xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

e0ae7c18938f65d603fdc5ccf0fe562cc30757c2

40

py

Python

tests/__init__.py

fabianSorn/semantic_text_similarity

0caba4797b81bc3b7b5647ac128cf31a263f2aaf

[ "MIT" ]

null

tests/__init__.py

fabianSorn/semantic_text_similarity

0caba4797b81bc3b7b5647ac128cf31a263f2aaf

[ "MIT" ]

null

tests/__init__.py

fabianSorn/semantic_text_similarity

0caba4797b81bc3b7b5647ac128cf31a263f2aaf

[ "MIT" ]

null

"""Unit test package for semtextsim."""

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e0b466cb2eba7f7b4fe51e2e9ab96616ac3425d5

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py

Python

scintillant/controllers/__init__.py

PaperDevil/scintillant

369eb4e9613e21d436af8d5cdbd07d91632766a7

[ "Apache-2.0" ]

null

scintillant/controllers/__init__.py

PaperDevil/scintillant

369eb4e9613e21d436af8d5cdbd07d91632766a7

[ "Apache-2.0" ]

null

scintillant/controllers/__init__.py

PaperDevil/scintillant

369eb4e9613e21d436af8d5cdbd07d91632766a7

[ "Apache-2.0" ]

null

from scintillant.controllers.context_controller import ContextUpdater

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5

e0b92158609dc05e7f0caf8674364b3b2477ec93

916

py

Python

ENIAC/api/__init__.py

Ahrli/fast_tools

144d764e4f169d3ab3753dcc6a79db9f9449de59

[ "Apache-2.0" ]

1

2021-12-11T16:33:47.000Z

ENIAC/api/__init__.py

webclinic017/fast_tools

144d764e4f169d3ab3753dcc6a79db9f9449de59

[ "Apache-2.0" ]

null

ENIAC/api/__init__.py

webclinic017/fast_tools

144d764e4f169d3ab3753dcc6a79db9f9449de59

[ "Apache-2.0" ]

3

2021-11-22T09:46:43.000Z

2022-01-28T22:33:07.000Z

# api/__init__.py from sanic import Blueprint # 蓝图 # from .eniac_bps.factors import factor # from .eniac_bps.loopback import loop # from .eniac_bps.backtrader import backtrader # from .eniac_bps.btresultApi import api # from .eniac_bps.piplineStatus import pipline # from .eniac_bps.trading import trading # from .eniac_bps.ai import ai # from .eniac_bps.validation import validation # from .eniac_bps.loop_coin import loopcoin # from .eniac_bps.financial import financial # # from sanic_openapi import swagger_blueprint, openapi_blueprint # # from .loop_statistics import loop_indicators # from .loop_stack import loop_indicators # iquant_eniac = Blueprint.group(factor, loop, backtrader, api, pipline, trading,ai,validation, loopcoin,financial) # eniac = Blueprint.group(factor, loop, swagger_blueprint, openapi_blueprint, url_prefix='/') from .eniac_bps.car_info import car iquant_eniac = Blueprint.group(car)

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py

Python

bob/pipelines/config/distributed/local_parallel.py

bioidiap/bob.pipelines

cbefdaf3b384ee11cb26a279281f007adc2d8f19

[ "BSD-3-Clause" ]

1

2020-10-13T19:58:44.000Z

bob/pipelines/config/distributed/local_parallel.py

bioidiap/bob.pipelines

cbefdaf3b384ee11cb26a279281f007adc2d8f19

[ "BSD-3-Clause" ]

null

bob/pipelines/config/distributed/local_parallel.py

bioidiap/bob.pipelines

cbefdaf3b384ee11cb26a279281f007adc2d8f19

[ "BSD-3-Clause" ]

null

from bob.pipelines.distributed import get_local_parallel_client dask_client = get_local_parallel_client()

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py

Python

reamber/dummy/__init__.py

Bestfast/reamberPy

91b76ca6adf11fbe8b7cee7c186481776a4d7aaa

[ "MIT" ]

null

reamber/dummy/__init__.py

Bestfast/reamberPy

91b76ca6adf11fbe8b7cee7c186481776a4d7aaa

[ "MIT" ]

null

reamber/dummy/__init__.py

Bestfast/reamberPy

91b76ca6adf11fbe8b7cee7c186481776a4d7aaa

[ "MIT" ]

null

from reamber.dummy.DmBpm import DmBpm from reamber.dummy.DmHit import DmHit from reamber.dummy.DmHold import DmHold from reamber.dummy.DmMap import DmMap from reamber.dummy.DmMapMeta import DmMapMeta from reamber.dummy.DmSv import DmSv __all__ = ['DmBpm', 'DmHit', 'DmHold', 'DmMap', 'DmMapMeta', 'DmSv']

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1cb66cf33c42d1635a1a15ff6b8f76d546c04d2d

32

py

Python

test/run/t60.py

timmartin/skulpt

2e3a3fbbaccc12baa29094a717ceec491a8a6750

[ "MIT" ]

2,671

2015-01-03T08:23:25.000Z

2022-03-31T06:15:48.000Z

test/run/t60.py

csev/skulpt

9aa25b7dbf29f23ee8d3140d01a6f4353d12e66f

[ "MIT" ]

972

2015-01-05T08:11:00.000Z

2022-03-29T13:47:15.000Z

test/run/t60.py

csev/skulpt

9aa25b7dbf29f23ee8d3140d01a6f4353d12e66f

[ "MIT" ]

845

2015-01-03T19:53:36.000Z

2022-03-29T18:34:22.000Z

if not "?" in "xyz": print "OK"

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5

1cfe75cf3778a5714bb9a45a95de3d68688708f8

201

py

Python

dddm/samplers/__init__.py

JoranAngevaare/dddm

3461e37984bac4d850beafecc9d1881b84fb226c

[ "MIT" ]

null

dddm/samplers/__init__.py

JoranAngevaare/dddm

3461e37984bac4d850beafecc9d1881b84fb226c

[ "MIT" ]

85

2021-09-20T12:08:53.000Z

2022-03-30T12:48:06.000Z

dddm/samplers/__init__.py

JoranAngevaare/dddm

3461e37984bac4d850beafecc9d1881b84fb226c

[ "MIT" ]

null

from . import emcee from .emcee import * from . import nestle from .nestle import * from . import pymultinest from .pymultinest import * from .multi_detectors import * from . import multi_detectors

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5

e80ae07d8d706641a0024783b60fe1d4244fde50

66

py

Python

apollo_ad/__init__.py

connorcapitolo/apollo_ad

6a56845ae299789b84fe3235da847ab31180855e

[ "MIT" ]

1

2021-01-29T20:47:35.000Z

apollo_ad/__init__.py

connorcapitolo/apollo_ad

6a56845ae299789b84fe3235da847ab31180855e

[ "MIT" ]

null

apollo_ad/__init__.py

connorcapitolo/apollo_ad

6a56845ae299789b84fe3235da847ab31180855e

[ "MIT" ]

2

2021-01-29T20:47:45.000Z

2021-10-03T13:06:58.000Z

from .apollo_ad import * from .UI import UI from .demo import demo

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5

e81fbbd2b23821fc0c078a6c0ab96898d6e6529d

4,316

py

Python

lemur/tests/test_users.py

caiges/lemur

376b2b80517fb7f24fa505461d11bffeafefc713

[ "Apache-2.0" ]

null

lemur/tests/test_users.py

caiges/lemur

376b2b80517fb7f24fa505461d11bffeafefc713

[ "Apache-2.0" ]

1

2022-03-29T22:05:53.000Z

lemur/tests/test_users.py

TinLe/lemur

dfb9e3a0c8f8f1f1bd908b1fcb8596af7c65f739

[ "Apache-2.0" ]

null

import json import pytest from lemur.tests.factories import UserFactory, RoleFactory from lemur.users.views import * # noqa from .vectors import VALID_ADMIN_HEADER_TOKEN, VALID_USER_HEADER_TOKEN def test_user_input_schema(client): from lemur.users.schemas import UserInputSchema input_data = { 'username': 'example', 'password': '1233432', 'email': 'example@example.com' } data, errors = UserInputSchema().load(input_data) assert not errors @pytest.mark.parametrize("token,status", [ (VALID_USER_HEADER_TOKEN, 200), (VALID_ADMIN_HEADER_TOKEN, 200), ('', 401) ]) def test_user_get(client, token, status): assert client.get(api.url_for(Users, user_id=1), headers=token).status_code == status @pytest.mark.parametrize("token,status", [ (VALID_USER_HEADER_TOKEN, 405), (VALID_ADMIN_HEADER_TOKEN, 405), ('', 405) ]) def test_user_post_(client, token, status): assert client.post(api.url_for(Users, user_id=1), data={}, headers=token).status_code == status @pytest.mark.parametrize("token,status", [ (VALID_USER_HEADER_TOKEN, 403), (VALID_ADMIN_HEADER_TOKEN, 400), ('', 401) ]) def test_user_put(client, token, status): assert client.put(api.url_for(Users, user_id=1), data={}, headers=token).status_code == status @pytest.mark.parametrize("token,status", [ (VALID_USER_HEADER_TOKEN, 405), (VALID_ADMIN_HEADER_TOKEN, 405), ('', 405) ]) def test_user_delete(client, token, status): assert client.delete(api.url_for(Users, user_id=1), headers=token).status_code == status @pytest.mark.parametrize("token,status", [ (VALID_USER_HEADER_TOKEN, 405), (VALID_ADMIN_HEADER_TOKEN, 405), ('', 405) ]) def test_user_patch(client, token, status): assert client.patch(api.url_for(Users, user_id=1), data={}, headers=token).status_code == status @pytest.mark.parametrize("token,status", [ (VALID_USER_HEADER_TOKEN, 403), (VALID_ADMIN_HEADER_TOKEN, 400), ('', 401) ]) def test_user_list_post_(client, token, status): assert client.post(api.url_for(UsersList), data={}, headers=token).status_code == status @pytest.mark.parametrize("token,status", [ (VALID_USER_HEADER_TOKEN, 200), (VALID_ADMIN_HEADER_TOKEN, 200), ('', 401) ]) def test_user_list_get(client, token, status): assert client.get(api.url_for(UsersList), headers=token).status_code == status @pytest.mark.parametrize("token,status", [ (VALID_USER_HEADER_TOKEN, 405), (VALID_ADMIN_HEADER_TOKEN, 405), ('', 405) ]) def test_user_list_delete(client, token, status): assert client.delete(api.url_for(UsersList), headers=token).status_code == status @pytest.mark.parametrize("token,status", [ (VALID_USER_HEADER_TOKEN, 405), (VALID_ADMIN_HEADER_TOKEN, 405), ('', 405) ]) def test_user_list_patch(client, token, status): assert client.patch(api.url_for(UsersList), data={}, headers=token).status_code == status def test_sensitive_filter(client): resp = client.get(api.url_for(UsersList) + '?filter=password;a', headers=VALID_ADMIN_HEADER_TOKEN) assert "'password' is not sortable or filterable" in resp.json['message'] def test_sensitive_sort(client): resp = client.get(api.url_for(UsersList) + '?sortBy=password&sortDir=asc', headers=VALID_ADMIN_HEADER_TOKEN) assert "'password' is not sortable or filterable" in resp.json['message'] def test_user_role_changes(client, session): user = UserFactory() role1 = RoleFactory() role2 = RoleFactory() session.flush() data = { 'active': True, 'id': user.id, 'username': user.username, 'email': user.email, 'roles': [ {'id': role1.id}, {'id': role2.id}, ], } # PUT two roles resp = client.put(api.url_for(Users, user_id=user.id), data=json.dumps(data), headers=VALID_ADMIN_HEADER_TOKEN) assert resp.status_code == 200 assert len(resp.json['roles']) == 2 assert set(user.roles) == {role1, role2} # Remove one role and PUT again del data['roles'][1] resp = client.put(api.url_for(Users, user_id=user.id), data=json.dumps(data), headers=VALID_ADMIN_HEADER_TOKEN) assert resp.status_code == 200 assert len(resp.json['roles']) == 1 assert set(user.roles) == {role1}

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py

Python

src/genie/libs/parser/iosxe/tests/ShowVlanFilter/cli/equal/golden_output_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

204

2018-06-27T00:55:27.000Z

2022-03-06T21:12:18.000Z

src/genie/libs/parser/iosxe/tests/ShowVlanFilter/cli/equal/golden_output_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

468

2018-06-19T00:33:18.000Z

2022-03-31T23:23:35.000Z

src/genie/libs/parser/iosxe/tests/ShowVlanFilter/cli/equal/golden_output_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

309

2019-01-16T20:21:07.000Z

2022-03-30T12:56:41.000Z

expected_output = { "vlan_id": { "100": {"access_map_tag": "karim"}, "3": {"access_map_tag": "mordred"}, "15": {"access_map_tag": "mordred"}, "5": {"access_map_tag": "mordred"}, } }

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1c0a8e9a6d73b236560d63e413673b60a9ca7854

137

py

Python

desafio021.py

WebertiBarbosa/python

640a70c327c262d4e867a4b4620ca50d42398c00

[ "MIT" ]

null

desafio021.py

WebertiBarbosa/python

640a70c327c262d4e867a4b4620ca50d42398c00

[ "MIT" ]

1

2020-06-06T21:34:44.000Z

2020-06-06T21:44:58.000Z

desafio021.py

WebertiBarbosa/python

640a70c327c262d4e867a4b4620ca50d42398c00

[ "MIT" ]

null

import pygame pygame.mixer.init() pygame.mixer.music.load('ex021.mp3') pygame.mixer.music.play() #pygame.event.wait() input('Agora sim')

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1c4adcf7e64b4d92e082b9ba0e6857c359ce8ed3

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py

Python

ex030.py

Roninho514/Treinamento-Python

fc6ad0b64fb3dc3cfa5381f8fc53b5b3243a7ff6

[ "MIT" ]

null

ex030.py

Roninho514/Treinamento-Python

fc6ad0b64fb3dc3cfa5381f8fc53b5b3243a7ff6

[ "MIT" ]

null

ex030.py

Roninho514/Treinamento-Python

fc6ad0b64fb3dc3cfa5381f8fc53b5b3243a7ff6

[ "MIT" ]

null

numero = int(input('Digite um número:')) print('Esse número é par' if numero % 2 == 0 else 'Esse número é impa7r')

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1c7939a542a02d3eb204d675ac62e0ab9ada58f9

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py

Python

example/scan.py

Hong-Xiang/pitem

5ab08a5e085f97cde096b680953fbee4f775ed8c

[ "Apache-2.0" ]

null

example/scan.py

Hong-Xiang/pitem

5ab08a5e085f97cde096b680953fbee4f775ed8c

[ "Apache-2.0" ]

null

example/scan.py

Hong-Xiang/pitem

5ab08a5e085f97cde096b680953fbee4f775ed8c

[ "Apache-2.0" ]

null

# This file is generated via pitem, DO NOT EDIT import attrs @attr.s class ScanItem: id: attrs.ib(type=int) begin_position: attrs.ib(type=float) end_position: attrs.ib(type=float) is_denoise: attrs.ib(type=float, validator=is_in_range(0.000000, 1.000000))

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5

1c7bb9f1675178ac870e3a65a1d2da0a675995b9

43

py

Python

example_data/yes03.py

Cogmob/epr

7217c978afd2af87cce06db0ad1e0ab7e395ee9d

[ "MIT" ]

null

example_data/yes03.py

Cogmob/epr

7217c978afd2af87cce06db0ad1e0ab7e395ee9d

[ "MIT" ]

null

example_data/yes03.py

Cogmob/epr

7217c978afd2af87cce06db0ad1e0ab7e395ee9d

[ "MIT" ]

null

epr( jsd kfjaksjdkfjaksjdkfjaksdjkfjaksjdf

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5

98c82d8ad45244a99725605e54e230077e6e15ca

168

py

Python

street_food_api/trucks/managers.py

ImustAdmit/Street-food-api

7c232304379c558c1250d906536f367b6e890e76

[ "MIT" ]

1

2021-01-26T04:56:05.000Z

street_food_api/trucks/managers.py

ImustAdmit/Street-food-api

7c232304379c558c1250d906536f367b6e890e76

[ "MIT" ]

null

street_food_api/trucks/managers.py

ImustAdmit/Street-food-api

7c232304379c558c1250d906536f367b6e890e76

[ "MIT" ]

null

from django.db import models class ConfirmedTruckManager(models.Manager): def get_queryset(self): return super().get_queryset().filter(is_confirmed=True)

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98d42c4673a4e695362e57430f0ae0b23f0c30e4

151

py

Python

dashboard/overview/views.py

colinspear/music-dashboard

35a7c082a8a6dab4637152adce5e9921a2984a97

[ "FTL" ]

null

dashboard/overview/views.py

colinspear/music-dashboard

35a7c082a8a6dab4637152adce5e9921a2984a97

[ "FTL" ]

5

2020-03-24T17:21:56.000Z

2021-03-17T21:23:28.000Z

dashboard/overview/views.py

colinspear/music-dashboard

35a7c082a8a6dab4637152adce5e9921a2984a97

[ "FTL" ]

null

from django.shortcuts import render from django.http import HttpResponse def i_exist(request): return HttpResponse('Indeed, this view exists')

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0.8

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0

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151

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52

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0

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0

null

0

1

0

1

0

5

98dfafe821513600b628a434f1ae38d505be517f

1,772

py

Python

tests/bash/grep.py

Mamatu/pysh

1bacd6d18a1c40dfcb7ebdcc69711256bf6b9b3a

[ "MIT" ]

null

tests/bash/grep.py

Mamatu/pysh

1bacd6d18a1c40dfcb7ebdcc69711256bf6b9b3a

[ "MIT" ]

null

tests/bash/grep.py

Mamatu/pysh

1bacd6d18a1c40dfcb7ebdcc69711256bf6b9b3a

[ "MIT" ]

null

from unittest import TestCase import pytest from pysh.bash.grep import * from pysh import core, shells from pysh.tests import test class GrepTests(TestCase): def test_notmatch_exit1_1(self): test.inShell(lambda: inText("testa").match("test").endBool("exit 0", "exit 1"), 1) def test_notmatch_exit1_2(self): test.inShell(lambda: inText("textlongechotwo").match("echo").endBool("exit 0", "exit 1"), 1) def test_notmatch_exit1_3(self): test.inShell(lambda: inText("textlongechotwo").match("echo1").endBool("exit 0", "exit 1"), 1) def test_match_exit0_1(self): test.inShell(lambda: inText("test").match("test").endBool("exit 0", "exit 1"), 0) def test_match_exit0_2(self): test.inShell(lambda: inText("echo").match("ech[a-z]").endBool("exit 0", "exit 1"), 0) def test_match_exit0_3(self): test.inShell(lambda: inText("coredump").match("core.*").endBool("exit 0", "exit 1"), 0) def test_notcontain_exit1_1(self): test.inShell(lambda: inText("tesa").contain("test").endBool("exit 0", "exit 1"), 1) def test_notcontain_exit1_2(self): test.inShell(lambda: inText("textlongechtwo").contain("tst").endBool("exit 0", "exit 1"), 1) def test_notcontain_exit1_3(self): test.inShell(lambda: inText("textlongechtwo").contain("echo1").endBool("exit 0", "exit 1"), 1) def test_contain_exit0_1(self): test.inShell(lambda: inText("testa").contain("test").endBool("exit 0", "exit 1"), 0) def test_contain_exit0_2(self): test.inShell(lambda: inText("textlongecho12").contain("ech[a-z]").endBool("exit 0", "exit 1"), 0) def test_contain_exit0_3(self): test.inShell(lambda: inText("coredump loop cat").contain("core").endBool("exit 0", "exit 1"), 0)

53.69697

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1,772

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0

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0.6

0

null

0

1

0

null

0

1

0

5

98f08b2635043ba01adc2ce87b41a555cd8aadd7

199

py

Python

tests/test_dags_script.py

nleguillarme/inteGraph

65faae4b7c16977094c387f6359980a4e99f94cb

[ "Apache-2.0" ]

null

tests/test_dags_script.py

nleguillarme/inteGraph

65faae4b7c16977094c387f6359980a4e99f94cb

[ "Apache-2.0" ]

null

tests/test_dags_script.py

nleguillarme/inteGraph

65faae4b7c16977094c387f6359980a4e99f94cb

[ "Apache-2.0" ]

null

from airflow.models.dagbag import DagBag def test_import_dags(): dags = DagBag() print("DAG import failures. Errors: {}".format(dags.import_errors)) assert len(dags.import_errors) == 0

24.875

71

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199

5.111111

0.592593

0.144928

0.231884

0

0.005988

0.160804

199

7

72

28.428571

0.820359

0

0.155779

0

0.2

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0.2

false

0

0.8

0

1

0.2

1

0

null

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0

1

0

null

0

1

0

1

0

5

c710ff8ddfb3eb4e9d6e8b51ad5c8baae30db38d

158

py

Python

datanator_rest_api/spec/__init__.py

KarrLab/datanator_rest_api

eeadf30703329fbc8feeb9b96db1b78b54a8ccce

[ "MIT" ]

null

datanator_rest_api/spec/__init__.py

KarrLab/datanator_rest_api

eeadf30703329fbc8feeb9b96db1b78b54a8ccce

[ "MIT" ]

130

2019-08-22T22:29:05.000Z

2020-12-02T15:32:23.000Z

datanator_rest_api/spec/__init__.py

KarrLab/datanator_rest_api

eeadf30703329fbc8feeb9b96db1b78b54a8ccce

[ "MIT" ]

null

""" API init :Author: Bilal Shaikh <bilalshaikh42@gmail.com> :Date: 2019-08-16 :Copyright: 2019, Karr Lab :License: MIT """ from .SpecUtils import SpecUtils

17.555556

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0.727848

22

158

5.227273

0.909091

0

0.10219

0.132911

158

8

48

19.75

0.737226

0.734177

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

c729517630f536cdeb70f466c58d5b7694116344

515

py

Python

common/metrics.py

m-bizhani/Digital-rock-image-processing

4d3914dcfa1f814b953e6ce7e97a198f861f8e3a

[ "MIT" ]

null

common/metrics.py

m-bizhani/Digital-rock-image-processing

4d3914dcfa1f814b953e6ce7e97a198f861f8e3a

[ "MIT" ]

null

common/metrics.py

m-bizhani/Digital-rock-image-processing

4d3914dcfa1f814b953e6ce7e97a198f861f8e3a

[ "MIT" ]

null

import tensorflow as tf def PSNR(y_true, y_pred): max_pixel = 1.0 return tf.image.psnr(y_true, y_pred, max_val =max_pixel) def ssim(y_true, y_pred): max_val = 1.0 return tf.image.ssim(y_true, y_pred, max_val = max_val, filter_size=11, filter_sigma=1.5, k1=0.01, k2=0.03) def mssim(y_true, y_pred): max_val = 1.0 return tf.image.ssim_multiscale( y_true, y_pred, max_val = max_val, filter_size=8, filter_sigma=1.5, k1=0.01, k2=0.03)

30.294118

112

0.625243

97

515

3.051546

0.298969

0.141892

0.121622

0.202703

0.807432

0.756757

0.685811

0.608108

0

0.075718

0.256311

515

16

113

32.1875

0.697128

0

0.166667

0

1

0.25

false

0

0.083333

0

0.583333

0

null

0

1

0

1

0

null

0

1

0

5

c729878274666c8a59a63612852502334789acb8

330

py

Python

scattertext/viz/__init__.py

laugustyniak/scattertext

95d865091ccb35d1798d650e737e401707a4b5af

[ "Apache-2.0" ]

null

scattertext/viz/__init__.py

laugustyniak/scattertext

95d865091ccb35d1798d650e737e401707a4b5af

[ "Apache-2.0" ]

null

scattertext/viz/__init__.py

laugustyniak/scattertext

95d865091ccb35d1798d650e737e401707a4b5af

[ "Apache-2.0" ]

null

from .ScatterplotStructure import ScatterplotStructure from .BasicHTMLFromScatterplotStructure import BasicHTMLFromScatterplotStructure from scattertext.viz.PairPlotFromScattertextSctructure import PairPlotFromScatterplotStructure from .VizDataAdapter import VizDataAdapter from .HTMLSemioticSquareViz import HTMLSemioticSquareViz

66

94

0.924242

22

330

13.863636

0.454545

0

0.057576

330

5

95

66

0.980707

0

1

0

true

0

1

0

1

0

1

0

1

null

0

1

0

null

0

1

0

1

0

5

c737ccf9a9465649ccdab76b5acd96d8f58f4328

3,824

gyp

Python

src/third_party/harfbuzz/harfbuzz.gyp

bdon/fontview

6e3d9835dafe69d19b1eb185dc9acb9bd01ce708

[ "Apache-2.0" ]

null

src/third_party/harfbuzz/harfbuzz.gyp

bdon/fontview

6e3d9835dafe69d19b1eb185dc9acb9bd01ce708

[ "Apache-2.0" ]

null

src/third_party/harfbuzz/harfbuzz.gyp

bdon/fontview

6e3d9835dafe69d19b1eb185dc9acb9bd01ce708

[ "Apache-2.0" ]

1

2022-01-14T10:20:29.000Z

{ 'includes': ['../../common.gypi'], 'targets': [ { 'target_name': 'harfbuzz', 'type': 'static_library', 'defines': [ 'HAVE_FREETYPE', 'HAVE_FT_GET_VAR_BLEND_COORDINATES', 'HAVE_INTEL_ATOMIC_PRIMITIVES', 'HAVE_OT', 'HAVE_UCDN', ], 'sources': [ 'harfbuzz/src/hb-blob.cc', 'harfbuzz/src/hb-buffer-serialize.cc', 'harfbuzz/src/hb-buffer.cc', 'harfbuzz/src/hb-common.cc', #'harfbuzz/src/hb-coretext.cc', #'harfbuzz/src/hb-directwrite.cc', 'harfbuzz/src/hb-face.cc', #'harfbuzz/src/hb-fallback-shape.cc', 'harfbuzz/src/hb-font.cc', 'harfbuzz/src/hb-ft.cc', #'harfbuzz/src/hb-glib.cc', #'harfbuzz/src/hb-gobject-structs.cc', #'harfbuzz/src/hb-graphite2.cc', #'harfbuzz/src/hb-icu.cc', 'harfbuzz/src/hb-ot-font.cc', 'harfbuzz/src/hb-ot-layout.cc', 'harfbuzz/src/hb-ot-map.cc', 'harfbuzz/src/hb-ot-var.cc', 'harfbuzz/src/hb-ot-shape-complex-arabic.cc', 'harfbuzz/src/hb-ot-shape-complex-default.cc', 'harfbuzz/src/hb-ot-shape-complex-hangul.cc', 'harfbuzz/src/hb-ot-shape-complex-hebrew.cc', 'harfbuzz/src/hb-ot-shape-complex-indic-table.cc', 'harfbuzz/src/hb-ot-shape-complex-indic.cc', 'harfbuzz/src/hb-ot-shape-complex-khmer.cc', 'harfbuzz/src/hb-ot-shape-complex-myanmar.cc', 'harfbuzz/src/hb-ot-shape-complex-thai.cc', 'harfbuzz/src/hb-ot-shape-complex-tibetan.cc', 'harfbuzz/src/hb-ot-shape-complex-use-table.cc', 'harfbuzz/src/hb-ot-shape-complex-use.cc', 'harfbuzz/src/hb-ot-shape-fallback.cc', 'harfbuzz/src/hb-ot-shape-normalize.cc', 'harfbuzz/src/hb-ot-shape.cc', 'harfbuzz/src/hb-ot-tag.cc', 'harfbuzz/src/hb-set.cc', 'harfbuzz/src/hb-shape-plan.cc', 'harfbuzz/src/hb-shape.cc', 'harfbuzz/src/hb-shaper.cc', 'harfbuzz/src/hb-ucdn.cc', #'harfbuzz/src/hb-ucdn/ucdn.c', 'harfbuzz/src/hb-unicode.cc', #'harfbuzz/src/hb-uniscribe.cc', 'harfbuzz/src/hb-warning.cc', 'harfbuzz/src/hb-buffer-deserialize-json.rl', 'harfbuzz/src/hb-buffer-deserialize-text.rl', 'harfbuzz/src/hb-ot-shape-complex-indic-machine.rl', 'harfbuzz/src/hb-ot-shape-complex-khmer-machine.rl', 'harfbuzz/src/hb-ot-shape-complex-myanmar-machine.rl', 'harfbuzz/src/hb-ot-shape-complex-use-machine.rl', ], 'direct_dependent_settings': { 'include_dirs': [ 'autoconf_generated', 'harfbuzz/src', ], }, 'include_dirs': [ 'autoconf_generated', 'harfbuzz/src', #'harfbuzz/src/hb-ucdn', '<(INTERMEDIATE_DIR)', ], 'rules': [ { 'rule_name': 'ragel', 'extension': 'rl', 'outputs': [ '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).hh' ], 'action': [ '<(PRODUCT_DIR)/ragel', '-e', '-F1', '-o', '<@(_outputs)', '<(RULE_INPUT_PATH)' ], } ], 'dependencies': [ '../freetype/freetype.gyp:freetype', '../ragel/ragel.gyp:ragel', '../ucdn/ucdn.gyp:ucdn', ], }, ] }

38.24

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404

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0.37768

0.298516

0.137438

0

0.000804

0.349634

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0.730599

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0

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0

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0.447608

0

1

0

true

0

null

1

0

1

null

0

1

0

5

c77e06c71c9b8e58f994249c505faf5776f2b966

75

py

Python

batch_face/fast_alignment/__init__.py

mowshon/batch-face

fa5bb5903622dd9142af9b139a72b2b884b65cde

[ "MIT" ]

4

2020-11-16T10:25:32.000Z

2021-11-25T09:41:37.000Z

batch_face/fast_alignment/__init__.py

mowshon/batch-face

fa5bb5903622dd9142af9b139a72b2b884b65cde

[ "MIT" ]

3

2021-04-07T11:29:11.000Z

2022-02-28T11:34:09.000Z

batch_face/fast_alignment/__init__.py

mowshon/batch-face

fa5bb5903622dd9142af9b139a72b2b884b65cde

[ "MIT" ]

5

2020-11-19T05:33:52.000Z

2021-10-15T14:32:30.000Z

from ._version import __version__ from .predictor import LandmarkPredictor

25

40

0.866667

8

75

7.5

0.625

0

0.106667

75

2

41

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true

0

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0

1

0

1

0

1

0

5

c7af572ab82baef1dba629f150b53f37b38c70bc

91

py

Python

pandas_ml/imbaccessors/__init__.py

matsavage/pandas-ml

794cddc8dc5d0a49fbc9734d826d9465078f376e

[ "BSD-3-Clause" ]

305

2016-02-21T06:35:25.000Z

2022-03-30T11:53:31.000Z

pandas_ml/imbaccessors/__init__.py

matsavage/pandas-ml

794cddc8dc5d0a49fbc9734d826d9465078f376e

[ "BSD-3-Clause" ]

69

2016-02-16T08:10:46.000Z

2022-03-04T14:36:12.000Z

pandas_ml/imbaccessors/__init__.py

matsavage/pandas-ml

794cddc8dc5d0a49fbc9734d826d9465078f376e

[ "BSD-3-Clause" ]

73

2016-02-16T08:27:28.000Z

2022-03-10T06:57:51.000Z

#!/usr/bin/env python from pandas_ml.imbaccessors.base import ImbalanceMethods # noqa

22.75

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91

3

66

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null

0

1

0

1

0

1

0

5

c7afb0a2d05fd2b544af6b88629198886b263767

31,853

py

Python

report_generation.py

rohit-k-das/vulnerability-management-reporter

0d3f2177669ff4dc72ba1a80e825e7e8de18cc86

[ "MIT" ]

null

report_generation.py

rohit-k-das/vulnerability-management-reporter

0d3f2177669ff4dc72ba1a80e825e7e8de18cc86

[ "MIT" ]

null

report_generation.py

rohit-k-das/vulnerability-management-reporter

0d3f2177669ff4dc72ba1a80e825e7e8de18cc86

[ "MIT" ]

null

import logging import drive import datetime import sheet from typing import List, Dict, Tuple import ConfigParser import os logger = logging.getLogger(__name__) Config = ConfigParser.ConfigParser() Config.read(os.path.join(os.path.abspath(os.path.dirname(__file__)), 'settings.ini')) google_user_for_service_account = Config.get('Settings', 'Google_User_For_Project') google_team_drive = Config.get('Settings', 'Gdrive_Team_Drive') gdrive_folder_in_team_drive = Config.get('Settings', 'GDrive_Vulnerabilty_Management_Folder') # Creates root folder that will contain vulnerability report def check_and_create_report_root_folders() -> Tuple[str, str]: drive_id = drive.find_drive(google_team_drive, google_user_for_service_account) # Check main folder in Security Engineering root_folder_id = drive.find_folder(gdrive_folder_in_team_drive, google_user_for_service_account, drive_id) year = datetime.datetime.now().strftime('%Y') month_year = datetime.datetime.now().strftime('%B - %Y') if root_folder_id is not None: # Check year folder in main folder sub_folder_id = drive.find_folder(year, google_user_for_service_account, drive_id, root_folder_id) if sub_folder_id is not None: # Check month year folder in year sub-folder sub_sub_folder_id = drive.find_folder(month_year, google_user_for_service_account, drive_id, sub_folder_id) if sub_sub_folder_id is None: sub_sub_folder_id = drive.create_file(sub_folder_id, month_year, 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) else: sub_folder_id = drive.create_file(root_folder_id, year, 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) sub_sub_folder_id = drive.create_file(sub_folder_id, month_year, 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) else: root_folder_id = drive.create_file(root_folder_id, gdrive_folder_in_team_drive, 'application/vnd.google-apps.folder', drive.google_user_for_service_account, drive_id) sub_folder_id = drive.create_file(root_folder_id, year, 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) sub_sub_folder_id = drive.create_file(sub_folder_id, month_year, 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) return drive_id, sub_sub_folder_id def check_and_create_report_prod_folders(drive_id: str, sub_sub_folder_id: str) -> Tuple[str, str, str]: # Check Production Folder production_folder_id = drive.find_folder('Production', google_user_for_service_account, drive_id, sub_sub_folder_id) if production_folder_id is not None: # Check GCP Folder prod_gcp_folder_id = drive.find_folder('GCP', google_user_for_service_account, drive_id, production_folder_id) if prod_gcp_folder_id is None: prod_gcp_folder_id = drive.create_file(production_folder_id, 'GCP', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) # Check Windows Folder Prod prod_windows_folder_id = drive.find_folder('Windows', google_user_for_service_account, drive_id, production_folder_id) if prod_windows_folder_id is None: prod_windows_folder_id = drive.create_file(production_folder_id, 'Windows', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) # Check Linux Folder prod_linux_folder_id = drive.find_folder('Linux', google_user_for_service_account, drive_id, production_folder_id) if prod_linux_folder_id is None: prod_linux_folder_id = drive.create_file(production_folder_id, 'Linux', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) else: production_folder_id = drive.create_file(sub_sub_folder_id, 'Production', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) prod_windows_folder_id = drive.create_file(production_folder_id, 'Windows', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) prod_linux_folder_id = drive.create_file(production_folder_id, 'Linux', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) prod_gcp_folder_id = drive.create_file(production_folder_id, 'GCP', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) return prod_gcp_folder_id, prod_windows_folder_id, prod_linux_folder_id def check_and_create_report_corp_folders(drive_id: str, sub_sub_folder_id: str) -> Tuple[str, str]: # Check Corporate Folder corporate_folder_id = drive.find_folder('Corporate', google_user_for_service_account, drive_id, sub_sub_folder_id) if corporate_folder_id is not None: # Check Windows Folder Corporate corp_windows_folder_id = drive.find_folder('Windows', google_user_for_service_account, drive_id, corporate_folder_id) if corp_windows_folder_id is None: corp_windows_folder_id = drive.create_file(corporate_folder_id, 'Windows', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) # Check Mac Folder Corporate corp_mac_folder_id = drive.find_folder('Macs', google_user_for_service_account, drive_id, corporate_folder_id) if corp_mac_folder_id is None: corp_mac_folder_id = drive.create_file(corporate_folder_id, 'Macs', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) else: corporate_folder_id = drive.create_file(sub_sub_folder_id, 'Corporate', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) corp_windows_folder_id = drive.create_file(corporate_folder_id, 'Windows', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) corp_mac_folder_id = drive.create_file(corporate_folder_id, 'Macs', 'application/vnd.google-apps.folder', google_user_for_service_account, drive_id) return corp_windows_folder_id, corp_mac_folder_id def generate_windows_package_report(report_name: str, vulnerabilities: List, folder_id: str, drive_id: str) -> None: package_rows = [] package_rows.append('Device,Criticality,Vulnerability,KB,CVE,Info'.split(',')) package_sheet_id = drive.create_file(folder_id, 'KB_%s' % report_name, 'application/vnd.google-apps.spreadsheet', google_user_for_service_account, drive_id) update_rows = [] update_rows.append('Device,Criticality,Vulnerability,Solution,CVE,Info'.split(',')) update_sheet_id = drive.create_file(folder_id, 'Software_Update_%s' % report_name, 'application/vnd.google-apps.spreadsheet', google_user_for_service_account, drive_id) if package_sheet_id is not None and update_sheet_id is not None: criticality_of_vulnerabilities = categorize_vulnerabilities_on_criticality(vulnerabilities) for category in criticality_of_vulnerabilities: kb_patch_vulnerabilities = [] update_patch_vulnerabilities = [] for vulnerability in criticality_of_vulnerabilities[category]: if 'KB' in vulnerability.resolution[:3]: kb_patch_vulnerabilities.append(vulnerability) else: update_patch_vulnerabilities.append(vulnerability) kb_patch_devices = {} ''' { testhost.com: { KB: [] Plugin Name: [] CVE: [] Link: [] Critcality: '' } } ''' update_patch_device = {} for vulnerability in kb_patch_vulnerabilities: if 'centos' not in vulnerability.plugin_name.lower(): if vulnerability.dns: if vulnerability.dns in kb_patch_devices: kb_patch_devices[vulnerability.dns].append(vulnerability) else: kb_patch_devices[vulnerability.dns] = [vulnerability] else: if vulnerability.ip in kb_patch_devices: kb_patch_devices[vulnerability.ip].append(vulnerability) else: kb_patch_devices[vulnerability.ip] = [vulnerability] for vulnerability in update_patch_vulnerabilities: if 'centos' not in vulnerability.plugin_name.lower(): if vulnerability.dns: if vulnerability.dns in update_patch_device: update_patch_device[vulnerability.dns].append(vulnerability) else: update_patch_device[vulnerability.dns] = [vulnerability] else: if vulnerability.ip in update_patch_device: update_patch_device[vulnerability.ip].append(vulnerability) else: update_patch_device[vulnerability.ip] = [vulnerability] logger.info('Found %d devices that marked as %s for KB patches' % (len(kb_patch_devices), category)) logger.info('Found %d devices that marked as %s for updates' % (len(update_patch_device), category)) for device in kb_patch_devices: KB = [] plugins = [] cves = [] info_links = [] for vulnerability in kb_patch_devices[device]: KB.extend(vulnerability.resolution.split(',')) plugins.append(vulnerability.plugin_name) if vulnerability.cves: cves.extend(vulnerability.cves) info_links.extend(vulnerability.additional_links) KB = '\r'.join(list(set(KB))).replace("'", '').replace('"', '') plugins = '\r'.join(list(set(plugins))).replace("'", '').replace('"', '') cves = ', '.join(list(set(cves))).replace("'", '').replace('"', '') info_links = '\r'.join(list(set(info_links))).replace("'", '').replace('"', '') package_rows.append(("%s|%s|%s|%s|%s|%s" % (device, category, plugins, KB, cves, info_links)).split('|')) for device in update_patch_device: solution = [] plugins = [] cves = [] info_links = [] for vulnerability in update_patch_device[device]: solution.append(vulnerability.resolution) plugins.append(vulnerability.plugin_name) if vulnerability.cves: cves.extend(vulnerability.cves) info_links.extend(vulnerability.additional_links) solution = '\r'.join(list(set(solution))).replace("'", '').replace('"', '') plugins = '\r'.join(list(set(plugins))).replace("'", '').replace('"', '') cves = ', '.join(list(set(cves))).replace("'", '').replace('"', '') info_links = '\r'.join(list(set(info_links))).replace("'", '').replace('"', '') update_rows.append(("%s|%s|%s|%s|%s|%s" % (device, category, plugins, solution, cves, info_links)).split('|')) sheet.update_sheet('KB_%s' % report_name, package_rows, google_user_for_service_account, package_sheet_id) sheet.update_sheet('Software_Update_%s' % report_name, update_rows, google_user_for_service_account, update_sheet_id) def generate_linux_package_report(report_name: str, vulnerabilities: List, folder_id: str, drive_id: str) -> None: rows = [] rows.append('Device,Criticality,Vulnerability,Upgrade/Update,CVE,Info'.split(',')) sheet_id = drive.create_file(folder_id, report_name, 'application/vnd.google-apps.spreadsheet', google_user_for_service_account, drive_id) if sheet_id is not None: criticality_of_vulnerabilities = categorize_vulnerabilities_on_criticality(vulnerabilities) for category in criticality_of_vulnerabilities: devices = {} for vulnerability in criticality_of_vulnerabilities[category]: if vulnerability.dns: if vulnerability.dns in devices: devices[vulnerability.dns].append(vulnerability) else: devices[vulnerability.dns] = [vulnerability] else: if vulnerability.ip in devices: devices[vulnerability.ip].append(vulnerability) else: devices[vulnerability.ip] = [vulnerability] logger.info('Found %d devices that marked as %s for linux security updates' % (len(devices), category)) for device in devices: packages = [] plugins = [] cves = [] info_links = [] for vulnerability in devices[device]: packages.extend(vulnerability.resolution.split(',')) plugins.append(vulnerability.plugin_name) if vulnerability.cves: cves.extend(vulnerability.cves) info_links.extend(vulnerability.additional_links) packages = '\r'.join(list(set(packages))).replace("'", '').replace('"', '') plugins = '\r'.join(list(set(plugins))).replace("'", '').replace('"', '') cves = ', '.join(list(set(cves))).replace("'", '').replace('"', '') info_links = '\r'.join(list(set(info_links))).replace("'", '').replace('"', '') rows.append(("%s|%s|%s|%s|%s|%s" % (device, category, plugins, packages, cves, info_links)).split('|')) sheet.update_sheet(report_name, rows, google_user_for_service_account, sheet_id) def generate_config_report(report_name: str, vulnerabilities: List, folder_id: str, drive_id: str) -> None: rows = [] rows.append('Device,Criticality,Vulnerability,Changes,CVE,Info'.split(',')) sheet_id = drive.create_file(folder_id, 'Change_Configuration_%s' % report_name, 'application/vnd.google-apps.spreadsheet', google_user_for_service_account, drive_id) if sheet_id is not None: criticality_of_vulnerabilities = categorize_vulnerabilities_on_criticality(vulnerabilities) for category in criticality_of_vulnerabilities: devices = {} for vulnerability in criticality_of_vulnerabilities[category]: if vulnerability.dns: if vulnerability.dns in devices: devices[vulnerability.dns].append(vulnerability) else: devices[vulnerability.dns] = [vulnerability] else: if vulnerability.ip in devices: devices[vulnerability.ip].append(vulnerability) else: devices[vulnerability.ip] = [vulnerability] logger.info('Found %d devices that marked as %s for config updates' % (len(devices), category)) for device in devices: changes = [] plugins = [] cves = [] info_links = [] for vulnerability in devices[device]: changes.extend(vulnerability.resolution.split(',')) plugins.append(vulnerability.plugin_name) if vulnerability.cves: cves.extend(vulnerability.cves) info_links.extend(vulnerability.additional_links) changes = '\r'.join(list(set(changes))).replace("'", '').replace('"', '') plugins = '\r'.join(list(set(plugins))).replace("'", '').replace('"', '') cves = ', '.join(list(set(cves))).replace("'", '').replace('"', '') info_links = '\r'.join(list(set(info_links))).replace("'", '').replace('"', '') rows.append(("%s|%s|%s|%s|%s|%s" % (device, category, plugins, changes, cves, info_links)).split('|')) sheet.update_sheet(report_name, rows, google_user_for_service_account, sheet_id) def generate_general_report(report_name: str, vulnerabilities: List, folder_id: str, drive_id: str) -> None: rows = [] sheet_id = drive.create_file(folder_id, report_name, 'application/vnd.google-apps.spreadsheet', google_user_for_service_account, drive_id) if sheet_id is not None: rows.append('Device,Criticality,Vulnerability,Solution,CVE,Info'.split(',')) criticality_of_vulnerabilities = categorize_vulnerabilities_on_criticality(vulnerabilities) for category in criticality_of_vulnerabilities: solutions = {} for vulnerability in criticality_of_vulnerabilities[category]: if vulnerability.resolution in solutions: solutions[vulnerability.resolution].append(vulnerability) else: solutions[vulnerability.resolution] = [vulnerability] for solution in solutions: devices = [] plugins = [] cves = [] info_links = [] for vulnerability in solutions[solution]: devices.append(vulnerability.dns or vulnerability.ip) plugins.append(vulnerability.plugin_name) if vulnerability.cves: cves.extend(vulnerability.cves) info_links.extend(vulnerability.additional_links) plugins = '\r'.join(list(set(plugins))).replace("'", '').replace('"', '') cves = ', '.join(list(set(cves))).replace("'", '').replace('"', '') info_links = '\r'.join(list(set(info_links))).replace("'", '').replace('"', '') devices = list(set(devices)) # Sheet can accept a max of 50000 characters in a single cell if len(str(devices)) > 45000: number_in_each_block_list = int(len(devices)/(len(str(devices))/45000)) device_list = [devices[i:number_in_each_block_list] for i in range(0, len(devices), number_in_each_block_list)] for each_list in device_list: devices = '\r'.join(each_list).replace("'", '').replace('"', '') rows.append(("%s|%s|%s|%s|%s|%s" % (devices, category, plugins, solution, cves, info_links)).split('|')) else: devices = '\r'.join(devices).replace("'", '').replace('"', '') rows.append(("%s|%s|%s|%s|%s|%s" % (devices, category, plugins, solution, cves, info_links)).split('|')) sheet.update_sheet(report_name, rows, google_user_for_service_account, sheet_id) def categorize_vulnerabilities_on_criticality(vulnerabilities: List) -> Dict[str, List]: criticality_of_vulnerabilities = { 'High': [], 'Medium': [], 'Low': [] } for vulnerability in vulnerabilities: if vulnerability.actual_criticality == 'High': criticality_of_vulnerabilities['High'].append(vulnerability) elif vulnerability.actual_criticality == 'Medium': criticality_of_vulnerabilities['Medium'].append(vulnerability) elif vulnerability.actual_criticality == 'Low': criticality_of_vulnerabilities['Low'].append(vulnerability) else: if vulnerability.nessus_criticiality == 'High': criticality_of_vulnerabilities['High'].append(vulnerability) elif vulnerability.nessus_criticiality == 'Medium': criticality_of_vulnerabilities['Medium'].append(vulnerability) elif vulnerability.nessus_criticiality == 'Low': criticality_of_vulnerabilities['Low'].append(vulnerability) return criticality_of_vulnerabilities def divide_linux_vulnerabilities_based_on_os_version(vulnerabilities: List) -> Dict[str, List]: os_flavors = list(set(vulnerability.os for vulnerability in vulnerabilities)) categorized_on_os = {} for os in os_flavors: if os: categorized_on_os[os] = [] categorized_on_os['Linux'] = [] for vulnerability in vulnerabilities: if vulnerability.os: categorized_on_os[vulnerability.os].append(vulnerability) else: categorized_on_os['Linux'].append(vulnerability) return categorized_on_os def generate_prod_reports(vulnerabilities: List, gcp: bool = False) -> None: drive.drive_access_tokens[google_user_for_service_account] = {} access_token, expiry = drive.generate_drive_api_access_token(google_user_for_service_account) if access_token is not None and expiry is not None: drive.drive_access_tokens[google_user_for_service_account]['access_token'] = access_token drive.drive_access_tokens[google_user_for_service_account]['expiry'] = expiry drive_id, folder_id = check_and_create_report_root_folders() if drive_id is not None and folder_id is not None: prod_gcp_folder_id, prod_windows_folder_id, prod_linux_folder_id = check_and_create_report_prod_folders(drive_id, folder_id) else: logger.info('Unable to find drive id and folder id') exit(-1) sheet.sheet_access_tokens[google_user_for_service_account] = {} access_token, expiry = sheet.generate_sheet_api_access_token(google_user_for_service_account) if access_token is not None and expiry is not None: sheet.sheet_access_tokens[google_user_for_service_account]['access_token'] = access_token sheet.sheet_access_tokens[google_user_for_service_account]['expiry'] = expiry server_windows_package_vulnerabilities = [] server_windows_config_vulnerabilities = [] server_linux_package_vulnerabilities = [] server_linux_config_vulnerabilities = [] logger.info('Dividing vulnerabilities into packages and configs') for vulnerability in vulnerabilities: if vulnerability.platform == 'Windows' and vulnerability.vulnerability_type == 'package': server_windows_package_vulnerabilities.append(vulnerability) elif vulnerability.platform == 'Windows' and vulnerability.vulnerability_type == 'config': server_windows_config_vulnerabilities.append(vulnerability) elif vulnerability.platform == 'Linux' and vulnerability.vulnerability_type == 'package': server_linux_package_vulnerabilities.append(vulnerability) elif vulnerability.platform == 'Linux' and vulnerability.vulnerability_type == 'config': server_linux_config_vulnerabilities.append(vulnerability) vulnerabilities.clear() logger.info('Dividing Linux Vulnerabilities based on OS') server_linux_package_vulnerabilities_based_on_os = divide_linux_vulnerabilities_based_on_os_version(server_linux_package_vulnerabilities) server_linux_config_vulnerabilities_based_on_os = divide_linux_vulnerabilities_based_on_os_version(server_linux_config_vulnerabilities) server_linux_package_vulnerabilities.clear() server_linux_config_vulnerabilities.clear() if not gcp: # Windows Packages logger.info('Generating reports for High, Medium & Low vulnerabilities for windows packages across dev, qa, test and prod') if server_windows_package_vulnerabilities and prod_windows_folder_id is not None: generate_windows_package_report('windows_package_%s' % datetime.date.today().isoformat().replace('-', ''), server_windows_package_vulnerabilities, prod_windows_folder_id, drive_id) server_windows_package_vulnerabilities.clear() # Windows Config logger.info('Generating reports for High, Medium & Low vulnerabilities for windows config across dev, qa, test and prod') if server_windows_config_vulnerabilities and prod_windows_folder_id is not None: generate_general_report('Windows_config_%s' % datetime.date.today().isoformat().replace('-', ''), server_windows_config_vulnerabilities, prod_windows_folder_id, drive_id) server_windows_config_vulnerabilities.clear() # Linux Packages logger.info('Generating reports for High, Medium & Low vulnerabilities for linux packages across dev, qa, test and prod') for os in server_linux_package_vulnerabilities_based_on_os: if server_linux_package_vulnerabilities_based_on_os[os] and prod_linux_folder_id is not None: generate_linux_package_report('Linux_package_%s_%s' % (os, datetime.date.today().isoformat().replace('-', '')), server_linux_package_vulnerabilities_based_on_os[os], prod_linux_folder_id, drive_id) server_linux_package_vulnerabilities_based_on_os.clear() # Linux Config logger.info('Generating reports for High, Medium & Low vulnerabilities for linux config across dev, qa, test and prod') for os in server_linux_config_vulnerabilities_based_on_os: if server_linux_config_vulnerabilities_based_on_os[os] and prod_linux_folder_id is not None: generate_general_report('Linux_config_%s_%s' % (os, datetime.date.today().isoformat().replace('-', '')), server_linux_config_vulnerabilities_based_on_os[os], prod_linux_folder_id, drive_id) server_linux_config_vulnerabilities_based_on_os.clear() #drive.assign_permission(prod_windows_folder_id, email, recipient) else: # GCP Windows Packages logger.info('Generating reports for High, Medium & Low vulnerabilities for GCP windows packages across dev, qa, test and prod') if server_windows_package_vulnerabilities and prod_gcp_folder_id is not None: generate_windows_package_report('windows_package_%s' % datetime.date.today().isoformat().replace('-', ''), server_windows_package_vulnerabilities, prod_gcp_folder_id, drive_id) server_windows_package_vulnerabilities.clear() # GCP Windows Config logger.info('Generating reports for High, Medium & Low vulnerabilities for GCP windows config across dev, qa, test and prod') if server_windows_config_vulnerabilities and prod_gcp_folder_id is not None: generate_general_report('Windows_config_%s' % datetime.date.today().isoformat().replace('-', ''), server_windows_config_vulnerabilities, prod_gcp_folder_id, drive_id) server_windows_config_vulnerabilities.clear() # GCP Linux Packages logger.info('Generating reports for High, Medium & Low vulnerabilities for GCP linux packages across dev, qa, test and prod') for os in server_linux_package_vulnerabilities_based_on_os: if server_linux_package_vulnerabilities_based_on_os[os] and prod_gcp_folder_id is not None: generate_linux_package_report('Linux_package_%s_%s' % (os, datetime.date.today().isoformat().replace('-', '')), server_linux_package_vulnerabilities_based_on_os[os], prod_gcp_folder_id, drive_id) server_linux_package_vulnerabilities_based_on_os.clear() # GCP Linux Config logger.info('Generating reports for High, Medium & Low vulnerabilities for GCP linux config across dev, qa, test and prod') for os in server_linux_config_vulnerabilities_based_on_os: if server_linux_config_vulnerabilities_based_on_os[os] and prod_gcp_folder_id is not None: generate_general_report('Linux_config_%s_%s' % (os,datetime.date.today().isoformat().replace('-', '')), server_linux_config_vulnerabilities_based_on_os[os], prod_gcp_folder_id, drive_id) server_linux_config_vulnerabilities_based_on_os.clear() def generate_corp_reports(vulnerabilities: List) -> None: drive.drive_access_tokens[google_user_for_service_account] = {} access_token, expiry = drive.generate_drive_api_access_token(google_user_for_service_account) if access_token is not None and expiry is not None: drive.drive_access_tokens[google_user_for_service_account]['access_token'] = access_token drive.drive_access_tokens[google_user_for_service_account]['expiry'] = expiry drive_id, folder_id = check_and_create_report_root_folders() if drive_id is not None and folder_id is not None: corp_windows_folder_id, corp_mac_folder_id = check_and_create_report_corp_folders(drive_id, folder_id) else: logger.info('Unable to find drive id and folder id') exit(-1) sheet.sheet_access_tokens[google_user_for_service_account] = {} access_token, expiry = sheet.generate_sheet_api_access_token(google_user_for_service_account) if access_token is not None and expiry is not None: sheet.sheet_access_tokens[google_user_for_service_account]['access_token'] = access_token sheet.sheet_access_tokens[google_user_for_service_account]['expiry'] = expiry windows_package_vulnerabilities = [] windows_config_vulnerabilities = [] mac_package_vulnerabilities = [] mac_config_vulnerabilities = [] logger.info('Dividing vulnerabilities into dev, qa, test and prod') for vulnerability in vulnerabilities: if vulnerability.platform == 'Windows' and vulnerability.vulnerability_type == 'package': windows_package_vulnerabilities.append(vulnerability) elif vulnerability.platform == 'Windows' and vulnerability.vulnerability_type == 'config': windows_config_vulnerabilities.append(vulnerability) if vulnerability.platform == 'Mac' and vulnerability.vulnerability_type == 'package': mac_package_vulnerabilities.append(vulnerability) elif vulnerability.platform == 'Mac' and vulnerability.vulnerability_type == 'config': mac_config_vulnerabilities.append(vulnerability) vulnerabilities.clear() # Windows Packages logger.info('Generating reports for High, Medium & Low vulnerabilities for Corp windows packages corp environment') if windows_package_vulnerabilities and corp_windows_folder_id is not None: generate_windows_package_report('windows_package_%s' % datetime.date.today().isoformat().replace('-', ''), windows_package_vulnerabilities, corp_windows_folder_id, drive_id) windows_package_vulnerabilities.clear() # Windows Config logger.info('Generating reports for High, Medium & Low vulnerabilities for Corp windows config corp environment') if windows_config_vulnerabilities and corp_windows_folder_id is not None: generate_general_report('Windows_config_%s' % datetime.date.today().isoformat().replace('-', ''), windows_config_vulnerabilities, corp_windows_folder_id, drive_id) windows_config_vulnerabilities.clear() # Mac Packages logger.info('Generating reports for High, Medium & Low vulnerabilities for Corp mac packages corp environment') if mac_package_vulnerabilities and corp_mac_folder_id is not None: generate_linux_package_report('Mac_package_%s' % datetime.date.today().isoformat().replace('-', ''), mac_package_vulnerabilities, corp_mac_folder_id, drive_id) mac_package_vulnerabilities.clear() # Mac Config logger.info('Generating reports for High, Medium & Low vulnerabilities for Corp mac config corp environment') if mac_config_vulnerabilities and corp_mac_folder_id is not None: generate_general_report('Mac_config_%s' % datetime.date.today().isoformat().replace('-', ''), mac_config_vulnerabilities, corp_mac_folder_id, drive_id) mac_config_vulnerabilities.clear()

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0

0.000767

0.221832

31,853

546

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0.055288

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null

0

1

0

1

0

null

0

5

c7f4e4d4d4fb5516d40f6ce6d63f7fb0a55a8a78

111

py

Python

Data_Conversion/Kfunc/__init__.py

simay1224/K-project-UI

c69f83b6446052a1cd32a00700e7db197f36a1ed

[ "Apache-2.0" ]

null

Data_Conversion/Kfunc/__init__.py

simay1224/K-project-UI

c69f83b6446052a1cd32a00700e7db197f36a1ed

[ "Apache-2.0" ]

1

2018-06-19T22:21:43.000Z

Data_Conversion/Kfunc/__init__.py

simay1224/K-project-UI

c69f83b6446052a1cd32a00700e7db197f36a1ed

[ "Apache-2.0" ]

3

2018-08-29T18:39:57.000Z

2020-06-05T15:29:07.000Z

# -*- coding: utf-8 -*- """ Created on Tue Nov 15 17:09:56 2016 @author: medialab """ from model import *

11.1

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0.151163

0.225225

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null

0

1

0

1

0

1

0

5

1bf68078a26440e3f5260b505f96ef272240aaf8

95

py

Python

Class 12 Record Book/Length.py

Bamgm14/My-Random-Work

b9678a3a84dd8ff00efd638890cff76eb6967c1b

[ "MIT" ]

null

Class 12 Record Book/Length.py

Bamgm14/My-Random-Work

b9678a3a84dd8ff00efd638890cff76eb6967c1b

[ "MIT" ]

null

Class 12 Record Book/Length.py

Bamgm14/My-Random-Work

b9678a3a84dd8ff00efd638890cff76eb6967c1b

[ "MIT" ]

null

def Length(file='Weird.txt'): return len(list(open(file,'r').readlines())) print(Length())

23.75

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95

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0

null

0

1

0

1

0

5

4043fd507df5bdbc5820b08b225176806f2983d1

1,836

py

Python

stonesoup/types/array.py

dlast-dstl/Stone-Soup

033254add5adc00097b746f81d6640308a3e3319

[ "MIT" ]

1

2021-04-13T11:47:42.000Z

stonesoup/types/array.py

dlast-dstl/Stone-Soup

033254add5adc00097b746f81d6640308a3e3319

[ "MIT" ]

null

stonesoup/types/array.py

dlast-dstl/Stone-Soup

033254add5adc00097b746f81d6640308a3e3319

[ "MIT" ]

null

# -*- coding: utf-8 -*- import numpy as np class StateVector(np.ndarray): """State vector wrapper for :class:`numpy.ndarray` This class returns a view to a :class:`numpy.ndarray`, but ensures that its initialised at a *Nx1* vector. It's called same as to :func:`numpy.asarray`. """ def __new__(cls, *args, **kwargs): array = np.asarray(*args, **kwargs) if not (array.ndim == 2 and array.shape[1] == 1): raise ValueError( "state vector shape should be Nx1 dimensions: got {}".format( array.shape)) return array.view(cls) def __array_wrap__(self, array): return np.asarray(array) def __matmul__(self, other): out = np.matmul(np.asfarray(self), np.asfarray(other)) return out.view(type=type(self)) def __rmatmul__(self, other): out = np.matmul(np.asfarray(other), np.asfarray(self)) return out.view(type=type(other)) class CovarianceMatrix(np.ndarray): """Covariance matrix wrapper for :class:`numpy.ndarray`. This class returns a view to a :class:`numpy.ndarray`, but ensures that its initialised at a *NxN* matrix. It's called similar to :func:`numpy.asarray`. """ def __new__(cls, *args, **kwargs): array = np.asarray(*args, **kwargs) if not array.ndim == 2: raise ValueError("Covariance should have ndim of 2: got {}" "".format(array.ndim)) return array.view(cls) def __array_wrap__(self, array): return np.asarray(array) def __matmul__(self, other): out = np.matmul(self, np.asfarray(other)) return out.view(type=type(self)) def __rmatmul__(self, other): out = np.matmul(np.asfarray(other), self) return out.view(type=type(other))

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0.610022

242

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4.487603

0.280992

0.055249

0.062615

0.051565

0.712707

0.64825

0

0.005878

0.258715

1,836

57

78

32.210526

0.792065

0.235294

0

0.5625

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false

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1

0

null

0

1

0

1

0

5

40517258bb4832a077d5c1ffbc13d2bd7db0e5b6

2,508

py

Python

bannerpunk/print.py

jarret/bannerpunk

f51d29fadf72c04b0b66adf8f5674328bff9f599

[ "MIT" ]

3

2019-12-09T02:03:57.000Z

2019-12-29T03:42:18.000Z

bannerpunk/print.py

jarret/bannerpunk

f51d29fadf72c04b0b66adf8f5674328bff9f599

[ "MIT" ]

null

bannerpunk/print.py

jarret/bannerpunk

f51d29fadf72c04b0b66adf8f5674328bff9f599

[ "MIT" ]

null

# Copyright (c) 2018 PrimeVR # All rights Reserved ############################################################################### # print helpers ############################################################################### CHILL_WHITE = '\x1b[0;37;40m' CHILL_PURPLE = '\x1b[0;35;40m' CHILL_LIGHT_BLUE = '\x1b[0;36;40m' CHILL_BLUE = '\x1b[0;34;40m' MEGA_WHITE = '\x1b[1;37;40m' LIGHT_BLUE = '\x1b[1;36;40m' BLUE = '\x1b[1;34;40m' GREEN = '\x1b[1;32;40m' CHILL_GREEN = '\x1b[0;32;40m' RED = '\x1b[1;31;40m' YELLOW = '\x1b[1;33;40m' CHILL_YELLOW = '\x1b[0;33;40m' FANCY_BLUE = '\x1b[1;37;44m' ANNOYING = '\x1b[5;31;44m' ENDC = '\x1b[0m' def print_red(string): print(RED + string + ENDC) def print_green(string): print(GREEN + string + ENDC) def print_chill_green(string): print(CHILL_GREEN + string + ENDC) def print_light_blue(string): print(LIGHT_BLUE + string + ENDC) def print_fancy_blue(string): print(FANCY_BLUE + string + ENDC) def print_blue(string): print(BLUE + string + ENDC) def print_yellow(string): print(YELLOW + string + ENDC) def print_chill_yellow(string): print(CHILL_YELLOW + string + ENDC) def print_chill_white(string): print(CHILL_WHITE + string + ENDC) def print_chill_purple(string): print(CHILL_PURPLE + string + ENDC) def print_chill_light_blue(string): print(CHILL_LIGHT_BLUE + string + ENDC) def print_chill_blue(string): print(CHILL_BLUE + string + ENDC) def print_mega_white(string): print(MEGA_WHITE + string + ENDC) def print_annoying(string): print(ANNOYING + string + ENDC) ################################################################## def red_str(string): return RED + string + ENDC def chill_green_str(string): return CHILL_GREEN + string + ENDC def light_blue_str(string): return LIGHT_BLUE + string + ENDC def fancy_blue_str(string): return FANCY_BLUE + string + ENDC def blue_str(string): return BLUE + string + ENDC def yellow_str(string): return YELLOW + string + ENDC def chill_yellow_str(string): return CHILL_YELLOW + string + ENDC def chill_white_str(string): return CHILL_WHITE + string + ENDC def chill_purple_str(string): return CHILL_PURPLE + string + ENDC def chill_light_blue_str(string): return CHILL_LIGHT_BLUE + string + ENDC def chill_blue_str(string): return CHILL_BLUE + string + ENDC def mega_white_str(string): return MEGA_WHITE + string + ENDC def annoying_str(string): return ANNOYING + string + ENDC

23.660377

79

0.642743

348

2,508

4.41092

0.112069

0.175896

0.220195

0.152443

0.441694

0.093811

0

0.042715

0.159888

2,508

105

80

23.885714

0.685809

0.023923

0

0.085135

0

1

0.391304

false

0

0.188406

0.57971

0.405797

0

null

0

1

0

null

0

1

0

1

0

5

40517478ae6e37ed546d663cd3159a7be1cafc5d

107

py

Python

slybot/slybot/starturls/__init__.py

bowlofstew/portia

41aaf2ef1a3ac75aeda363b6a5b67bf21b1afd4c

[ "BSD-3-Clause" ]

1

2017-11-03T13:00:21.000Z

slybot/slybot/starturls/__init__.py

Save22/portia

961d2c87b99d99fbdc17aa932ec897bdbcd54d79

[ "BSD-3-Clause" ]

2

2021-03-31T20:04:55.000Z

2021-12-13T20:47:09.000Z

slybot/slybot/starturls/__init__.py

bowlofstew/portia

41aaf2ef1a3ac75aeda363b6a5b67bf21b1afd4c

[ "BSD-3-Clause" ]

2

2017-11-03T13:00:23.000Z

2020-08-28T19:59:40.000Z

from .generator import UrlGenerator class StartUrls(): def __call__(self, spec): return spec

15.285714

35

0.691589

12

107

5.833333

0.916667

0

0.233645

107

6

36

17.833333

0.853659

0

1

0.25

false

0

0.25

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

409f30d07086ca905cdec06fd445e125530e6735

1,564

py

Python

guillotina/utils/__init__.py

karannaoh/guillotina

dbc04f142734c465a04cb94ef6801ba819e63c76

[ "BSD-2-Clause" ]

null

guillotina/utils/__init__.py

karannaoh/guillotina

dbc04f142734c465a04cb94ef6801ba819e63c76

[ "BSD-2-Clause" ]

null

guillotina/utils/__init__.py

karannaoh/guillotina

dbc04f142734c465a04cb94ef6801ba819e63c76

[ "BSD-2-Clause" ]

null

from .auth import get_authenticated_user # noqa from .auth import get_authenticated_user_id # noqa from .content import get_behavior # noqa from .content import get_containers # noqa from .content import get_content_depth # noqa from .content import get_content_path # noqa from .content import get_object_by_oid # noqa from .content import get_object_url # noqa from .content import get_owners # noqa from .content import iter_databases # noqa from .content import iter_parents # noqa from .content import navigate_to # noqa from .content import valid_id # noqa from .crypto import get_jwk_key # noqa from .crypto import secure_passphrase # noqa from .misc import apply_coroutine # noqa from .misc import get_current_request # noqa from .misc import get_random_string # noqa from .misc import get_url # noqa from .misc import lazy_apply # noqa from .misc import list_or_dict_items # noqa from .misc import loop_apply_coroutine # noqa from .misc import merge_dicts # noqa from .misc import run_async # noqa from .misc import safe_unidecode # noqa from .misc import strings_differ # noqa from .misc import to_str # noqa from .modules import get_caller_module # noqa from .modules import get_class_dotted_name # noqa from .modules import get_dotted_name # noqa from .modules import get_module_dotted_name # noqa from .modules import import_class # noqa from .modules import resolve_dotted_name # noqa from .modules import resolve_module_path # noqa from .modules import resolve_path # noqa from .navigator import Navigator # noqa

42.27027

51

0.792839

237

1,564

4.991561

0.248945

0.236686

0.121724

0.182587

0.559594

0.324598

0.057481

0

0.161125

1,564

36

52

43.444444

0.901677

0.11445

0

1

0

true

0.027778

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

5

40ba7aab465979e7dcec90e2c60e8d488a3753b6

24,098

py

Python

tests/test_report_writer.py

lemoncheesecake/lemoncheesecake

bc92cb8225d74e2687ed5825ee5af3f56f907829

[ "Apache-2.0", "MIT" ]

34

2017-06-12T18:50:36.000Z

2021-11-29T01:59:07.000Z

tests/test_report_writer.py

lemoncheesecake/lemoncheesecake

bc92cb8225d74e2687ed5825ee5af3f56f907829

[ "Apache-2.0", "MIT" ]

25

2017-12-07T13:35:29.000Z

2022-03-10T01:27:58.000Z

tests/test_report_writer.py

lemoncheesecake/lemoncheesecake

bc92cb8225d74e2687ed5825ee5af3f56f907829

[ "Apache-2.0", "MIT" ]

4

2019-05-05T03:19:00.000Z

2021-10-06T13:12:05.000Z

# -*- coding: utf-8 -*- ''' Created on Nov 1, 2016 @author: nicolas ''' import os.path as osp import time import pytest import six import lemoncheesecake.api as lcc from lemoncheesecake.matching import * from helpers.runner import run_suite_class, run_suite_classes, run_func_in_test from helpers.report import assert_report_from_suite, assert_report_from_suites, get_last_test, get_last_attachment, \ assert_attachment SAMPLE_IMAGE_PATH = osp.join(osp.dirname(__file__), osp.pardir, "doc", "_static", "report-sample.png") with open(SAMPLE_IMAGE_PATH, "rb") as fh: SAMPLE_IMAGE_CONTENT = fh.read() def _get_suite(report, suite_path=None): return report.get_suite(suite_path) if suite_path else report.get_suites()[0] def _get_suite_setup(report, suite_path=None): suite = _get_suite(report, suite_path) return suite.suite_setup def _get_suite_teardown(report, suite_path=None): suite = _get_suite(report, suite_path) return suite.suite_teardown def make_file_reader(encoding=None, binary=False): def reader(path): with open(path, "rb" if binary else "r") as fh: content = fh.read() if encoding and six.PY2: content = content.decode(encoding) return content return reader def test_simple_test(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): pass report = run_suite_class(mysuite) assert_report_from_suite(report, mysuite) def test_test_with_all_metadata(): @lcc.suite("MySuite") class mysuite: @lcc.link("http://foo.bar", "foobar") @lcc.prop("foo", "bar") @lcc.tags("foo", "bar") @lcc.test("Some test") def sometest(self): pass report = run_suite_class(mysuite) assert_report_from_suite(report, mysuite) def test_suite_with_all_metadata(): @lcc.link("http://foo.bar", "foobar") @lcc.prop("foo", "bar") @lcc.tags("foo", "bar") @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): pass report = run_suite_class(mysuite) assert_report_from_suite(report, mysuite) def test_multiple_suites_and_tests(): @lcc.suite("MySuite1") class mysuite1: @lcc.tags("foo") @lcc.test("Some test 1") def test_1_1(self): pass @lcc.tags("bar") @lcc.test("Some test 2") def test_1_2(self): pass @lcc.tags("baz") @lcc.test("Some test 3") def test_1_3(self): pass @lcc.suite("MySuite2") class mysuite2: @lcc.prop("foo", "bar") @lcc.test("Some test 1") def test_2_1(self): pass @lcc.prop("foo", "baz") @lcc.test("Some test 2") def test_2_2(self): pass @lcc.test("Some test 3") def test_2_3(self): pass # suite3 is a sub suite of suite2 @lcc.suite("MySuite3") class mysuite3: @lcc.prop("foo", "bar") @lcc.test("Some test 1") def test_3_1(self): pass @lcc.prop("foo", "baz") @lcc.test("Some test 2") def test_3_2(self): pass @lcc.test("Some test 3") def test_3_3(self): pass report = run_suite_classes([mysuite1, mysuite2]) assert_report_from_suites(report, [mysuite1, mysuite2]) def test_check_success(): @lcc.suite("MySuite") class mysuite: @lcc.test("Test 1") def test_1(self): check_that("somevalue", "foo", equal_to("foo")) report = run_suite_class(mysuite) test = get_last_test(report) assert test.status == "passed" step = test.get_steps()[0] assert "somevalue" in step.get_logs()[0].description assert "foo" in step.get_logs()[0].description assert step.get_logs()[0].is_successful is True assert "foo" in step.get_logs()[0].details def test_check_failure(): @lcc.suite("MySuite") class mysuite: @lcc.test("Test 1") def test_1(self): check_that("somevalue", "foo", equal_to("bar")) report = run_suite_class(mysuite) test = get_last_test(report) assert test.status == "failed" step = test.get_steps()[0] assert "somevalue" in step.get_logs()[0].description assert "bar" in step.get_logs()[0].description assert step.get_logs()[0].is_successful is False assert "foo" in step.get_logs()[0].details def test_require_success(): @lcc.suite("MySuite") class mysuite: @lcc.test("Test 1") def test_1(self): require_that("somevalue", "foo", equal_to("foo")) report = run_suite_class(mysuite) test = get_last_test(report) assert test.status == "passed" step = test.get_steps()[0] assert "somevalue" in step.get_logs()[0].description assert "foo" in step.get_logs()[0].description assert step.get_logs()[0].is_successful is True assert "foo" in step.get_logs()[0].details def test_require_failure(): @lcc.suite("MySuite") class mysuite: @lcc.test("Test 1") def test_1(self): require_that("somevalue", "foo", equal_to("bar")) report = run_suite_class(mysuite) test = get_last_test(report) assert test.status == "failed" step = test.get_steps()[0] assert "somevalue" in step.get_logs()[0].description assert "bar" in step.get_logs()[0].description assert step.get_logs()[0].is_successful is False assert "foo" in step.get_logs()[0].details def test_all_types_of_logs(): @lcc.suite("MySuite") class mysuite: @lcc.test("Test 1") def test_1(self): lcc.log_debug("some debug message") lcc.log_info("some info message") lcc.log_warning("some warning message") @lcc.test("Test 2") def test_2(self): lcc.log_error("some error message") report = run_suite_class(mysuite) test = report.get_test("mysuite.test_1") assert test.status == "passed" step = test.get_steps()[0] assert step.get_logs()[0].level == "debug" assert step.get_logs()[0].message == "some debug message" assert step.get_logs()[1].level == "info" assert step.get_logs()[1].message == "some info message" assert step.get_logs()[2].level == "warn" test = report.get_test("mysuite.test_2") assert test.status == "failed" step = test.get_steps()[0] assert step.get_logs()[0].message == "some error message" assert step.get_logs()[0].level == "error" def test_multiple_steps(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): lcc.set_step("step 1") lcc.log_info("do something") lcc.set_step("step 2") lcc.log_info("do something else") report = run_suite_class(mysuite) test = get_last_test(report) assert test.status == "passed" steps = test.get_steps() assert steps[0].description == "step 1" assert steps[0].get_logs()[0].level == "info" assert steps[0].get_logs()[0].message == "do something" assert steps[1].description == "step 2" assert steps[1].get_logs()[0].level == "info" assert steps[1].get_logs()[0].message == "do something else" def test_multiple_steps_on_different_threads(): def thread_func(i): lcc.set_step(str(i)) time.sleep(0.001) lcc.log_info(str(i)) @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): threads = [lcc.Thread(target=thread_func, args=(i,)) for i in range(3)] for thread in threads: thread.start() for thread in threads: thread.join() report = run_suite_class(mysuite) test = get_last_test(report) remainings = list(range(3)) steps = test.get_steps() for step in steps: remainings.remove(int(step.description)) assert len(step.get_logs()) == 1 assert step.get_logs()[0].message == step.description assert len(remainings) == 0 def test_thread_logging_without_explicit_step(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): thread = lcc.Thread(target=lambda: lcc.log_info("doing something")) thread.start() thread.join() report = run_suite_class(mysuite) test = get_last_test(report) assert test.status == "passed" assert len(test.get_steps()) == 1 step = test.get_steps()[0] assert step.description == "Some test" assert step.get_logs()[0].level == "info" assert "doing something" == step.get_logs()[0].message def test_thread_logging_without_detached_bis(): def func(): lcc.log_info("log in thread") @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): lcc.set_step("Step 1") lcc.log_info("log 1") thread = lcc.Thread(target=func) lcc.set_step("Step 2") lcc.log_info("log 2") thread.start() thread.join() report = run_suite_class(mysuite) test = get_last_test(report) assert test.status == "passed" steps = test.get_steps() assert len(steps) == 3 step = test.get_steps()[0] assert step.description == "Step 1" assert step.get_logs()[0].message == "log 1" step = test.get_steps()[1] assert step.description == "Step 2" assert step.get_logs()[0].message == "log 2" step = test.get_steps()[2] assert step.description == "Step 1" assert step.get_logs()[0].message == "log in thread" def test_exception_in_thread(): def thread_func(): lcc.log_info("doing something") raise Exception("this_is_an_exception") @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): thread = lcc.Thread(target=thread_func) thread.start() thread.join() report = run_suite_class(mysuite) test = get_last_test(report) assert test.status == "failed" steps = test.get_steps() assert len(steps) == 1 step = steps[0] assert step.description == "Some test" assert step.get_logs()[-1].level == "error" assert "this_is_an_exception" in step.get_logs()[-1].message def test_same_step_in_two_threads(): def thread_func(): lcc.set_step("step 2") lcc.log_info("log 2") time.sleep(0.001) lcc.set_step("step 1") lcc.log_info("log 3") @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): lcc.set_step("step 1") lcc.log_info("log 1") thread = lcc.Thread(target=thread_func) thread.start() lcc.log_info("log 4") thread.join() report = run_suite_class(mysuite) test = get_last_test(report) steps = test.get_steps() assert len(steps) == 3 step = steps[0] assert step.description == "step 1" assert len(step.get_logs()) == 2 assert step.get_logs()[0].message == "log 1" assert step.get_logs()[1].message == "log 4" step = steps[1] assert step.description == "step 2" assert len(step.get_logs()) == 1 assert step.get_logs()[0].message == "log 2" step = steps[2] assert step.description == "step 1" assert len(step.get_logs()) == 1 assert step.get_logs()[0].message == "log 3" def test_deprecated_end_step(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): lcc.set_step("step") lcc.log_info("log") lcc.end_step("step") with pytest.warns(DeprecationWarning, match="deprecated"): report = run_suite_class(mysuite) test = get_last_test(report) assert test.status == "passed" step = test.get_steps()[0] assert step.description == "step" assert step.get_logs()[0].level == "info" assert step.get_logs()[0].message == "log" def test_deprecated_detached_step(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): with lcc.detached_step("step"): lcc.log_info("log") with pytest.warns(DeprecationWarning, match="deprecated"): report = run_suite_class(mysuite) test = get_last_test(report) step = test.get_steps()[0] assert test.status == "passed" assert step.description == "step" assert step.get_logs()[0].level == "info" assert step.get_logs()[0].message == "log" def test_default_step(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): lcc.log_info("do something") report = run_suite_class(mysuite) test = get_last_test(report) assert test.status == "passed" step = test.get_steps()[0] assert step.description == "Some test" assert step.get_logs()[0].level == "info" assert step.get_logs()[0].message == "do something" def test_step_after_test_setup(): @lcc.suite("mysuite") class mysuite: def setup_test(self, test): lcc.log_info("in test setup") @lcc.test("Some test") def sometest(self): lcc.log_info("do something") report = run_suite_class(mysuite) test = get_last_test(report) assert test.status == "passed" steps = test.get_steps() assert steps[0].description == "Setup test" assert steps[0].get_logs()[0].level == "info" assert steps[0].get_logs()[0].message == "in test setup" assert steps[1].description == "Some test" assert steps[1].get_logs()[0].level == "info" assert steps[1].get_logs()[0].message == "do something" def test_prepare_attachment(tmpdir): def do(): with lcc.prepare_attachment("foobar.txt", "some description") as filename: with open(filename, "w") as fh: fh.write("some content") report = run_func_in_test(do, tmpdir=tmpdir) assert_attachment( get_last_attachment(report), "foobar.txt", "some description", False, "some content", make_file_reader() ) def test_prepare_image_attachment(tmpdir): def do(): with lcc.prepare_image_attachment("foobar.png", "some description") as filename: with open(filename, "wb") as fh: fh.write(SAMPLE_IMAGE_CONTENT) report = run_func_in_test(do, tmpdir=tmpdir) assert_attachment( get_last_attachment(report), "foobar.png", "some description", True, SAMPLE_IMAGE_CONTENT, make_file_reader(binary=True) ) def test_save_attachment_file(tmpdir): def do(): filename = osp.join(tmpdir.strpath, "somefile.txt") with open(filename, "w") as fh: fh.write("some other content") lcc.save_attachment_file(filename, "some other file") report = run_func_in_test(do, tmpdir=tmpdir.mkdir("report")) assert_attachment( get_last_attachment(report), "somefile.txt", "some other file", False, "some other content", make_file_reader() ) def test_save_image_file(tmpdir): def do(): lcc.save_image_file(SAMPLE_IMAGE_PATH, "some other file") report = run_func_in_test(do, tmpdir=tmpdir.mkdir("report")) assert_attachment( get_last_attachment(report), osp.basename(SAMPLE_IMAGE_PATH), "some other file", True, SAMPLE_IMAGE_CONTENT, make_file_reader(binary=True) ) def _test_save_attachment_content(tmpdir, file_name, file_content, file_reader): def do(): lcc.save_attachment_content(file_content, file_name) report = run_func_in_test(do, tmpdir=tmpdir) assert_attachment(get_last_attachment(report), file_name, file_name, False, file_content, file_reader) def test_save_attachment_text_ascii(tmpdir): _test_save_attachment_content(tmpdir, "foobar.txt", "foobar", make_file_reader()) def test_save_attachment_text_utf8(tmpdir): _test_save_attachment_content(tmpdir, "foobar.txt", u"éééçççààà", make_file_reader(encoding="utf-8")) def test_save_attachment_binary(tmpdir): _test_save_attachment_content(tmpdir, "foobar.png", SAMPLE_IMAGE_CONTENT, make_file_reader(binary=True)) def test_save_image_content(tmpdir): def do(): lcc.save_image_content(SAMPLE_IMAGE_CONTENT, "somefile.png", "some file") report = run_func_in_test(do, tmpdir=tmpdir) assert_attachment( get_last_attachment(report), "somefile.png", "some file", True, SAMPLE_IMAGE_CONTENT, make_file_reader(binary=True) ) def test_log_url(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): lcc.log_url("http://example.com", "example") report = run_suite_class(mysuite) test = get_last_test(report) step = test.get_steps()[0] assert step.get_logs()[0].description == "example" assert step.get_logs()[0].url == "http://example.com" def test_unicode(tmpdir): @lcc.suite("MySuite") class mysuite: @lcc.test("some test") def sometest(self): lcc.set_step(u"éééààà") check_that(u"éééààà", 1, equal_to(1)) lcc.log_info(u"éééààà") lcc.save_attachment_content("A" * 1024, u"somefileààà", u"éééààà") report = run_suite_class(mysuite, tmpdir=tmpdir) test = get_last_test(report) assert test.status == "passed" step = test.get_steps()[0] assert step.description == u"éééààà" assert u"éééààà" in step.get_logs()[0].description assert "1" in step.get_logs()[0].description assert step.get_logs()[1].message == u"éééààà" assert_attachment(step.get_logs()[2], u"somefileààà", u"éééààà", False, "A" * 1024, make_file_reader(encoding="utf8")) def test_setup_suite_success(): @lcc.suite("MySuite") class mysuite: def setup_suite(self): lcc.log_info("some log") @lcc.test("Some test") def sometest(self): pass report = run_suite_class(mysuite) setup = _get_suite_setup(report) assert setup.status == "passed" assert setup.start_time is not None assert setup.end_time is not None assert setup.get_steps()[0].get_logs()[0].message == "some log" assert setup.is_successful() def test_setup_suite_failure(): @lcc.suite("MySuite") class mysuite: def setup_suite(self): lcc.log_error("something bad happened") @lcc.test("Some test") def sometest(self): pass report = run_suite_class(mysuite) setup = _get_suite_setup(report) assert setup.status == "failed" assert setup.start_time is not None assert setup.end_time is not None assert setup.get_steps()[0].get_logs()[0].message == "something bad happened" assert not setup.is_successful() def test_setup_suite_without_content(): @lcc.suite("MySuite") class mysuite: def setup_suite(self): pass @lcc.test("Some test") def sometest(self): pass report = run_suite_class(mysuite) assert _get_suite_setup(report) is None def test_teardown_suite_success(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): pass def teardown_suite(self): lcc.log_info("some log") report = run_suite_class(mysuite) teardown = _get_suite_teardown(report) assert teardown.status == "passed" assert teardown.start_time is not None assert teardown.end_time is not None assert teardown.get_steps()[0].get_logs()[0].message == "some log" assert teardown.is_successful() def test_teardown_suite_failure(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): pass def teardown_suite(self): check_that("val", 1, equal_to(2)) report = run_suite_class(mysuite) teardown = _get_suite_teardown(report) assert teardown.status == "failed" assert teardown.start_time is not None assert teardown.end_time is not None assert teardown.get_steps()[0].get_logs()[0].is_successful is False assert not teardown.is_successful() def test_teardown_suite_without_content(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self): pass def teardown_suite(self): pass report = run_suite_class(mysuite) assert _get_suite_teardown(report) is None def test_setup_test_session_success(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self, fixt): pass @lcc.fixture(scope="session") def fixt(): lcc.log_info("some log") report = run_suite_class(mysuite, fixtures=[fixt]) setup = report.test_session_setup assert setup.status == "passed" assert setup.start_time is not None assert setup.end_time is not None assert setup.get_steps()[0].get_logs()[0].message == "some log" assert setup.is_successful() def test_setup_test_session_failure(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self, fixt): pass @lcc.fixture(scope="session") def fixt(): lcc.log_error("something bad happened") report = run_suite_class(mysuite, fixtures=[fixt]) setup = report.test_session_setup assert setup.status == "failed" assert setup.start_time is not None assert setup.end_time is not None assert setup.get_steps()[0].get_logs()[0].message == "something bad happened" assert not setup.is_successful() def test_setup_test_session_without_content(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self, fixt): pass @lcc.fixture(scope="session") def fixt(): pass report = run_suite_class(mysuite, fixtures=[fixt]) assert report.test_session_setup is None def test_teardown_test_session_success(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self, fixt): pass @lcc.fixture(scope="session") def fixt(): yield lcc.log_info("some log") report = run_suite_class(mysuite, fixtures=[fixt]) teardown = report.test_session_teardown assert teardown.status == "passed" assert teardown.start_time is not None assert teardown.end_time is not None assert teardown.get_steps()[0].get_logs()[0].message == "some log" assert teardown.is_successful() def test_teardown_test_session_failure(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self, fixt): pass @lcc.fixture(scope="session") def fixt(): yield check_that("val", 1, equal_to(2)) report = run_suite_class(mysuite, fixtures=[fixt]) teardown = report.test_session_teardown assert teardown.status == "failed" assert teardown.start_time is not None assert teardown.end_time is not None assert teardown.get_steps()[0].get_logs()[0].is_successful is False assert not teardown.is_successful() def test_teardown_test_session_without_content(): @lcc.suite("MySuite") class mysuite: @lcc.test("Some test") def sometest(self, fixt): pass @lcc.fixture(scope="session") def fixt(): yield report = run_suite_class(mysuite, fixtures=[fixt]) assert report.test_session_teardown is None def test_add_report_info(): @lcc.suite("Some suite") class mysuite: @lcc.test("Some test") def sometest(self): lcc.add_report_info("some info", "some data") report = run_suite_class(mysuite) assert report.info[-1] == ["some info", "some data"]

27.603666

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0.632086

3,221

24,098

4.519093

0.063645

0.03222

0.030228

0.032152

0.8018

0.762572

0.729321

0.691261

0.669964

0.653476

0

0.012425

0.238526

24,098

872

123

27.635321

0.780817

0.003942

0

0.683721

0

0.102151

0

0.235659

1

0.176744

false

0.065116

0.012403

0.00155

0.252713

0

null

0

1

0

1

0

null

0

1

0

5

40f56b6672d61b45315a677a55d834c92ed3b91e

110

py

Python

quand.py

gaoyan0629/ml

c1ad3a3a6bdbe75e5911e8946bdf73d6cf14c3c8

[ "Apache-2.0" ]

null

quand.py

gaoyan0629/ml

c1ad3a3a6bdbe75e5911e8946bdf73d6cf14c3c8

[ "Apache-2.0" ]

null

quand.py

gaoyan0629/ml

c1ad3a3a6bdbe75e5911e8946bdf73d6cf14c3c8

[ "Apache-2.0" ]

null

import quandl mydata = quandl.get("YAHOO/INDEX_DJI", start_date="2005-12-01", end_date="2005-12-05")

27.5

55

0.681818

18

110

4

0.777778

0.222222

0.277778

0

0.170213

0.145455

110

3

56

36.666667

0.595745

0

0.318182

0

1

0

false

0

0.333333

0

0.333333

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null

1

0

1

0

null

0

1

0

5

dc0e01e5c601a01f2950a7352ea2398fa5d1ff2e

285

py

Python

qtrader/agents/random.py

aaron8tang/qtrader

9bd50fd173c7b55707e91d75985055bbe8664548

[ "Apache-2.0" ]

381

2017-10-25T19:17:04.000Z

2021-03-02T08:46:53.000Z

qtrader/agents/random.py

362115815/qtrader

e5c1e175e19b20381f9140fb76c30ad5cb81f01c

[ "Apache-2.0" ]

3

2018-02-13T23:19:40.000Z

2018-12-03T22:50:58.000Z

qtrader/agents/random.py

362115815/qtrader

e5c1e175e19b20381f9140fb76c30ad5cb81f01c

[ "Apache-2.0" ]

145

2017-10-25T19:17:06.000Z

2021-02-15T04:54:08.000Z

import numpy as np from qtrader.agents.base import Agent class RandomAgent(Agent): """Random agent.""" _id = 'random' def __init__(self, action_space): self.action_space = action_space def act(self, observation): return self.action_space.sample()

17.8125

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0.673684

36

285

5.083333

0.611111

0.240437

0.245902

0

0.224561

285

15

42

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0.045614

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false

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0.25

0.125

0.875

0

null

1

0

null

0

1

0

1

0

5

9074a91f6d1cd93585f26530bb8637feb3d5a91f

109

py

Python

avatar/signals.py

davmlaw/django-avatar

a634433a273f2d24c0a476c73943dfaa59eb0fd6

[ "BSD-3-Clause" ]

null

avatar/signals.py

davmlaw/django-avatar

a634433a273f2d24c0a476c73943dfaa59eb0fd6

[ "BSD-3-Clause" ]

null

avatar/signals.py

davmlaw/django-avatar

a634433a273f2d24c0a476c73943dfaa59eb0fd6

[ "BSD-3-Clause" ]

null

import django.dispatch avatar_updated = django.dispatch.Signal() avatar_deleted = django.dispatch.Signal()

18.166667

41

0.807339

13

109

6.615385

0.538462

0.488372

0.465116

0

0.091743

109

5

42

21.8

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false

0

0.333333

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0.333333

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null

1

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1

0

null

0

1

0

5

90a87194ba14bd6a3d01f3dabd02bf63a4148a42

5,867

py

Python

models/.ipynb_checkpoints/model_architecture-checkpoint.py

punyajoy/Fear-speech-analysis

a20f0032eee0114aac04710a5961f395bf0e4d59

[ "MIT" ]

10

2021-02-07T19:41:01.000Z

2021-02-28T08:07:07.000Z

models/.ipynb_checkpoints/model_architecture-checkpoint.py

punyajoy/Fear-speech-analysis

a20f0032eee0114aac04710a5961f395bf0e4d59

[ "MIT" ]

1

2021-02-07T18:28:25.000Z

models/.ipynb_checkpoints/model_architecture-checkpoint.py

punyajoy/Fear-speech-analysis

a20f0032eee0114aac04710a5961f395bf0e4d59

[ "MIT" ]

2

2021-02-07T19:40:49.000Z

2021-02-20T17:08:01.000Z

#from transformers import BertForSequenceClassification,BertPreTrainedModel,RobertaPreTrainedModel,XLMRobertaForSequenceClassification from transformers.modeling_bert import * from transformers.modeling_roberta import * from transformers.modeling_xlm_roberta import * from torch import nn import torch from torch.nn import LSTM def select_transformer_model(type_of_model,path,params): if(type_of_model=='lstm_transformer'): if (path=='bert-base-multilingual-cased'): model = DocumentBERTLSTM.from_pretrained( path, # Use the 12-layer BERT model, with an uncased vocab. num_labels = 2, params=params ) elif (path=='xlm-roberta-base'): model = DocumentRobertaLSTM.from_pretrained( path, # Use the 12-layer BERT model, with an uncased vocab. num_labels = 2, # The number of output labels--2 for binary classification # You can increase this for multi-class tasks. params=params ) return model class DocumentBERTLSTM(BertPreTrainedModel): """ BERT output over document in LSTM """ def __init__(self,config,params): super(DocumentBERTLSTM, self).__init__(config) self.bert = BertModel(config) print(params) self.num_labels = config.num_labels self.batch_size= params['batch_size'] self.weights=params['weights'] self.bert_batch_size=params['max_sentences_per_doc'] self.dropout = nn.Dropout(p=config.hidden_dropout_prob) self.lstm = LSTM(config.hidden_size,config.hidden_size) self.classifier = nn.Sequential( nn.Dropout(p=config.hidden_dropout_prob), nn.Linear(config.hidden_size, config.num_labels), nn.Tanh() ) #input_ids, token_type_ids, attention_masks def forward(self, document_batch, labels= None,device='cuda'): #contains all BERT sequences #bert should output a (batch_size, num_sequences, bert_hidden_size) bert_output = torch.zeros(size=(document_batch.shape[0], min(document_batch.shape[1],self.bert_batch_size), self.bert.config.hidden_size), dtype=torch.float, device=device) #only pass through bert_batch_size numbers of inputs into bert. #this means that we are possibly cutting off the last part of documents. for doc_id in range(document_batch.shape[0]): bert_output[doc_id][:self.bert_batch_size] = self.dropout(self.bert(document_batch[doc_id][:self.bert_batch_size,0], token_type_ids=document_batch[doc_id][:self.bert_batch_size,1], attention_mask=document_batch[doc_id][:self.bert_batch_size,2])[1]) output, (_, _) = self.lstm(bert_output.permute(1,0,2)) last_layer = output[-1] prediction = self.classifier(last_layer) assert prediction.shape[0] == document_batch.shape[0] if labels is not None: loss_funct = CrossEntropyLoss(weight=torch.tensor(self.weights).to(device)) loss_logits = loss_funct(prediction.view(-1, self.num_labels), labels.view(-1)) loss= loss_logits output = [loss, output] return output class DocumentRobertaLSTM(RobertaPreTrainedModel): """ Roberta output over document in LSTM """ def __init__(self,config,params): super().__init__(config) self.num_labels = config.num_labels self.roberta= RobertaModel(config) self.batch_size= params['batch_size'] self.weights=params['weights'] self.bert_batch_size=params['max_sentences_per_doc'] self.dropout = nn.Dropout(p=config.hidden_dropout_prob) self.lstm = LSTM(config.hidden_size,config.hidden_size) self.classifier = nn.Sequential( nn.Dropout(p=config.hidden_dropout_prob), nn.Linear(config.hidden_size, config.num_labels), nn.Tanh() ) self.init_weights() #input_ids, token_type_ids, attention_masks def forward(self, document_batch,labels= None,device='cuda'): #contains all BERT sequences #bert should output a (batch_size, num_sequences, bert_hidden_size) bert_output = torch.ones(size=(document_batch.shape[0], min(document_batch.shape[1],self.bert_batch_size), self.roberta.config.hidden_size), dtype=torch.float, device=device) #only pass through bert_batch_size numbers of inputs into bert. #this means that we are possibly cutting off the last part of documents. print(document_batch.shape) for doc_id in range(document_batch.shape[0]): temp=self.roberta(document_batch[doc_id][:self.bert_batch_size,0], token_type_ids=document_batch[doc_id][:self.bert_batch_size,1], attention_mask=document_batch[doc_id][:self.bert_batch_size,2]) print(temp.shape) bert_output[doc_id][:self.bert_batch_size] = self.dropout(temp[1]) output, (_, _) = self.lstm(bert_output.permute(1,0,2)) last_layer = output[-1] prediction = self.classifier(last_layer) assert prediction.shape[0] == document_batch.shape[0] if labels is not None: loss_funct = CrossEntropyLoss(weight=torch.tensor(self.weights).to(device)) loss_logits = loss_funct(prediction.view(-1, self.num_labels), labels.view(-1)) loss= loss_logits outputs = (loss,) + outputs return outputs

42.208633

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0.633373

703

5,867

5.051209

0.192034

0.05069

0.051253

0.057449

0.73782

0.720924

0.701774

0

0.008661

0.27186

5,867

139

149

42.208633

0.822566

0.163968

0

0.565217

0

0.029624

0.0144

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0.021739

1

0.054348

false

0

0.065217

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0.173913

0.032609

0

null

0

1

0

null

0

5

90daff38b261653bbebc6b1dc07df60be513b782

13

py

Python

Module00/myfirst-python.py

geiyer/cis189-python

2b85ff66277b337aab9f6a7a6fa1c86dccf0178c

[ "MIT" ]

2

2021-02-24T00:32:36.000Z

2021-04-21T00:09:36.000Z

Module00/myfirst-python.py

geiyer/cis189-python

2b85ff66277b337aab9f6a7a6fa1c86dccf0178c

[ "MIT" ]

null

Module00/myfirst-python.py

geiyer/cis189-python

2b85ff66277b337aab9f6a7a6fa1c86dccf0178c

[ "MIT" ]

2

2021-03-30T23:37:49.000Z

2021-04-21T00:08:32.000Z

print('gopi')

13

0.692308

2

13

4.5

1

0

13

1

13

0.692308

0

0.285714

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

90eac991fed069567cc92ab449b4869d566e3e75

48

py

Python

converty/image_convert/__init__.py

sharmas1ddharth/converty

eb32dfc1882a7c20d57916287c10e154adbe67d9

[ "MIT" ]

null

converty/image_convert/__init__.py

sharmas1ddharth/converty

eb32dfc1882a7c20d57916287c10e154adbe67d9

[ "MIT" ]

null

converty/image_convert/__init__.py

sharmas1ddharth/converty

eb32dfc1882a7c20d57916287c10e154adbe67d9

[ "MIT" ]

null

#from img_convert import jpg_to_png, png_to_jpg

24

47

0.854167

10

48

3.6

0.7

0

0.104167

48

1

48

0.837209

0.958333

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

2903d5d69b9135292976689b8bee6d75b64c1f3f

10,412

py

Python

spytest/tests/routing/BGP/bgp4nodelib.py

mykolaf/sonic-mgmt

de77268526173c5e3a345f3f3703b56eb40c5eed

[ "Apache-2.0" ]

1

2021-09-15T17:09:13.000Z

spytest/tests/routing/BGP/bgp4nodelib.py

mykolaf/sonic-mgmt

de77268526173c5e3a345f3f3703b56eb40c5eed

[ "Apache-2.0" ]

1

2020-02-05T16:51:53.000Z

spytest/tests/routing/BGP/bgp4nodelib.py

mykolaf/sonic-mgmt

de77268526173c5e3a345f3f3703b56eb40c5eed

[ "Apache-2.0" ]

null

#BGP 4 node linear topology from spytest import st from spytest.dicts import SpyTestDict import apis.routing.ip as ipapi import apis.routing.bgp as bgpapi import utilities.common as utils import BGP.bgplib as bgplib global topo topo = SpyTestDict() def l3_ipv4v6_address_config_unconfig(config='yes', vrf_type='all', config_type='all'): """ :param config: :param vrf_type: :param config_type: :return: """ st.banner("{}Configuring IP Addresses between linear topology nodes.".format('Un' if config != 'yes' else '')) tb_vars = st.get_testbed_vars() st.log("TestBed Vars => {}\n".format(tb_vars)) topo['dut_list'] = tb_vars.dut_list st.log("topo dut_list {}".format(topo['dut_list'])) config = 'add' if config == 'yes' else 'remove' ipv4_adr = '11' ipv6_adr = '67fe' result = True k = 1 i=0 while i < (len(topo['dut_list']) - 1): dut = topo['dut_list'][i] peer_dut = topo['dut_list'][i+1] link = 1 for local, partner, remote in st.get_dut_links(dut, peer_dut): if config_type == 'ipv4' or config_type == 'all': ipaddr1 = "{}.{}.0.1".format(ipv4_adr, k) ipaddr2 = "{}.{}.0.2".format(ipv4_adr, k) topo['D{}D{}P{}'.format(i+1,i+2,link)] = local topo['D{}D{}P{}_ipv4'.format(i+1,i+2,link)] = ipaddr1 topo['D{}D{}P{}_neigh_ipv4'.format(i+1,i+2,link)] = ipaddr2 topo['D{}D{}P{}'.format(i+2,i+1,link)] = remote topo['D{}D{}P{}_ipv4'.format(i+2,i+1,link)] = ipaddr2 topo['D{}D{}P{}_neigh_ipv4'.format(i+2,i+1,link)] = ipaddr1 [out, exceptions] = utils.exec_all(bgplib.fast_start,[[ipapi.config_ip_addr_interface, dut, local, ipaddr1, '24', "ipv4", config],[ipapi.config_ip_addr_interface, peer_dut, remote, ipaddr2,'24', "ipv4", config]]) st.log([out, exceptions]) if config_type == 'ipv6' or config_type == 'all': ip6addr1 = "{}:{}::1".format(ipv6_adr, k) ip6addr2 = "{}:{}::2".format(ipv6_adr, k) topo['D{}D{}P{}'.format(i+1,i+2,link)] = local topo['D{}D{}P{}_ipv6'.format(i+1,i+2,link)] = ip6addr1 topo['D{}D{}P{}_neigh_ipv6'.format(i+1,i+2,link)] = ip6addr2 topo['D{}D{}P{}'.format(i+2,i+1,link)] = remote topo['D{}D{}P{}_ipv6'.format(i+2,i+1,link)] = ip6addr2 topo['D{}D{}P{}_neigh_ipv6'.format(i+2,i+1,link)] = ip6addr1 [out, exceptions] = utils.exec_all(bgplib.fast_start,[[ipapi.config_ip_addr_interface, dut, local, ip6addr1, '64', "ipv6", config],[ipapi.config_ip_addr_interface, peer_dut, remote, ip6addr2,'64', "ipv6", config]]) st.log([out, exceptions]) link += 1 break k += 1 i += 1 return result def l3tc_vrfipv4v6_address_ping_test(vrf_type='all', config_type='all', ping_count=3): """ :param vrf_type: :param config_type: :param ping_count: :return: """ st.banner("Ping Checking between Spine and Leaf nodes.") ipv4_adr = '11' ipv6_adr = '67fe' result = True k = 1 i=0 while i < (len(topo['dut_list']) - 1): dut = topo['dut_list'][i] peer_dut = topo['dut_list'][i+1] link = 1 for local, partner, remote in st.get_dut_links(dut, peer_dut): if config_type == 'ipv4' or config_type == 'all': ipaddr1 = "{}.{}.0.1".format(ipv4_adr, k) ipaddr2 = "{}.{}.0.2".format(ipv4_adr, k) if not ipapi.ping(dut, ipaddr2, family='ipv4', count=ping_count): st.log("{}- {} configured on {} - ping failed".format(dut, local, ipaddr2)) result = False if config_type == 'ipv6' or config_type == 'all': ip6addr1 = "{}:{}::1".format(ipv6_adr, k) ip6addr2 = "{}:{}::2".format(ipv6_adr, k) if not ipapi.ping(dut, ip6addr2, family='ipv6', count=ping_count): st.log("{}- {} configured on {} - ping v6 failed".format(dut, local, ip6addr2)) result = False link += 1 break k += 1 i += 1 return result def l3tc_vrfipv4v6_confed_bgp_config(config='yes', vrf_type='all', config_type='all'): """ :param config: :param vrf_type: :param config_type: :return: """ st.banner("{}Configuring BGP with 4-node confederation topology.".format('Un' if config != 'yes' else '')) #Confedration topo: #DUT1 in sub-AS1 (AS1 = 24) #DUT2, DUT3, DUT 4 in sub-AS2 (AS2 = 35) #IBGP AS = 100 config = 'add' if config == 'yes' else 'remove' leftconfed_as = 24 rightconfed_as = 35 iBGP_as = 100 topo['D1_as'] = 24 topo['D2_as'] = 35 topo['D3_as'] = 35 topo['D4_as'] = 35 result = True if config == 'add': if config_type == 'ipv4' or config_type == 'all': #Confederation config for DUT1 dut = topo['dut_list'][0] neighbor = topo['D1D2P1_neigh_ipv4'] bgpapi.config_bgp(dut, local_as = leftconfed_as, config = 'yes', conf_peers = rightconfed_as, conf_identf = iBGP_as, remote_as = rightconfed_as, config_type_list = ["neighbor"], neighbor = neighbor) #Confederation config for DUT2 dut = topo['dut_list'][1] neighbor = topo['D2D3P1_neigh_ipv4'] bgpapi.config_bgp(dut, local_as = rightconfed_as, config = 'yes', conf_peers = leftconfed_as, conf_identf = iBGP_as, remote_as = rightconfed_as, config_type_list = ["neighbor"], neighbor = neighbor) bgpapi.create_bgp_neighbor(dut, rightconfed_as, topo['D2D1P1_neigh_ipv4'], leftconfed_as) #Confederation config for DUT3 dut = topo['dut_list'][2] neighbor = topo['D3D4P1_neigh_ipv4'] bgpapi.config_bgp(dut, local_as = rightconfed_as, config = 'yes', conf_peers = leftconfed_as, conf_identf = iBGP_as, remote_as = rightconfed_as, config_type_list = ["neighbor"], neighbor = neighbor) bgpapi.create_bgp_neighbor(dut, rightconfed_as, topo['D3D2P1_neigh_ipv4'], rightconfed_as) #Confederation config for DUT4 dut = topo['dut_list'][3] neighbor = topo['D4D3P1_neigh_ipv4'] bgpapi.config_bgp(dut, local_as = rightconfed_as, config = 'yes', conf_peers = leftconfed_as, conf_identf = iBGP_as, remote_as = rightconfed_as, config_type_list = ["neighbor"], neighbor = neighbor) if config_type == 'ipv6' or config_type == 'all': #Confederation config for DUT1 dut = topo['dut_list'][0] neighbor = topo['D1D2P1_neigh_ipv6'] bgpapi.config_bgp(dut, local_as = leftconfed_as, config = 'yes', addr_family ='ipv6', conf_peers = rightconfed_as, conf_identf = iBGP_as, remote_as = rightconfed_as, config_type_list = ["neighbor", "activate"], neighbor = neighbor) #Confederation config for DUT2 dut = topo['dut_list'][1] neighbor = topo['D2D3P1_neigh_ipv6'] bgpapi.config_bgp(dut, local_as = rightconfed_as, config = 'yes', addr_family ='ipv6', conf_peers = leftconfed_as, conf_identf = iBGP_as, remote_as = rightconfed_as, config_type_list = ["neighbor", "activate"], neighbor = neighbor) bgpapi.create_bgp_neighbor(dut, rightconfed_as, topo['D2D1P1_neigh_ipv6'], leftconfed_as, family="ipv6") #Confederation config for DUT3 dut = topo['dut_list'][2] neighbor = topo['D3D4P1_neigh_ipv6'] bgpapi.config_bgp(dut, local_as = rightconfed_as, config = 'yes', addr_family ='ipv6', conf_peers = leftconfed_as, conf_identf = iBGP_as, remote_as = rightconfed_as, config_type_list = ["neighbor", "activate"], neighbor = neighbor) bgpapi.create_bgp_neighbor(dut, rightconfed_as, topo['D3D2P1_neigh_ipv6'], rightconfed_as, family="ipv6") #Confederation config for DUT4 dut = topo['dut_list'][3] neighbor = topo['D4D3P1_neigh_ipv6'] bgpapi.config_bgp(dut, local_as = rightconfed_as, config = 'yes', addr_family ='ipv6', conf_peers = leftconfed_as, conf_identf = iBGP_as, remote_as = rightconfed_as, config_type_list = ["neighbor", "activate"], neighbor = neighbor) else: bgpapi.cleanup_router_bgp(topo['dut_list']) return result def l3tc_vrfipv4v6_address_confed_bgp_check(config_type='all'): st.banner("BGP Neighbor Checking in confederation topology") result = True if config_type == 'ipv4' or config_type == 'all': #Check link between DUT 1----DUT2 and DUT2----DUT3 neigh_list = [] neigh_list.append(topo['D2D3P1_neigh_ipv4']) neigh_list.append(topo['D2D1P1_neigh_ipv4']) neigh_list = list(set(neigh_list)) if not bgpapi.verify_bgp_summary(topo['dut_list'][1], family='ipv4', neighbor=neigh_list, state='Established'): st.log("{} - Neighbor {} is failed to Establish".format(topo['dut_list'][1], neigh_list)) result = False #Check link between DUT3----DUT4 if not bgpapi.verify_bgp_summary(topo['dut_list'][2], family='ipv4', neighbor=topo['D3D4P1_neigh_ipv4'], state='Established'): st.log("{} - Neighbor {} is failed to Establish".format(topo['dut_list'][2], topo['D3D4P1_neigh_ipv4'])) result = False if config_type == 'ipv6' or config_type == 'all': #Check link between DUT 1----DUT2 and DUT2----DUT3 neigh_list = [] neigh_list.append(topo['D2D3P1_neigh_ipv6']) neigh_list.append(topo['D2D1P1_neigh_ipv6']) neigh_list = list(set(neigh_list)) if not bgpapi.verify_bgp_summary(topo['dut_list'][1], family='ipv6', neighbor=neigh_list, state='Established'): st.log("{} - Neighbor {} is failed to Establish".format(topo['dut_list'][1], neigh_list)) result = False #Check link between DUT3----DUT4 if not bgpapi.verify_bgp_summary(topo['dut_list'][2], family='ipv6', neighbor=topo['D3D4P1_neigh_ipv6'], state='Established'): st.log("{} - Neighbor {} is failed to Establish".format(topo['dut_list'][2], topo['D3D4P1_neigh_ipv6'])) result = False return result def get_confed_topology_info(): return topo

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2911616b731165fcdfcdc35a01337dbcf1f0bef8

72,048

py

Python

google/ads/google_ads/v5/proto/resources/ad_group_criterion_pb2.py

arammaliachi/google-ads-python

a4fe89567bd43eb784410523a6306b5d1dd9ee67

[ "Apache-2.0" ]

1

2021-04-09T04:28:47.000Z

google/ads/google_ads/v5/proto/resources/ad_group_criterion_pb2.py

arammaliachi/google-ads-python

a4fe89567bd43eb784410523a6306b5d1dd9ee67

[ "Apache-2.0" ]

null

google/ads/google_ads/v5/proto/resources/ad_group_criterion_pb2.py

arammaliachi/google-ads-python

a4fe89567bd43eb784410523a6306b5d1dd9ee67

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: google/ads/googleads_v5/proto/resources/ad_group_criterion.proto from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from google.ads.google_ads.v5.proto.common import criteria_pb2 as google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2 from google.ads.google_ads.v5.proto.common import custom_parameter_pb2 as google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_custom__parameter__pb2 from google.ads.google_ads.v5.proto.enums import ad_group_criterion_approval_status_pb2 as google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_ad__group__criterion__approval__status__pb2 from google.ads.google_ads.v5.proto.enums import ad_group_criterion_status_pb2 as google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_ad__group__criterion__status__pb2 from google.ads.google_ads.v5.proto.enums import bidding_source_pb2 as google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_bidding__source__pb2 from google.ads.google_ads.v5.proto.enums import criterion_system_serving_status_pb2 as google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_criterion__system__serving__status__pb2 from google.ads.google_ads.v5.proto.enums import criterion_type_pb2 as google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_criterion__type__pb2 from google.ads.google_ads.v5.proto.enums import quality_score_bucket_pb2 as google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_quality__score__bucket__pb2 from google.api import field_behavior_pb2 as google_dot_api_dot_field__behavior__pb2 from google.api import resource_pb2 as google_dot_api_dot_resource__pb2 from google.api import annotations_pb2 as google_dot_api_dot_annotations__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='google/ads/googleads_v5/proto/resources/ad_group_criterion.proto', package='google.ads.googleads.v5.resources', syntax='proto3', serialized_options=b'\n%com.google.ads.googleads.v5.resourcesB\025AdGroupCriterionProtoP\001ZJgoogle.golang.org/genproto/googleapis/ads/googleads/v5/resources;resources\242\002\003GAA\252\002!Google.Ads.GoogleAds.V5.Resources\312\002!Google\\Ads\\GoogleAds\\V5\\Resources\352\002%Google::Ads::GoogleAds::V5::Resources', create_key=_descriptor._internal_create_key, serialized_pb=b'\n@google/ads/googleads_v5/proto/resources/ad_group_criterion.proto\x12!google.ads.googleads.v5.resources\x1a\x33google/ads/googleads_v5/proto/common/criteria.proto\x1a;google/ads/googleads_v5/proto/common/custom_parameter.proto\x1aLgoogle/ads/googleads_v5/proto/enums/ad_group_criterion_approval_status.proto\x1a\x43google/ads/googleads_v5/proto/enums/ad_group_criterion_status.proto\x1a\x38google/ads/googleads_v5/proto/enums/bidding_source.proto\x1aIgoogle/ads/googleads_v5/proto/enums/criterion_system_serving_status.proto\x1a\x38google/ads/googleads_v5/proto/enums/criterion_type.proto\x1a>google/ads/googleads_v5/proto/enums/quality_score_bucket.proto\x1a\x1fgoogle/api/field_behavior.proto\x1a\x19google/api/resource.proto\x1a\x1cgoogle/api/annotations.proto\"\xab#\n\x10\x41\x64GroupCriterion\x12H\n\rresource_name\x18\x01 \x01(\tB1\xe0\x41\x05\xfa\x41+\n)googleads.googleapis.com/AdGroupCriterion\x12\x1e\n\x0c\x63riterion_id\x18\x38 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, dependencies=[google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_custom__parameter__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_ad__group__criterion__approval__status__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_ad__group__criterion__status__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_bidding__source__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_criterion__system__serving__status__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_criterion__type__pb2.DESCRIPTOR,google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_quality__score__bucket__pb2.DESCRIPTOR,google_dot_api_dot_field__behavior__pb2.DESCRIPTOR,google_dot_api_dot_resource__pb2.DESCRIPTOR,google_dot_api_dot_annotations__pb2.DESCRIPTOR,]) _ADGROUPCRITERION_QUALITYINFO = _descriptor.Descriptor( name='QualityInfo', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.QualityInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='quality_score', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.QualityInfo.quality_score', index=0, number=5, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='creative_quality_score', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.QualityInfo.creative_quality_score', index=1, number=2, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='post_click_quality_score', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.QualityInfo.post_click_quality_score', index=2, number=3, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='search_predicted_ctr', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.QualityInfo.search_predicted_ctr', index=3, number=4, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='_quality_score', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.QualityInfo._quality_score', index=0, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), ], serialized_start=3954, serialized_end=4351, ) _ADGROUPCRITERION_POSITIONESTIMATES = _descriptor.Descriptor( name='PositionEstimates', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='first_page_cpc_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates.first_page_cpc_micros', index=0, number=6, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='first_position_cpc_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates.first_position_cpc_micros', index=1, number=7, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='top_of_page_cpc_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates.top_of_page_cpc_micros', index=2, number=8, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='estimated_add_clicks_at_first_position_cpc', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates.estimated_add_clicks_at_first_position_cpc', index=3, number=9, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='estimated_add_cost_at_first_position_cpc', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates.estimated_add_cost_at_first_position_cpc', index=4, number=10, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='_first_page_cpc_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates._first_page_cpc_micros', index=0, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_first_position_cpc_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates._first_position_cpc_micros', index=1, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_top_of_page_cpc_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates._top_of_page_cpc_micros', index=2, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_estimated_add_clicks_at_first_position_cpc', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates._estimated_add_clicks_at_first_position_cpc', index=3, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_estimated_add_cost_at_first_position_cpc', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates._estimated_add_cost_at_first_position_cpc', index=4, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), ], serialized_start=4354, serialized_end=4798, ) _ADGROUPCRITERION = _descriptor.Descriptor( name='AdGroupCriterion', full_name='google.ads.googleads.v5.resources.AdGroupCriterion', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='resource_name', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.resource_name', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005\372A+\n)googleads.googleapis.com/AdGroupCriterion', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='criterion_id', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.criterion_id', index=1, number=56, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='status', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.status', index=2, number=3, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='quality_info', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.quality_info', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='ad_group', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.ad_group', index=4, number=57, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005\372A\"\n googleads.googleapis.com/AdGroup', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='type', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.type', index=5, number=25, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='negative', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.negative', index=6, number=58, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='system_serving_status', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.system_serving_status', index=7, number=52, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='approval_status', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.approval_status', index=8, number=53, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='disapproval_reasons', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.disapproval_reasons', index=9, number=59, type=9, cpp_type=9, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='bid_modifier', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.bid_modifier', index=10, number=61, type=1, cpp_type=5, label=1, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='cpc_bid_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.cpc_bid_micros', index=11, number=62, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='cpm_bid_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.cpm_bid_micros', index=12, number=63, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='cpv_bid_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.cpv_bid_micros', index=13, number=64, type=3, cpp_type=2, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='percent_cpc_bid_micros', 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is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='effective_cpc_bid_source', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.effective_cpc_bid_source', index=19, number=21, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='effective_cpm_bid_source', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.effective_cpm_bid_source', index=20, number=22, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='effective_cpv_bid_source', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.effective_cpv_bid_source', index=21, number=23, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='effective_percent_cpc_bid_source', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.effective_percent_cpc_bid_source', index=22, number=35, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='position_estimates', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.position_estimates', index=23, number=10, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\003', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='final_urls', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.final_urls', index=24, number=70, type=9, cpp_type=9, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='final_mobile_urls', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.final_mobile_urls', index=25, number=71, type=9, cpp_type=9, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='final_url_suffix', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.final_url_suffix', index=26, number=72, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='tracking_url_template', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.tracking_url_template', index=27, number=73, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='url_custom_parameters', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.url_custom_parameters', index=28, number=14, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='keyword', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.keyword', index=29, number=27, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='placement', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.placement', index=30, number=28, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='mobile_app_category', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.mobile_app_category', index=31, number=29, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='mobile_application', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.mobile_application', index=32, number=30, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='listing_group', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.listing_group', index=33, number=32, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='age_range', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.age_range', index=34, number=36, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='gender', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.gender', index=35, number=37, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='income_range', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.income_range', index=36, number=38, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='parental_status', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.parental_status', index=37, number=39, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='user_list', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.user_list', index=38, number=42, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='youtube_video', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.youtube_video', index=39, number=40, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='youtube_channel', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.youtube_channel', index=40, number=41, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='topic', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.topic', index=41, number=43, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='user_interest', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.user_interest', index=42, number=45, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='webpage', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.webpage', index=43, number=46, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='app_payment_model', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.app_payment_model', index=44, number=47, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='custom_affinity', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.custom_affinity', index=45, number=48, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='custom_intent', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.custom_intent', index=46, number=49, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=b'\340A\005', file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[_ADGROUPCRITERION_QUALITYINFO, _ADGROUPCRITERION_POSITIONESTIMATES, ], enum_types=[ ], serialized_options=b'\352Af\n)googleads.googleapis.com/AdGroupCriterion\0229customers/{customer}/adGroupCriteria/{ad_group_criterion}', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ _descriptor.OneofDescriptor( name='criterion', full_name='google.ads.googleads.v5.resources.AdGroupCriterion.criterion', index=0, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_criterion_id', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._criterion_id', index=1, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_ad_group', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._ad_group', index=2, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_negative', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._negative', index=3, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_bid_modifier', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._bid_modifier', index=4, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_cpc_bid_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._cpc_bid_micros', index=5, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_cpm_bid_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._cpm_bid_micros', index=6, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_cpv_bid_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._cpv_bid_micros', index=7, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_percent_cpc_bid_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._percent_cpc_bid_micros', index=8, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_effective_cpc_bid_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._effective_cpc_bid_micros', index=9, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_effective_cpm_bid_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._effective_cpm_bid_micros', index=10, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_effective_cpv_bid_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._effective_cpv_bid_micros', index=11, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_effective_percent_cpc_bid_micros', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._effective_percent_cpc_bid_micros', index=12, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_final_url_suffix', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._final_url_suffix', index=13, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), _descriptor.OneofDescriptor( name='_tracking_url_template', full_name='google.ads.googleads.v5.resources.AdGroupCriterion._tracking_url_template', index=14, containing_type=None, create_key=_descriptor._internal_create_key, fields=[]), ], serialized_start=710, serialized_end=5233, ) _ADGROUPCRITERION_QUALITYINFO.fields_by_name['creative_quality_score'].enum_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_quality__score__bucket__pb2._QUALITYSCOREBUCKETENUM_QUALITYSCOREBUCKET _ADGROUPCRITERION_QUALITYINFO.fields_by_name['post_click_quality_score'].enum_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_quality__score__bucket__pb2._QUALITYSCOREBUCKETENUM_QUALITYSCOREBUCKET _ADGROUPCRITERION_QUALITYINFO.fields_by_name['search_predicted_ctr'].enum_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_quality__score__bucket__pb2._QUALITYSCOREBUCKETENUM_QUALITYSCOREBUCKET _ADGROUPCRITERION_QUALITYINFO.containing_type = _ADGROUPCRITERION _ADGROUPCRITERION_QUALITYINFO.oneofs_by_name['_quality_score'].fields.append( _ADGROUPCRITERION_QUALITYINFO.fields_by_name['quality_score']) _ADGROUPCRITERION_QUALITYINFO.fields_by_name['quality_score'].containing_oneof = _ADGROUPCRITERION_QUALITYINFO.oneofs_by_name['_quality_score'] _ADGROUPCRITERION_POSITIONESTIMATES.containing_type = _ADGROUPCRITERION _ADGROUPCRITERION_POSITIONESTIMATES.oneofs_by_name['_first_page_cpc_micros'].fields.append( _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['first_page_cpc_micros']) _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['first_page_cpc_micros'].containing_oneof = _ADGROUPCRITERION_POSITIONESTIMATES.oneofs_by_name['_first_page_cpc_micros'] _ADGROUPCRITERION_POSITIONESTIMATES.oneofs_by_name['_first_position_cpc_micros'].fields.append( _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['first_position_cpc_micros']) _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['first_position_cpc_micros'].containing_oneof = _ADGROUPCRITERION_POSITIONESTIMATES.oneofs_by_name['_first_position_cpc_micros'] _ADGROUPCRITERION_POSITIONESTIMATES.oneofs_by_name['_top_of_page_cpc_micros'].fields.append( _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['top_of_page_cpc_micros']) _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['top_of_page_cpc_micros'].containing_oneof = _ADGROUPCRITERION_POSITIONESTIMATES.oneofs_by_name['_top_of_page_cpc_micros'] _ADGROUPCRITERION_POSITIONESTIMATES.oneofs_by_name['_estimated_add_clicks_at_first_position_cpc'].fields.append( _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['estimated_add_clicks_at_first_position_cpc']) _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['estimated_add_clicks_at_first_position_cpc'].containing_oneof = _ADGROUPCRITERION_POSITIONESTIMATES.oneofs_by_name['_estimated_add_clicks_at_first_position_cpc'] _ADGROUPCRITERION_POSITIONESTIMATES.oneofs_by_name['_estimated_add_cost_at_first_position_cpc'].fields.append( _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['estimated_add_cost_at_first_position_cpc']) _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['estimated_add_cost_at_first_position_cpc'].containing_oneof = _ADGROUPCRITERION_POSITIONESTIMATES.oneofs_by_name['_estimated_add_cost_at_first_position_cpc'] _ADGROUPCRITERION.fields_by_name['status'].enum_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_ad__group__criterion__status__pb2._ADGROUPCRITERIONSTATUSENUM_ADGROUPCRITERIONSTATUS _ADGROUPCRITERION.fields_by_name['quality_info'].message_type = _ADGROUPCRITERION_QUALITYINFO _ADGROUPCRITERION.fields_by_name['type'].enum_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_criterion__type__pb2._CRITERIONTYPEENUM_CRITERIONTYPE _ADGROUPCRITERION.fields_by_name['system_serving_status'].enum_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_criterion__system__serving__status__pb2._CRITERIONSYSTEMSERVINGSTATUSENUM_CRITERIONSYSTEMSERVINGSTATUS _ADGROUPCRITERION.fields_by_name['approval_status'].enum_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_ad__group__criterion__approval__status__pb2._ADGROUPCRITERIONAPPROVALSTATUSENUM_ADGROUPCRITERIONAPPROVALSTATUS _ADGROUPCRITERION.fields_by_name['effective_cpc_bid_source'].enum_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_bidding__source__pb2._BIDDINGSOURCEENUM_BIDDINGSOURCE _ADGROUPCRITERION.fields_by_name['effective_cpm_bid_source'].enum_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_bidding__source__pb2._BIDDINGSOURCEENUM_BIDDINGSOURCE _ADGROUPCRITERION.fields_by_name['effective_cpv_bid_source'].enum_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_bidding__source__pb2._BIDDINGSOURCEENUM_BIDDINGSOURCE _ADGROUPCRITERION.fields_by_name['effective_percent_cpc_bid_source'].enum_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_enums_dot_bidding__source__pb2._BIDDINGSOURCEENUM_BIDDINGSOURCE _ADGROUPCRITERION.fields_by_name['position_estimates'].message_type = _ADGROUPCRITERION_POSITIONESTIMATES _ADGROUPCRITERION.fields_by_name['url_custom_parameters'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_custom__parameter__pb2._CUSTOMPARAMETER _ADGROUPCRITERION.fields_by_name['keyword'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._KEYWORDINFO _ADGROUPCRITERION.fields_by_name['placement'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._PLACEMENTINFO _ADGROUPCRITERION.fields_by_name['mobile_app_category'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._MOBILEAPPCATEGORYINFO _ADGROUPCRITERION.fields_by_name['mobile_application'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._MOBILEAPPLICATIONINFO _ADGROUPCRITERION.fields_by_name['listing_group'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._LISTINGGROUPINFO _ADGROUPCRITERION.fields_by_name['age_range'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._AGERANGEINFO _ADGROUPCRITERION.fields_by_name['gender'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._GENDERINFO _ADGROUPCRITERION.fields_by_name['income_range'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._INCOMERANGEINFO _ADGROUPCRITERION.fields_by_name['parental_status'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._PARENTALSTATUSINFO _ADGROUPCRITERION.fields_by_name['user_list'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._USERLISTINFO _ADGROUPCRITERION.fields_by_name['youtube_video'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._YOUTUBEVIDEOINFO _ADGROUPCRITERION.fields_by_name['youtube_channel'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._YOUTUBECHANNELINFO _ADGROUPCRITERION.fields_by_name['topic'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._TOPICINFO _ADGROUPCRITERION.fields_by_name['user_interest'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._USERINTERESTINFO _ADGROUPCRITERION.fields_by_name['webpage'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._WEBPAGEINFO _ADGROUPCRITERION.fields_by_name['app_payment_model'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._APPPAYMENTMODELINFO _ADGROUPCRITERION.fields_by_name['custom_affinity'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._CUSTOMAFFINITYINFO _ADGROUPCRITERION.fields_by_name['custom_intent'].message_type = google_dot_ads_dot_googleads__v5_dot_proto_dot_common_dot_criteria__pb2._CUSTOMINTENTINFO _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['keyword']) _ADGROUPCRITERION.fields_by_name['keyword'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['placement']) _ADGROUPCRITERION.fields_by_name['placement'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['mobile_app_category']) _ADGROUPCRITERION.fields_by_name['mobile_app_category'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['mobile_application']) _ADGROUPCRITERION.fields_by_name['mobile_application'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['listing_group']) _ADGROUPCRITERION.fields_by_name['listing_group'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['age_range']) _ADGROUPCRITERION.fields_by_name['age_range'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['gender']) _ADGROUPCRITERION.fields_by_name['gender'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['income_range']) _ADGROUPCRITERION.fields_by_name['income_range'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['parental_status']) _ADGROUPCRITERION.fields_by_name['parental_status'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['user_list']) _ADGROUPCRITERION.fields_by_name['user_list'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['youtube_video']) _ADGROUPCRITERION.fields_by_name['youtube_video'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['youtube_channel']) _ADGROUPCRITERION.fields_by_name['youtube_channel'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['topic']) _ADGROUPCRITERION.fields_by_name['topic'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['user_interest']) _ADGROUPCRITERION.fields_by_name['user_interest'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['webpage']) _ADGROUPCRITERION.fields_by_name['webpage'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['app_payment_model']) _ADGROUPCRITERION.fields_by_name['app_payment_model'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['custom_affinity']) _ADGROUPCRITERION.fields_by_name['custom_affinity'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['criterion'].fields.append( _ADGROUPCRITERION.fields_by_name['custom_intent']) _ADGROUPCRITERION.fields_by_name['custom_intent'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['criterion'] _ADGROUPCRITERION.oneofs_by_name['_criterion_id'].fields.append( _ADGROUPCRITERION.fields_by_name['criterion_id']) _ADGROUPCRITERION.fields_by_name['criterion_id'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_criterion_id'] _ADGROUPCRITERION.oneofs_by_name['_ad_group'].fields.append( _ADGROUPCRITERION.fields_by_name['ad_group']) _ADGROUPCRITERION.fields_by_name['ad_group'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_ad_group'] _ADGROUPCRITERION.oneofs_by_name['_negative'].fields.append( _ADGROUPCRITERION.fields_by_name['negative']) _ADGROUPCRITERION.fields_by_name['negative'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_negative'] _ADGROUPCRITERION.oneofs_by_name['_bid_modifier'].fields.append( _ADGROUPCRITERION.fields_by_name['bid_modifier']) _ADGROUPCRITERION.fields_by_name['bid_modifier'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_bid_modifier'] _ADGROUPCRITERION.oneofs_by_name['_cpc_bid_micros'].fields.append( _ADGROUPCRITERION.fields_by_name['cpc_bid_micros']) _ADGROUPCRITERION.fields_by_name['cpc_bid_micros'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_cpc_bid_micros'] _ADGROUPCRITERION.oneofs_by_name['_cpm_bid_micros'].fields.append( _ADGROUPCRITERION.fields_by_name['cpm_bid_micros']) _ADGROUPCRITERION.fields_by_name['cpm_bid_micros'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_cpm_bid_micros'] _ADGROUPCRITERION.oneofs_by_name['_cpv_bid_micros'].fields.append( _ADGROUPCRITERION.fields_by_name['cpv_bid_micros']) _ADGROUPCRITERION.fields_by_name['cpv_bid_micros'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_cpv_bid_micros'] _ADGROUPCRITERION.oneofs_by_name['_percent_cpc_bid_micros'].fields.append( _ADGROUPCRITERION.fields_by_name['percent_cpc_bid_micros']) _ADGROUPCRITERION.fields_by_name['percent_cpc_bid_micros'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_percent_cpc_bid_micros'] _ADGROUPCRITERION.oneofs_by_name['_effective_cpc_bid_micros'].fields.append( _ADGROUPCRITERION.fields_by_name['effective_cpc_bid_micros']) _ADGROUPCRITERION.fields_by_name['effective_cpc_bid_micros'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_effective_cpc_bid_micros'] _ADGROUPCRITERION.oneofs_by_name['_effective_cpm_bid_micros'].fields.append( _ADGROUPCRITERION.fields_by_name['effective_cpm_bid_micros']) _ADGROUPCRITERION.fields_by_name['effective_cpm_bid_micros'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_effective_cpm_bid_micros'] _ADGROUPCRITERION.oneofs_by_name['_effective_cpv_bid_micros'].fields.append( _ADGROUPCRITERION.fields_by_name['effective_cpv_bid_micros']) _ADGROUPCRITERION.fields_by_name['effective_cpv_bid_micros'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_effective_cpv_bid_micros'] _ADGROUPCRITERION.oneofs_by_name['_effective_percent_cpc_bid_micros'].fields.append( _ADGROUPCRITERION.fields_by_name['effective_percent_cpc_bid_micros']) _ADGROUPCRITERION.fields_by_name['effective_percent_cpc_bid_micros'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_effective_percent_cpc_bid_micros'] _ADGROUPCRITERION.oneofs_by_name['_final_url_suffix'].fields.append( _ADGROUPCRITERION.fields_by_name['final_url_suffix']) _ADGROUPCRITERION.fields_by_name['final_url_suffix'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_final_url_suffix'] _ADGROUPCRITERION.oneofs_by_name['_tracking_url_template'].fields.append( _ADGROUPCRITERION.fields_by_name['tracking_url_template']) _ADGROUPCRITERION.fields_by_name['tracking_url_template'].containing_oneof = _ADGROUPCRITERION.oneofs_by_name['_tracking_url_template'] DESCRIPTOR.message_types_by_name['AdGroupCriterion'] = _ADGROUPCRITERION _sym_db.RegisterFileDescriptor(DESCRIPTOR) AdGroupCriterion = _reflection.GeneratedProtocolMessageType('AdGroupCriterion', (_message.Message,), { 'QualityInfo' : _reflection.GeneratedProtocolMessageType('QualityInfo', (_message.Message,), { 'DESCRIPTOR' : _ADGROUPCRITERION_QUALITYINFO, '__module__' : 'google.ads.googleads_v5.proto.resources.ad_group_criterion_pb2' , '__doc__': """A container for ad group criterion quality information. Attributes: quality_score: Output only. The quality score. This field may not be populated if Google does not have enough information to determine a value. creative_quality_score: Output only. The performance of the ad compared to other advertisers. post_click_quality_score: Output only. The quality score of the landing page. search_predicted_ctr: Output only. The click-through rate compared to that of other advertisers. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v5.resources.AdGroupCriterion.QualityInfo) }) , 'PositionEstimates' : _reflection.GeneratedProtocolMessageType('PositionEstimates', (_message.Message,), { 'DESCRIPTOR' : _ADGROUPCRITERION_POSITIONESTIMATES, '__module__' : 'google.ads.googleads_v5.proto.resources.ad_group_criterion_pb2' , '__doc__': """Estimates for criterion bids at various positions. Attributes: first_page_cpc_micros: Output only. The estimate of the CPC bid required for ad to be shown on first page of search results. first_position_cpc_micros: Output only. The estimate of the CPC bid required for ad to be displayed in first position, at the top of the first page of search results. top_of_page_cpc_micros: Output only. The estimate of the CPC bid required for ad to be displayed at the top of the first page of search results. estimated_add_clicks_at_first_position_cpc: Output only. Estimate of how many clicks per week you might get by changing your keyword bid to the value in first\_position\_cpc\_micros. estimated_add_cost_at_first_position_cpc: Output only. Estimate of how your cost per week might change when changing your keyword bid to the value in first\_position\_cpc\_micros. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v5.resources.AdGroupCriterion.PositionEstimates) }) , 'DESCRIPTOR' : _ADGROUPCRITERION, '__module__' : 'google.ads.googleads_v5.proto.resources.ad_group_criterion_pb2' , '__doc__': """An ad group criterion. Attributes: resource_name: Immutable. The resource name of the ad group criterion. Ad group criterion resource names have the form: ``customers/{cu stomer_id}/adGroupCriteria/{ad_group_id}~{criterion_id}`` criterion_id: Output only. The ID of the criterion. This field is ignored for mutates. status: The status of the criterion. This is the status of the ad group criterion entity, set by the client. Note: UI reports may incorporate additional information that affects whether a criterion is eligible to run. In some cases a criterion that's REMOVED in the API can still show as enabled in the UI. For example, campaigns by default show to users of all age ranges unless excluded. The UI will show each age range as "enabled", since they're eligible to see the ads; but AdGroupCriterion.status will show "removed", since no positive criterion was added. quality_info: Output only. Information regarding the quality of the criterion. ad_group: Immutable. The ad group to which the criterion belongs. type: Output only. The type of the criterion. negative: Immutable. Whether to target (``false``) or exclude (``true``) the criterion. This field is immutable. To switch a criterion from positive to negative, remove then re-add it. system_serving_status: Output only. Serving status of the criterion. approval_status: Output only. Approval status of the criterion. disapproval_reasons: Output only. List of disapproval reasons of the criterion. The different reasons for disapproving a criterion can be found here: https://support.google.com/adspolicy/answer/6008942 This field is read-only. bid_modifier: The modifier for the bid when the criterion matches. The modifier must be in the range: 0.1 - 10.0. Most targetable criteria types support modifiers. cpc_bid_micros: The CPC (cost-per-click) bid. cpm_bid_micros: The CPM (cost-per-thousand viewable impressions) bid. cpv_bid_micros: The CPV (cost-per-view) bid. percent_cpc_bid_micros: The CPC bid amount, expressed as a fraction of the advertised price for some good or service. The valid range for the fraction is [0,1) and the value stored here is 1,000,000 \* [fraction]. effective_cpc_bid_micros: Output only. The effective CPC (cost-per-click) bid. effective_cpm_bid_micros: Output only. The effective CPM (cost-per-thousand viewable impressions) bid. effective_cpv_bid_micros: Output only. The effective CPV (cost-per-view) bid. effective_percent_cpc_bid_micros: Output only. The effective Percent CPC bid amount. effective_cpc_bid_source: Output only. Source of the effective CPC bid. effective_cpm_bid_source: Output only. Source of the effective CPM bid. effective_cpv_bid_source: Output only. Source of the effective CPV bid. effective_percent_cpc_bid_source: Output only. Source of the effective Percent CPC bid. position_estimates: Output only. Estimates for criterion bids at various positions. final_urls: The list of possible final URLs after all cross-domain redirects for the ad. final_mobile_urls: The list of possible final mobile URLs after all cross-domain redirects. final_url_suffix: URL template for appending params to final URL. tracking_url_template: The URL template for constructing a tracking URL. url_custom_parameters: The list of mappings used to substitute custom parameter tags in a ``tracking_url_template``, ``final_urls``, or ``mobile_final_urls``. criterion: The ad group criterion. Exactly one must be set. keyword: Immutable. Keyword. placement: Immutable. Placement. mobile_app_category: Immutable. Mobile app category. mobile_application: Immutable. Mobile application. listing_group: Immutable. Listing group. age_range: Immutable. Age range. gender: Immutable. Gender. income_range: Immutable. Income range. parental_status: Immutable. Parental status. user_list: Immutable. User List. youtube_video: Immutable. YouTube Video. youtube_channel: Immutable. YouTube Channel. topic: Immutable. Topic. user_interest: Immutable. User Interest. webpage: Immutable. Webpage app_payment_model: Immutable. App Payment Model. custom_affinity: Immutable. Custom Affinity. custom_intent: Immutable. Custom Intent. """, # @@protoc_insertion_point(class_scope:google.ads.googleads.v5.resources.AdGroupCriterion) }) _sym_db.RegisterMessage(AdGroupCriterion) _sym_db.RegisterMessage(AdGroupCriterion.QualityInfo) _sym_db.RegisterMessage(AdGroupCriterion.PositionEstimates) DESCRIPTOR._options = None _ADGROUPCRITERION_QUALITYINFO.fields_by_name['quality_score']._options = None _ADGROUPCRITERION_QUALITYINFO.fields_by_name['creative_quality_score']._options = None _ADGROUPCRITERION_QUALITYINFO.fields_by_name['post_click_quality_score']._options = None _ADGROUPCRITERION_QUALITYINFO.fields_by_name['search_predicted_ctr']._options = None _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['first_page_cpc_micros']._options = None _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['first_position_cpc_micros']._options = None _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['top_of_page_cpc_micros']._options = None _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['estimated_add_clicks_at_first_position_cpc']._options = None _ADGROUPCRITERION_POSITIONESTIMATES.fields_by_name['estimated_add_cost_at_first_position_cpc']._options = None _ADGROUPCRITERION.fields_by_name['resource_name']._options = None _ADGROUPCRITERION.fields_by_name['criterion_id']._options = None _ADGROUPCRITERION.fields_by_name['quality_info']._options = None _ADGROUPCRITERION.fields_by_name['ad_group']._options = None _ADGROUPCRITERION.fields_by_name['type']._options = None _ADGROUPCRITERION.fields_by_name['negative']._options = None _ADGROUPCRITERION.fields_by_name['system_serving_status']._options = None _ADGROUPCRITERION.fields_by_name['approval_status']._options = None _ADGROUPCRITERION.fields_by_name['disapproval_reasons']._options = None _ADGROUPCRITERION.fields_by_name['effective_cpc_bid_micros']._options = None _ADGROUPCRITERION.fields_by_name['effective_cpm_bid_micros']._options = None _ADGROUPCRITERION.fields_by_name['effective_cpv_bid_micros']._options = None _ADGROUPCRITERION.fields_by_name['effective_percent_cpc_bid_micros']._options = None _ADGROUPCRITERION.fields_by_name['effective_cpc_bid_source']._options = None _ADGROUPCRITERION.fields_by_name['effective_cpm_bid_source']._options = None _ADGROUPCRITERION.fields_by_name['effective_cpv_bid_source']._options = None _ADGROUPCRITERION.fields_by_name['effective_percent_cpc_bid_source']._options = None _ADGROUPCRITERION.fields_by_name['position_estimates']._options = None _ADGROUPCRITERION.fields_by_name['keyword']._options = None _ADGROUPCRITERION.fields_by_name['placement']._options = None _ADGROUPCRITERION.fields_by_name['mobile_app_category']._options = None _ADGROUPCRITERION.fields_by_name['mobile_application']._options = None _ADGROUPCRITERION.fields_by_name['listing_group']._options = None _ADGROUPCRITERION.fields_by_name['age_range']._options = None _ADGROUPCRITERION.fields_by_name['gender']._options = None _ADGROUPCRITERION.fields_by_name['income_range']._options = None _ADGROUPCRITERION.fields_by_name['parental_status']._options = None _ADGROUPCRITERION.fields_by_name['user_list']._options = None _ADGROUPCRITERION.fields_by_name['youtube_video']._options = None _ADGROUPCRITERION.fields_by_name['youtube_channel']._options = None _ADGROUPCRITERION.fields_by_name['topic']._options = None _ADGROUPCRITERION.fields_by_name['user_interest']._options = None _ADGROUPCRITERION.fields_by_name['webpage']._options = None _ADGROUPCRITERION.fields_by_name['app_payment_model']._options = None _ADGROUPCRITERION.fields_by_name['custom_affinity']._options = None _ADGROUPCRITERION.fields_by_name['custom_intent']._options = None _ADGROUPCRITERION._options = None # @@protoc_insertion_point(module_scope)

71.832502

7,972

0.798426

9,605

72,048

5.567829

0.065487

0.025805

0.034331

0.049739

0.830943

0.798239

0.7436

0.684811

0.651676

0.583201

0

0.038577

0.100155

72,048

1,002

7,973

71.904192

0.786309

0.007231

0

0.45221

1

0.004111

0.35468

0.223972

0

1

0

false

0

0.015416

0

0.015416

0

null

0

1

0

1

0

1

0

null

0

5

2920ca4dd0173ed4466604445038b0eb072ca1d0

74

py

Python

pyretina/mc/__init__.py

yandexdataschool/pyretina

300d3cd460ded071d75d3729e9b5dc1489d86d73

[ "Apache-2.0" ]

2

2016-05-28T15:59:47.000Z

2018-07-30T21:05:18.000Z

pyretina/mc/__init__.py

yandexdataschool/pyretina

300d3cd460ded071d75d3729e9b5dc1489d86d73

[ "Apache-2.0" ]

null

pyretina/mc/__init__.py

yandexdataschool/pyretina

300d3cd460ded071d75d3729e9b5dc1489d86d73

[ "Apache-2.0" ]

null

from pseudo_velo_mc import monte_carlo, mc_stream from config import Event

37

49

0.878378

13

74

4.692308

0.769231

0

0.108108

74

2

50

37

0.924242

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

4625660b6d5d04c16c34782448fe3d79c97a7f98

112

py

Python

detection/__main__.py

janaSunrise/opencv2-face-detection-python

319f158f5f8eeadea597a447fee065d3926eefca

[ "MIT" ]

3

2021-05-04T17:50:02.000Z

2021-05-10T14:38:34.000Z

detection/__main__.py

janaSunrise/opencv2-face-detection-python

319f158f5f8eeadea597a447fee065d3926eefca

[ "MIT" ]

null

detection/__main__.py

janaSunrise/opencv2-face-detection-python

319f158f5f8eeadea597a447fee065d3926eefca

[ "MIT" ]

null

if __name__ == "__main__": print("You cannot run this module directly. Try running one of the submodules.")

37.333333

84

0.723214

16

112

4.5625

1

0

0.178571

112

2

85

56

0.793478

0

0.705357

0

1

0

true

0

0.5

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

464396c60b52257d002eea4cf825e7bdb78ee009

99

py

Python

main.py

TheRavehorn/KeyLogger

19faa15f929417942f6aaac1a28ada42ae3de384

[ "MIT" ]

null

main.py

TheRavehorn/KeyLogger

19faa15f929417942f6aaac1a28ada42ae3de384

[ "MIT" ]

null

main.py

TheRavehorn/KeyLogger

19faa15f929417942f6aaac1a28ada42ae3de384

[ "MIT" ]

null

#!/usr/bin/env python3 import keylogger my_keylogger = keylogger.KeyLogger() my_keylogger.start()

16.5

36

0.787879

13

99

5.846154

0.615385

0.289474

0.526316

0

0.011111

0.090909

99

5

37

19.8

0.833333

0.212121

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

5

4649cd8b599afe84623169e1d007d61a6131e097

39

py

Python

setupegg.py

joshua-sterner/stockwell_transform

6b78613cc3b2f6e0ac872813f41e57e949327c8c

[ "MIT" ]

25

2017-03-23T19:21:00.000Z

2022-03-03T14:49:42.000Z

setupegg.py

joshua-sterner/stockwell_transform

6b78613cc3b2f6e0ac872813f41e57e949327c8c

[ "MIT" ]

3

2017-12-18T16:49:06.000Z

2019-06-30T12:24:40.000Z

setupegg.py

joshua-sterner/stockwell_transform

6b78613cc3b2f6e0ac872813f41e57e949327c8c

[ "MIT" ]

13

2016-04-25T23:17:45.000Z

2021-01-30T23:42:35.000Z

import setuptools execfile("setup.py")

13

20

0.794872

5

39

6.2

1

0

0.076923

39

2

21

19.5

0.861111

0

0.205128

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

5

d3c01ed5c9aad5e69c4a89e695d078cf93edc0e2

19

py

Python

gym/version.py

MrJayK/gym

49d33fa83c6b65859d584939dc6e72f1ad36882d

[ "Python-2.0", "OLDAP-2.7" ]

9

2019-12-11T20:34:20.000Z

2021-05-23T04:35:29.000Z

gym/version.py

MrJayK/gym

49d33fa83c6b65859d584939dc6e72f1ad36882d

[ "Python-2.0", "OLDAP-2.7" ]

null

gym/version.py

MrJayK/gym

49d33fa83c6b65859d584939dc6e72f1ad36882d

[ "Python-2.0", "OLDAP-2.7" ]

1

2018-12-18T12:21:47.000Z

VERSION = '0.11.0'

9.5

18

0.578947

4

19

2.75

0.75

0

0.25

0.157895

19

1

19

0.4375

0

0.315789

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

5

d3dfd6b2d289d0878c6eea0c8424f0e05509ec2c

6,999

py

Python

modules/2.79/freestyle/functions.py

cmbasnett/fake-bpy-module

acb8b0f102751a9563e5b5e5c7cd69a4e8aa2a55

[ "MIT" ]

null

modules/2.79/freestyle/functions.py

cmbasnett/fake-bpy-module

acb8b0f102751a9563e5b5e5c7cd69a4e8aa2a55

[ "MIT" ]

null

modules/2.79/freestyle/functions.py

cmbasnett/fake-bpy-module

acb8b0f102751a9563e5b5e5c7cd69a4e8aa2a55

[ "MIT" ]

null

class ChainingTimeStampF1D: def __init__(self): pass def __call__(self, inter): pass class Curvature2DAngleF0D: def __init__(self): pass def __call__(self, it): pass class Curvature2DAngleF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class CurveMaterialF0D: pass class CurveNatureF0D: def __init__(self): pass def __call__(self, it): pass class CurveNatureF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class DensityF0D: def __init__(self, sigma=2.0): pass def __call__(self, it): pass class DensityF1D: def __init__(self, sigma=2.0, integration_type=IntegrationType.MEAN, sampling=2.0): pass def __call__(self, inter): pass class GetCompleteViewMapDensityF1D: def __init__(self, level, integration_type=IntegrationType.MEAN, sampling=2.0): pass def __call__(self, inter): pass class GetCurvilinearAbscissaF0D: def __init__(self): pass def __call__(self, it): pass class GetDirectionalViewMapDensityF1D: def __init__(self, orientation, level, integration_type=IntegrationType.MEAN, sampling=2.0): pass def __call__(self, inter): pass class GetOccludeeF0D: def __init__(self): pass def __call__(self, it): pass class GetOccludeeF1D: def __init__(self): pass def __call__(self, inter): pass class GetOccludersF0D: def __init__(self): pass def __call__(self, it): pass class GetOccludersF1D: def __init__(self): pass def __call__(self, inter): pass class GetParameterF0D: def __init__(self): pass def __call__(self, it): pass class GetProjectedXF0D: def __init__(self): pass def __call__(self, it): pass class GetProjectedXF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class GetProjectedYF0D: def __init__(self): pass def __call__(self, it): pass class GetProjectedYF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class GetProjectedZF0D: def __init__(self): pass def __call__(self, it): pass class GetProjectedZF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class GetShapeF0D: def __init__(self): pass def __call__(self, it): pass class GetShapeF1D: def __init__(self): pass def __call__(self, inter): pass class GetSteerableViewMapDensityF1D: def __init__(self, level, integration_type=IntegrationType.MEAN, sampling=2.0): pass def __call__(self, inter): pass class GetViewMapGradientNormF0D: def __init__(self, level): pass def __call__(self, it): pass class GetViewMapGradientNormF1D: def __init__(self, level, integration_type=IntegrationType.MEAN, sampling=2.0): pass def __call__(self, inter): pass class GetXF0D: def __init__(self): pass def __call__(self, it): pass class GetXF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class GetYF0D: def __init__(self): pass def __call__(self, it): pass class GetYF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class GetZF0D: def __init__(self): pass def __call__(self, it): pass class GetZF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class IncrementChainingTimeStampF1D: def __init__(self): pass def __call__(self, inter): pass class LocalAverageDepthF0D: def __init__(self, mask_size=5.0): pass def __call__(self, it): pass class LocalAverageDepthF1D: def __init__(self, sigma, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class MaterialF0D: def __init__(self): pass def __call__(self, it): pass class Normal2DF0D: def __init__(self): pass def __call__(self, it): pass class Normal2DF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class Orientation2DF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class Orientation3DF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class QuantitativeInvisibilityF0D: def __init__(self): pass def __call__(self, it): pass class QuantitativeInvisibilityF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class ReadCompleteViewMapPixelF0D: def __init__(self, level): pass def __call__(self, it): pass class ReadMapPixelF0D: def __init__(self, map_name, level): pass def __call__(self, it): pass class ReadSteerableViewMapPixelF0D: def __init__(self, orientation, level): pass def __call__(self, it): pass class ShapeIdF0D: def __init__(self): pass def __call__(self, it): pass class TimeStampF1D: def __init__(self): pass def __call__(self, inter): pass class VertexOrientation2DF0D: def __init__(self): pass def __call__(self, it): pass class VertexOrientation3DF0D: def __init__(self): pass def __call__(self, it): pass class ZDiscontinuityF0D: def __init__(self): pass def __call__(self, it): pass class ZDiscontinuityF1D: def __init__(self, integration_type=IntegrationType.MEAN): pass def __call__(self, inter): pass class pyCurvilinearLengthF0D: pass class pyDensityAnisotropyF0D: pass class pyDensityAnisotropyF1D: pass class pyGetInverseProjectedZF1D: pass class pyGetSquareInverseProjectedZF1D: pass class pyInverseCurvature2DAngleF0D: pass class pyViewMapGradientNormF0D: pass class pyViewMapGradientNormF1D: pass class pyViewMapGradientVectorF0D: def __init__(self, level): pass

12.431616

96

0.627947

709

6,999

5.588152

0.118477

0.136295

0.144372

0.193084

0.687027

0.670873

0.662039

0.632761

0

0.017515

0.298471

6,999

562

97

12.453737

0.789409

0

0.753623

0

1

0.373188

false

0.405797

0

0.594203

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

5

3103ec75192ef137fa9a0eceec55142a3a9fbe40

60

py

Python

Unicorn.py

Hackerx0406/termux.clone

31d7d7320eda8db35c7e6a48cd20edd0da0e441d

[ "Apache-2.0" ]

null

Unicorn.py

Hackerx0406/termux.clone

31d7d7320eda8db35c7e6a48cd20edd0da0e441d

[ "Apache-2.0" ]

null

Unicorn.py

Hackerx0406/termux.clone

31d7d7320eda8db35c7e6a48cd20edd0da0e441d

[ "Apache-2.0" ]

null

print("Hello User!") print ("stay safe & have a nice day!")

20

38

0.65

10

60

3.9

0.9

0

0.166667

60

2

39

30

0.78

0

0.65

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

31136bccb043f041d3a62fd66e12d2049a118cc4

126,549

py

Python

NetFlax_pipeline_code/scripts/TAGs.py

GCA-VH-lab/coreNet

19d328e808df93b7ea8ac18ed54982a6e720c09e

[ "MIT" ]

null

NetFlax_pipeline_code/scripts/TAGs.py

GCA-VH-lab/coreNet

19d328e808df93b7ea8ac18ed54982a6e720c09e

[ "MIT" ]

null

NetFlax_pipeline_code/scripts/TAGs.py

GCA-VH-lab/coreNet

19d328e808df93b7ea8ac18ed54982a6e720c09e

[ "MIT" ]

null

__author__ = "Chayan Kumar Saha, Gemma C. Atkinson" __copyright__ = "MIT License: Copyright (c) 2020 Chayan Kumar Saha" __email__ = "chayan.sust7@gmail.com" from Bio import SeqIO from Bio import Entrez from Bio.Seq import Seq from Bio.SeqRecord import SeqRecord from Bio.Alphabet import generic_protein, IUPAC import math, re import argparse import ftplib import socket import random import time from random import randint import colorsys import os, sys, os.path, math import gzip import getopt from collections import OrderedDict import subprocess from tkinter import * master = Tk() usage= ''' Description: TAGs in an extended version of FlaGs, which finds TA-like [type 2] structure by analysing conservation of genomic neighbourhood of protein accession input made of either toxins or antitoxins; and visualize the structure; Requirement= Python3, BioPython; tkinter ; Optional Requirement= ETE3. ''' parser = argparse.ArgumentParser(description=usage) parser.add_argument("-a", "--assemblyList", help=" Protein Accession with assembly Identifier eg. GCF_000001765.3 in a text file separated by newline. ") parser.add_argument("-p", "--proteinList", help=" Protein Accession eg. XP_ or WP_047256880.1 in a text file separated by newline. ") parser.add_argument("-l", "--localGenomeList", help=" Genome File name and Protein Accession ") parser.add_argument("-ld", "--localGenomeDirectory", help=" Path for Local Files, Default directory is './' which is the same directory where the script is located or running from. ") parser.add_argument("-r", "--redundant", help=" To search all assembly type -r A or -r a but for selected number of assembly eg.,5 for each query use -r 5. ") parser.add_argument("-e", "--ethreshold", help=" E value threshold. Default = 1e-10 ") parser.add_argument("-n", "--number", help=" Number of Jackhmmer iterations. Default = 3") parser.add_argument("-g", "--gene", help=" Number of genes for looking up or downstream. Default = 4 ") parser.add_argument("-i", "--intergenic", help=" Number of intergenic space. Default = 100 ") parser.add_argument("-t", "--tree", action="store_true", help=" If you want to see flanking genes along with phylogenetic tree, requires ETE3 installation. By default it will not produce. ") parser.add_argument("-ts", "--tshape", help=" Size of triangle shapes that represent flanking genes, this option only works when -t is used. Default = 12 ") parser.add_argument("-tf", "--tfontsize", help=" Size of font inside triangles that represent flanking genes, this option only works when -t is used. Default = 4 ") parser.add_argument("-tl", "--taxalist", help="List of Taxa name and GCF") parser.add_argument("-to", "--tree_order", action="store_true", help=" Generate Output with Tree, and then use the tree order to generate other view. ") parser.add_argument("-u", "--user_email", required=True, action="append", metavar="RECIPIENT",default=[], dest="recipients", help=" User Email Address (at least one required) ") parser.add_argument("-api", "--api_key", help=" NCBI API Key, To get this key kindly check https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/new-api-keys-for-the-e-utilities/ ") parser.add_argument("-o", "--out_prefix", required= True, help=" Any Keyword to define your output eg. MyQuery ") parser.add_argument("-c", "--cpu", help="Maximum number of parallel CPU workers to use for multithreads. ") parser.add_argument("-k", "--keep", action="store_true", help=" If you want to keep the intermediate files eg. gff3 use [-k]. By default it will remove. ") parser.add_argument("-v", "--version", action="version", version='%(prog)s 1.2.7.21') parser.add_argument("-vb", "--verbose", action="store_true", help=" Use this option to see the work progress for each query as stdout. ") args = parser.parse_args() parser.parse_args() print('\nStarting TAGs version 1.2.7.21 \nPlease only run one instance of TAGs at a time to avoid making more queries than NCBI’s limit.') print('For more information, please check https://ncbiinsights.ncbi.nlm.nih.gov/2017/11/02/new-api-keys-for-the-e-utilities/ \n') print('Checking for RefSeq and Genbank summary files and downloading if needed ... \n') Entrez.tool = 'FlaGs' ncbi_time=0.4 timeout = 10 socket.setdefaulttimeout(timeout) def checkBioPython(): #Checking Biopython Version import Bio return (Bio.__version__) from tkinter.font import Font #Font for postscript to-scale output myFont12 = Font(family="Helvetica", size=12) myFont7 = Font(family="Helvetica", size=7) Entrez.email = args.recipients[0] #User email Entrez.max_tries = 5 Entrez.sleep_between_tries = 60 if not args.localGenomeList: if args.api_key: Entrez.api_key = args.api_key #Valid API-key allows 10 queries per seconds, which makes the tool run faster else: if args.api_key: print('Since FlaGs will use Local Data api_key is not necessary, Thanks!') sys.exit() #Color generator def random_color(h=None): """Generates a random color in RGB format.""" if not h: c = random.random() d = 0.5 e = 0.5 return _hls2hex(c, d, e) def _hls2hex(c, d, e): return '#%02x%02x%02x' %tuple(map(lambda f: int(f*255),colorsys.hls_to_rgb(c, d, e))) def outliner (item): if item =='#ffffff': return '#bebebe' elif item =='#f2f2f2': return '#008000' elif item =='#f2f2f3': return '#000080' else: return item if args.redundant: #Search flanking genes in limited or all available GCFs for each query if args.redundant.isdigit(): if int(args.redundant)==0: print('Please use -r option correctly, kindly check help or manual and try again. Thanks!') sys.exit() else: pass if not args.redundant.isdigit(): if args.redundant.lower()=='a': pass else: print('Please use -r option correctly, kindly check help or manual and try again. Thanks!') sys.exit() if args.cpu: if int(args.cpu)>0: core=int(args.cpu) else: print('Please use number eg, 1,2...') sys.exit() if args.assemblyList: if args.redundant: print('"-r" option is only works with "-p", please try again with proper command') sys.exit() if args.localGenomeList: if args.redundant: print('"-r" option is only works with "-p", please try again with proper command') sys.exit() if args.tree: if args.tshape: if int(args.tshape)>0: size=int(args.tshape) else: print("Kindly input the size of triangles, recommended 12. Not applicable for 0 and negative values") else: size=12 else: if args.tshape: print("Kindly make sure that you are using -t to make this -ts argument working") sys.exit() if args.tree: if args.tfontsize: if int(args.tfontsize)>0: fsize=str(args.tfontsize) else: print("Kindly input the font Size required inside triangles, recommended 4. Not applicable for 0 and negative values") else: fsize=str(4) else: if args.tfontsize: print("Kindly make sure that you are using -t to make this -tf argument working") sys.exit() if args.tree_order: if not args.tree: print("Kindly make sure that you are using -t to make this -to argument working") sys.exit() if args.ethreshold: evthresh=args.ethreshold else: evthresh="1e-10" if args.number: iters=args.number else: iters="3" if args.gene: if int(args.gene)>0: s= str(int(args.gene)+1) else: print('Please insert positive values, starting from 1') sys.exit() else: s= "5" if args.localGenomeList: if args.localGenomeDirectory: if os.path.isdir(args.localGenomeDirectory): if args.localGenomeDirectory[-1]=='/': localDirIn=args.localGenomeDirectory print('Local Data path : ', localDirIn, '\n') else: localDirIn=args.localGenomeDirectory+'/' print('Local Data path : ', localDirIn, '\n') else: print('No directory Found as : '+ args.localGenomeDirectory) sys.exit() else: localDirIn='./' else: if args.localGenomeDirectory: print('Please use -l flag to make -ld flag working') sys.exit() if not args.localGenomeList: localDir='./' else: localDir=localDirIn #TAGs if args.intergenic: if int(args.intergenic)>0: gappyness=int(args.intergenic) else: print('Please insert positive values, starting from 1') sys.exit() else: gappyness=100 def checkChar(item): #removing characters import re items=item.replace('\t','').replace(' ','') return re.sub("[a-zA-Z0-9_.]","",items) queryList=[] #Formatting input as a list #(queryList) #eg 1. [['WP_019504790.1', 'GCF_000332195.1'], ['WP_028108719.1', 'GCF_000422645.1']] #eg 2. [['WP_019504790.1'], ['WP_028108719.1']] #TAGs netIn_SpDict={} if args.taxalist: with open(args.taxalist,'r') as taxaName: for line in taxaName: Line=line.rstrip().split('\t') netIn_SpDict[Line[0]]=Line[1] def tspLocal(faa,acc): #getting species name using assembly number or accession if netIn_SpDict: #TAGS if faa in netIn_SpDict: return netIn_SpDict[faa] if not netIn_SpDict: faaFile=faa+'.faa.gz' fastaSeq = gzip.open(localDir+faaFile, "rt") for record in SeqIO.parse(fastaSeq, "fasta"): if record.id==acc: return remBadChar(record.description.split('[')[-1][:-1]) if args.localGenomeList: with open (args.localGenomeList, 'r') as gList, open (args.out_prefix+'_taxaList.txt', 'w') as taxOut: for line in gList: if checkChar(line.rstrip().replace(' ',''))=='': Line=line.rstrip().replace(' ','').split('\t') if len(Line)<2: print('Check Input file, Incorrect Format.') sys.exit() else: #GCF_001639265.1 WP_066970962.1 Methanobrevibacter_filiformis_DSM_11501 newFormat=Line[1]+'\t'+Line[0] queryList.append(newFormat.split('\t')) print(Line[0], Line[1], tspLocal(Line[0],Line[1]), sep='\t', file=taxOut) if Line[0] not in netIn_SpDict: netIn_SpDict[Line[0]]=tspLocal(Line[0],Line[1]) #netIn_SpDict[Line[0]]=Line[2] else: print('The submitted query might include characters not found in NCBI protein accessions eg. > , # , ! etc. Please provide correct format, Thanks!') sys.exit() else: if args.proteinList and not args.assemblyList: with open (args.proteinList, 'r') as pList: for line in pList: if checkChar(line.rstrip().replace(' ',''))=='': Line=line.rstrip().replace(' ','').split('\t') if len(Line)>1: print('Check Input file, Incorrect Format.') sys.exit() else: queryList.append(Line) else: print('The submitted query might include characters not found in NCBI protein accessions eg. > , # , ! etc. Please provide correct format, Thanks!') sys.exit() elif args.assemblyList and not args.proteinList : with open (args.assemblyList, 'r') as apList: for line in apList: if checkChar(line.rstrip().replace(' ',''))=='': Line=line.rstrip().replace(' ','').split('\t') if len(Line)<2: print('Check Input file, Incorrect Format.') sys.exit() else: newFormat=Line[1]+'\t'+Line[0] queryList.append(newFormat.split('\t')) else: print('The submitted query might include characters not found in NCBI protein accessions eg. > , # , ! etc. Please provide correct format, Thanks!') sys.exit() else: print('Incorrect Input!') sys.exit() def accession_from_xp(accession_nr): """ :param accession_nr: NCBI protein accession :return: Bioproject number of all species for that protein which is used to grab Assembly number """ i=1 retry=True while (retry) and i<6: #Retry 5 times with changed socket timeout #Entrez.email = "_@gmail.com" # If you do >3 entrez searches on NCBI per second, your ip will be # blocked, warning is sent to this email. try: variableIsquare=i**2 changedtimeout = 10*variableIsquare #10-250 seconds (when i =1 , changedtimeout= 10*1 =10 | when i=2, changedtimeout= 10 * 2square =40 ) socket.setdefaulttimeout(changedtimeout) time.sleep(ncbi_time) handle = Entrez.efetch(db="protein", id=accession_nr, rettype="gbwithparts", retmode="text") if handle: retry=False record = SeqIO.read(handle, "genbank") bioproj=record.dbxrefs handle.close() bio=[] for item in bioproj: if item.split(':')[0]=='BioProject': bio.append(item.split(':')[1]) if bio: return set(bio) else: return {'NAI'} else: i+=1 retry=True except Exception as e: retry=True i+=1 if not i<6: print("\t\tQuery {}, not found in database. \n" "\t\tContinuing with the next protein in the list ... \n".format(accession_nr)) return False def accession_from_wp(accession_nr): """ :param accession_nr: NCBI protein accession :return: Set of assembly number of all species for particular protein """ i=1 retry=True while (retry) and i<6: #Retry 5 times with changed socket timeout #Entrez.email = "_@gmail.com" # If you do >3 entrez searches on NCBI per second, your ip will be # blocked, warning is sent to this email. try: variableIsquare=i**2 changedtimeout = 10*variableIsquare #10-250 seconds (when i =1 , changedtimeout= 10*1 =10 | when i=2, changedtimeout= 10 * 2square =40 ) socket.setdefaulttimeout(changedtimeout) time.sleep(ncbi_time) handle = Entrez.efetch(db="protein", id=accession_nr, rettype="ipg", retmode="xml") if handle: retry=False if float(checkBioPython())<=1.72: record = list(Entrez.parse(handle)) handle.close() assembly = re.findall("GC._\d*\.\d", str(record)) if assembly and len(assembly)>0: return (set(assembly)) else: return {'NAI'} else: record = Entrez.read(handle) handle.close() assembly = re.findall("GC._\d*\.\d", str(record['IPGReport'])) if assembly and len(assembly)>0: return (set(assembly)) else: return {'NAI'} else: i+=1 retry=True except Exception as e: retry=True i+=1 if not i<6: print("\t\tQuery {}, not found in database. \n" "\t\tContinuing with the next protein in the list ... \n".format(accession_nr)) return False def seq_from_wp(accession_nr): """ :param accession_nr: NCBI protein accession :return: Protein Sequence """ if accession_nr[-1]!='*': #Entrez.email = "_@gmail.com" # If you do >3 entrez searches on NCBI per second, your ip will be # blocked, warning is sent to this email. try: time.sleep(ncbi_time) handle = Entrez.efetch(db="protein", id=accession_nr, rettype="gbwithparts", retmode="text") except Exception as e: print(str(e), ", error in entrez-fetch protein accession, {}, not found in database. \n" "Continuing with the next protein in the list. \nError in function: {}".format(accession_nr, seq_from_wp.__name__)) return False record = SeqIO.read(handle, "genbank") handle.close() return record.description.split('[')[0]+'\t'+record.seq else: return accession_nr[:-1]+'\t'+'--' def remBadChar(item): #removing characters from species name import re return re.sub("[^a-zA-Z0-9]"," ",item).replace(" ","_") def identicalProtID(accnr): #searching for identical proteins i=1 retry=True while (retry) and i<6: #Retry 5 times with changed socket timeout #Entrez.email = "_@gmail.com" # If you do >3 entrez searches on NCBI per second, your ip will be # blocked, warning is sent to this email. try: variableIsquare=i**2 changedtimeout = 10*variableIsquare #10-250 seconds (when i =1 , changedtimeout= 10*1 =10 | when i=2, changedtimeout= 10 * 2square =40 ) socket.setdefaulttimeout(changedtimeout) time.sleep(ncbi_time) epost_1 = Entrez.read(Entrez.epost(db="protein", id=accnr)) webenv = epost_1["WebEnv"] query_key = epost_1["QueryKey"] iden_prots = Entrez.efetch(db="protein", rettype='ipg', retmode='text', webenv=epost_1["WebEnv"], query_key=epost_1["QueryKey"]) iAccSet=set() sAccSet=set() inrAccSet=set() snrAccSet=set() for item in iden_prots: if item[0:2]!='Id': if re.search("GC._\d*\.\d", item): itemLine=item.rstrip().split('\t') iAccession=itemLine[6] iAssembly=itemLine[-1] if iAccession!=accnr and iAccession[2]=='_': iAccSet.add(iAccession) if iAccession!=accnr and iAccession[2]!='_': inrAccSet.add(iAccession) if iAccession==accnr and iAccession[2]=='_': sAccSet.add(iAccession) if iAccession==accnr and iAccession[2]!='_': snrAccSet.add(iAccession) if len(iAccSet)>0 and len(sAccSet)==0: for ids in random.sample(iAccSet,1): return ids elif len(sAccSet)!=0: for ids in random.sample(sAccSet,1): return ids else: if len(inrAccSet)>0 and len(snrAccSet)==0 and len(iAccSet)==0: for ids in random.sample(inrAccSet,1): return ids else: return accnr retry=False except: retry=True i+=1 if not i<6: return accnr def identicalProtID_WP(accnr): #searching for identical proteins i=1 retry=True while (retry) and i<6: #Retry 5 times with changed socket timeout #Entrez.email = "_@gmail.com" # If you do >3 entrez searches on NCBI per second, your ip will be # blocked, warning is sent to this email. try: variableIsquare=i**2 changedtimeout = 10*variableIsquare #10-250 seconds (when i =1 , changedtimeout= 10*1 =10 | when i=2, changedtimeout= 10 * 2square =40 ) socket.setdefaulttimeout(changedtimeout) time.sleep(ncbi_time) epost_1 = Entrez.read(Entrez.epost(db="protein", id=accnr)) webenv = epost_1["WebEnv"] query_key = epost_1["QueryKey"] iden_prots = Entrez.efetch(db="protein", rettype='ipg', retmode='text', webenv=epost_1["WebEnv"], query_key=epost_1["QueryKey"]) iAccSet=set() for item in iden_prots: if item[0:2]!='Id': if re.search("GC._\d*\.\d", item): itemLine=item.rstrip().split('\t') iAccession=itemLine[6] iAssembly=itemLine[-1] if iAccession!=accnr and iAccession[:3]=='WP_': iAccSet.add(iAccession) if len(iAccSet)>0: for ids in random.sample(iAccSet,1): return ids else: return accnr retry=False except: retry=True i+=1 if not i<6: return accnr def identicalProtID_WP_Sp(accnr): #searching for identical proteins with same assembly for 'NP_417570.1' > WP_000785722.1|GCF_000005845.2 i=1 retry=True while (retry) and i<6: #Retry 5 times with changed socket timeout #Entrez.email = "_@gmail.com" # If you do >3 entrez searches on NCBI per second, your ip will be # blocked, warning is sent to this email. try: variableIsquare=i**2 changedtimeout = 10*variableIsquare #10-250 seconds (when i =1 , changedtimeout= 10*1 =10 | when i=2, changedtimeout= 10 * 2square =40 ) socket.setdefaulttimeout(changedtimeout) time.sleep(ncbi_time) epost_1 = Entrez.read(Entrez.epost(db="protein", id=accnr)) webenv = epost_1["WebEnv"] query_key = epost_1["QueryKey"] iden_prots = Entrez.efetch(db="protein", rettype='ipg', retmode='text', webenv=epost_1["WebEnv"], query_key=epost_1["QueryKey"]) iAccSetSpecial=set() iAccNRSetSpecial=set() iAssemblyList=[] iAssemblyListNR=[] for item in iden_prots: if item[0:2]!='Id': if re.search("GC._\d*\.\d", item): itemLine=item.rstrip().split('\t') iAccession=itemLine[6] iAssembly=itemLine[-1] if iAccession==accnr and iAccession[2]=='_': iAssemblyList.append(iAssembly) if iAccession==accnr and iAccession[-2]=='.' and iAssembly[0]=='G': iAssemblyListNR.append(iAssembly) if iAccession!=accnr and iAccession[-2]=='.' and iAssembly[0]=='G': assNR=iAccession+'|'+iAssembly iAccNRSetSpecial.add(assNR) if iAccession!=accnr and iAccession[:3]=='WP_': if iAssemblyList: if iAssembly==iAssemblyList[0]: assWp=iAccession+'|'+iAssembly iAccSetSpecial.add(assWp) if iAccSetSpecial: for ids in random.sample(iAccSetSpecial,1): return ids else: if iAssemblyList: for ids in random.sample(iAssemblyList,1): return accnr+'|'+ids else: if iAssemblyListNR: for nrids in random.sample(iAssemblyListNR,1): return accnr+'|'+nrids else: if iAccNRSetSpecial: for ids in random.sample(iAccNRSetSpecial,1): return ids else: return '#' retry=False except: retry=True i+=1 if not i<6: return '#' def identicalProtID_redundant(accnr): #searching for identical proteins with same assembly for 'NP_417570.1' > WP_000785722.1|GCF_000005845.2 i=1 retry=True while (retry) and i<6: #Retry 5 times with changed socket timeout #Entrez.email = "_@gmail.com" # If you do >3 entrez searches on NCBI per second, your ip will be # blocked, warning is sent to this email. try: variableIsquare=i**2 changedtimeout = 10*variableIsquare #10-250 seconds (when i =1 , changedtimeout= 10*1 =10 | when i=2, changedtimeout= 10 * 2square =40 ) socket.setdefaulttimeout(changedtimeout) time.sleep(ncbi_time) epost_1 = Entrez.read(Entrez.epost(db="protein", id=accnr)) webenv = epost_1["WebEnv"] query_key = epost_1["QueryKey"] iden_prots = Entrez.efetch(db="protein", rettype='ipg', retmode='text', webenv=epost_1["WebEnv"], query_key=epost_1["QueryKey"]) iAssemblyset=set() for item in iden_prots: if item[0:2]!='Id': if re.search("GC._\d*\.\d", item): itemLine=item.rstrip().split('\t') iAccession=itemLine[6] iAssembly=itemLine[-1] if iAccession==accnr: iAssemblyset.add(iAssembly) if iAssemblyset and len(iAssemblyset)>0: return iAssemblyset else: return '#' retry=False except: retry=True i+=1 if not i<6: return '#' def sortGCFvsGCA(gcagcfSet): if gcagcfSet!='NAI': Aset=set() Fset=set() for items in gcagcfSet: if items[2]=='A': Aset.add(items) if items[2]=='F': Fset.add(items) if len(Fset)>0: return Fset elif len(Fset)==0 and len(Aset)>0: return Aset else: return gcagcfSet else: gcagcfSet def des_check(item): if item: return item else: return 'notFound' def normalize_strand(item1, item2): #Strand direction change if item1=='+': return item2 else: if item2=='+': return '-' else: return '+' def up(item): if item=='+': return 'Upstream ' else: return 'Downstream ' def down(item): if item=='+': return 'Downstream ' else: return 'Upstream ' def ups(item): if item=='+': return '-' else: return '+' def downs(item): if item=='+': return '+' else: return '-' def lcheck(item): if 1 in item: return 1 else: return 0 def postscriptSize(item): if int(item)<1000: return(0) else: return(int(item)/1000) def getSpeciesFromGCF(faa,item): if item!='': if args.redundant: return remBadChar(item)+'_'+remBadChar(faa) else: return remBadChar(item) else: return 'Nothing' def spLocal(faa,acc): #getting species name using assembly number or accession if netIn_SpDict: #TAGS if faa in netIn_SpDict: return netIn_SpDict[faa] if not netIn_SpDict: if faa in speciesNameFromOnlineDict: return speciesNameFromOnlineDict[faa] else: faaFile=faa+'.faa.gz' fastaSeq = gzip.open(localDir+faaFile, "rt") for record in SeqIO.parse(fastaSeq, "fasta"): if record.id==acc: if args.redundant: return remBadChar(record.description.split('[')[-1][:-1])+'_'+remBadChar(faa) else: return remBadChar(record.description.split('[')[-1][:-1]) def desLocal(faa,acc): faaFile=faa+'.faa.gz' fastaSeq = gzip.open(localDir+faaFile, "rt") for record in SeqIO.parse(fastaSeq, "fasta"): if record.id==acc: return record.description.split('[')[0] def seqLocal(faa,acc): faaFile=faa+'.faa.gz' fastaSeq = gzip.open(localDir+faaFile, "rt") for record in SeqIO.parse(fastaSeq, "fasta"): if record.id==acc: return str(record.seq) def localNone(item): if item==None: return '--' else: return item def seqFasLocal(faa,acc): #making fasta file from accession if spLocal(faa,acc): faaFile=faa+'.faa.gz' fastaSeq = gzip.open(localDir+faaFile, "rt") for record in SeqIO.parse(fastaSeq, "fasta"): if record.id==acc.split('#')[0]: record.id=acc+'|'+spLocal(faa,acc)#.replace(':','_').replace('[','_').replace(']','_') record.description='' return record.format("fasta") else: faaFile=faa+'.faa.gz' fastaSeq = gzip.open(localDir+faaFile, "rt") for record in SeqIO.parse(fastaSeq, "fasta"): if record.id==acc.split('#')[0]: if args.redundant: record.id=acc+'|'+remBadChar(record.description.split('[')[-1][:-1])+'_'+remBadChar(faa)#.replace(':','_').replace('[','_').replace(']','_') else: record.id=acc+'|'+remBadChar(record.description.split('[')[-1][:-1]) record.description='' return record.format("fasta") def seqFasLenLocal(faa,acc): #making fasta file from accession if spLocal(faa,acc): faaFile=faa+'.faa.gz' fastaSeq = gzip.open(localDir+faaFile, "rt") for record in SeqIO.parse(fastaSeq, "fasta"): if record.id==acc.split('#')[0]: record.id=acc+'|'+spLocal(faa,acc)#.replace(':','_').replace('[','_').replace(']','_') record.description='' if record.seq: return len(record.seq) else: faaFile=faa+'.faa.gz' fastaSeq = gzip.open(localDir+faaFile, "rt") for record in SeqIO.parse(fastaSeq, "fasta"): if record.id==acc.split('#')[0]: if args.redundant: record.id=acc+'|'+remBadChar(record.description.split('[')[-1][:-1])+'_'+remBadChar(faa)#.replace(':','_').replace('[','_').replace(']','_') else: record.id=acc+'|'+remBadChar(record.description.split('[')[-1][:-1]) record.description='' if record.seq: return len(record.seq) def redundantCreate(setDict,nums): if nums=='A' or nums=='a': newList=random.sample(setDict,len(setDict)) else: if len(setDict)>int(nums): newList=random.sample(setDict,int(nums)) else: newList=random.sample(setDict,len(setDict)) return newList #Download assembly summary report from NCBI Refseq and genBank if not args.localGenomeList: refDb='./refSeq.db' genDb='./genBank.db' if os.path.isfile(refDb): refDbSize=os.path.getsize(refDb) else: refDbSize='0' if os.path.isfile(genDb): genDbSize=os.path.getsize(genDb) else: genDbSize='0' ftp = ftplib.FTP('ftp.ncbi.nih.gov', 'anonymous', 'anonymous@ftp.ncbi.nih.gov') ftp.cwd("/genomes/refseq") # move to refseq directory filenames = ftp.nlst() # get file/directory names within the directory if 'assembly_summary_refseq.txt' in filenames: ftp.sendcmd("TYPE i") if int(ftp.size('assembly_summary_refseq.txt'))!=int(refDbSize):#check if the previously downloaded db exists and if that's updated to recent one ftp.retrbinary('RETR ' + 'assembly_summary_refseq.txt', open('refSeq.db', 'wb').write) # get the assembly summary from refseq else: pass ftp_gen = ftplib.FTP('ftp.ncbi.nih.gov', 'anonymous', 'anonymous@ftp.ncbi.nih.gov') ftp_gen.cwd("/genomes/genbank") # move to refseq directory filenames = ftp_gen.nlst() # get file/directory names within the directory if 'assembly_summary_genbank.txt' in filenames: ftp_gen.sendcmd("TYPE i") if int(ftp_gen.size('assembly_summary_genbank.txt'))!=int(genDbSize):#check if the previously downloaded db exists and if that's updated to recent one ftp_gen.retrbinary('RETR ' + 'assembly_summary_genbank.txt', open('genBank.db', 'wb').write) # get the assembly summary from refseq else: pass assemblyName={} bioDict={} #bioproject as keys and assemble number (eg.GCF_000001765.1) as value accnr_list_dict={} #create a dictionary accessionNumber is a key and Organism name and ftp Gff3 download Link as value with open('refSeq.db', 'r') as fileIn: for line in fileIn: if line[0]!='#': Line=line.rstrip().split('\t') accnr_list_dict[Line[0]]= Line[7]+'\t'+Line[19] bioDict[Line[1]]=Line[0] assemblyName[Line[0]]=Line[0] ftp_gen = ftplib.FTP('ftp.ncbi.nih.gov', 'anonymous', 'anonymous@ftp.ncbi.nih.gov') ftp_gen.cwd("/genomes/genbank") # move to refseq directory assemblyName_GCA={} bioDict_gen={} accnr_list_dict_gen={} #create a dictionary accessionNumber is a key and Organism name and ftp Gff3 download Link as value with open('genBank.db', 'r') as fileIn: for line in fileIn: if line[0]!='#': Line=line.rstrip().split('\t') if len(Line)>19: if Line[18]=='identical': if Line[17] in accnr_list_dict: bioDict_gen[Line[1]]=Line[0] accnr_list_dict_gen[Line[0]]= accnr_list_dict[Line[17]] assemblyName_GCA[Line[0]]=Line[17] else: accnr_list_dict_gen[Line[0]]=Line[7]+'\t'+Line[19] else: accnr_list_dict_gen[Line[0]]=Line[7]+'\t'+Line[19] bioDict.update(bioDict_gen) accnr_list_dict.update(accnr_list_dict_gen) assemblyName.update(assemblyName_GCA) print ('\n'+ '>> Database Downloaded. Cross-checking of the accession list in progress ...'+ '\n') q=0 ne=0 queryDict={} #protein Id as query and a set of assembly number as value [either All or Species of interest] #{'WP_019504790.1#1': {'GCF_000332195.1'}, 'WP_028108719.1#2': {'GCF_000422645.1'}, 'WP_087820443.1#3': {'GCF_900185565.1'}} #{'WP_019504790.1#1': 'GCF_000332195.1', 'WP_028108719.1#2': 'GCF_000422645.1', 'WP_087820443.1#3': 'GCF_900185565.1'} local if not args.localGenomeList: with open (args.out_prefix+'_NameError.txt', 'w') as fbad: for query in queryList: q+=1 accession_from_wp_out='' accession_from_xp_out='' identicalProtID_Out='' accession_from_wp_ID_out='' accession_from_xp_ID_out='' accession_from_wp_IDSame_out='' exceptionalWP_out='' accession_from_wp_exceptional='' special_out = '' assembly_from_identical='' if args.verbose: print('\t Checking Query '+ query[0] +' ....'+ '('+str(q)+'/'+str(len(queryList))+')') if len(query)<2: if query[0][:2]=='WP' and query[0][-2]=='.': #WP Accession full WP_000785722.1 accession_from_wp_out=accession_from_wp(query[0]) if accession_from_wp_out: queryDict[query[0]+'#'+str(q)]=sortGCFvsGCA(accession_from_wp_out) else: ne+=1 print(query[0], file= fbad) elif query[0][:2]=='XP' and query[0][-2]=='.': #XP Accession full XP_003256407.1 accession_from_xp_out=accession_from_xp(query[0]) if accession_from_xp_out: assemList=[] for bioprojs in accession_from_xp_out: if bioprojs in bioDict: assemList.append(bioDict[bioprojs]) if assemList: queryDict[query[0]+'#'+str(q)]=sortGCFvsGCA(set(assemList)) else: ne+=1 print(query[0], file= fbad) else: #other accessions can be XP_003256407 , WP_000785722 too identicalProtID_Out=identicalProtID(query[0]) if identicalProtID_Out!=query[0]: #can be anything XP_ or WP_ or YP_ or NP_ if identicalProtID_Out[:-3]!='XP_': #Not XPs accession_from_wp_ID_out=accession_from_wp(identicalProtID_Out) if accession_from_wp_ID_out: asset=set() for elements in accession_from_wp_ID_out: asset.add(elements) if len(asset)>0: queryDict[identicalProtID_Out+'#'+str(q)+'.'+query[0]]=sortGCFvsGCA(asset) else: ne+=1 print(query[0], file= fbad) if identicalProtID_Out[:-3]=='XP_': #if XPs accession_from_xp_ID_out=accession_from_xp(identicalProtID_Out) if accession_from_xp_ID_out: assemList=[] for bioprojs in accession_from_xp_ID_out: if bioprojs in bioDict: assemList.append(bioDict[bioprojs]) if assemList: queryDict[identicalProtID_Out+'#'+str(q)+'.'+query[0]]=sortGCFvsGCA(set(assemList)) else: ne+=1 print(query[0], file= fbad) elif identicalProtID_Out==query[0]: #excluding XP Wp pre #YP NP exceptionalWP_out = identicalProtID_WP(identicalProtID_Out) special_out = identicalProtID_WP_Sp(identicalProtID_Out) #list Query GCF if not args.redundant: if special_out!='#': asset=set() asset.add(special_out.split('|')[1]) queryDict[query[0]+'#'+str(q)]=asset else: if exceptionalWP_out[:3]=='WP_': accession_from_wp_exceptional=accession_from_wp(exceptionalWP_out) if accession_from_wp_exceptional: asset=set() for elements in accession_from_wp_exceptional: asset.add(elements) if len(asset)>0: if query[0]!=exceptionalWP_out: queryDict[exceptionalWP_out+'#'+str(q)+'.'+query[0]]=sortGCFvsGCA(asset) else: queryDict[exceptionalWP_out+'#'+str(q)]=sortGCFvsGCA(asset) else: ne+=1 print(query[0], file= fbad) if args.redundant: if exceptionalWP_out[1:3]=='P_': accession_from_wp_exceptional=accession_from_wp(exceptionalWP_out) if accession_from_wp_exceptional: asset=set() for elements in accession_from_wp_exceptional: asset.add(elements) if len(asset)>0: if query[0]!=exceptionalWP_out: queryDict[exceptionalWP_out+'#'+str(q)+'.'+query[0]]=sortGCFvsGCA(asset) else: queryDict[exceptionalWP_out+'#'+str(q)]=sortGCFvsGCA(asset) else: ne+=1 print(query[0], file= fbad) elif exceptionalWP_out[2]!='_': assembly_from_identical=identicalProtID_redundant(identicalProtID_Out) if assembly_from_identical!='#': asset=set() for elements in assembly_from_identical: asset.add(elements) if len(asset)>0: #queryDict[identicalProtID_Out+'#'+str(q)+'.'+query[0]]=sortGCFvsGCA(asset) if query[0]!=exceptionalWP_out: queryDict[exceptionalWP_out+'#'+str(q)+'.'+query[0]]=sortGCFvsGCA(asset) else: queryDict[exceptionalWP_out+'#'+str(q)]=sortGCFvsGCA(asset) else: ne+=1 print(query[0], file= fbad) else: if query[0][:3]=='XP_' and query[0][-2]=='.': #XP Accession asset=set() accession_from_xp_out=accession_from_xp(query[0]) if accession_from_xp_out: for bioprojs in accession_from_xp_out: if bioprojs in bioDict: if bioDict[bioprojs]==query[1]: asset.add(query[1]) if len(asset)>0: queryDict[query[0]+'#'+str(q)]=asset else: ne+=1 print(query[0], file= fbad) elif query[0][:3]!='XP_' and query[0][-2]=='.': #not XP Accession asset=set() accession_from_wp_out=accession_from_wp(query[0]) if accession_from_wp_out: for elements in accession_from_wp_out: if query[1]==elements: asset.add(query[1]) if len(asset)>0: queryDict[query[0]+'#'+str(q)]=asset else: ne+=1 print(query[0], file= fbad) else: for query in queryList: q+=1 queryDict[query[0]+'#'+str(q)]=query[1] nai=0 NqueryDict={} #{'WP_019504790.1#1': ['GCF_000332195.1'], 'WP_028108719.1#2': ['GCF_000422645.1'], 'WP_087820443.1#3': ['GCF_900185565.1']} if args.localGenomeList: with open (args.out_prefix+'_Insufficient_Info_In_DB.txt', 'w') as fNai: for query in queryDict: assemblyIdlist=[] if queryDict[query]!={'NAI'}: assemblyId=queryDict[query] faa_gz=localDir+queryDict[query]+'.faa.gz' if os.path.isfile(faa_gz): with gzip.open(localDir+assemblyId+'.faa.gz', 'rb') as faaIn: for line in faaIn: if line.decode('utf-8')[0]=='>': Line=line.decode('utf-8').rstrip() if '>'+query.split('#')[0]==Line.split(' ')[0]: gff_gz=localDir+assemblyId+'.gff.gz' if os.path.isfile(gff_gz): with gzip.open(localDir+assemblyId+'.gff.gz', 'rb') as lgffIn: #Download and read gff.gz cds_c=0 name_c=0 prot_c=0 cset=set() nset=set() pset=set() for line in lgffIn: if line.decode('utf-8')[0]!='#': Line=line.decode('utf-8').rstrip().split('\t') if Line[2]=='CDS': cds_c=1 cset.add(cds_c) if Line[8].split(';')[3][:5]=='Name=': #eliminates pseudo gene as they don't have 'Name=' name_c=1 nset.add(name_c) if Line[8].split(';')[3].split('=')[1]==query.split('#')[0]: assemblyIdlist.append(assemblyId) NqueryDict[query]=list(set(assemblyIdlist)) prot_c=1 pset.add(prot_c) else: prot_c=0 pset.add(prot_c) else: name_c=0 nset.add(name_c) else: cds_c=0 cset.add(cds_c) if lcheck(pset)>0: pass elif lcheck(pset)==0: if lcheck(cset)>0 and lcheck(nset)>0: print(query.split('#')[0],' did not match with supplement local GFF File') print(query, file=fNai) nai+=1 else: print('Use recommended [NCBI refseq] format of GFF file') break else: print("Error: %s file not found" % gff_gz) else: print("Error: %s file not found" % faa_gz) else: print(query, file=fNai) nai+=1 else: with open (args.out_prefix+'_Insufficient_Info_In_DB.txt', 'w') as fNai: for query in queryDict: #print('\t', query, queryDict[query], 'All') if queryDict[query]: if len(queryDict[query])!=0: if queryDict[query]!={'NAI'}: #print('\t', query, queryDict[query], 'filtered') if args.redundant: redun=0 for newRed in (redundantCreate(queryDict[query],args.redundant)): redun+=1 NqueryDict[query+'.'+str(redun)]=list(str(newRed).split()) else: NqueryDict[query]=random.sample(queryDict[query],1) else: print(query, file=fNai) nai+=1 else: print(query, file=fNai) nai+=1 else: print(query, file=fNai) nai+=1 #print(NqueryDict) if not args.localGenomeList: print('\n> Downloading Genome Assembly Files from NCBI FTP Server \n') speciesNameFromOnlineDict={} newQ=0 for query in NqueryDict: newQ+=1 total=0 for item in NqueryDict[query]: if not args.localGenomeList: AssemDown=0 AssemFailed=0 if item in accnr_list_dict: speciesNameFromOnlineDict[item]=getSpeciesFromGCF(item, accnr_list_dict[item].split('\t')[0]) retry = True while (retry): try: ftpLine=accnr_list_dict[item].split('\t')[1] ftpsplitDir = ftpLine.split('/')[3:] ftp_path = '/'.join(map(str,ftpsplitDir)) #time.sleep(1) ftp = ftplib.FTP('ftp.ncbi.nih.gov', 'anonymous', 'anonymous@ftp.ncbi.nih.gov') ftp.cwd('/'+ftp_path) files = ftp.nlst() FileToDownload=[] for ftpelements in files: if '_genomic.gff.gz' in ftpelements: FileToDownload.append(ftpelements) if '_protein.faa.gz' in ftpelements: FileToDownload.append(ftpelements) if len(FileToDownload)==2: for elements in FileToDownload: #print(elements) #GCF_000964005.1_WiARP1.0_genomic.gff.gz GCF_000964005.1_WiARP1.0_protein.faa.gz if '_genomic.gff.gz' in elements: #Check if GFF.gz is there if args.verbose: ftp.set_debuglevel(1) ftp.set_pasv(True) ftp.voidcmd('TYPE I') ftp.sendcmd("TYPE i") try: gffFileSize=ftp.size(elements) gffFileName=item+'.gff.gz' gffFileDownloaded=open(item+'.gff.gz', 'wb') ftp.retrbinary('RETR ' + elements, gffFileDownloaded.write) ftp.sock.setsockopt(socket.SOL_SOCKET, socket.SO_KEEPALIVE, 1) ftp.sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_KEEPINTVL, 15) ftp.sock.setsockopt(socket.IPPROTO_TCP,socket.TCP_KEEPCNT, 8) ftp.voidcmd("NOOP") gffFileDownloaded.close() if os.path.isfile(localDir+gffFileName): if os.path.getsize(gffFileName)==gffFileSize: AssemDown+=1 retry = False except: AssemFailed+=-1 retry = True if '_protein.faa.gz' in elements: #Check if faa.gz is there if args.verbose: ftp.set_debuglevel(1) ftp.set_pasv(True) ftp.voidcmd('TYPE I') ftp.sendcmd("TYPE i") ftp.sendcmd("TYPE i") try: faaFileSize=ftp.size(elements) faaFileName=item+'.faa.gz' faaFileDownloaded=open(item+'.faa.gz', 'wb') ftp.retrbinary('RETR ' + elements, faaFileDownloaded.write) ftp.sock.setsockopt(socket.SOL_SOCKET, socket.SO_KEEPALIVE, 1) ftp.sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_KEEPINTVL, 15) ftp.sock.setsockopt(socket.IPPROTO_TCP,socket.TCP_KEEPCNT, 8) ftp.voidcmd("NOOP") faaFileDownloaded.close() if os.path.isfile(localDir+faaFileName): if os.path.getsize(faaFileName)==faaFileSize: AssemDown+=1 retry = False except: AssemFailed+=-1 retry = True ftp.close() else: AssemFailed+=-2 retry = False except: retry = True else: AssemFailed+=-2 total=AssemDown+AssemFailed if total==2: if args.verbose: print('\n\t'+'> NCBI Genome Assembly has been downloaded for '+query.split('#')[0]+' ('+str(newQ)+'/'+str(len(NqueryDict))+')'+'\n') for query in NqueryDict: for item in NqueryDict[query]: if args.localGenomeList: faaFile=item+'.faa.gz' fastaSeq = gzip.open(localDir+faaFile, "rt") for record in SeqIO.parse(fastaSeq, "fasta"): if record.id==query.split('#')[0]: if args.redundant: speciesNameFromOnlineDict[item]=remBadChar(record.description.split('[')[-1][:-1])+'_'+remBadChar(item) else: speciesNameFromOnlineDict[item]=remBadChar(record.description.split('[')[-1][:-1]) else: if item not in speciesNameFromOnlineDict or speciesNameFromOnlineDict[item]=='Nothing': faaFile=item+'.faa.gz' if os.path.isfile(localDir+faaFile): fastaSeq = gzip.open(localDir+faaFile, "rt") for record in SeqIO.parse(fastaSeq, "fasta"): if record.id==query.split('#')[0]: if args.redundant: speciesNameFromOnlineDict[item]=remBadChar(record.description.split('[')[-1][:-1])+'_'+remBadChar(item) else: speciesNameFromOnlineDict[item]=remBadChar(record.description.split('[')[-1][:-1]) else: speciesNameFromOnlineDict[item]=item+'#not_found' if args.keep: with open(args.out_prefix+'_speciesInfo.txt','w') as asmOut: for query in NqueryDict: for item in NqueryDict[query]: print(item, query.split('#')[0], speciesNameFromOnlineDict[item], sep='\t', file=asmOut) #print(NqueryDict) #{'WP_019504790.1#1': ['GCF_000332195.1'], 'WP_028108719.1#2': ['GCF_000422645.1'], 'WP_087820443.1#3': ['GCF_900185565.1']} print('\n'+'>> Input file assessment report: ') print('\t'+'Discarded protein ids with improper accession : '+str(ne)+'. See "'+args.out_prefix+'_NameError.txt'+'" file for details.') print('\t'+'Discarded protein ids lacking proper information in RefSeq DB : '+str(nai)+'. See "'+args.out_prefix+'_Insufficient_Info_In_DB.txt'+'" file for details.') print('\t'+'Remaining queries: '+str(newQ)) def getGeneId(item): matchObject = re.search('(GeneID:.*?,)', item) if matchObject: return matchObject.group(1)[:-1] def getGeneId_gene(item): matchObject2 = re.search('(GeneID:.*;)', item) if matchObject2: return matchObject2.group(1).split(';')[0] def lenChecker(List): if List: found=0 for item in List: if item==True and item>5000: found+=1 if found==0: return 'keep' else: return 'delete' else: return 'keep' FoundDict={} #Accession that found in Refseq FlankFoundDict={} #Accession that have flanking genes accFlankDict={} #{'WP_092250023.1#1': {0: 'WP_092250023.1+', 1: 'WP_092250020.1+', 2: 'WP_092250017.1-', -1: 'tRNA*+', -2: 'WP_092250026.1-'}} positionDict={} #Accession as keys:Start and end position as value speciesDict={} #SpeciesName stored here queryStrand={} #Strand Information for each query LengthDict={} #Length of each query seqDict={} desDict={} acc_CGF_Dict={} treeFastadict={} #Query as key and sequence in fasta as value querySeqDict={} #For Tree Command count=0 for query in NqueryDict: count+=1 if args.verbose: print('\n'+'> '+str(count)+' in process out of '+str(newQ)+' ... '+'\n') print('Query Name =', query.split('#')[0], '\n') for item in NqueryDict[query]: #{'WP_019504790.1#1': ['GCF_000332195.1'],NqueryDict a=0 LineList=[] geneProt={} # 'gene2504': 'WP_092248795.1', 'gene1943': 'tRNA' geneChrom={} #'gene1708': 'NZ_MJLP01000030.1' #item='GCF_'+items[4:] speciesNameFromDB=speciesNameFromOnlineDict[item] gff_gz=localDir+item+'.gff.gz' if os.path.isfile(gff_gz): LineList=[] geneProt={} # 'gene2504': 'WP_092248795.1', 'gene1943': 'tRNA' geneChrom={} #'gene1708': 'NZ_MJLP01000030.1' with gzip.open(localDir+item+'.gff.gz', 'rb') as gffIn: #Download and read gff.gz for line in gffIn: if line.decode('utf-8')[0]!='#': Line=line.decode('utf-8').rstrip().split('\t') if Line[2]=='CDS': if Line[8].split(';')[3][:5]=='Name=': #eliminates pseudo gene as they don't have 'Name=' if query.split('_')[0]=='XP': if 'GeneID:' in Line[8]: geneProt[getGeneId(Line[8])]=Line[8].split(';')[3].split('=')[1] geneChrom[getGeneId(Line[8])]=Line[0] #print(getGeneId(Line[8]), Line[8].split(';')[3].split('=')[1], Line[0], 'gpc#') else: #print(Line[8].split(';')[1].split('=')[1], Line[8].split(';')[3].split('=')[1], Line[0], 'gpc#') geneProt[Line[8].split(';')[1].split('=')[1]]=Line[8].split(';')[3].split('=')[1] geneChrom[Line[8].split(';')[1].split('=')[1]]=Line[0] ##print(geneProt)>'GeneID:187667': 'NP_493855.2' NP_417570.1 gene-b3099 if Line[2][-4:]=='gene': a+=1 if query.split('_')[0]=='XP': if 'GeneID:' in Line[8]: newGene=str(a)+'\t'+getGeneId_gene(Line[8])+'\t'+ Line[3]+'\t'+Line[4]+'\t'+ Line[6]+ '\t'+ Line[0] #print(newGene) #1 GeneID:353377 3747 3909 - NC_003279.8 LineList.append(newGene.split('\t')) for genDes in Line[8].split(';'): if 'gene_biotype=' in genDes: if getGeneId_gene(Line[8]) not in geneProt: geneProt[getGeneId_gene(Line[8])]=genDes.split('=')[1]+'_'+query.split('#')[1]+'.'+str(random.randint(0,int(s)*2-1))+'*' else: newGene=str(a)+'\t'+Line[8].split(';')[0][3:]+'\t'+ Line[3]+'\t'+Line[4]+'\t'+ Line[6]+ '\t'+ Line[0] LineList.append(newGene.split('\t')) #1 gene3006 10266 10342 - NZ_FPCC01000034.1 for genDes in Line[8].split(';'): if 'gene_biotype=' in genDes: if Line[8].split(';')[0][3:] not in geneProt: geneProt[Line[8].split(';')[0][3:]]=genDes.split('=')[1]+'_'+query.split('#')[1]+'.'+str(random.randint(0,int(s)*2-1))+'*' geneList=[] ##List of gene names coding same protein (accession), we are taking one from them for genes in geneProt: if geneProt[genes]==query.split('#')[0]: geneList.append(genes) if len(geneList)>0: rangeList=[] for line in LineList: if geneChrom[geneList[0]]==line[5]: rangeList.append(int(LineList[LineList.index(line)][0])) for genes in geneProt: if genes==geneList[0]: if query.split('#')[0]==geneProt[genes]: for line in LineList: if genes==line[1]: FoundDict[query]='Yes' if args.tree: #print(query, item, seqFasLocal(item,query), tspLocal(item,query.split('#')[0]), seqLocal(item,query.split('#')[0])) treeFastadict[query]=str(seqFasLocal(item,query)) querySeqDict[query+'|'+tspLocal(item,query.split('#')[0])]=str(seqLocal(item,query.split('#')[0])) #querySeqDict[query+'|'+remBadChar(spLocal(item,query.split('#')[0]))]=str(seqLocal(item,query.split('#')[0])) #TAGs #if speciesNameFromDB!='Nothing' or speciesNameFromDB!='': #print(speciesNameFromDB, 1) # speciesDict[query]=speciesNameFromDB #else: #print(spLocal(item, query.split('#')[0]), 2) speciesDict[query]=spLocal(item, query.split('#')[0]) if query not in speciesDict: if speciesNameFromDB!='Nothing' or speciesNameFromDB!='': speciesDict[query]=speciesNameFromDB queryStrand[query]= LineList[LineList.index(line)][4] positionDict[query]= ("\t".join(map(str,LineList[LineList.index(line)][2:-2]))) LengthDict[query]= int(LineList[LineList.index(line)][3])-int(LineList[LineList.index(line)][2])+1 udsDict={} dsDict={} udsDict[0]= query+'+' # O strand lengthCheck=[] for x in range(1,int(s)): if LineList.index(line)-x>=0 and LineList.index(line)-x<len(LineList): if rangeList.count(int(LineList[LineList.index(line)-x][0]))>0: acc_CGF_Dict[query]= LineList[LineList.index(line)-x][-1] +'\t'+ item seqDict[str(geneProt[LineList[LineList.index(line)-x][1]])]=localNone(seqLocal(item, geneProt[LineList[LineList.index(line)-x][1]])) desDict[geneProt[LineList[LineList.index(line)-x][1]]]=desLocal(item, geneProt[LineList[LineList.index(line)-x][1]]) positionDict[geneProt[LineList[LineList.index(line)-x][1]]+'#'+query.split('#')[1]]= ("\t".join(map(str,LineList[LineList.index(line)-x][2:-2]))) lengthCheck.append(seqFasLenLocal(item,geneProt[LineList[LineList.index(line)-x][1]]+'#'+query.split('#')[1])) LengthDict[geneProt[LineList[LineList.index(line)-x][1]]+'#'+query.split('#')[1]]= int(LineList[LineList.index(line)-x][3])-int(LineList[LineList.index(line)-x][2])+1 udsDict[int(ups(LineList[LineList.index(line)][4])[0]+str(x))]= geneProt[LineList[LineList.index(line)-x][1]]+'#'+query.split('#')[1]+\ normalize_strand(LineList[LineList.index(line)][4],LineList[LineList.index(line)-x][4]) for y in range(1,int(s)): if LineList.index(line)+y<len(LineList): if rangeList.count(int(LineList[LineList.index(line)+y][0]))>0: acc_CGF_Dict[query]= LineList[LineList.index(line)+y][-1] +'\t'+ item seqDict[str(geneProt[LineList[LineList.index(line)+y][1]])]=localNone(seqLocal(item,geneProt[LineList[LineList.index(line)+y][1]])) desDict[geneProt[LineList[LineList.index(line)+y][1]]]=desLocal(item,geneProt[LineList[LineList.index(line)+y][1]]) positionDict[geneProt[LineList[LineList.index(line)+y][1]]+'#'+query.split('#')[1]]= ("\t".join(map(str,LineList[LineList.index(line)+y][2:-2]))) lengthCheck.append(seqFasLenLocal(item,geneProt[LineList[LineList.index(line)+y][1]]+'#'+query.split('#')[1])) LengthDict[geneProt[LineList[LineList.index(line)+y][1]]+'#'+query.split('#')[1]]= int(LineList[LineList.index(line)+y][3])-int(LineList[LineList.index(line)+y][2])+1 dsDict[int(downs(LineList[LineList.index(line)][4])[0]+str(y))]= geneProt[LineList[LineList.index(line)+y][1]]+'#'+query.split('#')[1]+\ normalize_strand(LineList[LineList.index(line)][4],LineList[LineList.index(line)+y][4]) if lenChecker(lengthCheck)=='keep': udsDict.update(dsDict) accFlankDict[query]=udsDict if query in accFlankDict: if len(accFlankDict[query])>0: FlankFoundDict[query]='Yes' if args.verbose: print('\t', query.split('#')[0], 'Report: Flanking Genes Found', '\n') else: FlankFoundDict[query]='No' if args.verbose: print('\t', query.split('#')[0], 'Report: Flanking Genes Not Found', '\n') else: FlankFoundDict[query]='No' if args.verbose: print('\t', query.split('#')[0], 'Report: Flanking Genes Not Found', '\n') else: FlankFoundDict[query]='Yes' if args.verbose: print('\t', query.split('#')[0], 'Report: Flanking Gene is longer than 7000 amino acid, thus query is discarded', '\n') else: if query not in FoundDict: FlankFoundDict[query]='No' if args.verbose: print('\t', query.split('#')[0], 'Report: Flanking Genes Not Found', '\n') else: FlankFoundDict[query]='No' FoundDict[query]='No: ProteinID was not found in Genome Assembly' if args.verbose: print('\t', query.split('#')[0], 'Report: Flanking Genes Not Found', '\n') else: FlankFoundDict[query]='No' FoundDict[query]='No: ProteinID was not found in Genome Assembly' if args.verbose: print('\t', query.split('#')[0], 'Report: Flanking Genes Not Found', '\n') if not args.localGenomeList: if args.keep: pass else: subprocess.Popen("rm GC*_*.gz", shell=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) allFlankGeneList=[] for keys in accFlankDict: for item in accFlankDict[keys]: allFlankGeneList.append(accFlankDict[keys][item].split('#')[0]) flankF=0 with open (args.out_prefix+'_flankgene_Report.log', 'w') as errOut: serial=0 print('#Serial','Query','Assembly_Found', 'FlankingGene_Found', sep='\t', file=errOut) for queries in NqueryDict: serial+=1 if queries in FoundDict: if queries in FlankFoundDict: if FlankFoundDict[queries]=='Yes': flankF+=1 print(str(serial), queries.split('#')[0], FoundDict[queries], FlankFoundDict[queries], sep='\t', file=errOut) else: print(str(serial), queries.split('#')[0], FoundDict[queries], 'No', sep='\t', file=errOut) else: print(str(serial), queries.split('#')[0], 'No', 'No', sep='\t', file=errOut) reportDict={} for query in queryList: queryNumList=[] for queryNum in NqueryDict: if query[0] in queryNum: queryNumList.append(queryNum) if len(queryNumList)>0: reportDict[query[0]]=queryNumList else: reportDict[query[0]]=str('no').split() def similarityID (item1, item2): if item1==item2: return 'Same' else: return 'Changed' def reporter(i1,i2,i3,i4,i5): if i2=='No' and i3=='No' and i4=='No' and i5=='No': return i1 + ' Failed : No record for accession ' + i1 if i2!='No' and i3=='Same' and i4!='No' and i5=='No': return i1 + ' is a valid NCBI protein accession but Discarded : No Flanking Gene was found for ' + i1 + ' in Assembly ID '+ i4 if i2!='No' and i3=='Same' and i4!='No' and i5!='No': return i1 + ' is valid as a NCBI protein accession and reported in Assembly ID '+ i4 if i2!='No' and i3=='Changed' and i4!='No' and i5=='No': return i1 + ' is invalid NCBI protein accession therefore converted to identical RefSeq sequence with accession '+ i2 + ' but Discarded : No Flanking Gene was found for ' + i2 + 'in Assembly ID '+ i4 if i2!='No' and i3=='Changed' and i4!='No' and i5!='No': return i1 + ' is invalid NCBI protein accession therefore converted to identical RefSeq sequence with accession '+ i2 + ' which is reported in Assembly ID '+ i4 qcount=0 discardedGene=0 with open (args.out_prefix+'_QueryStatus.txt', 'w') as sumOut: print('#Serial', 'Status', sep='\t', file=sumOut) for query in queryList: #print('query',query) qcount+=1 for item in reportDict[query[0]]: #print('item',item) if item in FlankFoundDict: if item in accFlankDict: if FlankFoundDict[item]=='Yes': print(str(qcount), reporter(query[0], item.split('#')[0], similarityID(query[0], item.split('#')[0]), ''.join(NqueryDict[item]), 'Yes'), sep='\t', file=sumOut) else: print(str(qcount), reporter(query[0], item.split('#')[0], similarityID(query[0], item.split('#')[0]), ''.join(NqueryDict[item]), 'No'), sep='\t', file=sumOut) else: if FlankFoundDict[item]=='Yes': discardedGene+=1 print(str(qcount), query[0]+' is a valid NCBI protein accession but Discarded : Flanking gene with a length more than 5000 amino acid detected.', sep='\t',file=sumOut) else: print(str(qcount), reporter(query[0], item.split('#')[0], similarityID(query[0], item.split('#')[0]), ''.join(NqueryDict[item]), 'No'), sep='\t', file=sumOut) else: print(str(qcount), reporter(query[0], 'No', 'No', 'No', 'No'), sep='\t', file=sumOut) print('\n'+'>> Flanking Genes found : '+str(flankF)+' out of remaining '+str(serial)+'. See "'+args.out_prefix+'_flankgene_Report.log'+'" file for details.'+'\n'+'\n') if int(flankF)==0: print('>> No Flanking Genes found, please update your accession list') sys.exit() else: pass if args.tree: #Generate fasta file for making phylogenetic Tree with open(args.out_prefix+'_tree.fasta', 'w') as treeOut: for queries in NqueryDict: if queries in treeFastadict: print(treeFastadict[queries], file=treeOut) if len(seqDict)!=len(desDict): if len(seqDict)>len(desDict): for seqids in sorted(seqDict): if seqids not in desDict: desDict[seqids]=des_check(str(seq_from_wp(seqids).split('\t')[0])) else: for seqids in sorted(desDict): if seqids not in seqDict: seqDict[seqids]=str(seq_from_wp(seqids).split('\t')[1]) else: if args.verbose: print ('Description collected for Flanking Genes!') b=0 with open (args.out_prefix+'_flankgene.fasta'+'_cluster_out', 'w') as fastaNew: for seqids in sorted(seqDict): if seqDict[seqids]!='--': b+=1 print('>'+seqids+'|'+desDict[seqids]+'\n'+seqDict[seqids], file=fastaNew) if args.verbose: print ('Total Flanking genes found = '+ str(b)) print('\n>> Now running Jackhmmer and clustering flanking genes\n') infilename=args.out_prefix+'_flankgene.fasta'+'_cluster_out' directory = args.out_prefix+'_flankgene.fasta'+'_cluster_out_individuals' if not os.path.exists(directory): os.makedirs(directory) infile=open(args.out_prefix+'_flankgene.fasta'+'_cluster_out',"r").read() al=infilename+"_"+iters+"_"+evthresh+"_jackhits.tsv" outacclists=open(al,"w") percentileJack=0 i=1 for seqids in sorted(seqDict): #Running Jackhmmer for finding homologs if seqDict[seqids]!='--': percentileJack+=1 if args.verbose: if percentileJack % 5 == 0: print('\t'+'>>> '+str(round(int(percentileJack)*100/b))+'%'+' Completed...'+'('+str(percentileJack)+'/'+str(b)+')') if percentileJack % b == 0: print('\t'+'>>> Completed ' +'\n') i_f=directory+"/"+str(i)+".txt" indivfile=open(i_f,"w") indivfile.write(">"+seqids+'\n'+seqDict[seqids]) indivfile.close() if args.cpu: command="jackhmmer --cpu %s -N %s --incE %s --incdomE %s --tblout %s/tblout%s.txt %s %s>%s/out%s.txt" %(core, iters, evthresh, evthresh, directory, str(i), i_f, infilename, directory, str(i)) else: command="jackhmmer -N %s --incE %s --incdomE %s --tblout %s/tblout%s.txt %s %s>%s/out%s.txt" %(iters, evthresh, evthresh, directory, str(i), i_f, infilename, directory, str(i)) os.system(command) tbl=open(directory+"/tblout"+str(i)+".txt").read() part=tbl.split("----------\n")[1].split("\n#")[0] lines=part.splitlines() acclist=[] for line in lines: lineList=line.split() if len(lineList)>17: inc=line.split()[17] acc=line.split('|')[0] if inc=="1": acclist.append(acc) outacclists.write(str(i)+"\t"+str(acclist)+"\n") i=i+1 outacclists.close() raw=open(al).read().strip() d={} index=0 for line in raw.split("\n"): if line.split("\t")[1]!='[]': index+=1 actxt=line.split("\t")[1].replace(",","").replace("[","").replace("]","").replace("'","") actlist=actxt.split(" ") d[index]=(actlist) i=1 while i<len(d)+1: #use i and j to iterate through the combinations list1=d[i] j=i+1 while j<len(d)+1: list2=d[j] #print "i", i, list1, " vs ", #print "j", j, list2 if set(list1) & (set(list2)): # if there is an intersection #print "yes there is", list1, list2 union=list(set(list2) | set(list1)) d[j]=union d[i]=[] #...and empty the redundant list j=j+1 i=i+1 #d : {1: ['WP_000153877.1'], 2: [], 3: ['WP_000291520.1'], 4: ['WP_000342211.1'], 5: [],... 30: ['WP_055032751.1', 'WP_001246052.1']} trueAccessionCount={} for keys in d: numbers=[] for item in d[keys]: numbers.append(allFlankGeneList.count(item)) trueAccessionCount[(';'.join(map(str,d[keys])))]=sum(numbers) #trueAccessionCount: 'WP_001229260.1;WP_001229255.1': 4 odtrue=OrderedDict(sorted(trueAccessionCount.items(), key= lambda item:item[1],reverse=True)) familyNumber=0 with open(infilename+"_"+iters+"_"+evthresh+"_clusters.tsv","w") as clusOut: for k, v in odtrue.items(): #print (k.split(';'), odtrue[k], v) if len(k.split(';'))>0 and v>0: familyNumber+=1 print(str(familyNumber),str(odtrue[k]),k, sep='\t', file=clusOut) outfile_des=open(infilename+"_"+iters+"_"+evthresh+"_outdesc.txt","w") inf=open(infilename+"_"+iters+"_"+evthresh+"_clusters.tsv","r") acclists=inf.read().splitlines() for line in acclists: acclist=line.split("\t")[2].split(";") familyAssignedValue=line.split("\t")[0] if int(line.split("\t")[1])>1: for acc in acclist: outfile_des.write(familyAssignedValue+'('+str(allFlankGeneList.count(acc))+')'+"\t"+acc+"\t"+desDict[acc]+"\n") outfile_des.write ("\n\n") familyDict={} # Accession:Assigned family Number from Jackhammer with open(args.out_prefix+'_flankgene.fasta_cluster_out_'+iters+'_'+evthresh+'_clusters.tsv', 'r') as clusterIn: for line in clusterIn: if line[0]!='#': line=line.rstrip().split('\t') if int(line[1])>1: for item in (line[2].split(';')): familyDict[item]=int(line[0]) else: familyDict[line[2]]=0 familynum=[] for acc in familyDict: familynum.append(familyDict[acc]) center=int(max(familynum))+1 noProt=int(max(familynum))+2 noProtP=int(max(familynum))+3 noColor=int(max(familynum))+4 for ids in LengthDict: if ids.split('#')[0][-1]=='*': if ids.split('#')[0][:2].lower()=='ps': familyDict[ids.split('#')[0]]=noProtP else: familyDict[ids.split('#')[0]]=noProt if ids.split('#')[0] not in familyDict: if ids in NqueryDict: familyDict[ids.split('#')[0]]=center else: familyDict[ids.split('#')[0]]=noColor color={} color[noColor]='#ffffff' color[center]='#000000' color[noProt]='#f2f2f2' color[noProtP]='#f2f2f3' colorDict={} #Assigned family Number from Jackhammer : colorcode for families in set(familynum): if families == 0: colorDict[families]=str('#ffffff') else: if random_color()!='#ffffff' or random_color()!='#000000' or random_color()!='#f2f2f2' or random_color()!='#f2f2f3' : colorDict[families]=random_color() colorDict.update(color) maxs=(int(s)-1) # required to calculate border size of postscript output mins=maxs-(maxs*2) # required to calculate border size of postscript output if not args.tree_order: nPos=[] pPos=[] with open(args.out_prefix+'_operon.tsv', 'w') as opOut: for queries in accFlankDict: for items in sorted(accFlankDict[queries]): if queryStrand[queries]=='+': ids=accFlankDict[queries][items][:-1] lengths=LengthDict[accFlankDict[queries][items][:-1]] species=queries+'|'+remBadChar(speciesDict[queries]) qStrand=queryStrand[queries] nStrand=accFlankDict[queries][items][-1] family=familyDict[accFlankDict[queries][items][:-1].split('#')[0]] startPos=int(positionDict[accFlankDict[queries][0][:-1]].split('\t')[0])-1 start=int(positionDict[accFlankDict[queries][items][:-1]].split('\t')[0]) end=int(positionDict[accFlankDict[queries][items][:-1]].split('\t')[1]) if queries in acc_CGF_Dict: info=acc_CGF_Dict[queries] else: info='not_found'+'\t'+'not_found'+'\t'+'not_found' print(species, lengths, qStrand, nStrand, family, start-startPos, end-startPos, start, end, ids, info, sep='\t', file=opOut) nP=start-startPos pP=end-startPos nPos.append(nP) pPos.append(pP) else: ids=accFlankDict[queries][items][:-1] lengths=LengthDict[accFlankDict[queries][items][:-1]] #c2 species=queries+'|'+remBadChar(speciesDict[queries]) qStrand=queryStrand[queries] nStrand=accFlankDict[queries][items][-1] family=familyDict[accFlankDict[queries][items][:-1].split('#')[0]] startPos=int(positionDict[accFlankDict[queries][0][:-1]].split('\t')[1])+1 start=int(positionDict[accFlankDict[queries][items][:-1]].split('\t')[1]) end=int(positionDict[accFlankDict[queries][items][:-1]].split('\t')[0]) if queries in acc_CGF_Dict: info=acc_CGF_Dict[queries] else: info='not_found'+'\t'+'not_found'+'\t'+'not_found' print(species, lengths, qStrand, nStrand, family, startPos-start, startPos-end, end, start, ids, info, sep='\t', file=opOut) nP=startPos-start pP=startPos-end nPos.append(nP) pPos.append(pP) print('\n\n', file=opOut) windowMost=round(((max(pPos)+abs(min(nPos))+1)*4)/100) widthM=(windowMost*3)+500 heightM=int(newQ)*20 canvas = Canvas(master, width=widthM,height=heightM,background='white', scrollregion=(0,0,round(widthM*2.5),round(heightM*2.5))) hbar=Scrollbar(master,orient=HORIZONTAL) hbar.pack(side=BOTTOM,fill=X) hbar.config(command=canvas.xview) vbar=Scrollbar(master,orient=VERTICAL) vbar.pack(side=RIGHT,fill=Y) vbar.config(command=canvas.yview) canvas.config(xscrollcommand=hbar.set, yscrollcommand=vbar.set) canvas.pack(side=LEFT,expand=True,fill=BOTH) def operonFamily(item): if item==0: return ' ' elif item==center: return ' ' elif item==noProt: return ' ' elif item==noProtP: return ' ' elif item==noColor: return ' ' else: return item eg1=open(args.out_prefix+'_operon.tsv','r').read() egs=eg1.split("\n\n\n\n") line_pos_y=0 for eg in egs: if eg!='': coln=0 entries=eg.splitlines() ndoms=len(entries) ptnstats=entries[0].split("\t") #c2 org=ptnstats[0][:ptnstats[0].index('|')]+ptnstats[0][ptnstats[0].index('|'):].replace('_',' ') textspace=widthM/2 line_pos_y=line_pos_y+16-round(postscriptSize(newQ)) half_dom_height=5-round(postscriptSize(newQ)) text = canvas.create_text(textspace/2-textspace/8,line_pos_y, text=org, fill="#404040", font=myFont12) for entry in entries: items=entry.split("\t") aln_start=round(int(items[5])*4/100) aln_end=round(int(items[6])*4/100) strandType=items[3] dom1_name=int(items[4]) dom1_len=(aln_end-aln_start) oL80=round(dom1_len*80/100) dom1_start=aln_start+textspace dom1_end=dom1_len+dom1_start if strandType=='+': rect = canvas.create_polygon(dom1_start, line_pos_y+half_dom_height, dom1_start, line_pos_y-half_dom_height,dom1_start+oL80, line_pos_y-half_dom_height, dom1_end, line_pos_y, dom1_start+oL80, line_pos_y+half_dom_height,fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) else: rect = canvas.create_polygon(dom1_end-oL80, line_pos_y+half_dom_height, dom1_start, line_pos_y, dom1_end-oL80, line_pos_y-half_dom_height,dom1_end, line_pos_y-half_dom_height, dom1_end, line_pos_y+half_dom_height, fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) textd1 = canvas.create_text(dom1_start+(dom1_len/2),line_pos_y, text=operonFamily(dom1_name), font=myFont7) coln=coln+1 retval = canvas.postscript(file=args.out_prefix+"_flankgenes.ps", height=heightM, width=widthM, colormode="color") ##TAGs egsList=[] queryNameList=set() family_Query_set=set() querySPDict={} querySPSDict={} fgInfoDict={}# WP_090521055.1#293|9:7:0 WP_090521058.1#+ 0 954:1322 for Line in egs: if Line!='': FlankSet=Line.split('\n') egsList.append(FlankSet) fgTotal=len(FlankSet) count=0 for item in FlankSet: count+=1 queryACC=item.split('\t')[0].split('#')[0] querySerial=item.split('\t')[9].split('#')[1] fgACC=item.split('\t')[9].split('#')[0] strandPN=str(item.split('\t')[3]) fgFamily=int(item.split('\t')[4]) fgStart=int(item.split('\t')[5]) fgEnd=int(item.split('\t')[6]) ##chayanChange if queryACC==fgACC: family_Query_set.add(fgFamily) queryACCnum='' if queryACC==fgACC: queryACCnum=str(count) else: queryACCnum=str(0) queryNameList.add(str(queryACC+'#'+str(querySerial))) fgInfoDict[str(queryACC+'#'+str(querySerial)+'|'+str(fgTotal)+':'+str(count)+':'+str(queryACCnum))]= fgACC+'#'+strandPN+'\t'+str(fgFamily)+'\t'+str(fgStart)+':'+str(fgEnd) querySPDict[str(queryACC+'#'+str(querySerial)+'|'+str(fgTotal)+':'+str(count)+':'+str(queryACCnum))]=item.split('\t')[0] querySPSDict[str(queryACC+'#'+str(querySerial))]=item.split('\t')[0] queryNameListDict={} strandListDict={} AccessionNameListDict={} FamListDict={} posListDict={} for item in queryNameList: queryNameList=[] AccessionNameList=[] strandList=[] FamList=[] posList=[] for query in fgInfoDict: if item==query.split('|')[0]: queryNameList.append(query) strandList.append(fgInfoDict[query].split('\t')[0].split('#')[1]) FamList.append(fgInfoDict[query].split('\t')[1]) posList.append(fgInfoDict[query].split('\t')[2]) AccessionNameList.append(fgInfoDict[query].split('\t')[0].split('#')[0]) queryNameListDict[item]=queryNameList strandListDict[item]=strandList AccessionNameListDict[item]=AccessionNameList FamListDict[item]=FamList posListDict[item]=posList def continuousVerifyCheck(item): strings=';'.join(map(str,item)) splitStrings=strings.split(';') listC=[] for item in splitStrings: listC.append(int(item)) #print (sorted(listC), list(range(min(listC), max(listC)+1))) if sorted(listC) == list(range(min(listC), max(listC)+1)): return strings.split(';') sameStrandWindowDict={} noToxDict_dis={} startContig_dis={} endContig_dis={} for keys in queryNameListDict: query=keys.split('#')[0] mainPoint=AccessionNameListDict[keys].index(query) LengthOfFlankFound=len(AccessionNameListDict[keys]) if mainPoint!=0: #Not starting of Contig if mainPoint!=LengthOfFlankFound-1: #Not end of Contig numList=[] #Window size of FlankGenes for num in range(LengthOfFlankFound): numList.append(num) sameStrand=[] for x in range(LengthOfFlankFound): if strandListDict[keys][mainPoint]==strandListDict[keys][x]: sameStrand.append(x) diffStrand=[] for y in range(LengthOfFlankFound): if strandListDict[keys][mainPoint]!=strandListDict[keys][y]: diffStrand.append(y) #print(query, mainPoint, LengthOfFlankFound, sameStrand, diffStrand) sameStrandWindowD=[] sameStrandWindowU=[] if mainPoint in sameStrand: sameStrandWindowD.append(mainPoint) if mainPoint+1 in sameStrand or mainPoint+1 in diffStrand: GapStart=int(posListDict[keys][mainPoint].split(':')[1]) GapEnd=int(posListDict[keys][mainPoint+1].split(':')[0]) difference=(GapEnd-GapStart)-1 if int(gappyness)>int(difference) or int(gappyness)==int(difference): if int(FamListDict[keys][mainPoint+1])!=0:#and int(FamListDict[keys][mainPoint+1])!=int(FamListDict[keys][mainPoint]): sameStrandWindowD.append(mainPoint+1) #print(keys,mainPoint, LengthOfFlankFound, strandListDict[keys],posListDict[keys][mainPoint], posListDict[keys][mainPoint+1], difference) if mainPoint+2 in sameStrand or mainPoint+2 in diffStrand: GapStart2=int(posListDict[keys][mainPoint+1].split(':')[1]) GapEnd2=int(posListDict[keys][mainPoint+2].split(':')[0]) difference2=(GapEnd2-GapStart2)-1 if int(gappyness)>int(difference2) or int(gappyness)==int(difference2): if int(FamListDict[keys][mainPoint+2])!=0: sameStrandWindowD.append(mainPoint+2) #print(keys,mainPoint, LengthOfFlankFound, strandListDict[keys],posListDict[keys][mainPoint+1], posListDict[keys][mainPoint+2], difference2) if mainPoint-1 in sameStrand or mainPoint-1 in diffStrand: GapStart4=int(posListDict[keys][mainPoint-1].split(':')[1]) GapEnd4=int(posListDict[keys][mainPoint].split(':')[0]) difference4=(GapEnd4-GapStart4)-1 if int(gappyness)>int(difference4) or int(gappyness)==int(difference4): if int(FamListDict[keys][mainPoint-1])!=0 :#and int(FamListDict[keys][mainPoint-1])!=int(FamListDict[keys][mainPoint]): sameStrandWindowU.append(mainPoint-1) #print(keys,mainPoint, LengthOfFlankFound, strandListDict[keys],posListDict[keys][mainPoint-1], posListDict[keys][mainPoint], difference4) if mainPoint-2 in sameStrand or mainPoint-2 in diffStrand: GapStart5=int(posListDict[keys][mainPoint-2].split(':')[1]) GapEnd5=int(posListDict[keys][mainPoint-1].split(':')[0]) difference5=(GapEnd5-GapStart5)-1 if int(gappyness)>int(difference5) or int(gappyness)==int(difference5): if int(FamListDict[keys][mainPoint-2])!=0: sameStrandWindowU.append(mainPoint-2) #print(keys,mainPoint, LengthOfFlankFound, strandListDict[keys],posListDict[keys][mainPoint-2], posListDict[keys][mainPoint-1], difference5) if continuousVerifyCheck(sorted(sameStrandWindowU+sameStrandWindowD)): if len(continuousVerifyCheck(sorted(sameStrandWindowU+sameStrandWindowD)))>1: sameStrandWindowDict[keys+':'+str(continuousVerifyCheck(sorted(sameStrandWindowU+sameStrandWindowD)).index(str(mainPoint)))]=continuousVerifyCheck(sorted(sameStrandWindowU+sameStrandWindowD)) #print(keys,mainPoint, LengthOfFlankFound, strandListDict[keys], sameStrand, continuousVerifyCheck(sorted(sameStrandWindowU+sameStrandWindowD)), FamListDict[keys]) else: noToxDict_dis[keys]='No Cluster found or '+ 'Gap >'+str(gappyness)+' or Strand Difference' else: endContig_dis[keys]='Contig Error: Query is in the end of Contig' else: startContig_dis[keys]='Contig Error: Query is in the start of contig' OperonFamilyDict={} for keys in sameStrandWindowDict: opFamList=[] for item in sameStrandWindowDict[keys]: opFamList.append(str(FamListDict[keys[:-2]][int(item)])) OperonFamilyDict[keys]=opFamList #print(OperonFamilyDict, 'OperonFamilyDict') #'WP_127015184.1#37:1': ['36', '47', '4', '35'] queryFamilySet=set() for keys in OperonFamilyDict: queryFamilySet.add(int(OperonFamilyDict[keys][int(keys[-1:])])) #print(keys, OperonFamilyDict[keys]) aattDict_dis={} nocoding_dis={} probableTApairFamDict={} probableTApairFamPosDict={} for keys in OperonFamilyDict: taPairList=[] taPairPosList=[] for i in range (len(OperonFamilyDict[keys])-1): for j in range (1,len(OperonFamilyDict[keys])): if j==i+1: if i==int(keys[-1]) or j==int(keys[-1]): if int(OperonFamilyDict[keys][i]) in queryFamilySet and int(OperonFamilyDict[keys][j]) in queryFamilySet: aattDict_dis[keys.split(':')[0]]='Pair Error: Paired with homolog cluster' pass #if condition like 'Toxin(518)-Toxin(518)' we discard else: if int(OperonFamilyDict[keys][i]) in queryFamilySet or int(OperonFamilyDict[keys][j]) in queryFamilySet: #if one of them in queryFamily if int(OperonFamilyDict[keys][i])<=max(queryFamilySet) and int(OperonFamilyDict[keys][j])<=max(queryFamilySet): #not pseudo/noncoding rna probableTA=str(OperonFamilyDict[keys][i])+'.'+str(OperonFamilyDict[keys][j]) probableTAPos=str(i)+'.'+str(j) taPairList.append(probableTA) taPairPosList.append(probableTAPos) else: nocoding_dis[keys.split(':')[0]]='Pair Error: Non coding RNA' #else: #print(keys) if len(taPairList)>0: probableTApairFamDict[keys]=taPairList probableTApairFamPosDict[keys]=taPairPosList #else: #print(keys, OperonFamilyDict[keys], taPairList) probableOperonFamDict={} probableOperonFamSet=set() probableOperonList=[] for keys in OperonFamilyDict: operonList=[] if len(OperonFamilyDict[keys])>2: for i in range (len(OperonFamilyDict[keys])-2): for j in range (1,len(OperonFamilyDict[keys])-1): for k in range (2,len(OperonFamilyDict[keys])): if j==i+1 and k==j+1: #we need to get operon that contains query pair if int(OperonFamilyDict[keys][i]) in queryFamilySet or int(OperonFamilyDict[keys][j]) in queryFamilySet \ or int(OperonFamilyDict[keys][k]) in queryFamilySet : probableOperon=str(OperonFamilyDict[keys][i])+'.'+str(OperonFamilyDict[keys][j])+'.'+\ str(OperonFamilyDict[keys][k]) operonList.append(probableOperon) probableOperonList.append(probableOperon) probableOperonFamSet.add(probableOperon) if len(operonList)>0: probableOperonFamDict[keys]=operonList else: #print(keys) noToxDict_dis[keys.split(':')[0]]='No Cluster found or '+ 'Gap >'+str(gappyness)+' or Strand Difference' def pseudoCheck(item): itemSplit=item.split('.') if int((max(itemSplit)))>max(queryFamilySet): return 'pseudoFound' operonOccuranceDict={} #operons that are conserved more than one time trueOperonOccuranceDict={} for item in probableOperonFamSet: if pseudoCheck(item)!='pseudoFound': #remove pseudogenes/noncoding containing operons keyset=set() for keys in probableOperonFamDict: if item in probableOperonFamDict[keys]: keyset.add(keys.split(':')[0]) if len(keyset)>1: #operons that are conserved more than one time operonOccuranceDict[item]=keyset filteredTApairPosFamily={} filteredTApairFamily={} filteredTApairSet=set() for items in probableTApairFamDict: Fpset=set() #rev1 for item in probableTApairFamDict[items]: for operons in operonOccuranceDict: taItem=item.split('.') operonItem1=operons.split('.')[0:2] operonItem2=operons.split('.')[1:3] #rev1 operonItem3=operons.split('.')[2:4] if taItem==operonItem1 or taItem==operonItem2: #rev1 or taItem==operonItem3: if items.split(':')[0] in operonOccuranceDict[operons]: Fpset.add(items) #print(items, probableTApairFamPosDict[items], probableTApairFamDict[items], operons, probableOperonList.count(operons), 'FP') if items not in Fpset: #print(items, probableTApairFamPosDict[items], probableTApairFamDict[items], operons, probableOperonList.count(operons), 'TP') filteredTApairFamily[items]=probableTApairFamDict[items] #'WP_057732687.1#38:2': ['2.518', '518.9'], filteredTApairPosFamily[items]=probableTApairFamPosDict[items] #'WP_015310665.1#174:1': ['0.1', '1.2'] for elements in probableTApairFamDict[items]: filteredTApairSet.add(elements) def getTA_ACCpair(pair, accessionSerial): if accessionSerial in filteredTApairFamily: if accessionSerial in probableTApairFamDict: for pairVar in probableTApairFamDict[accessionSerial]: if pairVar==pair: splitPair=pair.split('.') pairIndex=probableTApairFamPosDict[accessionSerial][probableTApairFamDict[accessionSerial].index(pairVar)] #print('new',pairVar, pairIndex)#new 12.1658 0.1 index1=int(sameStrandWindowDict[accessionSerial][int(pairIndex.split('.')[0])]) index2=int(sameStrandWindowDict[accessionSerial][int(pairIndex.split('.')[1])]) accession1=AccessionNameListDict[accessionSerial.split(':')[0]][index1] accession2=AccessionNameListDict[accessionSerial.split(':')[0]][index2] #print(index1,index2,accession1, accession2) position1=posListDict[accessionSerial.split(':')[0]][index1].split(':')[1] position2=posListDict[accessionSerial.split(':')[0]][index2].split(':')[0] difference=(int(position2)-int(position1))-1 return accession1+'|'+accession2+'\t'+str(difference)+'\t'+splitPair[0]+'|'+splitPair[1] def descriptionFromTA(item): descriptionList=[] itemList=item.split('\t')[0].split('|') for item in itemList: if item in desDict: descriptionList.append(desDict[item]) return '|'.join(map(str,descriptionList)) trueTApairCount={} trueTApairAccession={} for items in filteredTApairSet: accessionSet=set() accessionSet2=set() for keys in filteredTApairFamily: if items in filteredTApairFamily[keys]: accessionSet.add(keys) accessionSet2.add(keys.split(':')[0]) trueTApairAccession[items]=accessionSet #518.50 {'WP_010875036.1#440:2', 'WP_010869490.1#706:3'} trueTApairCount[items]=len(accessionSet2) def contigCheck(accs, accPair, strandDict, accsInSPList): if accs in accPair: accPairSplit=accPair.split('|') accPairSplit.remove(accs) if strandDict[accsInSPList.index(accs)]==strandDict[accsInSPList.index(accPairSplit[0])]: rangeL=[] for i in range (1,len(accsInSPList)-1): rangeL.append(i) if accsInSPList.index(accPairSplit[0]) in rangeL: return 'P' else: return 'Fc' else: return 'Fs' else: return 'Fx' discard_dis={} twoThree_List=[] tsvAccessionSet=set() ta_Accession=set() operonTA_TXT=[] #with open (args.out_prefix+'_operonTA.txt', 'w') as opTAOut: # print('#Query_Species', 'QueryAccession', 'TA_System', 'AccessopnInPredictedTA-LikeRegion', 'IntergenicSpace', 'ClusterNumber_TA-likeSystem', 'Number_Occurred', 'Conserve(%)', 'Description',sep='\t', file=opTAOut) for item in sorted(trueTApairAccession): #print (item, (trueTApairCount[item]), len(trueTApairCount[item])) for accs in trueTApairAccession[item]: #if accs=='WP_056969168.1#334:2': if contigCheck(accs.split('#')[0], getTA_ACCpair(item, accs).split('\t')[0], strandListDict[accs[:-2]], AccessionNameListDict[accs[:-2]])=='P': #print(accs, item, getTA_ACCpair(item, accs)) if accs.split('#')[0] in getTA_ACCpair(item, accs).split('\t')[0]: pairQuery=accs.split(':')[0]+'\t'+getTA_ACCpair(item, accs).split('\t')[0] twoThree_List.append(pairQuery.split('\t')) tsvAccessionSet.add(querySPSDict[accs.split(':')[0]]) ta_Accession.add(accs.split(':')[0]) #print(querySPSDict[accs.split(':')[0]], accs.split('#')[0], len(item.split('.')), getTA_ACCpair(item, accs), str(trueTApairCount[item])+'/'+str(len(querySPSDict)), round(int(trueTApairCount[item])*100/len(querySPSDict),2), sep='\t', file=opTAOut)#descriptionFromTA(getTA_ACCpair(item, accs)) operonTAInfo=str(querySPSDict[accs.split(':')[0]])+'\t'+str(accs.split('#')[0])+'\t'+str(len(item.split('.')))+'\t'+str(getTA_ACCpair(item, accs))+'\t'+str(trueTApairCount[item])+'/'+str(len(querySPSDict))+'\t'+str(round(int(trueTApairCount[item])*100/len(querySPSDict),2)) operonTAInfosplit=operonTAInfo.split('\t') operonTA_TXT.append(operonTAInfosplit) else: if contigCheck(accs.split('#')[0], getTA_ACCpair(item, accs).split('\t')[0], strandListDict[accs[:-2]], AccessionNameListDict[accs[:-2]])=='Fc': if accs.split('#')[0] in getTA_ACCpair(item, accs).split('\t')[0]: if accs.split(':')[0] not in startContig_dis and endContig_dis and noToxDict_dis and aattDict_dis and nocoding_dis: #print(accs.split(':')[0], 'Fc') discard_dis[accs.split(':')[0]]='Contig Error: Contig starts/ends with predicted TA' if contigCheck(accs.split('#')[0], getTA_ACCpair(item, accs).split('\t')[0], strandListDict[accs[:-2]], AccessionNameListDict[accs[:-2]])=='Fs': if accs.split('#')[0] in getTA_ACCpair(item, accs).split('\t')[0]: if accs.split(':')[0] not in startContig_dis and endContig_dis and noToxDict_dis and aattDict_dis and nocoding_dis: #print(accs.split(':')[0], 'Fs') discard_dis[accs.split(':')[0]]='No Cluster found or '+ 'Gap >'+str(gappyness)+' or Strand Difference' if contigCheck(accs.split('#')[0], getTA_ACCpair(item, accs).split('\t')[0], strandListDict[accs[:-2]], AccessionNameListDict[accs[:-2]])=='Fx': if accs.split('#')[0] in getTA_ACCpair(item, accs).split('\t')[0]: if accs.split(':')[0] not in startContig_dis and endContig_dis and noToxDict_dis and aattDict_dis and nocoding_dis: #print(accs.split(':')[0], 'Fx') discard_dis[accs.split(':')[0]]='NotAcceptable' operonLong_dis={} for item in querySPSDict: if item not in ta_Accession: for element in operonOccuranceDict: if item in operonOccuranceDict[element]: operonLong_dis[item]='Long Conserved Operon' def TA_status(query): if query not in ta_Accession: reasonList=[] if query in startContig_dis: reasonList.append(startContig_dis[query]) if query in endContig_dis: reasonList.append(endContig_dis[query]) if query in noToxDict_dis: reasonList.append(noToxDict_dis[query]) if query in aattDict_dis : reasonList.append(aattDict_dis[query]) if query in nocoding_dis : reasonList.append(nocoding_dis[query]) if query in operonLong_dis: reasonList.append(operonLong_dis[query]) if query in discard_dis: reasonList.append(discard_dis[query]) if len(reasonList)>0: if len(reasonList)==1: return 'notTA_like'+'\t'+reasonList[0] else: return 'notTA_like'+'\t'+'; '.join(map(str,list(set(reasonList)))) else: for elements in filteredTApairPosFamily: if elements.split(':')[0]==query and len(filteredTApairPosFamily[elements])==1: glist=[] for items in twoThree_List: if query==items[0]: glist.append(items[1]) if len(glist)==1: return 'TA_like'+'\t'+'2G' if elements.split(':')[0]==query and len(filteredTApairPosFamily[elements])==2: return 'TA_like'+'\t'+'3G' i=0 discard3Gset=set() with open (args.out_prefix+'_TA_Status_report.txt', 'w') as sTAOut: print('#Serial', 'Query', 'Status', 'Reason', sep='\t', file=sTAOut) for item in querySPSDict: i+=1 print(i, querySPSDict[item], TA_status(item), sep='\t', file=sTAOut) if TA_status(item)=='TA_like'+'\t'+'3G': discard3Gset.add(querySPSDict[item]) #print(discard3Gset) with open (args.out_prefix+'_operonTA.txt', 'w') as opTAOut: print('#Query_Species', 'QueryAccession', 'TA_System', 'AccessopnInPredictedTA-LikeRegion', 'IntergenicSpace', 'ClusterNumber_TA-likeSystem', 'Number_Occurred', 'Conserve(%)', 'Description',sep='\t', file=opTAOut) for item in operonTA_TXT: if item[0] not in discard3Gset: print('\t'.join(map(str,item)), file=opTAOut) with open (args.out_prefix+'_operonTA.tsv', 'w') as opTAtsv: for item in egsList: if item!='': #tsvAccession=item[0].split('\t')[0].split('#')[0]+'#'+item[0].split('\t')[0].split('#')[1].split('_')[0] #print(item[0].split('\t')[0]) if item[0].split('\t')[0] in tsvAccessionSet: if item[0].split('\t')[0] not in discard3Gset: print('\n'.join(item), file=opTAtsv) print("\n\n", file=opTAtsv) windowMost=round(((max(pPos)+abs(min(nPos))+1)*4)/100) widthM=(windowMost*3)+500 heightM=int(newQ)*20 #aheightM=heightM*1.3 from tkinter import * master = Tk() canvas = Canvas(master, width=widthM,height=heightM,background='white', scrollregion=(0,0,round(widthM*2.5),round(heightM*2.5))) hbar=Scrollbar(master,orient=HORIZONTAL) hbar.pack(side=BOTTOM,fill=X) hbar.config(command=canvas.xview) vbar=Scrollbar(master,orient=VERTICAL) vbar.pack(side=RIGHT,fill=Y) vbar.config(command=canvas.yview) #canvas.config(width=1500,height=1000) canvas.config(xscrollcommand=hbar.set, yscrollcommand=vbar.set) canvas.pack(side=LEFT,expand=True,fill=BOTH) def operonFamily(item): if item==0: return ' ' elif item==center: return ' ' elif item==noProt: return ' ' elif item==noProtP: return ' ' elif item==noColor: return ' ' else: return item egTA=open(args.out_prefix+'_operonTA.tsv','r').read() egTAs=egTA.split("\n\n\n\n") line_pos_y=0 for eg in egTAs: if eg!='': coln=0 entries=eg.splitlines() ndoms=len(entries) ptnstats=entries[0].split("\t") org=ptnstats[0].replace("_"," ") textspace=widthM/2 line_pos_y=line_pos_y+16-round(postscriptSize(newQ)) half_dom_height=5-round(postscriptSize(newQ)) text = canvas.create_text(textspace/2,line_pos_y, text=org, fill="#404040", font=("Arial", "12")) for entry in entries: items=entry.split("\t") aln_start=round(int(items[5])*4/100) aln_end=round(int(items[6])*4/100) strandType=items[3] dom1_name=int(items[4]) dom1_len=(aln_end-aln_start) oL80=round(dom1_len*80/100) dom1_start=aln_start+textspace dom1_end=dom1_len+dom1_start if strandType=='+': rect = canvas.create_polygon(dom1_start, line_pos_y+half_dom_height, dom1_start, line_pos_y-half_dom_height,dom1_start+oL80, line_pos_y-half_dom_height, dom1_end, line_pos_y, dom1_start+oL80, line_pos_y+half_dom_height,fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) else: rect = canvas.create_polygon(dom1_end-oL80, line_pos_y+half_dom_height, dom1_start, line_pos_y, dom1_end-oL80, line_pos_y-half_dom_height,dom1_end, line_pos_y-half_dom_height, dom1_end, line_pos_y+half_dom_height, fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) textd1 = canvas.create_text(dom1_start+(dom1_len/2),line_pos_y, text=operonFamily(dom1_name), font=("Arial", "7")) coln=coln+1 retval2 = canvas.postscript(file=args.out_prefix+"_flankgenesTA.ps", height=heightM, width=widthM, colormode="color") #disqualified with open (args.out_prefix+'_operonTAdisqualified.tsv', 'w') as opTAtsvd: for item in egsList: if item!='': #tsvAccession=item[0].split('\t')[0].split('#')[0]+'#'+item[0].split('\t')[0].split('#')[1].split('_')[0] #print(item[0].split('\t')[0]) if item[0].split('\t')[0] not in tsvAccessionSet: print('\n'.join(item), file=opTAtsvd) print("\n\n", file=opTAtsvd) windowMost=round(((max(pPos)+abs(min(nPos))+1)*4)/100) widthM=(windowMost*3)+500 heightM=int(newQ)*20 #aheightM=heightM*1.3 from tkinter import * master = Tk() canvas = Canvas(master, width=widthM,height=heightM,background='white', scrollregion=(0,0,round(widthM*2.5),round(heightM*2.5))) hbar=Scrollbar(master,orient=HORIZONTAL) hbar.pack(side=BOTTOM,fill=X) hbar.config(command=canvas.xview) vbar=Scrollbar(master,orient=VERTICAL) vbar.pack(side=RIGHT,fill=Y) vbar.config(command=canvas.yview) #canvas.config(width=1500,height=1000) canvas.config(xscrollcommand=hbar.set, yscrollcommand=vbar.set) canvas.pack(side=LEFT,expand=True,fill=BOTH) def operonFamily(item): if item==0: return ' ' elif item==center: return ' ' elif item==noProt: return ' ' elif item==noProtP: return ' ' elif item==noColor: return ' ' else: return item egTAD=open(args.out_prefix+'_operonTAdisqualified.tsv','r').read() egTADs=egTAD.split("\n\n\n\n") line_pos_y=0 for eg in egTADs: if eg!='': coln=0 entries=eg.splitlines() ndoms=len(entries) ptnstats=entries[0].split("\t") org=ptnstats[0].replace("_"," ") textspace=widthM/2 line_pos_y=line_pos_y+16-round(postscriptSize(newQ)) half_dom_height=5-round(postscriptSize(newQ)) text = canvas.create_text(textspace/2,line_pos_y, text=org, fill="#404040", font=("Arial", "12")) for entry in entries: items=entry.split("\t") aln_start=round(int(items[5])*4/100) aln_end=round(int(items[6])*4/100) strandType=items[3] dom1_name=int(items[4]) dom1_len=(aln_end-aln_start) oL80=round(dom1_len*80/100) dom1_start=aln_start+textspace dom1_end=dom1_len+dom1_start if strandType=='+': rect = canvas.create_polygon(dom1_start, line_pos_y+half_dom_height, dom1_start, line_pos_y-half_dom_height,dom1_start+oL80, line_pos_y-half_dom_height, dom1_end, line_pos_y, dom1_start+oL80, line_pos_y+half_dom_height,fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) else: rect = canvas.create_polygon(dom1_end-oL80, line_pos_y+half_dom_height, dom1_start, line_pos_y, dom1_end-oL80, line_pos_y-half_dom_height,dom1_end, line_pos_y-half_dom_height, dom1_end, line_pos_y+half_dom_height, fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) textd1 = canvas.create_text(dom1_start+(dom1_len/2),line_pos_y, text=operonFamily(dom1_name), font=("Arial", "7")) coln=coln+1 retval3 = canvas.postscript(file=args.out_prefix+"_flankgenesTAdisqualified.ps", height=heightM, width=widthM, colormode="color") if args.tree:###Tree Command with ETE### tree_file= args.out_prefix+'_tree.fasta' if args.cpu: tree_command="ete3 build -a %s -o %s --nochecks --clearall -w mafft_default-trimal01-none-fasttree_full --rename-dup-seqnames --cpu %s" %(tree_file, tree_file[:-6], core) else: tree_command="ete3 build -a %s -o %s --nochecks --clearall -w mafft_default-trimal01-none-fasttree_full --rename-dup-seqnames" %(tree_file, tree_file[:-6]) os.system(tree_command) from ete3 import Tree, SeqMotifFace, TreeStyle, add_face_to_node def normalize_strandView(item): #Strand view change if item=='+': return '>' else: return '<' def familyView(item): #Strand view change if item==0: return ' ' elif item==center: return ' ' elif item==noProt: return ' ' elif item==noProtP: return ' ' elif item==noColor: return ' ' else: return str(item) seqMult=((maxs)*2)+1 seq = ("XXXXXXXXXXXXX--"*seqMult) startDict={} udList=[] for ud in range (mins, maxs+1, 1): udList.append(ud) sList=[] for sa in range(1, 15*seqMult, 15): sList.append(sa) for ln in range(len(udList)): startDict[udList[ln]]=sList[ln] nwTree='' motifDict={} motifDict_2={} if os.path.isfile(args.out_prefix+'_tree/mafft_default-trimal01-none-fasttree_full/'+args.out_prefix+'_tree.fasta.final_tree.nw') == True: with open(args.out_prefix+'_tree/mafft_default-trimal01-none-fasttree_full/'+args.out_prefix+'_tree.fasta.final_tree.nw', 'r') as treeIn: for line in treeIn: nwTree=line for items in line.replace('(','').replace(')', '').replace(';', '').replace(',','\t').split('\t'): item=items.split('|')[0] simple_motifs=[] simple_motifs_2=[] for keys in sorted(startDict): if keys in accFlankDict[item]: simple_motifs_s = [startDict[keys], startDict[keys]+13, normalize_strandView(accFlankDict[item][keys][-1]), None, size, outliner(colorDict[familyDict[accFlankDict[item][keys][:-1].split('#')[0]]]), 'rgradient:'+colorDict[familyDict[accFlankDict[item][keys][:-1].split('#')[0]]], "arial|"+fsize+"|black|"+familyView(familyDict[accFlankDict[item][keys][:-1].split('#')[0]])] simple_motifs.append(simple_motifs_s) simple_motifs_2_s = [startDict[keys], startDict[keys]+13, normalize_strandView(accFlankDict[item][keys][-1]), None, size, outliner(colorDict[familyDict[accFlankDict[item][keys][:-1].split('#')[0]]]),colorDict[familyDict[accFlankDict[item][keys][:-1].split('#')[0]]], "arial|"+fsize+"|black|"] simple_motifs_2.append(simple_motifs_2_s) else: simple_motifs_s = [startDict[keys], startDict[keys]+13, '[]', None, size, '#eeeeee', 'rgradient:'+'#ffffff', "arial|"+fsize+"|black|"] simple_motifs.append(simple_motifs_s) simple_motifs_2_s = [startDict[keys], startDict[keys]+13, '[]', None, size, '#eeeeee', '#ffffff', "arial|"+fsize+"|black|"] simple_motifs_2.append(simple_motifs_2_s) motifDict[items[:items.index(':')]]=simple_motifs motifDict_2[items[:items.index(':')]]=simple_motifs_2 else: print('> ETE3 failed to create tree due to lack of valid protein accesions, at least 2 required !') sys.exit() def get_example_tree(): # Create a random tree and add to each leaf a random set of motifs # from the original set t= Tree(nwTree) for item in nwTree.replace('(','').replace(')', '').replace(';', '').replace(',','\t').split('\t'): seqFace = SeqMotifFace(seq, motifs=motifDict[item[:item.index(':')]], seq_format="-", gap_format="blank") (t & item[:item.index(':')]).add_face(seqFace, 0, "aligned") t.ladderize() return t def get_example_tree_2(): # Create a random tree and add to each leaf a random set of motifs # from the original set t= Tree(nwTree) for item in nwTree.replace('(','').replace(')', '').replace(';', '').replace(',','\t').split('\t'): seqFace2 = SeqMotifFace(seq, motifs=motifDict_2[item[:item.index(':')]], seq_format="-", gap_format="blank") (t & item[:item.index(':')]).add_face(seqFace2, 0, "aligned") t.ladderize() return t if __name__ == '__main__': t = get_example_tree() ts = TreeStyle() ts.tree_width = 300 ts.show_branch_support = True if args.tree_order: t.write(outfile=args.out_prefix+'_ladderTree.nw') t.render(args.out_prefix+"_flankgenes_1.svg",tree_style=ts) else: t.render(args.out_prefix+"_flankgenes_1.svg",tree_style=ts) if __name__ == '__main__': t = get_example_tree_2() ts = TreeStyle() ts.tree_width = 300 ts.show_branch_support = True if args.tree_order: t.write(outfile=args.out_prefix+'_ladderTree.nw') t.render(args.out_prefix+"_flankgenes_2.svg", tree_style=ts) else: t.render(args.out_prefix+"_flankgenes_2.svg", tree_style=ts) if args.tree and args.tree_order: # Queries in postscript file will be presented as tree order treeOrderList=[] with open(args.out_prefix+'_ladderTree.nw', 'r') as laddertreeIn: for line in laddertreeIn: for items in line.replace('(','').replace(')', '').replace(';', '').replace(',','\t').split('\t'): item=items.split('|')[0] treeOrderList.append(item) ntPos=[] ptPos=[] with open(args.out_prefix+'_TreeOrder_operon.tsv', 'w') as opOut: for queries in treeOrderList: for items in sorted(accFlankDict[queries]): if queryStrand[queries]=='+': ids=accFlankDict[queries][items][:-1] lengths=LengthDict[accFlankDict[queries][items][:-1]] species=queries+'|'+remBadChar(speciesDict[queries]) qStrand=queryStrand[queries] nStrand=accFlankDict[queries][items][-1] family=familyDict[accFlankDict[queries][items][:-1].split('#')[0]] startPos=int(positionDict[accFlankDict[queries][0][:-1]].split('\t')[0])-1 start=int(positionDict[accFlankDict[queries][items][:-1]].split('\t')[0]) end=int(positionDict[accFlankDict[queries][items][:-1]].split('\t')[1]) if queries in acc_CGF_Dict: info=acc_CGF_Dict[queries] else: info='not_found'+'\t'+'not_found'+'\t'+'not_found' print(species, lengths, qStrand, nStrand, family, start-startPos, end-startPos, start, end, ids, info, sep='\t', file=opOut) nP=start-startPos pP=end-startPos ntPos.append(nP) ptPos.append(pP) else: ids=accFlankDict[queries][items][:-1] lengths=LengthDict[accFlankDict[queries][items][:-1]] species=queries+'|'+remBadChar(speciesDict[queries]) qStrand=queryStrand[queries] nStrand=accFlankDict[queries][items][-1] family=familyDict[accFlankDict[queries][items][:-1].split('#')[0]] startPos=int(positionDict[accFlankDict[queries][0][:-1]].split('\t')[1])+1 start=int(positionDict[accFlankDict[queries][items][:-1]].split('\t')[1]) end=int(positionDict[accFlankDict[queries][items][:-1]].split('\t')[0]) if queries in acc_CGF_Dict: info=acc_CGF_Dict[queries] else: info='not_found'+'\t'+'not_found'+'\t'+'not_found' print(species, lengths, qStrand, nStrand, family, startPos-start, startPos-end, end, start, ids, info, sep='\t', file=opOut) nP=startPos-start pP=startPos-end ntPos.append(nP) ptPos.append(pP) print('\n\n', file=opOut) windowMost=round(((max(ptPos)+abs(min(ntPos))+1)*4)/100) widthM=(windowMost*3)+500 heightM=int(newQ)*20 canvas = Canvas(master, width=widthM,height=heightM,background='white', scrollregion=(0,0,round(widthM*2.5),round(heightM*2.5))) hbar=Scrollbar(master,orient=HORIZONTAL) hbar.pack(side=BOTTOM,fill=X) hbar.config(command=canvas.xview) vbar=Scrollbar(master,orient=VERTICAL) vbar.pack(side=RIGHT,fill=Y) vbar.config(command=canvas.yview) canvas.config(xscrollcommand=hbar.set, yscrollcommand=vbar.set) canvas.pack(side=LEFT,expand=True,fill=BOTH) def operonFamily(item): if item==0: return ' ' elif item==center: return ' ' elif item==noProt: return ' ' elif item==noProtP: return ' ' elif item==noColor: return ' ' else: return item eg1=open(args.out_prefix+'_TreeOrder_operon.tsv','r').read() egs=eg1.split("\n\n\n\n") line_pos_y=0 for eg in egs: if eg!='': coln=0 entries=eg.splitlines() ndoms=len(entries) ptnstats=entries[0].split("\t") org=ptnstats[0][:ptnstats[0].index('|')]+ptnstats[0][ptnstats[0].index('|'):].replace('_',' ') textspace=widthM/2 line_pos_y=line_pos_y+16-round(postscriptSize(newQ)) half_dom_height=5-round(postscriptSize(newQ)) text = canvas.create_text(textspace/2-textspace/8,line_pos_y, text=org, fill="#404040", font=myFont12) for entry in entries: items=entry.split("\t") aln_start=round(int(items[5])*4/100) aln_end=round(int(items[6])*4/100) strandType=items[3] dom1_name=int(items[4]) dom1_len=(aln_end-aln_start) oL80=round(dom1_len*80/100) dom1_start=aln_start+textspace dom1_end=dom1_len+dom1_start if strandType=='+': rect = canvas.create_polygon(dom1_start, line_pos_y+half_dom_height, dom1_start, line_pos_y-half_dom_height,dom1_start+oL80, line_pos_y-half_dom_height, dom1_end, line_pos_y, dom1_start+oL80, line_pos_y+half_dom_height,fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) else: rect = canvas.create_polygon(dom1_end-oL80, line_pos_y+half_dom_height, dom1_start, line_pos_y, dom1_end-oL80, line_pos_y-half_dom_height,dom1_end, line_pos_y-half_dom_height, dom1_end, line_pos_y+half_dom_height, fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) textd1 = canvas.create_text(dom1_start+(dom1_len/2),line_pos_y, text=operonFamily(dom1_name), font=myFont7) coln=coln+1 retval = canvas.postscript(file=args.out_prefix+"_treeOrder_flankgenes.ps", height=heightM, width=widthM, colormode="color") #TAGs egsList=[] queryNameList=set() family_Query_set=set() querySPDict={} querySPSDict={} fgInfoDict={}# WP_090521055.1#293|9:7:0 WP_090521058.1#+ 0 954:1322 for Line in egs: if Line!='': FlankSet=Line.split('\n') egsList.append(FlankSet) fgTotal=len(FlankSet) count=0 for item in FlankSet: count+=1 queryACC=item.split('\t')[0].split('#')[0] querySerial=item.split('\t')[9].split('#')[1] fgACC=item.split('\t')[9].split('#')[0] strandPN=str(item.split('\t')[3]) fgFamily=int(item.split('\t')[4]) fgStart=int(item.split('\t')[5]) fgEnd=int(item.split('\t')[6]) ##chayanChange if queryACC==fgACC: family_Query_set.add(fgFamily) queryACCnum='' if queryACC==fgACC: queryACCnum=str(count) else: queryACCnum=str(0) queryNameList.add(str(queryACC+'#'+str(querySerial))) fgInfoDict[str(queryACC+'#'+str(querySerial)+'|'+str(fgTotal)+':'+str(count)+':'+str(queryACCnum))]= fgACC+'#'+strandPN+'\t'+str(fgFamily)+'\t'+str(fgStart)+':'+str(fgEnd) querySPDict[str(queryACC+'#'+str(querySerial)+'|'+str(fgTotal)+':'+str(count)+':'+str(queryACCnum))]=item.split('\t')[0] querySPSDict[str(queryACC+'#'+str(querySerial))]=item.split('\t')[0] #print(queryACC+'#'+querySerial, queryACCnum, fgTotal, count, fgACC, fgFamily, fgStart, fgEnd, sep='\t') #print(fgInfoDict) queryNameListDict={} strandListDict={} AccessionNameListDict={} FamListDict={} posListDict={} for item in queryNameList: queryNameList=[] AccessionNameList=[] strandList=[] FamList=[] posList=[] for query in fgInfoDict: if item==query.split('|')[0]: queryNameList.append(query) strandList.append(fgInfoDict[query].split('\t')[0].split('#')[1]) FamList.append(fgInfoDict[query].split('\t')[1]) posList.append(fgInfoDict[query].split('\t')[2]) AccessionNameList.append(fgInfoDict[query].split('\t')[0].split('#')[0]) queryNameListDict[item]=queryNameList strandListDict[item]=strandList AccessionNameListDict[item]=AccessionNameList FamListDict[item]=FamList posListDict[item]=posList #print(item, queryNameList, AccessionNameList, strandList, FamList) def continuousVerifyCheck(item): strings=';'.join(map(str,item)) splitStrings=strings.split(';') listC=[] for item in splitStrings: listC.append(int(item)) #print (sorted(listC), list(range(min(listC), max(listC)+1))) if sorted(listC) == list(range(min(listC), max(listC)+1)): return strings.split(';') sameStrandWindowDict={} noToxDict_dis={} startContig_dis={} endContig_dis={} for keys in queryNameListDict: query=keys.split('#')[0] mainPoint=AccessionNameListDict[keys].index(query) LengthOfFlankFound=len(AccessionNameListDict[keys]) if mainPoint!=0: #Not starting of Contig if mainPoint!=LengthOfFlankFound-1: #Not end of Contig numList=[] #Window size of FlankGenes for num in range(LengthOfFlankFound): numList.append(num) sameStrand=[] for x in range(LengthOfFlankFound): if strandListDict[keys][mainPoint]==strandListDict[keys][x]: sameStrand.append(x) diffStrand=[] for y in range(LengthOfFlankFound): if strandListDict[keys][mainPoint]!=strandListDict[keys][y]: diffStrand.append(y) #print(query, mainPoint, LengthOfFlankFound, sameStrand, diffStrand) sameStrandWindowD=[] sameStrandWindowU=[] if mainPoint in sameStrand: sameStrandWindowD.append(mainPoint) if mainPoint+1 in sameStrand or mainPoint+1 in diffStrand: GapStart=int(posListDict[keys][mainPoint].split(':')[1]) GapEnd=int(posListDict[keys][mainPoint+1].split(':')[0]) difference=(GapEnd-GapStart)-1 if int(gappyness)>int(difference) or int(gappyness)==int(difference): if int(FamListDict[keys][mainPoint+1])!=0:#and int(FamListDict[keys][mainPoint+1])!=int(FamListDict[keys][mainPoint]): sameStrandWindowD.append(mainPoint+1) #print(keys,mainPoint, LengthOfFlankFound, strandListDict[keys],posListDict[keys][mainPoint], posListDict[keys][mainPoint+1], difference) if mainPoint+2 in sameStrand or mainPoint+2 in diffStrand: GapStart2=int(posListDict[keys][mainPoint+1].split(':')[1]) GapEnd2=int(posListDict[keys][mainPoint+2].split(':')[0]) difference2=(GapEnd2-GapStart2)-1 if int(gappyness)>int(difference2) or int(gappyness)==int(difference2): if int(FamListDict[keys][mainPoint+2])!=0: sameStrandWindowD.append(mainPoint+2) #print(keys,mainPoint, LengthOfFlankFound, strandListDict[keys],posListDict[keys][mainPoint+1], posListDict[keys][mainPoint+2], difference2) if mainPoint-1 in sameStrand or mainPoint-1 in diffStrand: GapStart4=int(posListDict[keys][mainPoint-1].split(':')[1]) GapEnd4=int(posListDict[keys][mainPoint].split(':')[0]) difference4=(GapEnd4-GapStart4)-1 if int(gappyness)>int(difference4) or int(gappyness)==int(difference4): if int(FamListDict[keys][mainPoint-1])!=0 :#and int(FamListDict[keys][mainPoint-1])!=int(FamListDict[keys][mainPoint]): sameStrandWindowU.append(mainPoint-1) #print(keys,mainPoint, LengthOfFlankFound, strandListDict[keys],posListDict[keys][mainPoint-1], posListDict[keys][mainPoint], difference4) if mainPoint-2 in sameStrand or mainPoint-2 in diffStrand: GapStart5=int(posListDict[keys][mainPoint-2].split(':')[1]) GapEnd5=int(posListDict[keys][mainPoint-1].split(':')[0]) difference5=(GapEnd5-GapStart5)-1 if int(gappyness)>int(difference5) or int(gappyness)==int(difference5): if int(FamListDict[keys][mainPoint-2])!=0: sameStrandWindowU.append(mainPoint-2) #print(keys,mainPoint, LengthOfFlankFound, strandListDict[keys],posListDict[keys][mainPoint-2], posListDict[keys][mainPoint-1], difference5) if continuousVerifyCheck(sorted(sameStrandWindowU+sameStrandWindowD)): if len(continuousVerifyCheck(sorted(sameStrandWindowU+sameStrandWindowD)))>1: sameStrandWindowDict[keys+':'+str(continuousVerifyCheck(sorted(sameStrandWindowU+sameStrandWindowD)).index(str(mainPoint)))]=continuousVerifyCheck(sorted(sameStrandWindowU+sameStrandWindowD)) #print(keys,mainPoint, LengthOfFlankFound, strandListDict[keys], sameStrand, continuousVerifyCheck(sorted(sameStrandWindowU+sameStrandWindowD)), FamListDict[keys]) else: noToxDict_dis[keys]='No Cluster found or '+ 'Gap >'+str(gappyness)+' or Strand Difference' else: endContig_dis[keys]='Contig Error: Query is in the end of Contig' else: startContig_dis[keys]='Contig Error: Query is in the start of contig' OperonFamilyDict={} for keys in sameStrandWindowDict: opFamList=[] for item in sameStrandWindowDict[keys]: opFamList.append(str(FamListDict[keys[:-2]][int(item)])) OperonFamilyDict[keys]=opFamList queryFamilySet=set() for keys in OperonFamilyDict: queryFamilySet.add(int(OperonFamilyDict[keys][int(keys[-1:])])) #print(keys, OperonFamilyDict[keys]) #print(queryFamilySet, 'queryFamilySet') aattDict_dis={} nocoding_dis={} probableTApairFamDict={} probableTApairFamPosDict={} for keys in OperonFamilyDict: taPairList=[] taPairPosList=[] for i in range (len(OperonFamilyDict[keys])-1): for j in range (1,len(OperonFamilyDict[keys])): if j==i+1: if i==int(keys[-1]) or j==int(keys[-1]): if int(OperonFamilyDict[keys][i]) in queryFamilySet and int(OperonFamilyDict[keys][j]) in queryFamilySet: aattDict_dis[keys.split(':')[0]]='Pair Error: Paired with homolog cluster' pass #if condition like 'Toxin(518)-Toxin(518)' we discard else: if int(OperonFamilyDict[keys][i]) in queryFamilySet or int(OperonFamilyDict[keys][j]) in queryFamilySet: #if one of them in queryFamily if int(OperonFamilyDict[keys][i])<=max(queryFamilySet) and int(OperonFamilyDict[keys][j])<=max(queryFamilySet): #not pseudo/noncoding rna probableTA=str(OperonFamilyDict[keys][i])+'.'+str(OperonFamilyDict[keys][j]) probableTAPos=str(i)+'.'+str(j) taPairList.append(probableTA) taPairPosList.append(probableTAPos) else: nocoding_dis[keys.split(':')[0]]='Pair Error: Non coding RNA' #else: #print(keys) if len(taPairList)>0: probableTApairFamDict[keys]=taPairList probableTApairFamPosDict[keys]=taPairPosList #else: #print(keys, OperonFamilyDict[keys], taPairList) probableOperonFamDict={} probableOperonFamSet=set() probableOperonList=[] for keys in OperonFamilyDict: operonList=[] #rev1 if len(OperonFamilyDict[keys])>2: for i in range (len(OperonFamilyDict[keys])-2): for j in range (1,len(OperonFamilyDict[keys])-1): for k in range (2,len(OperonFamilyDict[keys])): if j==i+1 and k==j+1: #we need to get operon that contains query pair if int(OperonFamilyDict[keys][i]) in queryFamilySet or int(OperonFamilyDict[keys][j]) in queryFamilySet \ or int(OperonFamilyDict[keys][k]) in queryFamilySet : probableOperon=str(OperonFamilyDict[keys][i])+'.'+str(OperonFamilyDict[keys][j])+'.'+\ str(OperonFamilyDict[keys][k]) operonList.append(probableOperon) probableOperonList.append(probableOperon) probableOperonFamSet.add(probableOperon) if len(operonList)>0: probableOperonFamDict[keys]=operonList else: noToxDict_dis[keys.split(':')[0]]='No Cluster found or '+ 'Gap >'+str(gappyness)+' or Strand Difference' def pseudoCheck(item): itemSplit=item.split('.') if int((max(itemSplit)))>max(queryFamilySet): return 'pseudoFound' operonOccuranceDict={} #operons that are conserved more than one time trueOperonOccuranceDict={} for item in probableOperonFamSet: if pseudoCheck(item)!='pseudoFound': #remove pseudogenes/noncoding containing operons keyset=set() for keys in probableOperonFamDict: if item in probableOperonFamDict[keys]: keyset.add(keys.split(':')[0]) if len(keyset)>1: #operons that are conserved more than one time operonOccuranceDict[item]=keyset #else: # print(item,pseudoCheck(item)) filteredTApairPosFamily={} filteredTApairFamily={} filteredTApairSet=set() for items in probableTApairFamDict: Fpset=set()#rev1 for item in probableTApairFamDict[items]: for operons in operonOccuranceDict: taItem=item.split('.') operonItem1=operons.split('.')[0:2] operonItem2=operons.split('.')[1:3] #rev1 operonItem3=operons.split('.')[2:4] if taItem==operonItem1 or taItem==operonItem2: #rev1 or taItem==operonItem3: if items.split(':')[0] in operonOccuranceDict[operons]: Fpset.add(items) #print(items, probableTApairFamPosDict[items], probableTApairFamDict[items], operons, probableOperonList.count(operons), 'FP') if items not in Fpset: #print(items, probableTApairFamPosDict[items], probableTApairFamDict[items], operons, probableOperonList.count(operons), 'TP') filteredTApairFamily[items]=probableTApairFamDict[items] #'WP_057732687.1#38:2': ['2.518', '518.9'], filteredTApairPosFamily[items]=probableTApairFamPosDict[items] #'WP_015310665.1#174:1': ['0.1', '1.2'] for elements in probableTApairFamDict[items]: filteredTApairSet.add(elements) def getTA_ACCpair(pair, accessionSerial): if accessionSerial in filteredTApairFamily: if accessionSerial in probableTApairFamDict: for pairVar in probableTApairFamDict[accessionSerial]: if pairVar==pair: splitPair=pair.split('.') pairIndex=probableTApairFamPosDict[accessionSerial][probableTApairFamDict[accessionSerial].index(pairVar)] #print('new',pairVar, pairIndex)#new 12.1658 0.1 index1=int(sameStrandWindowDict[accessionSerial][int(pairIndex.split('.')[0])]) index2=int(sameStrandWindowDict[accessionSerial][int(pairIndex.split('.')[1])]) accession1=AccessionNameListDict[accessionSerial.split(':')[0]][index1] accession2=AccessionNameListDict[accessionSerial.split(':')[0]][index2] #print(index1,index2,accession1, accession2) position1=posListDict[accessionSerial.split(':')[0]][index1].split(':')[1] position2=posListDict[accessionSerial.split(':')[0]][index2].split(':')[0] difference=(int(position2)-int(position1))-1 return accession1+'|'+accession2+'\t'+str(difference)+'\t'+splitPair[0]+'|'+splitPair[1] def descriptionFromTA(item): descriptionList=[] itemList=item.split('\t')[0].split('|') for item in itemList: if item in desDict: descriptionList.append(desDict[item]) return '|'.join(map(str,descriptionList)) trueTApairCount={} trueTApairAccession={} for items in filteredTApairSet: accessionSet=set() accessionSet2=set() for keys in filteredTApairFamily: if items in filteredTApairFamily[keys]: accessionSet.add(keys) accessionSet2.add(keys.split(':')[0]) trueTApairAccession[items]=accessionSet trueTApairCount[items]=len(accessionSet2) def contigCheck(accs, accPair, strandDict, accsInSPList): if accs in accPair: accPairSplit=accPair.split('|') accPairSplit.remove(accs) if strandDict[accsInSPList.index(accs)]==strandDict[accsInSPList.index(accPairSplit[0])]: rangeL=[] for i in range (1,len(accsInSPList)-1): rangeL.append(i) if accsInSPList.index(accPairSplit[0]) in rangeL: return 'P' else: return 'Fc' else: return 'Fs' else: return 'Fx' discard_dis={} twoThree_List=[] tsvAccessionSet=set() ta_Accession=set() operonTA_TXT=[] #with open (args.out_prefix+'_TreeOrderOperonTA.txt', 'w') as opTAOut: # print('#Query_Species', 'QueryAccession', 'TA_System', 'AccessopnInPredictedTA-LikeRegion', 'IntergenicSpace', 'ClusterNumber_TA-likeSystem', 'Number_Occurred', 'Conserve(%)', 'Description',sep='\t', file=opTAOut) for item in sorted(trueTApairAccession): #print (item, (trueTApairCount[item]), len(trueTApairCount[item])) for accs in trueTApairAccession[item]: #if accs=='WP_056969168.1#334:2': if contigCheck(accs.split('#')[0], getTA_ACCpair(item, accs).split('\t')[0], strandListDict[accs[:-2]], AccessionNameListDict[accs[:-2]])=='P': #print(accs, item, getTA_ACCpair(item, accs)) if accs.split('#')[0] in getTA_ACCpair(item, accs).split('\t')[0]: pairQuery=accs.split(':')[0]+'\t'+getTA_ACCpair(item, accs).split('\t')[0] twoThree_List.append(pairQuery.split('\t')) tsvAccessionSet.add(querySPSDict[accs.split(':')[0]]) ta_Accession.add(accs.split(':')[0]) #print(querySPSDict[accs.split(':')[0]], accs.split('#')[0], len(item.split('.')), getTA_ACCpair(item, accs), str(trueTApairCount[item])+'/'+str(len(querySPSDict)), round(int(trueTApairCount[item])*100/len(querySPSDict),2), sep='\t', file=opTAOut)#descriptionFromTA(getTA_ACCpair(item, accs)) operonTAInfo=str(querySPSDict[accs.split(':')[0]])+'\t'+str(accs.split('#')[0])+'\t'+str(len(item.split('.')))+'\t'+str(getTA_ACCpair(item, accs))+'\t'+str(trueTApairCount[item])+'/'+str(len(querySPSDict))+'\t'+str(round(int(trueTApairCount[item])*100/len(querySPSDict),2)) operonTAInfosplit=operonTAInfo.split('\t') operonTA_TXT.append(operonTAInfosplit) else: if contigCheck(accs.split('#')[0], getTA_ACCpair(item, accs).split('\t')[0], strandListDict[accs[:-2]], AccessionNameListDict[accs[:-2]])=='Fc': if accs.split('#')[0] in getTA_ACCpair(item, accs).split('\t')[0]: if accs.split(':')[0] not in startContig_dis and endContig_dis and noToxDict_dis and aattDict_dis and nocoding_dis: #print(accs.split(':')[0], 'Fc') discard_dis[accs.split(':')[0]]='Contig Error: Contig starts/ends with predicted TA' if contigCheck(accs.split('#')[0], getTA_ACCpair(item, accs).split('\t')[0], strandListDict[accs[:-2]], AccessionNameListDict[accs[:-2]])=='Fs': if accs.split('#')[0] in getTA_ACCpair(item, accs).split('\t')[0]: if accs.split(':')[0] not in startContig_dis and endContig_dis and noToxDict_dis and aattDict_dis and nocoding_dis: #print(accs.split(':')[0], 'Fs') discard_dis[accs.split(':')[0]]='No Cluster found or '+ 'Gap >'+str(gappyness)+' or Strand Difference' if contigCheck(accs.split('#')[0], getTA_ACCpair(item, accs).split('\t')[0], strandListDict[accs[:-2]], AccessionNameListDict[accs[:-2]])=='Fx': if accs.split('#')[0] in getTA_ACCpair(item, accs).split('\t')[0]: if accs.split(':')[0] not in startContig_dis and endContig_dis and noToxDict_dis and aattDict_dis and nocoding_dis: #print(accs.split(':')[0], 'Fx') discard_dis[accs.split(':')[0]]='NotAcceptable' operonLong_dis={} for item in querySPSDict: if item not in ta_Accession: for element in operonOccuranceDict: if item in operonOccuranceDict[element]: operonLong_dis[item]='Long Conserved Operon' def TA_status(query): if query not in ta_Accession: reasonList=[] if query in startContig_dis: reasonList.append(startContig_dis[query]) if query in endContig_dis: reasonList.append(endContig_dis[query]) if query in noToxDict_dis: reasonList.append(noToxDict_dis[query]) if query in aattDict_dis : reasonList.append(aattDict_dis[query]) if query in nocoding_dis : reasonList.append(nocoding_dis[query]) if query in operonLong_dis: reasonList.append(operonLong_dis[query]) if query in discard_dis: reasonList.append(discard_dis[query]) if len(reasonList)>0: if len(reasonList)==1: return 'notTA_like'+'\t'+reasonList[0] else: return 'notTA_like'+'\t'+'; '.join(map(str,list(set(reasonList)))) else: for elements in filteredTApairPosFamily: if elements.split(':')[0]==query and len(filteredTApairPosFamily[elements])==1: glist=[] for items in twoThree_List: if query==items[0]: glist.append(items[1]) if len(glist)==1: return 'TA_like'+'\t'+'2G' if elements.split(':')[0]==query and len(filteredTApairPosFamily[elements])==2: return 'TA_like'+'\t'+'3G' i=0 discard3Gset=set() with open (args.out_prefix+'_TA_Status_report.txt', 'w') as sTAOut: print('#Serial', 'Query', 'Status', 'Reason', sep='\t', file=sTAOut) for item in querySPSDict: i+=1 print(i, querySPSDict[item], TA_status(item), sep='\t', file=sTAOut) if TA_status(item)=='TA_like'+'\t'+'3G': discard3Gset.add(querySPSDict[item]) #print(discard3Gset) with open (args.out_prefix+'_TreeOrderOperonTA.txt', 'w') as opTAOut: print('#Query_Species', 'QueryAccession', 'TA_System', 'AccessopnInPredictedTA-LikeRegion', 'IntergenicSpace', 'ClusterNumber_TA-likeSystem', 'Number_Occurred', 'Conserve(%)', 'Description',sep='\t', file=opTAOut) for item in operonTA_TXT: if item[0] not in discard3Gset: print('\t'.join(map(str,item)), file=opTAOut) with open (args.out_prefix+'_TreeOrderOperonTA.tsv', 'w') as opTAtsv: for item in egsList: if item!='': #tsvAccession=item[0].split('\t')[0].split('#')[0]+'#'+item[0].split('\t')[0].split('#')[1].split('_')[0] #print(item[0].split('\t')[0]) if item[0].split('\t')[0] in tsvAccessionSet: if item[0].split('\t')[0] not in discard3Gset: print('\n'.join(item), file=opTAtsv) print("\n\n", file=opTAtsv) windowMost=round(((max(ptPos)+abs(min(ntPos))+1)*4)/100) widthM=(windowMost*3)+500 heightM=int(newQ)*20 #aheightM=heightM*1.3 from tkinter import * master = Tk() canvas = Canvas(master, width=widthM,height=heightM,background='white', scrollregion=(0,0,round(widthM*2.5),round(heightM*2.5))) hbar=Scrollbar(master,orient=HORIZONTAL) hbar.pack(side=BOTTOM,fill=X) hbar.config(command=canvas.xview) vbar=Scrollbar(master,orient=VERTICAL) vbar.pack(side=RIGHT,fill=Y) vbar.config(command=canvas.yview) canvas.config(xscrollcommand=hbar.set, yscrollcommand=vbar.set) canvas.pack(side=LEFT,expand=True,fill=BOTH) def operonFamily(item): if item==0: return ' ' elif item==center: return ' ' elif item==noProt: return ' ' elif item==noProtP: return ' ' elif item==noColor: return ' ' else: return item egTA=open(args.out_prefix+'_TreeOrderOperonTA.tsv','r').read() egTAs=egTA.split("\n\n\n\n") line_pos_y=0 for eg in egTAs: if eg!='': coln=0 entries=eg.splitlines() ndoms=len(entries) ptnstats=entries[0].split("\t") org=ptnstats[0].replace("_"," ") textspace=widthM/2 line_pos_y=line_pos_y+16-round(postscriptSize(newQ)) half_dom_height=5-round(postscriptSize(newQ)) text = canvas.create_text(textspace/2,line_pos_y, text=org, fill="#404040", font=("Arial", "12")) for entry in entries: items=entry.split("\t") aln_start=round(int(items[5])*4/100) aln_end=round(int(items[6])*4/100) strandType=items[3] dom1_name=int(items[4]) dom1_len=(aln_end-aln_start) oL80=round(dom1_len*80/100) dom1_start=aln_start+textspace dom1_end=dom1_len+dom1_start if strandType=='+': rect = canvas.create_polygon(dom1_start, line_pos_y+half_dom_height, dom1_start, line_pos_y-half_dom_height,dom1_start+oL80, line_pos_y-half_dom_height, dom1_end, line_pos_y, dom1_start+oL80, line_pos_y+half_dom_height,fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) else: rect = canvas.create_polygon(dom1_end-oL80, line_pos_y+half_dom_height, dom1_start, line_pos_y, dom1_end-oL80, line_pos_y-half_dom_height,dom1_end, line_pos_y-half_dom_height, dom1_end, line_pos_y+half_dom_height, fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) textd1 = canvas.create_text(dom1_start+(dom1_len/2),line_pos_y, text=operonFamily(dom1_name), font=("Arial", "7")) coln=coln+1 retval2 = canvas.postscript(file=args.out_prefix+"_treeOrder_flankgenesTA.ps", height=heightM, width=widthM, colormode="color") #disqualified with open (args.out_prefix+'_TreeOrderOperonTAdisqualified.tsv', 'w') as opTAtsvd: for item in egsList: if item!='': #tsvAccession=item[0].split('\t')[0].split('#')[0]+'#'+item[0].split('\t')[0].split('#')[1].split('_')[0] #print(item[0].split('\t')[0]) if item[0].split('\t')[0] not in tsvAccessionSet: print('\n'.join(item), file=opTAtsvd) print("\n\n", file=opTAtsvd) windowMost=round(((max(ptPos)+abs(min(ntPos))+1)*4)/100) widthM=(windowMost*3)+500 heightM=int(newQ)*20 #aheightM=heightM*1.3 from tkinter import * master = Tk() canvas = Canvas(master, width=widthM,height=heightM,background='white', scrollregion=(0,0,round(widthM*2.5),round(heightM*2.5))) hbar=Scrollbar(master,orient=HORIZONTAL) hbar.pack(side=BOTTOM,fill=X) hbar.config(command=canvas.xview) vbar=Scrollbar(master,orient=VERTICAL) vbar.pack(side=RIGHT,fill=Y) vbar.config(command=canvas.yview) canvas.config(xscrollcommand=hbar.set, yscrollcommand=vbar.set) canvas.pack(side=LEFT,expand=True,fill=BOTH) def operonFamily(item): if item==0: return ' ' elif item==center: return ' ' elif item==noProt: return ' ' elif item==noProtP: return ' ' elif item==noColor: return ' ' else: return item egTAD=open(args.out_prefix+'_TreeOrderOperonTAdisqualified.tsv','r').read() egTADs=egTAD.split("\n\n\n\n") line_pos_y=0 for eg in egTADs: if eg!='': coln=0 entries=eg.splitlines() ndoms=len(entries) ptnstats=entries[0].split("\t") org=ptnstats[0].replace("_"," ") textspace=widthM/2 line_pos_y=line_pos_y+16-round(postscriptSize(newQ)) half_dom_height=5-round(postscriptSize(newQ)) text = canvas.create_text(textspace/2,line_pos_y, text=org, fill="#404040", font=("Arial", "12")) for entry in entries: items=entry.split("\t") aln_start=round(int(items[5])*4/100) aln_end=round(int(items[6])*4/100) strandType=items[3] dom1_name=int(items[4]) dom1_len=(aln_end-aln_start) oL80=round(dom1_len*80/100) dom1_start=aln_start+textspace dom1_end=dom1_len+dom1_start if strandType=='+': rect = canvas.create_polygon(dom1_start, line_pos_y+half_dom_height, dom1_start, line_pos_y-half_dom_height,dom1_start+oL80, line_pos_y-half_dom_height, dom1_end, line_pos_y, dom1_start+oL80, line_pos_y+half_dom_height,fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) else: rect = canvas.create_polygon(dom1_end-oL80, line_pos_y+half_dom_height, dom1_start, line_pos_y, dom1_end-oL80, line_pos_y-half_dom_height,dom1_end, line_pos_y-half_dom_height, dom1_end, line_pos_y+half_dom_height, fill=colorDict[dom1_name], outline=outliner(colorDict[dom1_name])) textd1 = canvas.create_text(dom1_start+(dom1_len/2),line_pos_y, text=operonFamily(dom1_name), font=("Arial", "7")) coln=coln+1 retval3 = canvas.postscript(file=args.out_prefix+"_treeOrder_flankgenesTAdisqualified.ps", height=heightM, width=widthM, colormode="color") #disqualified import shutil def remove_folder(path): if os.path.exists(path): shutil.rmtree(path) else: raise XXError("Files not found") directory = args.out_prefix+'_flankgene.fasta'+'_cluster_out_individuals' if os.path.exists(directory): remove_folder(directory) print('\n'+'<<< Done >>>') print('\nIf you use TAGs in your work, please remember to cite these papers!'+'\n\n- Saha CK, Pires RS, Brolin H, Delannoy M, Atkinson GC. 2020. FlaGs and webFlaGs: discovering novel biology through the analysis of gene neighbourhood conservation. Bioinformatics.'+\ '\nhttps://doi.org/10.1093/bioinformatics/btaa788') sys.exit()

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null

0

5

31471ce1c12c18064307381d689bd7c604c7e3ce

149

py

Python

angr/procedures/libc/setbuf.py

Kyle-Kyle/angr

345b2131a7a67e3a6ffc7d9fd475146a3e12f837

[ "BSD-2-Clause" ]

6,132

2015-08-06T23:24:47.000Z

2022-03-31T21:49:34.000Z

angr/procedures/libc/setbuf.py

Kyle-Kyle/angr

345b2131a7a67e3a6ffc7d9fd475146a3e12f837

[ "BSD-2-Clause" ]

2,272

2015-08-10T08:40:07.000Z

2022-03-31T23:46:44.000Z

angr/procedures/libc/setbuf.py

Kyle-Kyle/angr

345b2131a7a67e3a6ffc7d9fd475146a3e12f837

[ "BSD-2-Clause" ]

1,155

2015-08-06T23:37:39.000Z

2022-03-31T05:54:11.000Z

import angr class setbuf(angr.SimProcedure): #pylint:disable=arguments-differ, unused-argument def run(self, stream, buf): return

16.555556

53

0.697987

18

149

5.777778

0.944444

0

0.201342

149

8

54

18.625

0.87395

0.322148

0

1

0.25

false

0

0.25

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null

0

1

0

null

0

1

0

1

0

5

31486c72d7dc2979eab1de3e230296c92ab947dd

170

wsgi

Python

Monitora-backend/main.wsgi

miiila/nasi-politici

3edbf7adc3d89e2839c50ff2e7693101784868a0

[ "MIT" ]

16

2019-11-26T16:30:39.000Z

2021-07-25T19:13:15.000Z

Monitora-backend/main.wsgi

miiila/nasi-politici

3edbf7adc3d89e2839c50ff2e7693101784868a0

[ "MIT" ]

33

2019-11-25T08:17:54.000Z

2022-02-26T21:08:41.000Z

Monitora-backend/main.wsgi

miiila/nasi-politici

3edbf7adc3d89e2839c50ff2e7693101784868a0

[ "MIT" ]

8

2020-01-06T10:39:52.000Z

2021-10-16T15:06:08.000Z

#!/usr/bin/python import sys import logging logging.basicConfig(stream=sys.stderr) sys.path.insert(0,"/var/www/fullreport/API/main/") from main import app as application

24.285714

50

0.788235

27

170

4.962963

0.777778

0

0.006369

0.076471

170

7

51

24.285714

0.847134

0.094118

0

0.188312

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true

0

0.6

0

0.6

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null

0

1

0

null

0

1

0

1

0

1

0

5

314ba3a5881c9855c3210c8a581e1ee7bed8a510

168

py

Python

tests/test_utils/__init__.py

ketyi/dgl

a1b859c29b63a673c148d13231a49504740e0e01

[ "Apache-2.0" ]

null

tests/test_utils/__init__.py

ketyi/dgl

a1b859c29b63a673c148d13231a49504740e0e01

[ "Apache-2.0" ]

null

tests/test_utils/__init__.py

ketyi/dgl

a1b859c29b63a673c148d13231a49504740e0e01

[ "Apache-2.0" ]

null

import pytest import backend as F parametrize_idtype = pytest.mark.parametrize("idtype", [F.int32, F.int64]) from .checks import * from .graph_cases import get_cases

21

74

0.779762

25

168

5.12

0.6

0.265625

0

0.027211

0.125

168

7

75

24

0.843537

0

0.035714

0

1

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false

0

0.8

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null

1

0

1

0

null

0

1

0

1

0

5

314cd3af076d89a6ef53dd505680bb47e99707ba

2,881

py

Python

tests/test_influx.py

letrout/home_automation

290a710ebecbb799746b4eaa1377865f833009bb

[ "Apache-2.0" ]

null

tests/test_influx.py

letrout/home_automation

290a710ebecbb799746b4eaa1377865f833009bb

[ "Apache-2.0" ]

1

2022-01-04T19:24:40.000Z

2022-01-29T19:24:02.000Z

tests/test_influx.py

letrout/home_automation

290a710ebecbb799746b4eaa1377865f833009bb

[ "Apache-2.0" ]

null

import pytest from sensors.lib.influx import influx def test_lp_1f1v(): test = influx.influx_lp( "temp", {"field1": 1}, {"tag1": 2}, 1634158455045502066 ) assert test == "temp,tag1=2 field1=1 1634158455045502066" def test_lp_2f2v(): test = influx.influx_lp( "temp", {"field1": 1, "field2": 5.5}, {"tag1": 2, "tag2": 6}, 1634158455045502066 ) assert test == "temp,tag1=2,tag2=6 field1=1,field2=5.5 1634158455045502066" def test_lp_emptytag(): test = influx.influx_lp( "temp", {"field1": 1, "field2": 5.5}, {}, 1634158455045502066 ) assert test == "temp field1=1,field2=5.5 1634158455045502066" def test_lp_emptryfield(): test = influx.influx_lp( "temp", {}, {"tag1": 2, "tag2": 6}, 1634158455045502066 ) assert test is None # FIXME: don't know how to handle spaces in strings #def test_lp_string_space(): # test = influx.influx_lp( # "temp", # {"field1": 1, "field2": "a string"}, # {"tag1": 2, "tag2": 6}, # 1634158455045502066 # ) # assert test == """temp,tag1=2,tag2=6 field1=1,field2="a string" 1634158455045502066""" def test_lp_string(): test = influx.influx_lp( "temp", {"field1": 1, "field2": "string"}, {"tag1": 2, "tag2": 6}, 1634158455045502066 ) assert test == """temp,tag1=2,tag2=6 field1=1,field2=string 1634158455045502066""" def test_lp_true(): test = influx.influx_lp( "temp", {"field1": 1, "field2": "string"}, {"tag1": 2, "tag2": "true"}, 1634158455045502066 ) assert test == 'temp,tag1=2,tag2=true field1=1,field2=string 1634158455045502066' def test_lp_false(): test = influx.influx_lp( "temp", {"field1": 1, "field2": "string"}, {"tag1": 2, "tag2": "False"}, 1634158455045502066 ) assert test == 'temp,tag1=2,tag2=False field1=1,field2=string 1634158455045502066' def test_lp_falsestring(): test = influx.influx_lp( "temp", {"field1": 1, "field2": "string"}, {"tag1": 2, "tag2": "FAlse"}, 1634158455045502066 ) assert test == 'temp,tag1=2,tag2=FAlse field1=1,field2=string 1634158455045502066' def test_lp_bad_ts(): test = influx.influx_lp( "temp", {"field1": 1}, {"tag1": 2}, "manynanoseconds" ) assert test is None def test_lp_bad_field(): test = influx.influx_lp( "temp", ["field1", 1], {"tag1": 2}, 1634158455045502066 ) assert test is None def test_lp_bad_tag(): test = influx.influx_lp( "temp", {"field1": 1}, "tag1", 1634158455045502066 ) assert test is None

23.048

91

0.552933

323

2,881

4.80805

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0.117193

0.139086

0.841597

0.777849

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0.705087

0.579524

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0

0.23657

0.295731

2,881

124

92

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0.528832

0.111073

0

0.588889

0

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1

0.122222

false

0

0.022222

0

0.144444

0

null

0

1

0

1

0

null

0

5

9edb5b37e160f7a0e9572c7c5ee19a5cbb3758c9

192

py

Python

infiltrate/views/faq.py

Qazzquimby/eternalCardEvaluator

ef8640ed819a89e5198f8aedf0861a29c57c5720

[ "MIT" ]

4

2019-04-08T09:30:10.000Z

2020-09-15T19:25:30.000Z

infiltrate/views/faq.py

Qazzquimby/eternalCardEvaluator

ef8640ed819a89e5198f8aedf0861a29c57c5720

[ "MIT" ]

19

2019-04-09T19:02:14.000Z

2020-12-25T05:22:45.000Z

infiltrate/views/faq.py

Qazzquimby/eternalCardEvaluator

ef8640ed819a89e5198f8aedf0861a29c57c5720

[ "MIT" ]

null

"""This is where the routes are defined.""" import flask from flask_classful import FlaskView class FaqView(FlaskView): def index(self): return flask.render_template("faq.html")

21.333333

48

0.729167

26

192

5.307692

0.846154

0

0.171875

192

8

49

24

0.867925

0.192708

0

0.053691

0

1

0.2

false

0

0.4

0.2

1

0

1

0

null

0

1

0

null

0

1

0

5

7305f64bed74a8cd99a86a6e7a9ee70628c723d7

2,688

py

Python

apps/people/tests/test_create_people.py

bergran/people

a2639b238005bd37b7a08f220b57c4b5ad5c031d

[ "MIT" ]

null

apps/people/tests/test_create_people.py

bergran/people

a2639b238005bd37b7a08f220b57c4b5ad5c031d

[ "MIT" ]

null

apps/people/tests/test_create_people.py

bergran/people

a2639b238005bd37b7a08f220b57c4b5ad5c031d

[ "MIT" ]

null

# -*- coding: utf-8 -*- from fastapi.encoders import jsonable_encoder from starlette import status from apps.people.serializers.people import PeopleOutSerializer from core.test.transaction_test_case import TransactionTestCase class CreatePeopleTestCase(TransactionTestCase): @staticmethod def get_url(): return '/api/v1/people/' def check_fields(self, people, response): payload = response.json() for key, value in people.items(): self.assertEqual(value, payload.get(key)) def test_create_kink_successfully(self): people = { 'first_name': 'Kirigaya', 'last_name': 'Kazuto', 'place_id': 1, 'is_king': True, } response = self.client.post(self.get_url(), json=people) self.assertEqual(status.HTTP_201_CREATED, response.status_code) self.check_fields(people, response) def test_create_duplicated_people(self): people = { 'first_name': 'Kirigaya', 'last_name': 'Kazuto', 'place_id': 1, 'is_king': False, } response = self.client.post(self.get_url(), json=people) self.assertEqual(status.HTTP_201_CREATED, response.status_code) self.check_fields(people, response) response = self.client.post(self.get_url(), json=people) self.assertEqual(status.HTTP_400_BAD_REQUEST, response.status_code) def test_create_duplicated_king(self): people = { 'first_name': 'Kirigaya', 'last_name': 'Kazuto', 'place_id': 1, 'is_king': True, } response = self.client.post(self.get_url(), json=people) self.assertEqual(status.HTTP_201_CREATED, response.status_code) self.check_fields(people, response) people['first_name'] = 'Asuna' people['last_name'] = 'Yuuki' response = self.client.post(self.get_url(), json=people) self.assertEqual(status.HTTP_400_BAD_REQUEST, response.status_code) def test_create_duplicated_king_non_alive(self): people = { 'first_name': 'Kirigaya', 'last_name': 'Kazuto', 'place_id': 1, 'is_king': True, } response = self.client.post(self.get_url(), json=people) self.assertEqual(status.HTTP_201_CREATED, response.status_code) self.check_fields(people, response) people['first_name'] = 'Asuna' people['last_name'] = 'Yuuki' people['is_alive'] = False response = self.client.post(self.get_url(), json=people) self.assertEqual(status.HTTP_201_CREATED, response.status_code)

33.185185

75

0.629092

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2,688

5.284314

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0.029685

0.077922

0.095238

0.717996

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2,688

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0

0.102439

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1

0.095238

false

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0.063492

0.015873

0.190476

0

null

0

1

0

null

0

5

b44906c6a4f9e4f33b182018ea4cd4e8c43e4617

18,876

py

Python

GPyOpt/optimization/acquisition_optimizer.py

RaulAstudillo/bocf

cd84eab2d1b4ea5a4bdeeb452df92296afbafb87

[ "BSD-3-Clause" ]

null

GPyOpt/optimization/acquisition_optimizer.py

RaulAstudillo/bocf

cd84eab2d1b4ea5a4bdeeb452df92296afbafb87

[ "BSD-3-Clause" ]

null

GPyOpt/optimization/acquisition_optimizer.py

RaulAstudillo/bocf

cd84eab2d1b4ea5a4bdeeb452df92296afbafb87

[ "BSD-3-Clause" ]

null

# Copyright (c) 2016, the GPyOpt Authors # Licensed under the BSD 3-clause license (see LICENSE.txt) from .optimizer import OptLbfgs, OptSGD, OptDirect, OptCma, apply_optimizer, choose_optimizer, apply_optimizer_inner from .anchor_points_generator import ObjectiveAnchorPointsGenerator, ThompsonSamplingAnchorPointsGenerator from ..core.task.space import Design_space from GPyOpt.experiment_design import initial_design import multiprocessing from pathos.multiprocessing import ProcessingPool as Pool import numpy as np import time max_objective_anchor_points_logic = "max_objective" thompson_sampling_anchor_points_logic = "thompsom_sampling" sobol_design_type = "sobol" random_design_type = "random" latin_design_type = "latin" class AcquisitionOptimizer(object): """ General class for acquisition optimizers defined in domains with mix of discrete, continuous, bandit variables :param space: design space class from GPyOpt. :param optimizer: optimizer to use. Can be selected among: - 'lbfgs': L-BFGS. - 'DIRECT': Dividing Rectangles. - 'CMA': covariance matrix adaptation. """ def __init__(self, space, optimizer='lbfgs', inner_optimizer='lbfgs2', n_starting=400, n_anchor=16, **kwargs): self.space = space self.optimizer_name = optimizer self.inner_optimizer_name = inner_optimizer self.n_starting = n_starting self.n_anchor = n_anchor self.kwargs = kwargs ## -- save extra options than can be passed to the optimizer if 'model' in self.kwargs: self.model = self.kwargs['model'] if 'anchor_points_logic' in self.kwargs: self.type_anchor_points_logic = self.kwargs['type_anchor_points_logic'] else: self.type_anchor_points_logic = max_objective_anchor_points_logic ## -- Context handler: takes self.context_manager = ContextManager(space) ## -- Set optimizer and inner optimizer (WARNING: this won't update context) self.optimizer = choose_optimizer(self.optimizer_name, self.context_manager.noncontext_bounds) self.inner_optimizer = choose_optimizer(self.inner_optimizer_name, self.context_manager.noncontext_bounds) def optimize2(self, f=None, df=None, f_df=None, duplicate_manager=None): """ Optimizes the input function. :param f: function to optimize. :param df: gradient of the function to optimize. :param f_df: returns both the function to optimize and its gradient. """ self.f = f self.df = df self.f_df = f_df ## --- Update the optimizer, in case context has beee passed. self.optimizer = choose_optimizer(self.optimizer_name, self.context_manager.noncontext_bounds) ## --- Selecting the anchor points and removing duplicates if self.type_anchor_points_logic == max_objective_anchor_points_logic: anchor_points_generator = ObjectiveAnchorPointsGenerator(self.space, latin_design_type, f) elif self.type_anchor_points_logic == thompson_sampling_anchor_points_logic: anchor_points_generator = ThompsonSamplingAnchorPointsGenerator(self.space, sobol_design_type, self.model) ## -- Select the anchor points (with context) anchor_points = anchor_points_generator.get(duplicate_manager=duplicate_manager, context_manager=self.context_manager) print('anchor_points ready') print(anchor_points) pool = Pool(4) optimized_points = pool.map(self._parallel_optimization_wrapper, anchor_points) print('parallel') print(optimized_points) optimized_points2 = [apply_optimizer(self.optimizer, a, f=f, df=None, f_df=f_df, duplicate_manager=duplicate_manager, context_manager=self.context_manager, space = self.space) for a in anchor_points] print('sequential') print(optimized_points2) x_min, fx_min = min(optimized_points, key=lambda t:t[1]) return x_min, fx_min def optimize(self, f=None, df=None, f_df=None, duplicate_manager=None, x_baseline=None): """ Optimizes the input function. :param f: function to optimize. :param df: gradient of the function to optimize. :param f_df: returns both the function to optimize and its gradient. """ self.f = f self.df = df self.f_df = f_df ## --- Update the optimizer, in case context has beee passed. self.optimizer = choose_optimizer(self.optimizer_name, self.context_manager.noncontext_bounds) ## --- Selecting the anchor points and removing duplicates if self.type_anchor_points_logic == max_objective_anchor_points_logic: anchor_points_generator = ObjectiveAnchorPointsGenerator(self.space, random_design_type, f, self.n_starting) elif self.type_anchor_points_logic == thompson_sampling_anchor_points_logic: anchor_points_generator = ThompsonSamplingAnchorPointsGenerator(self.space, sobol_design_type, self.model) ## -- Select the anchor points (with context) anchor_points, anchor_points_values = anchor_points_generator.get(num_anchor=self.n_anchor, duplicate_manager=duplicate_manager, context_manager=self.context_manager, get_scores=True) print('anchor points') print(anchor_points) print(anchor_points_values) parallel = True if parallel: pool = Pool(4) optimized_points = pool.map(self._parallel_optimization_wrapper, anchor_points) print('optimized points') print(optimized_points) else: #pass optimized_points = [apply_optimizer(self.optimizer, a, f=f, df=None, f_df=f_df, duplicate_manager=duplicate_manager, context_manager=self.context_manager, space = self.space) for a in anchor_points] x_min, fx_min = min(optimized_points, key=lambda t:t[1]) if x_baseline is not None: f_baseline = f(x_baseline) if f_baseline < fx_min: print('baseline was best found') print(f_baseline) x_min = x_baseline fx_min = f_baseline #if np.asscalar(anchor_points_values[0]) < np.asscalar(fx_min): #print('anchor_point was best found') #fx_min = np.atleast_2d(anchor_points_values[0]) #x_min = np.atleast_2d(anchor_points[0]) return x_min, fx_min def optimize_comparison(self, f=None, df=None, f_df=None, duplicate_manager=None): """ Optimizes the input function. :param f: function to optimize. :param df: gradient of the function to optimize. :param f_df: returns both the function to optimize and its gradient. """ self.f = f self.df = df self.f_df = f_df ## --- Update the optimizer, in case context has beee passed. self.optimizer = choose_optimizer(self.optimizer_name, self.context_manager.noncontext_bounds) ## --- Selecting the anchor points and removing duplicates if self.type_anchor_points_logic == max_objective_anchor_points_logic: anchor_points_generator = ObjectiveAnchorPointsGenerator(self.space, random_design_type, f, self.n_starting) elif self.type_anchor_points_logic == thompson_sampling_anchor_points_logic: anchor_points_generator = ThompsonSamplingAnchorPointsGenerator(self.space, sobol_design_type, self.model) ## -- Select the anchor points (with context) anchor_points, anchor_points_values = anchor_points_generator.get(num_anchor=self.n_anchor, duplicate_manager=duplicate_manager, context_manager=self.context_manager, get_scores=True) print('anchor points') print(anchor_points) print(anchor_points_values) parallel = True if parallel: pool = Pool(4) optimized_points = pool.map(self._parallel_optimization_wrapper, anchor_points) print('optimized points') print(optimized_points) else: # pass optimized_points = [ apply_optimizer(self.optimizer, a, f=f, df=None, f_df=f_df, duplicate_manager=duplicate_manager, context_manager=self.context_manager, space=self.space) for a in anchor_points] x_min, fx_min = min(optimized_points, key=lambda t: t[1]) if np.asscalar(anchor_points_values[0]) < np.asscalar(fx_min): print('anchor_point was best found') fx_min = np.atleast_2d(anchor_points_values[0]) x_min = np.atleast_2d(anchor_points[0]) # Comparison print('sgd results') ## --- Update the optimizer, in case context has beee passed. self.optimizer = choose_optimizer('sgd', self.context_manager.noncontext_bounds) parallel = True if parallel: pool = Pool(4) optimized_points = pool.map(self._parallel_optimization_wrapper, anchor_points) print('optimized points') print(optimized_points) else: optimized_points = [ apply_optimizer(self.optimizer, a, f=f, df=None, f_df=f_df, duplicate_manager=duplicate_manager, context_manager=self.context_manager, space=self.space) for a in anchor_points] x_min, fx_min = min(optimized_points, key=lambda t: t[1]) if np.asscalar(anchor_points_values[0]) < np.asscalar(fx_min): print('anchor_point was best found') fx_min = np.atleast_2d(anchor_points_values[0]) x_min = np.atleast_2d(anchor_points[0]) return x_min, fx_min def optimize1(self, f=None, df=None, f_df=None, duplicate_manager=None): """ Optimizes the input function. :param f: function to optimize. :param df: gradient of the function to optimize. :param f_df: returns both the function to optimize and its gradient. """ self.f = f self.df = df self.f_df = f_df ## --- Update the optimizer, in case context has beee passed. self.optimizer = choose_optimizer(self.optimizer_name, self.context_manager.noncontext_bounds) ## --- Selecting the anchor points and removing duplicates if self.type_anchor_points_logic == max_objective_anchor_points_logic: anchor_points_generator = ObjectiveAnchorPointsGenerator(self.space, random_design_type, f) elif self.type_anchor_points_logic == thompson_sampling_anchor_points_logic: anchor_points_generator = ThompsonSamplingAnchorPointsGenerator(self.space, sobol_design_type, self.model) ## -- Select the anchor points (with context) anchor_points, anchor_points_values = anchor_points_generator.get(duplicate_manager=duplicate_manager, context_manager=self.context_manager) ## --- Applying local optimizers at the anchor points and update bounds of the optimizer (according to the context) optimized_points = [apply_optimizer(self.optimizer, a, f=f, df=None, f_df=f_df, duplicate_manager=duplicate_manager, context_manager=self.context_manager, space = self.space) for a in anchor_points] x_min, fx_min = min(optimized_points, key=lambda t:t[1]) #x_min, fx_min = min([apply_optimizer(self.optimizer, a, f=f, df=None, f_df=f_df, duplicate_manager=duplicate_manager, context_manager=self.context_manager, space = self.space) for a in anchor_points], key=lambda t:t[1]) return x_min, fx_min def optimize_inner_func(self, f=None, df=None, f_df=None, duplicate_manager=None, n_starting=64, n_anchor=8): """ Optimizes the input function. :param f: function to optimize. :param df: gradient of the function to optimize. :param f_df: returns both the function to optimize and its gradient. """ self.f = f self.df = df self.f_df = f_df ## --- Update the optimizer, in case context has beee passed. self.inner_optimizer = choose_optimizer(self.inner_optimizer_name, self.context_manager.noncontext_bounds) ## --- Selecting the anchor points and removing duplicates if self.type_anchor_points_logic == max_objective_anchor_points_logic: anchor_points_generator = ObjectiveAnchorPointsGenerator(self.space, latin_design_type, f, n_starting) elif self.type_anchor_points_logic == thompson_sampling_anchor_points_logic: anchor_points_generator = ThompsonSamplingAnchorPointsGenerator(self.space, sobol_design_type, self.model) ## -- Select the anchor points (with context) anchor_points, anchor_points_values = anchor_points_generator.get(num_anchor=n_anchor, duplicate_manager=duplicate_manager, context_manager=self.context_manager, get_scores=True) #print(anchor_points) ## --- Applying local optimizers at the anchor points and update bounds of the optimizer (according to the context) optimized_points = [apply_optimizer_inner(self.inner_optimizer, a, f=f, df=None, f_df=f_df, duplicate_manager=duplicate_manager, context_manager=self.context_manager, space = self.space) for a in anchor_points] #print('inner optimized points') #print(optimized_points) x_min, fx_min = min(optimized_points, key=lambda t:t[1]) #x_min = np.atleast_2d(anchor_points[0]) #fx_min = np.atleast_2d(anchor_points_values[0]) return x_min, fx_min def optimize_inner_func2(self, f=None, df=None, f_df=None, duplicate_manager=None, n_starting=64, n_anchor=32): """ Optimizes the input function. :param f: function to optimize. :param df: gradient of the function to optimize. :param f_df: returns both the function to optimize and its gradient. """ self.f = f self.df = df self.f_df = f_df ## --- Update the optimizer, in case context has beee passed. self.inner_optimizer = choose_optimizer(self.inner_optimizer_name, self.context_manager.noncontext_bounds) ## --- Selecting the anchor points and removing duplicates if self.type_anchor_points_logic == max_objective_anchor_points_logic: anchor_points_generator = ObjectiveAnchorPointsGenerator(self.space, latin_design_type, f, n_starting) elif self.type_anchor_points_logic == thompson_sampling_anchor_points_logic: anchor_points_generator = ThompsonSamplingAnchorPointsGenerator(self.space, sobol_design_type, self.model) ## -- Select the anchor points (with context) anchor_points, anchor_points_values = anchor_points_generator.get(num_anchor=n_anchor, duplicate_manager=duplicate_manager, context_manager=self.context_manager, get_scores=True) ## --- Applying local optimizers at the anchor points and update bounds of the optimizer (according to the context) optimized_points = [ apply_optimizer_inner(self.inner_optimizer, a, f=f, df=None, f_df=f_df, duplicate_manager=duplicate_manager, context_manager=self.context_manager, space=self.space) for a in anchor_points] x_min, fx_min = min(optimized_points, key=lambda t: t[1]) print('test begins') optimized_points2 = optimized_points[0:2] x_min2, fx_min2 = min(optimized_points2, key=lambda t: t[1]) print(fx_min2-fx_min) time.sleep(1) #for i in range(len(optimized_points)): #if np.array_equal(optimized_points[i][0], x_min): #print('optimal point was found at anchor point: {}'.format(i)) #break # x_min = np.atleast_2d(anchor_points[0]) # fx_min = np.atleast_2d(anchor_points_values[0]) return x_min, fx_min def _parallel_optimization_wrapper(self, x0): #print(x0) return apply_optimizer(self.optimizer, x0, self.f, None, self.f_df) class ContextManager(object): """ class to handle the context variable in the optimizer :param space: design space class from GPyOpt. :param context: dictionary of variables and their contex values """ def __init__ (self, space, context = None): self.space = space self.all_index = list(range(space.model_dimensionality)) self.all_index_obj = list(range(len(self.space.config_space_expanded))) self.context_index = [] self.context_value = [] self.context_index_obj = [] self.nocontext_index_obj= self.all_index_obj self.noncontext_bounds = self.space.get_bounds()[:] self.noncontext_index = self.all_index[:] if context is not None: #print('context') ## -- Update new context for context_variable in context.keys(): variable = self.space.find_variable(context_variable) self.context_index += variable.index_in_model self.context_index_obj += variable.index_in_objective self.context_value += variable.objective_to_model(context[context_variable]) ## --- Get bounds and index for non context self.noncontext_index = [idx for idx in self.all_index if idx not in self.context_index] self.noncontext_bounds = [self.noncontext_bounds[idx] for idx in self.noncontext_index] ## update non context index in objective self.nocontext_index_obj = [idx for idx in self.all_index_obj if idx not in self.context_index_obj] def _expand_vector(self,x): ''' Takes a value x in the subspace of not fixed dimensions and expands it with the values of the fixed ones. :param x: input vector to be expanded by adding the context values ''' x = np.atleast_2d(x) x_expanded = np.zeros((x.shape[0],self.space.model_dimensionality)) x_expanded[:,np.array(self.noncontext_index).astype(int)] = x x_expanded[:,np.array(self.context_index).astype(int)] = self.context_value return x_expanded

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class PillowtopCheckpointReset(Exception): pass class PillowNotFoundError(Exception): pass class PillowtopIndexingError(Exception): pass class PillowConfigError(Exception): pass class BulkDocException(Exception): pass

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\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\ " def qInitResources(): QtCore.qRegisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data) def qCleanupResources(): QtCore.qUnregisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data) qInitResources()

57

96

0.727149

2,439

10,317

3.068471

0.051251

0.14992

0.17798

0.234099

0.667023

0.568813

0.525922

0.493453

0.427312

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0.40006

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57.316667

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false

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null

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1

0

1

0

1

0

null

1

0

5

b47ef3e80d6b7f715ea653b06064311987b035cd

40

py

Python

tingting.py

yaserqaziuva/cs3240-labdemo

bc17db0fc4107d0f4524fbc5eaf121a117a96409

[ "MIT" ]

null

tingting.py

yaserqaziuva/cs3240-labdemo

bc17db0fc4107d0f4524fbc5eaf121a117a96409

[ "MIT" ]

null

tingting.py

yaserqaziuva/cs3240-labdemo

bc17db0fc4107d0f4524fbc5eaf121a117a96409

[ "MIT" ]

null

# Yaser Qazi (yq4du) print("tingting")

10

20

0.675

5

40

5.4

1

0

0.029412

0.15

40

3

21

13.333333

0.764706

0.45

0

0.4

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

b48168930bbe2bb695b47d99581f63e11478b98f

129

py

Python

forex/admin.py

Shokr/Stocks-Screener

0b8da91da40b715beaf3a79163b1bdf6ea3be3b9

[ "MIT" ]

1

2021-06-28T23:08:51.000Z

forex/admin.py

Shokr/Stocks-Screener

0b8da91da40b715beaf3a79163b1bdf6ea3be3b9

[ "MIT" ]

40

2020-03-06T10:24:55.000Z

2022-03-12T00:56:44.000Z

forex/admin.py

Shokr/Stocks-Screener

0b8da91da40b715beaf3a79163b1bdf6ea3be3b9

[ "MIT" ]

3

2020-01-19T07:27:24.000Z

2021-09-11T10:09:25.000Z

from django.contrib import admin from forex.froms import Currency # Register your models here. admin.site.register(Currency)

14.333333

32

0.79845

18

129

5.722222

0.722222

0

0.139535

129

8

33

16.125

0.927928

0.20155

0

1

0

true

0

0.666667

0

0.666667

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1

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null

0

1

0

1

0

1

0

5

c30f073fb033a503d24e113794d48e97a857cd31

88

py

Python

slave/app/pulls/__init__.py

darksigma/traceless

eed3a35e90b8bbbf272e1f324e1c28de7afe08da

[ "MIT" ]

1

2015-06-19T14:27:52.000Z

slave/app/pulls/__init__.py

pratheeknagaraj/securechat

eed3a35e90b8bbbf272e1f324e1c28de7afe08da

[ "MIT" ]

null

slave/app/pulls/__init__.py

pratheeknagaraj/securechat

eed3a35e90b8bbbf272e1f324e1c28de7afe08da

[ "MIT" ]

1

2016-04-09T19:25:11.000Z

from flask import Blueprint pulls = Blueprint('pulls', __name__) from . import routes

14.666667

36

0.761364

11

88

5.727273

0.636364

0.444444

0

0.159091

88

5

37

17.6

0.851351

0

0.056818

0

1

0

false

0

0.666667

0

0.666667

1

0

null

1

0

1

0

null

0

1

0

1

0

5

c31bf247f1306151cec5627d0a7771767e7d85d7

2,351

py

Python

tests/permutils/test_stats.py

quintant/Permuta

4cdc7990e3dc298d0089ba8c48cd8967acd9b81f

[ "BSD-3-Clause" ]

12

2015-09-09T02:40:50.000Z

2021-06-02T13:40:25.000Z

tests/permutils/test_stats.py

quintant/Permuta

4cdc7990e3dc298d0089ba8c48cd8967acd9b81f

[ "BSD-3-Clause" ]

80

2015-12-17T15:00:17.000Z

2022-01-25T20:31:54.000Z

tests/permutils/test_stats.py

quintant/Permuta

4cdc7990e3dc298d0089ba8c48cd8967acd9b81f

[ "BSD-3-Clause" ]

19

2015-12-16T13:16:10.000Z

2021-06-01T14:37:33.000Z

from permuta import Av from permuta.permutils.statistics import PermutationStatistic def test_distribution_all_perms(): assert sum(PermutationStatistic.inv().distribution_up_to(7), []) == [ 1, 1, 1, 1, 1, 2, 2, 1, 1, 3, 5, 6, 5, 3, 1, 1, 4, 9, 15, 20, 22, 20, 15, 9, 4, 1, 1, 5, 14, 29, 49, 71, 90, 101, 101, 90, 71, 49, 29, 14, 5, 1, 1, 6, 20, 49, 98, 169, 259, 359, 455, 531, 573, 573, 531, 455, 359, 259, 169, 98, 49, 20, 6, 1, ] assert PermutationStatistic.maj().distribution_for_length(8) == [ 1, 7, 27, 76, 174, 343, 602, 961, 1415, 1940, 2493, 3017, 3450, 3736, 3836, 3736, 3450, 3017, 2493, 1940, 1415, 961, 602, 343, 174, 76, 27, 7, 1, ] def test_distribution_av(): assert sum( PermutationStatistic.des().distribution_up_to(11, Av.from_string("123")), [] ) == [ 1, 1, 1, 1, 0, 4, 1, 0, 2, 11, 1, 0, 0, 15, 26, 1, 0, 0, 5, 69, 57, 1, 0, 0, 0, 56, 252, 120, 1, 0, 0, 0, 14, 364, 804, 247, 1, 0, 0, 0, 0, 210, 1800, 2349, 502, 1, 0, 0, 0, 0, 42, 1770, 7515, 6455, 1013, 1, 0, 0, 0, 0, 0, 792, 11055, 27940, 16962, 2036, 1, ]

13.282486

84

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206

2,351

2.975728

0.417476

0.052202

0.044046

0.032626

0.02447

0

0.395709

0.643131

2,351

176

85

13.357955

0.334923

0

0.77907

0

0.001276

0

0.017442

1

0.011628

true

0

0.011628

0

0.023256

0

null

0

1

0

1

0

1

0

null

0

1

0

5

c33ae417974841443f9d3d480f417e86768f558d

292

py

Python

own_blockchain_sdk/__init__.py

Muncan90/OwnBlockchainSdkPython

730b519eca99629d6ee4b006d70b5fde7e7031fa

[ "MIT" ]

1

2020-06-23T17:03:03.000Z

own_blockchain_sdk/__init__.py

Muncan90/OwnBlockchainSdkPython

730b519eca99629d6ee4b006d70b5fde7e7031fa

[ "MIT" ]

null

own_blockchain_sdk/__init__.py

Muncan90/OwnBlockchainSdkPython

730b519eca99629d6ee4b006d70b5fde7e7031fa

[ "MIT" ]

1

2020-07-09T04:09:20.000Z

from own_blockchain_sdk.crypto import encode64, decode64, encode58, decode58, \ hash, derive_hash, \ generate_wallet, address_from_private_key, wallet_from_private_key, Wallet, sign_message, sign_plain_text, verify_plain_text_signature from own_blockchain_sdk.transactions import Tx

48.666667

138

0.839041

40

292

5.675

0.625

0.061674

0.14978

0.176211

0

0.030651

0.106164

292

5

139

58.4

0.83908

0

1

0

1

0

true

0

0.5

0

0.5

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null

0

1

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1

0

1

0

null

0

1

0

1

0

5

c33e00e451f84e278456f18bebb719f3dcb4ceba

135

py

Python

fusion/criterion/mi_estimator/critic/base_critic.py

Mrinal18/fusion

34e563f2e50139385577c3880c5de11f8a73f220

[ "BSD-3-Clause" ]

14

2021-04-05T01:25:12.000Z

2022-02-17T19:44:28.000Z

fusion/criterion/mi_estimator/critic/base_critic.py

Mrinal18/fusion

34e563f2e50139385577c3880c5de11f8a73f220

[ "BSD-3-Clause" ]

1

2021-07-05T08:32:49.000Z

2021-07-05T12:34:57.000Z

fusion/criterion/mi_estimator/critic/base_critic.py

Mrinal18/fusion

34e563f2e50139385577c3880c5de11f8a73f220

[ "BSD-3-Clause" ]

1

2022-02-01T21:56:11.000Z

import abc from torch import Tensor class ABaseCritic(abc.ABC): def __call__(self, x: Tensor, y: Tensor) -> Tensor: pass

16.875

55

0.674074

19

135

4.578947

0.684211

0

0.22963

135

7

56

19.285714

0.836538

0

1

0.2

false

0.2

0.4

0

0.8

0

1

0

null

0

1

0

null

0

1

0

1

0

5

c35955a44ee17802df94f2fa3143422f91ff3d81

638

py

Python

test/tests/dict.py

jonco3/dynamic

76d10b012a7860595c7d9abbdf542c7d8f2a4d53

[ "MIT" ]

1

2020-11-26T23:37:19.000Z

test/tests/dict.py

jonco3/dynamic

76d10b012a7860595c7d9abbdf542c7d8f2a4d53

[ "MIT" ]

null

test/tests/dict.py

jonco3/dynamic

76d10b012a7860595c7d9abbdf542c7d8f2a4d53

[ "MIT" ]

null

# output: ok a = {} assert(len(a) == 0) for i in range(0, 100): a[i] = i * 2 assert(len(a) == 100) for i in range(0, 100): assert i in a assert(a[i] == i * 2) assert 101 not in a for i in range(0, 100, 2): del a[i] assert(len(a) == 50) for i in range(0, 100): assert (i in a) == ((i % 2) != 0) a = {} for i in range(0, 100): a[str(i)] = i assert(len(a) == 100) for i in range(0, 100): k = str(i) assert k in a assert(a[k] == i) assert '101' not in a for i in range(0, 100, 2): del a[str(i)] assert(len(a) == 50) for i in range(0, 100): assert (str(i) in a) == ((i % 2) != 0) print('ok')

16.789474

42

0.510972

136

638

2.397059

0.139706

0.101227

0.147239

0.269939

0.791411

0.769939

0.739264

0.638037

0

0.124183

0.280564

638

37

43

17.243243

0.586057

0.015674

0

0.482759

0

0.007987

0

0.448276

1

0

false

0

0.034483

0

null

0

1

0

1

0

1

0

null

0

1

0

5

c37008ebbba38d989e1e9087d8f9d9d569f9d1e6

14,145

py

Python

codes/models/modules/Subnet_constructor.py

lin-zhao-resoLve/Symmetric-Enhancement

11c1a662020582d1333d11cf5f9c99556ec0f427

[ "Apache-2.0" ]

14

2021-09-30T07:05:04.000Z

2022-03-31T08:22:39.000Z

codes/models/modules/Subnet_constructor.py

lin-zhao-resoLve/Symmetric-Enhancement

11c1a662020582d1333d11cf5f9c99556ec0f427

[ "Apache-2.0" ]

3

2021-11-09T06:52:13.000Z

2021-11-20T08:00:46.000Z

codes/models/modules/Subnet_constructor.py

lin-zhao-resoLve/Symmetric-Enhancement

11c1a662020582d1333d11cf5f9c99556ec0f427

[ "Apache-2.0" ]

null

import torch import torch.nn as nn import torch.nn.functional as F import models.modules.module_util as mutil # from MPNCOV.python import MPNCOV class DenseBlock(nn.Module): def __init__(self, channel_in, channel_out, init='xavier', gc=32, bias=True): super(DenseBlock, self).__init__() self.conv1 = nn.Conv2d(channel_in, gc, 3, 1, 1, bias=bias) self.conv2 = nn.Conv2d(channel_in + gc, gc, 3, 1, 1, bias=bias) self.conv3 = nn.Conv2d(channel_in + 2 * gc, gc, 3, 1, 1, bias=bias) self.conv4 = nn.Conv2d(channel_in + 3 * gc, gc, 3, 1, 1, bias=bias) self.conv5 = nn.Conv2d(channel_in + 4 * gc, channel_out, 3, 1, 1, bias=bias) # self.lrelu = nn.LeakyReLU(negative_slope=0.2, inplace=True) self.prelu = nn.PReLU(num_parameters=1, init=0.2) if init == 'xavier': mutil.initialize_weights_xavier([self.conv1, self.conv2, self.conv3, self.conv4], 0.1) else: mutil.initialize_weights([self.conv1, self.conv2, self.conv3, self.conv4], 0.1) mutil.initialize_weights(self.conv5, 0) def forward(self, x): x1 = self.prelu(self.conv1(x)) x2 = self.prelu(self.conv2(torch.cat((x, x1), 1))) x3 = self.prelu(self.conv3(torch.cat((x, x1, x2), 1))) x4 = self.prelu(self.conv4(torch.cat((x, x1, x2, x3), 1))) x5 = self.conv5(torch.cat((x, x1, x2, x3, x4), 1)) return x5 class FBBlock(nn.Module): def __init__(self, channel_in, channel_out, init='xavier', gc=64, bias=True): super(FBBlock, self).__init__() self.conv1 = nn.Conv2d(channel_in, gc, 3, 1, 1, bias=bias) self.conv2 = nn.Conv2d(gc, gc, 3, 1, 1, bias=bias) self.conv3 = nn.Conv2d(channel_in + gc, gc, 3, 1, 1, bias=bias) self.conv4 = nn.Conv2d(2*gc, gc, 3, 1, 1, bias=bias) self.conv5 = nn.Conv2d(channel_in + 2 * gc, gc, 3, 1, 1, bias=bias) self.conv6 = nn.Conv2d(3 * gc, gc, 3, 1, 1, bias=bias) self.conv7 = nn.Conv2d(3 * gc, channel_out, 1) # self.lrelu = nn.LeakyReLU(negative_slope=0.2, inplace=True) self.prelu = nn.PReLU(num_parameters=1, init=0.2) if init == 'xavier': mutil.initialize_weights_xavier([self.conv1, self.conv2, self.conv3, self.conv4, self.conv5, self.conv6], 0.1) else: mutil.initialize_weights([self.conv1, self.conv2, self.conv3, self.conv4, self.conv5, self.conv6], 0.1) mutil.initialize_weights(self.conv7, 0) def forward(self, x): x1 = self.prelu(self.conv1(x)) x2 = self.prelu(self.conv2(x1)) x3 = self.prelu(self.conv3(torch.cat((x, x2), 1))) x4 = self.prelu(self.conv4(torch.cat((x1, x3), 1))) x5 = self.prelu(self.conv5(torch.cat((x, x2, x4), 1))) x6 = self.prelu(self.conv6(torch.cat((x1, x3, x5), 1))) x7 = self.conv7(torch.cat((x2, x4, x6), 1)) return x7 ## second-order Channel attention (SOCA) class SOCA(nn.Module): def __init__(self, channel, reduction=16): super(SOCA, self).__init__() # global average pooling: feature --> point # self.avg_pool = nn.AdaptiveAvgPool2d(1) # self.max_pool = nn.AdaptiveMaxPool2d(1) self.avg_pool = nn.AdaptiveAvgPool2d(1) # feature channel downscale and upscale --> channel weight self.conv_du = nn.Sequential( nn.Conv2d(channel, channel // reduction, 1, padding=0, bias=True), nn.PReLU(num_parameters=1, init=0.2), nn.Conv2d(channel // reduction, channel, 1, padding=0, bias=True), nn.Sigmoid() # nn.BatchNorm2d(channel) ) def forward(self, x): b, c, _, _ = x.size() y = self.avg_pool(x).view(b, c, 1, 1) y = self.conv_du(y).view(b, c, 1, 1) return x * y.expand_as(x) class ResidualBlock_noBN_S0(nn.Module): '''Residual block w/o BN ---Conv-ReLU-Conv-+- |________________| ''' def __init__(self, nf=64): super(ResidualBlock_noBN_S0, self).__init__() self.conv1 = nn.Conv2d(nf, nf*2, 3, 1, 1, bias=True) self.conv2 = nn.Conv2d(nf*2, nf, 3, 1, 1, bias=True) self.prelu = nn.PReLU(num_parameters=1, init=0.2) self.so = (SOCA(nf)) # initialization mutil.initialize_weights([self.conv1, self.conv2, self.so], 0.1) def forward(self, x): identity = x out = self.prelu(self.conv1(x)) out = self.so(self.conv2(out)) return identity + out class ResidualBlock_AT(nn.Module): def __init__(self, channel_in, channel_out, init='xavier', gc=64, bias=True): super(ResidualBlock_AT, self).__init__() self.conv1 = nn.Conv2d(channel_in, gc, 3, 1, 1, bias=bias) # self.res_list = nn.ModuleList([mutil.ResidualBlock_noBN(gc) for _ in range(3)]) self.res1 = ResidualBlock_noBN_S0(gc) self.res2 = ResidualBlock_noBN_S0(gc) self.res3 = ResidualBlock_noBN_S0(gc) self.conv2 = nn.Conv2d(gc, channel_out, 3, 1, 1, bias=bias) self.prelu = nn.PReLU(num_parameters=1, init=0.2) self.soca = (SOCA(gc)) if init == 'xavier': mutil.initialize_weights_xavier([self.conv1], 0.1) else: mutil.initialize_weights([self.conv1], 0.1) mutil.initialize_weights(self.conv2, 0) def forward(self, x): x1 = self.prelu(self.conv1(x)) x2 = self.res1(x1) x3 = self.res2(x2) x4 = self.res3(x3) x5 = self.conv2(x4) return x5 class ResidualBlock_AT_skip(nn.Module): def __init__(self, channel_in, channel_out, init='xavier', gc=64, bias=True): super(ResidualBlock_AT_skip, self).__init__() self.conv1 = nn.Conv2d(channel_in, gc, 3, 1, 1, bias=bias) # self.res_list = nn.ModuleList([mutil.ResidualBlock_noBN(gc) for _ in range(3)]) self.res1 = ResidualBlock_noBN_S0(gc) self.res2 = ResidualBlock_noBN_S0(gc) self.res3 = ResidualBlock_noBN_S0(gc) self.conv2 = nn.Conv2d(gc, channel_out, 3, 1, 1, bias=bias) self.prelu = nn.PReLU(num_parameters=1, init=0.2) self.soca = (SOCA(gc)) if init == 'xavier': mutil.initialize_weights_xavier([self.conv1], 0.1) else: mutil.initialize_weights([self.conv1], 0.1) mutil.initialize_weights(self.conv2, 0) def forward(self, x): x1 = self.prelu(self.conv1(x)) x2 = self.res1(x1) x3 = self.res2(x2+x1) x4 = self.res3(x3+x2+x1) x5 = self.conv2(x4) return x5 class SELayer(nn.Module): def __init__(self, channel, reduction=16): super(SELayer, self).__init__() self.avg_pool = nn.AdaptiveAvgPool2d(1) self.fc = nn.Sequential( nn.Linear(channel, channel // reduction, bias=False), nn.PReLU(num_parameters=1, init=0.2), nn.Linear(channel // reduction, channel, bias=False), nn.Sigmoid() ) def forward(self, x): b, c, _, _ = x.size() y = self.avg_pool(x).view(b, c) y = self.fc(y).view(b, c, 1, 1) return x * y.expand_as(x) class ResidualBlock_noBN_SE(nn.Module): '''Residual block w/o BN ---Conv-ReLU-Conv-+- |________________| ''' def __init__(self, nf=64): super(ResidualBlock_noBN_SE, self).__init__() self.conv1 = nn.Conv2d(nf, nf*2, 3, 1, 1, bias=True) self.conv2 = nn.Conv2d(nf*2, nf, 3, 1, 1, bias=True) self.prelu = nn.PReLU(num_parameters=1, init=0.2) self.se = SELayer(nf) # initialization mutil.initialize_weights([self.conv1, self.conv2, self.se], 0.1) def forward(self, x): identity = x out = self.prelu(self.conv1(x)) out = self.se(self.conv2(out)) return identity + out class ResidualBlock_SE(nn.Module): def __init__(self, channel_in, channel_out, init='xavier', gc=64, bias=True): super(ResidualBlock_SE, self).__init__() self.conv1 = nn.Conv2d(channel_in, gc, 3, 1, 1, bias=bias) self.res1 = ResidualBlock_noBN_SE(gc) self.res2 = ResidualBlock_noBN_SE(gc) self.res3 = ResidualBlock_noBN_SE(gc) self.conv2 = nn.Conv2d(gc, channel_out, 3, 1, 1, bias=bias) self.prelu = nn.PReLU(num_parameters=1, init=0.2) self.se = SELayer(gc) if init == 'xavier': mutil.initialize_weights_xavier([self.conv1], 0.1) else: mutil.initialize_weights([self.conv1], 0.1) mutil.initialize_weights(self.conv2, 0) def forward(self, x): x1 = self.prelu(self.conv1(x)) x2 = self.res1(x1) x3 = self.res2(x2) x4 = self.res3(x3) x5 = self.conv2(x4) return x5 class atmLayer(nn.Module): def __init__(self, channel=6): super(atmLayer, self).__init__() self.fc = nn.Sequential( nn.Conv2d(channel, 64, 3, 1, 1), nn.PReLU(num_parameters=1, init=0.2), nn.Conv2d(64, 64, 3, 1, 1), nn.PReLU(num_parameters=1, init=0.2), nn.Conv2d(64, 1, 1, 1) ) mutil.initialize_weights([self.fc], 0.1) def forward(self, x): x = self.fc(x) return x class ResidualBlock_atm(nn.Module): def __init__(self, channel_in, channel_out, init='xavier', gc=64, bias=True): super(ResidualBlock_atm, self).__init__() self.conv1 = nn.Conv2d(channel_in, gc, 3, 1, 1, bias=bias) self.res1 = mutil.ResidualBlock_noBN(gc) self.map1 = atmLayer(channel_in) self.res2 = mutil.ResidualBlock_noBN(gc) self.map2 = atmLayer(channel_in) self.res3 = mutil.ResidualBlock_noBN(gc) self.map3 = atmLayer(channel_in) self.conv2 = nn.Conv2d(gc, channel_out, 3, 1, 1, bias=bias) self.prelu = nn.PReLU(num_parameters=1, init=0.2) if init == 'xavier': mutil.initialize_weights_xavier([self.conv1], 0.1) else: mutil.initialize_weights([self.conv1], 0.1) mutil.initialize_weights(self.conv2, 0) def forward(self, x): x1 = self.prelu(self.conv1(x)) x2 = self.res1(x1) * self.map1(x) x3 = self.res2(x2) * self.map2(x) x4 = self.res3(x3) * self.map3(x) x5 = self.conv2(x4) return x5 class ResidualBlock(nn.Module): def __init__(self, channel_in, channel_out, init='xavier', gc=64, bias=True): super(ResidualBlock, self).__init__() self.conv1 = nn.Conv2d(channel_in, gc, 3, 1, 1, bias=bias) self.res1 = mutil.ResidualBlock_noBN(gc) self.res2 = mutil.ResidualBlock_noBN(gc) self.res3 = mutil.ResidualBlock_noBN(gc) self.conv2 = nn.Conv2d(gc, channel_out, 3, 1, 1, bias=bias) self.prelu = nn.PReLU(num_parameters=1, init=0.2) if init == 'xavier': mutil.initialize_weights_xavier([self.conv1], 0.1) else: mutil.initialize_weights([self.conv1], 0.1) mutil.initialize_weights(self.conv2, 0) def forward(self, x): x1 = self.prelu(self.conv1(x)) x2 = self.res1(x1) x3 = self.res2(x2) x4 = self.res3(x3) x5 = self.conv2(x4) return x5 class ResidualNet(nn.Module): '''Residual block w/o BN ---Conv-ReLU-Conv-+- |________________| ''' def __init__(self, channel_in, channel_out, init='xavier', nf=64, bias=True): super(ResidualNet, self).__init__() self.conv1 = nn.Conv2d(channel_in, nf, 3, 1, 1, bias=True) self.conv2 = nn.Conv2d(nf, nf, 3, 1, 1, bias=True) self.conv3 = nn.Conv2d(nf, nf, 3, 1, 1, bias=True) self.conv4 = nn.Conv2d(nf, nf, 3, 1, 1, bias=True) self.conv5 = nn.Conv2d(nf, channel_out, 3, 1, 1, bias=True) self.prelu = nn.PReLU(num_parameters=1, init=0.2) # initialization if init == 'xavier': mutil.initialize_weights_xavier([self.conv1, self.conv2, self.conv3, self.conv4], 0.1) else: mutil.initialize_weights([self.conv1, self.conv2, self.conv3, self.conv4], 0.1) mutil.initialize_weights(self.conv5, 0) def forward(self, x): identity = x out = self.prelu(self.conv1(x)) out = self.prelu(self.conv2(out)) out = self.prelu(self.conv3(out)) out = self.prelu(self.conv4(out)) out = self.conv5(out) return identity + out def subnet(net_structure, init='xavier'): def constructor(channel_in, channel_out): if net_structure == 'DBNet': if init == 'xavier': return DenseBlock(channel_in, channel_out, init) else: return DenseBlock(channel_in, channel_out) elif net_structure == 'ResNet': if init == 'xavier': return ResidualNet(channel_in, channel_out, init) else: return ResidualNet(channel_in, channel_out) elif net_structure == 'ResAT2Net': if init == 'xavier': return ResidualBlock_AT(channel_in, channel_out, init) else: return ResidualBlock_AT(channel_in, channel_out) elif net_structure == 'ResAT2Net_skip': if init == 'xavier': return ResidualBlock_AT_skip(channel_in, channel_out, init) else: return ResidualBlock_AT_skip(channel_in, channel_out) elif net_structure == 'ResNet_SE': if init == 'xavier': return ResidualBlock_SE(channel_in, channel_out, init) else: return ResidualBlock_SE(channel_in, channel_out) elif net_structure == 'ResNet_atm': if init == 'xavier': return ResidualBlock_atm(channel_in, channel_out, init) else: return ResidualBlock_atm(channel_in, channel_out) elif net_structure == 'FBNet': if init == 'xavier': return FBBlock(channel_in, channel_out, init) else: return FBBlock(channel_in, channel_out) else: return None return constructor

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0

5

5ee434cb8445c7b25537aee5cb2b09397197a2d1

136

py

Python

fooof/__init__.py

TheCheeseToast/fooof

f3f8422af7d87fa73772e083deaf8439ca59908d

[ "Apache-2.0" ]

null

fooof/__init__.py

TheCheeseToast/fooof

f3f8422af7d87fa73772e083deaf8439ca59908d

[ "Apache-2.0" ]

null

fooof/__init__.py

TheCheeseToast/fooof

f3f8422af7d87fa73772e083deaf8439ca59908d

[ "Apache-2.0" ]

null

"""FOOOF - Fitting Oscillations & One-Over F""" from .version import __version__ from .fit import FOOOF from .group import FOOOFGroup

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177

py

Python

Android/parser/webserver/test.py

Bravest-Ptt/Useful-Shell

75016ff44f218afce6b885af7b23fb801a7ef2d4

[ "Apache-2.0" ]

1

2020-05-31T08:46:45.000Z

Android/parser/webserver/test.py

Bravest-Ptt/Useful-Shell

75016ff44f218afce6b885af7b23fb801a7ef2d4

[ "Apache-2.0" ]

null

Android/parser/webserver/test.py

Bravest-Ptt/Useful-Shell

75016ff44f218afce6b885af7b23fb801a7ef2d4

[ "Apache-2.0" ]

null

import subprocess sys_command = "gedit /home/qinsw/pengtian/shell/Useful-Shell/Android/parser/html/html/websocket.html".encode('utf-8') subprocess.Popen(sys_command, shell=True)

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5

5eef24c797dbd4502e427473033368654c5319fe

38,133

py

Python

api/tests/test_views.py

posm/osm-export-tool2

5a1f4096f1afbe7420363376e6e1e8d42e47e1d1

[ "BSD-3-Clause" ]

2

2018-08-31T18:30:28.000Z

2018-11-27T01:50:06.000Z

api/tests/test_views.py

posm/osm-export-tool2

5a1f4096f1afbe7420363376e6e1e8d42e47e1d1

[ "BSD-3-Clause" ]

null

api/tests/test_views.py

posm/osm-export-tool2

5a1f4096f1afbe7420363376e6e1e8d42e47e1d1

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- import json import logging import os import uuid from unittest import skip from mock import patch from django.contrib.auth.models import Group, User from django.contrib.gis.geos import GEOSGeometry, Polygon from django.core.files import File from rest_framework import status from rest_framework.authtoken.models import Token from rest_framework.reverse import reverse from rest_framework.test import APITestCase from api.pagination import LinkHeaderPagination from jobs.models import ExportConfig, ExportFormat, ExportProfile, Job from tasks.models import ExportRun, ExportTask logger = logging.getLogger(__name__) class TestJobViewSet(APITestCase): def setUp(self, ): self.path = os.path.dirname(os.path.realpath(__file__)) self.group = Group.objects.create(name='TestDefaultExportExtentGroup') profile = ExportProfile.objects.create( name='DefaultExportProfile', max_extent=2500000, group=self.group ) self.user = User.objects.create_user( username='demo', email='demo@demo.com', password='demo' ) extents = (-3.9, 16.1, 7.0, 27.6) bbox = Polygon.from_bbox(extents) the_geom = GEOSGeometry(bbox, srid=4326) self.job = Job.objects.create(name='TestJob', event='Test Activation', description='Test description', user=self.user, the_geom=the_geom) format = ExportFormat.objects.get(slug='obf') self.job.formats.add(format) token = Token.objects.create(user=self.user) self.client.credentials(HTTP_AUTHORIZATION='Token ' + token.key, HTTP_ACCEPT='application/json; version=1.0', HTTP_ACCEPT_LANGUAGE='en', HTTP_HOST='testserver') # create a test config f = File(open(self.path + '/files/hdm_presets.xml')) filename = f.name.split('/')[-1] name = 'Test Configuration File' self.config = ExportConfig.objects.create(name='Test Preset Config', filename=filename, upload=f, config_type='PRESET', user=self.user) f.close() self.assertIsNotNone(self.config) self.job.configs.add(self.config) self.tags = [ { "name": "Telecommunication office", "key": "office", "value": "telecommunication", "data_model": "HDM", "geom_types": ["point", "polygon"], "groups": ['HDM Presets v2.11', 'Commercial and Economic', 'Telecommunication'] }, { "name": "Radio or TV Studio", "key": "amenity", "value": "studio", "data_model": "OSM", "geom_types": ["point", "polygon"], "groups": ['HDM Presets v2.11', 'Commercial and Economic', 'Telecommunication'] }, { "name": "Telecommunication antenna", "key": "man_made", "value": "tower", "data_model": "OSM", "geom_types": ["point", "polygon"], "groups": ['HDM Presets v2.11', 'Commercial and Economic', 'Telecommunication'] }, { "name": "Telecommunication company retail office", "key": "office", "value": "telecommunication", "data_model": "OSM", "geom_types": ["point", "polygon"], "groups": ['HDM Presets v2.11', 'Commercial and Economic', 'Telecommunication'] } ] def tearDown(self,): self.config.delete() # clean up def test_list(self, ): expected = '/api/jobs' url = reverse('api:jobs-list') self.assertEquals(expected, url) def test_get_job_detail(self, ): expected = '/api/jobs/{0}'.format(self.job.uid) url = reverse('api:jobs-detail', args=[self.job.uid]) self.assertEquals(expected, url) data = {"uid": str(self.job.uid), "name": "Test", "url": 'http://testserver{0}'.format(url), "description": "Test Description", "exports": [{"uid": "8611792d-3d99-4c8f-a213-787bc7f3066", "url": "http://testserver/api/formats/obf", "name": "OBF Format", "description": "OSMAnd OBF Export Format."}], "created_at": "2015-05-21T19:46:37.163749Z", "updated_at": "2015-05-21T19:46:47.207111Z", "status": "SUCCESS"} response = self.client.get(url) # test the response headers self.assertEquals(response.status_code, status.HTTP_200_OK) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') # test significant content self.assertEquals(response.data['uid'], data['uid']) self.assertEquals(response.data['url'], data['url']) self.assertEqual(response.data['exports'][0]['url'], data['exports'][0]['url']) def test_delete_job(self, ): url = reverse('api:jobs-detail', args=[self.job.uid]) response = self.client.delete(url) # test the response headers self.assertEquals(response.status_code, status.HTTP_204_NO_CONTENT) self.assertEquals(response['Content-Length'], '0') self.assertEquals(response['Content-Language'], 'en') def test_delete_no_permissions(self, ): url = reverse('api:jobs-detail', args=[self.job.uid]) # create another user with token user = User.objects.create_user( username='other_user', email='other_user@demo.com', password='demo' ) token = Token.objects.create(user=user) # reset the client credentials to the new user self.client.credentials(HTTP_AUTHORIZATION='Token ' + token.key, HTTP_ACCEPT='application/json; version=1.0', HTTP_ACCEPT_LANGUAGE='en', HTTP_HOST='testserver') # try to delete a job belonging to self.user response = self.client.delete(url) # test the response headers self.assertEquals(response.status_code, status.HTTP_403_FORBIDDEN) @patch('api.views.ExportTaskRunner') def test_create_job_success(self, mock): task_runner = mock.return_value url = reverse('api:jobs-list') formats = [format.slug for format in ExportFormat.objects.all()] config_uid = self.config.uid request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': -3.9, 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, 'formats': formats, 'preset': config_uid, 'published': True, 'tags': self.tags } response = self.client.post(url, request_data, format='json') job_uid = response.data['uid'] # test the ExportTaskRunner.run_task(job_id) method gets called. task_runner.run_task.assert_called_once_with(job_uid=job_uid) # test the response headers self.assertEquals(response.status_code, status.HTTP_202_ACCEPTED) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') # test significant response content self.assertEqual(response.data['exports'][0]['slug'], request_data['formats'][0]) self.assertEqual(response.data['exports'][1]['slug'], request_data['formats'][1]) self.assertEqual(response.data['name'], request_data['name']) self.assertEqual(response.data['description'], request_data['description']) self.assertTrue(response.data['published']) # check we have the correct tags job = Job.objects.get(uid=job_uid) tags = job.tags.all() self.assertIsNotNone(tags) self.assertEquals(233, len(tags)) @patch('api.views.ExportTaskRunner') def test_create_job_with_config_success(self, mock): task_runner = mock.return_value config_uid = self.config.uid url = reverse('api:jobs-list') formats = [format.slug for format in ExportFormat.objects.all()] request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': -3.9, 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, 'formats': formats, 'preset': config_uid, 'transform': '', 'translation': '' } response = self.client.post(url, request_data, format='json') job_uid = response.data['uid'] # test the ExportTaskRunner.run_task(job_id) method gets called. task_runner.run_task.assert_called_once_with(job_uid=job_uid) # test the response headers self.assertEquals(response.status_code, status.HTTP_202_ACCEPTED) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') # test significant response content self.assertEqual(response.data['exports'][0]['slug'], request_data['formats'][0]) self.assertEqual(response.data['exports'][1]['slug'], request_data['formats'][1]) self.assertEqual(response.data['name'], request_data['name']) self.assertEqual(response.data['description'], request_data['description']) self.assertFalse(response.data['published']) configs = self.job.configs.all() self.assertIsNotNone(configs[0]) @patch('api.views.ExportTaskRunner') def test_create_job_with_tags(self, mock): # delete the existing tags and test adding them with json self.job.tags.all().delete() task_runner = mock.return_value config_uid = self.config.uid url = reverse('api:jobs-list') formats = [format.slug for format in ExportFormat.objects.all()] request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': -3.9, 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, 'formats': formats, # 'preset': config_uid, 'transform': '', 'translate': '', 'tags': self.tags } response = self.client.post(url, request_data, format='json') job_uid = response.data['uid'] # test the ExportTaskRunner.run_task(job_id) method gets called. task_runner.run_task.assert_called_once_with(job_uid=job_uid) # test the response headers self.assertEquals(response.status_code, status.HTTP_202_ACCEPTED) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') # test significant response content self.assertEqual(response.data['exports'][0]['slug'], request_data['formats'][0]) self.assertEqual(response.data['exports'][1]['slug'], request_data['formats'][1]) self.assertEqual(response.data['name'], request_data['name']) self.assertEqual(response.data['description'], request_data['description']) configs = self.job.configs.all() # self.assertIsNotNone(configs[0]) def test_missing_bbox_param(self, ): url = reverse('api:jobs-list') formats = [format.slug for format in ExportFormat.objects.all()] request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', # 'xmin': -3.9, missing 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, 'formats': formats } response = self.client.post(url, request_data) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(['xmin is required.'], response.data['xmin']) def test_invalid_bbox_param(self, ): url = reverse('api:jobs-list') formats = [str(format.uid) for format in ExportFormat.objects.all()] request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': '', # empty 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, 'formats': formats } response = self.client.post(url, request_data, format='json') self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(['invalid xmin value.'], response.data['xmin']) def test_invalid_bbox(self, ): url = reverse('api:jobs-list') formats = [format.slug for format in ExportFormat.objects.all()] request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': 7.0, # invalid 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, 'formats': formats } response = self.client.post(url, request_data) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(['invalid_bounds'], response.data['id']) def test_lat_lon_bbox(self, ): url = reverse('api:jobs-list') formats = [str(format.uid) for format in ExportFormat.objects.all()] request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': -227.14, # invalid 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, 'formats': formats } response = self.client.post(url, request_data) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(["Ensure this value is greater than or equal to -180."], response.data['xmin']) def test_coord_nan(self, ): url = reverse('api:jobs-list') formats = [format.slug for format in ExportFormat.objects.all()] request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': 'xyz', # invalid 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, 'formats': formats } response = self.client.post(url, request_data) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(['invalid xmin value.'], response.data['xmin']) def test_inverted_coords(self, ): url = reverse('api:jobs-list') formats = [format.slug for format in ExportFormat.objects.all()] request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': 7.0, # inverted 'ymin': 16.1, 'xmax': -3.9, # inverted 'ymax': 27.6, 'formats': formats } response = self.client.post(url, request_data) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(['inverted_coordinates'], response.data['id']) def test_empty_string_param(self, ): url = reverse('api:jobs-list') formats = [format.slug for format in ExportFormat.objects.all()] request_data = { 'name': 'TestJob', 'description': '', # empty 'event': 'Test Activation', 'xmin': -3.9, 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, 'formats': formats } response = self.client.post(url, request_data) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(['This field may not be blank.'], response.data['description']) def test_missing_format_param(self, ): url = reverse('api:jobs-list') request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': -3.9, 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, # 'formats': '', # missing } response = self.client.post(url, request_data) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(['Select an export format.'], response.data['formats']) def test_invalid_format_param(self, ): url = reverse('api:jobs-list') request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': -3.9, 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, 'formats': '', # invalid } response = self.client.post(url, request_data) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertIsNotNone(response.data['formats']) def test_no_matching_format_slug(self, ): url = reverse('api:jobs-list') request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': -3.9, 'ymin': 16.1, 'xmax': 7.0, 'ymax': 27.6, 'formats': ['broken-format-one', 'broken-format-two'] } response = self.client.post(url, request_data) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(response.data['formats'], ['invalid export format.']) @patch('api.views.ExportTaskRunner') def test_get_correct_region(self, mock): task_runner = mock.return_value url = reverse('api:jobs-list') formats = [format.slug for format in ExportFormat.objects.all()] # job extent spans africa / asia but greater intersection with asia request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': 36.90, 'ymin': 13.54, 'xmax': 48.52, 'ymax': 20.24, 'formats': formats } response = self.client.post(url, request_data, format='json') job_uid = response.data['uid'] # test the ExportTaskRunner.run_task(job_id) method gets called. task_runner.run_task.assert_called_once_with(job_uid=job_uid) # test the response headers self.assertEquals(response.status_code, status.HTTP_202_ACCEPTED) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') # test significant response content self.assertEqual(response.data['exports'][0]['slug'], request_data['formats'][0]) self.assertEqual(response.data['exports'][1]['slug'], request_data['formats'][1]) self.assertEqual(response.data['name'], request_data['name']) self.assertEqual(response.data['description'], request_data['description']) # test the region region = response.data['region'] self.assertIsNotNone(region) self.assertEquals(region['name'], 'Central Asia/Middle East') def test_invalid_region(self, ): url = reverse('api:jobs-list') formats = [format.slug for format in ExportFormat.objects.all()] # job outside any region request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': 2.74, 'ymin': 47.66, 'xmax': 11.61, 'ymax': 54.24, 'formats': formats } response = self.client.post(url, request_data) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(['invalid_region'], response.data['id']) def test_extents_too_large(self, ): url = reverse('api:jobs-list') formats = [format.slug for format in ExportFormat.objects.all()] # job outside any region request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': -40, 'ymin': -10, 'xmax': 40, 'ymax': 20, 'formats': formats } response = self.client.post(url, request_data) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(['invalid_extents'], response.data['id']) class TestBBoxSearch(APITestCase): """ Test cases for testing bounding box searches. """ @patch('api.views.ExportTaskRunner') def setUp(self, mock): task_runner = mock.return_value url = reverse('api:jobs-list') # create dummy user Group.objects.create(name='TestDefaultExportExtentGroup') self.user = User.objects.create_user( username='demo', email='demo@demo.com', password='demo' ) # setup token authentication token = Token.objects.create(user=self.user) self.client.credentials(HTTP_AUTHORIZATION='Token ' + token.key, HTTP_ACCEPT='application/json; version=1.0', HTTP_ACCEPT_LANGUAGE='en', HTTP_HOST='testserver') # pull out the formats formats = [format.slug for format in ExportFormat.objects.all()] # create test jobs extents = [(-3.9, 16.1, 7.0, 27.6), (36.90, 13.54, 48.52, 20.24), (-71.79, -49.57, -67.14, -46.16), (-61.27, -6.49, -56.20, -2.25), (-11.61, 32.07, -6.42, 36.31), (-10.66, 5.81, -2.45, 11.83), (47.26, 34.58, 52.92, 39.15), (90.00, 11.28, 95.74, 17.02)] for extent in extents: request_data = { 'name': 'TestJob', 'description': 'Test description', 'event': 'Test Activation', 'xmin': extent[0], 'ymin': extent[1], 'xmax': extent[2], 'ymax': extent[3], 'formats': formats } response = self.client.post(url, request_data, format='json') self.assertEquals(status.HTTP_202_ACCEPTED, response.status_code) self.assertEquals(8, len(Job.objects.all())) LinkHeaderPagination.page_size = 2 def test_bbox_search_success(self, ): url = reverse('api:jobs-list') extent = (-79.5, -16.16, 7.40, 52.44) param = 'bbox={0},{1},{2},{3}'.format(extent[0], extent[1], extent[2], extent[3]) response = self.client.get('{0}?{1}'.format(url, param)) self.assertEquals(status.HTTP_206_PARTIAL_CONTENT, response.status_code) self.assertEquals(2, len(response.data)) # 8 jobs in total but response is paginated def test_list_jobs_no_bbox(self, ): url = reverse('api:jobs-list') response = self.client.get(url) self.assertEquals(status.HTTP_206_PARTIAL_CONTENT, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals(response['Link'], '<http://testserver/api/jobs?page=2>; rel="next"') self.assertEquals(2, len(response.data)) # 8 jobs in total but response is paginated def test_bbox_search_missing_params(self, ): url = reverse('api:jobs-list') param = 'bbox=' # missing params response = self.client.get('{0}?{1}'.format(url, param)) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals('missing_bbox_parameter', response.data['id']) def test_bbox_missing_coord(self, ): url = reverse('api:jobs-list') extent = (-79.5, -16.16, 7.40) # one missing param = 'bbox={0},{1},{2}'.format(extent[0], extent[1], extent[2]) response = self.client.get('{0}?{1}'.format(url, param)) self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response['Content-Type'], 'application/json; version=1.0') self.assertEquals(response['Content-Language'], 'en') self.assertEquals('missing_bbox_parameter', response.data['id']) class TestPagination(APITestCase): pass class TestExportRunViewSet(APITestCase): """ Test cases for ExportRunViewSet """ def setUp(self, ): Group.objects.create(name='TestDefaultExportExtentGroup') self.user = User.objects.create(username='demo', email='demo@demo.com', password='demo') token = Token.objects.create(user=self.user) self.client.credentials(HTTP_AUTHORIZATION='Token ' + token.key, HTTP_ACCEPT='application/json; version=1.0', HTTP_ACCEPT_LANGUAGE='en', HTTP_HOST='testserver') extents = (-3.9, 16.1, 7.0, 27.6) bbox = Polygon.from_bbox(extents) the_geom = GEOSGeometry(bbox, srid=4326) self.job = Job.objects.create(name='TestJob', description='Test description', user=self.user, the_geom=the_geom) self.job_uid = str(self.job.uid) self.run = ExportRun.objects.create(job=self.job, user=self.user) self.run_uid = str(self.run.uid) def test_retrieve_run(self, ): expected = '/api/runs/{0}'.format(self.run_uid) url = reverse('api:runs-detail', args=[self.run_uid]) self.assertEquals(expected, url) response = self.client.get(url) self.assertIsNotNone(response) result = response.data # make sure we get the correct uid back out self.assertEquals(self.run_uid, result[0].get('uid')) def test_list_runs(self, ): expected = '/api/runs' url = reverse('api:runs-list') self.assertEquals(expected, url) query = '{0}?job_uid={1}'.format(url, self.job.uid) response = self.client.get(query) self.assertIsNotNone(response) result = response.data # make sure we get the correct uid back out self.assertEquals(1, len(result)) self.assertEquals(self.run_uid, result[0].get('uid')) class TestExportConfigViewSet(APITestCase): """ Test cases for ExportConfigViewSet """ def setUp(self, ): self.path = os.path.dirname(os.path.realpath(__file__)) Group.objects.create(name='TestDefaultExportExtentGroup') self.user = User.objects.create(username='demo', email='demo@demo.com', password='demo') bbox = Polygon.from_bbox((-7.96, 22.6, -8.14, 27.12)) the_geom = GEOSGeometry(bbox, srid=4326) self.job = Job.objects.create(name='TestJob', description='Test description', user=self.user, the_geom=the_geom) self.uid = self.job.uid # setup token authentication token = Token.objects.create(user=self.user) self.client.credentials(HTTP_AUTHORIZATION='Token ' + token.key, HTTP_ACCEPT='application/json; version=1.0', HTTP_ACCEPT_LANGUAGE='en', HTTP_HOST='testserver') def test_create_config(self, ): url = reverse('api:configs-list') path = os.path.dirname(os.path.realpath(__file__)) f = File(open(path + '/files/Example Transform.sql', 'r')) name = 'Test Export Config' response = self.client.post(url, {'name': name, 'upload': f, 'config_type': 'TRANSFORM', 'published': True}, format='multipart') data = response.data uid = data['uid'] saved_config = ExportConfig.objects.get(uid=uid) self.assertIsNotNone(saved_config) self.assertEquals(name, saved_config.name) self.assertTrue(saved_config.published) self.assertEquals('example_transform.sql', saved_config.filename) self.assertEquals('text/plain', saved_config.content_type) saved_config.delete() def test_delete_no_permissions(self, ): """ Test deletion of configuration when the user has no object permissions. """ post_url = reverse('api:configs-list') path = os.path.dirname(os.path.realpath(__file__)) f = File(open(path + '/files/hdm_presets.xml', 'r')) name = 'Test Export Preset' response = self.client.post(post_url, {'name': name, 'upload': f, 'config_type': 'PRESET', 'published': True}, format='multipart') data = response.data uid = data['uid'] saved_config = ExportConfig.objects.get(uid=uid) self.assertIsNotNone(saved_config) self.assertEquals(name, saved_config.name) self.assertTrue(saved_config.published) self.assertEquals('hdm_presets.xml', saved_config.filename) self.assertEquals('application/xml', saved_config.content_type) delete_url = reverse('api:configs-detail', args=[uid]) # create another user with token user = User.objects.create_user( username='other_user', email='other_user@demo.com', password='demo' ) token = Token.objects.create(user=user) # reset the client credentials to the new user self.client.credentials(HTTP_AUTHORIZATION='Token ' + token.key, HTTP_ACCEPT='application/json; version=1.0', HTTP_ACCEPT_LANGUAGE='en', HTTP_HOST='testserver') # try to delete a configuration belonging to self.user response = self.client.delete(delete_url) # test the response headers self.assertEquals(response.status_code, status.HTTP_403_FORBIDDEN) saved_config.delete() def test_invalid_config_type(self, ): url = reverse('api:configs-list') path = os.path.dirname(os.path.realpath(__file__)) f = open(path + '/files/Example Transform.sql', 'r') self.assertIsNotNone(f) response = self.client.post(url, {'upload': f, 'config_type': 'TRANSFORM-WRONG'}, format='multipart') self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) def test_invalid_preset(self, ): url = reverse('api:configs-list') path = os.path.dirname(os.path.realpath(__file__)) f = open(path + '/files/invalid_hdm_presets.xml', 'r') self.assertIsNotNone(f) response = self.client.post(url, {'name': 'Invalid Preset', 'upload': f, 'config_type': 'PRESET'}, format='multipart') self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) def test_invalid_name(self, ): url = reverse('api:configs-list') path = os.path.dirname(os.path.realpath(__file__)) f = open(path + '/files/Example Transform.sql', 'r') self.assertIsNotNone(f) response = self.client.post(url, {'upload': f, 'config_type': 'TRANSFORM'}, format='multipart') self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) self.assertEquals(response.data['name'], ['This field is required.']) def test_invalid_upload(self, ): url = reverse('api:configs-list') response = self.client.post(url, {'upload': '', 'config_type': 'TRANSFORM-WRONG'}, format='multipart') self.assertEquals(status.HTTP_400_BAD_REQUEST, response.status_code) @skip('Transform not implemented.') def test_update_config(self, ): url = reverse('api:configs-list') # create an initial config we can then update.. path = os.path.dirname(os.path.realpath(__file__)) f = File(open(path + '/files/Example Transform.sql', 'r')) name = 'Test Export Config' response = self.client.post(url, {'name': name, 'upload': f, 'config_type': 'TRANSFORM'}, format='multipart') data = response.data saved_uid = data['uid'] saved_config = ExportConfig.objects.get(uid=saved_uid) # update the config url = reverse('api:configs-detail', args=[saved_uid]) f = File(open(path + '/files/hdm_presets.xml', 'r')) updated_name = 'Test Export Config Updated' response = self.client.put(url, {'name': updated_name, 'upload': f, 'config_type': 'PRESET'}, format='multipart') data = response.data updated_uid = data['uid'] self.assertEquals(saved_uid, updated_uid) # check its the same uid updated_config = ExportConfig.objects.get(uid=updated_uid) self.assertIsNotNone(updated_config) self.assertEquals('hdm_presets.xml', updated_config.filename) self.assertEquals('application/xml', updated_config.content_type) self.assertEquals('Test Export Config Updated', updated_config.name) updated_config.delete() try: f = File(open(path + '/files/Example Transform.sql', 'r')) except IOError: pass # expected.. old file has been deleted during update. class TestExportTaskViewSet(APITestCase): """ Test cases for ExportTaskViewSet """ def setUp(self, ): self.path = os.path.dirname(os.path.realpath(__file__)) Group.objects.create(name='TestDefaultExportExtentGroup') self.user = User.objects.create(username='demo', email='demo@demo.com', password='demo') bbox = Polygon.from_bbox((-7.96, 22.6, -8.14, 27.12)) the_geom = GEOSGeometry(bbox, srid=4326) self.job = Job.objects.create(name='TestJob', description='Test description', user=self.user, the_geom=the_geom) # setup token authentication token = Token.objects.create(user=self.user) self.client.credentials(HTTP_AUTHORIZATION='Token ' + token.key, HTTP_ACCEPT='application/json; version=1.0', HTTP_ACCEPT_LANGUAGE='en', HTTP_HOST='testserver') self.run = ExportRun.objects.create(job=self.job) self.celery_uid = str(uuid.uuid4()) self.task = ExportTask.objects.create(run=self.run, name='Shapefile Export', celery_uid=self.celery_uid, status='SUCCESS') self.task_uid = str(self.task.uid) def test_retrieve(self, ): expected = '/api/tasks/{0}'.format(self.task_uid) url = reverse('api:tasks-detail', args=[self.task_uid]) self.assertEquals(expected, url) response = self.client.get(url) self.assertIsNotNone(response) self.assertEquals(200, response.status_code) result = json.dumps(response.data) data = json.loads(result) # make sure we get the correct uid back out self.assertEquals(self.task_uid, data[0].get('uid')) def test_list(self, ): expected = '/api/tasks'.format(self.task_uid) url = reverse('api:tasks-list') self.assertEquals(expected, url) response = self.client.get(url) self.assertIsNotNone(response) self.assertEquals(200, response.status_code) result = json.dumps(response.data) data = json.loads(result) # should only be one task in the list self.assertEquals(1, len(data)) # make sure we get the correct uid back out self.assertEquals(self.task_uid, data[0].get('uid'))

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6f039823adc1ecaf384a349c676b625abf54c7f1

4,929

py

Python

tests/test_validator.py

benoit9126/drf-recaptcha

959613c41585e500c42bfd74ced05e5f096282d9

[ "MIT" ]

null

tests/test_validator.py

benoit9126/drf-recaptcha

959613c41585e500c42bfd74ced05e5f096282d9

[ "MIT" ]

null

tests/test_validator.py

benoit9126/drf-recaptcha

959613c41585e500c42bfd74ced05e5f096282d9

[ "MIT" ]

null

from unittest import mock import pytest from rest_framework.serializers import ValidationError from drf_recaptcha.client import RecaptchaResponse from drf_recaptcha.validators import ReCaptchaV2Validator, ReCaptchaV3Validator @pytest.mark.parametrize( ("validator_class", "params"), [ (ReCaptchaV2Validator, {}), (ReCaptchaV3Validator, {"action": "test_action", "required_score": 0.4}), ], ) def test_recaptcha_validator_get_response_success(validator_class, params): validator = validator_class(secret_key="TEST_SECRET_KEY", **params) assert isinstance(validator.get_response("test_token"), RecaptchaResponse) @pytest.mark.parametrize( ("validator_class", "params"), [ (ReCaptchaV2Validator, {}), (ReCaptchaV3Validator, {"action": "test_action", "required_score": 0.4}), ], ) def test_recaptcha_validator_get_response_fail(validator_class, params): validator = validator_class(secret_key="TEST_SECRET_KEY", **params) assert isinstance(validator.get_response("test_token"), RecaptchaResponse) @pytest.mark.parametrize( ("validator_class", "params", "response"), [ (ReCaptchaV2Validator, {}, RecaptchaResponse(is_valid=True)), ( ReCaptchaV3Validator, {"action": "test_action", "required_score": 0.4}, RecaptchaResponse( is_valid=True, extra_data={"score": 0.6, "action": "test_action"} ), ), ], ) def test_recaptcha_validator_call_success(validator_class, params, response): validator = validator_class(secret_key="TEST_SECRET_KEY", **params) validator.get_response = mock.Mock(return_value=response) try: validator("test_token") except ValidationError: pytest.fail("Validation is not passed") @pytest.mark.parametrize( ("validator_class", "params", "response", "error"), [ ( ReCaptchaV2Validator, {}, RecaptchaResponse(is_valid=False), "[ErrorDetail(string='Error verifying reCAPTCHA, please try again.', code='captcha_invalid')]", ), ( ReCaptchaV2Validator, {}, RecaptchaResponse( is_valid=True, extra_data={"score": 0.6, "action": "test_action"} ), "[ErrorDetail(string='Error verifying reCAPTCHA, please try again.', code='captcha_error')]", ), ( ReCaptchaV3Validator, {"action": "test_action", "required_score": 0.4}, RecaptchaResponse(is_valid=False), "[ErrorDetail(string='Error verifying reCAPTCHA, please try again.', code='captcha_invalid')]", ), ( ReCaptchaV3Validator, {"action": "test_action", "required_score": 0.4}, RecaptchaResponse(is_valid=True), "[ErrorDetail(string='Error verifying reCAPTCHA, please try again.', code='captcha_error')]", ), ( ReCaptchaV3Validator, {"action": "test_action", "required_score": 0.4}, RecaptchaResponse(is_valid=True, extra_data={"score": 0.3}), "[ErrorDetail(string='Error verifying reCAPTCHA, please try again.', code='captcha_invalid')]", ), ( ReCaptchaV3Validator, {"action": "test_action", "required_score": 0.4}, RecaptchaResponse(is_valid=True, extra_data={"score": 0.5}), "[ErrorDetail(string='Error verifying reCAPTCHA, please try again.', code='captcha_invalid')]", ), ( ReCaptchaV3Validator, {"action": "test_action", "required_score": 0.4}, RecaptchaResponse( is_valid=True, extra_data={"score": 0.5, "action": "other_action"} ), "[ErrorDetail(string='Error verifying reCAPTCHA, please try again.', code='captcha_invalid')]", ), ], ) def test_recaptcha_validator_call_fail(validator_class, params, response, error): validator = validator_class(secret_key="TEST_SECRET_KEY", **params) validator.get_response = mock.Mock(return_value=response) with pytest.raises(ValidationError) as exc_info: validator("test_token") assert str(exc_info.value) == error @pytest.mark.parametrize( ("validator_class", "params"), [ (ReCaptchaV2Validator, {}), (ReCaptchaV3Validator, {"action": "test_action", "required_score": 0.4}), ], ) def test_recaptcha_validator_set_context(validator_class, params, settings): settings.DRF_RECAPTCHA_TESTING = True validator = validator_class(secret_key="TEST_SECRET_KEY", **params) assert validator.recaptcha_client_ip == "" serializer_field = mock.Mock( context={"request": mock.Mock(META={"HTTP_X_FORWARDED_FOR": "4.3.2.1"})} ) validator("test_token", serializer_field) assert validator.recaptcha_client_ip == "4.3.2.1"

35.717391

107

0.640495

480

4,929

6.325

0.177083

0.06917

0.057971

0.106719

0.797431

0.724308

0.705534

0

0.013914

0.227227

4,929

137

108

35.978102

0.783145

0

0.601695

0

0.26618

0.070197

0

0.042373

1

0.042373

false

0.008475

0.042373

0

0.084746

0

null

0

1

0

null

0

5

6f1931d551e3c84db6b4ec3803ff0fdadaf3d25a

6,123

py

Python

schedule.py

IkhwanFikri1997/Exam-Schedule-Generation

33b8a7faf714cd05552faa5b8ed2a3717eafbb72

[ "MIT" ]

null

schedule.py

IkhwanFikri1997/Exam-Schedule-Generation

33b8a7faf714cd05552faa5b8ed2a3717eafbb72

[ "MIT" ]

null

schedule.py

IkhwanFikri1997/Exam-Schedule-Generation

33b8a7faf714cd05552faa5b8ed2a3717eafbb72

[ "MIT" ]

null

import xlsxwriter import display import string isfilled = {} color = ['black', 'blue', 'brown', 'cyan', 'green', 'lime', 'magenta', 'navy', 'orange', 'pink', 'purple', 'silver', 'white', 'yellow'] workbook = xlsxwriter.Workbook('Exam_Revision_Schedule.xlsx') worksheet = workbook.add_worksheet() Bold = workbook.add_format({'bold': True}) worksheet.write('B1','Monday', Bold) worksheet.write('C1','Tuesday', Bold) worksheet.write('D1','Wednesday', Bold) worksheet.write('E1','Thursday', Bold) worksheet.write('F1','Friday', Bold) worksheet.write('G1','Saturday', Bold) worksheet.write('H1','Sunday', Bold) colList = ['B','C','D','E','F','G','H'] shleep_format = workbook.add_format({'bg_color':'#808080','border_color':'#000080'}) school_format = workbook.add_format({'bg_color':'#FF0000','border_color':'#008000'}) lesson_format = [] n = 0 lesson_format.append(workbook.add_format({'bg_color':color[n],'border_color':'#008000'})) def MakeHourlySchedule(slst,slnd,mnst,mnnd,tdst,tdnd,wdst,wdnd,thst,thnd,frst,frnd,stst,stnd,lesson): for i in range (8): for j in range(26): isfilled[string.ascii_uppercase[i]+str(j)] = False for x in range(24): worksheet.write(('A' + str(x + 2)),str(x)+':00') isfilled['A'+ str(x+1)] = True for h in range(0,7): if slst > slnd: for l in range(0, slnd): worksheet.write((colList[h] + str(l + 2)),'',shleep_format) isfilled[colList[h] + str(l+1)] = True for i in range(slst, 24): worksheet.write((colList[h] + str(i + 2)),'',shleep_format) isfilled[colList[h] + str(i+1)] = True if slst < slnd: for l in range(slst, slnd): worksheet.write((colList[h] + str(l + 2)),'',shleep_format) isfilled[colList[h] + str(l+1)] = True for a in range(mnst, mnnd): worksheet.write(('B' + str(a + 2)),'',school_format) isfilled['B' + str(a+1)] = True for b in range(tdst, tdnd): worksheet.write(('C' + str(b + 2)),'',school_format) isfilled['C' + str(b+1)] = True for c in range(wdst, wdnd): worksheet.write(('D' + str(c + 2)),'',school_format) isfilled['D' + str(c+1)] = True for d in range(thst, thnd): worksheet.write(('E' + str(d + 2)),'',school_format) isfilled['E' + str(d+1)] = True for e in range(frst, frnd): worksheet.write(('F' + str(e + 2)),'',school_format) isfilled['F' + str(e+1)] = True for f in range(stst, stnd): worksheet.write(('G' + str(f + 2)),'',school_format) isfilled['G' + str(f+1)] = True for k in range (0,len(lesson)): for m in range (1, (lesson[k]+1)): lessondone = False for i in range(7,1,-1): for j in range(24,1,-1): if (lessondone == False and isfilled[string.ascii_uppercase[i]+str(j)] == False): print(m) worksheet.write((string.ascii_uppercase[i]+str(j+1)),'',lesson_format[k]) isfilled[string.ascii_uppercase[i]+str(j)] = True lessondone = True n = k+1 lesson_format.append(workbook.add_format({'bg_color':color[n],'border_color':'#008000'})) print(color[n]) workbook.close() def MakeDetailedSchedule(slst,slnd,mnst,mnnd,tdst,tdnd,wdst,wdnd,thst,thnd,frst,frnd,stst,stnd,lesson): for i in range (8): for j in range(50): isfilled[string.ascii_uppercase[i]+str(j)] = False for x in range(48): if x % 2 == 0: worksheet.write(('A' + str(x + 2)),str(x//2)+':00') isfilled['A'+ str(x+1)] = True elif x % 2 == 1: worksheet.write(('A' + str(x + 2)),str((x-1)//2)+':30') isfilled['A'+ str(x+1)] = True for h in range(0,7): if slst > slnd: for l in range(0, slnd*2): worksheet.write((colList[h] + str(l + 2)),'',shleep_format) isfilled[colList[h] + str(l+1)] = True for i in range(slst*2, 48): worksheet.write((colList[h] + str(i + 2)),'',shleep_format) isfilled[colList[h] + str(i+1)] = True if slst < slnd: for l in range(slst*2, slnd*2): worksheet.write((colList[h] + str(l + 2)),'',shleep_format) isfilled[colList[h] + str(l+1)] = True for a in range(mnst*2, mnnd*2): worksheet.write(('B' + str(a + 2)),'',school_format) isfilled['B' + str(a+1)] = True for b in range(tdst*2, tdnd*2): worksheet.write(('C' + str(b + 2)),'',school_format) isfilled['C' + str(b+1)] = True for c in range(wdst*2, wdnd*2): worksheet.write(('D' + str(c + 2)),'',school_format) isfilled['D' + str(c+1)] = True for d in range(thst*2, thnd*2): worksheet.write(('E' + str(d + 2)),'',school_format) isfilled['E' + str(d+1)] = True for e in range(frst*2, frnd*2): worksheet.write(('F' + str(e + 2)),'',school_format) isfilled['F' + str(e+1)] = True for f in range(stst*2, stnd*2): worksheet.write(('G' + str(f + 2)),'',school_format) isfilled['G' + str(f+1)] = True for k in range (0,len(lesson)): for m in range (1, (lesson[k]+1)*2): lessondone = False for i in range(7,1,-1): for j in range(48,1,-1): if (lessondone == False and isfilled[string.ascii_uppercase[i]+str(j)] == False): print(m) worksheet.write((string.ascii_uppercase[i]+str(j+1)),'',lesson_format[k]) isfilled[string.ascii_uppercase[i]+str(j)] = True lessondone = True n = k+1 lesson_format.append(workbook.add_format({'bg_color':color[n],'border_color':'#008000'})) print(color[n]) workbook.close()

41.938356

136

0.529642

846

6,123

3.770686

0.13357

0.074608

0.045141

0.078997

0.796552

0.777743

0.770846

0.748276

0

0.037572

0.287114

6,123

146

137

41.938356

0.693242

0

0.582677

0

0.060378

0.004516

0

1

0.015748

false

0

0.023622

0

0.03937

0.031496

0

null

0

1

0

null

0

5

6f6c6527f36e7fb0f0afdf47372f4b5a5a7899ea

21

py

Python

christian.py

evydibble/EngineeringDesign

44838c6bf807efeea6c791bd13737218b9b81b7f

[ "MIT" ]

null

christian.py

evydibble/EngineeringDesign

44838c6bf807efeea6c791bd13737218b9b81b7f

[ "MIT" ]

null

christian.py

evydibble/EngineeringDesign

44838c6bf807efeea6c791bd13737218b9b81b7f

[ "MIT" ]

7

2018-12-19T01:35:44.000Z

2019-01-10T13:59:40.000Z

print ("helloworld")

21

0.714286

3

21

5.333333

1

0

0.047619

21

1

21

0.75

0

0.47619

0

null

0

null

1

0

null

0

1

0

null

0

1

0

1

0

5

48a5f97c7400fcb0479970d3e626f5c5de4ce64f

3,682

py

Python

task.py

technetbytes/Nested-Object-Serialization

86dc7812c2002010247af9f4edabaf29c78c3be9

[ "MIT" ]

null

task.py

technetbytes/Nested-Object-Serialization

86dc7812c2002010247af9f4edabaf29c78c3be9

[ "MIT" ]

null

task.py

technetbytes/Nested-Object-Serialization

86dc7812c2002010247af9f4edabaf29c78c3be9

[ "MIT" ]

null

import json from converter import datetime_converter from status import Status class Task: def __init__(self, task_name, task_id, message, conditions): self.task_name = task_name self.task_id = task_id self.conditions = conditions self.message = message def __iter__(self): yield from { "task_name": self.task_name, "task_id": self.task_id, "conditions": self.conditions, "message": self.message }.items() def __str__(self): return json.dumps(self.to_json(), ensure_ascii=False, default = datetime_converter) def __repr__(self): return self.__str__() def toJSON(self): return json.dumps(self, default=lambda o: o.__dict__, sort_keys=True, indent=4) def to_json(self): to_return = {"task_name": self.task_name, "task_id": self.task_id, "message": self.message, "conditions":self.conditions} statuses = [] for status in self.conditions: print("checking status type ->",type(status)) # print(" to_json status type", ) if isinstance(status, dict): from collections import namedtuple x = namedtuple("ObjectName", status.keys())(*status.values()) conditions = [] print("printing x data",x) s = Status(x.id, x.status_name, x.status_datetime, x.message) statuses.append(s.to_json()) if isinstance(status,Status): #x = namedtuple("ObjectName", status.keys())(*status.values()) #s = Status(status.id, status.status_name, status.status_datetime, status.message) statuses.append(status.to_json()) # # statuses = [] # # for status in self.conditions: # # statuses.append(status.__dict__) # #statuses = {} # #for key, status in self.conditions.items(): # # single_status = [] # # for status_set in status: # # single_status.append(status_set.__dict__) # # statuses[key] = single_status to_return["conditions"] = statuses return to_return # import json # from task_store.converter import datetime_converter # class Task: # def __init__(self, task_name, task_id, message, conditions): # self.task_name = task_name # self.task_id = task_id # self.conditions = conditions # self.message = message # def __iter__(self): # yield from { # "task_name": self.task_name, # "task_id": self.task_id, # "conditions": self.conditions, # "message": self.message # }.items() # def __str__(self): # return json.dumps(self.to_json(), ensure_ascii=False, default = datetime_converter) # def __repr__(self): # return self.__str__() # def toJSON(self): # return json.dumps(self, default=lambda o: o.__dict__, # sort_keys=True, indent=4) # def to_json(self): # to_return = {"task_name": self.task_name, "task_id": self.task_id, "message": self.message} # statuses = [] # for status in self.conditions: # statuses.append(status.__dict__) # #statuses = {} # #for key, status in self.conditions.items(): # # single_status = [] # # for status_set in status: # # single_status.append(status_set.__dict__) # # statuses[key] = single_status # to_return["conditions"] = statuses # return to_return

35.403846

129

0.572787

402

3,682

4.927861

0.141791

0.056537

0.04846

0.064614

0.766784

0.750126

0.706714

0

0.000789

0.311787

3,682

104

130

35.403846

0.780979

0.492395

0

0.068622

0

1

0.153846

false

0

0.102564

0.076923

0.384615

0.051282

0

null

0

1

0

null

0

5

48acb9b399d09e2e4fb3dde5930cb61b03c38394

109

py

Python

medseg/models/segmentation_models/__init__.py

cherise215/Cooperative_Training_and_Latent_Space_Data_Augmentation

f5a987fb4babb891a41116e934a9ce6432e0d803

[ "Apache-2.0" ]

18

2021-06-20T11:38:08.000Z

2022-01-04T11:53:10.000Z

medseg/models/segmentation_models/__init__.py

cherise215/Cooperative_Training_and_Latent_Space_Data_Augmentation

f5a987fb4babb891a41116e934a9ce6432e0d803

[ "Apache-2.0" ]

1

2021-10-04T07:12:27.000Z

2021-12-06T20:54:46.000Z

medseg/models/segmentation_models/__init__.py

cherise215/Cooperative_Training_and_Latent_Space_Data_Augmentation

f5a987fb4babb891a41116e934a9ce6432e0d803

[ "Apache-2.0" ]

2

2021-09-30T18:25:48.000Z

2022-03-14T17:16:41.000Z

# Created by cc215 at 05/05/19 # Enter feature description here # Enter scenario name here # Enter steps here

27.25

32

0.770642

18

109

4.666667

0.722222

0.214286

0

0.1

0.174312

109

4

33

27.25

0.833333

0.926606

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

1

0

1

0

1

0

null

0

1

0

5

d2905b005d20a53cba6ef5eba12d791aa88cd1f6

41

py

Python

kivymd/effects/fadingedge/__init__.py

vhn0912/KivyMD

2f6f2b78a3c1f9ff15d18ede24fd034a8db5371d

[ "MIT" ]

668

2018-08-31T12:38:18.000Z

2020-07-31T21:29:10.000Z

kivymd/effects/fadingedge/__init__.py

vhn0912/KivyMD

2f6f2b78a3c1f9ff15d18ede24fd034a8db5371d

[ "MIT" ]

377

2018-10-23T15:46:29.000Z

2020-08-01T14:03:36.000Z

kivymd/effects/fadingedge/__init__.py

vhn0912/KivyMD

2f6f2b78a3c1f9ff15d18ede24fd034a8db5371d

[ "MIT" ]

275

2018-09-04T19:27:51.000Z

2020-07-31T01:14:48.000Z

from .fadingedge import FadingEdgeEffect

20.5

40

0.878049

4

41

9

1

0

0.097561

41

1

41

0.972973

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

d2b472f9e9a27f7e72edeb5c7d63b20a18ad95d6

43

py

Python

python/src/log/token_exception.py

laxian/shell

4de76b413e806d52571f1a6900fdf00e70f4f1a5

[ "Apache-2.0" ]

6

2018-01-13T17:29:25.000Z

2022-03-13T15:33:52.000Z

python/src/log/token_exception.py

laxian/shell

4de76b413e806d52571f1a6900fdf00e70f4f1a5

[ "Apache-2.0" ]

null

python/src/log/token_exception.py

laxian/shell

4de76b413e806d52571f1a6900fdf00e70f4f1a5

[ "Apache-2.0" ]

3

2018-06-03T10:28:42.000Z

2021-08-09T13:32:55.000Z

class TokenException(Exception): pass

10.75

32

0.744186

4

43

8

1

0

0.186047

43

4

33

10.75

0.914286

0

1

0

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

5

d2c8c4e60374844fb4ca8bc854f31a975955baec

20

py

Python

baler/__init__.py

isabella232/baler

db4f09dd2c7729b2df5268c87ad3b4cb43396abf

[ "MIT" ]

18

2015-01-14T00:19:50.000Z

2021-10-21T22:48:08.000Z

baler/__init__.py

paypal/baler

db4f09dd2c7729b2df5268c87ad3b4cb43396abf

[ "MIT" ]

1

2021-02-23T10:25:10.000Z

baler/__init__.py

isabella232/baler

db4f09dd2c7729b2df5268c87ad3b4cb43396abf

[ "MIT" ]

9

2015-01-12T16:54:56.000Z

2021-06-10T15:14:20.000Z

from baler import *

10

19

0.75

3

20

5

1

0

0.2

20

1

20

0.9375

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

8273805bd559ff19996f467fc461c865f970b301

332

py

Python

test cases/unit/91 devenv/test-devenv.py

andriyor/meson

f9bfeb2add70973113ab4a98454a5c5d7e3a26ae

[ "Apache-2.0" ]

null

test cases/unit/91 devenv/test-devenv.py

andriyor/meson

f9bfeb2add70973113ab4a98454a5c5d7e3a26ae

[ "Apache-2.0" ]

null

test cases/unit/91 devenv/test-devenv.py

andriyor/meson

f9bfeb2add70973113ab4a98454a5c5d7e3a26ae

[ "Apache-2.0" ]

null

#! /usr/bin/python import os from pathlib import Path assert os.environ['MESON_DEVENV'] == '1' assert os.environ['MESON_PROJECT_NAME'] == 'devenv' assert os.environ['TEST_A'] == '1' assert os.environ['TEST_B'] == '0+1+2+3+4' from mymod.mod import hello assert hello == 'world' from mymod2.mod2 import hello assert hello() == 42

20.75

51

0.701807

54

332

4.222222

0.537037

0.140351

0.263158

0.175439

0

0.038194

0.13253

332

15

52

22.133333

0.753472

0.051205

0

0.203822

0

0.6

1

0

true

0

0.4

0

0.4

0

null

0

1

0

null

0

1

0

1

0

1

0

5

82945189fe4f47d7eceb6f8a549dad11b567833d

41

py

Python

models/__init__.py

killf/remove_glasses

e73eec238686fa539cff66905a086fb26329b253

[ "MIT" ]

null

models/__init__.py

killf/remove_glasses

e73eec238686fa539cff66905a086fb26329b253

[ "MIT" ]

null

models/__init__.py

killf/remove_glasses

e73eec238686fa539cff66905a086fb26329b253

[ "MIT" ]

null

from .networks import define_D, define_G

20.5

40

0.829268

7

41

4.571429

0.857143

0

0.121951

41

1

41

0.888889

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

82a228099e127f10947f580b359e0f7a3160f962

262

py

Python

dlocal/utils/dates.py

GoPreki/DlocalSDK

6c3f001454fcd6c8f1b5bec6b042777f5ab99b7d

[ "MIT" ]

null

dlocal/utils/dates.py

GoPreki/DlocalSDK

6c3f001454fcd6c8f1b5bec6b042777f5ab99b7d

[ "MIT" ]

null

dlocal/utils/dates.py

GoPreki/DlocalSDK

6c3f001454fcd6c8f1b5bec6b042777f5ab99b7d

[ "MIT" ]

null

from datetime import datetime def now_in_isoformat(): return datetime.utcnow().isoformat()[:-3] + 'Z' def isoformat_to_timestamp(isoformat_date, date_format='%Y-%m-%dT%H:%M:%S.%f%z'): return datetime.strptime(isoformat_date, date_format).timestamp()

26.2

81

0.729008

38

262

4.815789

0.578947

0.153005

0.185792

0.251366

0

0.004274

0.10687

262

9

82

29.111111

0.777778

0

0.087786

0.083969

0

1

0.4

false

0

0.2

0.4

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

82cb71a8ca4209fb10e248bc9376b17de3152b7e

6,176

py

Python

chapter05_CNN/5.6_alexnet.py

JessyLee/Jessy_Dive_into_DL_Pytorch

40b7921637b13507057f41485d928f3b59cc6f6a

[ "MIT" ]

null

chapter05_CNN/5.6_alexnet.py

JessyLee/Jessy_Dive_into_DL_Pytorch

40b7921637b13507057f41485d928f3b59cc6f6a

[ "MIT" ]

null

chapter05_CNN/5.6_alexnet.py

JessyLee/Jessy_Dive_into_DL_Pytorch

40b7921637b13507057f41485d928f3b59cc6f6a

[ "MIT" ]

null

# import time # import torch # from torch import nn, optim # import torchvision # # import sys # sys.path.append("..") # import d2lzh_pytorch as d2l # device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') # # print(torch.__version__) # print(torchvision.__version__) # print(device) # # class AlexNet(nn.Module): # def __init__(self): # super(AlexNet, self).__init__() # self.conv = nn.Sequential( # nn.Conv2d(1, 96, 11, 4), # nn.ReLU(), # nn.MaxPool2d(3, 2), # # nn.Conv2d(96, 256, 5, 1, 2), # nn.ReLU(), # nn.MaxPool2d(3, 2), # # nn.Conv2d(256, 384, 3, 1, 1), # nn.ReLU(), # # nn.Conv2d(384, 384, 3, 1, 1), # nn.ReLU(), # # nn.Conv2d(384, 256, 3, 1, 1), # nn.ReLU(), # nn.MaxPool2d(3, 2)) # # self.fc = nn.Sequential( # nn.Linear(256*5*5, 4096), # nn.ReLU(), # nn.Dropout(0.5), # # nn.Linear(4096, 4096), # nn.ReLU(), # nn.Dropout(0.5), # # nn.Linear(4096, 10)) # # def forward(self, img): # feature = self.conv(img) # output = self.fc(feature.view(img.shape[0], -1)) # return output # # def load_data_fashion_mnist(batch_size, resize=None, # root='~/Datasets/FashionMNIST'): # trans = [] # if resize: # trans.append(torchvision.transforms.Resize( # size=resize)) # trans.append(torchvision.transforms.ToTensor) # # transform = torchvision.transforms.Compose(trans) # mnist_train = torchvision.datasets.FashionMNIST( # root=root, train=True, download=True, transform=transform) # mnist_test = torchvision.datasets.FashionMNIST( # root=root, train=False, download=True, transform=transform) # torch.util # train_iter = torch.utils.data.DataLoader( # mnist_train, batch_size=batch_size, shuffle=True, num_workers=1) # test_iter = torch.utils.data.DataLoader( # mnist_test, batch_size=batch_size, shuffle=True, num_workers=1) # # return train_iter, test_iter # # # # net = AlexNet() # batch_size = 128 # train_iter, test_iter = load_data_fashion_mnist(batch_size=batch_size, resize=224) # # lr, num_epochs = 0.001, 5 # optimizer = torch.optim.Adam(net.parameters(), lr=lr) # d2l.train_ch5(net, train_iter, test_iter, batch_size, optimizer, device, num_epochs) import time import torch from torch import nn, optim import torchvision import sys sys.path.append("..") device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') print(torch.__version__) print(torchvision.__version__) print(device) class AlexNet(nn.Module): def __init__(self): super(AlexNet, self).__init__() self.conv = nn.Sequential( nn.Conv2d(1, 96, 11, 4), # in_channels, out_channels, kernel_size, stride, padding nn.ReLU(), nn.MaxPool2d(3, 2), # kernel_size, stride # 减小卷积窗口，使用填充为2来使得输入与输出的高和宽一致，且增大输出通道数 nn.Conv2d(96, 256, 5, 1, 2), nn.ReLU(), nn.MaxPool2d(3, 2), # 连续3个卷积层，且使用更小的卷积窗口。除了最后的卷积层外，进一步增大了输出通道数。 # 前两个卷积层后不使用池化层来减小输入的高和宽 nn.Conv2d(256, 384, 3, 1, 1), nn.ReLU(), nn.Conv2d(384, 384, 3, 1, 1), nn.ReLU(), nn.Conv2d(384, 256, 3, 1, 1), nn.ReLU(), nn.MaxPool2d(3, 2) ) # 这里全连接层的输出个数比LeNet中的大数倍。使用丢弃层来缓解过拟合 self.fc = nn.Sequential( nn.Linear(256*5*5, 4096), nn.ReLU(), nn.Dropout(0.5), nn.Linear(4096, 4096), nn.ReLU(), nn.Dropout(0.5), # 输出层。由于这里使用Fashion-MNIST，所以用类别数为10，而非论文中的1000 nn.Linear(4096, 10), ) def forward(self, img): feature = self.conv(img) output = self.fc(feature.view(img.shape[0], -1)) return output # 本函数已保存在d2lzh_pytorch包中方便以后使用 def load_data_fashion_mnist(batch_size, resize=None, root='~/Datasets/FashionMNIST'): """Download the fashion mnist dataset and then load into memory.""" trans = [] if resize: trans.append(torchvision.transforms.Resize(size=resize)) trans.append(torchvision.transforms.ToTensor()) transform = torchvision.transforms.Compose(trans) mnist_train = torchvision.datasets.FashionMNIST(root=root, train=True, download=True, transform=transform) mnist_test = torchvision.datasets.FashionMNIST(root=root, train=False, download=True, transform=transform) train_iter = torch.utils.data.DataLoader(mnist_train, batch_size=batch_size, shuffle=True, num_workers=4) test_iter = torch.utils.data.DataLoader(mnist_test, batch_size=batch_size, shuffle=False, num_workers=4) return train_iter, test_iter def train_ch5(net, train_iter, test_iter, batch_size, optimizer, device, num_epochs): net = net.to(device) print("training on ", device) loss = torch.nn.CrossEntropyLoss() batch_count = 0 for epoch in range(num_epochs): train_l_sum, train_acc_sum, n, start = 0.0, 0.0, 0, time.time() for X, y in train_iter: X = X.to(device) y = y.to(device) y_hat = net(X) l = loss(y_hat, y) optimizer.zero_grad() l.backward() optimizer.step() train_l_sum += l.cpu().item() train_acc_sum += (y_hat.argmax(dim=1) == y).sum().cpu().item() n += y.shape[0] batch_count += 1 test_acc = evaluate_accuracy(test_iter, net) print('epoch %d, loss %.4f, train acc %.3f, test acc %.3f, time %.1f sec' % (epoch + 1, train_l_sum / batch_count, train_acc_sum / n, test_acc, time.time() - start)) net = AlexNet() print(net) batch_size = 128 # 如出现“out of memory”的报错信息，可减小batch_size或resize train_iter, test_iter = load_data_fashion_mnist(batch_size, resize=224) lr, num_epochs = 0.001, 5 optimizer = torch.optim.Adam(net.parameters(), lr=lr) train_ch5(net, train_iter, test_iter, batch_size, optimizer, device, num_epochs)

32.505263

110

0.603627

791

6,176

4.543616

0.201011

0.045075

0.031163

0.033111

0.753478

0.740679

0.735392

0.730106

0.725654

0

0.048743

0.259229

6,176

190

111

32.505263

0.736831

0.440576

0

0.135802

0

0.012346

0.03244

0.006845

0

1

0.049383

false

0

0.061728

0

0.148148

0.074074

0

null

0

1

0

null

0

5

82ceb2ebc1a8bc1ef05e2d65e7880f7791ff9d53

115

py

Python

reverseCoding/is-42-the-answer-of-everything/gen.py

anirudhkannanvp/HACKERRANK-REVERSE-CODING-

1d454d7d403ab68a667c34dba9158ebb72bdda4c

[ "MIT" ]

1

2018-09-21T16:13:27.000Z

reverseCoding/is-42-the-answer-of-everything/gen.py

anirudhkannanvp/HACKERRANK-REVERSE-CODING-

1d454d7d403ab68a667c34dba9158ebb72bdda4c

[ "MIT" ]

null

reverseCoding/is-42-the-answer-of-everything/gen.py

anirudhkannanvp/HACKERRANK-REVERSE-CODING-

1d454d7d403ab68a667c34dba9158ebb72bdda4c

[ "MIT" ]

null

from random import randint t=randint(1,10000) print(t) while(t): t-=1 print(randint(1,100000),randint(1,100000))

19.166667

43

0.730435

21

115

4

0.47619

0.285714

0.333333

0

0.201923

0.095652

115

6

43

19.166667

0.605769

0

1

0

false

0

0.166667

0

0.166667

0.333333

1

0

null

1

0

1

0

1

0

null

0

5

82de53e37b6f9654ff9708e3b237cdfbad2bc9dd

122

py

Python

src/blip_sdk/extensions/chat/__init__.py

mirlarof/blip-sdk-python

f958149b2524d4340eeafad8739a33db71df45ed

[ "MIT" ]

2

2021-07-02T20:10:48.000Z

2021-07-13T20:51:18.000Z

src/blip_sdk/extensions/chat/__init__.py

mirlarof/blip-sdk-python

f958149b2524d4340eeafad8739a33db71df45ed

[ "MIT" ]

9

2021-05-27T21:08:23.000Z

2021-06-14T20:10:10.000Z

src/blip_sdk/extensions/chat/__init__.py

mirlarof/blip-sdk-python

f958149b2524d4340eeafad8739a33db71df45ed

[ "MIT" ]

3

2021-06-23T19:53:20.000Z

2022-01-04T17:50:44.000Z

from .content_types import ContentTypes from .uri_templates import UriTemplates from .chat_extension import ChatExtension

30.5

41

0.877049

15

122

6.933333

0.733333

0

0.098361

122

3

42

40.666667

0.945455

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

7d75729b46d86c9b3db59c5f1c54cc9ff0f4c444

119

py

Python

main.py

CrutoiAlexandru/Job_scrapper

d170188b71ca04d3515bbcbec109168c5edb951c

[ "MIT" ]

null

main.py

CrutoiAlexandru/Job_scrapper

d170188b71ca04d3515bbcbec109168c5edb951c

[ "MIT" ]

null

main.py

CrutoiAlexandru/Job_scrapper

d170188b71ca04d3515bbcbec109168c5edb951c

[ "MIT" ]

null

import user.input as ui if __name__ == '__main__': # start the user input on the terminal based app ui.start()

23.8

52

0.689076

19

119

3.894737

0.736842

0.243243

0

0.226891

119

5

53

23.8

0.804348

0.386555

0

0.111111

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

7d897bc5f402b4abc2ce30552a2e6f587cb52e42

16

py

Python

Week 1/assignment/assignment1.py

rasulbi528/Python-web-data-acess

2cd1c3d3772a7f9630c837bd7bcb31598c13d10c

[ "MIT" ]

1

2016-12-26T13:07:09.000Z

Week 1/assignment/assignment1.py

rasulbi528/Python-web-data-acess

2cd1c3d3772a7f9630c837bd7bcb31598c13d10c

[ "MIT" ]

null

Week 1/assignment/assignment1.py

rasulbi528/Python-web-data-acess

2cd1c3d3772a7f9630c837bd7bcb31598c13d10c

[ "MIT" ]

null

print "Hi!! :)"

8

15

0.4375

2

16

3.5

1

0

0.1875

16

1

16

0.538462

0

0.4375

0

null

0

null

1

0

null

0

1

0

null

0

1

0

1

0

5

7ddd3e58986132ebb9020f296e5a5d3e856e0754

513

py

Python

calculator/src/lexer_test.py

cestella/software_engineering_curriculum

5f4ac0f2ffe868abdea3c1baf29b66c091345a02

[ "Apache-2.0" ]

1

2020-08-19T19:43:45.000Z

calculator/src/lexer_test.py

cestella/software_engineering_curriculum

5f4ac0f2ffe868abdea3c1baf29b66c091345a02

[ "Apache-2.0" ]

3

2020-07-24T12:36:59.000Z

2021-05-28T18:01:36.000Z

calculator/src/lexer_test.py

cestella/software_engineering_curriculum

5f4ac0f2ffe868abdea3c1baf29b66c091345a02

[ "Apache-2.0" ]

1

2020-05-31T14:54:18.000Z

from src.lexer import lex def test_basecase(): assert lex("1 + 1") == [1, "+", 1] def test_negative_weirdness(): assert lex("1 - -1") == [1, "-", -1] def test_no_space(): assert lex("-1.2*2") == [-1.2, "*", 2] def test_multiple_spaces(): assert lex("1 + 1") == [1, "+", 1] def test_parens(): assert lex("(2 + 3) - 3.2") == ["(", 2, "+", 3, ")", "-", 3.2] def test_RPN(): assert lex("1 1 +") == [1, 1, "+"] def test_RPN_with_spaces(): assert lex("1 1 +") == [1, 1, "+"]

17.1

66

0.481481

79

513

2.974684

0.265823

0.12766

0.234043

0.446809

0.340426

0

0.086957

0.237817

513

29

67

17.689655

0.514067

0

0.266667

0

0.111111

0

0.466667

1

0.466667

true

0

0.066667

0

0.533333

0

null

0

1

0

null

0

1

0

1

0

1

0

5

8149d6d5371e10ee5d8956061019f0b7810c1ae5

130

py

Python

calculatorapp/admin.py

arpit456jain/CalculatorApp-In-Django

aa976117952db03128e4fe6d6d0dbf375ab29b5d

[ "MIT" ]

null

calculatorapp/admin.py

arpit456jain/CalculatorApp-In-Django

aa976117952db03128e4fe6d6d0dbf375ab29b5d

[ "MIT" ]

null

calculatorapp/admin.py

arpit456jain/CalculatorApp-In-Django

aa976117952db03128e4fe6d6d0dbf375ab29b5d

[ "MIT" ]

null

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

21.666667

33

0.823077

17

130

6.294118

0.647059

0

0.115385

130

6

33

21.666667

0.930435

0.2

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

816b0c81fba1986ec985dd3cb56e5f9b5969bc22

444

py

Python

command.py

ichiyonnana/nnutil

bb6ae2fe47da47f15fa256aa85602e7c3beb1f80

[ "MIT" ]

1

2021-08-08T22:18:04.000Z

nnutil/command.py

ichiyonnana/nntools_maya

6a0aa39194cac00aac35e9eca6fcf2b12a70f373

[ "MIT" ]

null

nnutil/command.py

ichiyonnana/nntools_maya

6a0aa39194cac00aac35e9eca6fcf2b12a70f373

[ "MIT" ]

null

#! python # coding:utf-8 import maya.cmds as cmds import maya.mel as mel import pymel.core as pm def get_selection(**kwargs): """ [cmds] Returns: [type]: [description] """ return cmds.ls(selection=True, flatten=True, **kwargs) def selected(**kwargs): """ [pm] flatten を有効にした pm.selected() Returns: [type]: [description] """ return pm.selected(flatten=True, **kwargs)

18.5

59

0.585586

52

444

4.980769

0.480769

0.07722

0.169884

0.216216

0

0.003077

0.268018

444

24

60

18.5

0.793846

0.301802

0

1

0.285714

true

0

0.428571

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

81e3c8e32867953c69e71802ef9948b2886604a1

120

py

Python

uci_cbp_demo/ui/__init__.py

taoyilee/bp_demo

eaaba09857a8a597f3691b6b79902b71e4af1ffe

[ "SWL" ]

1

2020-02-20T21:39:28.000Z

uci_cbp_demo/ui/__init__.py

taoyilee/bp_demo

eaaba09857a8a597f3691b6b79902b71e4af1ffe

[ "SWL" ]

19

2020-04-08T00:10:06.000Z

2020-06-21T04:39:48.000Z

uci_cbp_demo/ui/__init__.py

taoyilee/bp_demo

eaaba09857a8a597f3691b6b79902b71e4af1ffe

[ "SWL" ]

null

# MIT License # Copyright (C) Michael Tao-Yi Lee (taoyil AT UCI EDU) from .gui import main from .tui import tui_main

20

55

0.725

21

120

4.095238

0.809524

0

0.2

120

5

56

24

0.895833

0.541667

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

c4b41c63d6c0d9ceb82bae821585ed2753e8c1e0

208

py

Python

src/loralay/data/utils.py

laudao/loralay-modeling

a7c89717bac4f0ef9ed820544c4d27e2fe2e4228

[ "Apache-2.0" ]

null

src/loralay/data/utils.py

laudao/loralay-modeling

a7c89717bac4f0ef9ed820544c4d27e2fe2e4228

[ "Apache-2.0" ]

null

src/loralay/data/utils.py

laudao/loralay-modeling

a7c89717bac4f0ef9ed820544c4d27e2fe2e4228

[ "Apache-2.0" ]

null

def normalize_bbox(bbox, size): return [ int(1000 * bbox[0] / size[0]), int(1000 * bbox[1] / size[1]), int(1000 * bbox[2] / size[0]), int(1000 * bbox[3] / size[1]), ]

23.111111

38

0.475962

30

208

3.266667

0.366667

0.285714

0.44898

0.244898

0.326531

0

0.170213

0.322115

208

8

39

26

0.524823

0

1

0.142857

false

0

0.142857

0.285714

0

null

1

0

1

0

null

0

1

0

5

c4e46ee6de43bd254d0a5f54f2ef8afea92aaaf4

7,372

py

Python

programs/aniso_magic.py

schwehr/PmagPy

5e9edc5dc9a7a243b8e7f237fa156e0cd782076b

[ "BSD-3-Clause" ]

2

2020-07-05T01:11:33.000Z

2020-07-05T01:11:39.000Z

programs/aniso_magic.py

schwehr/PmagPy

5e9edc5dc9a7a243b8e7f237fa156e0cd782076b

[ "BSD-3-Clause" ]

null

programs/aniso_magic.py

schwehr/PmagPy

5e9edc5dc9a7a243b8e7f237fa156e0cd782076b

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # -*- python-indent-offset: 4; -*- #pylint: disable=invalid-name,wrong-import-position,line-too-long #import draw import sys import matplotlib if matplotlib.get_backend() != "TKAgg": matplotlib.use("TKAgg") import pmagpy.pmag as pmag from pmagpy import ipmag import pmagpy.pmagplotlib as pmagplotlib import pmagpy.contribution_builder as cb def old(): """ NAME aniso_magic.py DESCRIPTION plots anisotropy data with either bootstrap or hext ellipses SYNTAX aniso_magic.py [-h] [command line options] OPTIONS -h plots help message and quits -usr USER: set the user name -f AFILE, specify specimens.txt formatted file for input -fsa SAMPFILE, specify samples.txt file (required to plot by site) -fsi SITEFILE, specify site file (required to include location information) -x Hext [1963] and bootstrap -B DON'T do bootstrap, do Hext -par Tauxe [1998] parametric bootstrap -v plot bootstrap eigenvectors instead of ellipses -sit plot by site instead of entire file -crd [s,g,t] coordinate system, default is specimen (g=geographic, t=tilt corrected) -P don't make any plots - just fill in the specimens, samples, sites tables -sav don't make the tables - just save all the plots -fmt [svg, jpg, eps] format for output images, png default -gtc DEC INC dec,inc of pole to great circle [down(up) in green (cyan) -d Vi DEC INC; Vi (1,2,3) to compare to direction DEC INC -n N; specifies the number of bootstraps - default is 1000 DEFAULTS AFILE: specimens.txt plot bootstrap ellipses of Constable & Tauxe [1987] NOTES minor axis: circles major axis: triangles principal axis: squares directions are plotted on the lower hemisphere for bootstrapped eigenvector components: Xs: blue, Ys: red, Zs: black """ args = sys.argv if "-h" in args: print(main.__doc__) sys.exit() verbose = pmagplotlib.verbose dir_path = pmag.get_named_arg("-WD", ".") input_dir_path = pmag.get_named_arg("-ID", "") num_bootstraps = pmag.get_named_arg("-n", 1000) ipar = pmag.get_flag_arg_from_sys("-par", true=1, false=0) ihext = pmag.get_flag_arg_from_sys("-x", true=1, false=0) ivec = pmag.get_flag_arg_from_sys("-v", true=1, false=0) iplot = pmag.get_flag_arg_from_sys("-P", true=0, false=1) isite = pmag.get_flag_arg_from_sys("-sit", true=1, false=0) iboot, vec = 1, 0 infile = pmag.get_named_arg('-f', 'specimens.txt') samp_file = pmag.get_named_arg('-fsa', 'samples.txt') site_file = pmag.get_named_arg('-fsi', 'sites.txt') #outfile = pmag.get_named_arg("-F", "rmag_results.txt") fmt = pmag.get_named_arg("-fmt", "png") crd = pmag.get_named_arg("-crd", "s") comp, Dir, PDir = 0, [], [] user = pmag.get_named_arg("-usr", "") if '-B' in args: iboot, ihext = 0, 1 plots, verbose = 0, True if '-sav' in args: plots = 1 verbose = 0 if '-gtc' in args: ind = args.index('-gtc') d, i = float(args[ind+1]), float(args[ind+2]) PDir.append(d) PDir.append(i) if '-d' in args: comp = 1 ind = args.index('-d') vec = int(args[ind+1])-1 Dir = [float(args[ind+2]), float(args[ind+3])] ipmag.aniso_magic_old(infile=infile, samp_file=samp_file, site_file=site_file, ipar=ipar, ihext=ihext, ivec=ivec, iplot=iplot, isite=isite, iboot=iboot, vec=vec, Dir=Dir, PDir=PDir, comp=comp, user=user, fmt=fmt, crd=crd, verbose=verbose, plots=plots, num_bootstraps=num_bootstraps, dir_path=dir_path, input_dir_path=input_dir_path) def main(): """ NAME aniso_magic.py DESCRIPTION plots anisotropy data with either bootstrap or hext ellipses SYNTAX aniso_magic.py [-h] [command line options] OPTIONS -h plots help message and quits -f AFILE, specify specimens.txt formatted file for input -fsa SAMPFILE, specify samples.txt file (required to plot by site) -fsi SITEFILE, specify site file (required to include location information) -x Hext [1963] and bootstrap -B DON'T do bootstrap, do Hext -par Tauxe [1998] parametric bootstrap -v plot bootstrap eigenvectors instead of ellipses -sit plot by site instead of entire file -crd [s,g,t] coordinate system, default is specimen (g=geographic, t=tilt corrected) -P don't make any plots - just fill in the specimens, samples, sites tables -sav don't make the tables - just save all the plots -fmt [svg, jpg, eps] format for output images, png default -gtc DEC INC dec,inc of pole to great circle [down(up) in green (cyan) -d Vi DEC INC; Vi (1,2,3) to compare to direction DEC INC -n N; specifies the number of bootstraps - default is 1000 DEFAULTS AFILE: specimens.txt plot bootstrap ellipses of Constable & Tauxe [1987] NOTES minor axis: circles major axis: triangles principal axis: squares directions are plotted on the lower hemisphere for bootstrapped eigenvector components: Xs: blue, Ys: red, Zs: black """ args = sys.argv if '-h' in args: print(new.__doc__) return dir_path = pmag.get_named_arg("-WD", ".") if '-ID' in args and dir_path == '.': dir_path = pmag.get_named_arg("-ID", ".") iboot, vec = 1, 0 num_bootstraps = pmag.get_named_arg("-n", 1000) ipar = pmag.get_flag_arg_from_sys("-par", true=1, false=0) ihext = pmag.get_flag_arg_from_sys("-x", true=1, false=0) ivec = pmag.get_flag_arg_from_sys("-v", true=1, false=0) if ivec: vec = 3 #iplot = pmag.get_flag_arg_from_sys("-P", true=0, false=1) isite = pmag.get_flag_arg_from_sys("-sit", true=1, false=0) infile = pmag.get_named_arg('-f', 'specimens.txt') samp_file = pmag.get_named_arg('-fsa', 'samples.txt') site_file = pmag.get_named_arg('-fsi', 'sites.txt') #outfile = pmag.get_named_arg("-F", "rmag_results.txt") fmt = pmag.get_named_arg("-fmt", "png") crd = pmag.get_named_arg("-crd", "s") comp, Dir, PDir = 0, [], [] user = pmag.get_named_arg("-usr", "") if '-B' in args: iboot, ihext = 0, 1 save_plots, verbose, interactive = False, True, True if '-sav' in args: save_plots = True verbose = False interactive = False if '-gtc' in args: ind = args.index('-gtc') d, i = float(args[ind+1]), float(args[ind+2]) PDir.append(d) PDir.append(i) if '-d' in args: comp = 1 ind = args.index('-d') vec = int(args[ind+1])-1 Dir = [float(args[ind+2]), float(args[ind+3])] ipmag.aniso_magic_nb(infile, samp_file, site_file, verbose, ipar, ihext, ivec, isite, False, iboot, vec, Dir, PDir, crd, num_bootstraps, dir_path, save_plots=save_plots, interactive=interactive, fmt=fmt) if __name__ == "__main__": if "-old" in sys.argv: old() else: main()

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1

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null

0

5

1ee644ac8ac8c64862ca2f6c7c456ea0a2a57bf2

47

py

Python

neelu/__init__.py

NeeluGeorge/testpks

4b676a70e88490cdcdf5ed9f6b92a47b28eedc2d

[ "MIT" ]

null

neelu/__init__.py

NeeluGeorge/testpks

4b676a70e88490cdcdf5ed9f6b92a47b28eedc2d

[ "MIT" ]

null

neelu/__init__.py

NeeluGeorge/testpks

4b676a70e88490cdcdf5ed9f6b92a47b28eedc2d

[ "MIT" ]

null

from .neelu import printhi __all__=["printhi"]

15.666667

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0.765957

6

47

5.333333

0.833333

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0.106383

47

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15.666667

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0

null

0

1

0

null

0

1

0

1

0

5

1eefa53d1317567978c4addda55a56119ba40eda

278

py

Python

main_game/creditos.py

AlefAdonis/playgame

3f1049ad3682f169f2435faeeef63b0b1ddf5642

[ "MIT" ]

null

main_game/creditos.py

AlefAdonis/playgame

3f1049ad3682f169f2435faeeef63b0b1ddf5642

[ "MIT" ]

2

2020-09-21T14:32:38.000Z

2020-10-07T17:47:35.000Z

main_game/creditos.py

AlefAdonis/playgame

3f1049ad3682f169f2435faeeef63b0b1ddf5642

[ "MIT" ]

2

2020-10-07T19:53:57.000Z

2020-10-10T21:23:43.000Z

def credits(): print('\nObrigado por jogar !\n') print('-' * 20) print('CRÉDITOS FINAIS \nDiretor Geral - Álef Ádonis\nProgramador - Álef Ádonis\nRoteirista - Álef Ádonis\nEditor Chefe - Álef Ádonis\n\nUM PEQUENO GESTO PARA DEMOSTRAR MEU AMOR') print('-' *20)

39.714286

183

0.683453

36

278

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null

0

1

0

1

0

5

4808ae8e24928d021e6ff8a71a890563131b8265

176

py

Python

bin/cubes/solid-pentominoes-3x3x9-ring.py

tiwo/puzzler

7ad3d9a792f0635f7ec59ffa85fb46b54fd77a7e

[ "Intel" ]

null

bin/cubes/solid-pentominoes-3x3x9-ring.py

tiwo/puzzler

7ad3d9a792f0635f7ec59ffa85fb46b54fd77a7e

[ "Intel" ]

null

bin/cubes/solid-pentominoes-3x3x9-ring.py

tiwo/puzzler

7ad3d9a792f0635f7ec59ffa85fb46b54fd77a7e

[ "Intel" ]

1

2022-01-02T16:54:14.000Z

#!/usr/bin/env python # $Id$ """3 solutions""" import puzzler from puzzler.puzzles.solid_pentominoes import SolidPentominoes3x3x9Ring puzzler.run(SolidPentominoes3x3x9Ring)

17.6

71

0.801136

19

176

7.368421

0.789474

0

0.04375

0.090909

176

9

72

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0.210227

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null

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1

0

1

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1

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5

4813dc6e409e55e64fcb43edf90f0bc58640f97f

196

py

Python

app/__init__.py

lon9/Twitter-bot-maker

f1985dac43f5ceb8ea20983a8e418c4275f8b782

[ "MIT" ]

1

2019-10-12T23:28:02.000Z

app/__init__.py

Rompei/Twitter-bot-maker

f1985dac43f5ceb8ea20983a8e418c4275f8b782

[ "MIT" ]

1

2019-12-26T16:37:03.000Z

app/__init__.py

lon9/Twitter-bot-maker

f1985dac43f5ceb8ea20983a8e418c4275f8b782

[ "MIT" ]

null

# -*- coding:utf-8 -*- __version = '1.0' from bottle import Bottle, TEMPLATE_PATH app = Bottle() TEMPLATE_PATH.append("./app/views") TEMPLATE_PATH.remove("./views/") from app.controllers import *

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196

7

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null

1

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1

0

null

0

1

0

5

48862e16641b7648ac63c45ebe3f4f1e94b1c815

1,713

py

Python

hapthexa_main/launch/launch.py

tmcit-caolab/hapthexa_ros2

74030283bba2c0c3b4de6651320c8b8a243d723c

[ "MIT" ]

null

hapthexa_main/launch/launch.py

tmcit-caolab/hapthexa_ros2

74030283bba2c0c3b4de6651320c8b8a243d723c

[ "MIT" ]

null

hapthexa_main/launch/launch.py

tmcit-caolab/hapthexa_ros2

74030283bba2c0c3b4de6651320c8b8a243d723c

[ "MIT" ]

1

2021-11-01T08:14:32.000Z

from launch import LaunchDescription from launch_ros.actions import Node def generate_launch_description(): return LaunchDescription([ Node( package="hapthexa_main", executable="hapthexa_leg", name="hapthexa_leg_front_left", namespace="hapthexa/leg/front_left" ), Node( package="hapthexa_main", executable="hapthexa_leg", name="hapthexa_leg_middle_left", namespace="hapthexa/leg/middle_left", parameters=[{'leg_install_angle': 1.57079632679}] ), Node( package="hapthexa_main", executable="hapthexa_leg", name="hapthexa_leg_rear_left", namespace="hapthexa/leg/rear_left", parameters=[{'leg_install_angle': 3.14159265359}] ), Node( package="hapthexa_main", executable="hapthexa_leg", name="hapthexa_leg_front_right", namespace="hapthexa/leg/front_right" ), Node( package="hapthexa_main", executable="hapthexa_leg", name="hapthexa_leg_middle_right", namespace="hapthexa/leg/middle_right", parameters=[{'leg_install_angle': -1.57079632679}] ), Node( package="hapthexa_main", executable="hapthexa_leg", name="hapthexa_leg_rear_right", namespace="hapthexa/leg/rear_right", parameters=[{'leg_install_angle': -3.14159265359}] ), Node( package="hapthexa_main", executable="attitude_controller.py", name="attitude_controller" ) ])

33.588235

62

0.569177

153

1,713

6.045752

0.215686

0.214054

0.143784

0.174054

0.63027

0.610811

0

0.041415

0.323409

1,713

51

63

33.588235

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0.52

1

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0.323221

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0

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null

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1

0

1

0

null

0

1

0

5

6f7c0d29b94090986352ac8683b8b0b8b68e85e7

84

py

Python

IA/Python/5/5.1/6.py

worthl3ss/random-small

ffb60781f57eb865acbd81aaa07056046bad32fe

[ "MIT" ]

1

2022-02-23T12:47:00.000Z

IA/Python/5/5.1/6.py

worthl3ss/random-small

ffb60781f57eb865acbd81aaa07056046bad32fe

[ "MIT" ]

null

IA/Python/5/5.1/6.py

worthl3ss/random-small

ffb60781f57eb865acbd81aaa07056046bad32fe

[ "MIT" ]

null

def factorial(n): if n==1 or n==0: return 1 return n*factorial(n-1)

16.8

27

0.547619

16

84

2.875

0.5

0.434783

0

0.068966

0.309524

84

4

28

21

0.724138

0

1

0.25

false

0

0.75

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

6fa9d8cffa9de939322d66001851e7534ba08d5b

46

py

Python

src/signal_backtester/base/__init__.py

xibalbas/signal_backtester

8eaa52ecad22419b29b0e0e34eaadfea83f4e4b9

[ "MIT" ]

14

2022-03-04T20:23:45.000Z

2022-03-30T11:04:40.000Z

src/signal_backtester/base/__init__.py

xibalbas/signal_backtester

8eaa52ecad22419b29b0e0e34eaadfea83f4e4b9

[ "MIT" ]

null

src/signal_backtester/base/__init__.py

xibalbas/signal_backtester

8eaa52ecad22419b29b0e0e34eaadfea83f4e4b9

[ "MIT" ]

2

2022-03-05T10:18:19.000Z

2022-03-06T12:51:49.000Z

"""Base Base Package more description """

9.2

20

0.652174

5

46

6

0.8

0

0.217391

46

4

21

11.5

0.833333

0.826087

0

null

0

null

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null

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null

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null

true

0

null

1

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null

0

1

0

1

0

null

0

1

0

5

6fc786bf49e570d05ac98894f60c30b6ee77872d

1,285

py

Python

mollie/api/objects/invoice.py

bryanwills/mollie-api-python

8122569ae83f07ad07893f3dd56e9a60bcccae05

[ "BSD-2-Clause" ]

null

mollie/api/objects/invoice.py

bryanwills/mollie-api-python

8122569ae83f07ad07893f3dd56e9a60bcccae05

[ "BSD-2-Clause" ]

null

mollie/api/objects/invoice.py

bryanwills/mollie-api-python

8122569ae83f07ad07893f3dd56e9a60bcccae05

[ "BSD-2-Clause" ]

null

from .base import ObjectBase class Invoice(ObjectBase): @classmethod def get_resource_class(cls, client): from ..resources.invoices import Invoices return Invoices(client) @property def id(self): return self._get_property("id") @property def reference(self): return self._get_property("reference") @property def vat_number(self): return self._get_property("vatNumber") @property def status(self): return self._get_property("status") @property def issued_at(self): return self._get_property("issuedAt") @property def paid_at(self): return self._get_property("paidAt") @property def due_at(self): return self._get_property("dueAt") @property def resource(self): return self._get_property("resource") @property def net_amount(self): return self._get_property("netAmount") @property def vat_amount(self): return self._get_property("vatAmount") @property def gross_amount(self): return self._get_property("grossAmount") @property def lines(self): return self._get_property("lines") or [] @property def pdf(self): return self._get_link("pdf")

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5.346939

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0.231552

0.28117

0.412214

0.221374

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1,285

61

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21.065574

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0

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0.070039

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0.311111

false

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0.044444

0.288889

0.688889

0

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