.get(self, "health_check_path") @health_check_path.setter def health_check_path(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "health_check_path", value) @property @pulumi.getter(name="heathCheckHost") def heath_check_host(self) -> Optional[pulumi.Input[str]]: """ Address to bind the health check endpoint. It is better to set this option to the internal node address if the ingress nginx controller is running in the hostNetwork: true mode. """ return pulumi.get(self, "heath_check_host") @heath_check_host.setter def heath_check_host(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "heath_check_host", value) @property @pulumi.getter(name="hostNetwork") def host_network(self) -> Optional[pulumi.Input[bool]]: """ Required for use with CNI based kubernetes installations (such as ones set up by kubeadm), since CNI and hostport don't mix yet. Can be deprecated once https://github.com/kubernetes/kubernetes/issues/23920 is merged. """ return pulumi.get(self, "host_network") @host_network.setter def host_network(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "host_network", value) @property @pulumi.getter(name="hostPort") def host_port(self) -> Optional[pulumi.Input['ControllerHostPortArgs']]: """ Use host ports 80 and 443. Disabled by default. """ return pulumi.get(self, "host_port") @host_port.setter def host_port(self, value: Optional[pulumi.Input['ControllerHostPortArgs']]): pulumi.set(self, "host_port", value) @property @pulumi.getter def hostname(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: """ Optionally customize the pod hostname. """ return pulumi.get(self, "hostname") @hostname.setter def hostname(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "hostname", value) @property @pulumi.getter def image(self) -> Optional[pulumi.Input['ControllerImageArgs']]: return pulumi.get(self, "image") @image.setter def image(self, value: Optional[pulumi.Input['ControllerImageArgs']]): pulumi.set(self, "image", value) @property @pulumi.getter(name="ingressClassByName") def ingress_class_by_name(self) -> Optional[pulumi.Input[bool]]: """ Process IngressClass per name (additionally as per spec.controller). """ return pulumi.get(self, "ingress_class_by_name") @ingress_class_by_name.setter def ingress_class_by_name(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "ingress_class_by_name", value) @property @pulumi.getter(name="ingressClassResource") def ingress_class_resource(self) -> Optional[pulumi.Input['ControllerIngressClassResourceArgs']]: """ This section refers to the creation of the IngressClass resource. IngressClass resources are supported since k8s >= 1.18 and required since k8s >= 1.19 """ return pulumi.get(self, "ingress_class_resource") @ingress_class_resource.setter def ingress_class_resource(self, value: Optional[pulumi.Input['ControllerIngressClassResourceArgs']]): pulumi.set(self, "ingress_class_resource", value) @property @pulumi.getter def keda(self) -> Optional[pulumi.Input['KedaArgs']]: """ Mutually exclusive with hpa autoscaling. """ return pulumi.get(self, "keda") @keda.setter def keda(self, value: Optional[pulumi.Input['KedaArgs']]): pulumi.set(self, "keda", value) @property @pulumi.getter def kind(self) -> Optional[pulumi.Input[str]]: """ DaemonSet or Deployment. """ return pulumi.get(self, "kind") @kind.setter def kind(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "kind", value) @property @pulumi.getter def lifecycle(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.LifecycleArgs']]: """ Improve connection draining when ingress controller pod is deleted using a lifecycle hook: With this new hook, we increased the default terminationGracePeriodSeconds from 30 seconds to 300, allowing the draining of connections up to five minutes. If the active connections end before that, the pod will terminate gracefully at that time. To effectively take advantage of this feature, the Configmap feature worker-shutdown-timeout new value is 240s instead of 10s. """ return pulumi.get(self, "lifecycle") @lifecycle.setter def lifecycle(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.LifecycleArgs']]): pulumi.set(self, "lifecycle", value) @property @pulumi.getter(name="livenessProbe") def liveness_probe(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']]: """ Liveness probe values Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes. """ return pulumi.get(self, "liveness_probe") @liveness_probe.setter def liveness_probe(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']]): pulumi.set(self, "liveness_probe", value) @property @pulumi.getter(name="maxmindLicenseKey") def maxmind_license_key(self) -> Optional[pulumi.Input[str]]: """ Maxmind license key to download GeoLite2 Databases https://blog.maxmind.com/2019/12/18/significant-changes-to-accessing-and-using-geolite2-databases. """ return pulumi.get(self, "maxmind_license_key") @maxmind_license_key.setter def maxmind_license_key(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "maxmind_license_key", value) @property @pulumi.getter def metrics(self) -> Optional[pulumi.Input['ControllerMetricsArgs']]: return pulumi.get(self, "metrics") @metrics.setter def metrics(self, value: Optional[pulumi.Input['ControllerMetricsArgs']]): pulumi.set(self, "metrics", value) @property @pulumi.getter(name="minAvailable") def min_available(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "min_available") @min_available.setter def min_available(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "min_available", value) @property @pulumi.getter(name="minReadySeconds") def min_ready_seconds(self) -> Optional[pulumi.Input[int]]: """ minReadySeconds to avoid killing pods before we are ready. """ return pulumi.get(self, "min_ready_seconds") @min_ready_seconds.setter def min_ready_seconds(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "min_ready_seconds", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter(name="nodeSelector") def node_selector(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ Node labels for controller pod assignment Ref: https://kubernetes.io/docs/user-guide/node-selection/. """ return pulumi.get(self, "node_selector") @node_selector.setter def node_selector(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "node_selector", value) @property @pulumi.getter(name="podAnnotations") def pod_annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ Annotations to be added to controller pods. """ return pulumi.get(self, "pod_annotations") @pod_annotations.setter def pod_annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "pod_annotations", value) @property @pulumi.getter(name="podLabels") def pod_labels(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: """ labels to add to the pod container metadata. """ return pulumi.get(self, "pod_labels") @pod_labels.setter def pod_labels(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "pod_labels", value) @property @pulumi.getter(name="podSecurityContext") def pod_security_context(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.PodSecurityContextArgs']]: """ Security Context policies for controller pods. """ return pulumi.get(self, "pod_security_context") @pod_security_context.setter def pod_security_context(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.PodSecurityContextArgs']]): pulumi.set(self, "pod_security_context", value) @property @pulumi.getter(name="priorityClassName") def priority_class_name(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "priority_class_name") @priority_class_name.setter def priority_class_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "priority_class_name", value) @property @pulumi.getter(name="proxySetHeaders") def proxy_set_headers(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: """ Will add custom headers before sending traffic to backends according to https://github.com/kubernetes/ingress-nginx/tree/main/docs/examples/customization/custom-headers. """ return pulumi.get(self, "proxy_set_headers") @proxy_set_headers.setter def proxy_set_headers(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "proxy_set_headers", value) @property @pulumi.getter(name="publishService") def publish_service(self) -> Optional[pulumi.Input['ControllerPublishServiceArgs']]: """ Allows customization of the source of the IP address or FQDN to report in the ingress status field. By default, it reads the information provided by the service. If disable, the status field reports the IP address of the node or nodes where an ingress controller pod is running. """ return pulumi.get(self, "publish_service") @publish_service.setter def publish_service(self, value: Optional[pulumi.Input['ControllerPublishServiceArgs']]): pulumi.set(self, "publish_service", value) @property @pulumi.getter(name="readinessProbe") def readiness_probe(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']]: """ Readiness probe values Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes. """ return pulumi.get(self, "readiness_probe") @readiness_probe.setter def readiness_probe(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']]): pulumi.set(self, "readiness_probe", value) @property @pulumi.getter(name="replicaCount") def replica_count(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "replica_count") @replica_count.setter def replica_count(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "replica_count", value) @property @pulumi.getter(name="reportNodeInternalIp") def report_node_internal_ip(self) -> Optional[pulumi.Input[bool]]: """ Bare-metal considerations via the host network https://kubernetes.github.io/ingress-nginx/deploy/baremetal/#via-the-host-network Ingress status was blank because there is no Service exposing the NGINX Ingress controller in a configuration using the host network, the default --publish-service flag used in standard cloud setups does not apply. """ return pulumi.get(self, "report_node_internal_ip") @report_node_internal_ip.setter def report_node_internal_ip(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "report_node_internal_ip", value) @property @pulumi.getter def resources(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']]: """ Define requests resources to avoid probe issues due to CPU utilization in busy nodes ref: https://github.com/kubernetes/ingress-nginx/issues/4735#issuecomment-551204903 Ideally, there should be no limits. https://engineering.indeedblog.com/blog/2019/12/cpu-throttling-regression-fix/ """ return pulumi.get(self, "resources") @resources.setter def resources(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ResourceRequirementsArgs']]): pulumi.set(self, "resources", value) @property @pulumi.getter def scope(self) -> Optional[pulumi.Input['ControllerScopeArgs']]: """ Limit the scope of the controller. """ return pulumi.get(self, "scope") @scope.setter def scope(self, value: Optional[pulumi.Input['ControllerScopeArgs']]): pulumi.set(self, "scope", value) @property @pulumi.getter def service(self) -> Optional[pulumi.Input['ControllerServiceArgs']]: return pulumi.get(self, "service") @service.setter def service(self, value: Optional[pulumi.Input['ControllerServiceArgs']]): pulumi.set(self, "service", value) @property @pulumi.getter(name="startupProbe") def startup_probe(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']]: """ Startup probe values Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes. """ return pulumi.get(self, "startup_probe") @startup_probe.setter def startup_probe(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.ProbeArgs']]): pulumi.set(self, "startup_probe", value) @property @pulumi.getter def sysctls(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: """ See https://kubernetes.io/docs/tasks/administer-cluster/sysctl-cluster/ for notes on enabling and using sysctls. """ return pulumi.get(self, "sysctls") @sysctls.setter def sysctls(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "sysctls", value) @property @pulumi.getter def tcp(self) -> Optional[pulumi.Input['ControllerTcpArgs']]: """ Allows customization of the tcp-services-configmap. """ return pulumi.get(self, "tcp") @tcp.setter def tcp(self, value: Optional[pulumi.Input['ControllerTcpArgs']]): pulumi.set(self, "tcp", value) @property @pulumi.getter(name="terminateGracePeriodSeconds") def terminate_grace_period_seconds(self) -> Optional[pulumi.Input[int]]: """ How long to wait for the drain of connections. """ return pulumi.get(self, "terminate_grace_period_seconds") @terminate_grace_period_seconds.setter def terminate_grace_period_seconds(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "terminate_grace_period_seconds", value) @property @pulumi.getter def tolerations(self) -> Optional[pulumi.Input['pulumi_kubernetes.core.v1.TolerationArgs']]: """ Node tolerations for server scheduling to nodes with taints Ref: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/. """ return pulumi.get(self, "tolerations") @tolerations.setter def tolerations(self, value: Optional[pulumi.Input['pulumi_kubernetes.core.v1.TolerationArgs']]): pulumi.set(self, "tolerations", value) @property @pulumi.getter(name="topologySpreadConstraints") def topology_spread_constraints(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.TopologySpreadConstraintArgs']]]]: """ Topology spread constraints rely on node labels to identify the topology domain(s) that each Node is in. Ref: https://kubernetes.io/docs/concepts/workloads/pods/pod-topology-spread-constraints/. """ return pulumi.get(self, "topology_spread_constraints") @topology_spread_constraints.setter def topology_spread_constraints(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['pulumi_kubernetes.core.v1.TopologySpreadConstraintArgs']]]]): pulumi.set(self, "topology_spread_constraints", value) @property @pulumi.getter def udp(self) -> Optional[pulumi.Input['ControllerUdpArgs']]: return pulumi.get(self, "udp") @udp.setter def udp(self, value: Optional[pulumi.Input['ControllerUdpArgs']]): pulumi.set(self, "udp", value) @property @pulumi.getter(name="updateStrategy") def update_strategy(self) -> Optional[pulumi.Input['ControllerUpdateStrategyArgs']]: """ The update strategy to apply to the Deployment or DaemonSet. """ return pulumi.get(self, "update_strategy") @update_strategy.setter def update_strategy(self, value: Optional[pulumi.Input['ControllerUpdateStrategyArgs']]): pulumi.set(self, "update_strategy", value) @property @pulumi.getter(name="watchIngressWithoutClass") def watch_ingress_without_class(self) -> Optional[pulumi.Input[bool]]: """ Process Ingress objects without ingressClass annotation/ingressClassName field. Overrides value for --watch-ingress-without-class flag of the controller binary. Defaults to false. """ return pulumi.get(self, "watch_ingress_without_class") @watch_ingress_without_class.setter def watch_ingress_without_class(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "watch_ingress_without_class", value) @pulumi.input_type class KedaScaledObjectArgs: def __init__(__self__, *, annotations: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None): """ :param pulumi.Input[Mapping[str, pulumi.Input[str]]] annotations: Custom annotations for ScaledObject resource. """ if annotations is not None: pulumi.set(__self__, "annotations", annotations) @property @pulumi.getter def annotations(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ Custom annotations for ScaledObject resource. """ return pulumi.get(self, "annotations") @annotations.setter def annotations(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "annotations", value) @pulumi.input_type class KedaTriggerArgs: def __init__(__self__, *, metadata: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]] = None, type: Optional[pulumi.Input[str]] = None): if metadata is not None: pulumi.set(__self__, "metadata", metadata) if type is not None: pulumi.set(__self__, "type", type) @property @pulumi.getter def metadata(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]: return pulumi.get(self, "metadata") @metadata.setter def metadata(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Mapping[str, pulumi.Input[str]]]]]]): pulumi.set(self, "metadata", value) @property @pulumi.getter def type(self) -> Optional[pulumi.Input[str]]: return pulumi.get(self, "type") @type.setter def type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "type", value) @pulumi.input_type class KedaArgs: def __init__(__self__, *, api_version: Optional[pulumi.Input[str]] = None, behavior: Optional[pulumi.Input['AutoscalingBehaviorArgs']] = None, cooldown_period: Optional[pulumi.Input[int]] = None, enabled: Optional[pulumi.Input[bool]] = None, max_replicas: Optional[pulumi.Input[int]] = None, min_replicas: Optional[pulumi.Input[int]] = None, polling_interval: Optional[pulumi.Input[int]] = None, restore_to_original_replica_count: Optional[pulumi.Input[bool]] = None, scaled_object: Optional[pulumi.Input['KedaScaledObjectArgs']] = None, triggers: Optional[pulumi.Input[Sequence[pulumi.Input['KedaTriggerArgs']]]] = None): """ :param pulumi.Input[str] api_version: apiVersion changes with keda 1.x vs 2.x: 2.x = keda.sh/v1alpha1, 1.x = keda.k8s.io/v1alpha1. """ if api_version is not None: pulumi.set(__self__, "api_version", api_version) if behavior is not None: pulumi.set(__self__, "behavior", behavior) if cooldown_period is not None: pulumi.set(__self__, "cooldown_period", cooldown_period) if enabled is not None: pulumi.set(__self__, "enabled", enabled) if max_replicas is not None: pulumi.set(__self__, "max_replicas", max_replicas) if min_replicas is not None: pulumi.set(__self__, "min_replicas", min_replicas) if polling_interval is not None: pulumi.set(__self__, "polling_interval", polling_interval) if restore_to_original_replica_count is not None: pulumi.set(__self__, "restore_to_original_replica_count", restore_to_original_replica_count) if scaled_object is not None: pulumi.set(__self__, "scaled_object", scaled_object) if triggers is not None: pulumi.set(__self__, "triggers", triggers) @property @pulumi.getter(name="apiVersion") def api_version(self) -> Optional[pulumi.Input[str]]: """ apiVersion changes with keda 1.x vs 2.x: 2.x = keda.sh/v1alpha1, 1.x = keda.k8s.io/v1alpha1. """ return pulumi.get(self, "api_version") @api_version.setter def api_version(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "api_version", value) @property @pulumi.getter def behavior(self) -> Optional[pulumi.Input['AutoscalingBehaviorArgs']]: return pulumi.get(self, "behavior") @behavior.setter def behavior(self, value: Optional[pulumi.Input['AutoscalingBehaviorArgs']]): pulumi.set(self, "behavior", value) @property @pulumi.getter(name="cooldownPeriod") def cooldown_period(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "cooldown_period") @cooldown_period.setter def cooldown_period(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "cooldown_period", value) @property @pulumi.getter def enabled(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "enabled") @enabled.setter def enabled(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "enabled", value) @property @pulumi.getter(name="maxReplicas") def max_replicas(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "max_replicas") @max_replicas.setter def max_replicas(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "max_replicas", value) @property @pulumi.getter(name="minReplicas") def min_replicas(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "min_replicas") @min_replicas.setter def min_replicas(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "min_replicas", value) @property @pulumi.getter(name="pollingInterval") def polling_interval(self) -> Optional[pulumi.Input[int]]: return pulumi.get(self, "polling_interval") @polling_interval.setter def polling_interval(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "polling_interval", value) @property @pulumi.getter(name="restoreToOriginalReplicaCount") def restore_to_original_replica_count(self) -> Optional[pulumi.Input[bool]]: return pulumi.get(self, "restore_to_original_replica_count") @restore_to_original_replica_count.setter def restore_to_original_replica_count(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "restore_to_original_replica_count", value) @property @pulumi.getter(name="scaledObject") def scaled_object(self) -> Optional[pulumi.Input['KedaScaledObjectArgs']]: return pulumi.get(self, "scaled_object") @scaled_object.setter def scaled_object(self, value: Optional[pulumi.Input['KedaScaledObjectArgs']]): pulumi.set(self, "scaled_object", value) @property @pulumi.getter def triggers(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['KedaTriggerArgs']]]]: return pulumi.get(self, "triggers") @triggers.setter def triggers(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['KedaTriggerArgs']]]]): pulumi.set(self, "triggers", value) @pulumi.input_type class ReleaseArgs: def __init__(__self__, *, atomic: Optional[pulumi.Input[bool]] = None, chart: Optional[pulumi.Input[str]] = None, cleanup_on_fail: Optional[pulumi.Input[bool]] = None, create_namespace: Optional[pulumi.Input[bool]] = None, dependency_update: Optional[pulumi.Input[bool]] = None, description: Optional[pulumi.Input[str]] = None, devel: Optional[pulumi.Input[bool]] = None, disable_crd_hooks: Optional[pulumi.Input[bool]] = None, disable_openapi_validation: Optional[pulumi.Input[bool]] = None, disable_webhooks: Optional[pulumi.Input[bool]] = None, force_update: Optional[pulumi.Input[bool]] = None, keyring: Optional[pulumi.Input[str]] = None, lint: Optional[pulumi.Input[bool]] = None, manifest: Optional[pulumi.Input[Mapping[str, Any]]] = None, max_history: Optional[pulumi.Input[int]] = None, name: Optional[pulumi.Input[str]] = None, namespace: Optional[pulumi.Input[str]] = None, postrender: Optional[pulumi.Input[str]] = None, recreate_pods: Optional[pulumi.Input[bool]] = None, render_subchart_notes: Optional[pulumi.Input[bool]] = None, replace: Optional[pulumi.Input[bool]] = None, repository_opts: Optional[pulumi.Input['RepositoryOptsArgs']] = None, reset_values: Optional[pulumi.Input[bool]] = None, resource_names: Optional[pulumi.Input[Mapping[str, pulumi.Input[Sequence[pulumi.Input[str]]]]]] = None, reuse_values: Optional[pulumi.Input[bool]] = None, skip_await: Optional[pulumi.Input[bool]] = None, skip_crds: Optional[pulumi.Input[bool]] = None, timeout: Optional[pulumi.Input[int]] = None, value_yaml_files: Optional[pulumi.Input[Sequence[pulumi.Input[Union[pulumi.Asset, pulumi.Archive]]]]] = None, values: Optional[pulumi.Input[Mapping[str, Any]]] = None, verify: Optional[pulumi.Input[bool]] = None, version: Optional[pulumi.Input[str]] = None, wait_for_jobs: Optional[pulumi.Input[bool]] = None): """ A Release is an instance of a chart running in a Kubernetes cluster. A Chart is a Helm package. It contains all of the resource definitions necessary to run an application, tool, or service inside of a Kubernetes cluster. Note - Helm Release is currently in BETA and may change. Use in production environment is discouraged. :param pulumi.Input[bool] atomic: If set, installation process purges chart on fail. `skipAwait` will be disabled automatically if atomic is used. :param pulumi.Input[str] chart: Chart name to be installed. A path may be used. :param pulumi.Input[bool] cleanup_on_fail: Allow deletion of new resources created in this upgrade when upgrade fails. :param pulumi.Input[bool] create_namespace: Create the namespace if it does not exist. :param pulumi.Input[bool] dependency_update: Run helm dependency update before installing the chart. :param pulumi.Input[str] description: Add a custom description :param pulumi.Input[bool] devel: Use chart development versions, too. Equivalent to version '>0.0.0-0'. If `version` is set, this is ignored. :param pulumi.Input[bool] disable_crd_hooks: Prevent CRD hooks from, running, but run other hooks. See helm install --no-crd-hook :param pulumi.Input[bool] disable_openapi_validation: If set, the installation process will not validate rendered templates against the Kubernetes OpenAPI Schema :param pulumi.Input[bool] disable_webhooks: Prevent hooks from running. :param pulumi.Input[bool] force_update: Force resource update through delete/recreate if needed. :param pulumi.Input[str] keyring: Location of public keys used for verification. Used only if `verify` is true :param pulumi.Input[bool] lint: Run helm lint when planning. :param pulumi.Input[Mapping[str, Any]] manifest: The rendered manifests as JSON. Not yet supported. :param pulumi.Input[int] max_history: Limit the maximum number of revisions saved per release. Use 0 for no limit. :param pulumi.Input[str] name: Release name. :param pulumi.Input[str] namespace: Namespace to install the release into. :param pulumi.Input[str] postrender: Postrender command to run. :param pulumi.Input[bool] recreate_pods: Perform pods restart during upgrade/rollback. :param pulumi.Input[bool] render_subchart_notes: If set, render subchart notes along with the parent. :param pulumi.Input[bool] replace: Re-use the given name, even if that name is already used. This is unsafe in production :param pulumi.Input['RepositoryOptsArgs'] repository_opts: Specification defining the Helm chart repository to use. :param pulumi.Input[bool] reset_values: When upgrading, reset the values to the ones built into the chart. :param pulumi.Input[Mapping[str, pulumi.Input[Sequence[pulumi.Input[str]]]]] resource_names: Names of resources created by the release grouped by "kind/version". :param pulumi.Input[bool] reuse_values: When upgrading, reuse the last release's values and merge in any overrides. If 'resetValues' is specified, this is ignored :param pulumi.Input[bool] skip_await: By default, the provider waits until all resources are in a ready state before marking the release as successful. Setting this to true will skip such await logic. :param pulumi.Input[bool] skip_crds: If set, no CRDs will be installed. By default, CRDs are installed if not already present. :param pulumi.Input[int] timeout: Time in seconds to wait for any individual kubernetes operation. :param pulumi.Input[Sequence[pulumi.Input[Union[pulumi.Asset, pulumi.Archive]]]] value_yaml_files: List of assets (raw yaml files). Content is read and merged with values. Not yet supported. :param pulumi.Input[Mapping[str, Any]] values: Custom values set for the release. :param pulumi.Input[bool] verify: Verify the package before installing it. :param pulumi.Input[str] version: Specify the exact chart version to install. If this is not specified, the latest version is installed. :param pulumi.Input[bool] wait_for_jobs: Will wait until all Jobs have been completed before marking the release as successful. This is ignored if `skipAwait` is enabled. """ if atomic is not None: pulumi.set(__self__, "atomic", atomic) if chart is not None: pulumi.set(__self__, "chart", chart) if cleanup_on_fail is not None: pulumi.set(__self__, "cleanup_on_fail", cleanup_on_fail) if create_namespace is not None: pulumi.set(__self__, "create_namespace", create_namespace) if dependency_update is not None: pulumi.set(__self__, "dependency_update", dependency_update) if description is not None: pulumi.set(__self__, "description", description) if devel is not None: pulumi.set(__self__, "devel", devel) if disable_crd_hooks is not None: pulumi.set(__self__, "disable_crd_hooks", disable_crd_hooks) if disable_openapi_validation is not None: pulumi.set(__self__, "disable_openapi_validation", disable_openapi_validation) if disable_webhooks is not None: pulumi.set(__self__, "disable_webhooks", disable_webhooks) if force_update is not None: pulumi.set(__self__, "force_update", force_update) if keyring is not None: pulumi.set(__self__, "keyring", keyring) if lint is not None: pulumi.set(__self__, "lint", lint) if manifest is not None: pulumi.set(__self__, "manifest", manifest) if max_history is not None: pulumi.set(__self__, "max_history", max_history) if name is not None: pulumi.set(__self__, "name", name) if namespace is not None: pulumi.set(__self__, "namespace", namespace) if postrender is not None: pulumi.set(__self__, "postrender", postrender) if recreate_pods is not None: pulumi.set(__self__, "recreate_pods", recreate_pods) if render_subchart_notes is not None: pulumi.set(__self__, "render_subchart_notes", render_subchart_notes) if replace is not None: pulumi.set(__self__, "replace", replace) if repository_opts is not None: pulumi.set(__self__, "repository_opts", repository_opts) if reset_values is not None: pulumi.set(__self__, "reset_values", reset_values) if resource_names is not None: pulumi.set(__self__, "resource_names", resource_names) if reuse_values is not None: pulumi.set(__self__, "reuse_values", reuse_values) if skip_await is not None: pulumi.set(__self__, "skip_await", skip_await) if skip_crds is not None: pulumi.set(__self__, "skip_crds", skip_crds) if timeout is not None: pulumi.set(__self__, "timeout", timeout) if value_yaml_files is not None: pulumi.set(__self__, "value_yaml_files", value_yaml_files) if values is not None: pulumi.set(__self__, "values", values) if verify is not None: pulumi.set(__self__, "verify", verify) if version is not None: pulumi.set(__self__, "version", version) if wait_for_jobs is not None: pulumi.set(__self__, "wait_for_jobs", wait_for_jobs) @property @pulumi.getter def atomic(self) -> Optional[pulumi.Input[bool]]: """ If set, installation process purges chart on fail. `skipAwait` will be disabled automatically if atomic is used. """ return pulumi.get(self, "atomic") @atomic.setter def atomic(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "atomic", value) @property @pulumi.getter def chart(self) -> Optional[pulumi.Input[str]]: """ Chart name to be installed. A path may be used. """ return pulumi.get(self, "chart") @chart.setter def chart(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "chart", value) @property @pulumi.getter(name="cleanupOnFail") def cleanup_on_fail(self) -> Optional[pulumi.Input[bool]]: """ Allow deletion of new resources created in this upgrade when upgrade fails. """ return pulumi.get(self, "cleanup_on_fail") @cleanup_on_fail.setter def cleanup_on_fail(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "cleanup_on_fail", value) @property @pulumi.getter(name="createNamespace") def create_namespace(self) -> Optional[pulumi.Input[bool]]: """ Create the namespace if it does not exist. """ return pulumi.get(self, "create_namespace") @create_namespace.setter def create_namespace(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "create_namespace", value) @property @pulumi.getter(name="dependencyUpdate") def dependency_update(self) -> Optional[pulumi.Input[bool]]: """ Run helm dependency update before installing the chart. """ return pulumi.get(self, "dependency_update") @dependency_update.setter def dependency_update(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "dependency_update", value) @property @pulumi.getter def description(self) -> Optional[pulumi.Input[str]]: """ Add a custom description """ return pulumi.get(self, "description") @description.setter def description(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "description", value) @property @pulumi.getter def devel(self) -> Optional[pulumi.Input[bool]]: """ Use chart development versions, too. Equivalent to version '>0.0.0-0'. If `version` is set, this is ignored. """ return pulumi.get(self, "devel") @devel.setter def devel(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "devel", value) @property @pulumi.getter(name="disableCRDHooks") def disable_crd_hooks(self) -> Optional[pulumi.Input[bool]]: """ Prevent CRD hooks from, running, but run other hooks. See helm install --no-crd-hook """ return pulumi.get(self, "disable_crd_hooks") @disable_crd_hooks.setter def disable_crd_hooks(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "disable_crd_hooks", value) @property @pulumi.getter(name="disableOpenapiValidation") def disable_openapi_validation(self) -> Optional[pulumi.Input[bool]]: """ If set, the installation process will not validate rendered templates against the Kubernetes OpenAPI Schema """ return pulumi.get(self, "disable_openapi_validation") @disable_openapi_validation.setter def disable_openapi_validation(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "disable_openapi_validation", value) @property @pulumi.getter(name="disableWebhooks") def disable_webhooks(self) -> Optional[pulumi.Input[bool]]: """ Prevent hooks from running. """ return pulumi.get(self, "disable_webhooks") @disable_webhooks.setter def disable_webhooks(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "disable_webhooks", value) @property @pulumi.getter(name="forceUpdate") def force_update(self) -> Optional[pulumi.Input[bool]]: """ Force resource update through delete/recreate if needed. """ return pulumi.get(self, "force_update") @force_update.setter def force_update(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "force_update", value) @property @pulumi.getter def keyring(self) -> Optional[pulumi.Input[str]]: """ Location of public keys used for verification. Used only if `verify` is true """ return pulumi.get(self, "keyring") @keyring.setter def keyring(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "keyring", value) @property @pulumi.getter def lint(self) -> Optional[pulumi.Input[bool]]: """ Run helm lint when planning. """ return pulumi.get(self, "lint") @lint.setter def lint(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "lint", value) @property @pulumi.getter def manifest(self) -> Optional[pulumi.Input[Mapping[str, Any]]]: """ The rendered manifests as JSON. Not yet supported. """ return pulumi.get(self, "manifest") @manifest.setter def manifest(self, value: Optional[pulumi.Input[Mapping[str, Any]]]): pulumi.set(self, "manifest", value) @property @pulumi.getter(name="maxHistory") def max_history(self) -> Optional[pulumi.Input[int]]: """ Limit the maximum number of revisions saved per release. Use 0 for no limit. """ return pulumi.get(self, "max_history") @max_history.setter def max_history(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "max_history", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ Release name. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter def namespace(self) -> Optional[pulumi.Input[str]]: """ Namespace to install the release into. """ return pulumi.get(self, "namespace") @namespace.setter def namespace(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "namespace", value) @property @pulumi.getter def postrender(self) -> Optional[pulumi.Input[str]]: """ Postrender command to run. """ return pulumi.get(self, "postrender") @postrender.setter def postrender(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "postrender", value) @property @pulumi.getter(name="recreatePods") def recreate_pods(self) -> Optional[pulumi.Input[bool]]: """ Perform pods restart during upgrade/rollback. """ return pulumi.get(self, "recreate_pods") @recreate_pods.setter def recreate_pods(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "recreate_pods", value) @property @pulumi.getter(name="renderSubchartNotes") def render_subchart_notes(self) -> Optional[pulumi.Input[bool]]: """ If set, render subchart notes along with the parent. """ return pulumi.get(self, "render_subchart_notes") @render_subchart_notes.setter def render_subchart_notes(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "render_subchart_notes", value) @property @pulumi.getter def replace(self) -> Optional[pulumi.Input[bool]]: """ Re-use the given name, even if that name is already used. This is unsafe in production """ return pulumi.get(self, "replace") @replace.setter def replace(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "replace", value) @property @pulumi.getter(name="repositoryOpts") def repository_opts(self) -> Optional[pulumi.Input['RepositoryOptsArgs']]: """ Specification defining the Helm chart repository to use. """ return pulumi.get(self, "repository_opts") @repository_opts.setter def repository_opts(self, value: Optional[pulumi.Input['RepositoryOptsArgs']]): pulumi.set(self, "repository_opts", value) @property @pulumi.getter(name="resetValues") def reset_values(self) -> Optional[pulumi.Input[bool]]: """ When upgrading, reset the values to the ones built into the chart. """ return pulumi.get(self, "reset_values") @reset_values.setter def reset_values(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "reset_values", value) @property @pulumi.getter(name="resourceNames") def resource_names(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[Sequence[pulumi.Input[str]]]]]]: """ Names of resources created by the release grouped by "kind/version". """ return pulumi.get(self, "resource_names") @resource_names.setter def resource_names(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[Sequence[pulumi.Input[str]]]]]]): pulumi.set(self, "resource_names", value) @property @pulumi.getter(name="reuseValues") def reuse_values(self) -> Optional[pulumi.Input[bool]]: """ When upgrading, reuse the last release's values and merge in any overrides. If 'resetValues' is specified, this is ignored """ return pulumi.get(self, "reuse_values") @reuse_values.setter def reuse_values(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "reuse_values", value) @property @pulumi.getter(name="skipAwait") def skip_await(self) -> Optional[pulumi.Input[bool]]: """ By default, the provider waits until all resources are in a ready state before marking the release as successful. Setting this to true will skip such await logic. """ return pulumi.get(self, "skip_await") @skip_await.setter def skip_await(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "skip_await", value) @property @pulumi.getter(name="skipCrds") def skip_crds(self) -> Optional[pulumi.Input[bool]]: """ If set, no CRDs will be installed. By default, CRDs are installed if not already present. """ return pulumi.get(self, "skip_crds") @skip_crds.setter def skip_crds(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "skip_crds", value) @property @pulumi.getter def timeout(self) -> Optional[pulumi.Input[int]]: """ Time in seconds to wait for any individual kubernetes operation. """ return pulumi.get(self, "timeout") @timeout.setter def timeout(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "timeout", value) @property @pulumi.getter(name="valueYamlFiles") def value_yaml_files(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[Union[pulumi.Asset, pulumi.Archive]]]]]: """ List of assets (raw yaml files). Content is read and merged with values. Not yet supported. """ return pulumi.get(self, "value_yaml_files") @value_yaml_files.setter def value_yaml_files(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[Union[pulumi.Asset, pulumi.Archive]]]]]): pulumi.set(self, "value_yaml_files", value) @property @pulumi.getter def values(self) -> Optional[pulumi.Input[Mapping[str, Any]]]: """ Custom values set for the release. """ return pulumi.get(self, "values") @values.setter def values(self, value: Optional[pulumi.Input[Mapping[str, Any]]]): pulumi.set(self, "values", value) @property @pulumi.getter def verify(self) -> Optional[pulumi.Input[bool]]: """ Verify the package before installing it. """ return pulumi.get(self, "verify") @verify.setter def verify(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "verify", value) @property @pulumi.getter def version(self) -> Optional[pulumi.Input[str]]: """ Specify the exact chart version to install. If this is not specified, the latest version is installed. """ return pulumi.get(self, "version") @version.setter def version(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "version", value) @property @pulumi.getter(name="waitForJobs") def wait_for_jobs(self) -> Optional[pulumi.Input[bool]]: """ Will wait until all Jobs have been completed before marking the release as successful. This is ignored if `skipAwait` is enabled. """ return pulumi.get(self, "wait_for_jobs") @wait_for_jobs.setter def wait_for_jobs(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "wait_for_jobs", value) @pulumi.input_type class RepositoryOptsArgs: def __init__(__self__, *, ca_file: Optional[pulumi.Input[str]] = None, cert_file: Optional[pulumi.Input[str]] = None, key_file: Optional[pulumi.Input[str]] = None, password: Optional[pulumi.Input[str]] = None, repo: Optional[pulumi.Input[str]] = None, username: Optional[pulumi.Input[str]] = None): """ Specification defining the Helm chart repository to use. :param pulumi.Input[str] ca_file: The Repository's CA File :param pulumi.Input[str] cert_file: The repository's cert file :param pulumi.Input[str] key_file: The repository's cert key file :param pulumi.Input[str] password: Password for HTTP basic authentication :param pulumi.Input[str] repo: Repository where to locate the requested chart. If is a URL the chart is installed without installing the repository. :param pulumi.Input[str] username: Username for HTTP basic authentication """ if ca_file is not None: pulumi.set(__self__, "ca_file", ca_file) if cert_file is not None: pulumi.set(__self__, "cert_file", cert_file) if key_file is not None: pulumi.set(__self__, "key_file", key_file) if password is not None: pulumi.set(__self__, "password", password) if repo is not None: pulumi.set(__self__, "repo", repo) if username is not None: pulumi.set(__self__, "username", username) @property @pulumi.getter(name="caFile") def ca_file(self) -> Optional[pulumi.Input[str]]: """ The Repository's CA File """ return pulumi.get(self, "ca_file") @ca_file.setter def ca_file(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "ca_file", value) @property @pulumi.getter(name="certFile") def cert_file(self) -> Optional[pulumi.Input[str]]: """ The repository's cert file """ return pulumi.get(self, "cert_file") @cert_file.setter def cert_file(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "cert_file", value) @property @pulumi.getter(name="keyFile") def key_file(self) -> Optional[pulumi.Input[str]]: """ The repository's cert key file """ return pulumi.get(self, "key_file") @key_file.setter def key_file(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "key_file", value) @property @pulumi.getter def password(self) -> Optional[pulumi.Input[str]]: """ Password for HTTP basic authentication """ return pulumi.get(self, "password") @password.setter def password(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "password", value) @property @pulumi.getter def repo(self) -> Optional[pulumi.Input[str]]: """ Repository where to locate the requested chart. If is a URL the chart is installed without installing the repository. """ return pulumi.get(self, "repo") @repo.setter def repo(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "repo", value) @property @pulumi.getter def username(self) -> Optional[pulumi.Input[str]]: """ Username for HTTP basic authentication """ return pulumi.get(self, "username") @username.setter def username(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "username", value)

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546

0.675118

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191,137

5.554115

0.038666

0.120276

0.132577

0.056397

0.85927

0.769463

0.72531

0.675882

0.660416

0.617806

0

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0.205784

191,137

4,292

547

44.533318

0.822488

0.170511

0

0.5589

1

0

0.133228

0.061564

0

1

0.202265

false

0.002589

0.001942

0.054693

0.312298

0

null

0

1

0

1

0

1

0

null

0

1

0

6

2cadc79c172c8eae5ebb8268a4fce6df032492ff

35

py

Python

RESTfacebook/__init__.py

JoeyDP/REST-Facebook

6035f9d66e98020eb601b437bd5f559eccd37c17

[ "MIT" ]

null

RESTfacebook/__init__.py

JoeyDP/REST-Facebook

6035f9d66e98020eb601b437bd5f559eccd37c17

[ "MIT" ]

null

RESTfacebook/__init__.py

JoeyDP/REST-Facebook

6035f9d66e98020eb601b437bd5f559eccd37c17

[ "MIT" ]

null

from .facebook import FacebookAPI

11.666667

33

0.828571

4

35

7.25

1

0

0.142857

35

2

34

17.5

0.966667

0

1

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true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

e2ec198a4d03cfb5ee8bf6c201a6c08ed4395cd3

20,930

py

Python

qark/modules/findBroadcasts.py

pragyan1994/Jenkins_Integration

747382d5c6d5cd835d0c7c3324956e8e352876ac

[ "Apache-2.0" ]

1

2017-12-02T21:34:26.000Z

qark/modules/findBroadcasts.py

pragyan1994/Jenkins_Integration

747382d5c6d5cd835d0c7c3324956e8e352876ac

[ "Apache-2.0" ]

null

qark/modules/findBroadcasts.py

pragyan1994/Jenkins_Integration

747382d5c6d5cd835d0c7c3324956e8e352876ac

[ "Apache-2.0" ]

1

2018-05-12T16:01:58.000Z

from __future__ import absolute_import '''Copyright 2015 LinkedIn Corp. 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.''' import re import logging import lib.plyj.model as m import lib.plyj.parser as plyj from modules import common from modules import report from modules.report import ReportIssue from modules.common import Severity, ReportIssue from modules.createExploit import ExploitType from lib.pubsub import pub from modules.common import terminalPrint common.logger = logging.getLogger() logger = logging.getLogger(__name__) parser = plyj.Parser() current_file='' tree='' importFound='False' def main(queue): global current_file global parser global tree results = [] count = 0 common.logger.debug("Checking for any broadcasts sent from this app......") for j in common.java_files: count = count + 1 pub.sendMessage('progress', bar="Broadcast issues", percent=round(count*100/common.java_files.__len__())) current_file=j try: tree=parser.parse_file(j) if type(tree) is not None: if hasattr(tree,'type_declarations'): for type_decl in tree.type_declarations: if type(type_decl) is m.ClassDeclaration: for t in type_decl.body: try: recursive_broadcast_finder(t,results) except Exception as e: common.parsingerrors.add(str(j)) common.logger.debug("Unable to process recursive_broadcast_finder in findBroadcasts.py: " + str(e)) elif type(type_decl) is list: for y in type_decl: recursive_broadcast_finder(y,results) elif hasattr(type_decl,'_fields'): for d in type_decl._fields: recursive_broadcast_finder(getattr(type_decl,d),results) else: common.logger.debug("Unable to create tree for " + str(j)) except Exception as e: common.logger.debug("Tree exception during broadcast processing: " + str(e)) common.parsingerrors.add(str(j)) queue.put(results) return def local_broadcast_manager_imported(): ''' Need to ensure sendBroadcast is not the method from LocalBroadcastManager, which is not insecure ''' #To be thorough,we need to run through the whole import dance, but we'll save that for planned refactor #This will have to do for now global tree global importFound for imp_decl in tree.import_declarations: if str(imp_decl.name.value)=="android.support.v4.content.LocalBroadcastManager": importFound=True elif str(imp_decl.name.value)=="android.support.v4.content.*": importFound=True elif str(imp_decl.name.value)=="android.support.v4.*": importFound=True elif str(imp_decl.name.value)=="android.support.*": importFound=True elif str(imp_decl.name.value)=="android.*": importFound=True return importFound def recursive_broadcast_finder(t,results): if type(t) is m.MethodDeclaration: if str(t.name) == 'sendBroadcast': common.logger.debug("It appears the sendBroadcast method may be overridden in this class. The following findings for this class may be false positives") if str(t.name) == 'sendBroadcastAsUser': common.logger.debug("It appears the sendBroadcastAsUser method may be overridden in this class. The following findings for this class may be false positives") if str(t.name) == 'sendOrderedBroadcast': common.logger.debug("It appears the sendOrderedBroadcast method may be overridden in this class. The following findings for this class may be false positives") if str(t.name) == 'sendOrderedBroadcastAsUser': common.logger.debug("It appears the sendOrderedBroadcastAsUser method may be overridden in this class. The following findings for this class may be false positives") if str(t.name) == 'sendStickyBroadcast': common.logger.debug("It appears the sendStickyBroadcast method may be overridden in this class. The following findings for this class may be false positives") if str(t.name) == 'sendStickyBroadcastAsUser': common.logger.debug("It appears the sendStickyBroadcastAsUser method may be overridden in this class. The following findings for this class may be false positives") if str(t.name) == 'sendStickyOrderedBroadcast': common.logger.debug("It appears the sendStickyOrderedBroadcast method may be overridden in this class. The following findings for this class may be false positives") if str(t.name) == 'sendStickyOrderedBroadcastAsUser': common.logger.debug("It appears the sendStickyOrderedBroadcastAsUser method may be overridden in this class. The following findings for this class may be false positives") if type(t) is m.MethodInvocation: if str(t.name) == 'sendBroadcast': if len(t.arguments)==1: #We need to ensure this isn't a local broadcast #TODO - There is a lot more we need to do to fully qualify this, but should be good enough for now if local_broadcast_manager_imported()==True: common.logger.debug(tree) else: report.write_badger("manifest-issues", modules.common.Severity.INFO, "NO IMPORT") common.logger.debug("FOUND A sendBroadcast") issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("A broadcast is sent from this class: " + str(current_file) + ", which does not specify the receiverPermission. This means any application on the device can receive this broadcast. You should investigate this for potential data leakage.") issue.setFile(str(current_file)) issue.setSeverity(Severity.WARNING) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.WARNING) issue.setData("A broadcast is sent from this class: " + str(current_file) + ", which does not specify the receiverPermission. This means any application on the device can receive this broadcast. You should investigate this for potential data leakage.") results.append(issue) elif len(t.arguments)==2: if common.minSdkVersion<21: issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("A broadcast is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but may still be vulnerable to interception, due to the permission squatting vulnerability in API levels before 21. This means any application, installed prior to the expected receiver(s) on the device can potentially receive this broadcast. You should investigate this for potential data leakage.") issue.setFile(str(current_file)) issue.setSeverity(Severity.WARNING) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.WARNING) issue.setData("A broadcast is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but may still be vulnerable to interception, due to the permission squatting vulnerability in API levels before 21. This means any application, installed prior to the expected receiver(s) on the device can potentially receive this broadcast. You should investigate this for potential data leakage.") results.append(issue) else: issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("A broadcast is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but depending on the protection level of the permission (on the receiving app side), may still be vulnerable to interception, if the protection level of the permission is not set to signature or signatureOrSystem. You should investigate this for potential data leakage.") issue.setFile(str(current_file)) issue.setSeverity(Severity.WARNING) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.WARNING) issue.setData("A broadcast is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but depending on the protection level of the permission (on the receiving app side), may still be vulnerable to interception, if the protection level of the permission is not set to signature or signatureOrSystem. You should investigate this for potential data leakage.") results.append(issue) elif str(t.name) == 'sendBroadcastAsUser': if len(t.arguments)==2: issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("A broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which does not specify the receiverPermission. This means any application on the device can receive this broadcast. You should investigate this for potential data leakage.") issue.setFile(str(current_file)) issue.setSeverity(Severity.WARNING) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.WARNING) issue.setData("A broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which does not specify the receiverPermission. This means any application on the device can receive this broadcast. You should investigate this for potential data leakage.") results.append(issue) elif len(t.arguments)==3: if common.minSdkVersion<21: issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("A broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but may still be vulnerable to interception, due to the permission squatting vulnerability in API levels before 21. This means any application, installed prior to the expected receiver(s) on the device can potentially receive this broadcast. You should investigate this for potential data leakage.") issue.setFile(str(current_file)) issue.setSeverity(Severity.WARNING) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.WARNING) issue.setData("A broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but may still be vulnerable to interception, due to the permission squatting vulnerability in API levels before 21. This means any application, installed prior to the expected receiver(s) on the device can potentially receive this broadcast. You should investigate this for potential data leakage.") results.append(issue) else: issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("A broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but depending on the protection level of the permission (on the receiving app side), may still be vulnerable to interception, if the protection level of the permission is not set to signature or signatureOrSystem. You should investigate this for potential data leakage.") issue.setFile(str(current_file)) issue.setSeverity(Severity.WARNING) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.WARNING) issue.setData("A broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but depending on the protection level of the permission (on the receiving app side), may still be vulnerable to interception, if the protection level of the permission is not set to signature or signatureOrSystem. You should investigate this for potential data leakage.") results.append(issue) elif str(t.name) == 'sendOrderedBroadcast': if ((len(t.arguments)==2) or (len(t.arguments)==7)): if common.minSdkVersion<21: issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("An ordered broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but may still be vulnerable to interception, due to the permission squatting vulnerability in API levels before 21. This means any application, installed prior to the expected receiver(s) on the device can potentially receive this broadcast. You should investigate this for potential data leakage.") issue.setFile(str(current_file)) issue.setSeverity(Severity.WARNING) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.WARNING) issue.setData("An ordered broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but may still be vulnerable to interception, due to the permission squatting vulnerability in API levels before 21. This means any application, installed prior to the expected receiver(s) on the device can potentially receive this broadcast. You should investigate this for potential data leakage.") results.append(issue) else: issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("An ordered broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but may still be vulnerable to interception, due to the permission squatting vulnerability in API levels before 21. This means any application, installed prior to the expected receiver(s) on the device can potentially receive this broadcast. You should investigate this for potential data leakage.") issue.setFile(str(current_file)) issue.setSeverity(Severity.WARNING) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.WARNING) issue.setData("An ordered broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but may still be vulnerable to interception, due to the permission squatting vulnerability in API levels before 21. This means any application, installed prior to the expected receiver(s) on the device can potentially receive this broadcast. You should investigate this for potential data leakage.") results.append(issue) elif str(t.name) == 'sendOrderedBroadcastAsUser': if len(t.arguments)==7: if common.minSdkVersion<21: issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("An ordered broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but may still be vulnerable to interception, due to the permission squatting vulnerability in API levels before 21. This means any application, installed prior to the expected receiver(s) on the device can potentially receive this broadcast. You should investigate this for potential data leakage.") issue.setFile(str(current_file)) issue.setSeverity(Severity.WARNING) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.WARNING) issue.setData("An ordered broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but may still be vulnerable to interception, due to the permission squatting vulnerability in API levels before 21. This means any application, installed prior to the expected receiver(s) on the device can potentially receive this broadcast. You should investigate this for potential data leakage.") results.append(issue) else: issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("An ordered broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but depending on the protection level of the permission (on the receiving app side), may still be vulnerable to interception, if the protection level of the permission is not set to signature or signatureOrSystem. You should investigate this for potential data leakage.") issue.setFile(str(current_file)) issue.setSeverity(Severity.WARNING) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.WARNING) issue.setData("An ordered broadcast, as a specific user, is sent from this class: " + str(current_file) + ", which specifies the receiverPermission, but depending on the protection level of the permission (on the receiving app side), may still be vulnerable to interception, if the protection level of the permission is not set to signature or signatureOrSystem. You should investigate this for potential data leakage.") results.append(issue) elif str(t.name) == 'sendStickyBroadcast': issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("A sticky broadcast is sent from this class: " + str(current_file) + ". These should not be used, as they provide no security (anyone can access them), no protection (anyone can modify them), and many other problems. For more info: http://developer.android.com/reference/android/content/Context.html") issue.setFile(str(current_file)) issue.setSeverity(Severity.VULNERABILITY) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.VULNERABILITY) issue.setData("A sticky broadcast is sent from this class: " + str(current_file) + ". These should not be used, as they provide no security (anyone can access them), no protection (anyone can modify them), and many other problems. For more info: http://developer.android.com/reference/android/content/Context.html") results.append(issue) elif str(t.name) == 'sendStickyBroadcastAsUser': issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("A sticky user broadcast is sent from this class: " + str(current_file) + ". These should not be used, as they provide no security (anyone can access them), no protection (anyone can modify them), and many other problems. For more info: http://developer.android.com/reference/android/content/Context.html") issue.setFile(str(current_file)) issue.setSeverity(Severity.VULNERABILITY) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.VULNERABILITY) issue.setData("A sticky user broadcast is sent from this class: " + str(current_file) + ". These should not be used, as they provide no security (anyone can access them), no protection (anyone can modify them), and many other problems. For more info: http://developer.android.com/reference/android/content/Context.html") results.append(issue) elif str(t.name) == 'sendStickyOrderedBroadcast': issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("A sticky ordered broadcast is sent from this class: " + str(current_file) + ". These should not be used, as they provide no security (anyone can access them), no protection (anyone can modify them), and many other problems. For more info: http://developer.android.com/reference/android/content/Context.html") issue.setFile(str(current_file)) issue.setSeverity(Severity.VULNERABILITY) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.VULNERABILITY) issue.setData("A sticky ordered broadcast is sent from this class: " + str(current_file) + ". These should not be used, as they provide no security (anyone can access them), no protection (anyone can modify them), and many other problems. For more info: http://developer.android.com/reference/android/content/Context.html") results.append(issue) elif str(t.name) == 'sendStickyOrderedBroadcastAsUser': issue = ReportIssue() issue.setCategory(ExploitType.BROADCAST_INTENT) issue.setDetails("A sticky ordered user broadcast is sent from this class: " + str(current_file) + ". These should not be used, as they provide no security (anyone can access them), no protection (anyone can modify them), and many other problems. For more info: http://developer.android.com/reference/android/content/Context.html") issue.setFile(str(current_file)) issue.setSeverity(Severity.VULNERABILITY) results.append(issue) issue = terminalPrint() issue.setLevel(Severity.VULNERABILITY) issue.setData("A sticky ordered user broadcast is sent from this class: " + str(current_file) + ". These should not be used, as they provide no security (anyone can access them), no protection (anyone can modify them), and many other problems. For more info: http://developer.android.com/reference/android/content/Context.html") results.append(issue) elif hasattr(t,'_fields'): for g in t._fields: recursive_broadcast_finder(getattr(t,g),results) elif type(t) is list: for l in t: recursive_broadcast_finder(l,results) elif hasattr(t,'_fields'): for f in t._fields: if type(getattr(t,f)) is not str: recursive_broadcast_finder(getattr(t,f),results) return

68.175896

456

0.760965

2,867

20,930

5.51308

0.099407

0.031317

0.037201

0.024801

0.826901

0.801847

0.783753

0.777806

0

0.002893

0.157668

20,930

306

457

68.398693

0.893647

0.017678

0

0.552632

0

0.135338

0.556518

0.021353

0

0.003268

0

1

0.011278

false

0

0.090226

0

0.112782

0

null

0

1

0

null

0

6

393b5692033aa5a50648f05a403cf56b3d6666cc

9,522

py

Python

tests/model/test_stochastic.py

ycguo028/zhusuan

244536d93c55e486a3587e53229f0a7e1b19bef0

[ "MIT" ]

4

2017-05-23T20:18:41.000Z

2020-03-03T15:00:53.000Z

tests/model/test_stochastic.py

ycguo028/zhusuan

244536d93c55e486a3587e53229f0a7e1b19bef0

[ "MIT" ]

null

tests/model/test_stochastic.py

ycguo028/zhusuan

244536d93c55e486a3587e53229f0a7e1b19bef0

[ "MIT" ]

2

2018-11-27T02:43:22.000Z

2019-11-23T18:27:32.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- from __future__ import absolute_import from __future__ import print_function from __future__ import division import numpy as np import tensorflow as tf from zhusuan.model.stochastic import * from zhusuan.model.base import BayesianNet from zhusuan.model.utils import get_backward_ops class TestNormal(tf.test.TestCase): def test_Normal(self): with BayesianNet(): mean = tf.zeros([2, 3]) logstd = tf.zeros([2, 3]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = Normal('a', mean, logstd, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [mean, logstd, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.ones([2, 3])) log_p_ops = set(get_backward_ops(log_p)) for i in [mean, logstd, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestBernoulli(tf.test.TestCase): def test_Bernoulli(self): with BayesianNet(): logits = tf.zeros([2, 3]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = Bernoulli('a', logits, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [logits, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.ones([2, 3])) log_p_ops = set(get_backward_ops(log_p)) for i in [logits, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestCategorical(tf.test.TestCase): def test_Discrete(self): with BayesianNet(): logits = tf.zeros([2, 3]) n_samples = tf.placeholder(tf.int32, shape=()) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = Categorical('a', logits, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [logits, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.array([0, 1])) log_p_ops = set(get_backward_ops(log_p)) for i in [logits, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestUniform(tf.test.TestCase): def test_Uniform(self): with BayesianNet(): minval = tf.zeros([2, 3]) maxval = tf.ones([2, 3]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = Uniform('a', minval, maxval, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [minval, maxval, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.zeros([2, 3])) log_p_ops = set(get_backward_ops(log_p)) for i in [minval, maxval, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestGamma(tf.test.TestCase): def test_Gamma(self): with BayesianNet(): alpha = tf.ones([2, 3]) beta = tf.ones([2, 3]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = Gamma('a', alpha, beta, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [alpha, beta, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.ones([2, 3])) log_p_ops = set(get_backward_ops(log_p)) for i in [alpha, beta, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestBeta(tf.test.TestCase): def test_Beta(self): with BayesianNet(): alpha = tf.ones([2, 3]) beta = tf.ones([2, 3]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = Beta('a', alpha, beta, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [alpha, beta, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.ones([2, 3]) * 0.5) log_p_ops = set(get_backward_ops(log_p)) for i in [alpha, beta, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestPoisson(tf.test.TestCase): def test_Poisson(self): with BayesianNet(): rate = tf.ones([2, 3]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = Poisson('a', rate, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [rate, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.ones([2, 3], dtype=np.int32)) log_p_ops = set(get_backward_ops(log_p)) for i in [rate, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestBinomial(tf.test.TestCase): def test_Binomial(self): with BayesianNet(): logits = tf.zeros([2, 3]) n_experiments = tf.placeholder(tf.int32, shape=[]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = Binomial('a', logits, n_experiments, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [logits, n_experiments, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.ones([2, 3], dtype=np.int32)) log_p_ops = set(get_backward_ops(log_p)) for i in [logits, n_experiments, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestMultinomial(tf.test.TestCase): def test_Multinomial(self): with BayesianNet(): logits = tf.ones([2, 3]) n_experiments = tf.placeholder(tf.int32, shape=[]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = Multinomial('a', logits, n_experiments, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [logits, n_experiments, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.ones([2, 3], dtype=np.int32)) log_p_ops = set(get_backward_ops(log_p)) for i in [logits, n_experiments, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestOnehotCategorical(tf.test.TestCase): def test_OnehotCategorical(self): with BayesianNet(): logits = tf.ones([2, 3]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = OnehotCategorical('a', logits, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [logits, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(tf.one_hot([0, 2], 3, dtype=tf.int32)) log_p_ops = set(get_backward_ops(log_p)) for i in [logits, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestDirichlet(tf.test.TestCase): def test_Dirichlet(self): with BayesianNet(): alpha = tf.ones([2, 3]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = Dirichlet('a', alpha, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [alpha, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.array([[0.2, 0.3, 0.5], [0.1, 0.7, 0.2]])) log_p_ops = set(get_backward_ops(log_p)) for i in [alpha, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestInverseGamma(tf.test.TestCase): def test_InverseGamma(self): with BayesianNet(): alpha = tf.ones([2, 3]) beta = tf.ones([2, 3]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = InverseGamma('a', alpha, beta, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [alpha, beta, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.ones([2, 3])) log_p_ops = set(get_backward_ops(log_p)) for i in [alpha, beta, group_event_ndims]: self.assertTrue(i.op in log_p_ops) class TestLaplace(tf.test.TestCase): def test_Laplace(self): with BayesianNet(): loc = tf.zeros([2, 3]) scale = tf.ones([2, 3]) n_samples = tf.placeholder(tf.int32, shape=[]) group_event_ndims = tf.placeholder(tf.int32, shape=[]) a = Laplace('a', loc, scale, n_samples, group_event_ndims) sample_ops = set(get_backward_ops(a.tensor)) for i in [loc, scale, n_samples]: self.assertTrue(i.op in sample_ops) log_p = a.log_prob(np.ones([2, 3])) log_p_ops = set(get_backward_ops(log_p)) for i in [loc, scale, group_event_ndims]: self.assertTrue(i.op in log_p_ops)

41.043103

76

0.607961

1,370

9,522

3.989051

0.075182

0.03806

0.107045

0.10247

0.840439

0.779506

0.775114

0.759012

0

0.020356

0.267381

9,522

231

77

41.220779

0.763045

0.004411

0

0.65

0

0.001372

0

0.13

1

0.065

false

0

0.04

0

0.17

0.005

0

null

0

1

0

null

0

6

1a5960fec38fcaf4733d372d77761c72c65e8280

21

py

Python

src/services/f12020/__init__.py

jordansilva/raspberry-f1-dashboard

96446a348d036a75f4699bab4459eabec16705f8

[ "Apache-2.0" ]

null

src/services/f12020/__init__.py

jordansilva/raspberry-f1-dashboard

96446a348d036a75f4699bab4459eabec16705f8

[ "Apache-2.0" ]

null

src/services/f12020/__init__.py

jordansilva/raspberry-f1-dashboard

96446a348d036a75f4699bab4459eabec16705f8

[ "Apache-2.0" ]

null

from .domain import *

21

0.761905

3

21

5.333333

1

0

0.142857

21

1

21

0.888889

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

46bc25338a0a4e3325cf6af4b58db58031b2cc76

20

py

Python

addons14/company_dependent_attribute/models/__init__.py

odoochain/addons_oca

55d456d798aebe16e49b4a6070765f206a8885ca

[ "MIT" ]

1

2021-06-10T14:59:13.000Z

addons14/company_dependent_attribute/models/__init__.py

odoochain/addons_oca

55d456d798aebe16e49b4a6070765f206a8885ca

[ "MIT" ]

null

addons14/company_dependent_attribute/models/__init__.py

odoochain/addons_oca

55d456d798aebe16e49b4a6070765f206a8885ca

[ "MIT" ]

1

2021-04-09T09:44:44.000Z

from . import field

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2042ef5c22abd61e21de689873e76bba57ef5a02

157

py

Python

mcsrvstats/exceptions/__init__.py

Darkflame72/mc-server-stats

991020d3bac9aa453fd38546ef3eab914ce250fa

[ "MIT" ]

1

2020-06-01T21:03:20.000Z

mcsrvstats/exceptions/__init__.py

Darkflame72/mc-server-stats

991020d3bac9aa453fd38546ef3eab914ce250fa

[ "MIT" ]

22

2020-08-26T05:12:46.000Z

2021-12-20T15:20:45.000Z

mcsrvstats/exceptions/__init__.py

Obsidion-dev/mc-server-stats

991020d3bac9aa453fd38546ef3eab914ce250fa

[ "MIT" ]

2

2020-10-31T05:54:56.000Z

2021-02-15T03:11:32.000Z

"""Exceptions for mcsrvstats.""" from .exceptions import ApiError from .exceptions import PlayerNotFoundError __all__ = ["ApiError", "PlayerNotFoundError"]

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0.333333

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0.101911

157

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null

0

1

0

1

0

6

20470f5893bfc1fbe15db89d3b58d59a2ed1e4a0

156

py

Python

tests/test_import.py

bihealth/varfish-cli

e2b56ef8a158cc7fbe523cbd1c02f13cff8682e5

[ "MIT" ]

2

2020-09-24T08:01:03.000Z

2022-03-23T15:49:13.000Z

tests/test_import.py

bihealth/varfish-cli

e2b56ef8a158cc7fbe523cbd1c02f13cff8682e5

[ "MIT" ]

9

2021-02-16T21:07:35.000Z

2022-03-24T13:36:07.000Z

tests/test_import.py

bihealth/varfish-cli

e2b56ef8a158cc7fbe523cbd1c02f13cff8682e5

[ "MIT" ]

2

2022-03-23T15:06:19.000Z

2022-03-23T15:49:17.000Z

"""Test basic imports.""" import varfish_cli from varfish_cli import __main__ def test_example(): assert varfish_cli.__version__ assert __main__

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null

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6

645ca09a44e961583fbe6abb3a05d9b1b694876b

78

py

Python

src/nmea2tf/__init__.py

naoki-mizuno/nmea2tf

b3e6b4cfbbbeca4026bf488501ed756ecd29ae59

[ "MIT" ]

1

2020-01-07T01:41:18.000Z

src/nmea2tf/__init__.py

naoki-mizuno/nmea2tf

b3e6b4cfbbbeca4026bf488501ed756ecd29ae59

[ "MIT" ]

null

src/nmea2tf/__init__.py

naoki-mizuno/nmea2tf

b3e6b4cfbbbeca4026bf488501ed756ecd29ae59

[ "MIT" ]

null

from GGAParser import * from Converter import * from MarkerPublisher import *

19.5

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true

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null

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null

0

1

0

1

0

1

0

6

64864fa6bb6568c5fe4cfaacfbf82655f5ef32e4

22,593

py

Python

tests/src/python/test_qgslayoutsnapper.py

dyna-mis/Hilabeling

cb7d5d4be29624a20c8a367162dbc6fd779b2b52

[ "MIT" ]

null

tests/src/python/test_qgslayoutsnapper.py

dyna-mis/Hilabeling

cb7d5d4be29624a20c8a367162dbc6fd779b2b52

[ "MIT" ]

null

tests/src/python/test_qgslayoutsnapper.py

dyna-mis/Hilabeling

cb7d5d4be29624a20c8a367162dbc6fd779b2b52

[ "MIT" ]

1

2021-12-25T08:40:30.000Z

# -*- coding: utf-8 -*- """QGIS Unit tests for QgsLayoutSnapper. .. note:: This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. """ __author__ = 'Nyall Dawson' __date__ = '05/07/2017' __copyright__ = 'Copyright 2017, The QGIS Project' # This will get replaced with a git SHA1 when you do a git archive __revision__ = '176c06ceefb5f555205e72b20c962740cc0ec183' import qgis # NOQA from qgis.core import (QgsProject, QgsLayout, QgsLayoutSnapper, QgsLayoutGridSettings, QgsLayoutMeasurement, QgsUnitTypes, QgsLayoutPoint, QgsLayoutItemPage, QgsLayoutGuide, QgsReadWriteContext, QgsLayoutItemMap, QgsLayoutSize) from qgis.PyQt.QtCore import QPointF, Qt, QRectF from qgis.PyQt.QtWidgets import QGraphicsLineItem from qgis.PyQt.QtXml import QDomDocument from qgis.testing import start_app, unittest start_app() class TestQgsLayoutSnapper(unittest.TestCase): def testGettersSetters(self): p = QgsProject() l = QgsLayout(p) s = QgsLayoutSnapper(l) s.setSnapToGrid(False) self.assertFalse(s.snapToGrid()) s.setSnapToGrid(True) self.assertTrue(s.snapToGrid()) s.setSnapToGuides(False) self.assertFalse(s.snapToGuides()) s.setSnapToGuides(True) self.assertTrue(s.snapToGuides()) s.setSnapToItems(False) self.assertFalse(s.snapToItems()) s.setSnapToItems(True) self.assertTrue(s.snapToItems()) s.setSnapTolerance(15) self.assertEqual(s.snapTolerance(), 15) def testSnapPointToGrid(self): p = QgsProject() l = QgsLayout(p) # need a page to snap to grid page = QgsLayoutItemPage(l) page.setPageSize('A4') l.pageCollection().addPage(page) s = QgsLayoutSnapper(l) l.gridSettings().setResolution(QgsLayoutMeasurement(5, QgsUnitTypes.LayoutMillimeters)) s.setSnapToGrid(True) s.setSnapTolerance(1) point, snappedX, snappedY = s.snapPointToGrid(QPointF(1, 1), 1) self.assertTrue(snappedX) self.assertTrue(snappedY) self.assertEqual(point, QPointF(0, 0)) point, snappedX, snappedY = s.snapPointToGrid(QPointF(9, 1), 1) self.assertTrue(snappedX) self.assertTrue(snappedY) self.assertEqual(point, QPointF(10, 0)) point, snappedX, snappedY = s.snapPointToGrid(QPointF(1, 11), 1) self.assertTrue(snappedX) self.assertTrue(snappedY) self.assertEqual(point, QPointF(0, 10)) point, snappedX, snappedY = s.snapPointToGrid(QPointF(13, 11), 1) self.assertFalse(snappedX) self.assertTrue(snappedY) self.assertEqual(point, QPointF(13, 10)) point, snappedX, snappedY = s.snapPointToGrid(QPointF(11, 13), 1) self.assertTrue(snappedX) self.assertFalse(snappedY) self.assertEqual(point, QPointF(10, 13)) point, snappedX, snappedY = s.snapPointToGrid(QPointF(13, 23), 1) self.assertFalse(snappedX) self.assertFalse(snappedY) self.assertEqual(point, QPointF(13, 23)) # grid disabled s.setSnapToGrid(False) point, nappedX, snappedY = s.snapPointToGrid(QPointF(1, 1), 1) self.assertFalse(nappedX) self.assertFalse(snappedY) self.assertEqual(point, QPointF(1, 1)) s.setSnapToGrid(True) # with different pixel scale point, snappedX, snappedY = s.snapPointToGrid(QPointF(0.5, 0.5), 1) self.assertTrue(snappedX) self.assertTrue(snappedY) self.assertEqual(point, QPointF(0, 0)) point, snappedX, snappedY = s.snapPointToGrid(QPointF(0.5, 0.5), 3) self.assertFalse(snappedX) self.assertFalse(snappedY) self.assertEqual(point, QPointF(0.5, 0.5)) # with offset grid l.gridSettings().setOffset(QgsLayoutPoint(2, 0)) point, snappedX, snappedY = s.snapPointToGrid(QPointF(13, 23), 1) self.assertTrue(snappedX) self.assertFalse(snappedY) self.assertEqual(point, QPointF(12, 23)) def testSnapPointsToGrid(self): p = QgsProject() l = QgsLayout(p) # need a page to snap to grid page = QgsLayoutItemPage(l) page.setPageSize('A4') l.pageCollection().addPage(page) s = QgsLayoutSnapper(l) l.gridSettings().setResolution(QgsLayoutMeasurement(5, QgsUnitTypes.LayoutMillimeters)) s.setSnapToGrid(True) s.setSnapTolerance(1) delta, snappedX, snappedY = s.snapPointsToGrid([QPointF(1, 0.5)], 1) self.assertTrue(snappedX) self.assertTrue(snappedY) self.assertEqual(delta, QPointF(-1, -0.5)) point, snappedX, snappedY = s.snapPointsToGrid([QPointF(9, 2), QPointF(12, 6)], 1) self.assertTrue(snappedX) self.assertTrue(snappedY) self.assertEqual(point, QPointF(1, -1)) point, snappedX, snappedY = s.snapPointsToGrid([QPointF(9, 2), QPointF(12, 7)], 1) self.assertTrue(snappedX) self.assertFalse(snappedY) self.assertEqual(point, QPointF(1, 0)) point, snappedX, snappedY = s.snapPointsToGrid([QPointF(8, 2), QPointF(12, 6)], 1) self.assertFalse(snappedX) self.assertTrue(snappedY) self.assertEqual(point, QPointF(0, -1)) # grid disabled s.setSnapToGrid(False) point, snappedX, snappedY = s.snapPointsToGrid([QPointF(1, 1)], 1) self.assertFalse(snappedX) self.assertFalse(snappedY) self.assertEqual(point, QPointF(0, 0)) s.setSnapToGrid(True) # with different pixel scale point, snappedX, snappedY = s.snapPointsToGrid([QPointF(0.5, 0.5)], 1) self.assertTrue(snappedX) self.assertTrue(snappedY) self.assertEqual(point, QPointF(-.5, -.5)) point, snappedX, snappedY = s.snapPointsToGrid([QPointF(0.5, 0.5)], 3) self.assertFalse(snappedX) self.assertFalse(snappedY) self.assertEqual(point, QPointF(0, 0)) # with offset grid l.gridSettings().setOffset(QgsLayoutPoint(2, 0)) point, snappedX, snappedY = s.snapPointsToGrid([QPointF(13, 23)], 1) self.assertTrue(snappedX) self.assertFalse(snappedY) self.assertEqual(point, QPointF(-1, 0)) def testSnapPointToGuides(self): p = QgsProject() l = QgsLayout(p) page = QgsLayoutItemPage(l) page.setPageSize('A4') l.pageCollection().addPage(page) s = QgsLayoutSnapper(l) guides = l.guides() s.setSnapToGuides(True) s.setSnapTolerance(1) # no guides point, snapped = s.snapPointToGuides(0.5, Qt.Vertical, 1) self.assertFalse(snapped) guides.addGuide(QgsLayoutGuide(Qt.Vertical, QgsLayoutMeasurement(1), page)) point, snapped = s.snapPointToGuides(0.5, Qt.Vertical, 1) self.assertTrue(snapped) self.assertEqual(point, 1) # outside tolerance point, snapped = s.snapPointToGuides(5.5, Qt.Vertical, 1) self.assertFalse(snapped) # snapping off s.setSnapToGuides(False) point, snapped = s.snapPointToGuides(0.5, Qt.Vertical, 1) self.assertFalse(snapped) s.setSnapToGuides(True) # snap to hoz point, snapped = s.snapPointToGuides(0.5, Qt.Horizontal, 1) self.assertFalse(snapped) guides.addGuide(QgsLayoutGuide(Qt.Horizontal, QgsLayoutMeasurement(1), page)) point, snapped = s.snapPointToGuides(0.5, Qt.Horizontal, 1) self.assertTrue(snapped) self.assertEqual(point, 1) # with different pixel scale point, snapped = s.snapPointToGuides(0.5, Qt.Horizontal, 3) self.assertFalse(snapped) def testSnapPointsToGuides(self): p = QgsProject() l = QgsLayout(p) page = QgsLayoutItemPage(l) page.setPageSize('A4') l.pageCollection().addPage(page) s = QgsLayoutSnapper(l) guides = l.guides() s.setSnapToGuides(True) s.setSnapTolerance(1) # no guides delta, snapped = s.snapPointsToGuides([0.5], Qt.Vertical, 1) self.assertFalse(snapped) guides.addGuide(QgsLayoutGuide(Qt.Vertical, QgsLayoutMeasurement(1), page)) point, snapped = s.snapPointsToGuides([0.7], Qt.Vertical, 1) self.assertTrue(snapped) self.assertAlmostEqual(point, 0.3, 5) point, snapped = s.snapPointsToGuides([0.7, 1.2], Qt.Vertical, 1) self.assertTrue(snapped) self.assertAlmostEqual(point, -0.2, 5) # outside tolerance point, snapped = s.snapPointsToGuides([5.5], Qt.Vertical, 1) self.assertFalse(snapped) # snapping off s.setSnapToGuides(False) point, snapped = s.snapPointsToGuides([0.5], Qt.Vertical, 1) self.assertFalse(snapped) s.setSnapToGuides(True) # snap to hoz point, snapped = s.snapPointsToGuides([0.5], Qt.Horizontal, 1) self.assertFalse(snapped) guides.addGuide(QgsLayoutGuide(Qt.Horizontal, QgsLayoutMeasurement(1), page)) point, snapped = s.snapPointsToGuides([0.7], Qt.Horizontal, 1) self.assertTrue(snapped) self.assertAlmostEqual(point, 0.3, 5) point, snapped = s.snapPointsToGuides([0.7, 1.2], Qt.Horizontal, 1) self.assertTrue(snapped) self.assertAlmostEqual(point, -0.2, 5) point, snapped = s.snapPointsToGuides([0.7, 0.9, 1.2], Qt.Horizontal, 1) self.assertTrue(snapped) self.assertAlmostEqual(point, 0.1, 5) # with different pixel scale point, snapped = s.snapPointsToGuides([0.5, 1.5], Qt.Horizontal, 3) self.assertFalse(snapped) def testSnapPointToItems(self): p = QgsProject() l = QgsLayout(p) page = QgsLayoutItemPage(l) page.setPageSize('A4') #l.pageCollection().addPage(page) s = QgsLayoutSnapper(l) guides = l.guides() s.setSnapToItems(True) s.setSnapTolerance(1) # no items point, snapped = s.snapPointToItems(0.5, Qt.Horizontal, 1, []) self.assertFalse(snapped) line = QGraphicsLineItem() line.setVisible(True) point, snapped = s.snapPointToItems(0.5, Qt.Horizontal, 1, [], line) self.assertFalse(line.isVisible()) guides.addGuide(QgsLayoutGuide(Qt.Vertical, QgsLayoutMeasurement(1), page)) # add an item item1 = QgsLayoutItemMap(l) item1.attemptMove(QgsLayoutPoint(4, 8, QgsUnitTypes.LayoutMillimeters)) item1.attemptResize(QgsLayoutSize(18, 12, QgsUnitTypes.LayoutMillimeters)) l.addItem(item1) point, snapped = s.snapPointToItems(3.5, Qt.Horizontal, 1, [], line) self.assertTrue(snapped) self.assertEqual(point, 4) self.assertTrue(line.isVisible()) point, snapped = s.snapPointToItems(4.5, Qt.Horizontal, 1, []) self.assertTrue(snapped) self.assertEqual(point, 4) # ignoring item point, snapped = s.snapPointToItems(4.5, Qt.Horizontal, 1, [item1]) self.assertFalse(snapped) # outside tolerance point, snapped = s.snapPointToItems(5.5, Qt.Horizontal, 1, [], line) self.assertFalse(snapped) self.assertFalse(line.isVisible()) # snap to center point, snapped = s.snapPointToItems(12.5, Qt.Horizontal, 1, []) self.assertTrue(snapped) self.assertEqual(point, 13) # snap to right point, snapped = s.snapPointToItems(22.5, Qt.Horizontal, 1, []) self.assertTrue(snapped) self.assertEqual(point, 22) #snap to top point, snapped = s.snapPointToItems(7.5, Qt.Vertical, 1, [], line) self.assertTrue(snapped) self.assertEqual(point, 8) self.assertTrue(line.isVisible()) point, snapped = s.snapPointToItems(8.5, Qt.Vertical, 1, []) self.assertTrue(snapped) self.assertEqual(point, 8) # outside tolerance point, snapped = s.snapPointToItems(5.5, Qt.Vertical, 1, [], line) self.assertFalse(snapped) self.assertFalse(line.isVisible()) # snap to center point, snapped = s.snapPointToItems(13.5, Qt.Vertical, 1, []) self.assertTrue(snapped) self.assertEqual(point, 14) # snap to bottom point, snapped = s.snapPointToItems(20.5, Qt.Vertical, 1, []) self.assertTrue(snapped) self.assertEqual(point, 20) # snapping off s.setSnapToItems(False) line.setVisible(True) point, snapped = s.snapPointToItems(20.5, Qt.Vertical, 1, [], line) self.assertFalse(snapped) self.assertFalse(line.isVisible()) # with different pixel scale s.setSnapToItems(True) point, snapped = s.snapPointToItems(20.5, Qt.Vertical, 3, []) self.assertFalse(snapped) def testSnapPointsToItems(self): p = QgsProject() l = QgsLayout(p) page = QgsLayoutItemPage(l) page.setPageSize('A4') #l.pageCollection().addPage(page) s = QgsLayoutSnapper(l) guides = l.guides() s.setSnapToItems(True) s.setSnapTolerance(1) # no items point, snapped = s.snapPointsToItems([0.5], Qt.Horizontal, 1, []) self.assertFalse(snapped) line = QGraphicsLineItem() line.setVisible(True) point, snapped = s.snapPointsToItems([0.5], Qt.Horizontal, 1, [], line) self.assertFalse(line.isVisible()) guides.addGuide(QgsLayoutGuide(Qt.Vertical, QgsLayoutMeasurement(1), page)) # add an item item1 = QgsLayoutItemMap(l) item1.attemptMove(QgsLayoutPoint(4, 8, QgsUnitTypes.LayoutMillimeters)) item1.attemptResize(QgsLayoutSize(18, 12, QgsUnitTypes.LayoutMillimeters)) l.addItem(item1) point, snapped = s.snapPointsToItems([3.5], Qt.Horizontal, 1, [], line) self.assertTrue(snapped) self.assertEqual(point, 0.5) self.assertTrue(line.isVisible()) point, snapped = s.snapPointsToItems([4.5], Qt.Horizontal, 1, []) self.assertTrue(snapped) self.assertEqual(point, -0.5) point, snapped = s.snapPointsToItems([4.6, 4.5], Qt.Horizontal, 1, []) self.assertTrue(snapped) self.assertEqual(point, -0.5) point, snapped = s.snapPointsToItems([4.6, 4.5, 3.7], Qt.Horizontal, 1, []) self.assertTrue(snapped) self.assertAlmostEqual(point, 0.3, 5) # ignoring item point, snapped = s.snapPointsToItems([4.5], Qt.Horizontal, 1, [item1]) self.assertFalse(snapped) # outside tolerance point, snapped = s.snapPointsToItems([5.5], Qt.Horizontal, 1, [], line) self.assertFalse(snapped) self.assertFalse(line.isVisible()) # snap to center point, snapped = s.snapPointsToItems([12.5], Qt.Horizontal, 1, []) self.assertTrue(snapped) self.assertEqual(point, 0.5) # snap to right point, snapped = s.snapPointsToItems([22.5], Qt.Horizontal, 1, []) self.assertTrue(snapped) self.assertEqual(point, -0.5) #snap to top point, snapped = s.snapPointsToItems([7.5], Qt.Vertical, 1, [], line) self.assertTrue(snapped) self.assertEqual(point, 0.5) self.assertTrue(line.isVisible()) point, snapped = s.snapPointsToItems([8.5], Qt.Vertical, 1, []) self.assertTrue(snapped) self.assertEqual(point, -0.5) # outside tolerance point, snapped = s.snapPointsToItems([5.5], Qt.Vertical, 1, [], line) self.assertFalse(snapped) self.assertFalse(line.isVisible()) # snap to center point, snapped = s.snapPointsToItems([13.5], Qt.Vertical, 1, []) self.assertTrue(snapped) self.assertEqual(point, 0.5) # snap to bottom point, snapped = s.snapPointsToItems([20.5], Qt.Vertical, 1, []) self.assertTrue(snapped) self.assertEqual(point, -0.5) # snapping off s.setSnapToItems(False) line.setVisible(True) point, snapped = s.snapPointsToItems([20.5], Qt.Vertical, 1, [], line) self.assertFalse(snapped) self.assertFalse(line.isVisible()) # with different pixel scale s.setSnapToItems(True) point, snapped = s.snapPointsToItems([20.5], Qt.Vertical, 3, []) self.assertFalse(snapped) def testSnapPoint(self): p = QgsProject() l = QgsLayout(p) page = QgsLayoutItemPage(l) page.setPageSize('A4') l.pageCollection().addPage(page) s = QgsLayoutSnapper(l) guides = l.guides() # first test snapping to grid l.gridSettings().setResolution(QgsLayoutMeasurement(5, QgsUnitTypes.LayoutMillimeters)) s.setSnapToGrid(True) s.setSnapTolerance(1) point, snapped = s.snapPoint(QPointF(1, 1), 1) self.assertTrue(snapped) self.assertEqual(point, QPointF(0, 0)) s.setSnapToItems(False) s.setSnapToGrid(False) point, snapped = s.snapPoint(QPointF(1, 1), 1) self.assertFalse(snapped) self.assertEqual(point, QPointF(1, 1)) # test that guide takes precedence s.setSnapToGrid(True) s.setSnapToGuides(True) guides.addGuide(QgsLayoutGuide(Qt.Horizontal, QgsLayoutMeasurement(0.5), page)) point, snapped = s.snapPoint(QPointF(1, 1), 1) self.assertTrue(snapped) self.assertEqual(point, QPointF(0, 0.5)) # add an item item1 = QgsLayoutItemMap(l) item1.attemptMove(QgsLayoutPoint(121, 1.1, QgsUnitTypes.LayoutMillimeters)) l.addItem(item1) # test that guide takes precedence over item s.setSnapToGrid(True) s.setSnapToGuides(True) s.setSnapToItems(True) point, snapped = s.snapPoint(QPointF(1, 1), 1) self.assertTrue(snapped) self.assertEqual(point, QPointF(0, 0.5)) # but items take precedence over grid s.setSnapToGuides(False) point, snapped = s.snapPoint(QPointF(1, 1), 1) self.assertTrue(snapped) self.assertEqual(point, QPointF(0, 1.1)) # ... unless item is ignored! point, snapped = s.snapPoint(QPointF(1, 1), 1, None, None, [item1]) self.assertTrue(snapped) self.assertEqual(point, QPointF(0, 0)) def testSnapRect(self): p = QgsProject() l = QgsLayout(p) page = QgsLayoutItemPage(l) page.setPageSize('A4') l.pageCollection().addPage(page) s = QgsLayoutSnapper(l) guides = l.guides() # first test snapping to grid l.gridSettings().setResolution(QgsLayoutMeasurement(5, QgsUnitTypes.LayoutMillimeters)) s.setSnapToItems(False) s.setSnapToGrid(True) s.setSnapTolerance(1) rect, snapped = s.snapRect(QRectF(1, 1, 2, 1), 1) self.assertTrue(snapped) self.assertEqual(rect, QRectF(0, 0, 2, 1)) rect, snapped = s.snapRect(QRectF(1, 1, 3.5, 3.5), 1) self.assertTrue(snapped) self.assertEqual(rect, QRectF(1.5, 1.5, 3.5, 3.5)) s.setSnapToItems(False) s.setSnapToGrid(False) rect, snapped = s.snapRect(QRectF(1, 1, 3.5, 3.5), 1) self.assertFalse(snapped) self.assertEqual(rect, QRectF(1, 1, 3.5, 3.5)) # test that guide takes precedence s.setSnapToGrid(True) s.setSnapToGuides(True) guides.addGuide(QgsLayoutGuide(Qt.Horizontal, QgsLayoutMeasurement(0.5), page)) rect, snapped = s.snapRect(QRectF(1, 1, 2, 3), 1) self.assertTrue(snapped) self.assertEqual(rect, QRectF(0.0, 0.5, 2.0, 3.0)) # add an item item1 = QgsLayoutItemMap(l) item1.attemptMove(QgsLayoutPoint(121, 1.1, QgsUnitTypes.LayoutMillimeters)) l.addItem(item1) # test that guide takes precedence over item s.setSnapToGrid(True) s.setSnapToGuides(True) s.setSnapToItems(True) rect, snapped = s.snapRect(QRectF(1, 1, 2, 3), 1) self.assertTrue(snapped) self.assertEqual(rect, QRectF(0.0, 0.5, 2.0, 3.0)) # but items take precedence over grid s.setSnapToGuides(False) rect, snapped = s.snapRect(QRectF(1, 1, 2, 3), 1) self.assertTrue(snapped) self.assertEqual(rect, QRectF(0.0, 1.1, 2.0, 3.0)) # ... unless item is ignored! rect, snapped = s.snapRect(QRectF(1, 1, 2, 3), 1, None, None, [item1]) self.assertTrue(snapped) self.assertEqual(rect, QRectF(0.0, 0.0, 2.0, 3.0)) def testReadWriteXml(self): p = QgsProject() l = QgsLayout(p) l.initializeDefaults() snapper = l.snapper() snapper.setSnapToGrid(True) snapper.setSnapTolerance(1) snapper.setSnapToGuides(True) snapper.setSnapToItems(True) doc = QDomDocument("testdoc") elem = doc.createElement("test") self.assertTrue(snapper.writeXml(elem, doc, QgsReadWriteContext())) l2 = QgsLayout(p) l2.initializeDefaults() snapper2 = l2.snapper() self.assertTrue(snapper2.readXml(elem.firstChildElement(), doc, QgsReadWriteContext())) self.assertTrue(snapper2.snapToGrid()) self.assertEqual(snapper2.snapTolerance(), 1) self.assertTrue(snapper2.snapToGuides()) self.assertTrue(snapper2.snapToItems()) snapper.setSnapToGrid(False) snapper.setSnapTolerance(1) snapper.setSnapToGuides(False) snapper.setSnapToItems(False) doc = QDomDocument("testdoc") elem = doc.createElement("test") self.assertTrue(snapper.writeXml(elem, doc, QgsReadWriteContext())) self.assertTrue(snapper2.readXml(elem.firstChildElement(), doc, QgsReadWriteContext())) self.assertFalse(snapper2.snapToGrid()) self.assertFalse(snapper2.snapToGuides()) self.assertFalse(snapper2.snapToItems()) if __name__ == '__main__': unittest.main()

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0.037199

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null

0

1

0

null

0

6

64a4e83b993a419523a81b9eaaeb861ab617009b

33

py

Python

Sources/JYMT-ML-StructureFinder/xyz2mol/__init__.py

jerry0317/JYMoleculeTool-ML-Swift

5974806791c46334ff75e175cf59c1f0f8f09db7

[ "MIT" ]

null

Sources/JYMT-ML-StructureFinder/xyz2mol/__init__.py

jerry0317/JYMoleculeTool-ML-Swift

5974806791c46334ff75e175cf59c1f0f8f09db7

[ "MIT" ]

null

Sources/JYMT-ML-StructureFinder/xyz2mol/__init__.py

jerry0317/JYMoleculeTool-ML-Swift

5974806791c46334ff75e175cf59c1f0f8f09db7

[ "MIT" ]

null

from .oechem_xyz2smiles import *

16.5

32

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0

1

0

1

0

6

64a7f725de7ddf2854cd530ca2e60f4ec7a1c70b

114

py

Python

src/main/python/runtime/trees/__init__.py

danilkolikov/fnn

0f5ad2d9fdd1f03d3bf62255da14b05e4e0289e1

[ "MIT" ]

1

2019-01-06T04:42:28.000Z

src/main/python/runtime/trees/__init__.py

danilkolikov/fnn

0f5ad2d9fdd1f03d3bf62255da14b05e4e0289e1

[ "MIT" ]

null

src/main/python/runtime/trees/__init__.py

danilkolikov/fnn

0f5ad2d9fdd1f03d3bf62255da14b05e4e0289e1

[ "MIT" ]

null

from .tensor_tree import SumTree, ProdTree, empty_tree, stack, make_tuple from .operator_tree import OperatorTree

38

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0.105263

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null

0

1

0

1

0

1

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6

64b7dff811bf7ef3a2485e3ca06ce1244f45a760

4,334

py

Python

test/test_recipient_lists.py

Ometria/python-sparkpost

b7eb2e30effc0d35cf25d7acaa4a5c304c25c9e5

[ "Apache-2.0" ]

100

2015-02-11T20:07:23.000Z

2021-10-18T10:27:35.000Z

test/test_recipient_lists.py

Ometria/python-sparkpost

b7eb2e30effc0d35cf25d7acaa4a5c304c25c9e5

[ "Apache-2.0" ]

152

2015-02-09T01:34:02.000Z

2021-11-08T17:32:30.000Z

test/test_recipient_lists.py

Ometria/python-sparkpost

b7eb2e30effc0d35cf25d7acaa4a5c304c25c9e5

[ "Apache-2.0" ]

79

2015-02-14T07:42:17.000Z

2022-02-25T00:52:28.000Z

import pytest import responses from sparkpost import SparkPost from sparkpost import RecipientLists from sparkpost.exceptions import SparkPostAPIException def test_translate_keys_with_id(): t = RecipientLists('uri', 'key') results = t._translate_keys(id='test_id') assert results['id'] == 'test_id' @responses.activate def test_success_create(): responses.add( responses.POST, 'https://api.sparkpost.com/api/v1/recipient-lists', status=200, content_type='application/json', body='{"results": "yay"}' ) sp = SparkPost('fake-key') results = sp.recipient_lists.create() assert results == 'yay' @responses.activate def test_fail_create(): responses.add( responses.POST, 'https://api.sparkpost.com/api/v1/recipient-lists', status=500, content_type='application/json', body=""" {"errors": [{"message": "You failed", "description": "More Info"}]} """ ) with pytest.raises(SparkPostAPIException): sp = SparkPost('fake-key') sp.recipient_lists.create() @responses.activate def test_success_update(): responses.add( responses.PUT, 'https://api.sparkpost.com/api/v1/recipient-lists/foobar', status=200, content_type='application/json', body='{"results": "yay"}' ) sp = SparkPost('fake-key') results = sp.recipient_lists.update('foobar', name='foobar') assert results == 'yay' @responses.activate def test_fail_update(): responses.add( responses.PUT, 'https://api.sparkpost.com/api/v1/recipient-lists/foobar', status=500, content_type='application/json', body=""" {"errors": [{"message": "You failed", "description": "More Info"}]} """ ) with pytest.raises(SparkPostAPIException): sp = SparkPost('fake-key') sp.recipient_lists.update('foobar', name='foobar') @responses.activate def test_success_delete(): responses.add( responses.DELETE, 'https://api.sparkpost.com/api/v1/recipient-lists/foobar', status=200, content_type='application/json', body='{"results": "yay"}' ) sp = SparkPost('fake-key') results = sp.recipient_lists.delete('foobar') assert results == 'yay' @responses.activate def test_fail_delete(): responses.add( responses.DELETE, 'https://api.sparkpost.com/api/v1/recipient-lists/foobar', status=500, content_type='application/json', body=""" {"errors": [{"message": "You failed", "description": "More Info"}]} """ ) with pytest.raises(SparkPostAPIException): sp = SparkPost('fake-key') sp.recipient_lists.delete('foobar') @responses.activate def test_success_get(): responses.add( responses.GET, 'https://api.sparkpost.com/api/v1/recipient-lists/foobar', status=200, content_type='application/json', body='{"results": "yay"}' ) sp = SparkPost('fake-key') results = sp.recipient_lists.get('foobar') assert results == "yay" @responses.activate def test_success_get_with_recipients(): responses.add( responses.GET, 'https://api.sparkpost.com/api/v1/recipient-lists/foobar', status=200, content_type='application/json', body='{"results": "yay"}' ) sp = SparkPost('fake-key') results = sp.recipient_lists.get('foobar', True) assert results == "yay" @responses.activate def test_fail_get(): responses.add( responses.GET, 'https://api.sparkpost.com/api/v1/recipient-lists/foobar', status=404, content_type='application/json', body=""" {"errors": [{"message": "cant find", "description": "where you go"}]} """ ) with pytest.raises(SparkPostAPIException): sp = SparkPost('fake-key') sp.recipient_lists.get('foobar') @responses.activate def test_success_list(): responses.add( responses.GET, 'https://api.sparkpost.com/api/v1/recipient-lists', status=200, content_type='application/json', body='{"results": "yay"}' ) sp = SparkPost('fake-key') response = sp.recipient_lists.list() assert response == "yay"

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null

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null

0

6

b3edc9918af68489b61ac6a4d66c84088023032b

13,345

py

Python

inkscape/.config/inkscape/extensions/circuitSymbols/drawSwitches.py

Elyk8/dotrice

68924c7d1e3026ab94edd8c4f35c4ae30cf28f0c

[ "BSD-3-Clause" ]

null

inkscape/.config/inkscape/extensions/circuitSymbols/drawSwitches.py

Elyk8/dotrice

68924c7d1e3026ab94edd8c4f35c4ae30cf28f0c

[ "BSD-3-Clause" ]

null

inkscape/.config/inkscape/extensions/circuitSymbols/drawSwitches.py

Elyk8/dotrice

68924c7d1e3026ab94edd8c4f35c4ae30cf28f0c

[ "BSD-3-Clause" ]

null

#!/usr/bin/python import inkscapeMadeEasy.inkscapeMadeEasy_Base as inkBase import inkscapeMadeEasy.inkscapeMadeEasy_Draw as inkDraw class switch(inkBase.inkscapeMadeEasy): def add(self, vector, delta): # nector does not need to be numpy array. delta will be converted to numpy array. Numpy can then deal with np.array + list return vector + np.array(delta) # --------------------------------------------- def drawNPST(self, parent, position=[0, 0], value='S', label='Switch', angleDeg=0, isPushButton=False, nPoles=1, flagOpen=True, drawCommuteArrow=False, commuteText='', flagVolt=True, voltName='v', flagCurr=True, currName='i', invertArrows=False, convention='passive', wireExtraSize=0): """ draws a switch with two terminals only parent: parent object position: position [x,y] value: string with resistor value. (default 'S') label: label of the object (it can be repeated) angleDeg: rotation angle in degrees counter-clockwise (default 0) isPushButton: draws push-button (defalut: False) nPoles: numer of poles (default: 1) flagOpen: normaly open switch (default:True) drawCommuteArrow: draw comuting arrow (default: False) commuteText: string with comuting info flagVolt: indicates whether the voltage arrow must be drawn (default: true) voltName: voltage drop name (default: v) flagCurr: indicates whether the current arrow must be drawn (default: true) currName: current drop name (default: i) invertArrows: invert V/I arrow directions (default: False) convention: passive/active sign convention. available types: 'passive' (default) , 'active' wireExtraSize: additional length added to the terminals. If negative, the length will be reduced. default: 0) """ group = self.createGroup(parent, label) elem = self.createGroup(group, label) color = inkDraw.color.defined('red') colorBlack = inkDraw.color.defined('black') colorWhite = inkDraw.color.defined('white') lineStyleSign = inkDraw.lineStyle.set(lineWidth=0.7, lineColor=colorBlack, fillColor=colorWhite) [arrowStart, arrowEnd] = inkDraw.marker.createArrow1Marker(self, 'arrowSwitch', RenameMode=0, scale=0.25, strokeColor=color, fillColor=color) inkDraw.line.relCoords(elem, [[-(15 + wireExtraSize), 0]], self.add(position, [-10, 0])) inkDraw.line.relCoords(elem, [[15 + wireExtraSize, 0]], self.add(position, [10, 0])) if isPushButton: # push-button if flagOpen: inkDraw.line.relCoords(elem, [[20, 0]], self.add(position, [-10, -5])) inkDraw.line.relCoords(elem, [[0, -7]], self.add(position, [0, -5])) else: inkDraw.line.relCoords(elem, [[20, 0]], self.add(position, [-10, 2])) inkDraw.line.relCoords(elem, [[0, -9]], self.add(position, [0, 2])) else: # throw switch if flagOpen: inkDraw.line.relCoords(elem, [[20, -8]], self.add(position, [-10, 0])) else: inkDraw.line.relCoords(elem, [[20, -2]], self.add(position, [-10, 0])) inkDraw.circle.centerRadius(elem, self.add(position, [10, 0]), 1.2, offset=[0, 0], lineStyle=lineStyleSign) inkDraw.circle.centerRadius(elem, self.add(position, [-10, 0]), 1.2, offset=[0, 0], lineStyle=lineStyleSign) if drawCommuteArrow: if commuteText: if isPushButton: # push-button pos_text = self.add(position, [-13, -10 - self.textOffset]) else: # throw switch pos_text = self.add(position, [-13, -5 - self.textOffset]) if inkDraw.useLatex: commuteText = '$' + commuteText + '$' inkDraw.text.latex(self, group, commuteText, pos_text, textColor=color, fontSize=self.fontSize * 0.8, refPoint='tc', preambleFile=self.preambleFile) if isPushButton: # push-button lineStyle = inkDraw.lineStyle.set(lineWidth=0.6, lineColor=color, markerEnd=arrowEnd, strokeDashArray='1,1.5') inkDraw.line.relCoords(group, [[0, 14]], self.add(position, [-5, -8]), lineStyle=lineStyle) else: # throw switch if flagOpen: lineStyle = inkDraw.lineStyle.set(lineWidth=0.6, lineColor=color, markerEnd=arrowEnd, strokeDashArray='1,1.5') else: lineStyle = inkDraw.lineStyle.set(lineWidth=0.6, lineColor=color, markerStart=arrowStart, strokeDashArray='1,1.5') inkDraw.arc.startEndRadius(group, [-4, -10], [3, 1], 10, self.add(position, [-1, 0]), lineStyle=lineStyle, flagRightOf=False) if isPushButton: # push-button pos_text = self.add(position, [3, -6 - self.textOffset]) else: # throw switch if drawCommuteArrow: pos_text = self.add(position, [3, -8 - self.textOffset]) else: if nPoles > 1: pos_text = self.add(position, [3, -6 - self.textOffset]) else: pos_text = self.add(position, [-2, -6 - self.textOffset]) if value: if inkDraw.useLatex: value = '$' + value + '$' inkDraw.text.latex(self, group, value, pos_text, fontSize=self.fontSize, refPoint='bl', preambleFile=self.preambleFile) # multiple poles if nPoles > 1: spacingY = -25 for i in range(nPoles - 1): self.copyElement(elem, group, distance=[0, spacingY * (i + 1)]) lineStyle = inkDraw.lineStyle.set(lineWidth=0.6, lineColor=colorBlack, strokeDashArray='1.5,1.5') if isPushButton: # push-button if flagOpen: inkDraw.line.relCoords(elem, [[0, spacingY * (nPoles - 1)]], self.add(position, [0, -7]), lineStyle=lineStyle) else: inkDraw.line.relCoords(elem, [[0, spacingY * (nPoles - 1)]], self.add(position, [0, 2]), lineStyle=lineStyle) else: # throw switch if flagOpen: inkDraw.line.relCoords(elem, [[0, spacingY * (nPoles - 1)]], self.add(position, [0, -4]), lineStyle=lineStyle) else: inkDraw.line.relCoords(elem, [[0, spacingY * (nPoles - 1)]], self.add(position, [0, -1]), lineStyle=lineStyle) if angleDeg != 0: self.rotateElement(group, position, angleDeg) if flagVolt: if convention == 'passive': self.drawVoltArrow(group, self.add(position, [0, 7]), name=voltName, color=self.voltageColor, angleDeg=angleDeg, invertArrows=not invertArrows) if convention == 'active': self.drawVoltArrow(group, self.add(position, [0, 7]), name=voltName, color=self.voltageColor, angleDeg=angleDeg, invertArrows=invertArrows) if flagCurr: self.drawCurrArrow(group, self.add(position, [20 + wireExtraSize, -5]), name=currName, color=self.currentColor, angleDeg=angleDeg, invertArrows=invertArrows) return group # --------------------------------------------- def drawNPNT(self, parent, position=[0, 0], value='S', label='Switch', angleDeg=0, connection=1, nPoles=1, nThrows=1, drawCommuteArrow=False, commuteOrientation='ccw', commuteText='', flagVolt=True, voltName='v', flagCurr=True, currName='i', invertArrows=False, convention='passive', wireExtraSize=0): """ draws a switch with two terminals only parent: parent object position: position [x,y] value: string with resistor value. (default 'S') label: label of the object (it can be repeated) angleDeg: rotation angle in degrees counter-clockwise (default 0) connection: switch connection position (default:1) 0: OPEN drawCommuteArrow: draw comuting arrow (default: False) commuteOrientation: orientation of the commutation arrow, 'cw', 'ccw' (default) commuteText: string with comuting info flagVolt: indicates whether the voltage arrow must be drawn (default: true) voltName: voltage drop name (default: v) flagCurr: indicates whether the current arrow must be drawn (default: true) currName: current drop name (default: i) invertArrows: invert V/I arrow directions (default: False) convention: passive/active sign convention. available types: 'passive' (default) , 'active' wireExtraSize: additional length added to the terminals. If negative, the length will be reduced. default: 0) """ group = self.createGroup(parent, label) elem = self.createGroup(group, label) color = inkDraw.color.defined('red') colorBlack = inkDraw.color.defined('black') colorWhite = inkDraw.color.defined('white') lineStyleSign = inkDraw.lineStyle.set(lineWidth=0.7, lineColor=colorBlack, fillColor=colorWhite) [arrowStart, arrowEnd] = inkDraw.marker.createArrow1Marker(self, 'arrowSwitch', RenameMode=0, scale=0.25, strokeColor=color, fillColor=color) # pole inkDraw.line.relCoords(elem, [[-(15 + wireExtraSize), 0]], self.add(position, [-10, 0])) # throw if nThrows < 3: spacingThrowY = 20 else: spacingThrowY = 10 Y_positions = [(i - (nThrows - 1) / float(2)) * spacingThrowY for i in range(nThrows)] # connection position conn = min(connection, nThrows) if conn > 0: inkDraw.line.relCoords(elem, [[15, Y_positions[conn - 1]]], self.add(position, [-10, 0])) else: inkDraw.line.relCoords(elem, [[7.5, Y_positions[0]]], self.add(position, [-10, 0])) for i in range(nThrows): inkDraw.line.relCoords(elem, [[-10, 0], [-(10 + wireExtraSize), 0]], self.add(position, [25 + wireExtraSize, Y_positions[i]])) inkDraw.circle.centerRadius(elem, self.add(position, [5, Y_positions[i]]), 1.2, offset=[0, 0], lineStyle=lineStyleSign) inkDraw.text.latex(self, elem, chr(ord('@') + i + 1), self.add(position, [5, Y_positions[i] - self.fontSize * 0.4]), fontSize=self.fontSize * 0.5, refPoint='bc', preambleFile=self.preambleFile) inkDraw.circle.centerRadius(elem, self.add(position, [-10, 0]), 1.2, offset=[0, 0], lineStyle=lineStyleSign) # commute arrow if drawCommuteArrow: if commuteText: pos_text = self.add(position, [-13, - 5 - self.textOffset]) if inkDraw.useLatex: commuteText = '$' + commuteText + '$' inkDraw.text.latex(self, group, commuteText, pos_text, textColor=color, fontSize=self.fontSize * 0.8, refPoint='tc', preambleFile=self.preambleFile) if commuteOrientation == 'cw': lineStyle = inkDraw.lineStyle.set(lineWidth=0.6, lineColor=color, markerEnd=arrowEnd, strokeDashArray='1,1.5') else: lineStyle = inkDraw.lineStyle.set(lineWidth=0.6, lineColor=color, markerStart=arrowStart, strokeDashArray='1,1.5') inkDraw.arc.startEndRadius(group, [-4, -9], [-4, 9], 10, self.add(position, [-1, 0]), lineStyle=lineStyle, flagRightOf=False) # label pos_text = self.add(position, [-10, Y_positions[0] - self.textOffset]) if value: if inkDraw.useLatex: value = '$' + value + '$' inkDraw.text.latex(self, group, value, pos_text, fontSize=self.fontSize, refPoint='bl', preambleFile=self.preambleFile) # multiple poles if nPoles > 1: spacingY = -(25 + spacingThrowY * (nThrows - 1)) for i in range(nPoles - 1): self.copyElement(elem, group, distance=[0, spacingY * (i + 1)]) lineStyle = inkDraw.lineStyle.set(lineWidth=0.6, lineColor=colorBlack, strokeDashArray='1.5,1.5') inkDraw.line.relCoords(elem, [[0, spacingY * (nPoles - 1)]], self.add(position, [-2.5, Y_positions[conn - 1] / 2]), lineStyle=lineStyle) if angleDeg != 0: self.rotateElement(group, position, angleDeg) if flagVolt: if convention == 'passive': self.drawVoltArrow(group, self.add(position, [0, 6 + Y_positions[-1]]), name=voltName, color=self.voltageColor, angleDeg=angleDeg, invertArrows=not invertArrows) if convention == 'active': self.drawVoltArrow(group, self.add(position, [0, 6 + Y_positions[-1]]), name=voltName, color=self.voltageColor, angleDeg=angleDeg, invertArrows=invertArrows) if flagCurr: self.drawCurrArrowSimple(group, self.add(position, [-20 - wireExtraSize, 5]), name=currName, color=self.currentColor, angleDeg=angleDeg + 180, invertArrows=invertArrows, size=10.0, invertTextSide=False, extraAngleText=0.0) return group

53.810484

149

0.5997

1,464

13,345

5.450137

0.141393

0.034215

0.073317

0.051134

0.825793

0.799098

0.772653

0.754355

0.749467

0.732673

0

0.029626

0.269015

13,345

247

150

54.02834

0.788314

0.178569

0

0.690323

0

0.015873

0

1

0.019355

false

0.025806

0.012903

0.006452

0.058065

0

null

0

1

0

null

0

6

37526db6e56f22322a5ac557067ac6f95f661ba1

10,252

py

Python

tests/integration_tests.py

maurice-g/codit-api

ccab85976866e0b8e11f888beecc4aae361b0740

[ "MIT" ]

1

2022-03-06T01:57:34.000Z

tests/integration_tests.py

maurice-g/codit-api

ccab85976866e0b8e11f888beecc4aae361b0740

[ "MIT" ]

null

tests/integration_tests.py

maurice-g/codit-api

ccab85976866e0b8e11f888beecc4aae361b0740

[ "MIT" ]

null

import os, time import pytest from src.caplena_api_demo import CaplenaAPI, Question, Row, Answer, Project, Code @pytest.fixture(scope="session") def client(): caplena_api_key = os.environ.get('CAPLENA_API_KEY') api = CaplenaAPI('en', caplena_api_key) baseuri = os.environ.get('BASEURI') if baseuri: api.baseURI = baseuri return api def test_list_projects(client): _ = client.listProjects() def test_list_inheritable_projects(client): _ = client.listInheritableProjects() def test_update_question(client): codebook = [Code(id=1, label='test', category='A')] question_name = 'testq' question = Question(name=question_name, codebook=codebook) rows = [ Row(auxiliary_columns=[], answers=[Answer(text='test', question=question_name, reviewed=False)]), Row(auxiliary_columns=[], answers=[Answer(text='test2', question=question_name, reviewed=False)]) ] proj1 = client.createProject('testproject', 'en', rows=rows, questions=[question], upload_async=False) proj2 = client.createProject('testproject', 'en', rows=rows, questions=[question], upload_async=False) q = proj2.questions[0] q.inherits_from = proj1.questions[0].id q_new = client.updateQuestion(q) assert q_new.inherits_from == proj1.questions[0].id def test_sync_workflow(client): codebook = [ { 'id': 1, 'label': 'Code 1', 'category': 'CATEGORY 1' }, { 'id': 20, 'label': 'Code 2', 'category': 'CATEGORY 2' } ] questions = [{'name': 'Question 1', 'codebook': codebook}] # make sure to have at least 15 answers reviewed to enble predictions rows_init = [ { "answers": [{ "text": "Answer-text 1", "question": "Question 1" }], "auxiliary_columns": ["ID 1", "Some other column value 1"] # The values of the additional columns: Needs to be in same order as auxiliary_column_names of survey }, { "answers": [{ "text": "Answer-text 2", "question": "Question 1" }], "auxiliary_columns": ["ID 1", "Some other column value 1"] }, { "answers": [{ "text": "Answer-text 3", "question": "Question 1" }], "auxiliary_columns": ["ID 1", "Some other column value 1"] } ] num_projects_before = len(client.listProjects()) questions = [Question.from_json(q) for q in questions] rows_init = [Row.from_json(row_init) for row_init in rows_init] new_project = client.createProject( name="My new project", language="de", auxiliary_column_names=['ID', 'some other column'], translate=True, questions=questions, rows=rows_init, upload_async=False, request_training=True ) assert isinstance(new_project, Project) num_projects_after = len(client.listProjects()) assert num_projects_after == num_projects_before + 1 assert len(new_project.questions) == 1 question_id = new_project.questions[0].id n_not_reviewed = len([row for row in rows_init if not row.answers[0].reviewed]) assert new_project.rows is not None assert len(new_project.rows) == len(rows_init) additional_rows = [ { "answers": [{ "text": "Answer-text 1 new data", "question": question_id, "reviewed": False }], "auxiliary_columns": ["ID 1", "Some other column value 1"] # The values of the additional columns: Needs to be in same order as auxiliary_column_names of survey }, { "answers": [{ "text": "Answer-text 2 new data", "question": question_id, "reviewed": False }], "auxiliary_columns": ["ID 1", "Some other column value 1"] } ] try: new_answers = client.addRowsToProject( new_project.id, [Row.from_json(r) for r in additional_rows], upload_async=False, request_training=True ) answers = client.listAnswers(question_id, no_group=True) assert len(rows_init) + len(additional_rows) == len(answers) finally: _ = client.deleteProject(new_project.id) assert num_projects_before == len(client.listProjects()) def test_workflow_async(client): codebook = [ { 'id': 1, 'label': 'Code 1', 'category': 'CATEGORY 1' }, { 'id': 20, 'label': 'Code 2', 'category': 'CATEGORY 2' } ] questions = [{'name': 'Question 1', 'codebook': codebook}] # make sure to have at least 15 answers reviewed to enble predictions rows_init = [ { "answers": [{ "text": "Answer-text 1", "question": "Question 1", "codes": [1, 20], "reviewed": True }], "auxiliary_columns": ["ID 1", "Some other column value 1"] # The values of the additional columns: Needs to be in same order as auxiliary_column_names of survey }, { "answers": [{ "text": "Answer-text 2", "question": "Question 1", "codes": [1], "reviewed": True }], "auxiliary_columns": ["ID 1", "Some other column value 1"] }, { "answers": [{ "text": "Answer-text 3", "question": "Question 1", "codes": [20], "reviewed": True }], "auxiliary_columns": ["ID 1", "Some other column value 1"] }, { "answers": [{ "text": "Answer-text 4", "question": "Question 1", "codes": [20], "reviewed": True }], "auxiliary_columns": ["ID 1", "Some other column value 1"] }, { "answers": [{ "text": "Answer-text 5", "question": "Question 1", "codes": [1, 20], "reviewed": True }], "auxiliary_columns": ["ID 1", "Some other column value 1"] }, { "answers": [{ "text": "Answer-text 6", "question": "Question 1", "codes": [1], "reviewed": True }], "auxiliary_columns": ["ID 1", "Some other column value 1"] }, { "answers": [{ "text": "Answer-text 7", "question": "Question 1", "codes": [1, 20], "reviewed": True }], "auxiliary_columns": ["ID 1", "Some other column value 1"] }, { "answers": [{ "text": "Answer-text 8", "question": "Question 1", "reviewed": False }], "auxiliary_columns": ["ID 1", "Some other column value 1"] }, { "answers": [{ "text": "Answer-text 9", "question": "Question 1", "reviewed": False }], "auxiliary_columns": ["ID 1", "Some other column value 1"] } ] num_projects_before = len(client.listProjects()) questions = [Question.from_json(q) for q in questions] rows_init = [Row.from_json(row_init) for row_init in rows_init] new_project = client.createProject( name="My new project", language="de", auxiliary_column_names=['ID', 'some other column'], translate=True, questions=questions, rows=rows_init, upload_async=True, request_training=True ) assert isinstance(new_project, Project) try: # wait a bit since this is async upload time.sleep(10) num_projects_after = len(client.listProjects()) assert num_projects_after == num_projects_before + 1 assert len(new_project.questions) == 1 created_rows = client.listRows(new_project.id) question_id = new_project.questions[0].id n_not_reviewed_init = len([row for row in rows_init if not row.answers[0].reviewed]) n_not_reviewed_after_create = len([row for row in created_rows if not row.answers[0].reviewed]) assert n_not_reviewed_after_create == n_not_reviewed_init additional_rows = [ { "answers": [{ "text": "Answer-text 1 new data", "question": question_id, "reviewed": False }], "auxiliary_columns": ["ID 1", "Some other column value 1"] # The values of the additional columns: Needs to be in same order as auxiliary_column_names of survey }, { "answers": [{ "text": "Answer-text 2 new data", "question": question_id, "reviewed": False }], "auxiliary_columns": ["ID 1", "Some other column value 1"] } ] new_rows = client.addRowsToProject( new_project.id, [Row.from_json(r) for r in additional_rows], upload_async=True, request_training=False ) print(new_rows) time.sleep(10) answers = client.listAnswers(question_id, no_group=True) assert len(rows_init) + len(additional_rows) == len(answers) finally: _ = client.deleteProject(new_project.id) assert num_projects_before == len(client.listProjects())

34.635135

125

0.508974

1,031

10,252

4.900097

0.133851

0.011283

0.053444

0.066508

0.839272

0.809778

0.778306

0.77118

0.750594

0

0.018389

0.374073

10,252

295

126

34.752542

0.768895

0.055892

0

0.64794

0

0.192017

0

0.052434

1

0.022472

false

0

0.011236

0

0.037453

0.003745

0

null

0

1

0

null

0

6

3773af5b92a111793719ea64067c87f71aee7000

199

py

Python

hoa/forms.py

kokopelli314/hoa2

4923c28007ae81fa656fbe733b087c719051bd01

[ "BSD-2-Clause" ]

null

hoa/forms.py

kokopelli314/hoa2

4923c28007ae81fa656fbe733b087c719051bd01

[ "BSD-2-Clause" ]

1

2021-06-02T00:43:16.000Z

hoa/forms.py

kokopelli314/hoa2

4923c28007ae81fa656fbe733b087c719051bd01

[ "BSD-2-Clause" ]

null

from flask_wtf import FlaskForm from wtforms import StringField, PasswordField, SubmitField from wtforms.validators import DataRequired, Email, EqualTo, ValidationError from hoa.models import User

28.428571

76

0.849246

24

199

7

0.708333

0.130952

0

0.115578

199

6

77

33.166667

0.954545

0

1

0

true

0.25

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

37cba0234db3b441f2ef025e8bba69b246e80cc1

9,144

py

Python

oxe-api/test/resource/cron/test_run_database_compliance.py

CybersecurityLuxembourg/openxeco

8d4e5578bde6a07f5d6d569b16b4de224abf7bf0

[ "BSD-2-Clause" ]

null

oxe-api/test/resource/cron/test_run_database_compliance.py

CybersecurityLuxembourg/openxeco

8d4e5578bde6a07f5d6d569b16b4de224abf7bf0

[ "BSD-2-Clause" ]

null

oxe-api/test/resource/cron/test_run_database_compliance.py

CybersecurityLuxembourg/openxeco

8d4e5578bde6a07f5d6d569b16b4de224abf7bf0

[ "BSD-2-Clause" ]

null

from test.BaseCase import BaseCase class TestRunDatabaseCompliance(BaseCase): @BaseCase.login @BaseCase.grant_access("/cron/run_database_compliance") def test_ok_company_without_data(self, token): s = self.db.tables["Setting"] self.db.insert({"id": 1, "name": "Company"}, self.db.tables["Company"]) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_CREATION_DATE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_WEBSITE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_IMAGE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_POSTAL_ADDRESS", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITH_POSTAL_ADDRESS_MISSING_GEOLOCATION", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_PHONE_NUMBER", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_EMAIL_ADDRESS", "value": "TRUE"}, s) response = self.application.post('/cron/run_database_compliance', headers=self.get_standard_post_header(token)) data_controls = self.db.get(self.db.tables["DataControl"]) self.assertEqual(200, response.status_code) self.assertEqual(data_controls[0].category, 'DATABASE COMPLIANCE') self.assertEqual(data_controls[0].value, "Value 'creation_date' of <COMPANY:1> is empty") self.assertEqual(data_controls[1].category, 'DATABASE COMPLIANCE') self.assertEqual(data_controls[1].value, "Value 'website' of <COMPANY:1> is empty") self.assertEqual(data_controls[2].category, 'DATABASE COMPLIANCE') self.assertEqual(data_controls[2].value, "Value 'image' of <COMPANY:1> is empty") self.assertEqual(data_controls[3].category, 'DATABASE COMPLIANCE') self.assertEqual(data_controls[3].value, '<COMPANY:1> has no address registered') self.assertEqual(data_controls[4].category, 'DATABASE COMPLIANCE') self.assertEqual(data_controls[4].value, '<COMPANY:1> has no phone number registered as a contact') self.assertEqual(data_controls[5].category, 'DATABASE COMPLIANCE') self.assertEqual(data_controls[5].value, '<COMPANY:1> has no email address registered as a contact') @BaseCase.login @BaseCase.grant_access("/cron/run_database_compliance") def test_ok_company_with_all_contact_and_address_data(self, token): s = self.db.tables["Setting"] self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_CREATION_DATE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_WEBSITE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_IMAGE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_POSTAL_ADDRESS", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITH_POSTAL_ADDRESS_MISSING_GEOLOCATION", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_PHONE_NUMBER", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ENTITIES_WITHOUT_EMAIL_ADDRESS", "value": "TRUE"}, s) self.db.insert({"id": 11, "thumbnail": bytes("", 'utf8'), "width": 12, "height": 12, "creation_date": "2020-01-01"}, self.db.tables["Image"]) self.db.insert({"id": 1, "name": "Company", "website": "", "image": 11, "creation_date": "2020-01-01", "description": "desc"}, self.db.tables["Company"]) self.db.insert({"id": 21, "company_id": 1, "type": "EMAIL ADDRESS", "representative": "ENTITY", "value": "mail@example.com"}, self.db.tables["CompanyContact"]) self.db.insert({"id": 22, "company_id": 1, "type": "PHONE NUMBER", "representative": "ENTITY", "value": "045065561"}, self.db.tables["CompanyContact"]) self.db.insert({"id": 31, "company_id": 1, "address_1": "", "city": "", "country": "", "latitude": 1, "longitude": 1}, self.db.tables["Company_Address"]) response = self.application.post('/cron/run_database_compliance', headers=self.get_standard_post_header(token)) data_controls = self.db.get(self.db.tables["DataControl"]) self.assertEqual(200, response.status_code) self.assertEqual(len(data_controls), 0) @BaseCase.login @BaseCase.grant_access("/cron/run_database_compliance") def test_ok_news_with_no_data(self, token): s = self.db.tables["Setting"] self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_TITLE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_HANDLE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_PUBLICATION_DATE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_START_DATE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_END_DATE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_CONTENT", "value": "TRUE"}, s) self.db.insert({"id": 1, "title": "My article", "type": "NEWS"}, self.db.tables["Article"]) response = self.application.post('/cron/run_database_compliance', headers=self.get_standard_post_header(token)) data_controls = self.db.get(self.db.tables["DataControl"]) self.assertEqual(200, response.status_code) self.assertEqual(len(data_controls), 2) self.assertEqual(data_controls[0].category, 'DATABASE COMPLIANCE') self.assertEqual(data_controls[0].value, "Value 'handle' of article <ARTICLE:1> is empty") self.assertEqual(data_controls[1].category, 'DATABASE COMPLIANCE') self.assertEqual(data_controls[1].value, "<ARTICLE:1> has no main version and no link") @BaseCase.login @BaseCase.grant_access("/cron/run_database_compliance") def test_ok_news_with_empty_main_version(self, token): s = self.db.tables["Setting"] self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_TITLE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_HANDLE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_PUBLICATION_DATE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_START_DATE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_END_DATE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_CONTENT", "value": "TRUE"}, s) self.db.insert({"id": 1, "title": "My article", "type": "NEWS", "handle": "my_article", "publication_date": "2020-01-01"}, self.db.tables["Article"]) self.db.insert({"id": 1, "article_id": 1, "name": "Version 0", "is_main": 1}, self.db.tables["ArticleVersion"]) response = self.application.post('/cron/run_database_compliance', headers=self.get_standard_post_header(token)) data_controls = self.db.get(self.db.tables["DataControl"]) self.assertEqual(200, response.status_code) self.assertEqual(len(data_controls), 1) self.assertEqual(data_controls[0].category, 'DATABASE COMPLIANCE') self.assertEqual(data_controls[0].value, "<ARTICLE:1> has an empty main version and no link") @BaseCase.login @BaseCase.grant_access("/cron/run_database_compliance") def test_ok_news_with_all_data(self, token): s = self.db.tables["Setting"] self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_TITLE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_HANDLE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_PUBLICATION_DATE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_START_DATE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_END_DATE", "value": "TRUE"}, s) self.db.insert({"property": "HIGHLIGHT_ARTICLE_WITHOUT_CONTENT", "value": "TRUE"}, s) self.db.insert({"id": 1, "title": "My article", "type": "NEWS", "handle": "my_article", "publication_date": "2020-01-01"}, self.db.tables["Article"]) self.db.insert({"id": 1, "article_id": 1, "name": "Version 0", "is_main": 1}, self.db.tables["ArticleVersion"]) self.db.insert({"id": 1, "article_version_id": 1, "position": 1, "type": "TITLE1", "content": "title 1"}, self.db.tables["ArticleBox"]) response = self.application.post('/cron/run_database_compliance', headers=self.get_standard_post_header(token)) data_controls = self.db.get(self.db.tables["DataControl"]) self.assertEqual(200, response.status_code) self.assertEqual(len(data_controls), 0)

63.062069

119

0.653871

1,104

9,144

5.201087

0.10779

0.07419

0.091954

0.111459

0.886451

0.861372

0.857541

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0.784396

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0.182196

9,144

144

120

63.5

0.751003

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0.689655

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0.3715

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0.232759

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0.043103

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0.060345

0

null

0

1

0

null

0

6

8066e6022b3a6a7838fad6b070a55ef6df66c77e

340

py

Python

OPTUS/Basics/OptusTest.py

dehimmi/OptusPOC

16736af9a5d21afb7f3cbe7a2e0d55f0a12c174b

[ "bzip2-1.0.6" ]

null

OPTUS/Basics/OptusTest.py

dehimmi/OptusPOC

16736af9a5d21afb7f3cbe7a2e0d55f0a12c174b

[ "bzip2-1.0.6" ]

null

OPTUS/Basics/OptusTest.py

dehimmi/OptusPOC

16736af9a5d21afb7f3cbe7a2e0d55f0a12c174b

[ "bzip2-1.0.6" ]

null

import pytest def test_pass(): assert 1+1 == 3 #client.write_points(result, database='pythondb', time_precision='ms') # python -m pytest test_example.py --pytest-influxdb --influxdb_host=localhost --influxdb_name=pythondb # python -m pytest test_example.py --pytest-influxdb --influxdb_host=52.63.126.230 --influxdb_name=pythondb

26.153846

107

0.758824

49

340

5.081633

0.591837

0.056225

0.104418

0.136546

0.417671

0

0.042904

0.108824

340

12

108

28.333333

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0

0.333333

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0.333333

true

0.333333

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0.666667

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null

0

1

0

null

0

1

0

1

0

6

80768fb116752851f78498170f9d037461438e5e

8,821

py

Python

kooplex-proxy/proxy/models.py

enasequence/covid-workflow-manager

185899b236f925dadb45ea5f224713202c4e7b00

[ "Apache-2.0" ]

5

2020-06-29T19:50:36.000Z

2022-01-31T09:16:29.000Z

kooplex-proxy/proxy/models.py

enasequence/covid-workflow-manager

185899b236f925dadb45ea5f224713202c4e7b00

[ "Apache-2.0" ]

10

2020-06-29T19:48:57.000Z

2022-02-13T11:54:06.000Z

kooplex-proxy/proxy/models.py

enasequence/covid-workflow-manager

185899b236f925dadb45ea5f224713202c4e7b00

[ "Apache-2.0" ]

2

2020-06-25T13:40:52.000Z

2021-02-03T20:23:09.000Z

from sqlalchemy import Boolean, Column, ForeignKey, Integer, String from sqlalchemy.dialects.postgresql import DOUBLE_PRECISION, TEXT, TIMESTAMP, \ VARCHAR, INTEGER, REAL, BOOLEAN, DATE from database import Base class CovidCountryWeekly(Base): __tablename__ = "ecdc_covid_country_weekly" iso_a3 = Column(TEXT, primary_key=True) iso_a2 = Column(TEXT, primary_key=True) country_name = Column(TEXT, primary_key=True) country_name_local = Column(TEXT, primary_key=True) date_year = Column(DOUBLE_PRECISION, primary_key=True) date_week = Column(DOUBLE_PRECISION, primary_key=True) ecdc_covid_country_weekly_cases = Column(DOUBLE_PRECISION, primary_key=True) ecdc_covid_country_weekly_deaths = Column(DOUBLE_PRECISION, primary_key=True) class UniqueVCFAppend(Base): __tablename__ = "unique_vcf_append" insertion_ts = Column(TIMESTAMP, primary_key=True) ena_run = Column(VARCHAR, primary_key=True) snapshot = Column(VARCHAR, primary_key=True) integrity = Column(INTEGER, primary_key=True) class VCFAll(Base): __tablename__ = "vcf_all" ena_run = Column(VARCHAR, primary_key=True) chrom = Column(TEXT, primary_key=True) pos = Column(INTEGER, primary_key=True) ref = Column(TEXT, primary_key=True) alt = Column(TEXT, primary_key=True) qual = Column(INTEGER, primary_key=True) filter = Column(TEXT, primary_key=True) dp = Column(INTEGER, primary_key=True) af = Column(REAL, primary_key=True) sb = Column(INTEGER, primary_key=True) count_ref_forward_base = Column(INTEGER, primary_key=True) count_ref_reverse_base = Column(INTEGER, primary_key=True) count_alt_forward_base = Column(INTEGER, primary_key=True) count_alt_reverse_base = Column(INTEGER, primary_key=True) hrun = Column(INTEGER, primary_key=True) indel = Column(BOOLEAN, primary_key=True) lof = Column(TEXT, primary_key=True) nmd = Column(TEXT, primary_key=True) ann_num = Column(INTEGER, primary_key=True) annotation = Column(TEXT, primary_key=True) annotation_impact = Column(TEXT, primary_key=True) gene_name = Column(TEXT, primary_key=True) gene_id = Column(TEXT, primary_key=True) feature_type = Column(TEXT, primary_key=True) feature_id = Column(TEXT, primary_key=True) transcript_biotype = Column(TEXT, primary_key=True) rank_ = Column(TEXT, primary_key=True) hgvs_c = Column(TEXT, primary_key=True) hgvs_p = Column(TEXT, primary_key=True) cdna_pos__cdna_length = Column(TEXT, primary_key=True) cds_pos__cds_length = Column(TEXT, primary_key=True) aa_pos__aa_length = Column(TEXT, primary_key=True) distance = Column(INTEGER, primary_key=True) errors_warnings_info = Column(TEXT, primary_key=True) class Cov(Base): __tablename__ = "cov" ena_run = Column(VARCHAR, primary_key=True) pos = Column(INTEGER, primary_key=True) coverage = Column(INTEGER, primary_key=True) class Meta(Base): __tablename__ = "meta" ena_run = Column(VARCHAR, primary_key=True) collection_date = Column(DATE, primary_key=True) clean_country = Column(TEXT, primary_key=True) clean_host = Column(TEXT, primary_key=True) accession = Column(TEXT, primary_key=True) sample_accession = Column(TEXT, primary_key=True) experiment_accession = Column(TEXT, primary_key=True) study_accession = Column(TEXT, primary_key=True) description = Column(TEXT, primary_key=True) country = Column(TEXT, primary_key=True) first_created = Column(DATE, primary_key=True) first_public = Column(DATE, primary_key=True) host = Column(TEXT, primary_key=True) host_sex = Column(TEXT, primary_key=True) host_tax_id = Column(INTEGER, primary_key=True) host_body_site = Column(TEXT, primary_key=True) bio_material = Column(TEXT, primary_key=True) culture_collection = Column(TEXT, primary_key=True) instrument_model = Column(TEXT, primary_key=True) instrument_platform = Column(TEXT, primary_key=True) library_layout = Column(TEXT, primary_key=True) library_name = Column(TEXT, primary_key=True) library_selection = Column(TEXT, primary_key=True) library_source = Column(TEXT, primary_key=True) library_strategy = Column(TEXT, primary_key=True) sequencing_method = Column(TEXT, primary_key=True) isolate = Column(TEXT, primary_key=True) strain = Column(TEXT, primary_key=True) base_count = Column(DOUBLE_PRECISION, primary_key=True) collected_by = Column(TEXT, primary_key=True) broker_name = Column(TEXT, primary_key=True) center_name = Column(TEXT, primary_key=True) sample_capture_status = Column(TEXT, primary_key=True) fastq_ftp = Column(TEXT, primary_key=True) collection_date_submitted = Column(TEXT, primary_key=True) checklist = Column(TEXT, primary_key=True) clean_collection_date = Column(DATE, primary_key=True) date_isoweek = Column(INTEGER, primary_key=True) date_isoyear = Column(INTEGER, primary_key=True) class UniqueCovAppend(Base): __tablename__ = "unique_cov_append" insertion_ts = Column(TIMESTAMP, primary_key=True) ena_run = Column(VARCHAR, primary_key=True) snapshot = Column(VARCHAR, primary_key=True) integrity = Column(INTEGER, primary_key=True) class LineageDef(Base): __tablename__ = "lineage_def" variant_id = Column(TEXT, primary_key=True) pango = Column(TEXT, primary_key=True) nextstrain = Column(TEXT, primary_key=True) ref_pos_alt = Column(TEXT, primary_key=True) codon_change = Column(TEXT, primary_key=True) gene = Column(TEXT, primary_key=True) pos = Column(DOUBLE_PRECISION, primary_key=True) predicted_effect = Column(TEXT, primary_key=True) protein = Column(TEXT, primary_key=True) protein_codon_position = Column(DOUBLE_PRECISION, primary_key=True) ref = Column(TEXT, primary_key=True) type = Column(TEXT, primary_key=True) alt = Column(TEXT, primary_key=True) amino_acid_change = Column(TEXT, primary_key=True) description = Column(TEXT, primary_key=True) snp_codon_position = Column(TEXT, primary_key=True) class Operation(Base): __tablename__ = "operation" event_ts = Column(TIMESTAMP, primary_key=True) last_stage = Column(INTEGER, primary_key=True) last_exit_code = Column(INTEGER, primary_key=True) stage = Column(INTEGER, primary_key=True) exit_code = Column(INTEGER, primary_key=True) extra_info = Column(TEXT, primary_key=True) class UniqueCov(Base): __tablename__ = "unique_cov" insertion_ts = Column(TIMESTAMP, primary_key=True) ena_run = Column(VARCHAR, primary_key=True) snapshot = Column(VARCHAR, primary_key=True) integrity = Column(INTEGER, primary_key=True) class UniqueVCF(Base): __tablename__ = "unique_vcf" insertion_ts = Column(TIMESTAMP, primary_key=True) ena_run = Column(VARCHAR, primary_key=True) snapshot = Column(VARCHAR, primary_key=True) integrity = Column(INTEGER, primary_key=True) class VCFAllAppend(Base): __tablename__ = "vcf_all_append" ena_run = Column(TEXT, primary_key=True) chrom = Column(TEXT, primary_key=True) pos = Column(INTEGER, primary_key=True) ref = Column(TEXT, primary_key=True) alt = Column(TEXT, primary_key=True) qual = Column(INTEGER, primary_key=True) filter = Column(TEXT, primary_key=True) dp = Column(INTEGER, primary_key=True) af = Column(REAL, primary_key=True) sb = Column(INTEGER, primary_key=True) count_ref_forward_base = Column(INTEGER, primary_key=True) count_ref_reverse_base = Column(INTEGER, primary_key=True) count_alt_forward_base = Column(INTEGER, primary_key=True) count_alt_reverse_base = Column(INTEGER, primary_key=True) hrun = Column(INTEGER, primary_key=True) indel = Column(BOOLEAN, primary_key=True) lof = Column(TEXT, primary_key=True) nmd = Column(TEXT, primary_key=True) ann_num = Column(INTEGER, primary_key=True) annotation = Column(TEXT, primary_key=True) annotation_impact = Column(TEXT, primary_key=True) gene_name = Column(TEXT, primary_key=True) gene_id = Column(TEXT, primary_key=True) feature_type = Column(TEXT, primary_key=True) feature_id = Column(TEXT, primary_key=True) transcript_biotype = Column(TEXT, primary_key=True) rank_ = Column(TEXT, primary_key=True) hgvs_c = Column(TEXT, primary_key=True) hgvs_p = Column(TEXT, primary_key=True) cdna_pos__cdna_length = Column(TEXT, primary_key=True) cds_pos__cds_length = Column(TEXT, primary_key=True) aa_pos__aa_length = Column(TEXT, primary_key=True) distance = Column(INTEGER, primary_key=True) errors_warnings_info = Column(TEXT, primary_key=True)

42.613527

79

0.733817

1,181

8,821

5.165114

0.134632

0.255738

0.358033

0.295082

0.84377

0.768033

0.589508

0.53082

0.516885

0

0.000273

0.168688

8,821

206

80

42.820388

0.831583

0

0.5

0

0.014397

0.002834

0

1

0

false

0

0.016304

0

0.983696

0

null

1

0

null

0

1

0

6

80975bf10593e83235a256eff4cbffc2d218152a

1,467

py

Python

segme/model/cascade_psp/loss.py

shkarupa-alex/segme

d5bc0043f9e709c8ccaf8949d662bc6fd6144006

[ "MIT" ]

2

2021-05-25T18:53:00.000Z

2021-05-26T12:11:41.000Z

segme/model/cascade_psp/loss.py

shkarupa-alex/segme

d5bc0043f9e709c8ccaf8949d662bc6fd6144006

[ "MIT" ]

null

segme/model/cascade_psp/loss.py

shkarupa-alex/segme

d5bc0043f9e709c8ccaf8949d662bc6fd6144006

[ "MIT" ]

2

2021-11-21T02:39:37.000Z

2021-12-08T07:26:56.000Z

from keras.losses import MeanAbsoluteError, MeanSquaredError, BinaryCrossentropy from ...loss import SobelEdgeLoss, WeightedLossFunctionWrapper def _loss_224(y_true, y_pred, sample_weight=None): return MeanAbsoluteError()(y_true, y_pred, sample_weight) + \ MeanSquaredError()(y_true, y_pred, sample_weight) + \ 5. * SobelEdgeLoss()(y_true, y_pred, sample_weight) def _loss_28(y_true, y_pred, sample_weight=None): return BinaryCrossentropy()(y_true, y_pred, sample_weight) def _loss_56(y_true, y_pred, sample_weight=None): return .5 * BinaryCrossentropy()(y_true, y_pred, sample_weight) + \ .25 * MeanAbsoluteError()(y_true, y_pred, sample_weight) + \ .25 * MeanSquaredError()(y_true, y_pred, sample_weight) def _loss_28_2(y_true, y_pred, sample_weight=None): return BinaryCrossentropy()(y_true, y_pred, sample_weight) def _loss_28_3(y_true, y_pred, sample_weight=None): return BinaryCrossentropy()(y_true, y_pred, sample_weight) def _loss_56_2(y_true, y_pred, sample_weight=None): return .5 * BinaryCrossentropy()(y_true, y_pred, sample_weight) + \ .25 * MeanAbsoluteError()(y_true, y_pred, sample_weight) + \ .25 * MeanSquaredError()(y_true, y_pred, sample_weight) def total_losses(): return [_loss_224, _loss_56_2, _loss_28_3, _loss_56, _loss_28_2, _loss_28] def cascade_psp_losses(): return [WeightedLossFunctionWrapper(tl) for tl in total_losses()]

35.780488

80

0.731425

203

1,467

4.852217

0.152709

0.091371

0.109645

0.182741

0.715736

0.637563

0.605076

0.563452

0

0.034874

0.159509

1,467

40

81

36.675

0.76399

0

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0

1

0.333333

false

0

0.083333

0.333333

0.75

0

null

0

1

0

1

0

null

0

1

0

1

0

6

80caeb658d081ea0b3726b9bab9210e4cf442b67

556

py

Python

unb_cli/venv.py

jacktrades/unb-cli

51cb451fc66352ca85ded03bfbc3bf01913f33ca

[ "MIT" ]

null

unb_cli/venv.py

jacktrades/unb-cli

51cb451fc66352ca85ded03bfbc3bf01913f33ca

[ "MIT" ]

null

unb_cli/venv.py

jacktrades/unb-cli

51cb451fc66352ca85ded03bfbc3bf01913f33ca

[ "MIT" ]

null

"""Utilities for working with virtual environments.""" import sys def in_venv(): # NOTE: # If you are using virtualenv (github.com/pypa/virtualenv), this answer is # equally correct for Python 2 or Python 3. If you are using pyvenv # (legacy.python.org/dev/peps/pep-0405), a virtualenv-equivalent built into # Python 3.3+ (but not the same thing as virtualenv), then it uses # sys.base_prefix instead of sys.real_prefix, and sys.base_prefix always # exists; outside a pyvenv it is equal to sys.prefix. return hasattr(sys, 'real_prefix')

37.066667

77

0.735612

90

556

4.488889

0.688889

0.024752

0.039604

0.064356

0

0.017354

0.170863

556

14

78

39.714286

0.859002

0.820144

0

0.125

0

1

0.333333

true

0

0.333333

1

0

null

0

1

0

null

0

1

0

1

0

6

80f4c5da06f46f91e5327a5ff34e96af0a3891e2

1,015

py

Python

tests/test_mixin.py

thruflo/pyramid_basemodel

4fd264072b07b96f2413d7199a5c25f9229c9db0

[ "Unlicense" ]

9

2015-04-08T08:25:34.000Z

2020-07-20T11:59:49.000Z

tests/test_mixin.py

fizyk/pyramid_basemodel

63c1f78ad2c3cd9b00579ec00b6855adbabb531a

[ "Unlicense" ]

164

2020-07-31T12:49:48.000Z

2022-03-29T04:09:28.000Z

tests/test_mixin.py

thruflo/pyramid_basemodel

4fd264072b07b96f2413d7199a5c25f9229c9db0

[ "Unlicense" ]

8

2015-02-25T02:34:25.000Z

2020-03-17T11:51:10.000Z

from mock import Mock, patch from pyramid_basemodel.mixin import TouchMixin def test_touch_mixin(): """Check wether every argument of TouchMixin get's called in proper order.""" t = TouchMixin() saved_arg = [] def save_mock(instance): saved_arg.append(instance) assert not hasattr(t, "modified") with patch.object(t, "propagate_touch") as propagate_mock: t.touch(now=Mock, save=save_mock) assert propagate_mock.called assert hasattr(t, "modified") assert t == saved_arg[0] def test_touch_mixin_no_propagate(): """Check wether every argument of TouchMixin get's called in proper order.""" t = TouchMixin() saved_arg = [] def save_mock(instance): saved_arg.append(instance) assert not hasattr(t, "modified") with patch.object(t, "propagate_touch") as propagate_mock: t.touch(False, now=Mock, save=save_mock) assert not propagate_mock.called assert hasattr(t, "modified") assert t == saved_arg[0]

28.194444

81

0.683744

139

1,015

4.827338

0.28777

0.071535

0.09538

0.050671

0.825633

0.751118

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038241c72f04812024e5fbe27494cb84d327adb2

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py

Python

pybrain/structure/networks/custom/__init__.py

sveilleux1/pybrain

1e1de73142c290edb84e29ca7850835f3e7bca8b

[ "BSD-3-Clause" ]

2,208

2015-01-02T02:14:41.000Z

2022-03-31T04:45:46.000Z

pybrain/structure/networks/custom/__init__.py

sveilleux1/pybrain

1e1de73142c290edb84e29ca7850835f3e7bca8b

[ "BSD-3-Clause" ]

91

2015-01-08T16:42:16.000Z

2021-12-11T19:16:35.000Z

pybrain/structure/networks/custom/__init__.py

sveilleux1/pybrain

1e1de73142c290edb84e29ca7850835f3e7bca8b

[ "BSD-3-Clause" ]

786

2015-01-02T15:18:20.000Z

2022-02-23T23:42:40.000Z

from .capturegame import CaptureGameNetwork

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py

Python

extensions/__init__.py

apockill/webcam-ml

f001688cf891c44b407823cc866d8ae9bdc4c51b

[ "MIT" ]

null

extensions/__init__.py

apockill/webcam-ml

f001688cf891c44b407823cc866d8ae9bdc4c51b

[ "MIT" ]

null

extensions/__init__.py

apockill/webcam-ml

f001688cf891c44b407823cc866d8ae9bdc4c51b

[ "MIT" ]

null

from .only_masks import process as extension

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03c4a9ca9ba4c00d2dfa5e7c3472deed26895afd

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py

Python

scripts/npc/autogen_9400101.py

hsienjan/SideQuest-Server

3e88debaf45615b759d999255908f99a15283695

[ "MIT" ]

null

scripts/npc/autogen_9400101.py

hsienjan/SideQuest-Server

3e88debaf45615b759d999255908f99a15283695

[ "MIT" ]

null

scripts/npc/autogen_9400101.py

hsienjan/SideQuest-Server

3e88debaf45615b759d999255908f99a15283695

[ "MIT" ]

null

# ParentID: 9400101 # ObjectID: 1000047 # Character field ID when accessed: 100000000 # Object Position X: 2525 # Object Position Y: -199

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03d569e282af33d46631001a92eba1ea9afd1b88

79

py

Python

iotedgedev/version.py

vikas0212git/iotedgedev

ee6108b2cf8e9e006f83f19fcb1a94a65ffad93a

[ "MIT" ]

111

2018-04-09T18:24:30.000Z

2022-03-29T12:12:50.000Z

iotedgedev/version.py

nittaya1990/iotedgedev

d35c7d5d6112a1e26acb0104a577e59ea9378ca0

[ "MIT" ]

314

2018-04-09T19:59:27.000Z

2022-03-28T12:13:45.000Z

iotedgedev/version.py

nittaya1990/iotedgedev

d35c7d5d6112a1e26acb0104a577e59ea9378ca0

[ "MIT" ]

45

2018-04-09T21:52:23.000Z

2022-03-23T12:48:01.000Z

import sys PY35 = sys.version_info >= (3, 5) PY3 = sys.version_info >= (3, 0)

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03ffa9cb762f8e66ed624a1c7a14ce90642c1c54

48

py

Python

src/ekpmeasure/analysis/ppms/__init__.py

cjfinnell/ekpmeasure

e6611c053cad28e06f4f8a94764ebe3805cddb15

[ "MIT" ]

null

src/ekpmeasure/analysis/ppms/__init__.py

cjfinnell/ekpmeasure

e6611c053cad28e06f4f8a94764ebe3805cddb15

[ "MIT" ]

null

src/ekpmeasure/analysis/ppms/__init__.py

cjfinnell/ekpmeasure

e6611c053cad28e06f4f8a94764ebe3805cddb15

[ "MIT" ]

null

from ._load import * from ._data_funcs import *

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209b697412176cfed64eb622863bf6f4820fe0a3

14,098

py

Python

data_utils.py

plasmatiger/Adversary_ML

604f936abed54aa623f197cb100bbad7a3763732

[ "MIT" ]

null

data_utils.py

plasmatiger/Adversary_ML

604f936abed54aa623f197cb100bbad7a3763732

[ "MIT" ]

null

data_utils.py

plasmatiger/Adversary_ML

604f936abed54aa623f197cb100bbad7a3763732

[ "MIT" ]

null

from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import os import numpy as np from PIL import Image import skimage.io as skio from slic import slic_gaussian def read_image(address): #image = Image.open(add).resize((im_size, im_size)) image = Image.open(address) image = image.convert("RGB") image = np.array(image)/255.0 #image = image.reshape((1, im_size, im_size, 3)) return image def load_cifar(cache_dir): ''' Loads and returns CIFAR10 dataset Mode = 0 : Load from cached files (saves time) Mode = 1 : Load fresh by reading data from individual files ''' train_size = 40000 test_size = 10000 val_size = 10000 images_train = np.load(cache_dir + "/cifar_X_train.npy") images_test = np.load(cache_dir + "/cifar_X_test.npy") images_val = np.load(cache_dir + "/cifar_X_val.npy") labels_train = np.load(cache_dir + "/cifar_Y_train.npy") labels_test = np.load(cache_dir + "/cifar_Y_test.npy") labels_val = np.load(cache_dir + "/cifar_Y_val.npy") return images_train, images_test, images_val, labels_train, labels_test, labels_val def load_fashion_mnist(cache_dir): ''' Loads and returns Fashion MNIST dataset Mode = 0 : Load from cached files (saves time) Mode = 1 : Load fresh by reading data from individual files ''' train_size = 50000 test_size = 10000 val_size = 10000 images_train = np.load(cache_dir + "/fashion_X_train.npy") images_test = np.load(cache_dir + "/fashion_X_test.npy") images_val = np.load(cache_dir + "/fashion_X_val.npy") labels_train = np.load(cache_dir + "/fashion_Y_train.npy") labels_test = np.load(cache_dir + "/fashion_Y_test.npy") labels_val = np.load(cache_dir + "/fashion_Y_val.npy") return images_train, images_test, images_val, labels_train, labels_test, labels_val def load_cifar_sp(cache_dir): ''' Loads and returns CIFAR10 dataset Mode = 0 : Load from cached files (saves time) Mode = 1 : Load fresh by reading data from individual files ''' train_size = 40000 test_size = 10000 val_size = 10000 images_train = np.load(cache_dir + "/cifar_sp_X_train.npy") images_test = np.load(cache_dir + "/cifar_sp_X_test.npy") images_val = np.load(cache_dir + "/cifar_sp_X_val.npy") labels_train = np.load(cache_dir + "/cifar_sp_Y_train.npy") labels_test = np.load(cache_dir + "/cifar_sp_Y_test.npy") labels_val = np.load(cache_dir + "/cifar_sp_Y_val.npy") return images_train, images_test, images_val, labels_train, labels_test, labels_val def load_fashion_mnist_sp(cache_dir): ''' Loads and returns Fashion MNIST dataset Mode = 0 : Load from cached files (saves time) Mode = 1 : Load fresh by reading data from individual files ''' train_size = 50000 test_size = 10000 val_size = 10000 images_train = np.load(cache_dir + "/fashion_sp_X_train.npy") images_test = np.load(cache_dir + "/fashion_sp_X_test.npy") images_val = np.load(cache_dir + "/fashion_sp_X_val.npy") labels_train = np.load(cache_dir + "/fashion_sp_Y_train.npy") labels_test = np.load(cache_dir + "/fashion_sp_Y_test.npy") labels_val = np.load(cache_dir + "/fashion_sp_Y_val.npy") return images_train, images_test, images_val, labels_train, labels_test, labels_val def cache_cifar(base_dir, cache_dir): # Metadata num_classes = 10 train_size = 40000 test_size = 10000 val_size = 10000 im_chan = 3 im_size = 32 clas_names = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck'] clas_dict = {'airplane':0, 'automobile':1, 'bird':2, 'cat':3, 'deer':4, 'dog':5, 'frog':6, 'horse':7, 'ship':8, 'truck':9} classes = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'] all_train_img_add = [] all_train_labels = [] train_img_add = [] train_labels = [] test_img_add = [] test_labels = [] val_img_add = [] val_labels = [] # Reading file lists im_dir = base_dir + "train/" for root, dirs, files in os.walk(im_dir): for name in files: add = im_dir + name all_train_img_add.append(add) for clas in clas_names: if clas in add: all_train_labels.append(clas_dict[clas]) im_dir = base_dir + "test/" for root, dirs, files in os.walk(im_dir): for name in files: add = im_dir + name test_img_add.append(add) for clas in clas_names: if clas in add: test_labels.append(clas_dict[clas]) a = list(range(len(all_train_img_add))) np.random.shuffle(a) for i in range(train_size): train_img_add.append(all_train_img_add[a[i]]) for i in range(train_size): train_labels.append(all_train_labels[a[i]]) for i in range(train_size, train_size + val_size): val_img_add.append(all_train_img_add[a[i]]) for i in range(train_size, train_size + val_size): val_labels.append(all_train_labels[a[i]]) # Loop to load the data in Numpy array # Reading the training data ========================================== images_train = np.ndarray(shape=(train_size, im_size, im_size, im_chan)) labels_train = np.zeros(shape=(train_size, num_classes)) start = 0 end = train_size for ind, im_index in enumerate(range(start, end)): a = im_index images_train[ind, :, :, :] = read_image(train_img_add[im_index]) lab = train_labels[im_index] labels_train[ind, lab] = 1 # ==================================================================== # Reading the testing data =========================================== images_test = np.ndarray(shape=(test_size, im_size, im_size, im_chan)) labels_test = np.zeros(shape=(test_size, num_classes)) start = 0 end = test_size for ind, im_index in enumerate(range(start, end)): a =im_index images_test[ind, :, :, :] = read_image(test_img_add[im_index]) lab = test_labels[im_index] labels_test[ind, lab] = 1 # ==================================================================== # Reading the validation data ======================================== images_val = np.ndarray(shape=(val_size, im_size, im_size, im_chan)) labels_val = np.zeros(shape=(val_size, num_classes)) start = 0 end = val_size for ind, im_index in enumerate(range(start, end)): a =im_index images_val[ind, :, :, :] = read_image(val_img_add[im_index]) lab = val_labels[im_index] labels_val[ind, lab] = 1 # ==================================================================== # Save as numpy array ================================================ np.save(cache_dir + "/cifar_X_train.npy", images_train) np.save(cache_dir + "/cifar_X_test.npy" , images_test) np.save(cache_dir + "/cifar_X_val.npy" , images_val) np.save(cache_dir + "/cifar_Y_train.npy", labels_train) np.save(cache_dir + "/cifar_Y_test.npy" , labels_test) np.save(cache_dir + "/cifar_Y_val.npy" , labels_val) def cache_fashion_mnist(base_dir, cache_dir): # Metadata num_classes = 10 train_size = 50000 test_size = 10000 val_size = 10000 im_chan = 3 im_size = 28 classes = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'] # Reading file lists im_dir = base_dir + "/train/" train_img_add = [] train_labels = [] test_img_add = [] test_labels = [] val_img_add = [] val_labels = [] for ind, clas in enumerate(classes): im_dir = base_dir + "/train/" + clas for root, dirs, files in os.walk(im_dir): for name in files: add = im_dir + "/" + name train_img_add.append(add) train_labels.append(ind) im_dir = base_dir + "/test/" + clas for root, dirs, files in os.walk(im_dir): for name in files: add = im_dir + "/" + name test_img_add.append(add) test_labels.append(ind) im_dir = base_dir + "/val/" + clas for root, dirs, files in os.walk(im_dir): for name in files: add = im_dir + "/" + name val_img_add.append(add) val_labels.append(ind) # Loop to load the data in Numpy array # Reading the training data ========================================== images_train = np.ndarray(shape=(train_size, im_size, im_size, im_chan)) labels_train = np.zeros(shape=(train_size, num_classes)) start = 0 end = train_size for ind, im_index in enumerate(range(start, end)): a = im_index images_train[ind, :, :, :] = read_image(train_img_add[im_index]) lab = train_labels[im_index] labels_train[ind, lab] = 1 # ==================================================================== # Reading the testing data =========================================== images_test = np.ndarray(shape=(test_size, im_size, im_size, im_chan)) labels_test = np.zeros(shape=(test_size, num_classes)) start = 0 end = test_size for ind, im_index in enumerate(range(start, end)): a =im_index images_test[ind, :, :, :] = read_image(test_img_add[im_index]) lab = test_labels[im_index] labels_test[ind, lab] = 1 # ==================================================================== # Reading the validation data ======================================== images_val = np.ndarray(shape=(val_size, im_size, im_size, im_chan)) labels_val = np.zeros(shape=(val_size, num_classes)) start = 0 end = val_size for ind, im_index in enumerate(range(start, end)): a =im_index images_val[ind, :, :, :] = read_image(val_img_add[im_index]) lab = val_labels[im_index] labels_val[ind, lab] = 1 # ==================================================================== # Save as numpy array ================================================ np.save(cache_dir + "/fashion_X_train.npy", images_train) np.save(cache_dir + "/fashion_X_test.npy" , images_test) np.save(cache_dir + "/fashion_X_val.npy" , images_val) np.save(cache_dir + "/fashion_Y_train.npy", labels_train) np.save(cache_dir + "/fashion_Y_test.npy" , labels_test) np.save(cache_dir + "/fashion_Y_val.npy" , labels_val) def cache_cifar_sp(X_train, X_test, X_val, Y_train, Y_test, Y_val, cache_dir): slic_args = { 'n_segments' : 256, 'compactness' : 5, 'sigma' : 1, 'gaussian_filter' : 0 } images_train = np.ndarray(shape=X_train.shape) images_test = np.ndarray(shape=X_test.shape) images_val = np.ndarray(shape=X_val.shape) l = X_train.shape[0] for i in range(l): # Generating SLIC images images_train[i, :, :, :] = slic_gaussian(image=X_train[i, :, :, :], args=slic_args) print("Loop1") l = X_test.shape[0] for i in range(l): # Generating SLIC images images_test[i, :, :, :] = slic_gaussian(image=X_test[i, :, :, :], args=slic_args) ima = images_test[i, :, :, :] skio.imsave("./sample/slic/cifar/" + str(i) + ".png", ima) print("Loop2") l = X_val.shape[0] for i in range(l): # Generating SLIC images images_val[i, :, :, :] = slic_gaussian(image=X_val[i, :, :, :], args=slic_args) print("Loop3") labels_train = np.copy(Y_train) labels_test = np.copy(Y_test) labels_val = np.copy(Y_val) # Save as numpy array ================================================ np.save(cache_dir + "/cifar_sp_X_train.npy", images_train) np.save(cache_dir + "/cifar_sp_X_test.npy" , images_test) np.save(cache_dir + "/cifar_sp_X_val.npy" , images_val) np.save(cache_dir + "/cifar_sp_Y_train.npy", labels_train) np.save(cache_dir + "/cifar_sp_Y_test.npy" , labels_test) np.save(cache_dir + "/cifar_sp_Y_val.npy" , labels_val) def cache_fashion_sp(X_train, X_test, X_val, Y_train, Y_test, Y_val, cache_dir): slic_args = { 'n_segments' : 256, 'compactness' : 5, 'sigma' : 1, 'gaussian_filter' : 0 } images_train = np.ndarray(shape=X_train.shape) images_test = np.ndarray(shape=X_test.shape) images_val = np.ndarray(shape=X_val.shape) l = X_train.shape[0] for i in range(l): # Generating SLIC images images_train[i, :, :, :] = slic_gaussian(image=X_train[i, :, :, :], args=slic_args) print("Loop1") l = X_test.shape[0] for i in range(l): # Generating SLIC images images_test[i, :, :, :] = slic_gaussian(image=X_test[i, :, :, :], args=slic_args) ima = images_test[i, :, :, :] skio.imsave("./sample/slic/fashion/" + str(i) + ".png", ima) print("Loop2") l = X_val.shape[0] for i in range(l): # Generating SLIC images images_val[i, :, :, :] = slic_gaussian(image=X_val[i, :, :, :], args=slic_args) print("Loop3") labels_train = np.copy(Y_train) labels_test = np.copy(Y_test) labels_val = np.copy(Y_val) # Save as numpy array ================================================ np.save(cache_dir + "/fashion_sp_X_train.npy", images_train) np.save(cache_dir + "/fashion_sp_X_test.npy" , images_test) np.save(cache_dir + "/fashion_sp_X_val.npy" , images_val) np.save(cache_dir + "/fashion_sp_Y_train.npy", labels_train) np.save(cache_dir + "/fashion_sp_Y_test.npy" , labels_test) np.save(cache_dir + "/fashion_sp_Y_val.npy" , labels_val) ''' if __name__ == "__main__": print("Started!") X_train, X_test, X_val, Y_train, Y_test, Y_val = load_cifar("./cache") print("Loaded!") cache_cifar_sp(X_train, X_test, X_val, Y_train, Y_test, Y_val, "./cache") print("Done!") '''

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0.026119

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0

6

20b4f05855979e6da3839e203e556656092ea923

205

py

Python

prestify/__init__.py

omarkhd/prestify-client-py

8a7f08dde2a0986fff56bcbcbbdf61713f156667

[ "MIT" ]

null

prestify/__init__.py

omarkhd/prestify-client-py

8a7f08dde2a0986fff56bcbcbbdf61713f156667

[ "MIT" ]

null

prestify/__init__.py

omarkhd/prestify-client-py

8a7f08dde2a0986fff56bcbcbbdf61713f156667

[ "MIT" ]

null

# -*- coding: utf-8 -*- from prestify.client import Report try: from django.conf import settings Report.PRESTIFY_SERVICE_URL = settings.PRESTIFY_SERVICE_URL except (ImportError, AttributeError): pass

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20bb77e2f6bb8436105a15ba9425d049ae1d93ae

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py

Python

starwars/views.py

chrischongyj/NTU-Star-Wars

f26447035e6e18ad358787f4dd3f4116ac8e437f

[ "MIT" ]

null

starwars/views.py

chrischongyj/NTU-Star-Wars

f26447035e6e18ad358787f4dd3f4116ac8e437f

[ "MIT" ]

6

2020-06-06T00:02:01.000Z

2022-02-10T13:49:06.000Z

starwars/views.py

chrischongyj/NTU-Star-Wars

f26447035e6e18ad358787f4dd3f4116ac8e437f

[ "MIT" ]

null

from django.shortcuts import render from .models import CourseInfo def welcome(request): return render(request, './starwars/welcome.html', {'title': 'Welcome to End Star Wars'}) def havecourse(request): return render(request, './starwars/test.html') def addcourse(request): course_name = request.POST["course_name"] course_code = request.POST["course_code"] course_au = request.POST["course_au"] course_info = CourseInfo(course_name=course_name, course_code=course_code, course_au=course_au) course_info.save() all_courses = CourseInfo.objects.all() return render(request, './starwars/want.html', {'Courses': all_courses}) def selectcourse(request): course_name = request.POST["course_name"] course_code = request.POST["course_code"] course_au = request.POST["course_au"] my_obj = CourseInfo.objects.get(course_name=course_name, course_code=course_code, course_au=course_au) my_obj.delete() all_courses = CourseInfo.objects.all() return render(request, './starwars/want.html', {'Courses': all_courses}) def wantcourse(request): # course_name = request.POST["course_name"] # course_code = request.POST["course_code"] # course_au = request.POST["course_au"] # my_obj = CourseInfo.objects.get(course_name=course_name) # my_obj.delete() all_courses = CourseInfo.objects.all() return render(request, './starwars/want.html', {'Courses': all_courses})

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20f3987a5b3d131301ddcc31f04b60919e68ca94

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py

Python

app/tests/teams_tests/test_views.py

Tommos0/grand-challenge.org

187cd857f6a7c9651b7bda8c42c54801f071dd7c

[ "Apache-2.0" ]

null

app/tests/teams_tests/test_views.py

Tommos0/grand-challenge.org

187cd857f6a7c9651b7bda8c42c54801f071dd7c

[ "Apache-2.0" ]

null

app/tests/teams_tests/test_views.py

Tommos0/grand-challenge.org

187cd857f6a7c9651b7bda8c42c54801f071dd7c

[ "Apache-2.0" ]

null

import pytest from django.conf import settings from django.test import Client from tests.factories import TeamFactory, TeamMemberFactory from tests.utils import ( get_view_for_user, assert_viewname_status, assert_viewname_redirect, validate_admin_or_participant_view, validate_open_view, ) def validate_owner_or_admin_view( *, two_challenge_set, client: Client, **kwargs ): """ Assert that a view is only accessible to administrators or participants of that particular challenge """ # No user assert_viewname_redirect( redirect_url=settings.LOGIN_URL, challenge=two_challenge_set.ChallengeSet1.challenge, client=client, **kwargs, ) tests = [ (403, two_challenge_set.ChallengeSet1.non_participant), (200, two_challenge_set.ChallengeSet1.participant), (403, two_challenge_set.ChallengeSet1.participant1), (200, two_challenge_set.ChallengeSet1.creator), (200, two_challenge_set.ChallengeSet1.admin), (403, two_challenge_set.ChallengeSet2.non_participant), (403, two_challenge_set.ChallengeSet2.participant), (403, two_challenge_set.ChallengeSet2.participant1), (403, two_challenge_set.ChallengeSet2.creator), (403, two_challenge_set.ChallengeSet2.admin), (200, two_challenge_set.admin12), (403, two_challenge_set.participant12), (200, two_challenge_set.admin1participant2), ] for test in tests: assert_viewname_status( code=test[0], challenge=two_challenge_set.ChallengeSet1.challenge, client=client, user=test[1], **kwargs, ) def validate_member_owner_or_admin_view( *, two_challenge_set, client: Client, **kwargs ): """ Assert that a view is only accessible to administrators or participants of that particular challenge """ # No user assert_viewname_redirect( redirect_url=settings.LOGIN_URL, challenge=two_challenge_set.ChallengeSet1.challenge, client=client, **kwargs, ) tests = [ (403, two_challenge_set.ChallengeSet1.non_participant), (200, two_challenge_set.ChallengeSet1.participant), (200, two_challenge_set.ChallengeSet1.participant1), (200, two_challenge_set.ChallengeSet1.creator), (200, two_challenge_set.ChallengeSet1.admin), (403, two_challenge_set.ChallengeSet2.non_participant), (403, two_challenge_set.ChallengeSet2.participant), (403, two_challenge_set.ChallengeSet2.participant1), (403, two_challenge_set.ChallengeSet2.creator), (403, two_challenge_set.ChallengeSet2.admin), (200, two_challenge_set.admin12), (403, two_challenge_set.participant12), (200, two_challenge_set.admin1participant2), ] for test in tests: assert_viewname_status( code=test[0], challenge=two_challenge_set.ChallengeSet1.challenge, client=client, user=test[1], **kwargs, ) @pytest.mark.django_db @pytest.mark.parametrize( "view", ["teams:list", "teams:create", "teams:member-create"] ) def test_admin_or_participant_permissions(client, TwoChallengeSets, view): team = TeamFactory( challenge=TwoChallengeSets.ChallengeSet1.challenge, owner=TwoChallengeSets.ChallengeSet1.participant, ) if view in ("teams:detail", "teams:member-create"): pk = team.pk else: pk = None validate_admin_or_participant_view( viewname=view, reverse_kwargs={"pk": pk}, two_challenge_set=TwoChallengeSets, client=client, ) @pytest.mark.django_db def test_open_views(client, ChallengeSet): team = TeamFactory( challenge=ChallengeSet.challenge, owner=ChallengeSet.participant ) validate_open_view( viewname="teams:detail", reverse_kwargs={"pk": team.pk}, challenge_set=ChallengeSet, client=client, ) @pytest.mark.django_db @pytest.mark.parametrize("view", ["teams:update", "teams:delete"]) def test_team_update_delete_permissions(client, TwoChallengeSets, view): team = TeamFactory( challenge=TwoChallengeSets.ChallengeSet1.challenge, owner=TwoChallengeSets.ChallengeSet1.participant, ) TeamFactory( challenge=TwoChallengeSets.ChallengeSet1.challenge, owner=TwoChallengeSets.ChallengeSet1.participant1, ) validate_owner_or_admin_view( viewname=view, reverse_kwargs={"pk": team.pk}, two_challenge_set=TwoChallengeSets, client=client, ) @pytest.mark.django_db def test_team_member_delete_permissions(client, TwoChallengeSets): team = TeamFactory( challenge=TwoChallengeSets.ChallengeSet1.challenge, owner=TwoChallengeSets.ChallengeSet1.participant, ) team_member = TeamMemberFactory( team=team, user=TwoChallengeSets.ChallengeSet1.participant1 ) validate_member_owner_or_admin_view( viewname="teams:member-delete", reverse_kwargs={"pk": team_member.pk}, two_challenge_set=TwoChallengeSets, client=client, ) @pytest.mark.django_db @pytest.mark.parametrize("team_name", ["test_team_name"]) def test_team_creation(client, TwoChallengeSets, team_name): response = get_view_for_user( viewname="teams:create", challenge=TwoChallengeSets.ChallengeSet1.challenge, client=client, method=client.post, user=TwoChallengeSets.ChallengeSet1.participant, data={"name": team_name}, ) assert response.status_code == 302 response = get_view_for_user( url=response.url, client=client, user=TwoChallengeSets.ChallengeSet1.participant, ) assert response.status_code == 200 assert team_name in response.rendered_content @pytest.mark.django_db def test_team_member_addition(client, TwoChallengeSets): team = TeamFactory( challenge=TwoChallengeSets.ChallengeSet1.challenge, owner=TwoChallengeSets.ChallengeSet1.participant, ) assert TwoChallengeSets.ChallengeSet1.participant in team.get_members() assert ( TwoChallengeSets.ChallengeSet1.participant1 not in team.get_members() ) # Participant1 requests to join team response = get_view_for_user( viewname="teams:member-create", challenge=TwoChallengeSets.ChallengeSet1.challenge, client=client, method=client.post, user=TwoChallengeSets.ChallengeSet1.participant1, reverse_kwargs={"pk": team.pk}, ) assert TwoChallengeSets.ChallengeSet1.participant1 in team.get_members() assert response.status_code == 302 @pytest.mark.django_db def test_unique_membership(client, TwoChallengeSets): team = TeamFactory( challenge=TwoChallengeSets.ChallengeSet1.challenge, owner=TwoChallengeSets.ChallengeSet1.participant, ) team1 = TeamFactory( challenge=TwoChallengeSets.ChallengeSet1.challenge, owner=TwoChallengeSets.ChallengeSet1.participant1, ) # Try to create a new team, should be denied response = get_view_for_user( viewname="teams:create", challenge=TwoChallengeSets.ChallengeSet1.challenge, client=client, method=client.post, user=TwoChallengeSets.ChallengeSet1.participant, data={"name": "thisteamshouldnotbecreated"}, ) assert response.status_code == 200 assert ( "You are already a member of another team for this challenge" in response.rendered_content ) # Participant1 requests to join team, should be denied response = get_view_for_user( viewname="teams:member-create", challenge=TwoChallengeSets.ChallengeSet1.challenge, client=client, method=client.post, user=TwoChallengeSets.ChallengeSet1.participant1, reverse_kwargs={"pk": team.pk}, ) assert response.status_code == 200 assert ( "You are already a member of another team for this challenge" in response.rendered_content ) # participant12 should be able to create a team in their challenge and join another response = get_view_for_user( viewname="teams:create", challenge=TwoChallengeSets.ChallengeSet2.challenge, client=client, method=client.post, user=TwoChallengeSets.participant12, data={"name": "thisteamshouldbecreated"}, ) assert response.status_code == 302 response = get_view_for_user( viewname="teams:member-create", challenge=TwoChallengeSets.ChallengeSet1.challenge, client=client, method=client.post, user=TwoChallengeSets.participant12, reverse_kwargs={"pk": team.pk}, ) assert response.status_code == 302 assert TwoChallengeSets.participant12 in team.get_members() response = get_view_for_user( viewname="teams:member-create", challenge=TwoChallengeSets.ChallengeSet1.challenge, client=client, method=client.post, user=TwoChallengeSets.participant12, reverse_kwargs={"pk": team1.pk}, ) assert response.status_code == 200 assert ( "You are already a member of another team for this challenge" in response.rendered_content )

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456d22797f770af0d6c3e3c1d73e86251ceb6241

28

py

Python

src/config/__init__.py

supernlogn/squeezeDetTL

473be9c6c9081c6b1bd5622fbed4af6453576895

[ "MIT" ]

10

2018-11-13T14:18:11.000Z

2020-04-29T09:35:47.000Z

src/config/__init__.py

supernlogn/squeezeDetTL

473be9c6c9081c6b1bd5622fbed4af6453576895

[ "MIT" ]

3

2018-12-26T06:10:09.000Z

2021-11-23T22:23:10.000Z

src/config/__init__.py

supernlogn/squeezeDetTL

473be9c6c9081c6b1bd5622fbed4af6453576895

[ "MIT" ]

1

2020-12-08T12:36:43.000Z

from config_cooker import *

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45768d9dbdaa1a29d486a1885c16b7e4c2f4c7ae

20,208

py

Python

graphs/models/denseblock.py

hagerrady13/CondenseNet-PyTorch

93fb0d4b79d50f26988a50ed1e53f0df68f80264

[ "MIT" ]

8

2018-07-30T06:49:06.000Z

2021-07-28T15:18:40.000Z

graphs/models/denseblock.py

hagerrady13/CondenseNet-PyTorch

93fb0d4b79d50f26988a50ed1e53f0df68f80264

[ "MIT" ]

7

2019-07-23T08:03:59.000Z

2022-03-11T23:30:25.000Z

graphs/models/denseblock.py

hagerrady13/CondenseNet-PyTorch

93fb0d4b79d50f26988a50ed1e53f0df68f80264

[ "MIT" ]

3

2018-07-29T21:49:50.000Z

2021-03-26T06:27:39.000Z

""" Definitions for custom blocks """ import torch import torch.nn as nn from graphs.models.layers import LearnedGroupConv class DenseBlock(nn.Sequential): def __init__(self, num_layers, in_channels, growth_rate, config): super().__init__() for layer_id in range(num_layers): layer = DenseLayer(in_channels=in_channels + (layer_id * growth_rate), growth_rate=growth_rate, config=config) self.add_module('dense_layer_%d' % (layer_id + 1), layer) class DenseLayer(nn.Module): def __init__(self, in_channels, growth_rate, config): super().__init__() self.config = config self.conv_bottleneck = self.config.conv_bottleneck self.group1x1 = self.config.group1x1 self.group3x3 = self.config.group3x3 self.condense_factor = self.config.condense_factor self.dropout_rate = self.config.dropout_rate # 1x1 conv in_channels --> bottleneck*growth_rate self.conv_1 = LearnedGroupConv(in_channels=in_channels, out_channels=self.conv_bottleneck * growth_rate, kernel_size=1, groups=self.group1x1, condense_factor=self.condense_factor, dropout_rate=self.dropout_rate) self.batch_norm = nn.BatchNorm2d(self.conv_bottleneck * growth_rate) self.relu = nn.ReLU(inplace=True) # 3x3 conv bottleneck*growth_rate --> growth_rate self.conv_2 = nn.Conv2d(in_channels=self.conv_bottleneck * growth_rate, out_channels=growth_rate, kernel_size=3, padding=1, stride=1, groups=self.group3x3, bias=False) def forward(self, x): out = self.conv_1(x) out = self.batch_norm(out) out = self.relu(out) out = self.conv_2(out) return torch.cat([x, out], 1) """ --------------------------------- (denseblock_one): DenseBlock( (dense_layer_1): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(16, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_2): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(24, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(24, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_3): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(32, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_4): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(40, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(40, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_5): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(48, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(48, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_6): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(56, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(56, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_7): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(64, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_8): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(72, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(72, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_9): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(80, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(80, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_10): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(88, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(88, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_11): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(96, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_12): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(104, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(104, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_13): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(112, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(112, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_14): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(120, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(120, 32, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(32, 8, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) ) --------------------------------- (denseblock_two): DenseBlock( (dense_layer_1): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_2): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(144, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(144, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_3): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(160, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(160, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_4): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(176, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(176, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_5): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(192, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_6): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(208, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(208, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_7): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(224, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(224, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_8): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(240, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(240, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_9): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_10): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(272, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(272, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_11): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(288, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(288, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_12): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(304, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(304, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_13): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(320, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(320, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_14): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(336, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(336, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(64, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) ) --------------------------------- (denseblock_three): DenseBlock( (dense_layer_1): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(352, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(352, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_2): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(384, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) 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BatchNorm2d(480, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(480, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_6): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_7): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(544, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(544, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_8): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(576, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(576, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_9): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(608, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(608, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_10): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(640, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(640, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_11): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(672, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(672, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_12): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(704, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(704, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_13): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(736, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(736, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) (dense_layer_14): DenseLayer( (conv_1): LearnedGroupConv( (batch_norm): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) ) (batch_norm): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True) (relu): ReLU(inplace) (conv_2): Conv2d(128, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=4, bias=False) ) ) --------------------------------- """

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45a070175c1cc76870a9c06ccac2945680ec224c

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Python

diffxpy/unit_test/test_pairwise.py

SabrinaRichter/diffxpy

8eff054ca3ce097533134f490aac3580431eee15

[ "BSD-3-Clause" ]

null

diffxpy/unit_test/test_pairwise.py

SabrinaRichter/diffxpy

8eff054ca3ce097533134f490aac3580431eee15

[ "BSD-3-Clause" ]

null

diffxpy/unit_test/test_pairwise.py

SabrinaRichter/diffxpy

8eff054ca3ce097533134f490aac3580431eee15

[ "BSD-3-Clause" ]

null

import logging import unittest import numpy as np import pandas as pd import scipy.stats as stats from batchglm.api.models.glm_nb import Simulator, Estimator, InputData import diffxpy.api as de class TestPairwiseNull(unittest.TestCase): def test_null_distribution_ztest(self, n_cells: int = 2000, n_genes: int = 100, n_groups=2): """ Test if de.wald() generates a uniform p-value distribution if it is given data simulated based on the null model. Returns the p-value of the two-side Kolmgorov-Smirnov test for equality of the observed p-value distriubution and a uniform distribution. :param n_cells: Number of cells to simulate (number of observations per test). :param n_genes: Number of genes to simulate (number of tests). """ logging.getLogger("tensorflow").setLevel(logging.ERROR) logging.getLogger("batchglm").setLevel(logging.WARNING) logging.getLogger("diffxpy").setLevel(logging.WARNING) sim = Simulator(num_observations=n_cells, num_features=n_genes) sim.generate_sample_description(num_batches=0, num_conditions=0) sim.generate() random_sample_description = pd.DataFrame({ "condition": np.random.randint(n_groups, size=sim.num_observations) }) test = de.test.pairwise( data=sim.X, grouping="condition", test="z-test", noise_model="nb", sample_description=random_sample_description, dtype="float64" ) summary = test.summary() # Compare p-value distribution under null model against uniform distribution. pval_h0 = stats.kstest(test.pval[~np.eye(test.pval.shape[0]).astype(bool)].flatten(), 'uniform').pvalue logging.getLogger("diffxpy").info('KS-test pvalue for null model match of wald(): %f' % pval_h0) assert pval_h0 > 0.05, "KS-Test failed: pval_h0 is <= 0.05!" return True def test_null_distribution_z_lazy(self, n_cells: int = 2000, n_genes: int = 100): """ Test if de.pairwise() generates a uniform p-value distribution for lazy z-tests if it is given data simulated based on the null model. Returns the p-value of the two-side Kolmgorov-Smirnov test for equality of the observed p-value distriubution and a uniform distribution. :param n_cells: Number of cells to simulate (number of observations per test). :param n_genes: Number of genes to simulate (number of tests). """ logging.getLogger("tensorflow").setLevel(logging.ERROR) logging.getLogger("batchglm").setLevel(logging.WARNING) logging.getLogger("diffxpy").setLevel(logging.WARNING) sim = Simulator(num_observations=n_cells, num_features=n_genes) sim.generate_sample_description(num_batches=0, num_conditions=0) sim.generate() random_sample_description = pd.DataFrame({ "condition": np.random.randint(4, size=sim.num_observations) }) test = de.test.pairwise( data=sim.X, grouping="condition", test='z-test', lazy=True, noise_model="nb", pval_correction="global", quick_scale=True, sample_description=random_sample_description, dtype="float64" ) # Compare p-value distribution under null model against uniform distribution. pvals = test.pval_pairs(groups0=0, groups1=1) pval_h0 = stats.kstest(pvals.flatten(), 'uniform').pvalue logging.getLogger("diffxpy").info('KS-test pvalue for null model match of wald(): %f' % pval_h0) assert pval_h0 > 0.05, "KS-Test failed: pval_h0 is <= 0.05!" return True def test_null_distribution_lrt(self, n_cells: int = 2000, n_genes: int = 100, n_groups=2): """ Test if de.wald() generates a uniform p-value distribution if it is given data simulated based on the null model. Returns the p-value of the two-side Kolmgorov-Smirnov test for equality of the observed p-value distriubution and a uniform distribution. :param n_cells: Number of cells to simulate (number of observations per test). :param n_genes: Number of genes to simulate (number of tests). """ logging.getLogger("tensorflow").setLevel(logging.ERROR) logging.getLogger("batchglm").setLevel(logging.WARNING) logging.getLogger("diffxpy").setLevel(logging.WARNING) sim = Simulator(num_observations=n_cells, num_features=n_genes) sim.generate_sample_description(num_batches=0, num_conditions=0) sim.generate() random_sample_description = pd.DataFrame({ "condition": np.random.randint(n_groups, size=sim.num_observations) }) test = de.test.pairwise( data=sim.X, grouping="condition", test="lrt", noise_model="nb", sample_description=random_sample_description, dtype="float64" ) # Compare p-value distribution under null model against uniform distribution. pval_h0 = stats.kstest(test.pval[~np.eye(test.pval.shape[0]).astype(bool)].flatten(), 'uniform').pvalue logging.getLogger("diffxpy").info('KS-test pvalue for null model match of wald(): %f' % pval_h0) assert pval_h0 > 0.05, "KS-Test failed: pval_h0 is <= 0.05!" return True def test_null_distribution_ttest(self, n_cells: int = 2000, n_genes: int = 10000, n_groups=2): """ Test if de.wald() generates a uniform p-value distribution if it is given data simulated based on the null model. Returns the p-value of the two-side Kolmgorov-Smirnov test for equality of the observed p-value distriubution and a uniform distribution. :param n_cells: Number of cells to simulate (number of observations per test). :param n_genes: Number of genes to simulate (number of tests). """ logging.getLogger("tensorflow").setLevel(logging.ERROR) logging.getLogger("batchglm").setLevel(logging.WARNING) logging.getLogger("diffxpy").setLevel(logging.WARNING) sim = Simulator(num_observations=n_cells, num_features=n_genes) sim.generate_sample_description(num_batches=0, num_conditions=0) sim.generate() random_sample_description = pd.DataFrame({ "condition": np.random.randint(n_groups, size=sim.num_observations) }) test = de.test.pairwise( data=sim.X, grouping="condition", test="t-test", sample_description=random_sample_description, ) summary = test.summary() # Compare p-value distribution under null model against uniform distribution. pval_h0 = stats.kstest(test.pval[~np.eye(test.pval.shape[0]).astype(bool)].flatten(), 'uniform').pvalue logging.getLogger("diffxpy").info('KS-test pvalue for null model match of wald(): %f' % pval_h0) assert pval_h0 > 0.05, "KS-Test failed: pval_h0 is <= 0.05!" return True def test_null_distribution_wilcoxon(self, n_cells: int = 2000, n_genes: int = 10000, n_groups=2): """ Test if de.wald() generates a uniform p-value distribution if it is given data simulated based on the null model. Returns the p-value of the two-side Kolmgorov-Smirnov test for equality of the observed p-value distriubution and a uniform distribution. :param n_cells: Number of cells to simulate (number of observations per test). :param n_genes: Number of genes to simulate (number of tests). """ logging.getLogger("tensorflow").setLevel(logging.ERROR) logging.getLogger("batchglm").setLevel(logging.WARNING) logging.getLogger("diffxpy").setLevel(logging.WARNING) sim = Simulator(num_observations=n_cells, num_features=n_genes) sim.generate_sample_description(num_batches=0, num_conditions=0) sim.generate() random_sample_description = pd.DataFrame({ "condition": np.random.randint(n_groups, size=sim.num_observations) }) test = de.test.pairwise( data=sim.X, grouping="condition", test="wilcoxon", sample_description=random_sample_description, ) summary = test.summary() # Compare p-value distribution under null model against uniform distribution. pval_h0 = stats.kstest(test.pval[~np.eye(test.pval.shape[0]).astype(bool)].flatten(), 'uniform').pvalue logging.getLogger("diffxpy").info('KS-test pvalue for null model match of wald(): %f' % pval_h0) assert pval_h0 > 0.05, "KS-Test failed: pval_h0 is <= 0.05!" return True class TestPairwiseDE(unittest.TestCase): def test_ztest_de(self, n_cells: int = 2000, n_genes: int = 500): """ Test if de.lrt() generates a uniform p-value distribution if it is given data simulated based on the null model. Returns the p-value of the two-side Kolmgorov-Smirnov test for equality of the observed p-value distriubution and a uniform distribution. :param n_cells: Number of cells to simulate (number of observations per test). :param n_genes: Number of genes to simulate (number of tests). """ logging.getLogger("tensorflow").setLevel(logging.ERROR) logging.getLogger("batchglm").setLevel(logging.WARNING) logging.getLogger("diffxpy").setLevel(logging.WARNING) num_non_de = n_genes // 2 sim = Simulator(num_observations=n_cells, num_features=n_genes) sim.generate_sample_description(num_batches=0, num_conditions=2) # simulate: coefficients ~ log(N(1, 0.5)). # re-sample if N(1, 0.5) <= 0 sim.generate_params(rand_fn=lambda shape: 1 + stats.truncnorm.rvs(-1 / 0.5, np.infty, scale=0.5, size=shape)) sim.params["a"][1, :num_non_de] = 0 sim.params["b"][1, :num_non_de] = 0 sim.params["isDE"] = ("features",), np.arange(n_genes) >= num_non_de sim.generate_data() sample_description = sim.sample_description test = de.test.pairwise( data=sim.X, grouping="condition", test="z-test", noise_model="nb", sample_description=sample_description, ) summary = test.summary() logging.getLogger("diffxpy").info('fraction of non-DE genes with q-value < 0.05: %.1f%%' % float(100 * np.mean( np.sum(test.qval[~np.eye(test.pval.shape[0]).astype(bool), :num_non_de] < 0.05) / (2 * num_non_de) ))) logging.getLogger("diffxpy").info('fraction of DE genes with q-value < 0.05: %.1f%%' % float(100 * np.mean( np.sum(test.qval[~np.eye(test.pval.shape[0]).astype(bool), num_non_de:] < 0.05) / (2 * (n_genes - num_non_de)) ))) # TODO asserts return True if __name__ == '__main__': unittest.main()

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45b57c3093db5cb3160495cb03f73c0f5ee13cb4

29

py

Python

sierra_api/__init__.py

alexvancina/sierra-api

6fd5c04ac39569367db361d6a9d356d5fa3eb00f

[ "MIT" ]

2

2020-07-21T18:16:55.000Z

2022-03-14T19:48:04.000Z

sierra_api/__init__.py

alexvancina/sierra-api

6fd5c04ac39569367db361d6a9d356d5fa3eb00f

[ "MIT" ]

null

sierra_api/__init__.py

alexvancina/sierra-api

6fd5c04ac39569367db361d6a9d356d5fa3eb00f

[ "MIT" ]

null

from .sierra import SierraAPI

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45b94aa8fe149085a3fe69fa5d36aa71d765346b

43

py

Python

plugins/flytekit-athena/flytekitplugins/athena/__init__.py

slai/flytekit

9d73d096b748d263a638e6865d15db4880845305

[ "Apache-2.0" ]

1

2021-11-11T10:10:10.000Z

plugins/flytekit-athena/flytekitplugins/athena/__init__.py

slai/flytekit

9d73d096b748d263a638e6865d15db4880845305

[ "Apache-2.0" ]

2

2021-06-26T04:32:43.000Z

2021-07-14T04:47:52.000Z

plugins/flytekit-athena/flytekitplugins/athena/__init__.py

slai/flytekit

9d73d096b748d263a638e6865d15db4880845305

[ "Apache-2.0" ]

null

from .task import AthenaConfig, AthenaTask

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py

Python

backend/edw/signals/__init__.py

MMotionMan/django-edw

0f686429d29e0f40409a3b2318664973b2844c08

[ "BSD-3-Clause" ]

4

2019-09-18T05:51:12.000Z

2020-10-23T08:50:00.000Z

backend/edw/signals/__init__.py

Vvvnukova/django-edw

18397c2e6e2d7ddebad4d83ffee16425e7ac4e9f

[ "BSD-3-Clause" ]

10

2020-04-29T11:46:44.000Z

2022-03-11T23:38:27.000Z

backend/edw/signals/__init__.py

Vvvnukova/django-edw

18397c2e6e2d7ddebad4d83ffee16425e7ac4e9f

[ "BSD-3-Clause" ]

13

2020-04-09T07:49:48.000Z

2022-03-02T07:06:28.000Z

# -*- coding: utf-8 -*- def make_dispatch_uid(*args): return "::".join(map(lambda obj: obj if isinstance(obj, str) else str(id(obj)), args))

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2fbf03fe000c1b98be97869022ca4eec73963dab

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py

Python

modules/ui/introscreen.py

abstractdonut/primavista

c232cf2a67875233f677ee9d23dcc9227fc97a53

[ "MIT" ]

null

modules/ui/introscreen.py

abstractdonut/primavista

c232cf2a67875233f677ee9d23dcc9227fc97a53

[ "MIT" ]

null

modules/ui/introscreen.py

abstractdonut/primavista

c232cf2a67875233f677ee9d23dcc9227fc97a53

[ "MIT" ]

null

from kivymd.uix.screen import MDScreen class IntroScreen(MDScreen): def goto_exercise(self): self.manager.goto_exercise() print("IntroScreen: goto_exercise") def goto_choose(self): self.manager.goto_choose()

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2fcda9cf6d654da0edc4fb98bdd920c383ea0fad

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py

Python

daskms/experimental/arrow/__init__.py

ratt-ru/dask-ms

becd3572f86a0ad78b55540f25fce6e129976a29

[ "BSD-3-Clause" ]

7

2019-08-23T03:44:53.000Z

2021-05-06T00:51:18.000Z

daskms/experimental/arrow/__init__.py

ska-sa/dask-ms

ce33e7aad36eeb7c2c79093622b9776186856304

[ "BSD-3-Clause" ]

76

2019-08-20T14:34:05.000Z

2022-02-10T13:21:29.000Z

daskms/experimental/arrow/__init__.py

ratt-ru/dask-ms

becd3572f86a0ad78b55540f25fce6e129976a29

[ "BSD-3-Clause" ]

4

2019-10-15T13:35:19.000Z

2021-03-23T14:52:23.000Z

from daskms.experimental.arrow.reads import xds_from_parquet # noqa: F401 from daskms.experimental.arrow.writes import xds_to_parquet # noqa: F401

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Python

test/test_markdown_emphasis_rule_10.py

scop/pymarkdown

562ba8f7857d99ba09e86e42de5a37ec6d9b2c30

[ "MIT" ]

null

test/test_markdown_emphasis_rule_10.py

scop/pymarkdown

562ba8f7857d99ba09e86e42de5a37ec6d9b2c30

[ "MIT" ]

null

test/test_markdown_emphasis_rule_10.py

scop/pymarkdown

562ba8f7857d99ba09e86e42de5a37ec6d9b2c30

[ "MIT" ]

null

""" https://github.github.com/gfm/#emphasis-and-strong-emphasis """ import pytest from .utils import act_and_assert @pytest.mark.gfm def test_emphasis_431(): """ Test case 431: (part 1) Any nonempty sequence of inline elements can be the contents of an strongly emphasized span. """ # Arrange source_markdown = """**foo [bar](/url)**""" expected_tokens = [ "[para(1,1):]", "[emphasis(1,1):2:*]", "[text(1,3):foo :]", "[link(1,7):inline:/url:::::bar:False::::]", "[text(1,8):bar:]", "[end-link::]", "[end-emphasis(1,18)::]", "[end-para:::True]", ] expected_gfm = """foo <a href="/url">bar</a>""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_432(): """ Test case 432: (part 2) Any nonempty sequence of inline elements can be the contents of an strongly emphasized span. """ # Arrange source_markdown = """**foo bar**""" expected_tokens = [ "[para(1,1):\n]", "[emphasis(1,1):2:*]", "[text(1,3):foo\nbar::\n]", "[end-emphasis(2,4)::]", "[end-para:::True]", ] expected_gfm = """foo bar""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_433(): """ Test case 433: (part 1) In particular, emphasis and strong emphasis can be nested inside strong emphasis: """ # Arrange source_markdown = """__foo _bar_ baz__""" expected_tokens = [ "[para(1,1):]", "[emphasis(1,1):2:_]", "[text(1,3):foo :]", "[emphasis(1,7):1:_]", "[text(1,8):bar:]", "[end-emphasis(1,11)::]", "[text(1,12): baz:]", "[end-emphasis(1,16)::]", "[end-para:::True]", ] expected_gfm = """foo bar baz""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_434(): """ Test case 434: (part 2) In particular, emphasis and strong emphasis can be nested inside strong emphasis: """ # Arrange source_markdown = """__foo __bar__ baz__""" expected_tokens = [ "[para(1,1):]", "[emphasis(1,1):2:_]", "[text(1,3):foo :]", "[emphasis(1,7):2:_]", "[text(1,9):bar:]", "[end-emphasis(1,12)::]", "[text(1,14): baz:]", "[end-emphasis(1,18)::]", "[end-para:::True]", ] expected_gfm = """foo bar baz""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_435(): """ Test case 435: (part 3) In particular, emphasis and strong emphasis can be nested inside strong emphasis: """ # Arrange source_markdown = """____foo__ bar__""" expected_tokens = [ "[para(1,1):]", "[emphasis(1,1):2:_]", "[emphasis(1,3):2:_]", "[text(1,5):foo:]", "[end-emphasis(1,8)::]", "[text(1,10): bar:]", "[end-emphasis(1,14)::]", "[end-para:::True]", ] expected_gfm = """foo bar""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_436(): """ Test case 436: (part 4) In particular, emphasis and strong emphasis can be nested inside strong emphasis: """ # Arrange source_markdown = """**foo **bar****""" expected_tokens = [ "[para(1,1):]", "[emphasis(1,1):2:*]", "[text(1,3):foo :]", "[emphasis(1,7):2:*]", "[text(1,9):bar:]", "[end-emphasis(1,12)::]", "[end-emphasis(1,14)::]", "[end-para:::True]", ] expected_gfm = """foo bar""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_437(): """ Test case 437: (part 5) In particular, emphasis and strong emphasis can be nested inside strong emphasis: """ # Arrange source_markdown = """**foo *bar* baz**""" expected_tokens = [ "[para(1,1):]", "[emphasis(1,1):2:*]", "[text(1,3):foo :]", "[emphasis(1,7):1:*]", "[text(1,8):bar:]", "[end-emphasis(1,11)::]", "[text(1,12): baz:]", "[end-emphasis(1,16)::]", "[end-para:::True]", ] expected_gfm = """foo bar baz""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_438(): """ Test case 438: (part 6) In particular, emphasis and strong emphasis can be nested inside strong emphasis: """ # Arrange source_markdown = """**foo*bar*baz**""" expected_tokens = [ "[para(1,1):]", "[emphasis(1,1):2:*]", "[text(1,3):foo:]", "[emphasis(1,6):1:*]", "[text(1,7):bar:]", "[end-emphasis(1,10)::]", "[text(1,11):baz:]", "[end-emphasis(1,14)::]", "[end-para:::True]", ] expected_gfm = """foobarbaz""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_439(): """ Test case 439: (part 7) In particular, emphasis and strong emphasis can be nested inside strong emphasis: """ # Arrange source_markdown = """***foo* bar**""" expected_tokens = [ "[para(1,1):]", "[emphasis(1,1):2:*]", "[emphasis(1,3):1:*]", "[text(1,4):foo:]", "[end-emphasis(1,7)::]", "[text(1,8): bar:]", "[end-emphasis(1,12)::]", "[end-para:::True]", ] expected_gfm = """foo bar""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_440(): """ Test case 440: (part 8) In particular, emphasis and strong emphasis can be nested inside strong emphasis: """ # Arrange source_markdown = """**foo *bar***""" expected_tokens = [ "[para(1,1):]", "[emphasis(1,1):2:*]", "[text(1,3):foo :]", "[emphasis(1,7):1:*]", "[text(1,8):bar:]", "[end-emphasis(1,11)::]", "[end-emphasis(1,12)::]", "[end-para:::True]", ] expected_gfm = """foo bar""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_441(): """ Test case 441: (part 1) Indefinite levels of nesting are possible: """ # Arrange source_markdown = """**foo *bar **baz** bim* bop**""" expected_tokens = [ "[para(1,1):\n]", "[emphasis(1,1):2:*]", "[text(1,3):foo :]", "[emphasis(1,7):1:*]", "[text(1,8):bar :]", "[emphasis(1,12):2:*]", "[text(1,14):baz:]", "[end-emphasis(1,17)::]", "[text(1,19):\nbim::\n]", "[end-emphasis(2,4)::]", "[text(2,5): bop:]", "[end-emphasis(2,9)::]", "[end-para:::True]", ] expected_gfm = """foo bar baz bim bop""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_442(): """ Test case 442: (part 2) Indefinite levels of nesting are possible: """ # Arrange source_markdown = """**foo [*bar*](/url)**""" expected_tokens = [ "[para(1,1):]", "[emphasis(1,1):2:*]", "[text(1,3):foo :]", "[link(1,7):inline:/url:::::*bar*:False::::]", "[emphasis(1,8):1:*]", "[text(1,9):bar:]", "[end-emphasis(1,12)::]", "[end-link::]", "[end-emphasis(1,20)::]", "[end-para:::True]", ] expected_gfm = """foo <a href="/url">bar</a>""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_443(): """ Test case 443: (part 1) There can be no empty emphasis or strong emphasis: """ # Arrange source_markdown = """__ is not an empty emphasis""" expected_tokens = [ "[para(1,1):]", "[text(1,1):__:]", "[text(1,3): is not an empty emphasis:]", "[end-para:::True]", ] expected_gfm = """__ is not an empty emphasis""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens) @pytest.mark.gfm def test_emphasis_444(): """ Test case 444: (part 2) There can be no empty emphasis or strong emphasis: """ # Arrange source_markdown = """____ is not an empty strong emphasis""" expected_tokens = [ "[para(1,1):]", "[text(1,1):____:]", "[text(1,5): is not an empty strong emphasis:]", "[end-para:::True]", ] expected_gfm = """____ is not an empty strong emphasis""" # Act & Assert act_and_assert(source_markdown, expected_gfm, expected_tokens)

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py

Python

amspy/restfns.py

msleal/amspy

c691881c6b2bf9bae357a4cb327d71033426abed

[ "MIT" ]

11

2016-09-08T19:28:45.000Z

2020-10-13T00:31:57.000Z

amspy/restfns.py

msleal/amspy

c691881c6b2bf9bae357a4cb327d71033426abed

[ "MIT" ]

4

2016-09-19T18:18:01.000Z

2017-07-03T20:12:56.000Z

amspy/restfns.py

msleal/amspy

c691881c6b2bf9bae357a4cb327d71033426abed

[ "MIT" ]

7

2016-09-10T18:43:10.000Z

2019-12-05T11:05:21.000Z

""" Copyright (c) 2016, Marcelo Leal Description: Simple Azure Media Services Python library License: MIT (see LICENSE.txt file for details) """ # restfns - REST functions for amspy import requests import json from .settings import json_acceptformat, json_only_acceptformat, xml_acceptformat, batch_acceptformat, charset, dsversion_min, dsversion_max, xmsversion #Defaults # do_auth(endpoint, body, access_token) # do an HTTP POST request for authentication (acquire an access token) and return JSON def do_auth(endpoint, body): global dsversion_min, dsversion_max, json_acceptformat, json_acceptformat min_ds = dsversion_min; max_ds = dsversion_max; content_acceptformat = json_acceptformat; acceptformat = json_acceptformat headers = {"content-type": "application/x-www-form-urlencoded", "Accept": acceptformat} return requests.post(endpoint, data=body, headers=headers) # do_get(endpoint, path, access_token) # do an HTTP GET request and return JSON def do_get(endpoint, path, access_token): global dsversion_min, dsversion_max, json_acceptformat, json_acceptformat min_ds = dsversion_min; max_ds = dsversion_max; content_acceptformat = json_acceptformat; acceptformat = json_acceptformat headers = {"Content-Type": content_acceptformat, "DataServiceVersion": min_ds, "MaxDataServiceVersion": max_ds, "Accept": acceptformat, "Accept-Charset" : charset, "Authorization": "Bearer " + access_token, "x-ms-version" : xmsversion} body = '' response = requests.get(endpoint, headers=headers, allow_redirects=False) # AMS response to the first call can be a redirect, # so we handle it here to make it transparent for the caller... if (response.status_code == 301): redirected_url = ''.join([response.headers['location'], path]) response = requests.get(redirected_url, data=body, headers=headers) return response # do_put(endpoint, path, body, access_token, format="json", ds_min_version="3.0;NetFx") # do an HTTP PUT request and return JSON def do_put(endpoint, path, body, access_token, format="json", ds_min_version="3.0;NetFx"): global dsversion_min, dsversion_max, json_acceptformat, json_acceptformat min_ds = dsversion_min; max_ds = dsversion_max; content_acceptformat = json_acceptformat; acceptformat = json_acceptformat if (format == "json_only"): min_ds = ds_min_version content_acceptformat = json_only_acceptformat headers = {"Content-Type": content_acceptformat, "DataServiceVersion": min_ds, "MaxDataServiceVersion": max_ds, "Accept": acceptformat, "Accept-Charset" : charset, "Authorization": "Bearer " + access_token, "x-ms-version" : xmsversion} response = requests.put(endpoint, data=body, headers=headers, allow_redirects=False) # AMS response to the first call can be a redirect, # so we handle it here to make it transparent for the caller... if (response.status_code == 301): redirected_url = ''.join([response.headers['location'], path]) response = requests.put(redirected_url, data=body, headers=headers) return response # do_post(endpoint, body, access_token, format="json", ds_min_version="3.0;NetFx") # do an HTTP POST request and return JSON def do_post(endpoint, path, body, access_token, format="json", ds_min_version="3.0;NetFx"): global dsversion_min, dsversion_max, json_acceptformat, json_acceptformat min_ds = dsversion_min; max_ds = dsversion_max; content_acceptformat = json_acceptformat; acceptformat = json_acceptformat if (format == "json_only"): min_ds = ds_min_version content_acceptformat = json_only_acceptformat if (format == "xml"): content_acceptformat = xml_acceptformat acceptformat = xml_acceptformat + ",application/xml" headers = {"Content-Type": content_acceptformat, "DataServiceVersion": min_ds, "MaxDataServiceVersion": max_ds, "Accept": acceptformat, "Accept-Charset" : charset, "Authorization": "Bearer " + access_token, "x-ms-version" : xmsversion} response = requests.post(endpoint, data=body, headers=headers, allow_redirects=False) # AMS response to the first call can be a redirect, # so we handle it here to make it transparent for the caller... if (response.status_code == 301): redirected_url = ''.join([response.headers['location'], path]) response = requests.post(redirected_url, data=body, headers=headers) return response # do_patch(endpoint, path, body, access_token) # do an HTTP PATCH request and return JSON def do_patch(endpoint, path, body, access_token): global dsversion_min, dsversion_max, json_acceptformat, json_acceptformat min_ds = dsversion_min; max_ds = dsversion_max; content_acceptformat = json_acceptformat; acceptformat = json_acceptformat headers = {"Content-Type": content_acceptformat, "DataServiceVersion": min_ds, "MaxDataServiceVersion": max_ds, "Accept": acceptformat, "Accept-Charset" : charset, "Authorization": "Bearer " + access_token, "x-ms-version" : xmsversion} response = requests.patch(endpoint, data=body, headers=headers, allow_redirects=False) # AMS response to the first call can be a redirect, # so we handle it here to make it transparent for the caller... if (response.status_code == 301): redirected_url = ''.join([response.headers['location'], path]) response = requests.patch(redirected_url, data=body, headers=headers) return response # do_delete(endpoint, access_token) # do an HTTP DELETE request and return JSON def do_delete(endpoint, path, access_token): global dsversion_min, dsversion_max, json_acceptformat, json_acceptformat min_ds = dsversion_min; max_ds = dsversion_max; content_acceptformat = json_acceptformat; acceptformat = json_acceptformat headers = {"DataServiceVersion": min_ds, "MaxDataServiceVersion": max_ds, "Accept": acceptformat, "Accept-Charset" : charset, "Authorization": 'Bearer ' + access_token, "x-ms-version" : xmsversion} response = requests.delete(endpoint, headers=headers, allow_redirects=False) # AMS response to the first call can be a redirect, # so we handle it here to make it transparent for the caller... if (response.status_code == 301): redirected_url = ''.join([response.headers['location'], path]) response = requests.delete(redirected_url, headers=headers) return response # do_sto_put(endpoint, body, access_token) # do an HTTP PUT request to the azure storage api and return JSON def do_sto_put(endpoint, body, content_length, access_token): global dsversion_min, dsversion_max, json_acceptformat, json_acceptformat min_ds = dsversion_min; max_ds = dsversion_max; content_acceptformat = json_acceptformat; acceptformat = json_acceptformat headers = {"Accept": acceptformat, "Accept-Charset" : charset, "x-ms-blob-type" : "BlockBlob", "x-ms-meta-m1": "v1", "x-ms-meta-m2": "v2", "x-ms-version" : "2015-02-21", "Content-Length" : str(content_length)} return requests.put(endpoint, data=body, headers=headers) # do_get_url(endpoint, access_token) # do an HTTP GET request and return JSON def do_get_url(endpoint, access_token, flag=True): global dsversion_min, dsversion_max, json_acceptformat, json_acceptformat min_ds = dsversion_min; max_ds = dsversion_max; content_acceptformat = json_acceptformat; acceptformat = json_acceptformat headers = {"Content-Type": content_acceptformat, "DataServiceVersion": min_ds, "MaxDataServiceVersion": max_ds, "Accept": acceptformat, "Accept-Charset" : charset, "Authorization": "Bearer " + access_token, "x-ms-version" : xmsversion} body = '' response = requests.get(endpoint, headers=headers, allow_redirects=flag) if(flag): if (response.status_code == 301): response = requests.get(response.headers['location'], data=body, headers=headers) return response

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py

Python

cartex/__init__.py

tochikuji/Cartoon-Texture-Decomposition

9ac7bbafda426c653f2c3e66c73f65d927542154

[ "Apache-2.0" ]

7

2020-05-21T08:24:07.000Z

2022-02-27T16:47:20.000Z

cartex/__init__.py

tochikuji/Cartoon-Texture-Decomposition

9ac7bbafda426c653f2c3e66c73f65d927542154

[ "Apache-2.0" ]

null

cartex/__init__.py

tochikuji/Cartoon-Texture-Decomposition

9ac7bbafda426c653f2c3e66c73f65d927542154

[ "Apache-2.0" ]

null

from cartex.tools import expect_valid_float_image from cartex.iterative_lpf import iterativeLPF from cartex.ltv import LTV, channelwiseLTV from cartex.decomposition import CartoonTextureDecomposition

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9240896e2daac5e918da84944e0553ad3aacff53

19

py

Python

pyTGA/__init__.py

Lightslayer/pyTGA

7882e84dc6020119f3a1842e162f641061ff8248

[ "MIT" ]

17

2016-09-19T10:08:52.000Z

2022-02-28T09:24:35.000Z

pyTGA/__init__.py

Lightslayer/pyTGA

7882e84dc6020119f3a1842e162f641061ff8248

[ "MIT" ]

2

2019-01-19T16:45:52.000Z

2019-11-04T10:53:53.000Z

pyTGA/__init__.py

Lightslayer/pyTGA

7882e84dc6020119f3a1842e162f641061ff8248

[ "MIT" ]

5

2017-07-22T19:12:14.000Z

2019-08-17T07:25:29.000Z

from . tga import *

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925e80cbebca9ba89ee8f1a2f445e6ca760a0097

997

py

Python

test/test_get_image_info_result.py

Cloudmersive/Cloudmersive.APIClient.Python.Convert

dba2fe7257229ebdacd266531b3724552c651009

[ "Apache-2.0" ]

3

2018-07-25T23:04:34.000Z

2021-08-10T16:43:10.000Z

test/test_get_image_info_result.py

Cloudmersive/Cloudmersive.APIClient.Python.Convert

dba2fe7257229ebdacd266531b3724552c651009

[ "Apache-2.0" ]

3

2020-11-23T10:46:48.000Z

2021-12-30T14:09:34.000Z

test/test_get_image_info_result.py

Cloudmersive/Cloudmersive.APIClient.Python.Convert

dba2fe7257229ebdacd266531b3724552c651009

[ "Apache-2.0" ]

2

2020-01-07T09:48:01.000Z

2020-11-23T10:47:00.000Z

# coding: utf-8 """ convertapi Convert API lets you effortlessly convert file formats and types. # noqa: E501 OpenAPI spec version: v1 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import unittest import cloudmersive_convert_api_client from cloudmersive_convert_api_client.models.get_image_info_result import GetImageInfoResult # noqa: E501 from cloudmersive_convert_api_client.rest import ApiException class TestGetImageInfoResult(unittest.TestCase): """GetImageInfoResult unit test stubs""" def setUp(self): pass def tearDown(self): pass def testGetImageInfoResult(self): """Test GetImageInfoResult""" # FIXME: construct object with mandatory attributes with example values # model = cloudmersive_convert_api_client.models.get_image_info_result.GetImageInfoResult() # noqa: E501 pass if __name__ == '__main__': unittest.main()

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6

2bcef91853a1d15439679525195ad22cb6470db4

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py

Python

generators/tests/templates/tests/test_lib.py

The-Politico/generator-politico-python-package

b5882eed9dfc8c1025a6ac25212e325246961a48

[ "MIT" ]

5

2018-01-30T17:36:35.000Z

2021-02-28T12:08:29.000Z

generators/tests/templates/tests/test_lib.py

The-Politico/generator-politico-python-package

b5882eed9dfc8c1025a6ac25212e325246961a48

[ "MIT" ]

1

2018-01-05T19:33:47.000Z

generators/tests/templates/tests/test_lib.py

The-Politico/generator-politico-python-package

b5882eed9dfc8c1025a6ac25212e325246961a48

[ "MIT" ]

null

def tests_lib(): assert True is True

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6

2beab61857511c1e9ee2a2b7a4608d0eeed543ec

26,857

py

Python

tools/graph_builder.py

teploff/fractal-surface

e2b8a7cd30f710e3e2522c8f4eb0240832bea012

[ "MIT" ]

null

tools/graph_builder.py

teploff/fractal-surface

e2b8a7cd30f710e3e2522c8f4eb0240832bea012

[ "MIT" ]

null

tools/graph_builder.py

teploff/fractal-surface

e2b8a7cd30f710e3e2522c8f4eb0240832bea012

[ "MIT" ]

null

import pickle from typing import List import matplotlib.pyplot as plt def build_classic_one_phase(iter_count: int, depth: int): with open(f'../metrics/datasets/classic/iterations_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: iterations = pickle.load(fp) with open(f'../metrics/datasets/classic/length_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: line_length = pickle.load(fp) with open(f'../metrics/datasets/classic/square_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: square = pickle.load(fp) with open(f'../metrics/datasets/classic/volume_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: volume = pickle.load(fp) with open(f'../metrics/datasets/classic/s_l_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: s_l = pickle.load(fp) with open(f'../metrics/datasets/classic/v_s_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: v_s = pickle.load(fp) with open(f'../metrics/datasets/classic/v_l_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: v_l = pickle.load(fp) with open(f'../metrics/datasets/classic/v_v_base_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: v_v_base = pickle.load(fp) with open(f'../metrics/datasets/classic/fractal_span_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: fractal_span = pickle.load(fp) # # TODO: разкомментировать по необходиомости # # Производим интерполяцию по найденным метрикам # y_length = make_interpolation(iterations, line_length) # y_square = make_interpolation(iterations, square) # y_volume = make_interpolation(iterations, volume) # Строим графики для найденных и апроксимируемыъ метрик. fig1, ax1 = plt.subplots() ax1.plot(iterations, line_length, 'o', label=r'$a$', c='black', linewidth=1) fig2, ax2 = plt.subplots() ax2.plot(iterations, square, 'X', label=r'$a$', c='black', linewidth=1) fig3, ax3 = plt.subplots() ax3.plot(iterations, volume, '*', label=r'$a$', c='black', linewidth=1) fig4, ax4 = plt.subplots() ax4.plot(iterations, s_l, '*', label=r'$a$', c='black', linewidth=1) fig5, ax5 = plt.subplots() ax5.plot(iterations, v_s, '*', label=r'$a$', c='black', linewidth=1) fig6, ax6 = plt.subplots() ax6.plot(iterations, v_l, '*', label=r'$a$', c='black', linewidth=1) fig7, ax7 = plt.subplots() ax7.plot(iterations, v_v_base, '*', label=r'$a$', c='black', linewidth=1) fig8, ax8 = plt.subplots() ax8.plot(iterations, fractal_span, '*', label=r'$a$', c='black', linewidth=1) ax1.grid(True) ax2.grid(True) ax3.grid(True) ax4.grid(True) ax5.grid(True) ax6.grid(True) ax7.grid(True) ax8.grid(True) ax1.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax1.set(xlabel='Число циклов роста, ед.', ylabel='Длина фрактальной линии, ед.') ax2.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax2.set(xlabel='Число циклов роста, ед.', ylabel='Площадь фрактала, ед.') ax3.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax3.set(xlabel='Число циклов роста, ед.', ylabel='Объем фрактала, ед.') ax4.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax4.set(xlabel='Число циклов роста, ед.', ylabel='Отношение S/L, ед.') ax5.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax5.set(xlabel='Число циклов роста, ед.', ylabel='Отношение V/S, ед.') ax6.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax6.set(xlabel='Число циклов роста, ед.', ylabel='Отношение V/L, ед.') ax7.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax7.set(xlabel='Число циклов роста, ед.', ylabel='Отношение 4*V1/V0, ед.') ax8.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax8.set(xlabel='Число циклов роста, ед.', ylabel='Размах фрактала, ед.') fig1.savefig(f'../metrics/graphics/classic/length.png') fig2.savefig(f'../metrics/graphics/classic/square.png') fig3.savefig(f'../metrics/graphics/classic/value.png') fig4.savefig(f'../metrics/graphics/classic/s_l.png') fig5.savefig(f'../metrics/graphics/classic/v_s.png') fig6.savefig(f'../metrics/graphics/classic/v_l.png') fig7.savefig(f'../metrics/graphics/classic/4v1_v0.png') fig8.savefig(f'../metrics/graphics/classic/fractal_span.png') plt.show() def build_one_phase(iter_count: int, depth: int): with open(f'../metrics/datasets/one_phase/iterations_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: iterations = pickle.load(fp) with open(f'../metrics/datasets/one_phase/length_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: line_length = pickle.load(fp) with open(f'../metrics/datasets/one_phase/square_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: square = pickle.load(fp) with open(f'../metrics/datasets/one_phase/volume_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: volume = pickle.load(fp) with open(f'../metrics/datasets/one_phase/s_l_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: s_l = pickle.load(fp) with open(f'../metrics/datasets/one_phase/v_s_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: v_s = pickle.load(fp) with open(f'../metrics/datasets/one_phase/v_l_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: v_l = pickle.load(fp) with open(f'../metrics/datasets/one_phase/v_v_base_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: v_v_base = pickle.load(fp) with open(f'../metrics/datasets/one_phase/fractal_span_iter_count_{iter_count}_depth_{depth}.txt', 'rb') as fp: fractal_span = pickle.load(fp) # Строим графики для найденных и апроксимируемыъ метрик. fig1, ax1 = plt.subplots() ax1.plot(iterations, line_length, 'o', label=r'$a$', c='black', linewidth=1) fig2, ax2 = plt.subplots() ax2.plot(iterations, square, 'X', label=r'$a$', c='black', linewidth=1) fig3, ax3 = plt.subplots() ax3.plot(iterations, volume, '*', label=r'$a$', c='black', linewidth=1) fig4, ax4 = plt.subplots() ax4.plot(iterations, s_l, '*', label=r'$a$', c='black', linewidth=1) fig5, ax5 = plt.subplots() ax5.plot(iterations, v_s, '*', label=r'$a$', c='black', linewidth=1) fig6, ax6 = plt.subplots() ax6.plot(iterations, v_l, '*', label=r'$a$', c='black', linewidth=1) fig7, ax7 = plt.subplots() ax7.plot(iterations, v_v_base, '*', label=r'$a$', c='black', linewidth=1) fig8, ax8 = plt.subplots() ax8.plot(iterations, fractal_span, '*', label=r'$a$', c='black', linewidth=1) ax1.grid(True) ax2.grid(True) ax3.grid(True) ax4.grid(True) ax5.grid(True) ax6.grid(True) ax7.grid(True) ax8.grid(True) ax1.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax1.set(xlabel='Число циклов роста, ед.', ylabel='Длина фрактальной линии, ед.') ax2.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax2.set(xlabel='Число циклов роста, ед.', ylabel='Площадь фрактала, ед.') ax3.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax3.set(xlabel='Число циклов роста, ед.', ylabel='Объем фрактала, ед.') ax4.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax4.set(xlabel='Число циклов роста, ед.', ylabel='Отношение S/L, ед.') ax5.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax5.set(xlabel='Число циклов роста, ед.', ylabel='Отношение V/S, ед.') ax6.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax6.set(xlabel='Число циклов роста, ед.', ylabel='Отношение V/L, ед.') ax7.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax7.set(xlabel='Число циклов роста, ед.', ylabel='Отношение 4*V1/V0, ед.') ax8.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax8.set(xlabel='Число циклов роста, ед.', ylabel='Размах фрактала, ед.') fig1.savefig(f'../metrics/graphics/one_phase/length.png') fig2.savefig(f'../metrics/graphics/one_phase/square.png') fig3.savefig(f'../metrics/graphics/one_phase/value.png') fig4.savefig(f'../metrics/graphics/one_phase/s_l.png') fig5.savefig(f'../metrics/graphics/one_phase/v_s.png') fig6.savefig(f'../metrics/graphics/one_phase/v_l.png') fig7.savefig(f'../metrics/graphics/one_phase/4v1_v0.png') fig8.savefig(f'../metrics/graphics/one_phase/fractal_span.png') plt.show() def build_several_phases(iter_count: int, depth: int, deltas: List[int]): with open(f'../metrics/datasets/several_phases/iterations_iter_count_{iter_count}_depth_{depth}_delta_{deltas[0]}.txt', 'rb') as fp: iterations1 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/length_iter_count_{iter_count}_depth_{depth}_delta_{deltas[0]}.txt', 'rb') as fp: line_length1 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/square_iter_count_{iter_count}_depth_{depth}_delta_{deltas[0]}.txt', 'rb') as fp: square1 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/volume_iter_count_{iter_count}_depth_{depth}_delta_{deltas[0]}.txt', 'rb') as fp: volume1 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/s_l_iter_count_{iter_count}_depth_{depth}_delta_{deltas[0]}.txt', 'rb') as fp: s_l1 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/v_s_iter_count_{iter_count}_depth_{depth}_delta_{deltas[0]}.txt', 'rb') as fp: v_s1 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/v_l_iter_count_{iter_count}_depth_{depth}_delta_{deltas[0]}.txt', 'rb') as fp: v_l1 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/v_v_base_iter_count_{iter_count}_depth_{depth}_delta_{deltas[0]}.txt', 'rb') as fp: v_v_base1 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/fractal_span_iter_count_{iter_count}_depth_{depth}_delta_{deltas[0]}.txt', 'rb') as fp: fractal_span1 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/iterations_iter_count_{iter_count}_depth_{depth}_delta_{deltas[1]}.txt', 'rb') as fp: iterations2 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/length_iter_count_{iter_count}_depth_{depth}_delta_{deltas[1]}.txt', 'rb') as fp: line_length2 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/square_iter_count_{iter_count}_depth_{depth}_delta_{deltas[1]}.txt', 'rb') as fp: square2 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/volume_iter_count_{iter_count}_depth_{depth}_delta_{deltas[1]}.txt', 'rb') as fp: volume2 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/s_l_iter_count_{iter_count}_depth_{depth}_delta_{deltas[1]}.txt', 'rb') as fp: s_l2 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/v_s_iter_count_{iter_count}_depth_{depth}_delta_{deltas[1]}.txt', 'rb') as fp: v_s2 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/v_l_iter_count_{iter_count}_depth_{depth}_delta_{deltas[1]}.txt', 'rb') as fp: v_l2 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/v_v_base_iter_count_{iter_count}_depth_{depth}_delta_{deltas[1]}.txt', 'rb') as fp: v_v_base2 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/fractal_span_iter_count_{iter_count}_depth_{depth}_delta_{deltas[1]}.txt', 'rb') as fp: fractal_span2 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/iterations_iter_count_{iter_count}_depth_{depth}_delta_{deltas[2]}.txt', 'rb') as fp: iterations3 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/length_iter_count_{iter_count}_depth_{depth}_delta_{deltas[2]}.txt', 'rb') as fp: line_length3 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/square_iter_count_{iter_count}_depth_{depth}_delta_{deltas[2]}.txt', 'rb') as fp: square3 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/volume_iter_count_{iter_count}_depth_{depth}_delta_{deltas[2]}.txt', 'rb') as fp: volume3 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/s_l_iter_count_{iter_count}_depth_{depth}_delta_{deltas[2]}.txt', 'rb') as fp: s_l3 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/v_s_iter_count_{iter_count}_depth_{depth}_delta_{deltas[2]}.txt', 'rb') as fp: v_s3 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/v_l_iter_count_{iter_count}_depth_{depth}_delta_{deltas[2]}.txt', 'rb') as fp: v_l3 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/v_v_base_iter_count_{iter_count}_depth_{depth}_delta_{deltas[2]}.txt', 'rb') as fp: v_v_base3 = pickle.load(fp) with open(f'../metrics/datasets/several_phases/fractal_span_iter_count_{iter_count}_depth_{depth}_delta_{deltas[2]}.txt', 'rb') as fp: fractal_span3 = pickle.load(fp) # Строим графики для найденных и апроксимируемыъ метрик. fig1, ax1 = plt.subplots() ax1.plot(iterations1, line_length1, 'o', label=r'$1$', c='black', linewidth=1) ax1.plot(iterations2, line_length2, 'o', label=r'$200$', c='red', linewidth=1) ax1.plot(iterations3, line_length3, 'o', label=r'$400$', c='blue', linewidth=1) fig2, ax2 = plt.subplots() ax2.plot(iterations1, square1, 'X', label=r'$1$', c='black', linewidth=1) ax2.plot(iterations2, square2, 'X', label=r'$200$', c='red', linewidth=1) ax2.plot(iterations3, square3, 'X', label=r'$400$', c='blue', linewidth=1) fig3, ax3 = plt.subplots() ax3.plot(iterations1, volume1, '*', label=r'$1$', c='black', linewidth=1) ax3.plot(iterations2, volume2, '*', label=r'$200$', c='red', linewidth=1) ax3.plot(iterations3, volume3, '*', label=r'$400$', c='blue', linewidth=1) fig4, ax4 = plt.subplots() ax4.plot(iterations1, s_l1, '*', label=r'$1$', c='black', linewidth=1) ax4.plot(iterations2, s_l2, '*', label=r'$200$', c='red', linewidth=1) ax4.plot(iterations3, s_l3, '*', label=r'$400$', c='blue', linewidth=1) fig5, ax5 = plt.subplots() ax5.plot(iterations1, v_s1, '*', label=r'$1$', c='black', linewidth=1) ax5.plot(iterations2, v_s2, '*', label=r'$200$', c='red', linewidth=1) ax5.plot(iterations3, v_s3, '*', label=r'$400$', c='blue', linewidth=1) fig6, ax6 = plt.subplots() ax6.plot(iterations1, v_l1, '*', label=r'$1$', c='black', linewidth=1) ax6.plot(iterations2, v_l2, '*', label=r'$200$', c='red', linewidth=1) ax6.plot(iterations3, v_l3, '*', label=r'$400$', c='blue', linewidth=1) fig7, ax7 = plt.subplots() ax7.plot(iterations1, v_v_base1, '*', label=r'$1$', c='black', linewidth=1) ax7.plot(iterations2, v_v_base2, '*', label=r'$200$', c='red', linewidth=1) ax7.plot(iterations3, v_v_base3, '*', label=r'$400$', c='blue', linewidth=1) fig8, ax8 = plt.subplots() ax8.plot(iterations1, fractal_span1, '*', label=r'$1$', c='black', linewidth=1) ax8.plot(iterations2, fractal_span2, '*', label=r'$200$', c='red', linewidth=1) ax8.plot(iterations3, fractal_span3, '*', label=r'$400$', c='blue', linewidth=1) ax1.grid(True) ax2.grid(True) ax3.grid(True) ax4.grid(True) ax5.grid(True) ax6.grid(True) ax7.grid(True) ax8.grid(True) ax1.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax1.set(xlabel='Число циклов роста, ед.', ylabel='Длина фрактальной линии, ед.') ax2.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax2.set(xlabel='Число циклов роста, ед.', ylabel='Площадь фрактала, ед.') ax3.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax3.set(xlabel='Число циклов роста, ед.', ylabel='Объем фрактала, ед.') ax4.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax4.set(xlabel='Число циклов роста, ед.', ylabel='Отношение S/L, ед.') ax5.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax5.set(xlabel='Число циклов роста, ед.', ylabel='Отношение V/S, ед.') ax6.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax6.set(xlabel='Число циклов роста, ед.', ylabel='Отношение V/L, ед.') ax7.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax7.set(xlabel='Число циклов роста, ед.', ylabel='Отношение 4*V1/V0, ед.') ax8.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax8.set(xlabel='Число циклов роста, ед.', ylabel='Размах фрактала, ед.') fig1.savefig(f'../metrics/graphics/several_phases/length.png') fig2.savefig(f'../metrics/graphics/several_phases/square.png') fig3.savefig(f'../metrics/graphics/several_phases/value.png') fig4.savefig(f'../metrics/graphics/several_phases/s_l.png') fig5.savefig(f'../metrics/graphics/several_phases/v_s.png') fig6.savefig(f'../metrics/graphics/several_phases/v_l.png') fig7.savefig(f'../metrics/graphics/several_phases/4v1_v0.png') fig8.savefig(f'../metrics/graphics/several_phases/fractal_span.png') plt.show() def build_stochastic(iter_count: int, depth: int, l_rndms: List[float]): with open(f'../metrics/datasets/stochasticity/iterations_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[0]}.txt', 'rb') as fp: iterations1 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/length_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[0]}.txt', 'rb') as fp: line_length1 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/square_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[0]}.txt', 'rb') as fp: square1 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/volume_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[0]}.txt', 'rb') as fp: volume1 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/s_l_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[0]}.txt', 'rb') as fp: s_l1 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/v_s_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[0]}.txt', 'rb') as fp: v_s1 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/v_l_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[0]}.txt', 'rb') as fp: v_l1 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/v_v_base_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[0]}.txt', 'rb') as fp: v_v_base1 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/fractal_span_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[0]}.txt', 'rb') as fp: fractal_span1 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/iterations_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[1]}.txt', 'rb') as fp: iterations2 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/length_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[1]}.txt', 'rb') as fp: line_length2 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/square_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[1]}.txt', 'rb') as fp: square2 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/volume_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[1]}.txt', 'rb') as fp: volume2 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/s_l_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[1]}.txt', 'rb') as fp: s_l2 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/v_s_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[1]}.txt', 'rb') as fp: v_s2 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/v_l_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[1]}.txt', 'rb') as fp: v_l2 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/v_v_base_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[1]}.txt', 'rb') as fp: v_v_base2 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/fractal_span_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[1]}.txt', 'rb') as fp: fractal_span2 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/iterations_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[2]}.txt', 'rb') as fp: iterations3 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/length_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[2]}.txt', 'rb') as fp: line_length3 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/square_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[2]}.txt', 'rb') as fp: square3 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/volume_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[2]}.txt', 'rb') as fp: volume3 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/s_l_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[2]}.txt', 'rb') as fp: s_l3 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/v_s_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[2]}.txt', 'rb') as fp: v_s3 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/v_l_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[2]}.txt', 'rb') as fp: v_l3 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/v_v_base_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[2]}.txt', 'rb') as fp: v_v_base3 = pickle.load(fp) with open(f'../metrics/datasets/stochasticity/fractal_span_iter_count_{iter_count}_depth_{depth}_l_rnd_{l_rndms[2]}.txt', 'rb') as fp: fractal_span3 = pickle.load(fp) # Строим графики для найденных и апроксимируемыъ метрик. fig1, ax1 = plt.subplots() ax1.plot(iterations1, line_length1, 'o', label=r'$0.6$', c='black', linewidth=1) ax1.plot(iterations2, line_length2, 'o', label=r'$0.75$', c='red', linewidth=1) ax1.plot(iterations3, line_length3, 'o', label=r'$0.9$', c='blue', linewidth=1) fig2, ax2 = plt.subplots() ax2.plot(iterations1, square1, 'X', label=r'$0.6$', c='black', linewidth=1) ax2.plot(iterations2, square2, 'X', label=r'$0.75$', c='red', linewidth=1) ax2.plot(iterations3, square3, 'X', label=r'$0.9$', c='blue', linewidth=1) fig3, ax3 = plt.subplots() ax3.plot(iterations1, volume1, '*', label=r'$0.6$', c='black', linewidth=1) ax3.plot(iterations2, volume2, '*', label=r'$0.75$', c='red', linewidth=1) ax3.plot(iterations3, volume3, '*', label=r'$0.9$', c='blue', linewidth=1) fig4, ax4 = plt.subplots() ax4.plot(iterations1, s_l1, '*', label=r'$0.6$', c='black', linewidth=1) ax4.plot(iterations2, s_l2, '*', label=r'$0.75$', c='red', linewidth=1) ax4.plot(iterations3, s_l3, '*', label=r'$0.9$', c='blue', linewidth=1) fig5, ax5 = plt.subplots() ax5.plot(iterations1, v_s1, '*', label=r'$0.6$', c='black', linewidth=1) ax5.plot(iterations2, v_s2, '*', label=r'$0.75$', c='red', linewidth=1) ax5.plot(iterations3, v_s3, '*', label=r'$0.9$', c='blue', linewidth=1) fig6, ax6 = plt.subplots() ax6.plot(iterations1, v_l1, '*', label=r'$0.6$', c='black', linewidth=1) ax6.plot(iterations2, v_l2, '*', label=r'$0.75$', c='red', linewidth=1) ax6.plot(iterations3, v_l3, '*', label=r'$0.9$', c='blue', linewidth=1) fig7, ax7 = plt.subplots() ax7.plot(iterations1, v_v_base1, '*', label=r'$0.6$', c='black', linewidth=1) ax7.plot(iterations2, v_v_base2, '*', label=r'$0.75$', c='red', linewidth=1) ax7.plot(iterations3, v_v_base3, '*', label=r'$0.9$', c='blue', linewidth=1) fig8, ax8 = plt.subplots() ax8.plot(iterations1, fractal_span1, '*', label=r'$0.6$', c='black', linewidth=1) ax8.plot(iterations2, fractal_span2, '*', label=r'$0.75$', c='red', linewidth=1) ax8.plot(iterations3, fractal_span3, '*', label=r'$0.9$', c='blue', linewidth=1) ax1.grid(True) ax2.grid(True) ax3.grid(True) ax4.grid(True) ax5.grid(True) ax6.grid(True) ax7.grid(True) ax8.grid(True) ax1.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax1.set(xlabel='Число циклов роста, ед.', ylabel='Длина фрактальной линии, ед.') ax2.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax2.set(xlabel='Число циклов роста, ед.', ylabel='Площадь фрактала, ед.') ax3.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax3.set(xlabel='Число циклов роста, ед.', ylabel='Объем фрактала, ед.') ax4.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax4.set(xlabel='Число циклов роста, ед.', ylabel='Отношение S/L, ед.') ax5.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax5.set(xlabel='Число циклов роста, ед.', ylabel='Отношение V/S, ед.') ax6.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax6.set(xlabel='Число циклов роста, ед.', ylabel='Отношение V/L, ед.') ax7.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax7.set(xlabel='Число циклов роста, ед.', ylabel='Отношение 4*V1/V0, ед.') ax8.legend(loc='upper left', fancybox=True, framealpha=1, shadow=True, borderpad=1) ax8.set(xlabel='Число циклов роста, ед.', ylabel='Размах фрактала, ед.') fig1.savefig(f'../metrics/graphics/stochasticity/length.png') fig2.savefig(f'../metrics/graphics/stochasticity/square.png') fig3.savefig(f'../metrics/graphics/stochasticity/value.png') fig4.savefig(f'../metrics/graphics/stochasticity/s_l.png') fig5.savefig(f'../metrics/graphics/stochasticity/v_s.png') fig6.savefig(f'../metrics/graphics/stochasticity/v_l.png') fig7.savefig(f'../metrics/graphics/stochasticity/4v1_v0.png') fig8.savefig(f'../metrics/graphics/stochasticity/fractal_span.png') plt.show() if __name__ == '__main__': build_classic_one_phase(1000, 7) build_one_phase(1000, 7) build_several_phases(1000, 7, [1, 200, 400]) build_stochastic(1000, 7, [0.6, 0.75, 0.9])

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a637e891d8c6a5f525f598e654ebe48a31950462

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py

Python

pyioflash/postprocess/sources/energy.py

Balaras-Group/pyIOFlash

d75be74165a1b0114ed3f6186800ed33e06c3d58

[ "MIT" ]

null

pyioflash/postprocess/sources/energy.py

Balaras-Group/pyIOFlash

d75be74165a1b0114ed3f6186800ed33e06c3d58

[ "MIT" ]

null

pyioflash/postprocess/sources/energy.py

Balaras-Group/pyIOFlash

d75be74165a1b0114ed3f6186800ed33e06c3d58

[ "MIT" ]

null

""" This module defines the energy calculation methods of the post-processing subpackage of the pyioflash lbrary; part of the 'source' set of routines. This module currently defines the following methods: thermal -- -- -- -> thermal energy kinetic -- -- -- -> total instantanious kinetic energy kinetic_mean -- -> mean (time averaged) kinetic energy kinetic_turbulant -> turbulant instantanious kinetic energy Todo: """ from typing import List, Dict, Optional, Union, TYPE_CHECKING from pyioflash.postprocess.utility import _interpolate_ftc, make_sourceable, make_stackable, Output from pyioflash.postprocess.sources import fields from pyioflash.postprocess.elements import integral from pyioflash.postprocess.analyses import series if TYPE_CHECKING: from pyioflash.simulation.data import SimulationData from pyioflash.postprocess.utility import Type_Step, Type_Field, Type_Index, Type_Output # define the module api def __dir__() -> List[str]: return ["thermal", "kinetic", "kinetic_mean", "kinetic_turbulant"] def thermal(data: 'SimulationData', step: 'Type_Step' = -1, *, wrapped: bool = False, mapping: Dict[str, str] = {}, scale: Optional[float] = None, index: Optional['Type_Index'] = None, withguard: bool = False, keepdims: bool = True) -> 'Type_Output': """ Provides a method for calculation of the thermal energy by consuming a SimulationData object; must have a 'temp' attribute in the SimulationData.fields object. Attributes: data: object containing relavent flash simulation output step: time-like specification for which to process data, the key (optional) wrapped: whether to wrap context around result of sourcing (optional) mapping: if wrapped, how to map context to options of the next operation (optional) scale: used to convert returned quantity to dimensional units (optional) index: used for custom slicing operation; should be (blks, k, j, i) (optional) withguard: retain guard cell data for ploting and other actions (optional) keepdims: retain unused dimensions for broadcasting, else drop them (optional) Note: The thermal energy is computed according to the formula E(t)~ijk~ = T(t)~ijk~ *where t = step, step is float* * t = times[step], step is int* *ijk = all cells* The returned quantity is on the cell centered grid This function does not generate any dynamic context; this even if wrapping is desired and specified, the mapping attribute is ignored. Todo: """ # convert to integer from key if necessary if isinstance(step, float): try: step, = data.utility.indices(step) except ValueError as error: print(error) print('Could not find provided step in simulation keys!') # need the dimensionality dimension = data.geometry.grd_dim # get guard size guards = data.geometry.blk_guards # need to define slicing operators based on dims if index is None: i_all = slice(None) i_zax = 0 if not withguard else int(guards / 2) index = (i_all, ) * 4 if (keepdims or dimension == 3) else (i_all, i_zax, i_all, i_all) # define lookup based on desired guarding option name = 'temp' if withguard: name = '_' + name # thermal energy is temp in nondimensional units energy = data.fields[name][step][0] # apply a dimensional scale if scale is not None: energy = energy * scale # index results if desired energy = energy[index] # wrap result of integration if desired (no context to provide) wrap = {True: lambda source: Output(source), False: lambda source: source} return wrap[wrapped](energy) def kinetic(data: 'SimulationData', step: 'Type_Step' = -1, *, wrapped: bool = False, mapping: Dict[str, str] = {}, scale : Optional[float] = None, index: Optional['Type_Index'] = None, withguard: bool = False, keepdims: bool = True) -> 'Type_Output': """ Provides a method for calculation of the total kinetic energy by consuming a SimulationData object; must have 'fcx2', 'fcy2' ('fcz2' if 3d) attributes in the SimulationData.fields object. Attributes: data: object containing relavent flash simulation output step: time-like specification for which to process data, the key (optional) wrapped: whether to wrap context around result of sourcing (optional) mapping: if wrapped, how to map context to options of the next operation (optional) scale: used to convert returned quantity to dimensional units (optional) index: used for custom slicing operation; should be (blks, k, j, i) (optional) withguard: retain guard cell data for ploting and other actions (optional) keepdims: retain unused dimensions for broadcasting, else drop them (optional) Note: The total kinetic energy is computed according to the formula E(t)~ijk~ = u(t)~ijk~^2^ + v(t)~ijk~^2^ + w(t)~ijk~^2^ *where t = step, step is float* * t = times[step], step is int* *ijk = all cells* where the all terms are interpolated to cell centers This function does not generate any dynamic context; this even if wrapping is desired and specified, the mapping attribute is ignored. Todo: """ # convert to integer from key if necessary if isinstance(step, float): try: step, = data.utility.indices(step) except ValueError as error: print(error) print('Could not find provided step in simulation keys!') # need the dimensionality dimension = data.geometry.grd_dim # get guard size guards = data.geometry.blk_guards # need to define slicing operators based on dims if index is None: i_all = slice(None) i_zax = 0 if not withguard else int(guards / 2) index = (i_all, ) * 4 if (keepdims or dimension == 3) else (i_all, i_zax, i_all, i_all) # calculate kinetic energy energy = _interpolate_ftc(data.fields['_fcx2'][step][0], 0, guards, dimension, withguard=withguard)**2 energy = _interpolate_ftc(data.fields['_fcy2'][step][0], 1, guards, dimension, withguard=withguard)**2 + energy if dimension == 3: energy = _interpolate_ftc(data.fields['_fcz2'][step][0], 2, guards, dimension, withguard=withguard)**2 + energy # apply a dimensional scale if scale is not None: energy = energy * scale # index results if desired energy = energy[index] # wrap result of integration if desired (no context to provide) wrap = {True: lambda source: Output(source), False: lambda source: source} return wrap[wrapped](energy) def kinetic_mean(data: 'SimulationData', steps: Optional['Type_Index'] = slice(None), *, start: Optional['Type_Step'] = None, stop: Optional['Type_Step'] = None, skip: Optional[int] = None, wrapped: bool = False, mapping: Dict[str, str] = {}, scale : Optional[float] = None, index: Optional['Type_Index'] = None, withguard: bool = False, keepdims: bool = True) -> 'Type_Output': """ Provides a method for calculation of the mean or time-averaged kinetic energy by consuming a SimulationData object and a time interval specification; must have 'fcx2', 'fcy2' ('fcz2' if 3d) attributes in the SimulationData.fields object. Attributes: data: object containing relavent flash simulation output steps: iterable time-like specification for which to process data, the keys (optional) start: used to determine the starting time-like specification, start key (optional) stop: used to determine the ending time-like specification, stop key (optional) skip: used to determine the sampling interval for the specification (optional) wrapped: whether to wrap context around result of sourcing (optional) mapping: if wrapped, how to map context to options of the next operation (optional) scale: used to convert returned quantity to dimensional units (optional) index: used for custom slicing operation; should be (blks, k, j, i) (optional) withguard: retain guard cell data for ploting and other actions (optional) keepdims: retain unused dimensions for broadcasting, else drop them (optional) Note: The mean kinetic energy is computed according to the formula E(t)~ijk~ = $\sum_{$\tau$=t~0~}^{t} (u($\tau$)~ijk~^2^ + v($\tau)~ijk~^2^ + w($tau$)~ijk~^2^) / N *where the all terms are interpolated to cell centers* This function does not generate any dynamic context; this even if wrapping is desired and specified, the mapping attribute is ignored. Todo: """ # need the dimensionality dimension = data.geometry.grd_dim # get guard size guards = data.geometry.blk_guards # need to define slicing operators based on dims if index is None: i_all = slice(None) i_zax = 0 if not withguard else int(guards / 2) index = (i_all, ) * 4 if (keepdims or dimension == 3) else (i_all, i_zax, i_all, i_all) # use provided information to source times if start or stop: steps = slice(start, stop, skip) times = data.utility.times(steps) steps = data.utility.indices(steps) # use time series analysis to retreve mean kinetic energy source = make_sourceable(source=kinetic, args=data, method='step', options={'withguard': withguard}) stack = make_stackable(element=integral.time, args=data, method='whole', options={'times': times}) energy = series.simple(source=source, sourceby=steps, stack=stack) # apply a dimensional scale if scale is not None: energy = energy * scale # index results if desired energy = energy[index] # wrap result of integration if desired (no context to provide) wrap = {True: lambda source: Output(source), False: lambda source: source} return wrap[wrapped](energy) def kinetic_turbulant(data: 'SimulationData', step: Optional['Type_Step'] = -1, *, mean: Optional['Type_Field'] = None, start: Optional['Type_Step'] = None, stop: Optional['Type_Step'] = None, skip: Optional[int] = None, wrapped: bool = False, mapping: Dict[str, str] = {}, scale : Optional[float] = None, index: Optional['Type_Index'] = None, withguard: bool = False, keepdims: bool = True) -> 'Type_Output': """ Provides a method for calculation of the turbulant kinetic energy by consuming a SimulationData object and a either a mean field or a time interval specification to determine the mean field; must have 'fcx2', 'fcy2' ('fcz2' if 3d) attributes in the SimulationData.fields object. Attributes: data: object containing relavent flash simulation output step: time-like specification for which to process data, the key (optional) mean: provide mean turbulant kinetic energy to avoid calculating it (optional) start: used to determine the starting time-like specification, start key (optional) stop: used to determine the ending time-like specification, stop key (optional) skip: used to determine the sampling interval for the specification (optional) wrapped: whether to wrap context around result of sourcing (optional) mapping: if wrapped, how to map context to options of the next operation (optional) scale: used to convert returned quantity to dimensional units (optional) index: used for custom slicing operation; should be (blks, k, j, i) (optional) withguard: retain guard cell data for ploting and other actions (optional) keepdims: retain unused dimensions for broadcasting, else drop them (optional) Note: The turbulant kinetic energy is computed according to the formula E(t)~ijk~ = (u(t)~ijk~ - u_bar~ijk~)^2^ + ... *where the all terms are interpolated to cell centers* If a mean is provided it must be a 2 or 3 component field broadcastable with simulation data velocity components; specifically, (dims, blks, k, j, i). This function does not generate any dynamic context; this even if wrapping is desired and specified, the mapping attribute is ignored. Todo: """ # convert to integer from key if necessary if isinstance(step, float): try: step, = data.utility.indices(step) except ValueError as error: print(error) print('Could not find provided step in simulation keys!') # need the dimensionality dimension = data.geometry.grd_dim # get guard size guards = data.geometry.blk_guards # need to define slicing operators based on dims if index is None: i_all = slice(None) i_zax = 0 if not withguard else int(guards / 2) index = (i_all, ) * 4 if (keepdims or dimension == 3) else (i_all, i_zax, i_all, i_all) # retieve mean velocity components if not provided if mean is None: components = fields.velocity_mean(data, start=start, stop=stop, skip=skip, withguard=withguard) u_bar, v_bar = components[:2] if dimension == 3: w_bar = components[2] # mean is provided else: # is the provided mean usable if not hasattr(mean, '__len__') and len(mean) not in (2, 3): raise TypeError('Provided mean does not have three velocity components!') # unpack provided components u_bar, v_bar = mean[:2] if dimension == 3: w_bar = mean[2] # calculate instantanious velocity components on cell-centers u_ins = _interpolate_ftc(data.fields['_fcx2'][step][0], 0, guards, dimension, withguard=withguard) v_ins = _interpolate_ftc(data.fields['_fcy2'][step][0], 1, guards, dimension, withguard=withguard) if dimension == 3: w_ins = _interpolate_ftc(data.fields['_fcz2'][step][0], 2, guards, dimension, withguard=withguard) # calculate turbulant kinetic energy energy = ((u_ins - u_bar)**2 + (v_ins - v_bar)**2) / 2 if dimension == 3: energy = energy + ((w_ins - w_bar)**2 / 2) # apply a dimensional scale if scale is not None: energy = energy * scale # index results if desired energy = energy[index] # wrap result of integration if desired (no context to provide) wrap = {True: lambda source: Output(source), False: lambda source: source} return wrap[wrapped](energy)

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25

py

Python

pydobot/__init__.py

luismesas/pyDobotMagician

2ff8d7e1318ac9b7bc32bd33ff327d343f44927c

[ "MIT" ]

82

2017-04-08T04:15:39.000Z

2022-02-18T08:16:01.000Z

pydobot/__init__.py

luismesas/pyDobotMagician

2ff8d7e1318ac9b7bc32bd33ff327d343f44927c

[ "MIT" ]

30

2017-04-13T09:45:59.000Z

2022-03-11T07:51:31.000Z

pydobot/__init__.py

luismesas/pyDobotMagician

2ff8d7e1318ac9b7bc32bd33ff327d343f44927c

[ "MIT" ]

53

2017-06-13T15:36:47.000Z

2022-03-31T12:39:26.000Z

from .dobot import Dobot

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a6a0c7b8176fbfad01e7091cb6d0c95ac7af6175

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py

Python

calc.py

negi524/python_test

882e669d14ffb012dd2b640377d457541b9e8360

[ "MIT" ]

null

calc.py

negi524/python_test

882e669d14ffb012dd2b640377d457541b9e8360

[ "MIT" ]

null

calc.py

negi524/python_test

882e669d14ffb012dd2b640377d457541b9e8360

[ "MIT" ]

null

def double(number): return 2 * number

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py

Python

bootstrap/lib/overwrite_print.py

Cadene/bootstrap.pytorch

e7d55b52fe8d819de7ea3da8b1027d4a3dcc9e0c

[ "BSD-3-Clause" ]

196

2018-01-12T01:07:47.000Z

2022-03-18T21:42:11.000Z

bootstrap/lib/overwrite_print.py

jbegaint/bootstrap.pytorch

43b0be90e39fdb96018411cb5bfad6bc9d29f023

[ "BSD-3-Clause" ]

32

2019-02-24T11:08:22.000Z

2020-07-17T14:33:02.000Z

bootstrap/lib/overwrite_print.py

jbegaint/bootstrap.pytorch

43b0be90e39fdb96018411cb5bfad6bc9d29f023

[ "BSD-3-Clause" ]

30

2018-03-22T23:51:01.000Z

2022-03-27T12:13:06.000Z

from .logger import Logger # TODO: better overwritting def print(*msg): Logger().log_message(*msg, stack_displacement=2)

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py

Python

agent_listener.py

fringsoo/pragmatics_game

1b8ca08a043dbbd063374d9303e843aceb9fc335

[ "MIT" ]

4

2020-12-10T10:29:47.000Z

2021-06-06T23:06:43.000Z

agent_listener.py

fringsoo/pragmatics_game

1b8ca08a043dbbd063374d9303e843aceb9fc335

[ "MIT" ]

4

2021-06-06T13:05:37.000Z

2021-07-02T12:15:28.000Z

agent_listener.py

fringsoo/pragmatics_game

1b8ca08a043dbbd063374d9303e843aceb9fc335

[ "MIT" ]

1

2021-06-06T14:59:54.000Z

import random import numpy as np import scipy import time import json import os import pdb import pickle import pandas from progressbar import * from keras.layers import Input, Dense, LSTM, Lambda, concatenate, add, Dot from keras.models import Sequential, load_model, Model from keras.optimizers import RMSprop, Adam, SGD from keras import backend as K from keras import regularizers from keras.utils.np_utils import to_categorical from utils import convnet_vgg, convnet_mod, convnet_ori, convnet_com def softmax(x): e_x = np.exp(x - np.max(x)) return e_x / e_x.sum() #return x / np.linalg.norm(x) def makeFunc(x): return lambda y:y[:,x] class BaseListenerNetwork(object): def __init__(self, modelname, optfilename, lr, entropy_coefficient, config_dict): self.modelname = modelname self.optfilename = optfilename self.lr = lr self.entropy_coefficient = entropy_coefficient assert config_dict, "config_dict does not exist" self.config = config_dict self.initialize_model() self.build_train_fn() def rebuild_train_fn(self, entropy_coefficient=None, lr=None): if entropy_coefficient: self.entropy_coefficient = entropy_coefficient if lr: self.lr = lr self.build_train_fn() def save(self): self.listener_model.save(self.modelname) def load(self): self.listener_model = load_model(self.modelname) def save_weights(self): self.listener_model.save_weights(self.modelname) def load_weights(self): self.listener_model.load_weights(self.modelname) def save_opt(self): symbolic_weights = self.opt.weights weight_values = K.batch_get_value(symbolic_weights) with open(self.optfilename, 'wb') as f: pickle.dump(weight_values, f) def load_opt(self): with open(self.optfilename, 'rb') as f: weight_values = pickle.load(f) self.opt.set_weights(weight_values) def save_memory(self): self.memory_model_weights = self.listener_model.get_weights() def load_memory(self): self.listener_model.set_weights(self.memory_model_weights) class PaperListenerNetwork(BaseListenerNetwork): def __init__(self, modelname, optfilename, lr, entropy_coefficient, config_dict): super(PaperListenerNetwork, self).__init__(modelname, optfilename, lr, entropy_coefficient, config_dict) self.batch_speaker_message = [] self.batch_action = [] self.batch_candidates = [] self.batch_reward = [] def initialize_model(self): """ Batch input and output. """ if not os.path.exists(self.modelname): ## Define model t_input = Input(shape=(self.config['max_message_length'],)) #Speakers Message, shape(bs, max_message_length) c_inputs_all = Input(shape=(self.config['n_classes'], self.config['speaker_input_dim'])) #Candidates, shape(bs, n_class, speaker_input_dim) inputs = [t_input, c_inputs_all] z = Dense(self.config['speaker_input_dim'], activation='sigmoid')(t_input) #shape(bs, speaker_input_dim) ts = [] us = [] for _ in range(self.config['n_classes']): #c_input = Input(shape=(self.config['speaker_input_dim'],)) #shape(bs, speaker_input_dim) c_input = Lambda(makeFunc(_))(c_inputs_all) #shape(bs, speaker_input_dim) #t = Lambda(lambda x: K.expand_dims(K.sum(-K.square(x), axis=1)))(add([t_trans, Lambda(lambda x: -x)(c_input)])) #shape(bs, 1) t = Dot(1, False)([z, c_input]) #shape(bs, 1) ts.append(t) us.append(c_input) U = concatenate(ts) #shape(bs, n_classes) us = concatenate(us) final_output = Lambda(lambda x: K.softmax(x))(U) #shape(bs, n_classes) #final_output = Dense(self.n_classes, activation='softmax', kernel_initializer='identity')(U) #final_output = Dense(self.n_classes, activation='softmax')(U) #f1 = Dense(50)(U) #f2 = Lambda(lambda x: K.square(x))(f1) #final_output = Dense(self.n_classes, activation='softmax')(f2) self.listener_model = Model(inputs=inputs, outputs=[final_output, U, z, us]) #self.listener_model.compile(loss="categorical_crossentropy", optimizer=RMSprop(lr=self.config['listener_lr'])) else: self.load() #check!!! def build_train_fn(self): """ Batch input and output. """ #direct prob input!!! action_prob_placeholder = self.listener_model.output[0] #(bs, n_classes) action_onehot_placeholder = K.placeholder(shape=(None, self.config['n_classes']), name="action_onehot") #(bs, n_classes) reward_placeholder = K.placeholder(shape=(None,), name="reward") #(?) action_prob = K.sum(action_prob_placeholder * action_onehot_placeholder, axis=1) log_action_prob = K.log(action_prob) loss = - log_action_prob * reward_placeholder entropy = K.sum(action_prob_placeholder * K.log(action_prob_placeholder + 1e-10), axis=1) #entropy = K.sum(entropy) loss = loss + self.entropy_coefficient * entropy loss = K.mean(loss) self.opt = Adam(lr=self.lr) self.updates = self.opt.get_updates(params=self.listener_model.trainable_weights, loss=loss) if os.path.exists(self.optfilename): self.load_opt() self.train_fn = K.function( inputs = self.listener_model.input + [action_onehot_placeholder, reward_placeholder], outputs=[loss, loss], updates=self.updates) def reshape_message_candidates(self, speaker_message, candidates): assert len(speaker_message.shape)==1 and speaker_message.shape[0]==self.config['max_message_length'] assert len(candidates.shape)==2 and candidates.shape[0]==self.config['n_classes'] and candidates.shape[1]==self.config['speaker_input_dim'] speaker_message = np.expand_dims(speaker_message, axis=0) #shape(1, max_message_length) #X = [speaker_message] + [c.reshape([1,-1]) for c in candidates] X = [speaker_message, np.expand_dims(candidates, axis=0)] return X def sample_from_listener_policy(self, speaker_message, candidates): """ Input and output are all just one instance. No bs dimensize. """ X = self.reshape_message_candidates(speaker_message, candidates) listener_output= self.listener_model.predict_on_batch(X) y, U, z = listener_output[:3] #us = listener_output[3] listener_probs = y listener_probs = np.squeeze(listener_probs) #shape(n_class) listener_action = np.random.choice(np.arange(self.config['n_classes']), p=listener_probs) #int U = np.squeeze(U) return listener_action, listener_probs, U def infer_from_listener_policy(self, speaker_message, candidates): """ Input and output are all just one instance. No bs dimensize. """ X = self.reshape_message_candidates(speaker_message, candidates) listener_output= self.listener_model.predict_on_batch(X) y, U, z = listener_output[:3] #us = listener_output[3] listener_probs = y listener_probs = np.squeeze(listener_probs) #shape(n_class) listener_action = np.argmax(listener_probs) #int U = np.squeeze(U) return listener_action, listener_probs, U def train_listener_policy_on_batch(self): """ Train as a batch. Loss is an float for a batch """ action_onehot = to_categorical(self.batch_action, num_classes=self.config['n_classes']) #self.batch_candidates = np.array(self.batch_candidates).transpose([1, 0, 2]).tolist() #shape(num_classes, bs, speaker_input_dim) #self.batch_candidates = np.swapaxes(np.array(self.batch_candidates), 0, 1).tolist() #shape(num_classes, bs, speaker_input_dim) #self.batch_candidates = np.swapaxes(np.array(self.batch_candidates), 0, 1).astype('float32').tolist() #shape(num_classes, bs, speaker_input_dim) #self.batch_candidates = [np.array(_) for _ in self.batch_candidates] #_loss, _entropy = self.train_fn([self.batch_speaker_message] + self.batch_candidates + [action_onehot, self.batch_reward] ) _loss, _entropy = self.train_fn([np.array(self.batch_speaker_message), self.batch_candidates, action_onehot, self.batch_reward] ) #print("Listener loss: ", _loss) self.batch_speaker_message = [] #shape(bs, max_message_length) self.batch_action = [] #shape(bs) self.batch_candidates = [] #shape(bs, n_classes, speaker_input_dim) self.batch_reward = [] #shape(bs) def remember_listener_training_details(self, speaker_message, action, action_probs, target, candidates, reward): """ Inputs are just one instance. No bs dimensize. """ self.batch_speaker_message.append(speaker_message) self.batch_action.append(action) self.batch_candidates.append(candidates) self.batch_reward.append(reward) class PaperListenerNetwork_rnn(PaperListenerNetwork): def reshape_message_candidates(self, speaker_message, candidates): #if not self.config['fixed_length']: # assert len(speaker_message.shape)==1 and speaker_message.shape[0]<=self.config['max_message_length'] #else: # assert len(speaker_message.shape)==1 and speaker_message.shape[0]==self.config['max_message_length'] assert len(speaker_message.shape)==1 and speaker_message.shape[0]<=self.config['max_message_length'] assert len(candidates.shape)==2 and candidates.shape[0]==self.config['n_classes'] and candidates.shape[1]==self.config['speaker_input_dim'] speaker_message = np.expand_dims(to_categorical(speaker_message, self.config['alphabet_size']), axis=0) #shape(1, message_length, alphabet_size) #X = [speaker_message] + [c.reshape([1,-1]) for c in candidates] X = [speaker_message, np.expand_dims(candidates, axis=0)] return X def initialize_model(self): """ Batch input and output. """ ## Define model if not os.path.exists(self.modelname): t_input = Input(shape=(None, self.config['alphabet_size'],)) #Speakers Message, shape(bs, message_length, alphabet_size) #c_inputs_all = Input(shape=(self.config['n_classes'], self.config['speaker_input_dim'])) #Candidates, shape(bs, n_classes, speaker_input_dim) c_inputs_all = Input(shape=(None, self.config['speaker_input_dim'])) #Candidates, shape(bs, n_classes, speaker_input_dim) inputs = [t_input, c_inputs_all] lstm = LSTM(self.config['listener_dim'], activation='tanh', return_sequences=False, return_state=True) o, sh, sc = lstm(t_input) z = Dense(self.config['listener_dim'], activation='sigmoid')(o) #shape(bs, listener_dim) ts = [] us = [] u = Dense(self.config['listener_dim'], activation='sigmoid') for _ in range(self.config['n_classes']): #c_input = Input(shape=(self.config['speaker_input_dim'],)) #shape(bs, speaker_input_dim) c_input = Lambda(makeFunc(_))(c_inputs_all) uc = u(c_input) t = Lambda(lambda x: K.expand_dims(K.sum(-K.square(x), axis=1)))(add([z, Lambda(lambda x: -x)(uc)])) #shape(bs, 1) #t = Dot(1, False)([z,uc]) #shape(bs, 1) ts.append(t) us.append(uc) U = concatenate(ts) #shape(bs, n_classes) us = concatenate(us) final_output = Lambda(lambda x: K.softmax(x))(U) #shape(bs, n_classes) self.listener_model = Model(inputs=inputs, outputs=[final_output, U, z, us]) #self.listener_model.compile(loss="categorical_crossentropy", optimizer=RMSprop(lr=self.config['listener_lr'])) else: self.load() #check!!! def set_updates(self): self.opt = Adam(lr=self.lr) #adam = RMSprop(lr=self.lr) self.updates = self.opt.get_updates(params=self.listener_model.trainable_weights, loss=self.loss) if os.path.exists(self.optfilename): self.load_opt() def build_train_fn(self): """ Batch input and output. """ #direct prob input!!! action_prob_placeholder = self.listener_model.output[0] #(bs, n_classes) #action_onehot_placeholder = K.placeholder(shape=(None, self.config['n_classes']), name="action_onehot") #(bs, n_classes) action_onehot_placeholder = K.placeholder(shape=(None, None), name="action_onehot") #(bs, n_classes) reward_placeholder = K.placeholder(shape=(None,), name="reward") #(?) action_prob = K.sum(action_prob_placeholder*action_onehot_placeholder, axis=1) log_action_prob = K.log(action_prob) loss = - log_action_prob*reward_placeholder entropy = K.sum(action_prob_placeholder * K.log(action_prob_placeholder + 1e-10), axis=1) #entropy = K.sum(entropy) loss = loss + self.entropy_coefficient * entropy loss = K.mean(loss) self.loss =loss self.set_updates() self.train_fn = K.function( inputs = self.listener_model.input + [action_onehot_placeholder, reward_placeholder], outputs=[loss, loss], updates=self.updates) def remember_listener_training_details(self, speaker_message, action, action_probs, target, candidates, reward): """ Inputs are just one instance. No bs dimensize. """ #if not self.config['fixed_length']: toadd = self.config['max_message_length'] - len(speaker_message) for _ in range(toadd): speaker_message = np.append(speaker_message, -1) speaker_message = to_categorical(speaker_message, self.config['alphabet_size']) #shape(message_length, alphabet_size) self.batch_speaker_message.append(speaker_message) self.batch_action.append(action) self.batch_candidates.append(candidates) self.batch_reward.append(reward) class PaperListenerNetwork_rnn_conv(PaperListenerNetwork_rnn): def __init__(self, modelname, optfilename, lr, entropy_coefficient, pretrain_convmodel_file, traincnn, config): self.pretrain_convmodel_file = pretrain_convmodel_file self.traincnn = traincnn super(PaperListenerNetwork_rnn_conv, self).__init__(modelname, optfilename, lr, entropy_coefficient, config) def initialize_model(self): """ Batch input and output. """ if not os.path.exists(self.modelname): ## Define model self.conv_model = convnet_com(self.config['speaker_input_w'], self.config['speaker_input_h'], 3, preloadfile=self.pretrain_convmodel_file, name='conv_model_l') t_input = Input(shape=(None, self.config['alphabet_size'],)) #Speakers Message, shape(bs, message_length, alphabet_size) c_inputs_all = Input(shape=(self.config['n_classes'], self.config['speaker_input_w'], self.config['speaker_input_h'], 3), name='image_l') #Candidates, shape(bs, speaker_input_w, speaker_input_h, 3) inputs = [t_input, c_inputs_all] lstm = LSTM(self.config['listener_dim'], activation='tanh', return_sequences=False, return_state=True) o, sh, sc = lstm(t_input) z = Dense(self.config['listener_dim'], activation='sigmoid')(o) #shape(bs, listener_dim) #u = Dense(self.config['listener_dim'], activation='sigmoid',kernel_regularizer=regularizers.l2(0.01)) u = Dense(self.config['listener_dim'], activation='sigmoid') ts = [] us = [] for _ in range(self.config['n_classes']): #c_input = Input(shape=(self.config['speaker_input_w'],self.config['speaker_input_h'],3)) #speaker_model.input[0], shape(bs, speaker_input_w, speaker_input_h, 3) #c_input = Lambda(lambda x: x[:, _])(c_inputs_all) c_input = Lambda(makeFunc(_))(c_inputs_all) conv_outputs = self.conv_model(c_input) uc = u(conv_outputs) t = Lambda(lambda x: K.expand_dims(K.sum(-K.square(x),axis=1)))(add([z, Lambda(lambda x: -x)(uc)])) #shape(bs, 1) #t = Dot(1, False)([z,uc]) #shape(bs, 1) ts.append(t) us.append(uc) U = concatenate(ts) #shape(bs, n_classes) us = concatenate(us) final_output = Lambda(lambda x: K.softmax(x))(U) #shape(bs, n_classes) self.listener_model = Model(inputs=inputs, outputs=[final_output, U, z, us]) #self.listener_model.compile(loss="categorical_crossentropy", optimizer=RMSprop(lr=self.config['listener_lr'])) else: self.load() #check!!! self.conv_model = [l for l in self.listener_model.layers if l.name=='conv_model_l'][0] #self.listener_model.layers[6].kernel_regularizer = None #self.internal_model = Model(inputs=self.listener_model.inputs, outputs=[self.listener_model.layers[7].get_output_at(_) for _ in range(2)] + [self.listener_model.layers[6].output, self.listener_model.layers[-2].output]) #dot #self.internal_model = Model(inputs=self.listener_model.inputs, outputs=[self.listener_model.layers[6].get_output_at(_) for _ in range(2)] + [self.listener_model.layers[7].output, self.listener_model.layers[-2].output]) #euc self.trainable_weights_others = [] self.trainable_weights_conv = [] for layer in self.listener_model.layers: if layer.name!='conv_model_l': self.trainable_weights_others.extend(layer.trainable_weights) else: self.trainable_weights_conv.extend(layer.trainable_weights) def set_updates(self): self.opt = Adam(lr=self.lr) #self.opt = RMSprop(lr=self.lr) #opt = SGD(lr=self.lr, momentum=0.9, decay=1e-6, nesterov=True) if not self.traincnn: #self.updates = self.opt.get_updates(params=self.trainable_weights_others+self.trainable_weights_rnn, loss=self.loss) self.updates = self.opt.get_updates(params=self.trainable_weights_others, loss=self.loss) else: self.updates = self.opt.get_updates(params=self.listener_model.trainable_weights, loss=self.loss) if os.path.exists(self.optfilename): self.load_opt() def reshape_message_candidates(self, speaker_message, candidates): #if not self.config['fixed_length']: # assert len(speaker_message.shape)==1 and speaker_message.shape[0]<=self.config['max_message_length'] #else: # assert len(speaker_message.shape)==1 and speaker_message.shape[0]==self.config['max_message_length'] assert len(speaker_message.shape)==1 and speaker_message.shape[0]<=self.config['max_message_length'] assert len(candidates.shape)==4 and candidates.shape[0]==self.config['n_classes'] and candidates.shape[1]==self.config['speaker_input_w'] and candidates.shape[2]==self.config['speaker_input_h'] speaker_message = np.expand_dims(to_categorical(speaker_message, self.config['alphabet_size']), axis=0) #shape(1, ?, alphabet_size) X = [speaker_message, np.expand_dims(candidates, axis=0)] return X ''' class PaperListenerNetwork_rnn_conv_color(PaperListenerNetwork_rnn): def initialize_model(self): """ Batch input and output. """ if not os.path.exists(self.modelname): ## Define model t_input = Input(shape=(None, self.config['alphabet_size'],)) #Speakers Message, shape(bs, message_length, alphabet_size) c_inputs_all = Input(shape=(self.config['n_classes'], 8)) inputs = [t_input, c_inputs_all] lstm = LSTM(self.config['listener_dim'], activation='tanh', return_sequences=False, return_state=True) o, sh, sc = lstm(t_input) z = Dense(self.config['listener_dim'], activation='sigmoid')(o) #shape(bs, listener_dim) u = Dense(self.config['listener_dim'], activation='sigmoid') ts = [] for _ in range(self.config['n_classes']): #c_input = Input(shape=(self.config['speaker_input_w'],self.config['speaker_input_h'],3)) #speaker_model.input[0], shape(bs, speaker_input_w, speaker_input_h, 3) #c_input = Lambda(lambda x: x[:, _])(c_inputs_all) c_input = Lambda(makeFunc(_))(c_inputs_all) #conv_outputs = conv_model(c_input) #conv_outputs = c_input uc = u(c_input) t = Lambda(lambda x: K.expand_dims(K.sum(-K.square(x),axis=1)))(add([z, Lambda(lambda x: -x)(uc)])) #shape(bs, 1) ts.append(t) U = concatenate(ts) #shape(bs, n_classes) final_output = Lambda(lambda x: K.softmax(x))(U) #shape(bs, n_classes) self.listener_model = Model(inputs=inputs, outputs=[final_output, z, U]) #self.listener_model.compile(loss="categorical_crossentropy", optimizer=RMSprop(lr=self.config['listener_lr'])) else: self.load() #check!!! self.trainable_weights_rnn = self.listener_model.trainable_weights[:3] self.trainable_weights_others = self.listener_model.trainable_weights[3:] def set_updates(self): self.opt = Adam(lr=self.lr) #opt = RMSprop(lr=self.lr) #opt = SGD(lr=self.lr, momentum=0.9, decay=1e-6, nesterov=True) self.updates = self.opt.get_updates(params=self.listener_model.trainable_weights, loss=self.loss) if os.path.exists(self.optfilename): self.load_opt() def reshape_message_candidates(self, speaker_message, candidates): #if not self.config['fixed_length']: # assert len(speaker_message.shape)==1 and speaker_message.shape[0]<=self.config['max_message_length'] #else: # assert len(speaker_message.shape)==1 and speaker_message.shape[0]==self.config['max_message_length'] #pdb.set_trace() assert len(speaker_message.shape)==1 and speaker_message.shape[0]<=self.config['max_message_length'] assert len(candidates.shape)==2 and candidates.shape[0]==self.config['n_classes'] and candidates.shape[1]==8 speaker_message = np.expand_dims(to_categorical(speaker_message, self.config['alphabet_size']), axis=0) #shape(1, ?, alphabet_size) X = [speaker_message, np.expand_dims(candidates, axis=0)] return X class PaperListenerNetwork_direct(BaseListenerNetwork): def __init__(self, modelname, config_dict): assert False #TOMODIFY super(PaperListenerNetwork_direct, self).__init__(modelname, config_dict) self.batch_speaker_message = [] self.batch_action = [] self.batch_candidates = [] self.batch_reward = [] def initialize_model(self): """ Batch input and output. """ if not os.path.exists(self.modelname): ## Define model ## Speakers Message t_input = Input(shape=(self.config['max_message_length'],)) #shape(bs, max_message_length) t_trans = Dense(self.config['speaker_input_dim'], #kernel_initializer=keras.initializers.Identity(gain=1.0), #bias_initializer='zeros', activation='sigmoid')(t_input) #shape(bs, speaker_input_dim) inputs = [t_input] ts = [] for _ in range(self.config['n_classes']): c_input = Input(shape=(self.config['speaker_input_dim'],)) #shape(bs, speaker_input_dim) t = Lambda(lambda x: K.expand_dims(K.sum(-K.square(x),axis=1)))(add([t_trans, Lambda(lambda x: -x)(c_input)])) #shape(bs, 1) inputs.append(c_input) ts.append(t) U = concatenate(ts) #shape(bs, n_classes) listener_probs = U #listener_probs = Lambda(lambda x: K.softmax(x))(U) #shape(bs, n_classes) listener_infer_action = Lambda(lambda x: K.argmax(x))(U) #shape(bs) target_onehot_placeholder = Input(shape=(self.config['n_classes'],), name="action_onehot") #(bs, n_classes) listener_prob_2 = dot([listener_probs, target_onehot_placeholder], axes=1) listener_prob_2 = Lambda(lambda x:K.squeeze(x, axis=1))(listener_prob_2) self.listener_model = Model(inputs=inputs + [target_onehot_placeholder], outputs=[listener_probs, listener_infer_action, t_trans, listener_prob_2]) else: self.load() #check!!! def build_train_fn(self): """ Batch input and output. """ #direct prob input!!! #reward_placeholder = K.placeholder(shape=(None,), name="reward") #(?) action_prob = self.listener_model.output[3] #loss = K.log(-action_prob)*reward_placeholder #loss = - action_prob * reward_placeholder loss = - action_prob loss = K.mean(loss) self.opt = Adam(lr=self.config['listener_lr']) self.updates = self.opt.get_updates(params=self.listener_model.trainable_weights,loss=loss) #if os.path.exists(self.optfilename): # self.load_opt() self.train_fn = K.function( #inputs = self.listener_model.input + [reward_placeholder], inputs = self.listener_model.input, outputs=[loss, loss], updates=self.updates) def sample_from_listener_policy(self, speaker_message, candidates): """ Input and output are all just one instance. No bs dimensize. """ X = self.reshape_message_candidates(speaker_message, candidates) + [np.zeros([1, self.config['n_classes']])] listener_probs, listener_infer_action, _t_trans, _lp2 = self.listener_model.predict_on_batch(X) listener_probs = np.squeeze(listener_probs) #shape(n_class) #listener_probs = scipy.special.softmax(listener_probs) listener_probs = softmax(listener_probs) #pdb.set_trace() #???norm??? listener_action = np.random.choice(np.arange(self.config['n_classes']), p=listener_probs) #int return listener_action, listener_probs def infer_from_listener_policy(self, speaker_message, candidates): """ Input and output are all just one instance. No bs dimensize. """ X = self.reshape_message_candidates(speaker_message, candidates) + [np.zeros([1, self.config['n_classes']])] listener_probs, listener_infer_action, _t_trans, _lp2 = self.listener_model.predict_on_batch(X) listener_probs = np.squeeze(listener_probs) #shape(n_class) listener_probs = softmax(listener_probs) listener_action = np.squeeze(listener_infer_action).tolist() #int return listener_action, listener_probs def train_listener_policy_on_batch(self): """ Train as a batch. Loss is an float for a batch """ self.batch_candidates = np.array(self.batch_candidates).transpose([1, 0, 2]).tolist() #shape(num_classes, bs, speaker_input_dim #_loss, _entropy = self.train_fn([self.batch_speaker_message] + self.batch_candidates + [self.batch_action, self.batch_reward] ) _loss, _entropy = self.train_fn([self.batch_speaker_message] + self.batch_candidates + [self.batch_action] ) #print("Listener loss: ", _loss) self.batch_speaker_message = [] #shape(bs, max_message_length) self.batch_action = [] #shape(bs, n_classes) self.batch_candidates = [] #shape(bs, n_classes, speaker_input_dim) self.batch_reward = [] #shape(bs) def remember_listener_training_details(self, speaker_message, action, action_probs, target, candidates, reward): """ Inputs are just one instance. No bs dimensize. """ #action_onehot = np.zeros(self.config['n_classes']) #action_onehot[action] = 1 action_onehot = np.ones(self.config['n_classes']) * np.all(target==candidates, axis=1) self.batch_action.append(action_onehot) self.batch_speaker_message.append(speaker_message) self.batch_candidates.append(candidates) self.batch_reward.append(reward) '''

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5b480e609340e7c3163c99f85166ef4016ae608a

48

py

Python

src/apps/trainings/services/__init__.py

sanderland/katago-server

6414fab080d007c05068a06ff4f25907b92848bd

[ "MIT" ]

27

2020-05-03T11:01:27.000Z

2022-03-17T05:33:10.000Z

src/apps/trainings/services/__init__.py

sanderland/katago-server

6414fab080d007c05068a06ff4f25907b92848bd

[ "MIT" ]

54

2020-05-09T01:18:41.000Z

2022-01-22T10:31:15.000Z

src/apps/trainings/services/__init__.py

sanderland/katago-server

6414fab080d007c05068a06ff4f25907b92848bd

[ "MIT" ]

9

2020-09-29T11:31:32.000Z

2022-03-09T01:37:50.000Z

from .bayesian_elo import BayesianRatingService

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5b8b6d1f4ab0f3039cf2da903751e51e15cb144e

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py

Python

Variado_GeekUniversity/guppe/args.py

PauloFTeixeira/curso_python

9040c7dcc5262620f6330bb9637710bb8899bc6b

[ "MIT" ]

null

Variado_GeekUniversity/guppe/args.py

PauloFTeixeira/curso_python

9040c7dcc5262620f6330bb9637710bb8899bc6b

[ "MIT" ]

null

Variado_GeekUniversity/guppe/args.py

PauloFTeixeira/curso_python

9040c7dcc5262620f6330bb9637710bb8899bc6b

[ "MIT" ]

null

""" Entendendo o *args - O *args é um parâmetro, como outro qualquer. Isso significa que você poderá charmar de qualquer coisa, desde que começe com asterisco. Exemplo: *xis Mas por convenção, utilizamos *args para definí-lo Mas o que é o *args? O parâmetro *args utilizado em uma função, coloca os valores extras informados como entrada em uma tupla. Então desde já lembre-se que tuplas são imutáveis. # Exemplos def soma_todos_numeros(num1=1, num2=2, num3=3, num4=4): return num1 + num2 + num3 + num4 print(soma_todos_numeros(4, 6, 9)) print(soma_todos_numeros(4, 6)) print(soma_todos_numeros(4, 6, 9, 5)) # Entendendo o args def soma_todos_numeros(nome, email, *args): return sum(args) print(soma_todos_numeros('Angelina', 'Jolie')) print(soma_todos_numeros('Angelina', 'Jolie', 1)) print(soma_todos_numeros('Angelina', 'Jolie', 2, 3)) print(soma_todos_numeros('Angelina', 'Jolie', 2, 3, 4)) print(soma_todos_numeros('Angelina', 'Jolie', 3, 4, 5, 6)) print(soma_todos_numeros('Angelina', 'Jolie', 23.4, 12.5)) # Outro exemplo de utilização do *args def verifica_info(*args): if 'Geek' in args and 'University' in args: return 'Bem-vindo Geek!' return 'Eu não tenho certeza quem você é ...' print(verifica_info()) print(verifica_info(1, True, 'University', 'Geek')) print(verifica_info(1, 'University', 3.145)) """ def soma_todos_numeros(*args): return sum(args) # print(soma_todos_numeros()) # print(soma_todos_numeros(3, 4, 5, 6)) numeros = [1, 2, 3, 4, 5, 6, 7] # Desempacotador print(soma_todos_numeros(*numeros)) # OBS: O asterisco serve para que informemos ao Python que estamos #passando como argumento uma coleção de dados. Desta forma, ele saberá # que precisará antes desempacotar estes dados.

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5bebb317f5eba89ee7abe9c379e69ee3e8996039

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py

Python

octicons16px/typography.py

andrewp-as-is/octicons16px.py

1272dc9f290619d83bd881e87dbd723b0c48844c

[ "Unlicense" ]

1

2021-01-28T06:47:39.000Z

octicons16px/typography.py

andrewp-as-is/octicons16px.py

1272dc9f290619d83bd881e87dbd723b0c48844c

[ "Unlicense" ]

null

octicons16px/typography.py

andrewp-as-is/octicons16px.py

1272dc9f290619d83bd881e87dbd723b0c48844c

[ "Unlicense" ]

null

OCTICON_TYPOGRAPHY = """ <svg class="octicon octicon-typography" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" width="16" height="16"><path fill-rule="evenodd" d="M6.21 8.5L4.574 3.594 2.857 8.5H6.21zm.5 1.5l.829 2.487a.75.75 0 001.423-.474L5.735 2.332a1.216 1.216 0 00-2.302-.018l-3.39 9.688a.75.75 0 001.415.496L2.332 10H6.71zm3.13-4.358C10.53 4.374 11.87 4 13 4c1.5 0 3 .939 3 2.601v5.649a.75.75 0 01-1.448.275C13.995 12.82 13.3 13 12.5 13c-.77 0-1.514-.231-2.078-.709-.577-.488-.922-1.199-.922-2.041 0-.694.265-1.411.887-1.944C11 7.78 11.88 7.5 13 7.5h1.5v-.899c0-.54-.5-1.101-1.5-1.101-.869 0-1.528.282-1.84.858a.75.75 0 11-1.32-.716zM14.5 9H13c-.881 0-1.375.22-1.637.444-.253.217-.363.5-.363.806 0 .408.155.697.39.896.249.21.63.354 1.11.354.732 0 1.26-.209 1.588-.449.35-.257.412-.495.412-.551V9z"></path></svg> """

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py

Python

nesmdb/__init__.py

duhaime/nesmdb

d56b176cebbcf91b0069fc529f0884768acf42e8

[ "MIT" ]

408

2018-06-07T22:53:16.000Z

2022-03-23T09:48:57.000Z

nesmdb/__init__.py

duhaime/nesmdb

d56b176cebbcf91b0069fc529f0884768acf42e8

[ "MIT" ]

7

2018-07-05T23:51:40.000Z

2022-03-04T07:54:04.000Z

nesmdb/__init__.py

duhaime/nesmdb

d56b176cebbcf91b0069fc529f0884768acf42e8

[ "MIT" ]

36

2018-06-07T22:59:16.000Z

2022-03-01T01:37:05.000Z

import apu import convert import cycle

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f33ba4af0bdaf50c9e8fc29b830b7c17188cc394

99

py

Python

TSSR/__init__.py

cestcedric/TSSR-GAN

d6e1b50409e0f0591660552993e6d5b70d41e766

[ "BSD-2-Clause", "MIT" ]

null

TSSR/__init__.py

cestcedric/TSSR-GAN

d6e1b50409e0f0591660552993e6d5b70d41e766

[ "BSD-2-Clause", "MIT" ]

null

TSSR/__init__.py

cestcedric/TSSR-GAN

d6e1b50409e0f0591660552993e6d5b70d41e766

[ "BSD-2-Clause", "MIT" ]

null

from .Blocks import * from .Discriminator import * from .Generator import * from .Upscaler import *

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1

0

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f36756ca953d66dd6052a2a0fef734ba6b8d7e9c

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py

Python

zeus/vcs/__init__.py

conrad-kronos/zeus

ddb6bc313e51fb22222b30822b82d76f37dbbd35

[ "Apache-2.0" ]

221

2017-07-03T17:29:21.000Z

2021-12-07T19:56:59.000Z

zeus/vcs/__init__.py

conrad-kronos/zeus

ddb6bc313e51fb22222b30822b82d76f37dbbd35

[ "Apache-2.0" ]

298

2017-07-04T18:08:14.000Z

2022-03-03T22:24:51.000Z

zeus/vcs/__init__.py

conrad-kronos/zeus

ddb6bc313e51fb22222b30822b82d76f37dbbd35

[ "Apache-2.0" ]

24

2017-07-15T13:46:45.000Z

2020-08-16T16:14:45.000Z

from .client import vcs_client # NOQA

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py

Python

sbober_fractals/__init__.py

BoberSA/skb_package_tutorial

3b7671b981b7f9b39abe7a07335d2351d8749d76

[ "MIT" ]

null

sbober_fractals/__init__.py

BoberSA/skb_package_tutorial

3b7671b981b7f9b39abe7a07335d2351d8749d76

[ "MIT" ]

null

sbober_fractals/__init__.py

BoberSA/skb_package_tutorial

3b7671b981b7f9b39abe7a07335d2351d8749d76

[ "MIT" ]

null

from .fractals import Mandelbrot

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6

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py

Python

monitoring-center-backend/tests/unit/test_model_probe.py

Heimdall-monitoring/monitoring-center

acf56a796c25fb6804fd16b1ff8c93645bc77ff3

[ "MIT" ]

null

monitoring-center-backend/tests/unit/test_model_probe.py

Heimdall-monitoring/monitoring-center

acf56a796c25fb6804fd16b1ff8c93645bc77ff3

[ "MIT" ]

10

2020-09-09T14:37:05.000Z

2020-11-26T13:14:09.000Z

monitoring-center-backend/tests/unit/test_model_probe.py

Heimdall-monitoring/monitoring-center

acf56a796c25fb6804fd16b1ff8c93645bc77ff3

[ "MIT" ]

null

""" Test the probe model """ from monitoring_center import Probe def test_equality_1(): assert Probe('1234', 'name1') == Probe('1234', 'name1') assert Probe('1234', 'name2', 'description') == Probe('1234', 'name2', 'description') def test_equality_2(): assert Probe('1234', 'name2') != Probe('1234', 'name3') assert Probe('1234', 'name2') != Probe('12344', 'name2') assert Probe('1234', 'name2', 'description') != Probe('1234', 'name2', 'description2') assert Probe('1234', 'name2', 'description') != Probe('1234', 'name2') def test_equality_3(): assert Probe('1234', 'name') != {'uuid': '1234', 'name': 'name'}

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f3b76d7efea9b5c07ddb9d24c98da602483cbfb2

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py

Python

scribdl/__init__.py

vaibhavkaushal11/scribd-downloader

008e536f53df3478ae0ad48f4a0cba8ea6fff147

[ "MIT" ]

6

2019-05-23T08:50:26.000Z

2021-04-04T03:54:31.000Z

scribdl/__init__.py

vaibhavkaushal11/scribd-downloader

008e536f53df3478ae0ad48f4a0cba8ea6fff147

[ "MIT" ]

null

scribdl/__init__.py

vaibhavkaushal11/scribd-downloader

008e536f53df3478ae0ad48f4a0cba8ea6fff147

[ "MIT" ]

3

2019-06-13T05:50:34.000Z

2019-08-16T16:58:23.000Z

from .version import __version__ from .downloader import Downloader from .document import ScribdTextualDocument from .document import ScribdImageDocument from .book import ScribdBook from .pdf_converter import ConvertToPDF

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6

45fffccf3dc264d9c9690c6abab9fa0e6d68859f

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py

Python

src/interpreter/functions/slice.py

incrementals/b-star

325bb51eafd5c5173582bf065b82d10ef9669275

[ "MIT" ]

2

2021-11-02T04:28:32.000Z

2021-11-05T14:27:08.000Z

src/interpreter/functions/slice.py

incrementals/b-star

325bb51eafd5c5173582bf065b82d10ef9669275

[ "MIT" ]

6

2022-01-07T22:49:19.000Z

2022-03-11T05:39:04.000Z

src/interpreter/functions/slice.py

incrementals/b-star

325bb51eafd5c5173582bf065b82d10ef9669275

[ "MIT" ]

4

2021-11-26T01:38:32.000Z

2022-02-27T20:54:08.000Z

def slice_func(array, index_start, index_end): return array[int(index_start):int(index_end)]

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py

Python

OOP/Exercises/Inheritance_Lab/4_multilevel_inheritance/project/vehicle.py

tankishev/Python

60e511fc901f136b88c681f77f209fe2f8c46447

[ "MIT" ]

2

2022-03-04T11:39:03.000Z

2022-03-13T07:13:23.000Z

OOP/Exercises/Inheritance_Lab/4_multilevel_inheritance/project/vehicle.py

tankishev/Python

60e511fc901f136b88c681f77f209fe2f8c46447

[ "MIT" ]

null

OOP/Exercises/Inheritance_Lab/4_multilevel_inheritance/project/vehicle.py

tankishev/Python

60e511fc901f136b88c681f77f209fe2f8c46447

[ "MIT" ]

null

class Vehicle: def __init__(self) -> None: pass def move(self) -> str: return 'moving...'

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6

343d79a78200c12521be7538385d0595fd8f5ad0

235

py

Python

tonks/__init__.py

vanderveld/tonks

e87afbd9614b276b443b4a7527fd1fda01a8be4c

[ "BSD-3-Clause" ]

null

tonks/__init__.py

vanderveld/tonks

e87afbd9614b276b443b4a7527fd1fda01a8be4c

[ "BSD-3-Clause" ]

null

tonks/__init__.py

vanderveld/tonks

e87afbd9614b276b443b4a7527fd1fda01a8be4c

[ "BSD-3-Clause" ]

null

from ._version import __version__ from tonks.dataloader import MultiDatasetLoader from tonks.ensemble import * from tonks.learner import MultiTaskLearner, MultiInputMultiTaskLearner from tonks.text import * from tonks.vision import *

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6

3470c0e867b8fc3e58dfbe731c9e2f89beaae877

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py

Python

vae_lm/scripts/__init__.py

Nemexur/nonauto-lm

6f237e4fc2b3b679cd92126ea5facd58d3cf6e75

[ "Apache-2.0" ]

3

2021-05-04T09:41:20.000Z

2021-12-14T07:41:40.000Z

vae_lm/scripts/__init__.py

Nemexur/nonauto-lm

6f237e4fc2b3b679cd92126ea5facd58d3cf6e75

[ "Apache-2.0" ]

null

vae_lm/scripts/__init__.py

Nemexur/nonauto-lm

6f237e4fc2b3b679cd92126ea5facd58d3cf6e75

[ "Apache-2.0" ]

null

from .train_worker import train_worker

19.5

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null

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6

caa036a17f79f370dbdf5e6398073c70793161ad

238

py

Python

books_management/publisher/resource.py

blackriddle/books-management

ba485a362a8bc50052dd6f4fc3884e639ca762b0

[ "MIT" ]

null

books_management/publisher/resource.py

blackriddle/books-management

ba485a362a8bc50052dd6f4fc3884e639ca762b0

[ "MIT" ]

null

books_management/publisher/resource.py

blackriddle/books-management

ba485a362a8bc50052dd6f4fc3884e639ca762b0

[ "MIT" ]

null

from flask_restful import Resource from model import Publisher class PublisherResource(Resource): def get(self): pass def post(self): pass def patch(self): pass def delete(self): pass

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6

cabd0ae8af406e13aef94ab7ff8b51129c59efff

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py

Python

test/cut/test_cut_ops_preserve_id.py

stachu86/lhotse

d5e78154db2d4d52f15aaadc8882f76eb5b77640

[ "Apache-2.0" ]

353

2020-10-31T10:38:51.000Z

2022-03-30T05:22:52.000Z

test/cut/test_cut_ops_preserve_id.py

stachu86/lhotse

d5e78154db2d4d52f15aaadc8882f76eb5b77640

[ "Apache-2.0" ]

353

2020-10-27T23:25:12.000Z

2022-03-31T22:16:05.000Z

test/cut/test_cut_ops_preserve_id.py

stachu86/lhotse

d5e78154db2d4d52f15aaadc8882f76eb5b77640

[ "Apache-2.0" ]

66

2020-11-01T06:08:08.000Z

2022-03-29T02:03:07.000Z

import pytest # Note: # Definitions for `cut1`, `cut2` and `cut_set` parameters are standard Pytest fixtures located in test/cut/conftest.py # ######################################## # ############### PADDING ################ # ######################################## @pytest.mark.parametrize("direction", ["right", "left", "both"]) def test_pad_cut_preserve_id_false(cut1, direction: str): padded = cut1.pad(duration=300, direction=direction) assert padded.id != cut1.id @pytest.mark.parametrize("direction", ["right", "left", "both"]) def test_pad_cut_preserve_id_true(cut1, direction: str): padded = cut1.pad(duration=300, direction=direction, preserve_id=True) assert padded.id == cut1.id @pytest.mark.parametrize("direction", ["right", "left", "both"]) def test_pad_mixed_cut_preserve_id_false(cut1, direction: str): mixed = cut1.append(cut1) padded = mixed.pad(duration=300, direction=direction) assert padded.id != mixed.id @pytest.mark.parametrize("direction", ["right", "left", "both"]) def test_pad_mixed_cut_preserve_id_true(cut1, direction: str): mixed = cut1.append(cut1) padded = mixed.pad(duration=300, direction=direction, preserve_id=True) assert padded.id == mixed.id # ######################################## # ############## APPENDING ############### # ######################################## def test_append_cut_preserve_id_none(cut1, cut2): appended = cut1.append(cut2) assert appended.id != cut1.id assert appended.id != cut2.id def test_append_cut_preserve_id_left(cut1, cut2): appended = cut1.append(cut2, preserve_id="left") assert appended.id == cut1.id assert appended.id != cut2.id def test_append_cut_preserve_id_right(cut1, cut2): appended = cut1.append(cut2, preserve_id="right") assert appended.id != cut1.id assert appended.id == cut2.id def test_append_mixed_cut_preserve_id_none(cut1, cut2): premixed = cut1.append(cut1) appended = premixed.append(cut2) assert appended.id != premixed.id assert appended.id != cut2.id def test_append_mixed_cut_preserve_id_left(cut1, cut2): premixed = cut1.append(cut1) appended = premixed.append(cut2, preserve_id="left") assert appended.id == premixed.id assert appended.id != cut2.id def test_append_mixed_cut_preserve_id_right(cut1, cut2): premixed = cut1.append(cut1) appended = premixed.append(cut2, preserve_id="right") assert appended.id != premixed.id assert appended.id == cut2.id # ######################################## # ############### MIXING ################# # ######################################## def test_mix_cut_preserve_id_none(cut1, cut2): mixed = cut1.mix(cut2) assert mixed.id != cut1.id assert mixed.id != cut2.id def test_mix_cut_preserve_id_left(cut1, cut2): mixed = cut1.mix(cut2, preserve_id="left") assert mixed.id == cut1.id assert mixed.id != cut2.id def test_mix_cut_preserve_id_right(cut1, cut2): mixed = cut1.mix(cut2, preserve_id="right") assert mixed.id != cut1.id assert mixed.id == cut2.id def test_mix_mixed_cut_preserve_id_none(cut1, cut2): premixed = cut1.append(cut1) mixed = premixed.mix(cut2) assert mixed.id != premixed.id assert mixed.id != cut2.id def test_mix_mixed_cut_preserve_id_left(cut1, cut2): premixed = cut1.append(cut1) mixed = premixed.mix(cut2, preserve_id="left") assert mixed.id == premixed.id assert mixed.id != cut2.id def test_mix_mixed_cut_preserve_id_right(cut1, cut2): premixed = cut1.append(cut1) mixed = premixed.mix(cut2, preserve_id="right") assert mixed.id != premixed.id assert mixed.id == cut2.id # ######################################## # ############ PERTURB SPEED ############# # ######################################## def test_cut_perturb_speed_affix_id_true(cut1): cut_sp = cut1.perturb_speed(1.1) assert cut_sp.id != cut1.id def test_cut_perturb_speed_affix_id_false(cut1): cut_sp = cut1.perturb_speed(1.1, affix_id=False) assert cut_sp.id == cut1.id def test_mixed_cut_perturb_speed_affix_id_true(cut1): premixed = cut1.append(cut1) cut_sp = premixed.perturb_speed(1.1) assert cut_sp.id != premixed.id def test_mixed_cut_perturb_speed_affix_id_false(cut1): premixed = cut1.append(cut1) cut_sp = premixed.perturb_speed(1.1, affix_id=False) assert cut_sp.id == premixed.id # ######################################## # ############ PERTURB TEMPO ############# # ######################################## def test_cut_perturb_tempo_affix_id_true(cut1): cut_tp = cut1.perturb_tempo(1.1) assert cut_tp.id != cut1.id def test_cut_perturb_tempo_affix_id_false(cut1): cut_tp = cut1.perturb_tempo(1.1, affix_id=False) assert cut_tp.id == cut1.id def test_mixed_cut_perturb_tempo_affix_id_true(cut1): premixed = cut1.append(cut1) cut_tp = premixed.perturb_tempo(1.1) assert cut_tp.id != premixed.id def test_mixed_cut_perturb_tempo_affix_id_false(cut1): premixed = cut1.append(cut1) cut_tp = premixed.perturb_tempo(1.1, affix_id=False) assert cut_tp.id == premixed.id # ######################################## # ########### PERTURB VOLUME ############# # ######################################## def test_cut_perturb_volume_affix_id_true(cut1): cut_vp = cut1.perturb_volume(1.1) assert cut_vp.id != cut1.id def test_cut_perturb_volume_affix_id_false(cut1): cut_vp = cut1.perturb_volume(1.1, affix_id=False) assert cut_vp.id == cut1.id def test_mixed_cut_perturb_volume_affix_id_true(cut1): premixed = cut1.append(cut1) cut_vp = premixed.perturb_volume(1.1) assert cut_vp.id != premixed.id def test_mixed_cut_perturb_volume_affix_id_false(cut1): premixed = cut1.append(cut1) cut_vp = premixed.perturb_volume(1.1, affix_id=False) assert cut_vp.id == premixed.id # ######################################## # ############## RESAMPLE ################ # ######################################## def test_cut_resample_affix_id_true(cut1): cut_rs = cut1.resample(44100, affix_id=True) assert cut_rs.id != cut1.id def test_cut_resample_affix_id_false(cut1): cut_rs = cut1.resample(44100) assert cut_rs.id == cut1.id def test_mixed_cut_resample_affix_id_true(cut1): premixed = cut1.append(cut1) cut_rs = premixed.resample(44100, affix_id=True) assert cut_rs.id != premixed.id def test_mixed_cut_resample_affix_id_false(cut1): premixed = cut1.append(cut1) cut_rs = premixed.resample(44100) assert cut_rs.id == premixed.id

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cad1c4d020698b01d568f21867033469eb800799

5,278

py

Python

rules.py

Wichy76/wichess

d8f4112fee01416565b7d8828c8e79eeb8cd3947

[ "MIT" ]

null

rules.py

Wichy76/wichess

d8f4112fee01416565b7d8828c8e79eeb8cd3947

[ "MIT" ]

null

rules.py

Wichy76/wichess

d8f4112fee01416565b7d8828c8e79eeb8cd3947

[ "MIT" ]

null

import pieces import itertools def valid_pawn_movement(selected_piece, new_pos, current_turn): piece, old_x, old_y = selected_piece new_x, new_y = new_pos if piece != (current_turn, pieces.PAWN): return False else: if current_turn == pieces.WHITE: if old_x // 100 == new_x // 100 and old_y // 100 == (new_y // 100) + 1: return True elif old_x // 100 == new_x // 100 and old_y // 100 == 6 and (new_y // 100) == 4: return True if current_turn == pieces.BLACK: if old_x // 100 == new_x // 100 and old_y // 100 == (new_y // 100) - 1: return True elif old_x // 100 == new_x // 100 and old_y // 100 == 1 and (new_y // 100) == 3: return True return False def valid_knight_movement(selected_piece, new_pos, current_turn): possibles = [(-1, -2), (-1, 2), (1, -2), (1, 2), (-2, -1), (-2, 1), (2, -1), (2, 1)] piece, old_x, old_y = selected_piece new_x, new_y = new_pos if piece != (current_turn, pieces.KNIGHT): return False else: for posi in possibles: if old_x // 100 == (new_x // 100) + int(posi[0]) and old_y // 100 == (new_y // 100) + int(posi[1]): return True return False def valid_king_movement(selected_piece, new_pos, current_turn): possibles = list(itertools.product([-1, 0, 1], [-1, 0, 1])) piece, old_x, old_y = selected_piece new_x, new_y = new_pos if piece != (current_turn, pieces.KING): return False else: for posi in possibles: if old_x // 100 == (new_x // 100) + int(posi[0]) and old_y // 100 == (new_y // 100) + int(posi[1]): return True return False def is_horizontal_or_vertical_move(new_x, new_y, old_x, old_y): if old_x // 100 == (new_x // 100) and old_y // 100 != (new_y // 100) or old_x // 100 != ( new_x // 100) and old_y // 100 == (new_y // 100): return True def valid_rook_movement(selected_piece, new_pos, current_turn, board): piece, old_x, old_y = selected_piece new_x, new_y = new_pos if piece != (current_turn, pieces.ROOK): return False else: if is_horizontal_or_vertical_move(new_x, new_y, old_x, old_y): if have_between_own_pieces_horizontal(new_pos, board, selected_piece) or have_between_own_pieces_vertical( new_pos, board, selected_piece): return False return True return False def is_diagonal_move(new_x, new_y, old_x, old_y): if old_x // 100 - (old_y // 100) == new_x // 100 - (new_y // 100) or old_x // 100 + ( old_y // 100) == new_x // 100 + (new_y // 100): return True def valid_bishop_movement(selected_piece, new_pos, current_turn, board): piece, old_x, old_y = selected_piece new_x, new_y = new_pos if piece != (current_turn, pieces.BISHOP): return False else: if is_diagonal_move(new_x, new_y, old_x, old_y): if have_between_own_pieces_diagonal(new_pos, board, selected_piece) : return False return True return False def valid_queen_movement(selected_piece, new_pos, current_turn, board): piece, old_x, old_y = selected_piece new_x, new_y = new_pos if piece != (current_turn, pieces.QUEEN): return False else: if is_diagonal_move(new_x, new_y, old_x, old_y): if have_between_own_pieces_diagonal(new_pos, board, selected_piece) : return False return True if is_horizontal_or_vertical_move(new_x, new_y, old_x, old_y): if have_between_own_pieces_horizontal(new_pos, board, selected_piece) or have_between_own_pieces_vertical( new_pos, board, selected_piece): return False return True return False def have_between_own_pieces_vertical(new_pos, board, selected_piece): piece, old_x, old_y = selected_piece new_x, new_y = new_pos min_y = min(new_y // 100, old_y // 100) + 1 max_y = max(new_y // 100, old_y // 100) for y in range(min_y, max_y): if board[old_x // 100][y][0] == piece[0]: return True return False def have_between_own_pieces_horizontal(new_pos, board, selected_piece): piece, old_x, old_y = selected_piece new_x, new_y = new_pos min_x = min(new_x // 100, old_x // 100) + 1 max_x = max(new_x // 100, old_x // 100) for x in range(min_x, max_x): if board[x][old_y // 100][0] == piece[0]: return True return False def have_between_own_pieces_diagonal(new_pos, board, selected_piece): piece, old_x, old_y = selected_piece new_x, new_y = new_pos min_x = min(new_x // 100, old_x // 100) + 1 max_x = max(new_x // 100, old_x // 100) if new_y // 100 + new_x // 100 == old_y // 100 + old_x // 100: for x in range(min_x, max_x): y = (old_y // 100 + old_x // 100) - x if board[x][y][0] == piece[0]: return True else: for x in range(min_x, max_x): y = (old_y // 100 - old_x // 100) + x if board[x][y][0] == piece[0]: return True return False

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