xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

0efb8720ad0645c0753d8551dba0dae3a4ea407e

1,223

py

Python

decawave_1001_rjg/messages/dwm_config_response.py

Richard-Gemmell/decawave-1001-rjg

0ee70d1ca0a1a413ef4f634c0f3cd78a084e5c5f

[ "MIT" ]

6

2019-08-05T22:16:38.000Z

2021-01-16T02:45:26.000Z

decawave_1001_rjg/messages/dwm_config_response.py

Richard-Gemmell/decawave-1001-rjg

0ee70d1ca0a1a413ef4f634c0f3cd78a084e5c5f

[ "MIT" ]

null

decawave_1001_rjg/messages/dwm_config_response.py

Richard-Gemmell/decawave-1001-rjg

0ee70d1ca0a1a413ef4f634c0f3cd78a084e5c5f

[ "MIT" ]

3

2021-01-16T02:45:29.000Z

2022-03-26T21:38:44.000Z

from .dwm_response import DwmResponse class DwmConfigResponse(DwmResponse): """Returned by a dwm_cfg_get request """ def __init__(self, message: bytes): super().__init__(message) @property def anchor(self) -> bool: return (self[6] & 0x20) != 0 @property def tag(self) -> bool: return not self.anchor @property def initiator(self) -> bool: return (self[6] & 0x10) != 0 @property def bridge(self) -> bool: return (self[6] & 0x08) != 0 @property def accelerometer_enabled(self) -> bool: return (self[6] & 0x04) != 0 @property def two_way_ranging(self) -> bool: return (self[6] & 0x03) == 0 @property def low_power_enabled(self) -> bool: return (self[5] & 0x80) != 0 @property def location_engine_enabled(self) -> bool: return (self[5] & 0x40) != 0 @property def led_enabled(self) -> bool: return (self[5] & 0x10) != 0 @property def ble_enabled(self) -> bool: return (self[5] & 0x08) != 0 @property def firmware_update_enabled(self) -> bool: return (self[5] & 0x04) != 0

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py

Python

app/command/command.py

monosloth/console

a47e1479320a18a4b5716e87ee275985ebd5825f

[ "MIT" ]

null

app/command/command.py

monosloth/console

a47e1479320a18a4b5716e87ee275985ebd5825f

[ "MIT" ]

null

app/command/command.py

monosloth/console

a47e1479320a18a4b5716e87ee275985ebd5825f

[ "MIT" ]

null

from abc import ABCMeta, abstractmethod class AbstractCommand(metaclass=ABCMeta): @abstractmethod def invoke(self, args): pass

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116

py

Python

lenses/base.py

blandfort/mirror

70ae41fd151275d42506d07117aa2ea3ce59ad23

[ "MIT" ]

null

lenses/base.py

blandfort/mirror

70ae41fd151275d42506d07117aa2ea3ce59ad23

[ "MIT" ]

6

2020-11-06T22:40:05.000Z

2022-03-12T00:51:06.000Z

lenses/base.py

blandfort/mirror

70ae41fd151275d42506d07117aa2ea3ce59ad23

[ "MIT" ]

null

from abc import ABC, abstractmethod class Lens(ABC): @abstractmethod def show(self, rays): pass

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16220350b3dec328bea79f8b9497f3e66d179f02

110

py

Python

setup.py

Luigi-PastorePica/FreeD

e4267275b3edaefe3ca31bc38a5fc0fd3809cab0

[ "MIT" ]

null

setup.py

Luigi-PastorePica/FreeD

e4267275b3edaefe3ca31bc38a5fc0fd3809cab0

[ "MIT" ]

19

2020-09-30T02:57:33.000Z

2020-11-15T21:09:14.000Z

setup.py

Luigi-PastorePica/FreeD

e4267275b3edaefe3ca31bc38a5fc0fd3809cab0

[ "MIT" ]

null

# Pytest config setup from setuptools import setup, find_packages setup(name="src", packages=find_packages())

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167fd28ab1c37a93d5946fbd63b263ad16f39097

48

py

Python

tests/subcommands/test_local.py

jonathan-shemer/chenv

e2b86b7a53031a35def1be21ece87a05d74d2919

[ "MIT" ]

3

2020-10-15T07:46:48.000Z

2021-09-06T20:49:05.000Z

tests/subcommands/test_local.py

jonathan-shemer/chenv

e2b86b7a53031a35def1be21ece87a05d74d2919

[ "MIT" ]

5

2021-01-27T11:47:12.000Z

2021-08-30T08:49:37.000Z

tests/subcommands/test_local.py

jonathan-shemer/chenv

e2b86b7a53031a35def1be21ece87a05d74d2919

[ "MIT" ]

1

2022-03-15T09:29:19.000Z

"""Test cases for the `inputs.local` module."""

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py

Python

enthought/block_canvas/app/ui/configurable_import_ui.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

3

2016-12-09T06:05:18.000Z

2018-03-01T13:00:29.000Z

enthought/block_canvas/app/ui/configurable_import_ui.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

1

2020-12-02T00:51:32.000Z

2020-12-02T08:48:55.000Z

enthought/block_canvas/app/ui/configurable_import_ui.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

null

# proxy module from __future__ import absolute_import from blockcanvas.app.ui.configurable_import_ui import *

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16853577094d5e05ac96edc65a412de8144e742c

380

py

Python

bin/transformers/examples/transformers/data/__init__.py

shammur/news_categorization_english

58282c10f887a90932cbc0fd0dec0c556b98c19d

[ "Apache-2.0" ]

null

bin/transformers/examples/transformers/data/__init__.py

shammur/news_categorization_english

58282c10f887a90932cbc0fd0dec0c556b98c19d

[ "Apache-2.0" ]

19

2020-03-24T18:15:26.000Z

2022-02-10T01:54:04.000Z

bin/transformers/examples/transformers/data/__init__.py

shammur/news_categorization_english

58282c10f887a90932cbc0fd0dec0c556b98c19d

[ "Apache-2.0" ]

null

from .processors import InputExample, InputFeatures, DataProcessor from .processors import glue_output_modes, glue_processors, glue_tasks_num_labels, glue_convert_examples_to_features, glue_convert_examples_to_features_multiclass from .processors import tokenize from .metrics import is_sklearn_available if is_sklearn_available(): from .metrics import glue_compute_metrics

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67

py

Python

flambeau/misc/__init__.py

corenel/flambeau

3e90f37ba3d692af6df02da39907132ff9a490da

[ "MIT" ]

1

2021-07-15T02:06:23.000Z

flambeau/misc/__init__.py

corenel/flambeau

3e90f37ba3d692af6df02da39907132ff9a490da

[ "MIT" ]

null

flambeau/misc/__init__.py

corenel/flambeau

3e90f37ba3d692af6df02da39907132ff9a490da

[ "MIT" ]

null

from .config import OrderedEasyDict from .util import AverageMeter

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8,083

py

Python

tests/test_verification.py

1beb/django-rest-framework-passwordless

e5606e7d764aa4b951a0b7c643f76e27aec84556

[ "MIT" ]

null

tests/test_verification.py

1beb/django-rest-framework-passwordless

e5606e7d764aa4b951a0b7c643f76e27aec84556

[ "MIT" ]

null

tests/test_verification.py

1beb/django-rest-framework-passwordless

e5606e7d764aa4b951a0b7c643f76e27aec84556

[ "MIT" ]

null

from rest_framework import status from rest_framework.authtoken.models import Token from django.utils.translation import gettext_lazy as _ from rest_framework.test import APITestCase from django.contrib.auth import get_user_model from django.urls import reverse from drfpasswordless.settings import api_settings, DEFAULTS from drfpasswordless.utils import CallbackToken User = get_user_model() class AliasEmailVerificationTests(APITestCase): def setUp(self): api_settings.PASSWORDLESS_AUTH_TYPES = ['EMAIL'] api_settings.PASSWORDLESS_EMAIL_NOREPLY_ADDRESS = 'noreply@example.com' api_settings.PASSWORDLESS_USER_MARK_EMAIL_VERIFIED = True self.url = reverse('drfpasswordless:auth_email') self.callback_url = reverse('drfpasswordless:auth_token') self.verify_url = reverse('drfpasswordless:verify_email') self.callback_verify = reverse('drfpasswordless:verify_token') self.email_field_name = api_settings.PASSWORDLESS_USER_EMAIL_FIELD_NAME self.email_verified_field_name = api_settings.PASSWORDLESS_USER_EMAIL_VERIFIED_FIELD_NAME def test_email_unverified_to_verified_and_back(self): email = 'aaron@example.com' email2 = 'aaron2@example.com' data = {'email': email} # create a new user response = self.client.post(self.url, data) self.assertEqual(response.status_code, status.HTTP_200_OK) user = User.objects.get(**{self.email_field_name: email}) self.assertNotEqual(user, None) self.assertEqual(getattr(user, self.email_verified_field_name), False) # Verify a token exists for the user, sign in and check verified again callback = CallbackToken.objects.filter(user=user, type=CallbackToken.TOKEN_TYPE_AUTH, is_active=True).first() callback_data = {'email': email, 'token': callback} callback_response = self.client.post(self.callback_url, callback_data) self.assertEqual(callback_response.status_code, status.HTTP_200_OK) # Verify we got the token, then check and see that email_verified is now verified token = callback_response.data['token'] self.assertEqual(token, Token.objects.get(user=user).key) # Refresh and see that the endpoint is now verified as True user.refresh_from_db() self.assertEqual(getattr(user, self.email_verified_field_name), True) # Change email, should result in flag changing to false setattr(user, self.email_field_name, email2) user.save() user.refresh_from_db() self.assertEqual(getattr(user, self.email_verified_field_name), False) # Verify self.client.force_authenticate(user) verify_response = self.client.post(self.verify_url) self.assertEqual(verify_response.status_code, status.HTTP_200_OK) # Refresh User user = User.objects.get(**{self.email_field_name: email2}) self.assertNotEqual(user, None) self.assertNotEqual(getattr(user, self.email_field_name), None) self.assertEqual(getattr(user, self.email_verified_field_name), False) # Post callback token back. verify_token = CallbackToken.objects.filter(user=user, type=CallbackToken.TOKEN_TYPE_VERIFY, is_active=True).first() self.assertNotEqual(verify_token, None) verify_callback_response = self.client.post(self.callback_verify, {'email': email2, 'token': verify_token.key}) self.assertEqual(verify_callback_response.status_code, status.HTTP_200_OK) # Refresh User user = User.objects.get(**{self.email_field_name: email2}) self.assertNotEqual(user, None) self.assertNotEqual(getattr(user, self.email_field_name), None) self.assertEqual(getattr(user, self.email_verified_field_name), True) def tearDown(self): api_settings.PASSWORDLESS_AUTH_TYPES = DEFAULTS['PASSWORDLESS_AUTH_TYPES'] api_settings.PASSWORDLESS_EMAIL_NOREPLY_ADDRESS = DEFAULTS['PASSWORDLESS_EMAIL_NOREPLY_ADDRESS'] api_settings.PASSWORDLESS_USER_MARK_EMAIL_VERIFIED = DEFAULTS['PASSWORDLESS_USER_MARK_MOBILE_VERIFIED'] class AliasMobileVerificationTests(APITestCase): def setUp(self): api_settings.PASSWORDLESS_TEST_SUPPRESSION = True api_settings.PASSWORDLESS_AUTH_TYPES = ['MOBILE'] api_settings.PASSWORDLESS_MOBILE_NOREPLY_NUMBER = '+15550000000' api_settings.PASSWORDLESS_USER_MARK_MOBILE_VERIFIED = True self.url = reverse('drfpasswordless:auth_mobile') self.callback_url = reverse('drfpasswordless:auth_token') self.verify_url = reverse('drfpasswordless:verify_mobile') self.callback_verify = reverse('drfpasswordless:verify_token') self.mobile_field_name = api_settings.PASSWORDLESS_USER_MOBILE_FIELD_NAME self.mobile_verified_field_name = api_settings.PASSWORDLESS_USER_MOBILE_VERIFIED_FIELD_NAME def test_mobile_unverified_to_verified_and_back(self): mobile = '+15551234567' mobile2 = '+15557654321' data = {'mobile': mobile} # create a new user response = self.client.post(self.url, data) self.assertEqual(response.status_code, status.HTTP_200_OK) user = User.objects.get(**{self.mobile_field_name: mobile}) self.assertNotEqual(user, None) self.assertEqual(getattr(user, self.mobile_verified_field_name), False) # Verify a token exists for the user, sign in and check verified again callback = CallbackToken.objects.filter(user=user, type=CallbackToken.TOKEN_TYPE_AUTH, is_active=True).first() callback_data = {'mobile': mobile, 'token': callback} callback_response = self.client.post(self.callback_url, callback_data) self.assertEqual(callback_response.status_code, status.HTTP_200_OK) # Verify we got the token, then check and see that email_verified is now verified token = callback_response.data['token'] self.assertEqual(token, Token.objects.get(user=user).key) # Refresh and see that the endpoint is now verified as True user.refresh_from_db() self.assertEqual(getattr(user, self.mobile_verified_field_name), True) # Change mobile, should result in flag changing to false setattr(user, self.mobile_field_name, '+15557654321') user.save() user.refresh_from_db() self.assertEqual(getattr(user, self.mobile_verified_field_name), False) # Verify self.client.force_authenticate(user) verify_response = self.client.post(self.verify_url) self.assertEqual(verify_response.status_code, status.HTTP_200_OK) # Refresh User user = User.objects.get(**{self.mobile_field_name: mobile2}) self.assertNotEqual(user, None) self.assertNotEqual(getattr(user, self.mobile_field_name), None) self.assertEqual(getattr(user, self.mobile_verified_field_name), False) # Post callback token back. verify_token = CallbackToken.objects.filter(user=user, type=CallbackToken.TOKEN_TYPE_VERIFY, is_active=True).first() self.assertNotEqual(verify_token, None) verify_callback_response = self.client.post(self.callback_verify, {'mobile': mobile2, 'token': verify_token.key}) self.assertEqual(verify_callback_response.status_code, status.HTTP_200_OK) # Refresh User user = User.objects.get(**{self.mobile_field_name: mobile2}) self.assertNotEqual(user, None) self.assertNotEqual(getattr(user, self.mobile_field_name), None) self.assertEqual(getattr(user, self.mobile_verified_field_name), True) def tearDown(self): api_settings.PASSWORDLESS_TEST_SUPPRESSION = DEFAULTS['PASSWORDLESS_TEST_SUPPRESSION'] api_settings.PASSWORDLESS_AUTH_TYPES = DEFAULTS['PASSWORDLESS_AUTH_TYPES'] api_settings.PASSWORDLESS_MOBILE_NOREPLY_ADDRESS = DEFAULTS['PASSWORDLESS_MOBILE_NOREPLY_NUMBER'] api_settings.PASSWORDLESS_USER_MARK_MOBILE_VERIFIED = DEFAULTS['PASSWORDLESS_USER_MARK_MOBILE_VERIFIED']

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py

Python

brawlbracket/__init__.py

TheLastBanana/BrawlBracket

1cad26b6499352b1b282388f4f76bfb4b2b6b4fe

[ "BSD-3-Clause" ]

null

brawlbracket/__init__.py

TheLastBanana/BrawlBracket

1cad26b6499352b1b282388f4f76bfb4b2b6b4fe

[ "BSD-3-Clause" ]

null

brawlbracket/__init__.py

TheLastBanana/BrawlBracket

1cad26b6499352b1b282388f4f76bfb4b2b6b4fe

[ "BSD-3-Clause" ]

null

from brawlbracket.app import runWebServer

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py

Python

labuda/02.py

mallimuondu/python-homworks

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labuda/02.py

mallimuondu/python-homworks

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[ "MIT" ]

null

labuda/02.py

mallimuondu/python-homworks

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[ "MIT" ]

null

x =lambda a, b : a * b

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py

Python

src/Division.py

leivapaola/Calculator

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[ "MIT" ]

null

src/Division.py

leivapaola/Calculator

1d7e91f93c3f308c289e34c5872591bfd8bf7cdb

[ "MIT" ]

null

src/Division.py

leivapaola/Calculator

1d7e91f93c3f308c289e34c5872591bfd8bf7cdb

[ "MIT" ]

null

def division(a, b): return "{:.9f}".format(float(a) / float(b))

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py

Python

CodeWars/Python/6 kyu/Array.diff/main.py

opastushkov/codewars-solutions

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[ "MIT" ]

null

CodeWars/Python/6 kyu/Array.diff/main.py

opastushkov/codewars-solutions

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[ "MIT" ]

null

CodeWars/Python/6 kyu/Array.diff/main.py

opastushkov/codewars-solutions

0132a24259a4e87f926048318332dcb4d94858ca

[ "MIT" ]

null

def array_diff(a, b): return [x for x in a if x not in b]

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bc81221f69258c3819f8383ec54f19a6baf74f79

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py

Python

afs/service/VLDBServiceError.py

chanke/afspy

525e7b3b53e58be515f11b83cc59ddb0765ef8e5

[ "BSD-2-Clause" ]

null

afs/service/VLDBServiceError.py

chanke/afspy

525e7b3b53e58be515f11b83cc59ddb0765ef8e5

[ "BSD-2-Clause" ]

null

afs/service/VLDBServiceError.py

chanke/afspy

525e7b3b53e58be515f11b83cc59ddb0765ef8e5

[ "BSD-2-Clause" ]

null

from afs.util.AFSError import AFSError class VLDBServiceError(AFSError): pass

16.6

38

0.795181

10

83

6.6

0.8

0

0.144578

83

4

39

20.75

0.929577

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

5

bc8f3762d005e5803bb9673c1c08bf3c62f12df2

15,757

py

Python

desktop/core/ext-py/guppy-0.1.10/guppy/heapy/pbhelp.py

kokosing/hue

2307f5379a35aae9be871e836432e6f45138b3d9

[ "Apache-2.0" ]

11

2019-03-20T07:38:35.000Z

2021-06-18T09:42:46.000Z

desktop/core/ext-py/guppy-0.1.10/guppy/heapy/pbhelp.py

zks888/hue

93a8c370713e70b216c428caa2f75185ef809deb

[ "Apache-2.0" ]

4

2021-03-11T04:02:00.000Z

2022-03-27T08:31:56.000Z

desktop/core/ext-py/guppy-0.1.10/guppy/heapy/pbhelp.py

zks888/hue

93a8c370713e70b216c428caa2f75185ef809deb

[ "Apache-2.0" ]

5

2019-06-29T03:13:02.000Z

2020-04-23T04:47:11.000Z

# AUTOMATICALLY GENERATED BY GENGUPPY about="(iguppy.gsl.Text\nRecordingInter\np1\n(dp2\nS'tag_configs'\np3\n(dp4\nI0\n((S'spacing1'\np5\nI11\ntp6\n(S'font'\np7\n(S'times'\np8\nI24\nS'bold'\ntttp9\nsI1\n(g6\n(S'tabs'\np10\n(F23.5\nS'center'\np11\nF57\nS'left'\np12\nttp13\n(g7\n(g8\nI12\nS'bold'\ntp14\ntp15\ntp16\nsI2\n(g6\ng15\ntp17\nsI3\n(g6\n(g7\n(g8\nI12\ntp18\ntp19\ntp20\nsI4\n((g5\nI6\ntp21\ng13\ntp22\nsI5\n(g21\n(g7\n(g8\nI10\nS'italic'\ntttp23\nsI6\n(g21\n(g7\n(g8\nI10\ntttp24\nsI7\n(g21\ng19\ntp25\nsI8\n(g19\ntp26\nssS'_gsl_tk_geometry'\np27\nS'400x200'\np28\nsS'_gsl_title'\np29\nS'About Heapy Profile Browser'\np30\nsS'appends'\np31\n(lp32\nI0\naS'Heapy Profile Browser \\n'\np33\naI1\naS'\\t'\naI2\naS'Version'\np34\naI1\naS'\\t'\naI3\naS'0.1\\n'\np35\naI4\naS'\\t'\naI2\naS'Author'\np36\naI4\naS'\\t'\naI3\naS'Sverker Nilsson\\n'\np37\naI4\naS'\\t'\naI2\naS'Email'\np38\naI4\naS'\\t'\naI3\naS'sn@sncs.se\\n'\np39\naI4\naS'\\t'\naI2\naS'License'\np40\naI4\naS'\\t'\naI3\naS'MIT \\n'\np41\naI5\naS'Copyright (c) 2005--2008'\np42\naI6\naS' S. Nilsson Computer System AB Linkoping, Sweden '\np43\naI7\naS'\\n'\nasb." help='(iguppy.gsl.Text\nRecordingInter\np1\n(dp2\nS\'tag_configs\'\np3\n(dp4\nI0\n((S\'spacing1\'\np5\nI10\ntp6\n(S\'font\'\np7\n(S\'times\'\np8\nI20\nS\'bold\'\ntttp9\nsI1\n(g6\n(g7\n(g8\nI12\nttp10\ntp11\nsI2\n((g5\nI6\ntp12\ng10\ntp13\nsI3\n((g5\nI9\ntp14\n(g7\n(g8\nI16\nS\'bold\'\ntttp15\nsI4\n(g10\ntp16\nsI5\n((S\'lmargin2\'\np17\nI36\ntp18\ng12\n(S\'tabs\'\np19\n(F97.5\nS\'center\'\np20\nF169\nS\'left\'\np21\nttp22\n(S\'lmargin1\'\np23\nI36\ntp24\n(g7\n(g8\nI12\nS\'bold\'\ntp25\ntp26\ntp27\nsI6\n(g18\ng12\ng24\ng26\ntp28\nsI7\n(g18\ng12\ng24\ng10\ntp29\nsI8\n(g22\ntp30\nsI9\n(g12\ng22\ntp31\nsI10\n(g18\ng24\ng10\ntp32\nsI11\n(g18\ng12\n(g19\n(F96\ng20\nF166\ng21\nttp33\ng24\ng26\ntp34\nsI12\n(g12\ng33\ntp35\nsI13\n(g18\ng12\n(g19\n(F71.5\ng20\nF117\ng21\nttp36\ng24\ng26\ntp37\nsI14\n(g36\ntp38\nsI15\n(g12\ng36\ntp39\nsI16\n(g18\ng24\n(g7\n(g8\nI10\nttp40\ntp41\nsI17\n(g18\n(g5\nI8\ntp42\ng24\ng26\ntp43\nsI18\n((g17\nI72\ntp44\n(g23\nI72\ntp45\ng10\ntp46\nsI19\n(g44\ng12\n(g19\n(F125.5\ng20\nF189\ng21\nttp47\ng45\ng26\ntp48\nsI20\n(g44\ng12\ng45\ng26\ntp49\nsI21\n(g44\ng12\ng45\ng10\ntp50\nsI22\n(g47\ntp51\nsI23\n(g12\ng47\ntp52\nsI24\n(g44\ng45\ng26\ntp53\nsI25\n(g44\ng12\n(g19\n(F116.5\ng20\nF171\ng21\nttp54\ng45\ng26\ntp55\nsI26\n(g54\ntp56\nsI27\n(g18\ng12\n(g19\n(F54.5\ng20\nF83\ng21\nttp57\ng24\ng26\ntp58\nsI28\n(g12\ng57\ntp59\nsI29\n(g14\ng10\ntp60\nsI30\n(g44\ng12\n(g19\n(F115.5\ng20\nF169\ng21\nttp61\ng45\ng26\ntp62\nsI31\n(g61\ntp63\nsI32\n(g12\ng61\ntp64\nsI33\n(g44\ng45\ng40\ntp65\nsI34\n(g44\ng12\n(g19\n(F111.5\ng20\nF161\ng21\nttp66\ng45\ng26\ntp67\nsI35\n(g66\ntp68\nsI36\n(g12\ng66\ntp69\nsI37\n(g18\ng42\ng24\ng10\ntp70\nssS\'_gsl_title\'\np71\nS\'Help for Heapy Profile Browser\'\np72\nsS\'appends\'\np73\n(lp74\nI0\naS\'Menus\\n\'\np75\naI1\naS\'Click on the dotted line at the top of a menu to "tear it off": a separate window containing the menu is created. \\n\'\np76\naI3\naS\'File Menu\\n\'\np77\naI5\naS\'\\t\'\naI6\naS\'New Profile Browser\'\np78\naI5\naS\'\\t\'\naI7\naS\'Create a new browser window with the same\\n\'\np79\naI8\naS\'\\t\\t\'\np80\naI7\naS\'file as the one opened in the current window. \\n\'\np81\naI9\naS\'\\t\'\naI6\naS\'Open Profile\'\np82\naI9\naS\'\\t\'\naI7\naS\'Open a profile data file in the current window.\\n\'\np83\naI9\naS\'\\t\'\naI6\naS\'Close Window\'\np84\naI9\naS\'\\t\'\naI7\naS\'Close the current window (exits from Tk if it\\n\'\np85\naI8\nag80\naI7\naS\'was the last browser window). \\n\'\np86\naI9\naS\'\\t\'\naI6\naS\'Clear Cache\'\np87\naI9\naS\'\\t\'\naI7\naS\'Clear the sample cache, releasing its memory.\\n\'\np88\naI8\nag80\naI7\naS\'The cache will be automatically filled again\\n\'\np89\naI8\nag80\naI7\naS\'when needed. \\n\'\np90\naI8\nag80\naI10\naS\'This command is a kind of temporary /\'\np91\naI7\naS\'\\n\'\naI8\nag80\naI10\naS\'experimental feature. I think the cache handling\'\np92\naI7\naS\'\\n\'\naI8\nag80\naI10\naS\'should be made automatic and less memory\'\np93\naI7\naS\'\\n\'\naI8\nag80\naI10\naS\'consuming. \'\np94\naI7\naS\'\\n\'\naI3\naS\'Pane Menu\\n\'\np95\naI11\naS\'\\t\'\naI6\naS\'Show Control Panel\'\np96\naI11\naS\'\\t\'\naI7\naS\'Show the control panel pane.\\n\'\np97\naI12\naS\'\\t\'\naI6\naS\'Show Graph\'\np98\naI12\naS\'\\t\'\naI7\naS\'Show the graph pane.\\n\'\np99\naI12\naS\'\\t\'\naI6\naS\'Show Table\'\np100\naI12\naS\'\\t\'\naI7\naS\'Show the table pane. \\n\'\np101\naI3\naS\'Graph Menu\\n\'\np102\naI13\naS\'\\t\'\naI6\naS\'Bars / Lines\'\np103\naI13\naS\'\\t\'\naI7\naS\'Choose whether the graph should be displayed using bars\\n\'\np104\naI14\nag80\naI7\naS\'or lines. \\n\'\np105\naI14\nag80\naI10\naS\'When using bars, the sample value (size or count) for\'\np106\naI7\naS\'\\n\'\naI14\nag80\naI10\naS\'different kinds of objects will be stacked on top of each\'\np107\naI7\naS\'\\n\'\naI14\nag80\naI10\naS\'other so the total height represents the total value of a\'\np108\naI7\naS\'\\n\'\naI14\nag80\naI10\naS\'sample. When using lines, each line represents the value\'\np109\naI7\naS\'\\n\'\naI14\nag80\naI10\naS\'for a single kind of object. The 10 largest values are\'\np110\naI7\naS\'\\n\'\naI14\nag80\naI10\naS\'shown in each sample point. Each kind has a particular\'\np111\naI7\naS\'\\n\'\naI14\nag80\naI10\naS\'color, choosen arbitrary but it is always the same color\'\np112\naI7\naS\'\\n\'\naI14\nag80\naI10\naS\'for the same kind. The remaing kinds, if any, are shown in\'\np113\naI7\naS\'\\n\'\naI14\nag80\naI10\naS\'black. \'\np114\naI7\naS\'\\n\'\naI15\naS\'\\t\'\naI6\naS\'Size / Count\'\np115\naI15\naS\'\\t\'\naI7\naS\'Choose whether the graph should display the size of\\n\'\np116\naI14\nag80\naI7\naS\'objects of a particular kind or the number of objects of\\n\'\np117\naI14\nag80\naI7\naS\'that kind. \\n\'\np118\naI14\nag80\naI16\naS\'(Note that this affects only the graph, the table will still\'\np119\naI7\naS\'\\n\'\naI14\nag80\naI16\naS\'choose size or kind as it were choosen in the table menu.)\'\np120\naI7\naS\'\\n\'\naI14\nag80\naI7\naS\'\\n\'\naI3\naS\'Table Menu\\n\'\np121\naI17\naS\'Header submenu\\n\'\np122\naI18\naS\'This menu has a choice of header for each column of the table. The data of each column is determined by the header of that column, as well as the headers of previous columns. So if you change the first column header (A/B), the data in that column will change as well as the data under the next header (Size/Count) and the ones that follow. \\n\'\np123\naI19\naS\'\\t\'\naI20\naS\'A / B\'\np124\naI19\naS\'\\t\'\naI21\naS\'Use the sample at the A or B marker in the graph.\\n\'\np125\naI22\nag80\naI18\naS\'The kinds of objects shown in the table under this\'\np126\naI21\naS\'\\n\'\naI22\nag80\naI18\naS\'column are taken from the 10 largest sample values\'\np127\naI21\naS\'\\n\'\naI22\nag80\naI18\naS\'at that point, in the same order as they are shown in\'\np128\naI21\naS\'\\n\'\naI22\nag80\naI18\naS\'the graph. The ordering in the graph depends on\'\np129\naI21\naS\'\\n\'\naI22\nag80\naI18\naS\'the choice of count or size in the graph menu.\'\np130\naI21\naS\'\\n\'\naI22\nag80\naI18\naS\'However, the table may show count or size\'\np131\naI21\naS\'\\n\'\naI22\nag80\naI18\naS\'independent from the choice in the graph. \'\np132\naI21\naS\'\\n\'\naI23\naS\'\\t\'\naI20\nag115\naI23\naS\'\\t\'\naI21\naS\'Show the size or count of the kinds of objects in\\n\'\np133\naI22\nag80\naI21\naS\'each row, taken from those choosen in the A / B\\n\'\np134\naI22\nag80\naI21\naS\'column. \\n\'\np135\naI23\naS\'\\t\'\naI20\naS\'%A:Tot / %B:Tot\'\np136\naI23\naS\'\\t\'\naI21\naS\'Show percentage of the Size / Count column,\\n\'\np137\naI22\nag80\naI21\naS\'relative to the total (size or count) at either the A or\\n\'\np138\naI22\nag80\naI21\naS\'B sample point. \\n\'\np139\naI23\naS\'\\t\'\naI20\naS\'Cumul /\'\np140\naI23\naS\'\\t\'\naI21\naS\'Show either a cumulative sum of the Size / Count\\n\'\np141\naI22\naS\'\\t\'\naI20\naS\'\'\naI24\naS\'A-B / B-A\'\np142\naI22\naS\'\\t\'\naI21\naS\'column, or the difference A-B or B-A. \\n\'\np143\naI22\nag80\naI18\naS\'The cumulative sum is taken by summing from the\'\np144\naI21\naS\'\\n\'\naI22\nag80\naI18\naS\'first table row down to the last row. \'\np145\naI21\naS\'\\n\'\naI23\naS\'\\t\'\naI20\nag136\naI23\naS\'\\t\'\naI21\naS\'Show percentage of the previous field, relative to\\n\'\np146\naI22\nag80\naI21\naS\'either the A or B total. \\n\'\np147\naI23\naS\'\\t\'\naI20\naS\'Kind\'\np148\naI23\naS\'\\t\'\naI21\naS\'Shows the kind of objects. This is currently the only\\n\'\np149\naI22\nag80\naI21\naS\'alternative for this column. The kind shown\\n\'\np150\naI22\nag80\naI21\naS\'corresponds to the color shown in the A / B\\n\'\np151\naI22\nag80\naI21\naS\'column. A special kind is <Other> which\\n\'\np152\naI22\nag80\naI21\naS\'summarizes the remaining data if there were more\\n\'\np153\naI22\nag80\naI21\naS\'than 10 different kinds in the sample. \\n\'\np154\naI17\naS\'Scrollbar submenu\\n\'\np155\naI25\naS\'\\t\'\naI20\naS\'Auto / On / Off\'\np156\naI25\naS\'\\t\'\naI21\naS\'Choose a scrollbar mode. The usual setting is Auto\\n\'\np157\naI26\nag80\naI21\naS\'which shows the scrollbar only when needed. \\n\'\np158\naI3\naS\'Window Menu\\n\'\np159\naI10\naS\'This menu lists the names of all open windows. Selecting one brings it to the top, deiconifying it if necessary. \\n\'\np160\naI3\naS\'Help Menu\\n\'\np161\naI27\naS\'\\t\'\naI6\naS\'About\'\np162\naI27\naS\'\\t\'\naI7\naS\'Version, author, email, copyright.\\n\'\np163\naI28\naS\'\\t\'\naI6\naS\'Help\'\np164\naI28\naS\'\\t\'\naI7\naS\'Open this help window. \\n\'\np165\naI0\naS\'Panes\\n\'\np166\naI1\naS\'There are 3 panes in the main window shown by default. At the top is the Control Panel, at the bottom left the Graph and at the bottom right the Table. \\n\'\np167\naI3\naS\'Control Panel Pane\\n\'\np168\naI29\naS\'This contains controls for the graph and the markers. It also has a quick-exit button and a collect button.\\n\'\np169\naI17\naS\'X / Y axis control\\n\'\np170\naI18\naS\'The two frames in the Control Panel having an X or Y button in the top left corner control each axis of the graph. The X, horizontal, axis shows the sample point. The Y axis shows either the size or count, as choosen in the Graph menu. \\n\'\np171\naI30\naS\'\\t\'\naI20\naS\'X / Y Button\'\np172\naI30\naS\'\\t\'\naI21\naS\'Brings up a menu, currently containing some buttons\\n\'\np173\naI31\nag80\naI21\naS\'that can also be accessed directly in the panel. \\n\'\np174\naI32\naS\'\\t\'\naI20\naS\'Grid button\'\np175\naI32\naS\'\\t\'\naI21\naS\'Select if the graph should show grid lines.\\n\'\np176\naI32\naS\'\\t\'\naI20\naS\'Range buttons\'\np177\naI32\naS\'\\t\'\naI21\naS\'Change the range that is shown in the displayed\\n\'\np178\naI31\naS\'\\t\'\naI20\naS\'\'\naI24\naS\'- / +\'\np179\naI31\naS\'\\t\'\naI21\naS\'portion of the graph. For each time + or - is pressed the\\n\'\np180\naI31\nag80\naI21\naS\'range will be stepped up or down in the sequence (1, 2,\\n\'\np181\naI31\nag80\naI21\naS\'5) and multiples thereoff. \\n\'\np182\naI32\naS\'\\t\'\naI20\naS\'Range field\'\np183\naI32\naS\'\\t\'\naI21\naS\'The current range is shown here, and a new range can\\n\'\np184\naI31\nag80\naI21\naS\'be entered by writing to this field and pressing Enter.\\n\'\np185\naI31\nag80\naI21\naS\'The format is an integer that may be followed by a\\n\'\np186\naI31\nag80\naI21\naS\'multiplier, K, M, G, or T, meaning that the value is\\n\'\np187\naI31\nag80\naI21\naS\'multipled by 1000, 1E6, 1E9, or 1E12 respectively.\\n\'\np188\naI31\nag80\naI21\naS\'The maximum range is 1T. \\n\'\np189\naI17\naS\'A / B sample control\\n\'\np190\naI18\naS\'Each of the frames showing A or B in the top left corner controls one of the sample markers. The current position is shown in the bottom left corner.\'\np191\naI33\naS\'(This is currently not an entry field - TODO - but the marker may be moved long distances by directly dragging it in the Graph frame.) \'\np192\naI18\naS\'\\n\'\naI34\naS\'\\t\'\naI20\naS\'- / + \'\np193\naI34\naS\'\\t\'\naI21\naS\'Step the marker one step to the left (-) or to the right (+).\\n\'\np194\naI35\nag80\naI18\naS\'The table will be updated to show new data if it was set\'\np195\naI21\naS\'\\n\'\naI35\nag80\naI18\naS\'to show such data that were dependent on the marker\'\np196\naI21\naS\'\\n\'\naI35\nag80\naI18\naS\'moved. \'\np197\naI21\naS\'\\n\'\naI35\nag80\naI18\naS\'The graph will show the new marker position. If the\'\np198\naI21\naS\'\\n\'\naI35\nag80\naI18\naS\'marker was outside of the displayed portion of the\'\np199\naI21\naS\'\\n\'\naI35\nag80\naI18\naS\'graph, the graph will scroll so the marker becomes\'\np200\naI21\naS\'\\n\'\naI35\nag80\naI18\naS\'visible. \'\np201\naI21\naS\'\\n\'\naI36\naS\'\\t\'\naI20\naS\'Track button\'\np202\naI36\naS\'\\t\'\naI21\naS\'Press to set the marker to the last sample in the file and\\n\'\np203\naI35\nag80\naI21\naS\'stay at the end as new samples are added. (New\\n\'\np204\naI35\nag80\naI21\naS\'samples are periodically read from the end of the file\\n\'\np205\naI35\nag80\naI21\naS\'when auto-collect is selected via the Collect button.) \\n\'\np206\naI35\nag80\naI18\naS\'Tracking is turned off when the marker is manually\'\np207\naI21\naS\'\\n\'\naI35\nag80\naI18\nag197\naI21\naS\'\\n\'\naI17\naS\'Exit button\\n\'\np208\naI18\naS\'Exits the program, a shortcut for the Exit command in the File menu.\\n\'\np209\naI17\naS\'Collect button\\n\'\np210\naI18\naS\'When selected, the browser will collect new samples from the current file, and will continue to do this periodically.\\n\'\np211\naI33\naS\'Currently it will check the file for new data once a second. \'\np212\naI18\naS\'\\n\'\naI3\naS\'Graph Pane\\n\'\np213\naI10\naS\'This pane shows the currently visible portion of the sample file. It can be scrolled via an horizontal scrollbar. The two markers are shown as buttons labeled A and B above the graph and with lines extending down in the graph. Markers can be moved by the mouse. \\n\'\np214\naI7\naS\'How to move the markers is hopefully quite self evident when tried out but I wrote up some details about it anyway.\\n\'\np215\naI17\naS\'Marker movement details\\n\'\np216\naI37\naS"Holding down the mouse button and moving the mouse moves the underlying marker. Klicking the mouse button over a marker without moving the mouse, selects the marker. While it is selected any movement of the mouse within the graph will move the marker with it. Klicking again anywhere in the graph will deselect the marker. If the marker can be moved, the cursor will be an arrow indicating the direction it can be moved, left or right or both. If the marker can not be moved in any direction, the cursor will show a circle or disc. The marker can not move outside the available samples. Moving the mouse outside of the graph also restricts the movement of the mouse, even if the mouse button is pressed. This is intentional so that the marker can be moved longer distances than the mouse can move. Moving the mouse to the right of the graph, the marker can only be moved to the right - moving back the mouse will not move the marker back until the mouse enters the graph area again. Similarly for the left side. Above or below the graph, the mouse will not move the marker at all but will show a circle to indicate that the mouse may be \'recirculated\' to move back into the graph. \\n"\np217\naI3\naS\'Table Pane\\n\'\np218\naI10\naS\'This pane shows a table based on the configuration set in the Table menu. The sample number and time stamp show in the header. \\n\'\np219\nasb.'

3,151.4

14,624

0.727296

2,947

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0.123004

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15,757

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null

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5

bcd4d0f4e63aaadd90ad4f85aee28cffb52c6ada

150

py

Python

io-cesium-ion/operators/__init__.py

AnalyticalGraphicsInc/ion-blender-exporter

7326dd24bed76baeb9894aa29282fa51ee4f6d38

[ "Apache-2.0" ]

6

2020-06-25T11:47:57.000Z

2022-02-02T01:33:51.000Z

io-cesium-ion/operators/__init__.py

CesiumGS/cesium-ion-blender-addon

7326dd24bed76baeb9894aa29282fa51ee4f6d38

[ "Apache-2.0" ]

8

2019-05-29T13:16:09.000Z

2019-06-25T18:46:18.000Z

io-cesium-ion/operators/__init__.py

AnalyticalGraphicsInc/ion-blender-exporter

7326dd24bed76baeb9894aa29282fa51ee4f6d38

[ "Apache-2.0" ]

2

2019-07-16T07:56:34.000Z

2019-10-23T08:20:44.000Z

from .token import (GetTokenOperator, ClearTokenOperator) from .oauth import OAuthOperator from .upload import ExportUploadOperator, ProgressOperator

37.5

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0

5

4c01d71b16727db2c965b3f09775417a67ad7634

2,343

py

Python

wepppy/nodb/mods/locations/lt/selectors/__init__.py

hwbeeson/wepppy

6358552df99853c75be8911e7ef943108ae6923e

[ "BSD-3-Clause" ]

null

wepppy/nodb/mods/locations/lt/selectors/__init__.py

hwbeeson/wepppy

6358552df99853c75be8911e7ef943108ae6923e

[ "BSD-3-Clause" ]

null

wepppy/nodb/mods/locations/lt/selectors/__init__.py

hwbeeson/wepppy

6358552df99853c75be8911e7ef943108ae6923e

[ "BSD-3-Clause" ]

null

def all_hillslopes(landuse, soils): return list(landuse.domlc_d.keys()) def _identify_outcrop_mukeys(soils): outcrop_mukeys = [] _soils = soils.subs_summary for top in _soils: desc = _soils[top]['desc'].lower() if 'melody-rock outcrop' in desc or 'ellispeak-rock outcrop' in desc: mukey = str(_soils[top]['mukey']) outcrop_mukeys.append(mukey) return outcrop_mukeys def bare_or_sodgrass_or_bunchgrass_selector(landuse, soils): domlc_d = landuse.domlc_d topaz_ids = [] for top in domlc_d: if domlc_d[top] in ['100', '101', '103']: topaz_ids.append(top) return topaz_ids def not_shrub_and_not_outcrop_selector(landuse, soils): domlc_d = landuse.domlc_d domsoil_d = soils.domsoil_d outcrop_mukeys = _identify_outcrop_mukeys(soils) topaz_ids = [] for top in domsoil_d: if str(domsoil_d[top]) not in outcrop_mukeys and domlc_d[top] != '104': topaz_ids.append(top) return topaz_ids def shrub_and_not_outcrop_selector(landuse, soils): domlc_d = landuse.domlc_d domsoil_d = soils.domsoil_d outcrop_mukeys = _identify_outcrop_mukeys(soils) topaz_ids = [] for top in domsoil_d: if str(domsoil_d[top]) not in outcrop_mukeys and domlc_d[top] == '104': topaz_ids.append(top) return topaz_ids def not_shrub_selector(landuse, soils): domlc_d = landuse.domlc_d topaz_ids = [] for top in domlc_d: if str(domlc_d[top]) != '104': topaz_ids.append(top) return topaz_ids def shrub_selector(landuse, soils): domlc_d = landuse.domlc_d topaz_ids = [] for top in domlc_d: if domlc_d[top] == '104': topaz_ids.append(top) return topaz_ids def outcrop_selector(landuse, soils): domsoil_d = soils.domsoil_d outcrop_mukeys = _identify_outcrop_mukeys(soils) topaz_ids = [] for top in domsoil_d: if domsoil_d[top] in outcrop_mukeys: topaz_ids.append(top) return topaz_ids def not_outcrop_selector(landuse, soils): domsoil_d = soils.domsoil_d outcrop_mukeys = _identify_outcrop_mukeys(soils) topaz_ids = [] for top in domsoil_d: if domsoil_d[top] not in outcrop_mukeys: topaz_ids.append(top) return topaz_ids

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2,343

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0.272727

0

null

0

1

0

null

0

5

4c1867059b33f1e1a63ceade160ac824779cd12f

14

py

Python

tests/__init__.py

OrtnerMichael/magPyLib

4c7e7f56f6e0b915ec0e024c172c460fa80126e5

[ "BSD-2-Clause" ]

null

tests/__init__.py

OrtnerMichael/magPyLib

4c7e7f56f6e0b915ec0e024c172c460fa80126e5

[ "BSD-2-Clause" ]

1

2019-06-05T19:04:26.000Z

2019-06-06T17:23:02.000Z

tests/__init__.py

OrtnerMichael/magPyLib

4c7e7f56f6e0b915ec0e024c172c460fa80126e5

[ "BSD-2-Clause" ]

2

2017-03-15T01:45:19.000Z

2017-10-30T13:26:35.000Z

""" tests """

7

13

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14

0.454545

0.357143

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1

null

true

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0

1

0

1

0

null

0

1

0

5

4c1b56281c919066ab5de3033752e934db4cf03d

5,052

py

Python

homebytwo/routes/migrations/0042_activity_performance.py

drixselecta/homebytwo

29d26ce9f5586943e3b64c95aa4ce9ea7263bd10

[ "MIT" ]

7

2018-03-10T20:58:59.000Z

2021-08-22T17:18:09.000Z

homebytwo/routes/migrations/0042_activity_performance.py

HomebyTwo/homebytwo

29d26ce9f5586943e3b64c95aa4ce9ea7263bd10

[ "MIT" ]

69

2017-02-01T21:15:43.000Z

2022-02-26T09:33:27.000Z

homebytwo/routes/migrations/0042_activity_performance.py

drixselecta/homebytwo

29d26ce9f5586943e3b64c95aa4ce9ea7263bd10

[ "MIT" ]

null

# Generated by Django 2.2.13 on 2020-07-02 08:00 import django.contrib.postgres.fields from django.db import migrations, models import homebytwo.routes.fields import homebytwo.routes.models.activity class Migration(migrations.Migration): dependencies = [ ("routes", "0041_activity_streams"), ] operations = [ migrations.RenameField( model_name="activity", old_name="totalup", new_name="total_elevation_gain", ), migrations.RemoveField(model_name="activityperformance", name="flat_param",), migrations.RemoveField(model_name="activityperformance", name="slope_param",), migrations.RemoveField( model_name="activityperformance", name="slope_squared_param", ), migrations.RemoveField( model_name="activityperformance", name="total_elevation_gain_param", ), migrations.RemoveField(model_name="activitytype", name="flat_param",), migrations.RemoveField(model_name="activitytype", name="slope_param",), migrations.RemoveField(model_name="activitytype", name="slope_squared_param",), migrations.RemoveField( model_name="activitytype", name="total_elevation_gain_param", ), migrations.AddField( model_name="activity", name="commute", field=models.BooleanField(default=False), ), migrations.AddField( model_name="activityperformance", name="cv_scores", field=homebytwo.routes.fields.NumpyArrayField( base_field=models.FloatField(), default=homebytwo.routes.models.activity.get_default_array, size=None, ), ), migrations.AddField( model_name="activityperformance", name="flat_parameter", field=models.FloatField(default=0.36), ), migrations.AddField( model_name="activityperformance", name="model_score", field=models.FloatField(default=0.0), ), migrations.AddField( model_name="activityperformance", name="regression_coefficients", field=homebytwo.routes.fields.NumpyArrayField( base_field=models.FloatField(), default=homebytwo.routes.models.activity.get_default_array, size=None, ), ), migrations.AddField( model_name="activityperformance", name="gear_categories", field=homebytwo.routes.fields.NumpyArrayField( base_field=models.CharField(max_length=50), default=homebytwo.routes.models.activity.get_default_category, size=None, ), ), migrations.AddField( model_name="activityperformance", name="workout_type_categories", field=homebytwo.routes.fields.NumpyArrayField( base_field=models.CharField(max_length=50), default=homebytwo.routes.models.activity.get_default_category, size=None, ), ), migrations.AddField( model_name="activitytype", name="gear_categories", field=homebytwo.routes.fields.NumpyArrayField( base_field=models.CharField(max_length=50), default=homebytwo.routes.models.activity.get_default_category, size=None, ), ), migrations.AddField( model_name="activitytype", name="workout_type_categories", field=homebytwo.routes.fields.NumpyArrayField( base_field=models.CharField(max_length=50), default=homebytwo.routes.models.activity.get_default_category, size=None, ), ), migrations.AddField( model_name="activitytype", name="flat_parameter", field=models.FloatField(default=0.36), ), migrations.AddField( model_name="activitytype", name="max_gradient", field=models.FloatField(default=100.0), ), migrations.AddField( model_name="activitytype", name="max_pace", field=models.FloatField(default=2.4), ), migrations.AddField( model_name="activitytype", name="min_gradient", field=models.FloatField(default=-100.0), ), migrations.AddField( model_name="activitytype", name="min_pace", field=models.FloatField(default=0.12), ), migrations.AddField( model_name="activitytype", name="regression_coefficients", field=homebytwo.routes.fields.NumpyArrayField( base_field=models.FloatField(), default=homebytwo.routes.models.activity.get_default_array, size=None, ), ), ]

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null

0

1

0

1

0

null

0

5

4c270e5d639bb7fb66446071cc39d32cf219dc39

22

py

Python

hello.py

fredyramix/profiles-rest-api

99681e6db15cf3cf661b5b6529e46dd3331a30af

[ "MIT" ]

null

hello.py

fredyramix/profiles-rest-api

99681e6db15cf3cf661b5b6529e46dd3331a30af

[ "MIT" ]

null

hello.py

fredyramix/profiles-rest-api

99681e6db15cf3cf661b5b6529e46dd3331a30af

[ "MIT" ]

null

print ('Hola mundo')

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1

22

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null

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1

0

null

0

1

0

1

0

5

4c31429b48117a5a027c809869276ce590e0c35a

100

py

Python

enthought/units/unit_manipulation.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

3

2016-12-09T06:05:18.000Z

2018-03-01T13:00:29.000Z

enthought/units/unit_manipulation.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

1

2020-12-02T00:51:32.000Z

2020-12-02T08:48:55.000Z

enthought/units/unit_manipulation.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

null

# proxy module from __future__ import absolute_import from scimath.units.unit_manipulation import *

25

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13

100

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0

0.11

100

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0

null

0

1

0

1

0

1

0

5

4c75990a6c182bf118e300d4d9403a81a80d9736

302

py

Python

my_velov_assistant/conftest.py

thefifthagreement/my-velov

6688d22fde510dc93c1064bfb15ab556bb2e1f76

[ "MIT" ]

1

2021-05-07T07:16:00.000Z

my_velov_assistant/conftest.py

thefifthagreement/my-velov

6688d22fde510dc93c1064bfb15ab556bb2e1f76

[ "MIT" ]

7

2021-05-12T05:42:23.000Z

2022-03-30T21:07:09.000Z

my_velov_assistant/conftest.py

thefifthagreement/my-velov

6688d22fde510dc93c1064bfb15ab556bb2e1f76

[ "MIT" ]

null

import pytest from my_velov_assistant.users.models import User from my_velov_assistant.users.tests.factories import UserFactory @pytest.fixture(autouse=True) def media_storage(settings, tmpdir): settings.MEDIA_ROOT = tmpdir.strpath @pytest.fixture def user() -> User: return UserFactory()

20.133333

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5.825

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0.094421

0.171674

0.214592

0

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302

14

65

21.571429

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0

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false

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0.666667

0

null

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1

0

null

0

1

0

1

0

5

d5b5afca7471a7c1c0480c6a1575ef4a167f02a5

51,942

py

Python

evap/results/tests/test_views.py

janno42/EvaP

3da854058cf5694d96bab2089f8dd6c48c7cfd4a

[ "MIT" ]

null

evap/results/tests/test_views.py

janno42/EvaP

3da854058cf5694d96bab2089f8dd6c48c7cfd4a

[ "MIT" ]

null

evap/results/tests/test_views.py

janno42/EvaP

3da854058cf5694d96bab2089f8dd6c48c7cfd4a

[ "MIT" ]

null

import random from io import StringIO from unittest.mock import patch from django.contrib.auth.models import Group from django.core.cache import caches from django.core.management import call_command from django.db import connection from django.test import override_settings from django.test.testcases import TestCase from django.test.utils import CaptureQueriesContext from django_webtest import WebTest from model_bakery import baker from evap.evaluation.models import ( Contribution, Course, Degree, Evaluation, Question, Questionnaire, Semester, UserProfile, ) from evap.evaluation.tests.tools import let_user_vote_for_evaluation, make_manager, make_rating_answer_counters from evap.results.exporters import TextAnswerExporter from evap.results.tools import cache_results from evap.results.views import get_evaluations_with_prefetched_data from evap.staff.tests.utils import WebTestStaffMode, helper_exit_staff_mode, run_in_staff_mode class TestResultsView(WebTest): url = "/results/" @patch("evap.evaluation.models.Evaluation.can_be_seen_by", new=(lambda self, user: True)) def test_multiple_evaluations_per_course(self): student = baker.make(UserProfile, email="student@institution.example.com") # course with no evaluations does not show up course = baker.make(Course) page = self.app.get(self.url, user=student) self.assertNotContains(page, course.name) caches["results"].clear() # course with one evaluation is a single line with the evaluation's full_name evaluation = baker.make( Evaluation, course=course, name_en="unique_evaluation_name1", name_de="foo", state=Evaluation.State.PUBLISHED, ) page = self.app.get(self.url, user=student) self.assertContains(page, evaluation.full_name) caches["results"].clear() # course with two evaluations is three lines without using the full names evaluation2 = baker.make( Evaluation, course=course, name_en="unique_evaluation_name2", name_de="bar", state=Evaluation.State.PUBLISHED, ) page = self.app.get(self.url, user=student) self.assertContains(page, course.name) self.assertContains(page, evaluation.name_en) self.assertContains(page, evaluation2.name_en) self.assertNotContains(page, evaluation.full_name) self.assertNotContains(page, evaluation2.full_name) caches["results"].clear() @patch("evap.evaluation.models.Evaluation.can_be_seen_by", new=(lambda self, user: True)) def test_order(self): student = baker.make(UserProfile, email="student@institution.example.com") course = baker.make(Course) evaluation1 = baker.make( Evaluation, name_de="random_evaluation_d", name_en="random_evaluation_a", course=course, state=Evaluation.State.PUBLISHED, ) evaluation2 = baker.make( Evaluation, name_de="random_evaluation_c", name_en="random_evaluation_b", course=course, state=Evaluation.State.PUBLISHED, ) page = self.app.get(self.url, user=student).body.decode() self.assertLess(page.index(evaluation1.name_en), page.index(evaluation2.name_en)) page = self.app.get(self.url, user=student, extra_environ={"HTTP_ACCEPT_LANGUAGE": "de"}).body.decode() self.assertGreater(page.index(evaluation1.name_de), page.index(evaluation2.name_de)) # using LocMemCache so the cache queries don't show up in the query count that's measured here @override_settings( CACHES={ "default": { "BACKEND": "django.core.cache.backends.locmem.LocMemCache", "LOCATION": "testing_cache_default", }, "sessions": { "BACKEND": "django.core.cache.backends.locmem.LocMemCache", "LOCATION": "testing_cache_results", }, "results": { "BACKEND": "django.core.cache.backends.locmem.LocMemCache", "LOCATION": "testing_cache_sessions", }, } ) @patch("evap.evaluation.models.Evaluation.can_be_seen_by", new=(lambda self, user: True)) def test_num_queries_is_constant(self): """ ensures that the number of queries in the user list is constant and not linear to the number of courses/evaluations """ student = baker.make(UserProfile, email="student@institution.example.com") # warm up some caches self.app.get(self.url, user=student) def make_course_with_evaluations(unique_suffix): course = baker.make(Course) baker.make( Evaluation, course=course, name_en="foo" + unique_suffix, name_de="foo" + unique_suffix, state=Evaluation.State.PUBLISHED, _voter_count=0, ) baker.make( Evaluation, course=course, name_en="bar" + unique_suffix, name_de="bar" + unique_suffix, state=Evaluation.State.PUBLISHED, _voter_count=0, ) # first measure the number of queries with two courses make_course_with_evaluations("frob") make_course_with_evaluations("spam") call_command("refresh_results_cache", stdout=StringIO()) with CaptureQueriesContext(connection) as context: self.app.get(self.url, user=student) num_queries_before = context.final_queries - context.initial_queries # then measure the number of queries with one more course and compare make_course_with_evaluations("eggs") call_command("refresh_results_cache", stdout=StringIO()) with CaptureQueriesContext(connection) as context: self.app.get(self.url, user=student) num_queries_after = context.final_queries - context.initial_queries self.assertEqual(num_queries_before, num_queries_after) # django does not clear the LocMemCache in between tests. clear it here just to be safe. caches["default"].clear() caches["sessions"].clear() caches["results"].clear() class TestGetEvaluationsWithPrefetchedData(TestCase): def test_returns_correct_participant_count(self): """Regression test for #1248""" participants = baker.make(UserProfile, _bulk_create=True, _quantity=2) evaluation = baker.make( Evaluation, state=Evaluation.State.PUBLISHED, _participant_count=2, _voter_count=2, participants=participants, voters=participants, ) cache_results(evaluation) participants[0].delete() evaluation = Evaluation.objects.get(pk=evaluation.pk) evaluations = get_evaluations_with_prefetched_data([evaluation]) self.assertEqual(evaluations[0].num_participants, 2) self.assertEqual(evaluations[0].num_voters, 2) evaluations = get_evaluations_with_prefetched_data(Evaluation.objects.filter(pk=evaluation.pk)) self.assertEqual(evaluations[0].num_participants, 2) self.assertEqual(evaluations[0].num_voters, 2) class TestResultsViewContributionWarning(WebTest): @classmethod def setUpTestData(cls): cls.manager = make_manager() cls.semester = baker.make(Semester, id=3) contributor = baker.make(UserProfile) # Set up an evaluation with one question but no answers student1 = baker.make(UserProfile) student2 = baker.make(UserProfile) cls.evaluation = baker.make( Evaluation, id=21, state=Evaluation.State.PUBLISHED, course=baker.make(Course, semester=cls.semester), participants=[student1, student2], voters=[student1, student2], ) questionnaire = baker.make(Questionnaire) cls.evaluation.general_contribution.questionnaires.set([questionnaire]) cls.contribution = baker.make( Contribution, evaluation=cls.evaluation, questionnaires=[questionnaire], contributor=contributor, ) cls.likert_question = baker.make(Question, type=Question.LIKERT, questionnaire=questionnaire, order=2) cls.url = "/results/semester/%s/evaluation/%s" % (cls.semester.id, cls.evaluation.id) def test_many_answers_evaluation_no_warning(self): make_rating_answer_counters(self.likert_question, self.contribution, [0, 0, 10, 0, 0]) cache_results(self.evaluation) page = self.app.get(self.url, user=self.manager, status=200) self.assertNotIn("Only a few participants answered these questions.", page) def test_zero_answers_evaluation_no_warning(self): cache_results(self.evaluation) page = self.app.get(self.url, user=self.manager, status=200) self.assertNotIn("Only a few participants answered these questions.", page) def test_few_answers_evaluation_show_warning(self): make_rating_answer_counters(self.likert_question, self.contribution, [0, 0, 3, 0, 0]) cache_results(self.evaluation) page = self.app.get(self.url, user=self.manager, status=200) self.assertIn("Only a few participants answered these questions.", page) class TestResultsSemesterEvaluationDetailView(WebTestStaffMode): url = "/results/semester/2/evaluation/21" @classmethod def setUpTestData(cls): cls.manager = make_manager() cls.semester = baker.make(Semester, id=2) contributor = baker.make(UserProfile, email="contributor@institution.example.com") responsible = baker.make(UserProfile, email="responsible@institution.example.com") cls.test_users = [cls.manager, contributor, responsible] # Normal evaluation with responsible and contributor. cls.evaluation = baker.make( Evaluation, id=21, state=Evaluation.State.PUBLISHED, course=baker.make(Course, semester=cls.semester) ) baker.make( Contribution, evaluation=cls.evaluation, contributor=responsible, role=Contribution.Role.EDITOR, textanswer_visibility=Contribution.TextAnswerVisibility.GENERAL_TEXTANSWERS, ) cls.contribution = baker.make( Contribution, evaluation=cls.evaluation, contributor=contributor, role=Contribution.Role.EDITOR, ) def test_questionnaire_ordering(self): top_questionnaire = baker.make(Questionnaire, type=Questionnaire.Type.TOP) contributor_questionnaire = baker.make(Questionnaire, type=Questionnaire.Type.CONTRIBUTOR) bottom_questionnaire = baker.make(Questionnaire, type=Questionnaire.Type.BOTTOM) top_heading_question = baker.make(Question, type=Question.HEADING, questionnaire=top_questionnaire, order=0) top_likert_question = baker.make(Question, type=Question.LIKERT, questionnaire=top_questionnaire, order=1) contributor_likert_question = baker.make( Question, type=Question.LIKERT, questionnaire=contributor_questionnaire ) bottom_heading_question = baker.make( Question, type=Question.HEADING, questionnaire=bottom_questionnaire, order=0 ) bottom_likert_question = baker.make(Question, type=Question.LIKERT, questionnaire=bottom_questionnaire, order=1) self.evaluation.general_contribution.questionnaires.set([top_questionnaire, bottom_questionnaire]) self.contribution.questionnaires.set([contributor_questionnaire]) make_rating_answer_counters(top_likert_question, self.evaluation.general_contribution) make_rating_answer_counters(contributor_likert_question, self.contribution) make_rating_answer_counters(bottom_likert_question, self.evaluation.general_contribution) cache_results(self.evaluation) content = self.app.get(self.url, user=self.manager).body.decode() top_heading_index = content.index(top_heading_question.text) top_likert_index = content.index(top_likert_question.text) contributor_likert_index = content.index(contributor_likert_question.text) bottom_heading_index = content.index(bottom_heading_question.text) bottom_likert_index = content.index(bottom_likert_question.text) self.assertTrue( top_heading_index < top_likert_index < contributor_likert_index < bottom_heading_index < bottom_likert_index ) def test_heading_question_filtering(self): contributor = baker.make(UserProfile) questionnaire = baker.make(Questionnaire) heading_question_0 = baker.make(Question, type=Question.HEADING, questionnaire=questionnaire, order=0) heading_question_1 = baker.make(Question, type=Question.HEADING, questionnaire=questionnaire, order=1) likert_question = baker.make(Question, type=Question.LIKERT, questionnaire=questionnaire, order=2) heading_question_2 = baker.make(Question, type=Question.HEADING, questionnaire=questionnaire, order=3) contribution = baker.make( Contribution, evaluation=self.evaluation, questionnaires=[questionnaire], contributor=contributor ) make_rating_answer_counters(likert_question, contribution) cache_results(self.evaluation) page = self.app.get(self.url, user=self.manager) self.assertNotIn(heading_question_0.text, page) self.assertIn(heading_question_1.text, page) self.assertIn(likert_question.text, page) self.assertNotIn(heading_question_2.text, page) def test_default_view_is_public(self): cache_results(self.evaluation) random.seed(42) # use explicit seed to always choose the same "random" slogan page_without_get_parameter = self.app.get(self.url, user=self.manager) random.seed(42) page_with_get_parameter = self.app.get(self.url + "?view=public", user=self.manager) random.seed(42) page_with_random_get_parameter = self.app.get(self.url + "?view=asdf", user=self.manager) self.assertEqual(page_without_get_parameter.body, page_with_get_parameter.body) self.assertEqual(page_without_get_parameter.body, page_with_random_get_parameter.body) def test_wrong_state(self): helper_exit_staff_mode(self) evaluation = baker.make( Evaluation, state=Evaluation.State.REVIEWED, course=baker.make(Course, semester=self.semester) ) cache_results(evaluation) url = "/results/semester/%s/evaluation/%s" % (self.semester.id, evaluation.id) self.app.get(url, user="student@institution.example.com", status=403) def test_preview_without_rating_answers(self): evaluation = baker.make( Evaluation, state=Evaluation.State.EVALUATED, course=baker.make(Course, semester=self.semester) ) cache_results(evaluation) url = f"/results/semester/{self.semester.id}/evaluation/{evaluation.id}" self.app.get(url, user=self.manager) def test_preview_with_rating_answers(self): evaluation = baker.make( Evaluation, state=Evaluation.State.EVALUATED, course=baker.make(Course, semester=self.semester) ) questionnaire = baker.make(Questionnaire, type=Questionnaire.Type.TOP) likert_question = baker.make(Question, type=Question.LIKERT, questionnaire=questionnaire, order=1) evaluation.general_contribution.questionnaires.set([questionnaire]) participants = baker.make(UserProfile, _bulk_create=True, _quantity=20) evaluation.participants.set(participants) evaluation.voters.set(participants) make_rating_answer_counters(likert_question, evaluation.general_contribution, [20, 0, 0, 0, 0]) cache_results(evaluation) url = f"/results/semester/{self.semester.id}/evaluation/{evaluation.id}" self.app.get(url, user=self.manager) class TestResultsSemesterEvaluationDetailViewFewVoters(WebTest): @classmethod def setUpTestData(cls): make_manager() cls.semester = baker.make(Semester, id=2) responsible = baker.make(UserProfile, email="responsible@institution.example.com") cls.student1 = baker.make(UserProfile, email="student1@institution.example.com") cls.student2 = baker.make(UserProfile, email="student2@example.com") students = baker.make(UserProfile, _bulk_create=True, _quantity=10) students.extend([cls.student1, cls.student2]) cls.evaluation = baker.make( Evaluation, id=22, state=Evaluation.State.IN_EVALUATION, course=baker.make(Course, semester=cls.semester), participants=students, ) questionnaire = baker.make(Questionnaire) cls.question_grade = baker.make(Question, questionnaire=questionnaire, type=Question.GRADE) baker.make(Question, questionnaire=questionnaire, type=Question.LIKERT) cls.evaluation.general_contribution.questionnaires.set([questionnaire]) cls.responsible_contribution = baker.make( Contribution, contributor=responsible, evaluation=cls.evaluation, questionnaires=[questionnaire] ) def helper_test_answer_visibility_one_voter(self, user_email, expect_page_not_visible=False): page = self.app.get("/results/semester/2/evaluation/22", user=user_email, expect_errors=expect_page_not_visible) if expect_page_not_visible: self.assertEqual(page.status_code, 403) else: self.assertEqual(page.status_code, 200) number_of_grade_badges = str(page).count("badge-grade") self.assertEqual(number_of_grade_badges, 5) # 1 evaluation overview and 4 questions number_of_visible_grade_badges = str(page).count("background-color") self.assertEqual(number_of_visible_grade_badges, 0) number_of_disabled_grade_badges = str(page).count("badge-grade badge-disabled") self.assertEqual(number_of_disabled_grade_badges, 5) def helper_test_answer_visibility_two_voters(self, user_email): page = self.app.get("/results/semester/2/evaluation/22", user=user_email) number_of_grade_badges = str(page).count("badge-grade") self.assertEqual(number_of_grade_badges, 5) # 1 evaluation overview and 4 questions number_of_visible_grade_badges = str(page).count("background-color") self.assertEqual(number_of_visible_grade_badges, 4) # all but average grade in evaluation overview number_of_disabled_grade_badges = str(page).count("badge-grade badge-disabled") self.assertEqual(number_of_disabled_grade_badges, 1) def test_answer_visibility_one_voter(self): let_user_vote_for_evaluation(self.app, self.student1, self.evaluation) self.evaluation.end_evaluation() self.evaluation.end_review() self.evaluation.publish() self.evaluation.save() self.assertEqual(self.evaluation.voters.count(), 1) with run_in_staff_mode(self): self.helper_test_answer_visibility_one_voter("manager@institution.example.com") self.evaluation = Evaluation.objects.get(id=self.evaluation.id) self.helper_test_answer_visibility_one_voter("responsible@institution.example.com") self.helper_test_answer_visibility_one_voter("student@institution.example.com", expect_page_not_visible=True) def test_answer_visibility_two_voters(self): let_user_vote_for_evaluation(self.app, self.student1, self.evaluation) let_user_vote_for_evaluation(self.app, self.student2, self.evaluation) self.evaluation.end_evaluation() self.evaluation.end_review() self.evaluation.publish() self.evaluation.save() self.assertEqual(self.evaluation.voters.count(), 2) with run_in_staff_mode(self): self.helper_test_answer_visibility_two_voters("manager@institution.example.com") self.helper_test_answer_visibility_two_voters("responsible@institution.example.com") self.helper_test_answer_visibility_two_voters("student@institution.example.com") class TestResultsSemesterEvaluationDetailViewPrivateEvaluation(WebTest): @patch("evap.results.templatetags.results_templatetags.get_grade_color", new=lambda x: (0, 0, 0)) def test_private_evaluation(self): semester = baker.make(Semester) manager = make_manager() student = baker.make(UserProfile, email="student@institution.example.com") student_external = baker.make(UserProfile, email="student_external@example.com") contributor = baker.make(UserProfile, email="contributor@institution.example.com") responsible = baker.make(UserProfile, email="responsible@institution.example.com") editor = baker.make(UserProfile, email="editor@institution.example.com") voter1 = baker.make(UserProfile, email="voter1@institution.example.com") voter2 = baker.make(UserProfile, email="voter2@institution.example.com") non_participant = baker.make(UserProfile, email="non_participant@institution.example.com") degree = baker.make(Degree) course = baker.make( Course, semester=semester, degrees=[degree], is_private=True, responsibles=[responsible, editor] ) private_evaluation = baker.make( Evaluation, course=course, state=Evaluation.State.PUBLISHED, participants=[student, student_external, voter1, voter2], voters=[voter1, voter2], ) private_evaluation.general_contribution.questionnaires.set([baker.make(Questionnaire)]) baker.make( Contribution, evaluation=private_evaluation, contributor=editor, role=Contribution.Role.EDITOR, textanswer_visibility=Contribution.TextAnswerVisibility.GENERAL_TEXTANSWERS, ) baker.make(Contribution, evaluation=private_evaluation, contributor=contributor, role=Contribution.Role.EDITOR) cache_results(private_evaluation) url = "/results/" self.assertNotIn(private_evaluation.full_name, self.app.get(url, user=non_participant)) self.assertIn(private_evaluation.full_name, self.app.get(url, user=student)) self.assertIn(private_evaluation.full_name, self.app.get(url, user=responsible)) self.assertIn(private_evaluation.full_name, self.app.get(url, user=editor)) self.assertIn(private_evaluation.full_name, self.app.get(url, user=contributor)) with run_in_staff_mode(self): self.assertIn(private_evaluation.full_name, self.app.get(url, user=manager)) self.app.get(url, user=student_external, status=403) # external users can't see results semester view url = "/results/semester/%s/evaluation/%s" % (semester.id, private_evaluation.id) self.app.get(url, user=non_participant, status=403) self.app.get(url, user=student, status=200) self.app.get(url, user=responsible, status=200) self.app.get(url, user=editor, status=200) self.app.get(url, user=contributor, status=200) with run_in_staff_mode(self): self.app.get(url, user=manager, status=200) # this external user participates in the evaluation and can see the results self.app.get(url, user=student_external, status=200) class TestResultsTextanswerVisibilityForManager(WebTestStaffMode): fixtures = ["minimal_test_data_results"] @classmethod def setUpTestData(cls): cls.manager = make_manager() cache_results(Evaluation.objects.get(id=1)) def test_textanswer_visibility_for_manager_before_publish(self): evaluation = Evaluation.objects.get(id=1) evaluation._voter_count = 0 # set these to 0 to make unpublishing work evaluation._participant_count = 0 evaluation.unpublish() evaluation.save() page = self.app.get("/results/semester/1/evaluation/1?view=full", user=self.manager) self.assertIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertIn(".general_additional_orig_published.", page) self.assertNotIn(".general_additional_orig_hidden.", page) self.assertIn(".general_changed_published.", page) self.assertIn(".contributor_orig_published.", page) self.assertIn(".contributor_orig_private.", page) self.assertIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertIn(".responsible_contributor_changed_published.", page) self.assertIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) self.assertIn(".responsible_contributor_additional_orig_published.", page) self.assertNotIn(".responsible_contributor_additional_orig_hidden.", page) def test_textanswer_visibility_for_manager(self): page = self.app.get("/results/semester/1/evaluation/1?view=full", user=self.manager) self.assertIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertIn(".general_additional_orig_published.", page) self.assertNotIn(".general_additional_orig_hidden.", page) self.assertIn(".general_changed_published.", page) self.assertIn(".contributor_orig_published.", page) self.assertIn(".contributor_orig_private.", page) self.assertIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertIn(".responsible_contributor_changed_published.", page) self.assertIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) self.assertIn(".responsible_contributor_additional_orig_published.", page) self.assertNotIn(".responsible_contributor_additional_orig_hidden.", page) class TestResultsTextanswerVisibility(WebTest): fixtures = ["minimal_test_data_results"] @classmethod def setUpTestData(cls): cache_results(Evaluation.objects.get(id=1)) def test_textanswer_visibility_for_responsible(self): page = self.app.get("/results/semester/1/evaluation/1", user="responsible@institution.example.com") self.assertIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertIn(".general_additional_orig_published.", page) self.assertNotIn(".general_additional_orig_hidden.", page) self.assertIn(".general_changed_published.", page) self.assertNotIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) self.assertNotIn(".responsible_contributor_additional_orig_published.", page) self.assertNotIn(".responsible_contributor_additional_orig_hidden.", page) def test_textanswer_visibility_for_responsible_contributor(self): page = self.app.get("/results/semester/1/evaluation/1", user="responsible_contributor@institution.example.com") self.assertIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertIn(".general_additional_orig_published.", page) self.assertNotIn(".general_additional_orig_hidden.", page) self.assertIn(".general_changed_published.", page) self.assertNotIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertIn(".responsible_contributor_changed_published.", page) self.assertIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) self.assertIn(".responsible_contributor_additional_orig_published.", page) self.assertNotIn(".responsible_contributor_additional_orig_hidden.", page) def test_textanswer_visibility_for_delegate_for_responsible(self): page = self.app.get("/results/semester/1/evaluation/1", user="delegate_for_responsible@institution.example.com") self.assertIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertIn(".general_additional_orig_published.", page) self.assertNotIn(".general_additional_orig_hidden.", page) self.assertIn(".general_changed_published.", page) self.assertNotIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) self.assertNotIn(".responsible_contributor_additional_orig_published.", page) self.assertNotIn(".responsible_contributor_additional_orig_hidden.", page) def test_textanswer_visibility_for_contributor(self): page = self.app.get("/results/semester/1/evaluation/1", user="contributor@institution.example.com") self.assertNotIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertNotIn(".general_additional_orig_published.", page) self.assertNotIn(".general_additional_orig_hidden.", page) self.assertNotIn(".general_changed_published.", page) self.assertIn(".contributor_orig_published.", page) self.assertIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) self.assertNotIn(".responsible_contributor_additional_orig_published.", page) self.assertNotIn(".responsible_contributor_additional_orig_hidden.", page) def test_textanswer_visibility_for_delegate_for_contributor(self): page = self.app.get("/results/semester/1/evaluation/1", user="delegate_for_contributor@institution.example.com") self.assertNotIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertNotIn(".general_additional_orig_published.", page) self.assertNotIn(".general_additional_orig_hidden.", page) self.assertNotIn(".general_changed_published.", page) self.assertIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) self.assertNotIn(".responsible_contributor_additional_orig_published.", page) self.assertNotIn(".responsible_contributor_additional_orig_hidden.", page) def test_textanswer_visibility_for_contributor_general_textanswers(self): page = self.app.get( "/results/semester/1/evaluation/1", user="contributor_general_textanswers@institution.example.com" ) self.assertIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertIn(".general_additional_orig_published.", page) self.assertNotIn(".general_additional_orig_hidden.", page) self.assertIn(".general_changed_published.", page) self.assertNotIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) self.assertNotIn(".responsible_contributor_additional_orig_published.", page) self.assertNotIn(".responsible_contributor_additional_orig_hidden.", page) def test_textanswer_visibility_for_student(self): page = self.app.get("/results/semester/1/evaluation/1", user="student@institution.example.com") self.assertNotIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertNotIn(".general_additional_orig_published.", page) self.assertNotIn(".general_additional_orig_hidden.", page) self.assertNotIn(".general_changed_published.", page) self.assertNotIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) self.assertNotIn(".responsible_contributor_additional_orig_published.", page) self.assertNotIn(".responsible_contributor_additional_orig_hidden.", page) def test_textanswer_visibility_for_student_external(self): # the external user does not participate in or contribute to the evaluation and therefore can't see the results self.app.get("/results/semester/1/evaluation/1", user="student_external@example.com", status=403) def test_textanswer_visibility_info_is_shown(self): page = self.app.get("/results/semester/1/evaluation/1", user="contributor@institution.example.com") self.assertRegex(page.body.decode(), r"can be seen by:<br />\s*contributor user") def test_textanswer_visibility_info_for_proxy_user(self): page = self.app.get("/results/semester/1/evaluation/1", user="responsible@institution.example.com") self.assertIn("responsible_contributor user (1 person)", page) class TestResultsOtherContributorsListOnExportView(WebTest): @classmethod def setUpTestData(cls): cls.semester = baker.make(Semester, id=2) responsible = baker.make(UserProfile, email="responsible@institution.example.com") cls.evaluation = baker.make( Evaluation, id=21, state=Evaluation.State.PUBLISHED, course=baker.make(Course, semester=cls.semester, responsibles=[responsible]), ) questionnaire = baker.make(Questionnaire) baker.make(Question, questionnaire=questionnaire, type=Question.LIKERT) cls.evaluation.general_contribution.questionnaires.set([questionnaire]) baker.make( Contribution, evaluation=cls.evaluation, contributor=responsible, questionnaires=[questionnaire], role=Contribution.Role.EDITOR, textanswer_visibility=Contribution.TextAnswerVisibility.GENERAL_TEXTANSWERS, ) cls.other_contributor_1 = baker.make(UserProfile, email="other_contributor_1@institution.example.com") baker.make( Contribution, evaluation=cls.evaluation, contributor=cls.other_contributor_1, questionnaires=[questionnaire], textanswer_visibility=Contribution.TextAnswerVisibility.OWN_TEXTANSWERS, ) cls.other_contributor_2 = baker.make(UserProfile, email="other_contributor_2@institution.example.com") baker.make( Contribution, evaluation=cls.evaluation, contributor=cls.other_contributor_2, questionnaires=[questionnaire], textanswer_visibility=Contribution.TextAnswerVisibility.OWN_TEXTANSWERS, ) cache_results(cls.evaluation) def test_contributor_list(self): url = "/results/semester/{}/evaluation/{}?view=export".format(self.semester.id, self.evaluation.id) page = self.app.get(url, user="responsible@institution.example.com") self.assertIn("<li>{}</li>".format(self.other_contributor_1.full_name), page) self.assertIn("<li>{}</li>".format(self.other_contributor_2.full_name), page) class TestResultsTextanswerVisibilityForExportView(WebTest): fixtures = ["minimal_test_data_results"] @classmethod def setUpTestData(cls): cls.manager = make_manager() cache_results(Evaluation.objects.get(id=1)) def test_textanswer_visibility_for_responsible(self): page = self.app.get("/results/semester/1/evaluation/1?view=export", user="responsible@institution.example.com") self.assertIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertIn(".general_changed_published.", page) self.assertNotIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) def test_textanswer_visibility_for_responsible_contributor(self): page = self.app.get( "/results/semester/1/evaluation/1?view=export", user="responsible_contributor@institution.example.com" ) self.assertIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertIn(".general_changed_published.", page) self.assertNotIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) def test_textanswer_visibility_for_contributor(self): page = self.app.get("/results/semester/1/evaluation/1?view=export", user="contributor@institution.example.com") self.assertNotIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertNotIn(".general_changed_published.", page) self.assertIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) def test_textanswer_visibility_for_contributor_general_textanswers(self): page = self.app.get( "/results/semester/1/evaluation/1?view=export", user="contributor_general_textanswers@institution.example.com", ) self.assertIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertIn(".general_changed_published.", page) self.assertNotIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) def test_textanswer_visibility_for_student(self): page = self.app.get("/results/semester/1/evaluation/1?view=export", user="student@institution.example.com") self.assertNotIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertNotIn(".general_changed_published.", page) self.assertNotIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) def test_textanswer_visibility_for_manager(self): with run_in_staff_mode(self): contributor_id = UserProfile.objects.get(email="responsible@institution.example.com").id page = self.app.get( "/results/semester/1/evaluation/1?view=export&contributor_id={}".format(contributor_id), user="manager@institution.example.com", ) self.assertIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertIn(".general_changed_published.", page) self.assertNotIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) def test_textanswer_visibility_for_manager_contributor(self): manager_group = Group.objects.get(name="Manager") contributor = UserProfile.objects.get(email="contributor@institution.example.com") contributor.groups.add(manager_group) page = self.app.get( "/results/semester/1/evaluation/1?view=export&contributor_id={}".format(contributor.id), user="contributor@institution.example.com", ) self.assertNotIn(".general_orig_published.", page) self.assertNotIn(".general_orig_hidden.", page) self.assertNotIn(".general_orig_published_changed.", page) self.assertNotIn(".general_changed_published.", page) self.assertIn(".contributor_orig_published.", page) self.assertNotIn(".contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_published.", page) self.assertNotIn(".responsible_contributor_orig_hidden.", page) self.assertNotIn(".responsible_contributor_orig_published_changed.", page) self.assertNotIn(".responsible_contributor_changed_published.", page) self.assertNotIn(".responsible_contributor_orig_private.", page) self.assertNotIn(".responsible_contributor_orig_notreviewed.", page) class TestArchivedResults(WebTest): @classmethod def setUpTestData(cls): cls.semester = baker.make(Semester) cls.manager = make_manager() cls.reviewer = baker.make( UserProfile, email="reviewer@institution.example.com", groups=[Group.objects.get(name="Reviewer")] ) cls.student = baker.make(UserProfile, email="student@institution.example.com") cls.student_external = baker.make(UserProfile, email="student_external@example.com") cls.contributor = baker.make(UserProfile, email="contributor@institution.example.com") cls.responsible = baker.make(UserProfile, email="responsible@institution.example.com") course = baker.make(Course, semester=cls.semester, degrees=[baker.make(Degree)], responsibles=[cls.responsible]) cls.evaluation = baker.make( Evaluation, course=course, state=Evaluation.State.PUBLISHED, participants=[cls.student, cls.student_external], voters=[cls.student, cls.student_external], ) cls.evaluation.general_contribution.questionnaires.set([baker.make(Questionnaire)]) baker.make( Contribution, evaluation=cls.evaluation, contributor=cls.responsible, role=Contribution.Role.EDITOR, textanswer_visibility=Contribution.TextAnswerVisibility.GENERAL_TEXTANSWERS, ) baker.make(Contribution, evaluation=cls.evaluation, contributor=cls.contributor) cache_results(cls.evaluation) @patch("evap.results.templatetags.results_templatetags.get_grade_color", new=lambda x: (0, 0, 0)) def test_unarchived_results(self): url = "/results/" self.assertIn(self.evaluation.full_name, self.app.get(url, user=self.student)) self.assertIn(self.evaluation.full_name, self.app.get(url, user=self.responsible)) self.assertIn(self.evaluation.full_name, self.app.get(url, user=self.contributor)) self.assertIn(self.evaluation.full_name, self.app.get(url, user=self.manager)) self.assertIn(self.evaluation.full_name, self.app.get(url, user=self.reviewer)) self.app.get(url, user=self.student_external, status=403) # external users can't see results semester view url = "/results/semester/%s/evaluation/%s" % (self.semester.id, self.evaluation.id) self.app.get(url, user=self.student, status=200) self.app.get(url, user=self.responsible, status=200) self.app.get(url, user=self.contributor, status=200) self.app.get(url, user=self.manager, status=200) self.app.get(url, user=self.reviewer, status=200) self.app.get(url, user=self.student_external, status=200) def test_archived_results(self): self.semester.archive_results() url = "/results/semester/%s/evaluation/%s" % (self.semester.id, self.evaluation.id) self.app.get(url, user=self.student, status=403) self.app.get(url, user=self.responsible, status=200) self.app.get(url, user=self.contributor, status=200) with run_in_staff_mode(self): self.app.get(url, user=self.manager, status=200) self.app.get(url, user=self.reviewer, status=403) self.app.get(url, user=self.student_external, status=403) class TestTextAnswerExportView(WebTest): @classmethod def setUpTestData(cls): cls.reviewer = baker.make( UserProfile, email="reviewer@institution.example.com", groups=[Group.objects.get(name="Reviewer")], ) evaluation = baker.make(Evaluation, state=Evaluation.State.PUBLISHED) cache_results(evaluation) cls.url = f"/results/evaluation/{evaluation.id}/text_answers_export" def test_file_sent(self): def mock(_self, res): res.write(b"1337") with patch.object(TextAnswerExporter, "export", mock): with run_in_staff_mode(self): response = self.app.get(self.url, user=self.reviewer, status=200) self.assertEqual(response.headers["Content-Type"], "application/vnd.ms-excel") self.assertEqual(response.content, b"1337") @patch("evap.results.exporters.TextAnswerExporter.export") def test_permission_denied(self, export_method): manager = make_manager() student = baker.make(UserProfile, email="student@institution.example.com") self.app.get(self.url, user=student, status=403) export_method.assert_not_called() with run_in_staff_mode(self): self.app.get(self.url, user=self.reviewer, status=200) export_method.assert_called_once() export_method.reset_mock() with run_in_staff_mode(self): self.app.get(self.url, user=manager, status=200) export_method.assert_called_once()

51.478692

120

0.707789

5,649

51,942

6.265534

0.066029

0.055603

0.093406

0.08476

0.800559

0.770498

0.739278

0.708708

0.665565

0.627762

0

0.006901

0.185438

51,942

1,008

121

51.529762

0.829638

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0.583333

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0.232845

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0

null

0

1

0

1

0

null

0

5

d5c4ee0e7a5c52b43965785c5fc09749edcb44e9

21

py

Python

logparser/LogSig/__init__.py

tyronevb/logparser

3dcd1e1892fb65c344f3b5010298e3dfd88f33ed

[ "MIT" ]

2

2021-05-24T06:56:46.000Z

2021-05-24T06:56:48.000Z

logparser/LogSig/__init__.py

tyronevb/logparser

3dcd1e1892fb65c344f3b5010298e3dfd88f33ed

[ "MIT" ]

null

logparser/LogSig/__init__.py

tyronevb/logparser

3dcd1e1892fb65c344f3b5010298e3dfd88f33ed

[ "MIT" ]

1

2022-01-20T11:01:43.000Z

from .LogSig import *

21

0.761905

3

21

5.333333

1

0

0.142857

21

1

21

0.888889

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

d5e7aac51158290e5d848f9d68bdcfa7f99bc080

56

py

Python

pytorch_widedeep/models/image/__init__.py

TangleSpace/pytorch-widedeep

ccc55a15c1b3205ffc8c054abc5cd25cba9ccdff

[ "MIT" ]

null

pytorch_widedeep/models/image/__init__.py

TangleSpace/pytorch-widedeep

ccc55a15c1b3205ffc8c054abc5cd25cba9ccdff

[ "MIT" ]

null

pytorch_widedeep/models/image/__init__.py

TangleSpace/pytorch-widedeep

ccc55a15c1b3205ffc8c054abc5cd25cba9ccdff

[ "MIT" ]

null

from pytorch_widedeep.models.image.vision import Vision

28

55

0.875

8

56

6

0.875

0

0.071429

56

1

56

0.923077

0

1

0

true

0

1

0

1

0

1

0

null

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1

0

null

0

1

0

1

0

1

0

5

e68ca684b012b77a625308c02cf9fa153f8c823b

33

py

Python

hello.py

WeiLiqiang/python

c454d1e6627c746c2b024f66232a39ba0fc68b36

[ "Apache-2.0" ]

1

2017-11-02T03:56:40.000Z

hello.py

WeiLiqiang/python

c454d1e6627c746c2b024f66232a39ba0fc68b36

[ "Apache-2.0" ]

null

hello.py

WeiLiqiang/python

c454d1e6627c746c2b024f66232a39ba0fc68b36

[ "Apache-2.0" ]

null

# coding: UTF-8 print "你好，python"

16.5

17

0.69697

6

33

3.833333

1

0

0.034483

0.121212

33

2

17

16.5

0.758621

0.393939

0

0.473684

0

null

0

null

1

0

null

0

1

0

null

0

1

0

1

0

5

e69886d879941349151aa229f403a732b6ce8d98

273

py

Python

src/sage/combinat/integer_lists/__init__.py

fredstro/sage

c936d2cda81ec7ec3552a3bdb29c994b40d1bb24

[ "BSL-1.0" ]

null

src/sage/combinat/integer_lists/__init__.py

fredstro/sage

c936d2cda81ec7ec3552a3bdb29c994b40d1bb24

[ "BSL-1.0" ]

null

src/sage/combinat/integer_lists/__init__.py

fredstro/sage

c936d2cda81ec7ec3552a3bdb29c994b40d1bb24

[ "BSL-1.0" ]

null

from base import IntegerListsBackend, Envelope from lists import IntegerLists from invlex import IntegerListsLex from sage.structure.sage_object import register_unpickle_override register_unpickle_override('sage.combinat.integer_list', 'IntegerListsLex', IntegerListsLex)

39

92

0.875458

31

273

7.516129

0.580645

0.137339

0.206009

0

0.076923

273

6

93

45.5

0.924603

0

0.150183

0.095238

0

1

0

true

0

0.8

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0.8

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null

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1

0

null

0

1

0

1

0

1

0

5

e6a34c66efccf6675769cab3a5003b25eb856ed3

335

py

Python

src/falcon_oas/__init__.py

sisp/falcon-oas

fc135f72d27b4eba32b1b80d0486d5fb474a5ddc

[ "Apache-2.0" ]

6

2019-02-15T11:09:53.000Z

2021-06-09T16:06:56.000Z

src/falcon_oas/__init__.py

sisp/falcon-oas

fc135f72d27b4eba32b1b80d0486d5fb474a5ddc

[ "Apache-2.0" ]

35

2019-04-01T04:09:00.000Z

2021-04-20T17:40:54.000Z

src/falcon_oas/__init__.py

sisp/falcon-oas

fc135f72d27b4eba32b1b80d0486d5fb474a5ddc

[ "Apache-2.0" ]

5

2019-04-16T16:04:49.000Z

2021-12-10T07:35:38.000Z

from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals from .__version__ import __version__ # noqa: F401 from .factories import OAS # noqa: F401 from .middlewares import Middleware # noqa: F401 from .request import Request # noqa: F401

33.5

50

0.81791

43

335

5.744186

0.395349

0.161943

0.259109

0

0.041958

0.146269

335

9

51

37.222222

0.821678

0.128358

0

1

0

true

0

1

0

1

0.125

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

5

e6ad4dcaa4d311679ae98438e96e7d50fe916cb2

21,252

py

Python

k2/python/k2/autograd.py

freewym/k2

67c4328be96b65249b5adf690a24999f4bbb4b97

[ "MIT" ]

null

k2/python/k2/autograd.py

freewym/k2

67c4328be96b65249b5adf690a24999f4bbb4b97

[ "MIT" ]

null

k2/python/k2/autograd.py

freewym/k2

67c4328be96b65249b5adf690a24999f4bbb4b97

[ "MIT" ]

null

# Copyright (c) 2020 Mobvoi Inc. (authors: Fangjun Kuang) # See ../../../LICENSE for clarification regarding multiple authors from typing import List, Tuple import torch import _k2 from .fsa import Fsa from .dense_fsa_vec import DenseFsaVec class _GetTotScoresFunction(torch.autograd.Function): @staticmethod def forward(ctx, fsas: Fsa, log_semiring: bool, use_float_scores: bool, unused_scores: torch.Tensor) -> torch.Tensor: '''Compute the total loglikes of an FsaVec. Args: fsas: The input FsaVec. log_semiring: True to use log semiring. False to use tropical semiring. use_float_scores: True to use float, i.e., single precision floating point, to compute log likes. False to use double precision. unused_scores: It is used only for backward propagation purpose. It equals to `fsas.scores`. Returns: The forward loglike contained in a 1-D tensor. If `use_float_scores==True`, its dtype is `torch.float32`; it is `torch.float64` otherwise. ''' # the .detach() below avoids a reference cycle; if we didn't do that, # the backward_fn of tot_scores would be set to this object, giving # `fsas` a reference to this object, which also has a reference # to `fsas`. if log_semiring is False: tot_scores = fsas.get_tot_scores_tropical( use_float_scores).detach() else: tot_scores = fsas.get_tot_scores_log(use_float_scores).detach() # NOTE: since `fsas`, `log_semiring` and `use_float_scores` are # not tensors, they are saved as attributes of `ctx`. ctx.fsas = fsas ctx.log_semiring = log_semiring ctx.use_float_scores = use_float_scores ctx.save_for_backward(unused_scores) return tot_scores @staticmethod def backward(ctx, tot_scores_grad: torch.Tensor ) -> Tuple[None, None, None, torch.Tensor]: # noqa fsas = ctx.fsas log_semiring = ctx.log_semiring use_float_scores = ctx.use_float_scores scores, = ctx.saved_tensors if log_semiring is False: entering_arcs = fsas.get_entering_arcs(use_float_scores) _, ragged_int = _k2.shortest_path(fsas.arcs, entering_arcs) if use_float_scores: out_grad = _k2._get_tot_scores_float_tropical_backward( fsas.arcs, ragged_int, tot_scores_grad) else: out_grad = _k2._get_tot_scores_double_tropical_backward( fsas.arcs, ragged_int, tot_scores_grad) # We return four values since the `forward` method accepts four # arguments (excluding ctx). # fsas, log_semiring, use_float_scores, unused_scores return None, None, None, out_grad else: forward_scores = fsas.get_forward_scores_log(use_float_scores) backward_scores = fsas.get_backward_scores_log(use_float_scores) if use_float_scores: func = _k2._get_arc_scores_float bprop_func = _k2._get_tot_scores_float_log_backward else: func = _k2._get_arc_scores_double bprop_func = _k2._get_tot_scores_double_log_backward arc_scores = func(fsas=fsas.arcs, forward_scores=forward_scores, backward_scores=backward_scores) out_grad = bprop_func(fsas.arcs, arc_scores, tot_scores_grad) return None, None, None, out_grad class _IntersectDensePrunedFunction(torch.autograd.Function): @staticmethod def forward(ctx, a_fsas: Fsa, b_fsas: DenseFsaVec, out_fsa: List[Fsa], search_beam: float, output_beam: float, min_active_states: int, max_active_states: int, unused_scores_a: torch.Tensor, unused_scores_b: torch.Tensor) -> torch.Tensor: '''Intersect array of FSAs on CPU/GPU. Args: a_fsas: Input FsaVec, i.e., `decoding graphs`, one per sequence. It might just be a linear sequence of phones, or might be something more complicated. Must have either `a_fsas.shape[0] == b_fsas.dim0()`, or `a_fsas.shape[0] == 1` in which case the graph is shared. b_fsas: Input FSAs that correspond to neural network output. out_fsa: A list containing ONLY one entry which will be set to the generated FSA on return. We pass it as a list since the return value can only be types of torch.Tensor in the `forward` function. search_beam: Decoding beam, e.g. 20. Smaller is faster, larger is more exact (less pruning). This is the default value; it may be modified by `min_active_states` and `max_active_states`. output_beam: Pruning beam for the output of intersection (vs. best path); equivalent to kaldi's lattice-beam. E.g. 8. max_active_states: Maximum number of FSA states that are allowed to be active on any given frame for any given intersection/composition task. This is advisory, in that it will try not to exceed that but may not always succeed. You can use a very large number if no constraint is needed. min_active_states: Minimum number of FSA states that are allowed to be active on any given frame for any given intersection/composition task. This is advisory, in that it will try not to have fewer than this number active. Set it to zero if there is no constraint. unused_scores_a: It equals to `a_fsas.scores` and its sole purpose is for back propagation. unused_scores_b: It equals to `b_fsas.scores` and its sole purpose is for back propagation. Returns: Return `out_fsa[0].scores`. ''' assert len(out_fsa) == 1 ragged_arc, arc_map_a, arc_map_b = _k2.intersect_dense_pruned( a_fsas=a_fsas.arcs, b_fsas=b_fsas.dense_fsa_vec, search_beam=search_beam, output_beam=output_beam, min_active_states=min_active_states, max_active_states=max_active_states) out_fsa[0] = Fsa(ragged_arc) for name, a_value in a_fsas.named_tensor_attr(include_scores=False): value = _k2.index_select(a_value, arc_map_a) setattr(out_fsa[0], name, value) for name, a_value in a_fsas.named_non_tensor_attr(): setattr(out_fsa[0], name, a_value) ctx.arc_map_a = arc_map_a ctx.arc_map_b = arc_map_b ctx.save_for_backward(unused_scores_a, unused_scores_b) return out_fsa[0].scores @staticmethod def backward(ctx, out_fsa_grad: torch.Tensor) \ -> Tuple[None, None, None, None, None, None, None, torch.Tensor, torch.Tensor]: # noqa a_scores, b_scores = ctx.saved_tensors arc_map_a = ctx.arc_map_a arc_map_b = ctx.arc_map_b grad_a = torch.zeros(a_scores.size(0), dtype=torch.float32, device=a_scores.device, requires_grad=False) grad_b = torch.zeros( *b_scores.shape, dtype=torch.float32, device=b_scores.device, requires_grad=False).contiguous() # will use its `view()` later _k2.index_add(arc_map_a, out_fsa_grad, grad_a) _k2.index_add(arc_map_b, out_fsa_grad, grad_b.view(-1)) return None, None, None, None, None, None, None, grad_a, grad_b class _IntersectDenseFunction(torch.autograd.Function): @staticmethod def forward(ctx, a_fsas: Fsa, b_fsas: DenseFsaVec, out_fsa: List[Fsa], output_beam: float, unused_scores_a: torch.Tensor, unused_scores_b: torch.Tensor) -> torch.Tensor: '''Intersect array of FSAs on CPU/GPU. Args: a_fsas: Input FsaVec, i.e., `decoding graphs`, one per sequence. It might just be a linear sequence of phones, or might be something more complicated. Must have either `a_fsas.shape[0] == b_fsas.dim0()`, or `a_fsas.shape[0] == 1` in which case the graph is shared. b_fsas: Input FSAs that correspond to neural network output. out_fsa: A list containing ONLY one entry which will be set to the generated FSA on return. We pass it as a list since the return value can only be types of torch.Tensor in the `forward` function. search_beam: Decoding beam, e.g. 20. Smaller is faster, larger is more exact (less pruning). This is the default value; it may be modified by `min_active_states` and `max_active_states`. output_beam: Pruning beam for the output of intersection (vs. best path); equivalent to kaldi's lattice-beam. E.g. 8. max_active_states: Maximum number of FSA states that are allowed to be active on any given frame for any given intersection/composition task. This is advisory, in that it will try not to exceed that but may not always succeed. You can use a very large number if no constraint is needed. min_active_states: Minimum number of FSA states that are allowed to be active on any given frame for any given intersection/composition task. This is advisory, in that it will try not to have fewer than this number active. Set it to zero if there is no constraint. unused_scores_a: It equals to `a_fsas.scores` and its sole purpose is for back propagation. unused_scores_b: It equals to `b_fsas.scores` and its sole purpose is for back propagation. Returns: Return `out_fsa[0].scores`. ''' assert len(out_fsa) == 1 ragged_arc, arc_map_a, arc_map_b = _k2.intersect_dense( a_fsas=a_fsas.arcs, b_fsas=b_fsas.dense_fsa_vec, output_beam=output_beam) out_fsa[0] = Fsa(ragged_arc) for name, a_value in a_fsas.named_tensor_attr(include_scores=False): value = _k2.index_select(a_value, arc_map_a) setattr(out_fsa[0], name, value) for name, a_value in a_fsas.named_non_tensor_attr(): setattr(out_fsa[0], name, a_value) ctx.arc_map_a = arc_map_a ctx.arc_map_b = arc_map_b ctx.save_for_backward(unused_scores_a, unused_scores_b) return out_fsa[0].scores @staticmethod def backward(ctx, out_fsa_grad: torch.Tensor) \ -> Tuple[None, None, None, None, torch.Tensor, torch.Tensor]: # noqa a_scores, b_scores = ctx.saved_tensors arc_map_a = ctx.arc_map_a arc_map_b = ctx.arc_map_b grad_a = torch.zeros(a_scores.size(0), dtype=torch.float32, device=a_scores.device, requires_grad=False) grad_b = torch.zeros( *b_scores.shape, dtype=torch.float32, device=b_scores.device, requires_grad=False).contiguous() # will use its `view()` later _k2.index_add(arc_map_a, out_fsa_grad, grad_a) _k2.index_add(arc_map_b, out_fsa_grad, grad_b.view(-1)) return None, None, None, None, grad_a, grad_b class _IndexSelectFunction(torch.autograd.Function): @staticmethod def forward(ctx, src: torch.Tensor, index: torch.Tensor) -> torch.Tensor: '''Returns a new tensor which indexes the input tensor along dimension 0 using the entries in `index`. If the entry in `index` is -1, then the corresponding entry in the returned tensor is 0. Caution: `index.dtype == torch.int32` and `index.ndim == 1`. Args: src: The input tensor. Either 1-D or 2-D with dtype torch.int32 or torch.float32. index: 1-D tensor of dtype torch.int32 containing the indexes. If an entry is -1, the corresponding entry in the returned value is 0. The elements of `index` should be in the range `[-1..src.shape[0]-1]`. Returns: A tensor with shape (index.numel(), *src.shape[1:]) and dtype the same as `src`, e.g. if `src.ndim == 1`, ans.shape would be (index.shape[0],); if `src.ndim == 2`, ans.shape would be (index.shape[0], src.shape[1]). Will satisfy `ans[i] == src[index[i]]` if `src.ndim == 1`, or `ans[i,j] == src[index[i],j]` if `src.ndim == 2`, except for entries where `index[i] == -1` which will be zero. ''' ctx.save_for_backward(src, index) return _k2.index_select(src, index) @staticmethod def backward(ctx, out_grad) -> Tuple[torch.Tensor, None]: src, index = ctx.saved_tensors ans = torch.zeros(src.size(0), dtype=torch.float32, device=src.device, requires_grad=False) _k2.index_add(index, out_grad, ans) return ans, None class _UnionFunction(torch.autograd.Function): @staticmethod def forward(ctx, fsas: Fsa, out_fsa: List[Fsa], unused_fsas_scores: torch.Tensor) -> torch.Tensor: '''Compute the union of all fsas in a FsaVec. Args: fsas: The input FsaVec. Caution: We require that each fsa in the FsaVec is non-empty (i.e., with at least two states). out_fsa: A list containing one entry. Since this function can only return values of type `torch.Tensor`, we return the union result in the list. unused_fsas_scores: It is the same as `fsas.scores`, whose sole purpose is for autograd. It is not used in this function. ''' need_arc_map = True ragged_arc, arc_map = _k2.union(fsas.arcs, need_arc_map) out_fsa[0] = Fsa(ragged_arc) for name, value in fsas.named_tensor_attr(include_scores=False): value = _k2.index_select(value, arc_map) setattr(out_fsa[0], name, value) for name, value in fsas.named_non_tensor_attr(): setattr(out_fsa[0], name, value) ctx.arc_map = arc_map ctx.save_for_backward(unused_fsas_scores) return out_fsa[0].scores # the return value will be discarded @staticmethod def backward(ctx, out_fsa_grad: torch.Tensor ) -> Tuple[None, None, torch.Tensor]: # noqa arc_map = ctx.arc_map fsas_scores, = ctx.saved_tensors ans = torch.zeros(fsas_scores.size(0), dtype=torch.float32, device=fsas_scores.device, requires_grad=False) _k2.index_add(arc_map, out_fsa_grad, ans) return None, None, ans def get_tot_scores(fsas: Fsa, log_semiring: bool, use_float_scores: bool) -> torch.Tensor: '''Compute the total loglikes of an FsaVec. Args: fsas: The input FsaVec. log_semiring: True to use log semiring. False to use tropical semiring. use_float_scores: True to use float, i.e., single precision floating point, to compute log likes. False to use double precision. Returns: The forward loglike contained in a 1-D tensor. If `use_float_scores==True`, its dtype is `torch.float32`; it is `torch.float64` otherwise. ''' tot_scores = _GetTotScoresFunction.apply(fsas, log_semiring, use_float_scores, fsas.scores) return tot_scores def intersect_dense_pruned(a_fsas: Fsa, b_fsas: DenseFsaVec, search_beam: float, output_beam: float, min_active_states: int, max_active_states: int) -> Fsa: '''Intersect array of FSAs on CPU/GPU. Caution: `a_fsas` MUST be arc sorted. Args: a_fsas: Input FsaVec, i.e., `decoding graphs`, one per sequence. It might just be a linear sequence of phones, or might be something more complicated. Must have either `a_fsas.shape[0] == b_fsas.dim0()`, or `a_fsas.shape[0] == 1` in which case the graph is shared. b_fsas: Input FSAs that correspond to neural network output. search_beam: Decoding beam, e.g. 20. Smaller is faster, larger is more exact (less pruning). This is the default value; it may be modified by `min_active_states` and `max_active_states`. output_beam: Beam to prune output, similar to lattice-beam in Kaldi. Relative to best path of output. min_active_states: Minimum number of FSA states that are allowed to be active on any given frame for any given intersection/composition task. This is advisory, in that it will try not to have fewer than this number active. Set it to zero if there is no constraint. max_active_states: Maximum number of FSA states that are allowed to be active on any given frame for any given intersection/composition task. This is advisory, in that it will try not to exceed that but may not always succeed. You can use a very large number if no constraint is needed. Returns: The result of the intersection. ''' out_fsa = [0] # the following return value is discarded since it is already contained # in `out_fsa[0].scores` _IntersectDensePrunedFunction.apply(a_fsas, b_fsas, out_fsa, search_beam, output_beam, min_active_states, max_active_states, a_fsas.scores, b_fsas.scores) return out_fsa[0] def intersect_dense(a_fsas: Fsa, b_fsas: DenseFsaVec, output_beam: float) -> Fsa: '''Intersect array of FSAs on CPU/GPU. Caution: `a_fsas` MUST be arc sorted. Args: a_fsas: Input FsaVec, i.e., `decoding graphs`, one per sequence. It might just be a linear sequence of phones, or might be something more complicated. Must have either `a_fsas.shape[0] == b_fsas.dim0()`, or `a_fsas.shape[0] == 1` in which case the graph is shared. b_fsas: Input FSAs that correspond to neural network output. output_beam: Beam to prune output, similar to lattice-beam in Kaldi. Relative to best path of output. Returns: The result of the intersection (pruned to `output_beam`; this pruning is exact, it uses forward and backward scores. ''' out_fsa = [0] # the following return value is discarded since it is already contained # in `out_fsa[0].scores` _IntersectDenseFunction.apply(a_fsas, b_fsas, out_fsa, output_beam, a_fsas.scores, b_fsas.scores) return out_fsa[0] def index_select(src: torch.Tensor, index: torch.Tensor) -> torch.Tensor: '''Returns a new tensor which indexes the input tensor along dimension 0 using the entries in `index`. If the entry in `index` is -1, then the corresponding entry in the returned tensor is 0. Caution: `index.dtype == torch.int32` and `index.ndim == 1`. Args: src: The input tensor. Either 1-D or 2-D with dtype torch.int32 or torch.float32. index: 1-D tensor of dtype torch.int32 containing the indexes. If an entry is -1, the corresponding entry in the returned value is 0. The elements of `index` should be in the range `[-1..src.shape[0]-1]`. Returns: A tensor with shape (index.numel(), *src.shape[1:]) and dtype the same as `src`, e.g. if `src.ndim == 1`, ans.shape would be (index.shape[0],); if `src.ndim == 2`, ans.shape would be (index.shape[0], src.shape[1]). Will satisfy `ans[i] == src[index[i]]` if `src.ndim == 1`, or `ans[i,j] == src[index[i],j]` if `src.ndim == 2`, except for entries where `index[i] == -1` which will be zero. ''' ans = _IndexSelectFunction.apply(src, index) return ans def union(fsas: Fsa) -> Fsa: '''Compute the union of a FsaVec. Caution: We require that every fsa in fsas is non-empty, i.e., contains at least two states Args: fsas: A FsaVec. That is, len(fsas.shape) == 3. Returns: A single Fsa that is the union of the input fsas. ''' out_fsa = [0] # as a placeholder _UnionFunction.apply(fsas, out_fsa, fsas.scores) return out_fsa[0]

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py

Python

protocols/participant_1_0_3.py

Lucioric2000/GelReportModels

1704cdea3242d5b46c8b81ef46553ccae2799435

[ "Apache-2.0" ]

null

protocols/participant_1_0_3.py

Lucioric2000/GelReportModels

1704cdea3242d5b46c8b81ef46553ccae2799435

[ "Apache-2.0" ]

null

protocols/participant_1_0_3.py

Lucioric2000/GelReportModels

1704cdea3242d5b46c8b81ef46553ccae2799435

[ "Apache-2.0" ]

null

""" DO NOT EDIT THIS FILE!! This file is automatically generated by the process_schemas.py program in the scripts directory. It is not intended to be edited directly. If you need to update the GEL protocol classes, please run the script on the appropriate schema version. """ from protocols.protocol import ProtocolElement from protocols.protocol import SearchRequest from protocols.protocol import SearchResponse from protocols.protocol import avro_parse import avro.schema version = '1.0.3' class AdoptedStatus(object): """ adoptedin means adopted into the family adoptedout means child belonged to the family and was adopted out """ notadopted = "notadopted" adoptedin = "adoptedin" adoptedout = "adoptedout" def __hash__(self): return str(self).__hash__() class AffectionStatus(object): """ Affection Status """ UNAFFECTED = "UNAFFECTED" AFFECTED = "AFFECTED" UNCERTAIN = "UNCERTAIN" def __hash__(self): return str(self).__hash__() class AgeOfOnset(object): """ No documentation """ EMBRYONAL_ONSET = "EMBRYONAL_ONSET" FETAL_ONSET = "FETAL_ONSET" NEONATAL_ONSET = "NEONATAL_ONSET" INFANTILE_ONSET = "INFANTILE_ONSET" CHILDHOOD_ONSET = "CHILDHOOD_ONSET" JUVENILE_ONSET = "JUVENILE_ONSET" YOUNG_ADULT_ONSET = "YOUNG_ADULT_ONSET" LATE_ONSET = "LATE_ONSET" MIDDLE_AGE_ONSET = "MIDDLE_AGE_ONSET" def __hash__(self): return str(self).__hash__() class AnalysisPanel(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "AnalysisPanel", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "specificDisease", "type": "string"}, {"name": "panelName", "type": "string"}, {"name": "panelVersion", "type": ["null", "string"]}, {"name": "reviewOutcome", "type": "string"}, {"name": "multipleGeneticOrigins", "type": "string"}]} """ schema = avro_parse(_schemaSource) requiredFields = { "multipleGeneticOrigins", "panelName", "panelVersion", "reviewOutcome", "specificDisease", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'multipleGeneticOrigins', 'panelName', 'panelVersion', 'reviewOutcome', 'specificDisease' ] def __init__(self, **kwargs): self.multipleGeneticOrigins = kwargs.get( 'multipleGeneticOrigins', None) self.panelName = kwargs.get( 'panelName', None) self.panelVersion = kwargs.get( 'panelVersion', None) self.reviewOutcome = kwargs.get( 'reviewOutcome', None) self.specificDisease = kwargs.get( 'specificDisease', None) class Ancestries(ProtocolElement): """ Ancestries, defined as Ethnic category(ies) and Chi-square test """ _schemaSource = """ {"type": "record", "name": "Ancestries", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "mothersEthnicOrigin", "type": ["null", {"type": "enum", "name": "EthnicCategory", "doc": "", "symbols": ["D", "E", "F", "G", "A", "B", "C", "L", "M", "N", "H", "J", "K", "P", "S", "R", "Z"]}], "doc": ""}, {"name": "mothersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "fathersEthnicOrigin", "type": ["null", "EthnicCategory"], "doc": ""}, {"name": "fathersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "chiSquare1KGenomesPhase3Pop", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]}}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "chiSquare1KGenomesPhase3Pop", "fathersEthnicOrigin", "fathersOtherRelevantAncestry", "mothersEthnicOrigin", "mothersOtherRelevantAncestry", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'chiSquare1KGenomesPhase3Pop': ChiSquare1KGenomesPhase3Pop, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'chiSquare1KGenomesPhase3Pop': ChiSquare1KGenomesPhase3Pop, } return embeddedTypes[fieldName] __slots__ = [ 'chiSquare1KGenomesPhase3Pop', 'fathersEthnicOrigin', 'fathersOtherRelevantAncestry', 'mothersEthnicOrigin', 'mothersOtherRelevantAncestry' ] def __init__(self, **kwargs): self.chiSquare1KGenomesPhase3Pop = kwargs.get( 'chiSquare1KGenomesPhase3Pop', None) self.fathersEthnicOrigin = kwargs.get( 'fathersEthnicOrigin', None) self.fathersOtherRelevantAncestry = kwargs.get( 'fathersOtherRelevantAncestry', None) self.mothersEthnicOrigin = kwargs.get( 'mothersEthnicOrigin', None) self.mothersOtherRelevantAncestry = kwargs.get( 'mothersOtherRelevantAncestry', None) class CancerParticipant(ProtocolElement): """ This defines a Cancer Participant """ _schemaSource = """ {"type": "record", "name": "CancerParticipant", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "yearOfBirth", "type": ["null", "int"]}, {"name": "morphology", "type": ["null", {"type": "array", "items": "string"}]}, {"name": "readyForAnalysis", "type": "boolean"}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "center", "type": ["null", "string"], "doc": ""}, {"name": "individualId", "type": "string", "doc": ""}, {"name": "primaryDiagnosisDisease", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "primaryDiagnosisSubDisease", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "symbols": ["FEMALE", "MALE", "UNKNOWN"]}, "doc": ""}, {"name": "additionalInformation", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}, {"name": "assignedICD10", "type": ["null", {"type": "array", "items": "string"}], "doc": ""}, {"name": "tumourSamples", "type": {"type": "array", "items": {"type": "record", "name": "TumourSample", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "tumourId", "type": "string", "doc": ""}, {"name": "programmePhase", "type": ["null", {"type": "enum", "name": "ProgrammePhase", "symbols": ["CRUK", "OXFORD", "CLL", "IIP", "MAIN", "EXPT"]}], "doc": ""}, {"name": "diseaseType", "type": ["null", {"type": "enum", "name": "diseaseType", "symbols": ["ADULT_GLIOMA", "BLADDER", "BREAST", "CARCINOMA_OF_UNKNOWN_PRIMARY", "CHILDHOOD", "COLORECTAL", "ENDOMETRIAL_CARCINOMA", "HAEMONC", "HEPATOPANCREATOBILIARY", "LUNG", "MALIGNANT_MELANOMA", "NASOPHARYNGEAL", "ORAL_OROPHARYNGEAL", "OVARIAN", "PROSTATE", "RENAL", "SARCOMA", "SINONASAL", "TESTICULAR_GERM_CELL_TUMOURS", "UPPER_GASTROINTESTINAL", "NON_HODGKINS_B_CELL_LYMPHOMA_LOW_MOD_GRADE", "CLASSICAL_HODGKINS", "NODULAR_LYMPHOCYTE_PREDOMINANT_HODGKINS", "T_CELL_LYMPHOMA"]}], "doc": ""}, {"name": "diseaseSubType", "type": ["null", "string"], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}, {"name": "tumourType", "type": ["null", {"type": "enum", "name": "TumourType", "symbols": ["PRIMARY", "METASTATIC_RECURRENCE", "RECURRENCE_OF_PRIMARY_TUMOUR", "METASTASES"]}], "doc": ""}, {"name": "tumourContent", "type": ["null", {"type": "enum", "name": "TumourContent", "symbols": ["High", "Medium", "Low"]}], "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}, {"name": "tissueSource", "type": ["null", {"type": "enum", "name": "TissueSource", "symbols": ["BMA_TUMOUR_SORTED_CELLS", "CT_GUIDED_BIOPSY", "ENDOSCOPIC_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_FNA", "LAPAROSCOPIC_BIOPSY", "LAPAROSCOPIC_EXCISION", "MRI_GUIDED_BIOPSY", "NON_GUIDED_BIOPSY", "SURGICAL_RESECTION", "STEREOTACTICALLY_GUIDED_BIOPSY", "USS_GUIDED_BIOPSY", "NON_STANDARD_BIOPSY"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "morphologyICD", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedRT", "type": ["null", "string"], "doc": ""}, {"name": "topographyICD", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedRT", "type": ["null", "string"], "doc": ""}]}}}, {"name": "germlineSamples", "type": {"type": "array", "items": {"type": "record", "name": "GermlineSample", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "source", "type": ["null", "SampleSource"], "doc": ""}, {"name": "product", "type": ["null", "Product"], "doc": ""}, {"name": "preparationMethod", "type": ["null", "PreparationMethod"], "doc": ""}, {"name": "programmePhase", "type": ["null", "ProgrammePhase"], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}]}}}, {"name": "matchedSamples", "type": {"type": "array", "items": {"type": "record", "name": "MatchedSamples", "doc": "", "fields": [{"name": "germlineSampleId", "type": ["null", "string"], "doc": ""}, {"name": "tumourSampleId", "type": ["null", "string"], "doc": ""}]}}}, {"name": "versionControl", "type": ["null", {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.0.3"}]}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "additionalInformation", "assignedICD10", "center", "consentStatus", "germlineSamples", "individualId", "matchedSamples", "morphology", "primaryDiagnosisDisease", "primaryDiagnosisSubDisease", "readyForAnalysis", "sex", "tumourSamples", "versionControl", "yearOfBirth", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'consentStatus': ConsentStatus, 'germlineSamples': GermlineSample, 'matchedSamples': MatchedSamples, 'tumourSamples': TumourSample, 'versionControl': VersionControl, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'consentStatus': ConsentStatus, 'germlineSamples': GermlineSample, 'matchedSamples': MatchedSamples, 'tumourSamples': TumourSample, 'versionControl': VersionControl, } return embeddedTypes[fieldName] __slots__ = [ 'additionalInformation', 'assignedICD10', 'center', 'consentStatus', 'germlineSamples', 'individualId', 'matchedSamples', 'morphology', 'primaryDiagnosisDisease', 'primaryDiagnosisSubDisease', 'readyForAnalysis', 'sex', 'tumourSamples', 'versionControl', 'yearOfBirth' ] def __init__(self, **kwargs): self.additionalInformation = kwargs.get( 'additionalInformation', None) self.assignedICD10 = kwargs.get( 'assignedICD10', None) self.center = kwargs.get( 'center', None) self.consentStatus = kwargs.get( 'consentStatus', None) self.germlineSamples = kwargs.get( 'germlineSamples', None) self.individualId = kwargs.get( 'individualId', None) self.matchedSamples = kwargs.get( 'matchedSamples', None) self.morphology = kwargs.get( 'morphology', None) self.primaryDiagnosisDisease = kwargs.get( 'primaryDiagnosisDisease', None) self.primaryDiagnosisSubDisease = kwargs.get( 'primaryDiagnosisSubDisease', None) self.readyForAnalysis = kwargs.get( 'readyForAnalysis', None) self.sex = kwargs.get( 'sex', None) self.tumourSamples = kwargs.get( 'tumourSamples', None) self.versionControl = kwargs.get( 'versionControl', None) self.yearOfBirth = kwargs.get( 'yearOfBirth', None) class ChiSquare1KGenomesPhase3Pop(ProtocolElement): """ Chi-square test for goodness of fit of this sample to 1000 Genomes Phase 3 populations """ _schemaSource = """ {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "chiSquare", "kgPopCategory", "kgSuperPopCategory", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'chiSquare', 'kgPopCategory', 'kgSuperPopCategory' ] def __init__(self, **kwargs): self.chiSquare = kwargs.get( 'chiSquare', None) self.kgPopCategory = kwargs.get( 'kgPopCategory', None) self.kgSuperPopCategory = kwargs.get( 'kgSuperPopCategory', None) class ConsentStatus(ProtocolElement): """ Consent Status """ _schemaSource = """ {"type": "record", "name": "ConsentStatus", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]} """ schema = avro_parse(_schemaSource) requiredFields = {} @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'carrierStatusConsent', 'primaryFindingConsent', 'programmeConsent', 'secondaryFindingConsent' ] def __init__(self, **kwargs): self.carrierStatusConsent = kwargs.get( 'carrierStatusConsent', False) self.primaryFindingConsent = kwargs.get( 'primaryFindingConsent', False) self.programmeConsent = kwargs.get( 'programmeConsent', False) self.secondaryFindingConsent = kwargs.get( 'secondaryFindingConsent', False) class DiseasePenetrance(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "DiseasePenetrance", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "specificDisease", "type": "string"}, {"name": "penetrance", "type": {"type": "enum", "name": "Penetrance", "doc": "", "symbols": ["complete", "incomplete"]}}]} """ schema = avro_parse(_schemaSource) requiredFields = { "penetrance", "specificDisease", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'penetrance', 'specificDisease' ] def __init__(self, **kwargs): self.penetrance = kwargs.get( 'penetrance', None) self.specificDisease = kwargs.get( 'specificDisease', None) class Disorder(ProtocolElement): """ This is quite GEL specific. This is the way is stored in ModelCatalogue and PanelApp. Currently all specific disease titles are assigned to a disease subgroup so really only specificDisease needs to be completed but we add the others for generality """ _schemaSource = """ {"type": "record", "name": "Disorder", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "diseaseGroup", "type": ["null", "string"], "doc": ""}, {"name": "diseaseSubGroup", "type": ["null", "string"], "doc": ""}, {"name": "specificDisease", "type": ["null", "string"], "doc": ""}, {"name": "ageOfOnset", "type": ["null", "float"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "ageOfOnset", "diseaseGroup", "diseaseSubGroup", "specificDisease", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'ageOfOnset', 'diseaseGroup', 'diseaseSubGroup', 'specificDisease' ] def __init__(self, **kwargs): self.ageOfOnset = kwargs.get( 'ageOfOnset', None) self.diseaseGroup = kwargs.get( 'diseaseGroup', None) self.diseaseSubGroup = kwargs.get( 'diseaseSubGroup', None) self.specificDisease = kwargs.get( 'specificDisease', None) class EthnicCategory(object): """ This is the list of ethnicities in ONS16 * `D`: Mixed: White and Black Caribbean * `E`: Mixed: White and Black African * `F`: Mixed: White and Asian * `G`: Mixed: Any other mixed background * `A`: White: British * `B`: White: Irish * `C`: White: Any other White background * `L`: Asian or Asian British: Any other Asian background * `M`: Black or Black British: Caribbean * `N`: Black or Black British: African * `H`: Asian or Asian British: Indian * `J`: Asian or Asian British: Pakistani * `K`: Asian or Asian British: Bangladeshi * `P`: Black or Black British: Any other Black background * `S`: Other Ethnic Groups: Any other ethnic group * `R`: Other Ethnic Groups: Chinese * `Z`: Not stated """ D = "D" E = "E" F = "F" G = "G" A = "A" B = "B" C = "C" L = "L" M = "M" N = "N" H = "H" J = "J" K = "K" P = "P" S = "S" R = "R" Z = "Z" def __hash__(self): return str(self).__hash__() class FamilyQCState(object): """ FamilyQCState """ noState = "noState" passedMedicalReviewReadyForInterpretation = "passedMedicalReviewReadyForInterpretation" passedMedicalReviewNotReadyForInterpretation = "passedMedicalReviewNotReadyForInterpretation" queryToGel = "queryToGel" queryToGMC = "queryToGMC" failed = "failed" def __hash__(self): return str(self).__hash__() class GermlineSample(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "GermlineSample", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}, {"name": "programmePhase", "type": ["null", {"type": "enum", "name": "ProgrammePhase", "symbols": ["CRUK", "OXFORD", "CLL", "IIP", "MAIN", "EXPT"]}], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "LDPCode", "clinicalSampleDateTime", "labSampleId", "preparationMethod", "product", "programmePhase", "sampleId", "source", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'LDPCode', 'clinicalSampleDateTime', 'labSampleId', 'preparationMethod', 'product', 'programmePhase', 'sampleId', 'source' ] def __init__(self, **kwargs): self.LDPCode = kwargs.get( 'LDPCode', None) self.clinicalSampleDateTime = kwargs.get( 'clinicalSampleDateTime', None) self.labSampleId = kwargs.get( 'labSampleId', None) self.preparationMethod = kwargs.get( 'preparationMethod', None) self.product = kwargs.get( 'product', None) self.programmePhase = kwargs.get( 'programmePhase', None) self.sampleId = kwargs.get( 'sampleId', None) self.source = kwargs.get( 'source', None) class HpoTerm(ProtocolElement): """ This defines an HPO term and its modifiers (possibly multiple) If HPO term presence is unknown we don't have a entry on the list """ _schemaSource = """ {"type": "record", "name": "HpoTerm", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "term", "type": "string", "doc": ""}, {"name": "termPresence", "type": ["null", {"type": "enum", "name": "TernaryOption", "doc": "", "symbols": ["yes", "no", "unknown"]}], "doc": ""}, {"name": "hpoBuildNumber", "type": ["null", "string"], "doc": ""}, {"name": "modifiers", "type": ["null", {"type": "record", "name": "HpoTermModifiers", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]}], "doc": ""}, {"name": "ageOfOnset", "type": ["null", {"type": "enum", "name": "AgeOfOnset", "symbols": ["EMBRYONAL_ONSET", "FETAL_ONSET", "NEONATAL_ONSET", "INFANTILE_ONSET", "CHILDHOOD_ONSET", "JUVENILE_ONSET", "YOUNG_ADULT_ONSET", "LATE_ONSET", "MIDDLE_AGE_ONSET"]}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "ageOfOnset", "hpoBuildNumber", "modifiers", "term", "termPresence", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'modifiers': HpoTermModifiers, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'modifiers': HpoTermModifiers, } return embeddedTypes[fieldName] __slots__ = [ 'ageOfOnset', 'hpoBuildNumber', 'modifiers', 'term', 'termPresence' ] def __init__(self, **kwargs): self.ageOfOnset = kwargs.get( 'ageOfOnset', None) self.hpoBuildNumber = kwargs.get( 'hpoBuildNumber', None) self.modifiers = kwargs.get( 'modifiers', None) self.term = kwargs.get( 'term', None) self.termPresence = kwargs.get( 'termPresence', None) class HpoTermModifiers(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "HpoTermModifiers", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "laterality", "progression", "severity", "spatialPattern", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'laterality', 'progression', 'severity', 'spatialPattern' ] def __init__(self, **kwargs): self.laterality = kwargs.get( 'laterality', None) self.progression = kwargs.get( 'progression', None) self.severity = kwargs.get( 'severity', None) self.spatialPattern = kwargs.get( 'spatialPattern', None) class InbreedingCoefficient(ProtocolElement): """ Inbreeding coefficient """ _schemaSource = """ {"type": "record", "name": "InbreedingCoefficient", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "program", "type": "string", "doc": ""}, {"name": "version", "type": "string", "doc": ""}, {"name": "estimationMethod", "type": "string", "doc": ""}, {"name": "coefficient", "type": "double", "doc": ""}, {"name": "standardError", "type": ["null", "double"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "coefficient", "estimationMethod", "program", "sampleId", "standardError", "version", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'coefficient', 'estimationMethod', 'program', 'sampleId', 'standardError', 'version' ] def __init__(self, **kwargs): self.coefficient = kwargs.get( 'coefficient', None) self.estimationMethod = kwargs.get( 'estimationMethod', None) self.program = kwargs.get( 'program', None) self.sampleId = kwargs.get( 'sampleId', None) self.standardError = kwargs.get( 'standardError', None) self.version = kwargs.get( 'version', None) class KgPopCategory(object): """ 1K Population """ ACB = "ACB" ASW = "ASW" BEB = "BEB" CDX = "CDX" CEU = "CEU" CHB = "CHB" CHS = "CHS" CLM = "CLM" ESN = "ESN" FIN = "FIN" GBR = "GBR" GIH = "GIH" GWD = "GWD" IBS = "IBS" ITU = "ITU" JPT = "JPT" KHV = "KHV" LWK = "LWK" MSL = "MSL" MXL = "MXL" PEL = "PEL" PJL = "PJL" PUR = "PUR" STU = "STU" TSI = "TSI" YRI = "YRI" def __hash__(self): return str(self).__hash__() class KgSuperPopCategory(object): """ 1K Super Population """ AFR = "AFR" AMR = "AMR" EAS = "EAS" EUR = "EUR" SAS = "SAS" def __hash__(self): return str(self).__hash__() class Laterality(object): """ No documentation """ RIGHT = "RIGHT" UNILATERAL = "UNILATERAL" BILATERAL = "BILATERAL" LEFT = "LEFT" def __hash__(self): return str(self).__hash__() class LifeStatus(object): """ Life Status """ ALIVE = "ALIVE" ABORTED = "ABORTED" DECEASED = "DECEASED" UNBORN = "UNBORN" STILLBORN = "STILLBORN" MISCARRIAGE = "MISCARRIAGE" def __hash__(self): return str(self).__hash__() class MatchedSamples(ProtocolElement): """ This defines a pair of germline and tumor, this pair should/must be analyzed together """ _schemaSource = """ {"type": "record", "name": "MatchedSamples", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "germlineSampleId", "type": ["null", "string"], "doc": ""}, {"name": "tumourSampleId", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "germlineSampleId", "tumourSampleId", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'germlineSampleId', 'tumourSampleId' ] def __init__(self, **kwargs): self.germlineSampleId = kwargs.get( 'germlineSampleId', None) self.tumourSampleId = kwargs.get( 'tumourSampleId', None) class Method(object): """ No documentation """ RESECTION = "RESECTION" BIOPSY = "BIOPSY" BLOOD = "BLOOD" def __hash__(self): return str(self).__hash__() class ParticipantQCState(object): """ QCState Status """ noState = "noState" passedMedicalReviewReadyForInterpretation = "passedMedicalReviewReadyForInterpretation" passedMedicalReviewNotReadyForInterpretation = "passedMedicalReviewNotReadyForInterpretation" queryToGel = "queryToGel" queryToGMC = "queryToGMC" failed = "failed" def __hash__(self): return str(self).__hash__() class Pedigree(ProtocolElement): """ This is the concept of a family with associated phenotypes as present in the record RDParticipant """ _schemaSource = """ {"type": "record", "name": "Pedigree", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "versionControl", "type": ["null", {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.0.3"}]}], "doc": ""}, {"name": "LDPCode", "type": ["null", "string"]}, {"name": "familyId", "type": "string", "doc": ""}, {"name": "members", "type": {"type": "array", "items": {"type": "record", "name": "PedigreeMember", "doc": "", "fields": [{"name": "pedigreeId", "type": ["null", "int"], "doc": ""}, {"name": "isProband", "type": ["null", "boolean"], "doc": ""}, {"name": "participantId", "type": ["null", "string"], "doc": ""}, {"name": "participantQCState", "type": ["null", {"type": "enum", "name": "ParticipantQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}, {"name": "gelSuperFamilyId", "type": ["null", "string"], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}, "doc": ""}, {"name": "personKaryotypicSex", "type": ["null", {"type": "enum", "name": "PersonKaryotipicSex", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}], "doc": ""}, {"name": "yearOfBirth", "type": ["null", "int"], "doc": ""}, {"name": "fatherId", "type": ["null", "int"], "doc": ""}, {"name": "motherId", "type": ["null", "int"], "doc": ""}, {"name": "superFatherId", "type": ["null", "int"], "doc": ""}, {"name": "superMotherId", "type": ["null", "int"], "doc": ""}, {"name": "twinGroup", "type": ["null", "int"], "doc": ""}, {"name": "monozygotic", "type": ["null", {"type": "enum", "name": "TernaryOption", "doc": "", "symbols": ["yes", "no", "unknown"]}], "doc": ""}, {"name": "adoptedStatus", "type": ["null", {"type": "enum", "name": "AdoptedStatus", "doc": "", "symbols": ["notadopted", "adoptedin", "adoptedout"]}], "doc": ""}, {"name": "lifeStatus", "type": ["null", {"type": "enum", "name": "LifeStatus", "doc": "", "symbols": ["ALIVE", "ABORTED", "DECEASED", "UNBORN", "STILLBORN", "MISCARRIAGE"]}], "doc": ""}, {"name": "consanguineousParents", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "affectionStatus", "type": ["null", {"type": "enum", "name": "AffectionStatus", "doc": "", "symbols": ["UNAFFECTED", "AFFECTED", "UNCERTAIN"]}], "doc": ""}, {"name": "disorderList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Disorder", "doc": "", "fields": [{"name": "diseaseGroup", "type": ["null", "string"], "doc": ""}, {"name": "diseaseSubGroup", "type": ["null", "string"], "doc": ""}, {"name": "specificDisease", "type": ["null", "string"], "doc": ""}, {"name": "ageOfOnset", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}, {"name": "hpoTermList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "HpoTerm", "doc": "", "fields": [{"name": "term", "type": "string", "doc": ""}, {"name": "termPresence", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "hpoBuildNumber", "type": ["null", "string"], "doc": ""}, {"name": "modifiers", "type": ["null", {"type": "record", "name": "HpoTermModifiers", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]}], "doc": ""}, {"name": "ageOfOnset", "type": ["null", {"type": "enum", "name": "AgeOfOnset", "symbols": ["EMBRYONAL_ONSET", "FETAL_ONSET", "NEONATAL_ONSET", "INFANTILE_ONSET", "CHILDHOOD_ONSET", "JUVENILE_ONSET", "YOUNG_ADULT_ONSET", "LATE_ONSET", "MIDDLE_AGE_ONSET"]}], "doc": ""}]}}], "doc": ""}, {"name": "ancestries", "type": ["null", {"type": "record", "name": "Ancestries", "doc": "", "fields": [{"name": "mothersEthnicOrigin", "type": ["null", {"type": "enum", "name": "EthnicCategory", "doc": "", "symbols": ["D", "E", "F", "G", "A", "B", "C", "L", "M", "N", "H", "J", "K", "P", "S", "R", "Z"]}], "doc": ""}, {"name": "mothersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "fathersEthnicOrigin", "type": ["null", "EthnicCategory"], "doc": ""}, {"name": "fathersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "chiSquare1KGenomesPhase3Pop", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]}}], "doc": ""}]}], "doc": ""}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "samples", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Sample", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "symbols": ["BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}]}}], "doc": ""}, {"name": "inbreedingCoefficient", "type": ["null", {"type": "record", "name": "InbreedingCoefficient", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "program", "type": "string", "doc": ""}, {"name": "version", "type": "string", "doc": ""}, {"name": "estimationMethod", "type": "string", "doc": ""}, {"name": "coefficient", "type": "double", "doc": ""}, {"name": "standardError", "type": ["null", "double"], "doc": ""}]}], "doc": ""}, {"name": "additionalInformation", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}}}, {"name": "analysisPanels", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AnalysisPanel", "fields": [{"name": "specificDisease", "type": "string"}, {"name": "panelName", "type": "string"}, {"name": "panelVersion", "type": ["null", "string"]}, {"name": "reviewOutcome", "type": "string"}, {"name": "multipleGeneticOrigins", "type": "string"}]}}]}, {"name": "diseasePenetrances", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DiseasePenetrance", "fields": [{"name": "specificDisease", "type": "string"}, {"name": "penetrance", "type": {"type": "enum", "name": "Penetrance", "doc": "", "symbols": ["complete", "incomplete"]}}]}}]}, {"name": "readyForAnalysis", "type": "boolean"}, {"name": "familyQCState", "type": ["null", {"type": "enum", "name": "FamilyQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "LDPCode", "analysisPanels", "diseasePenetrances", "familyId", "familyQCState", "members", "readyForAnalysis", "versionControl", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'analysisPanels': AnalysisPanel, 'diseasePenetrances': DiseasePenetrance, 'members': PedigreeMember, 'versionControl': VersionControl, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'analysisPanels': AnalysisPanel, 'diseasePenetrances': DiseasePenetrance, 'members': PedigreeMember, 'versionControl': VersionControl, } return embeddedTypes[fieldName] __slots__ = [ 'LDPCode', 'analysisPanels', 'diseasePenetrances', 'familyId', 'familyQCState', 'members', 'readyForAnalysis', 'versionControl' ] def __init__(self, **kwargs): self.LDPCode = kwargs.get( 'LDPCode', None) self.analysisPanels = kwargs.get( 'analysisPanels', None) self.diseasePenetrances = kwargs.get( 'diseasePenetrances', None) self.familyId = kwargs.get( 'familyId', None) self.familyQCState = kwargs.get( 'familyQCState', None) self.members = kwargs.get( 'members', None) self.readyForAnalysis = kwargs.get( 'readyForAnalysis', None) self.versionControl = kwargs.get( 'versionControl', None) class PedigreeMember(ProtocolElement): """ This defines a RD Participant (demographics and pedigree information) """ _schemaSource = """ {"type": "record", "name": "PedigreeMember", "namespace": "org.gel.models.participant.avro", "doc": "", "fields": [{"name": "pedigreeId", "type": ["null", "int"], "doc": ""}, {"name": "isProband", "type": ["null", "boolean"], "doc": ""}, {"name": "participantId", "type": ["null", "string"], "doc": ""}, {"name": "participantQCState", "type": ["null", {"type": "enum", "name": "ParticipantQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}, {"name": "gelSuperFamilyId", "type": ["null", "string"], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}, "doc": ""}, {"name": "personKaryotypicSex", "type": ["null", {"type": "enum", "name": "PersonKaryotipicSex", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}], "doc": ""}, {"name": "yearOfBirth", "type": ["null", "int"], "doc": ""}, {"name": "fatherId", "type": ["null", "int"], "doc": ""}, {"name": "motherId", "type": ["null", "int"], "doc": ""}, {"name": "superFatherId", "type": ["null", "int"], "doc": ""}, {"name": "superMotherId", "type": ["null", "int"], "doc": ""}, {"name": "twinGroup", "type": ["null", "int"], "doc": ""}, {"name": "monozygotic", "type": ["null", {"type": "enum", "name": "TernaryOption", "doc": "", "symbols": ["yes", "no", "unknown"]}], "doc": ""}, {"name": "adoptedStatus", "type": ["null", {"type": "enum", "name": "AdoptedStatus", "doc": "", "symbols": ["notadopted", "adoptedin", "adoptedout"]}], "doc": ""}, {"name": "lifeStatus", "type": ["null", {"type": "enum", "name": "LifeStatus", "doc": "", "symbols": ["ALIVE", "ABORTED", "DECEASED", "UNBORN", "STILLBORN", "MISCARRIAGE"]}], "doc": ""}, {"name": "consanguineousParents", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "affectionStatus", "type": ["null", {"type": "enum", "name": "AffectionStatus", "doc": "", "symbols": ["UNAFFECTED", "AFFECTED", "UNCERTAIN"]}], "doc": ""}, {"name": "disorderList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Disorder", "doc": "", "fields": [{"name": "diseaseGroup", "type": ["null", "string"], "doc": ""}, {"name": "diseaseSubGroup", "type": ["null", "string"], "doc": ""}, {"name": "specificDisease", "type": ["null", "string"], "doc": ""}, {"name": "ageOfOnset", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}, {"name": "hpoTermList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "HpoTerm", "doc": "", "fields": [{"name": "term", "type": "string", "doc": ""}, {"name": "termPresence", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "hpoBuildNumber", "type": ["null", "string"], "doc": ""}, {"name": "modifiers", "type": ["null", {"type": "record", "name": "HpoTermModifiers", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]}], "doc": ""}, {"name": "ageOfOnset", "type": ["null", {"type": "enum", "name": "AgeOfOnset", "symbols": ["EMBRYONAL_ONSET", "FETAL_ONSET", "NEONATAL_ONSET", "INFANTILE_ONSET", "CHILDHOOD_ONSET", "JUVENILE_ONSET", "YOUNG_ADULT_ONSET", "LATE_ONSET", "MIDDLE_AGE_ONSET"]}], "doc": ""}]}}], "doc": ""}, {"name": "ancestries", "type": ["null", {"type": "record", "name": "Ancestries", "doc": "", "fields": [{"name": "mothersEthnicOrigin", "type": ["null", {"type": "enum", "name": "EthnicCategory", "doc": "", "symbols": ["D", "E", "F", "G", "A", "B", "C", "L", "M", "N", "H", "J", "K", "P", "S", "R", "Z"]}], "doc": ""}, {"name": "mothersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "fathersEthnicOrigin", "type": ["null", "EthnicCategory"], "doc": ""}, {"name": "fathersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "chiSquare1KGenomesPhase3Pop", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]}}], "doc": ""}]}], "doc": ""}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "samples", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Sample", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "symbols": ["BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}]}}], "doc": ""}, {"name": "inbreedingCoefficient", "type": ["null", {"type": "record", "name": "InbreedingCoefficient", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "program", "type": "string", "doc": ""}, {"name": "version", "type": "string", "doc": ""}, {"name": "estimationMethod", "type": "string", "doc": ""}, {"name": "coefficient", "type": "double", "doc": ""}, {"name": "standardError", "type": ["null", "double"], "doc": ""}]}], "doc": ""}, {"name": "additionalInformation", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "additionalInformation", "adoptedStatus", "affectionStatus", "ancestries", "consanguineousParents", "consentStatus", "disorderList", "fatherId", "gelSuperFamilyId", "hpoTermList", "inbreedingCoefficient", "isProband", "lifeStatus", "monozygotic", "motherId", "participantId", "participantQCState", "pedigreeId", "personKaryotypicSex", "samples", "sex", "superFatherId", "superMotherId", "twinGroup", "yearOfBirth", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'ancestries': Ancestries, 'consentStatus': ConsentStatus, 'disorderList': Disorder, 'hpoTermList': HpoTerm, 'inbreedingCoefficient': InbreedingCoefficient, 'samples': Sample, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'ancestries': Ancestries, 'consentStatus': ConsentStatus, 'disorderList': Disorder, 'hpoTermList': HpoTerm, 'inbreedingCoefficient': InbreedingCoefficient, 'samples': Sample, } return embeddedTypes[fieldName] __slots__ = [ 'additionalInformation', 'adoptedStatus', 'affectionStatus', 'ancestries', 'consanguineousParents', 'consentStatus', 'disorderList', 'fatherId', 'gelSuperFamilyId', 'hpoTermList', 'inbreedingCoefficient', 'isProband', 'lifeStatus', 'monozygotic', 'motherId', 'participantId', 'participantQCState', 'pedigreeId', 'personKaryotypicSex', 'samples', 'sex', 'superFatherId', 'superMotherId', 'twinGroup', 'yearOfBirth' ] def __init__(self, **kwargs): self.additionalInformation = kwargs.get( 'additionalInformation', None) self.adoptedStatus = kwargs.get( 'adoptedStatus', None) self.affectionStatus = kwargs.get( 'affectionStatus', None) self.ancestries = kwargs.get( 'ancestries', None) self.consanguineousParents = kwargs.get( 'consanguineousParents', None) self.consentStatus = kwargs.get( 'consentStatus', None) self.disorderList = kwargs.get( 'disorderList', None) self.fatherId = kwargs.get( 'fatherId', None) self.gelSuperFamilyId = kwargs.get( 'gelSuperFamilyId', None) self.hpoTermList = kwargs.get( 'hpoTermList', None) self.inbreedingCoefficient = kwargs.get( 'inbreedingCoefficient', None) self.isProband = kwargs.get( 'isProband', None) self.lifeStatus = kwargs.get( 'lifeStatus', None) self.monozygotic = kwargs.get( 'monozygotic', None) self.motherId = kwargs.get( 'motherId', None) self.participantId = kwargs.get( 'participantId', None) self.participantQCState = kwargs.get( 'participantQCState', None) self.pedigreeId = kwargs.get( 'pedigreeId', None) self.personKaryotypicSex = kwargs.get( 'personKaryotypicSex', None) self.samples = kwargs.get( 'samples', None) self.sex = kwargs.get( 'sex', None) self.superFatherId = kwargs.get( 'superFatherId', None) self.superMotherId = kwargs.get( 'superMotherId', None) self.twinGroup = kwargs.get( 'twinGroup', None) self.yearOfBirth = kwargs.get( 'yearOfBirth', None) class Penetrance(object): """ Penetrance assumed in the analysis """ complete = "complete" incomplete = "incomplete" def __hash__(self): return str(self).__hash__() class PersonKaryotipicSex(object): """ Karyotipic Sex """ UNKNOWN = "UNKNOWN" XX = "XX" XY = "XY" XO = "XO" XXY = "XXY" XXX = "XXX" XXYY = "XXYY" XXXY = "XXXY" XXXX = "XXXX" XYY = "XYY" OTHER = "OTHER" def __hash__(self): return str(self).__hash__() class PreparationMethod(object): """ No documentation """ EDTA = "EDTA" ORAGENE = "ORAGENE" FF = "FF" FFPE = "FFPE" CD128_SORTED_CELLS = "CD128_SORTED_CELLS" ASPIRATE = "ASPIRATE" def __hash__(self): return str(self).__hash__() class Product(object): """ No documentation """ DNA = "DNA" RNA = "RNA" def __hash__(self): return str(self).__hash__() class ProgrammePhase(object): """ No documentation """ CRUK = "CRUK" OXFORD = "OXFORD" CLL = "CLL" IIP = "IIP" MAIN = "MAIN" EXPT = "EXPT" def __hash__(self): return str(self).__hash__() class Progression(object): """ No documentation """ PROGRESSIVE = "PROGRESSIVE" NONPROGRESSIVE = "NONPROGRESSIVE" def __hash__(self): return str(self).__hash__() class RDFamilyChange(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "RDFamilyChange", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "FamilyId", "type": "string", "doc": ""}, {"name": "code", "type": {"type": "enum", "name": "RDFamilyChangeCode", "doc": "", "symbols": ["FamilyAdded", "FamilyDeleted", "ProbandChanged", "ParticipantAdded", "ParticipantRemoved", "ConsentStatusChanged", "AffectionStatusChanged", "PanelAssignmentChanged", "SexChanged", "SampleChanged"]}, "doc": ""}, {"name": "Family", "type": {"type": "record", "name": "Pedigree", "doc": "", "fields": [{"name": "versionControl", "type": ["null", {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.0.3"}]}], "doc": ""}, {"name": "LDPCode", "type": ["null", "string"]}, {"name": "familyId", "type": "string", "doc": ""}, {"name": "members", "type": {"type": "array", "items": {"type": "record", "name": "PedigreeMember", "doc": "", "fields": [{"name": "pedigreeId", "type": ["null", "int"], "doc": ""}, {"name": "isProband", "type": ["null", "boolean"], "doc": ""}, {"name": "participantId", "type": ["null", "string"], "doc": ""}, {"name": "participantQCState", "type": ["null", {"type": "enum", "name": "ParticipantQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}], "doc": ""}, {"name": "gelSuperFamilyId", "type": ["null", "string"], "doc": ""}, {"name": "sex", "type": {"type": "enum", "name": "Sex", "doc": "", "symbols": ["MALE", "FEMALE", "UNKNOWN"]}, "doc": ""}, {"name": "personKaryotypicSex", "type": ["null", {"type": "enum", "name": "PersonKaryotipicSex", "doc": "", "symbols": ["UNKNOWN", "XX", "XY", "XO", "XXY", "XXX", "XXYY", "XXXY", "XXXX", "XYY", "OTHER"]}], "doc": ""}, {"name": "yearOfBirth", "type": ["null", "int"], "doc": ""}, {"name": "fatherId", "type": ["null", "int"], "doc": ""}, {"name": "motherId", "type": ["null", "int"], "doc": ""}, {"name": "superFatherId", "type": ["null", "int"], "doc": ""}, {"name": "superMotherId", "type": ["null", "int"], "doc": ""}, {"name": "twinGroup", "type": ["null", "int"], "doc": ""}, {"name": "monozygotic", "type": ["null", {"type": "enum", "name": "TernaryOption", "doc": "", "symbols": ["yes", "no", "unknown"]}], "doc": ""}, {"name": "adoptedStatus", "type": ["null", {"type": "enum", "name": "AdoptedStatus", "doc": "", "symbols": ["notadopted", "adoptedin", "adoptedout"]}], "doc": ""}, {"name": "lifeStatus", "type": ["null", {"type": "enum", "name": "LifeStatus", "doc": "", "symbols": ["ALIVE", "ABORTED", "DECEASED", "UNBORN", "STILLBORN", "MISCARRIAGE"]}], "doc": ""}, {"name": "consanguineousParents", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "affectionStatus", "type": ["null", {"type": "enum", "name": "AffectionStatus", "doc": "", "symbols": ["UNAFFECTED", "AFFECTED", "UNCERTAIN"]}], "doc": ""}, {"name": "disorderList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Disorder", "doc": "", "fields": [{"name": "diseaseGroup", "type": ["null", "string"], "doc": ""}, {"name": "diseaseSubGroup", "type": ["null", "string"], "doc": ""}, {"name": "specificDisease", "type": ["null", "string"], "doc": ""}, {"name": "ageOfOnset", "type": ["null", "float"], "doc": ""}]}}], "doc": ""}, {"name": "hpoTermList", "type": ["null", {"type": "array", "items": {"type": "record", "name": "HpoTerm", "doc": "", "fields": [{"name": "term", "type": "string", "doc": ""}, {"name": "termPresence", "type": ["null", "TernaryOption"], "doc": ""}, {"name": "hpoBuildNumber", "type": ["null", "string"], "doc": ""}, {"name": "modifiers", "type": ["null", {"type": "record", "name": "HpoTermModifiers", "fields": [{"name": "laterality", "type": ["null", {"type": "enum", "name": "Laterality", "symbols": ["RIGHT", "UNILATERAL", "BILATERAL", "LEFT"]}]}, {"name": "progression", "type": ["null", {"type": "enum", "name": "Progression", "symbols": ["PROGRESSIVE", "NONPROGRESSIVE"]}]}, {"name": "severity", "type": ["null", {"type": "enum", "name": "Severity", "symbols": ["BORDERLINE", "MILD", "MODERATE", "SEVERE", "PROFOUND"]}]}, {"name": "spatialPattern", "type": ["null", {"type": "enum", "name": "SpatialPattern", "symbols": ["DISTAL", "GENERALIZED", "LOCALIZED", "PROXIMAL"]}]}]}], "doc": ""}, {"name": "ageOfOnset", "type": ["null", {"type": "enum", "name": "AgeOfOnset", "symbols": ["EMBRYONAL_ONSET", "FETAL_ONSET", "NEONATAL_ONSET", "INFANTILE_ONSET", "CHILDHOOD_ONSET", "JUVENILE_ONSET", "YOUNG_ADULT_ONSET", "LATE_ONSET", "MIDDLE_AGE_ONSET"]}], "doc": ""}]}}], "doc": ""}, {"name": "ancestries", "type": ["null", {"type": "record", "name": "Ancestries", "doc": "", "fields": [{"name": "mothersEthnicOrigin", "type": ["null", {"type": "enum", "name": "EthnicCategory", "doc": "", "symbols": ["D", "E", "F", "G", "A", "B", "C", "L", "M", "N", "H", "J", "K", "P", "S", "R", "Z"]}], "doc": ""}, {"name": "mothersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "fathersEthnicOrigin", "type": ["null", "EthnicCategory"], "doc": ""}, {"name": "fathersOtherRelevantAncestry", "type": ["null", "string"], "doc": ""}, {"name": "chiSquare1KGenomesPhase3Pop", "type": ["null", {"type": "array", "items": {"type": "record", "name": "ChiSquare1KGenomesPhase3Pop", "doc": "", "fields": [{"name": "kgSuperPopCategory", "type": {"type": "enum", "name": "KgSuperPopCategory", "doc": "", "symbols": ["AFR", "AMR", "EAS", "EUR", "SAS"]}, "doc": ""}, {"name": "kgPopCategory", "type": ["null", {"type": "enum", "name": "KgPopCategory", "doc": "", "symbols": ["ACB", "ASW", "BEB", "CDX", "CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS", "ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU", "TSI", "YRI"]}], "doc": ""}, {"name": "chiSquare", "type": "double", "doc": ""}]}}], "doc": ""}]}], "doc": ""}, {"name": "consentStatus", "type": ["null", {"type": "record", "name": "ConsentStatus", "doc": "", "fields": [{"name": "programmeConsent", "type": "boolean", "doc": "", "default": false}, {"name": "primaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "secondaryFindingConsent", "type": "boolean", "doc": "", "default": false}, {"name": "carrierStatusConsent", "type": "boolean", "doc": "", "default": false}]}], "doc": ""}, {"name": "samples", "type": ["null", {"type": "array", "items": {"type": "record", "name": "Sample", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "symbols": ["BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}]}}], "doc": ""}, {"name": "inbreedingCoefficient", "type": ["null", {"type": "record", "name": "InbreedingCoefficient", "doc": "", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "program", "type": "string", "doc": ""}, {"name": "version", "type": "string", "doc": ""}, {"name": "estimationMethod", "type": "string", "doc": ""}, {"name": "coefficient", "type": "double", "doc": ""}, {"name": "standardError", "type": ["null", "double"], "doc": ""}]}], "doc": ""}, {"name": "additionalInformation", "type": ["null", {"type": "map", "values": "string"}], "doc": ""}]}}}, {"name": "analysisPanels", "type": ["null", {"type": "array", "items": {"type": "record", "name": "AnalysisPanel", "fields": [{"name": "specificDisease", "type": "string"}, {"name": "panelName", "type": "string"}, {"name": "panelVersion", "type": ["null", "string"]}, {"name": "reviewOutcome", "type": "string"}, {"name": "multipleGeneticOrigins", "type": "string"}]}}]}, {"name": "diseasePenetrances", "type": ["null", {"type": "array", "items": {"type": "record", "name": "DiseasePenetrance", "fields": [{"name": "specificDisease", "type": "string"}, {"name": "penetrance", "type": {"type": "enum", "name": "Penetrance", "doc": "", "symbols": ["complete", "incomplete"]}}]}}]}, {"name": "readyForAnalysis", "type": "boolean"}, {"name": "familyQCState", "type": ["null", {"type": "enum", "name": "FamilyQCState", "doc": "", "symbols": ["noState", "passedMedicalReviewReadyForInterpretation", "passedMedicalReviewNotReadyForInterpretation", "queryToGel", "queryToGMC", "failed"]}]}]}, "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "Family", "FamilyId", "code", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'Family': Pedigree, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'Family': Pedigree, } return embeddedTypes[fieldName] __slots__ = [ 'Family', 'FamilyId', 'code' ] def __init__(self, **kwargs): self.Family = kwargs.get( 'Family', Pedigree()) self.FamilyId = kwargs.get( 'FamilyId', None) self.code = kwargs.get( 'code', None) class RDFamilyChangeCode(object): """ This code define the change type: * `FamilyAdded`: This is a new family. * `FamilyDeleted`: This family should be removed. * `ProbandChanged`: The proband participant is now a different member of the family. * `ParticipantAdded`: A new participant has been sequenced and added to the family. * `ParticipantRemoved`: A participant has been removed. * `ConsentStatusChanged`: One or more participant in this family has a different consent status. * `AffectionStatusChanged`: HPOterms or Disorder changed in one or more participants in this family. * `PanelAssignmentChanged`: Gene Panels has changed in this family. * `SexChanged`: Sex has changed for one or more participants in this family. * `SampleChanged`: The sample/s associated to one or more participant in this family has changed. """ FamilyAdded = "FamilyAdded" FamilyDeleted = "FamilyDeleted" ProbandChanged = "ProbandChanged" ParticipantAdded = "ParticipantAdded" ParticipantRemoved = "ParticipantRemoved" ConsentStatusChanged = "ConsentStatusChanged" AffectionStatusChanged = "AffectionStatusChanged" PanelAssignmentChanged = "PanelAssignmentChanged" SexChanged = "SexChanged" SampleChanged = "SampleChanged" def __hash__(self): return str(self).__hash__() class Sample(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "Sample", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "symbols": ["BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "labSampleId", "preparationMethod", "product", "sampleId", "source", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'labSampleId', 'preparationMethod', 'product', 'sampleId', 'source' ] def __init__(self, **kwargs): self.labSampleId = kwargs.get( 'labSampleId', None) self.preparationMethod = kwargs.get( 'preparationMethod', None) self.product = kwargs.get( 'product', None) self.sampleId = kwargs.get( 'sampleId', None) self.source = kwargs.get( 'source', None) class SampleSource(object): """ No documentation """ TUMOUR = "TUMOUR" BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS = "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS" BONE_MARROW_ASPIRATE_TUMOUR_CELLS = "BONE_MARROW_ASPIRATE_TUMOUR_CELLS" BLOOD = "BLOOD" SALIVA = "SALIVA" FIBROBLAST = "FIBROBLAST" TISSUE = "TISSUE" def __hash__(self): return str(self).__hash__() class SensitiveInformation(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "SensitiveInformation", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "versionControl", "type": {"type": "record", "name": "VersionControl", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.0.3"}]}, "doc": ""}, {"name": "gelID", "type": "string"}, {"name": "externalIds", "type": ["null", {"type": "array", "items": "string"}]}, {"name": "genomicMedicineCenter", "type": ["null", "string"]}, {"name": "fullNameOfResponsibleConsultant", "type": ["null", "string"]}, {"name": "contactNumber", "type": ["null", "string"]}, {"name": "hospitalOfResponsibleConsultant", "type": ["null", "string"]}, {"name": "centerSampleId", "type": ["null", "string"]}, {"name": "originatingCenter", "type": ["null", "string"]}, {"name": "centerPatientId", "type": ["null", "string"]}]} """ schema = avro_parse(_schemaSource) requiredFields = { "centerPatientId", "centerSampleId", "contactNumber", "externalIds", "fullNameOfResponsibleConsultant", "gelID", "genomicMedicineCenter", "hospitalOfResponsibleConsultant", "originatingCenter", "versionControl", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = { 'versionControl': VersionControl, } return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = { 'versionControl': VersionControl, } return embeddedTypes[fieldName] __slots__ = [ 'centerPatientId', 'centerSampleId', 'contactNumber', 'externalIds', 'fullNameOfResponsibleConsultant', 'gelID', 'genomicMedicineCenter', 'hospitalOfResponsibleConsultant', 'originatingCenter', 'versionControl' ] def __init__(self, **kwargs): self.centerPatientId = kwargs.get( 'centerPatientId', None) self.centerSampleId = kwargs.get( 'centerSampleId', None) self.contactNumber = kwargs.get( 'contactNumber', None) self.externalIds = kwargs.get( 'externalIds', None) self.fullNameOfResponsibleConsultant = kwargs.get( 'fullNameOfResponsibleConsultant', None) self.gelID = kwargs.get( 'gelID', None) self.genomicMedicineCenter = kwargs.get( 'genomicMedicineCenter', None) self.hospitalOfResponsibleConsultant = kwargs.get( 'hospitalOfResponsibleConsultant', None) self.originatingCenter = kwargs.get( 'originatingCenter', None) self.versionControl = kwargs.get( 'versionControl', VersionControl()) class Severity(object): """ No documentation """ BORDERLINE = "BORDERLINE" MILD = "MILD" MODERATE = "MODERATE" SEVERE = "SEVERE" PROFOUND = "PROFOUND" def __hash__(self): return str(self).__hash__() class Sex(object): """ No documentation """ FEMALE = "FEMALE" MALE = "MALE" UNKNOWN = "UNKNOWN" def __hash__(self): return str(self).__hash__() class SpatialPattern(object): """ No documentation """ DISTAL = "DISTAL" GENERALIZED = "GENERALIZED" LOCALIZED = "LOCALIZED" PROXIMAL = "PROXIMAL" def __hash__(self): return str(self).__hash__() class TernaryOption(object): """ This defines a yes/no/unknown case """ yes = "yes" no = "no" unknown = "unknown" def __hash__(self): return str(self).__hash__() class TissueSource(object): """ No documentation """ BMA_TUMOUR_SORTED_CELLS = "BMA_TUMOUR_SORTED_CELLS" CT_GUIDED_BIOPSY = "CT_GUIDED_BIOPSY" ENDOSCOPIC_BIOPSY = "ENDOSCOPIC_BIOPSY" ENDOSCOPIC_ULTRASOUND_GUIDED_BIOPSY = "ENDOSCOPIC_ULTRASOUND_GUIDED_BIOPSY" ENDOSCOPIC_ULTRASOUND_GUIDED_FNA = "ENDOSCOPIC_ULTRASOUND_GUIDED_FNA" LAPAROSCOPIC_BIOPSY = "LAPAROSCOPIC_BIOPSY" LAPAROSCOPIC_EXCISION = "LAPAROSCOPIC_EXCISION" MRI_GUIDED_BIOPSY = "MRI_GUIDED_BIOPSY" NON_GUIDED_BIOPSY = "NON_GUIDED_BIOPSY" SURGICAL_RESECTION = "SURGICAL_RESECTION" STEREOTACTICALLY_GUIDED_BIOPSY = "STEREOTACTICALLY_GUIDED_BIOPSY" USS_GUIDED_BIOPSY = "USS_GUIDED_BIOPSY" NON_STANDARD_BIOPSY = "NON_STANDARD_BIOPSY" def __hash__(self): return str(self).__hash__() class TumourContent(object): """ No documentation """ High = "High" Medium = "Medium" Low = "Low" def __hash__(self): return str(self).__hash__() class TumourSample(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "TumourSample", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "sampleId", "type": "string", "doc": ""}, {"name": "labSampleId", "type": "int", "doc": ""}, {"name": "LDPCode", "type": "string", "doc": ""}, {"name": "tumourId", "type": "string", "doc": ""}, {"name": "programmePhase", "type": ["null", {"type": "enum", "name": "ProgrammePhase", "symbols": ["CRUK", "OXFORD", "CLL", "IIP", "MAIN", "EXPT"]}], "doc": ""}, {"name": "diseaseType", "type": ["null", {"type": "enum", "name": "diseaseType", "symbols": ["ADULT_GLIOMA", "BLADDER", "BREAST", "CARCINOMA_OF_UNKNOWN_PRIMARY", "CHILDHOOD", "COLORECTAL", "ENDOMETRIAL_CARCINOMA", "HAEMONC", "HEPATOPANCREATOBILIARY", "LUNG", "MALIGNANT_MELANOMA", "NASOPHARYNGEAL", "ORAL_OROPHARYNGEAL", "OVARIAN", "PROSTATE", "RENAL", "SARCOMA", "SINONASAL", "TESTICULAR_GERM_CELL_TUMOURS", "UPPER_GASTROINTESTINAL", "NON_HODGKINS_B_CELL_LYMPHOMA_LOW_MOD_GRADE", "CLASSICAL_HODGKINS", "NODULAR_LYMPHOCYTE_PREDOMINANT_HODGKINS", "T_CELL_LYMPHOMA"]}], "doc": ""}, {"name": "diseaseSubType", "type": ["null", "string"], "doc": ""}, {"name": "clinicalSampleDateTime", "type": ["null", "string"], "doc": ""}, {"name": "tumourType", "type": ["null", {"type": "enum", "name": "TumourType", "symbols": ["PRIMARY", "METASTATIC_RECURRENCE", "RECURRENCE_OF_PRIMARY_TUMOUR", "METASTASES"]}], "doc": ""}, {"name": "tumourContent", "type": ["null", {"type": "enum", "name": "TumourContent", "symbols": ["High", "Medium", "Low"]}], "doc": ""}, {"name": "source", "type": ["null", {"type": "enum", "name": "SampleSource", "symbols": ["TUMOUR", "BONE_MARROW_ASPIRATE_TUMOUR_SORTED_CELLS", "BONE_MARROW_ASPIRATE_TUMOUR_CELLS", "BLOOD", "SALIVA", "FIBROBLAST", "TISSUE"]}], "doc": ""}, {"name": "preparationMethod", "type": ["null", {"type": "enum", "name": "PreparationMethod", "symbols": ["EDTA", "ORAGENE", "FF", "FFPE", "CD128_SORTED_CELLS", "ASPIRATE"]}], "doc": ""}, {"name": "tissueSource", "type": ["null", {"type": "enum", "name": "TissueSource", "symbols": ["BMA_TUMOUR_SORTED_CELLS", "CT_GUIDED_BIOPSY", "ENDOSCOPIC_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_BIOPSY", "ENDOSCOPIC_ULTRASOUND_GUIDED_FNA", "LAPAROSCOPIC_BIOPSY", "LAPAROSCOPIC_EXCISION", "MRI_GUIDED_BIOPSY", "NON_GUIDED_BIOPSY", "SURGICAL_RESECTION", "STEREOTACTICALLY_GUIDED_BIOPSY", "USS_GUIDED_BIOPSY", "NON_STANDARD_BIOPSY"]}], "doc": ""}, {"name": "product", "type": ["null", {"type": "enum", "name": "Product", "symbols": ["DNA", "RNA"]}], "doc": ""}, {"name": "morphologyICD", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "morphologySnomedRT", "type": ["null", "string"], "doc": ""}, {"name": "topographyICD", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedCT", "type": ["null", "string"], "doc": ""}, {"name": "topographySnomedRT", "type": ["null", "string"], "doc": ""}]} """ schema = avro_parse(_schemaSource) requiredFields = { "LDPCode", "clinicalSampleDateTime", "diseaseSubType", "diseaseType", "labSampleId", "morphologyICD", "morphologySnomedCT", "morphologySnomedRT", "preparationMethod", "product", "programmePhase", "sampleId", "source", "tissueSource", "topographyICD", "topographySnomedCT", "topographySnomedRT", "tumourContent", "tumourId", "tumourType", } @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'LDPCode', 'clinicalSampleDateTime', 'diseaseSubType', 'diseaseType', 'labSampleId', 'morphologyICD', 'morphologySnomedCT', 'morphologySnomedRT', 'preparationMethod', 'product', 'programmePhase', 'sampleId', 'source', 'tissueSource', 'topographyICD', 'topographySnomedCT', 'topographySnomedRT', 'tumourContent', 'tumourId', 'tumourType' ] def __init__(self, **kwargs): self.LDPCode = kwargs.get( 'LDPCode', None) self.clinicalSampleDateTime = kwargs.get( 'clinicalSampleDateTime', None) self.diseaseSubType = kwargs.get( 'diseaseSubType', None) self.diseaseType = kwargs.get( 'diseaseType', None) self.labSampleId = kwargs.get( 'labSampleId', None) self.morphologyICD = kwargs.get( 'morphologyICD', None) self.morphologySnomedCT = kwargs.get( 'morphologySnomedCT', None) self.morphologySnomedRT = kwargs.get( 'morphologySnomedRT', None) self.preparationMethod = kwargs.get( 'preparationMethod', None) self.product = kwargs.get( 'product', None) self.programmePhase = kwargs.get( 'programmePhase', None) self.sampleId = kwargs.get( 'sampleId', None) self.source = kwargs.get( 'source', None) self.tissueSource = kwargs.get( 'tissueSource', None) self.topographyICD = kwargs.get( 'topographyICD', None) self.topographySnomedCT = kwargs.get( 'topographySnomedCT', None) self.topographySnomedRT = kwargs.get( 'topographySnomedRT', None) self.tumourContent = kwargs.get( 'tumourContent', None) self.tumourId = kwargs.get( 'tumourId', None) self.tumourType = kwargs.get( 'tumourType', None) class TumourType(object): """ No documentation """ PRIMARY = "PRIMARY" METASTATIC_RECURRENCE = "METASTATIC_RECURRENCE" RECURRENCE_OF_PRIMARY_TUMOUR = "RECURRENCE_OF_PRIMARY_TUMOUR" METASTASES = "METASTASES" def __hash__(self): return str(self).__hash__() class VersionControl(ProtocolElement): """ No documentation """ _schemaSource = """ {"type": "record", "name": "VersionControl", "namespace": "org.gel.models.participant.avro", "fields": [{"name": "GitVersionControl", "type": "string", "doc": "", "default": "1.0.3"}]} """ schema = avro_parse(_schemaSource) requiredFields = {} @classmethod def isEmbeddedType(cls, fieldName): embeddedTypes = {} return fieldName in embeddedTypes @classmethod def getEmbeddedType(cls, fieldName): embeddedTypes = {} return embeddedTypes[fieldName] __slots__ = [ 'GitVersionControl' ] def __init__(self, **kwargs): self.GitVersionControl = kwargs.get( 'GitVersionControl', '1.0.3') class diseaseType(object): """ No documentation """ ADULT_GLIOMA = "ADULT_GLIOMA" BLADDER = "BLADDER" BREAST = "BREAST" CARCINOMA_OF_UNKNOWN_PRIMARY = "CARCINOMA_OF_UNKNOWN_PRIMARY" CHILDHOOD = "CHILDHOOD" COLORECTAL = "COLORECTAL" ENDOMETRIAL_CARCINOMA = "ENDOMETRIAL_CARCINOMA" HAEMONC = "HAEMONC" HEPATOPANCREATOBILIARY = "HEPATOPANCREATOBILIARY" LUNG = "LUNG" MALIGNANT_MELANOMA = "MALIGNANT_MELANOMA" NASOPHARYNGEAL = "NASOPHARYNGEAL" ORAL_OROPHARYNGEAL = "ORAL_OROPHARYNGEAL" OVARIAN = "OVARIAN" PROSTATE = "PROSTATE" RENAL = "RENAL" SARCOMA = "SARCOMA" SINONASAL = "SINONASAL" TESTICULAR_GERM_CELL_TUMOURS = "TESTICULAR_GERM_CELL_TUMOURS" UPPER_GASTROINTESTINAL = "UPPER_GASTROINTESTINAL" NON_HODGKINS_B_CELL_LYMPHOMA_LOW_MOD_GRADE = "NON_HODGKINS_B_CELL_LYMPHOMA_LOW_MOD_GRADE" CLASSICAL_HODGKINS = "CLASSICAL_HODGKINS" NODULAR_LYMPHOCYTE_PREDOMINANT_HODGKINS = "NODULAR_LYMPHOCYTE_PREDOMINANT_HODGKINS" T_CELL_LYMPHOMA = "T_CELL_LYMPHOMA" def __hash__(self): return str(self).__hash__()

41.471562

100

0.585817

6,942

80,206

6.657736

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0.033493

0.029772

0.755983

0.727812

0.69923

0.665801

0.619694

0.609157

0

0.001588

0.191482

80,206

1,933

101

41.493016

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0.003251

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0

null

0

1

0

1

0

1

0

null

0

5

fc02e55ee42e94f6f2e37688fcd818c62a2c20ae

159

py

Python

verboze/asgi.py

Verbozeteam/web

2aecd67ec823e9d6ac243d6f8a71849dd0f9ed9d

[ "MIT" ]

1

2018-12-17T15:31:03.000Z

verboze/asgi.py

Verbozeteam/web

2aecd67ec823e9d6ac243d6f8a71849dd0f9ed9d

[ "MIT" ]

null

verboze/asgi.py

Verbozeteam/web

2aecd67ec823e9d6ac243d6f8a71849dd0f9ed9d

[ "MIT" ]

null

import os from channels.asgi import get_channel_layer os.environ.setdefault("DJANGO_SETTINGS_MODULE", "verboze.settings") channel_layer = get_channel_layer()

26.5

67

0.836478

22

159

5.727273

0.636364

0.285714

0.238095

0

0.075472

159

6

68

26.5

0.857143

0

0.2375

0.1375

0

1

0

false

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

fc2bfa287025df1cec20e4b0d7bf89211c912705

520

py

Python

authentication/admin.py

luisza/vcl_django

43d04f7951cb8805502e51f6f6360c7ec63215cc

[ "Apache-2.0" ]

null

authentication/admin.py

luisza/vcl_django

43d04f7951cb8805502e51f6f6360c7ec63215cc

[ "Apache-2.0" ]

null

authentication/admin.py

luisza/vcl_django

43d04f7951cb8805502e51f6f6360c7ec63215cc

[ "Apache-2.0" ]

null

from django.contrib import admin # Register your models here. from authentication.models import (User, Usergroup, Usergroupmembers, Shibauth, Localauth) admin.site.register([User, Usergroup, Usergroupmembers, Shibauth, Localauth])

37.142857

53

0.363462

26

520

7.269231

0.615385

0.137566

0.306878

0.391534

0.486772

0

0.598077

520

14

54

37.142857

0.904306

0.05

0

0.545455

0

1

0

true

0

0.181818

0

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0

1

0

null

0

1

0

1

0

null

0

1

0

5

fc3871378a173b9f757032dbb802ee8af2aed424

38

py

Python

teste.py

buggers/bugfactory.github.io

364a57033750930337dbe1f7c39583db815467b4

[ "MIT" ]

null

teste.py

buggers/bugfactory.github.io

364a57033750930337dbe1f7c39583db815467b4

[ "MIT" ]

null

teste.py

buggers/bugfactory.github.io

364a57033750930337dbe1f7c39583db815467b4

[ "MIT" ]

null

name = raw_input('dasdsa') print name

12.666667

26

0.736842

6

38

4.5

0.833333

0

0.131579

38

2

27

19

0.818182

0

0.157895

0

null

0

null

0.5

1

0

null

0

1

0

null

0

1

0

1

0

5

fc4098a041905e68a2b8847659b0e1079bf89f06

431

py

Python

tests/rules/test_ls_lah.py

lardnicus/oops

2cabcdb6726f4583f954d5f3671574bd18c7fdf2

[ "MIT" ]

null

tests/rules/test_ls_lah.py

lardnicus/oops

2cabcdb6726f4583f954d5f3671574bd18c7fdf2

[ "MIT" ]

null

tests/rules/test_ls_lah.py

lardnicus/oops

2cabcdb6726f4583f954d5f3671574bd18c7fdf2

[ "MIT" ]

null

from mock import patch, Mock from oops.rules.ls_lah import match, get_new_command def test_match(): assert match(Mock(script='ls file.py'), None) assert match(Mock(script='ls /opt'), None) assert not match(Mock(script='ls -lah /opt'), None) def test_get_new_command(): assert get_new_command(Mock(script='ls file.py'), None) == 'ls -lah file.py' assert get_new_command(Mock(script='ls'), None) == 'ls -lah'

30.785714

80

0.693735

71

431

4.056338

0.295775

0.173611

0.208333

0.177083

0.444444

0.326389

0.215278

0

0.153132

431

13

81

33.153846

0.789041

0

0.146172

0

0.555556

1

0.222222

true

0

0.222222

0

0.444444

0

null

0

1

0

null

0

1

0

1

0

5

fc59861de2584c2668ef54b7e10277a29ef393b9

197

py

Python

twitteruser/admin.py

BethanyFolino/twitterclone

7dcdde05786575e2508f9ecde148202f387f9128

[ "MIT" ]

null

twitteruser/admin.py

BethanyFolino/twitterclone

7dcdde05786575e2508f9ecde148202f387f9128

[ "MIT" ]

null

twitteruser/admin.py

BethanyFolino/twitterclone

7dcdde05786575e2508f9ecde148202f387f9128

[ "MIT" ]

null

from django.contrib import admin from django.contrib.auth.admin import UserAdmin from twitteruser.models import TwitterUser # Register your models here. admin.site.register(TwitterUser, UserAdmin)

32.833333

47

0.84264

26

197

6.384615

0.5

0.120482

0.204819

0

0.096447

197

6

48

32.833333

0.932584

0.13198

0

1

0

true

0

0.75

0

0.75

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

5d92cf25118e4fef71a470b08908134836789b26

312

py

Python

poker_utils.py

zouyapeng/Texas-Hold-em-Player

d4b4ec12325845a894cfb66f885a2f2d067c04f5

[ "Apache-2.0" ]

null

poker_utils.py

zouyapeng/Texas-Hold-em-Player

d4b4ec12325845a894cfb66f885a2f2d067c04f5

[ "Apache-2.0" ]

null

poker_utils.py

zouyapeng/Texas-Hold-em-Player

d4b4ec12325845a894cfb66f885a2f2d067c04f5

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # @Time : 2018/6/29 11:24 # @Author : Bob Zou # @Mail : bob_zou@trendmicro.com # @File : poker_utils # @Software: PyCharm # @Function: from django.db import models class Player(models.Model): pass class Game(models.Model): pass class Round(models.Model): pass

14.857143

35

0.634615

43

312

4.55814

0.744186

0.168367

0.229592

0.204082

0

0.049383

0.221154

312

21

36

14.857143

0.757202

0.49359

0

0.428571

0

1

0

true

0.428571

0.142857

0

0.571429

0

null

0

1

0

null

0

1

0

1

0

5

5da77a712d591729ceb71914f14335724537545c

31

py

Python

masq/cms/utils/__init__.py

tehdiplomat/hidden-role-games

e6fdc132700db8d12fd57f08200a499cdc5bef7d

[ "MIT" ]

null

masq/cms/utils/__init__.py

tehdiplomat/hidden-role-games

e6fdc132700db8d12fd57f08200a499cdc5bef7d

[ "MIT" ]

null

masq/cms/utils/__init__.py

tehdiplomat/hidden-role-games

e6fdc132700db8d12fd57f08200a499cdc5bef7d

[ "MIT" ]

null

#from cms.models.polls import *

31

0.774194

5

31

4.8

1

0

0.096774

31

1

31

0.857143

0.967742

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

5dbefca05b30757d26ac684fa5ad02e5eeaf40b1

199

py

Python

hypernets/conf/__init__.py

Enpen/Hypernets

5fbf01412ffaef310855d98f52f8cc169e96246b

[ "Apache-2.0" ]

1,080

2020-06-22T07:44:22.000Z

2022-03-22T07:46:48.000Z

hypernets/conf/__init__.py

Enpen/Hypernets

5fbf01412ffaef310855d98f52f8cc169e96246b

[ "Apache-2.0" ]

24

2020-08-06T02:06:37.000Z

2022-03-31T03:34:35.000Z

hypernets/conf/__init__.py

Enpen/Hypernets

5fbf01412ffaef310855d98f52f8cc169e96246b

[ "Apache-2.0" ]

170

2020-08-14T08:39:18.000Z

2022-03-23T12:58:17.000Z

from traitlets import Unicode, Unicode as String, Bool, Int, Float, Enum, List, Dict, Union from ._configuration import Configurable, configure, observe, configure_and_observe, generate_config_file

49.75

105

0.819095

26

199

6.076923

0.807692

0

0.115578

199

3

106

66.333333

0.897727

0

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

5dc443510a3b499f63cbbb49e60128bb0c0707ac

8,303

py

Python

04 - Parser/src/lexer/unicode_chars.py

masyagin1998/TFL

e92bedd513855348e1e5648e91abecc3b5c1ad10

[ "MIT" ]

7

2018-10-05T13:12:00.000Z

2021-06-08T08:49:11.000Z

04 - Parser/src/lexer/unicode_chars.py

masyagin1998/TFL

e92bedd513855348e1e5648e91abecc3b5c1ad10

[ "MIT" ]

null

04 - Parser/src/lexer/unicode_chars.py

masyagin1998/TFL

e92bedd513855348e1e5648e91abecc3b5c1ad10

[ "MIT" ]

null

# 'Uppercase letter (Lu)', 'Lowercase letter (Ll)', # 'Titlecase letter(Lt)', 'Modifier letter (Lm)', 'Other letter (Lo)' LETTER = ( u'[A-Za-z\xaa\xb5\xba\xc0-\xd6\xd8-\xf6' u'\xf8-\u02c1\u02c6-\u02d1\u02e0-\u02e4\u02ec\u02ee\u0370-\u0374\u0376' u'\u0377\u037a-\u037d\u0386\u0388-\u038a\u038c\u038e-\u03a1\u03a3-\u03f5' u'\u03f7-\u0481\u048a-\u0523\u0531-\u0556\u0559\u0561-\u0587\u05d0-\u05ea' u'\u05f0-\u05f2\u0621-\u064a\u066e\u066f\u0671-\u06d3\u06d5\u06e5\u06e6' u'\u06ee\u06ef\u06fa-\u06fc\u06ff\u0710\u0712-\u072f\u074d-\u07a5\u07b1' u'\u07ca-\u07ea\u07f4\u07f5\u07fa\u0904-\u0939\u093d\u0950\u0958-\u0961' u'\u0971\u0972\u097b-\u097f\u0985-\u098c\u098f\u0990\u0993-\u09a8' u'\u09aa-\u09b0\u09b2\u09b6-\u09b9\u09bd\u09ce\u09dc\u09dd\u09df-\u09e1' u'\u09f0\u09f1\u0a05-\u0a0a\u0a0f\u0a10\u0a13-\u0a28\u0a2a-\u0a30\u0a32' u'\u0a33\u0a35\u0a36\u0a38\u0a39\u0a59-\u0a5c\u0a5e\u0a72-\u0a74' u'\u0a85-\u0a8d\u0a8f-\u0a91\u0a93-\u0aa8\u0aaa-\u0ab0\u0ab2\u0ab3' u'\u0ab5-\u0ab9\u0abd\u0ad0\u0ae0\u0ae1\u0b05-\u0b0c\u0b0f\u0b10' u'\u0b13-\u0b28\u0b2a-\u0b30\u0b32\u0b33\u0b35-\u0b39\u0b3d\u0b5c\u0b5d' u'\u0b5f-\u0b61\u0b71\u0b83\u0b85-\u0b8a\u0b8e-\u0b90\u0b92-\u0b95\u0b99' u'\u0b9a\u0b9c\u0b9e\u0b9f\u0ba3\u0ba4\u0ba8-\u0baa\u0bae-\u0bb9\u0bd0' u'\u0c05-\u0c0c\u0c0e-\u0c10\u0c12-\u0c28\u0c2a-\u0c33\u0c35-\u0c39\u0c3d' u'\u0c58\u0c59\u0c60\u0c61\u0c85-\u0c8c\u0c8e-\u0c90\u0c92-\u0ca8' u'\u0caa-\u0cb3\u0cb5-\u0cb9\u0cbd\u0cde\u0ce0\u0ce1\u0d05-\u0d0c' u'\u0d0e-\u0d10\u0d12-\u0d28\u0d2a-\u0d39\u0d3d\u0d60\u0d61\u0d7a-\u0d7f' u'\u0d85-\u0d96\u0d9a-\u0db1\u0db3-\u0dbb\u0dbd\u0dc0-\u0dc6\u0e01-\u0e30' u'\u0e32\u0e33\u0e40-\u0e46\u0e81\u0e82\u0e84\u0e87\u0e88\u0e8a\u0e8d' u'\u0e94-\u0e97\u0e99-\u0e9f\u0ea1-\u0ea3\u0ea5\u0ea7\u0eaa\u0eab' u'\u0ead-\u0eb0\u0eb2\u0eb3\u0ebd\u0ec0-\u0ec4\u0ec6\u0edc\u0edd\u0f00' u'\u0f40-\u0f47\u0f49-\u0f6c\u0f88-\u0f8b\u1000-\u102a\u103f\u1050-\u1055' u'\u105a-\u105d\u1061\u1065\u1066\u106e-\u1070\u1075-\u1081\u108e' u'\u10a0-\u10c5\u10d0-\u10fa\u10fc\u1100-\u1159\u115f-\u11a2\u11a8-\u11f9' u'\u1200-\u1248\u124a-\u124d\u1250-\u1256\u1258\u125a-\u125d\u1260-\u1288' u'\u128a-\u128d\u1290-\u12b0\u12b2-\u12b5\u12b8-\u12be\u12c0\u12c2-\u12c5' u'\u12c8-\u12d6\u12d8-\u1310\u1312-\u1315\u1318-\u135a\u1380-\u138f' u'\u13a0-\u13f4\u1401-\u166c\u166f-\u1676\u1681-\u169a\u16a0-\u16ea' u'\u1700-\u170c\u170e-\u1711\u1720-\u1731\u1740-\u1751\u1760-\u176c' u'\u176e-\u1770\u1780-\u17b3\u17d7\u17dc\u1820-\u1877\u1880-\u18a8\u18aa' u'\u1900-\u191c\u1950-\u196d\u1970-\u1974\u1980-\u19a9\u19c1-\u19c7' u'\u1a00-\u1a16\u1b05-\u1b33\u1b45-\u1b4b\u1b83-\u1ba0\u1bae\u1baf' u'\u1c00-\u1c23\u1c4d-\u1c4f\u1c5a-\u1c7d\u1d00-\u1dbf\u1e00-\u1f15' u'\u1f18-\u1f1d\u1f20-\u1f45\u1f48-\u1f4d\u1f50-\u1f57\u1f59\u1f5b\u1f5d' u'\u1f5f-\u1f7d\u1f80-\u1fb4\u1fb6-\u1fbc\u1fbe\u1fc2-\u1fc4\u1fc6-\u1fcc' u'\u1fd0-\u1fd3\u1fd6-\u1fdb\u1fe0-\u1fec\u1ff2-\u1ff4\u1ff6-\u1ffc\u2071' u'\u207f\u2090-\u2094\u2102\u2107\u210a-\u2113\u2115\u2119-\u211d\u2124' u'\u2126\u2128\u212a-\u212d\u212f-\u2139\u213c-\u213f\u2145-\u2149\u214e' u'\u2183\u2184\u2c00-\u2c2e\u2c30-\u2c5e\u2c60-\u2c6f\u2c71-\u2c7d' u'\u2c80-\u2ce4\u2d00-\u2d25\u2d30-\u2d65\u2d6f\u2d80-\u2d96\u2da0-\u2da6' u'\u2da8-\u2dae\u2db0-\u2db6\u2db8-\u2dbe\u2dc0-\u2dc6\u2dc8-\u2dce' u'\u2dd0-\u2dd6\u2dd8-\u2dde\u2e2f\u3005\u3006\u3031-\u3035\u303b\u303c' u'\u3041-\u3096\u309d-\u309f\u30a1-\u30fa\u30fc-\u30ff\u3105-\u312d' u'\u3131-\u318e\u31a0-\u31b7\u31f0-\u31ff\u3400\u4db5\u4e00\u9fc3' u'\ua000-\ua48c\ua500-\ua60c\ua610-\ua61f\ua62a\ua62b\ua640-\ua65f' u'\ua662-\ua66e\ua67f-\ua697\ua717-\ua71f\ua722-\ua788\ua78b\ua78c' u'\ua7fb-\ua801\ua803-\ua805\ua807-\ua80a\ua80c-\ua822\ua840-\ua873' u'\ua882-\ua8b3\ua90a-\ua925\ua930-\ua946\uaa00-\uaa28\uaa40-\uaa42' u'\uaa44-\uaa4b\uac00\ud7a3\uf900-\ufa2d\ufa30-\ufa6a\ufa70-\ufad9' u'\ufb00-\ufb06\ufb13-\ufb17\ufb1d\ufb1f-\ufb28\ufb2a-\ufb36\ufb38-\ufb3c' u'\ufb3e\ufb40\ufb41\ufb43\ufb44\ufb46-\ufbb1\ufbd3-\ufd3d\ufd50-\ufd8f' u'\ufd92-\ufdc7\ufdf0-\ufdfb\ufe70-\ufe74\ufe76-\ufefc\uff21-\uff3a' u'\uff41-\uff5a\uff66-\uffbe\uffc2-\uffc7\uffca-\uffcf\uffd2-\uffd7' u'\uffda-\uffdc]' ) NON_SPACING_MARK = ( u'[\u0300-\u036f\u0483-\u0487\u0591-\u05bd\u05bf\u05c1\u05c2\u05c4\u05c5' u'\u05c7\u0610-\u061a\u064b-\u065e\u0670\u06d6-\u06dc\u06df-\u06e4\u06e7' u'\u06e8\u06ea-\u06ed\u0711\u0730-\u074a\u07a6-\u07b0\u07eb-\u07f3' u'\u0816-\u0819\u081b-\u0823\u0825-\u0827\u0829-\u082d\u0900-\u0902\u093c' u'\u0941-\u0948\u094d\u0951-\u0955\u0962\u0963\u0981\u09bc\u09c1-\u09c4' u'\u09cd\u09e2\u09e3\u0a01\u0a02\u0a3c\u0a41\u0a42\u0a47\u0a48' u'\u0a4b-\u0a4d\u0a51\u0a70\u0a71\u0a75\u0a81\u0a82\u0abc\u0ac1-\u0ac5' u'\u0ac7\u0ac8\u0acd\u0ae2\u0ae3\u0b01\u0b3c\u0b3f\u0b41-\u0b44\u0b4d' u'\u0b56\u0b62\u0b63\u0b82\u0bc0\u0bcd\u0c3e-\u0c40\u0c46-\u0c48' u'\u0c4a-\u0c4d\u0c55\u0c56\u0c62\u0c63\u0cbc\u0cbf\u0cc6\u0ccc\u0ccd' u'\u0ce2\u0ce3\u0d41-\u0d44\u0d4d\u0d62\u0d63\u0dca\u0dd2-\u0dd4\u0dd6' u'\u0e31\u0e34-\u0e3a\u0e47-\u0e4e\u0eb1\u0eb4-\u0eb9\u0ebb\u0ebc' u'\u0ec8-\u0ecd\u0f18\u0f19\u0f35\u0f37\u0f39\u0f71-\u0f7e\u0f80-\u0f84' u'\u0f86\u0f87\u0f90-\u0f97\u0f99-\u0fbc\u0fc6\u102d-\u1030\u1032-\u1037' u'\u1039\u103a\u103d\u103e\u1058\u1059\u105e-\u1060\u1071-\u1074\u1082' u'\u1085\u1086\u108d\u109d\u135f\u1712-\u1714\u1732-\u1734\u1752\u1753' u'\u1772\u1773\u17b7-\u17bd\u17c6\u17c9-\u17d3\u17dd\u180b-\u180d\u18a9' u'\u1920-\u1922\u1927\u1928\u1932\u1939-\u193b\u1a17\u1a18\u1a56' u'\u1a58-\u1a5e\u1a60\u1a62\u1a65-\u1a6c\u1a73-\u1a7c\u1a7f\u1b00-\u1b03' u'\u1b34\u1b36-\u1b3a\u1b3c\u1b42\u1b6b-\u1b73\u1b80\u1b81\u1ba2-\u1ba5' u'\u1ba8\u1ba9\u1c2c-\u1c33\u1c36\u1c37\u1cd0-\u1cd2\u1cd4-\u1ce0' u'\u1ce2-\u1ce8\u1ced\u1dc0-\u1de6\u1dfd-\u1dff\u20d0-\u20dc\u20e1' u'\u20e5-\u20f0\u2cef-\u2cf1\u2de0-\u2dff\u302a-\u302f\u3099\u309a\ua66f' u'\ua67c\ua67d\ua6f0\ua6f1\ua802\ua806\ua80b\ua825\ua826\ua8c4' u'\ua8e0-\ua8f1\ua926-\ua92d\ua947-\ua951\ua980-\ua982\ua9b3\ua9b6-\ua9b9' u'\ua9bc\uaa29-\uaa2e\uaa31\uaa32\uaa35\uaa36\uaa43\uaa4c\uaab0' u'\uaab2-\uaab4\uaab7\uaab8\uaabe\uaabf\uaac1\uabe5\uabe8\uabed\ufb1e' u'\ufe00-\ufe0f\ufe20-\ufe26]' ) COMBINING_SPACING_MARK = ( u'[\u0903\u093e-\u0940\u0949-\u094c\u094e\u0982\u0983\u09be-\u09c0\u09c7' u'\u09c8\u09cb\u09cc\u09d7\u0a03\u0a3e-\u0a40\u0a83\u0abe-\u0ac0\u0ac9' u'\u0acb\u0acc\u0b02\u0b03\u0b3e\u0b40\u0b47\u0b48\u0b4b\u0b4c\u0b57' u'\u0bbe\u0bbf\u0bc1\u0bc2\u0bc6-\u0bc8\u0bca-\u0bcc\u0bd7\u0c01-\u0c03' u'\u0c41-\u0c44\u0c82\u0c83\u0cbe\u0cc0-\u0cc4\u0cc7\u0cc8\u0cca\u0ccb' u'\u0cd5\u0cd6\u0d02\u0d03\u0d3e-\u0d40\u0d46-\u0d48\u0d4a-\u0d4c\u0d57' u'\u0d82\u0d83\u0dcf-\u0dd1\u0dd8-\u0ddf\u0df2\u0df3\u0f3e\u0f3f\u0f7f' u'\u102b\u102c\u1031\u1038\u103b\u103c\u1056\u1057\u1062-\u1064' u'\u1067-\u106d\u1083\u1084\u1087-\u108c\u108f\u109a-\u109c\u17b6' u'\u17be-\u17c5\u17c7\u17c8\u1923-\u1926\u1929-\u192b\u1930\u1931' u'\u1933-\u1938\u19b0-\u19c0\u19c8\u19c9\u1a19-\u1a1b\u1a55\u1a57\u1a61' u'\u1a63\u1a64\u1a6d-\u1a72\u1b04\u1b35\u1b3b\u1b3d-\u1b41\u1b43\u1b44' u'\u1b82\u1ba1\u1ba6\u1ba7\u1baa\u1c24-\u1c2b\u1c34\u1c35\u1ce1\u1cf2' u'\ua823\ua824\ua827\ua880\ua881\ua8b4-\ua8c3\ua952\ua953\ua983\ua9b4' u'\ua9b5\ua9ba\ua9bb\ua9bd-\ua9c0\uaa2f\uaa30\uaa33\uaa34\uaa4d\uaa7b' u'\uabe3\uabe4\uabe6\uabe7\uabe9\uabea\uabec]' ) COMBINING_MARK = u'%s|%s' % (NON_SPACING_MARK, COMBINING_SPACING_MARK) CONNECTOR_PUNCTUATION = u'[_\u203f\u2040\u2054\ufe33\ufe34\ufe4d-\ufe4f\uff3f]' DIGIT = ( u'[0-9\u0660-\u0669\u06f0-\u06f9\u07c0-\u07c9\u0966-\u096f' u'\u09e6-\u09ef\u0a66-\u0a6f\u0ae6-\u0aef\u0b66-\u0b6f\u0be6-\u0bef' # noqa: E501,W293 u'\u0c66-\u0c6f\u0ce6-\u0cef\u0d66-\u0d6f\u0e50-\u0e59\u0ed0-\u0ed9' u'\u0f20-\u0f29\u1040-\u1049\u1090-\u1099\u17e0-\u17e9\u1810-\u1819' u'\u1946-\u194f\u19d0-\u19da\u1a80-\u1a89\u1a90-\u1a99\u1b50-\u1b59' u'\u1bb0-\u1bb9\u1c40-\u1c49\u1c50-\u1c59\ua620-\ua629\ua8d0-\ua8d9' u'\ua900-\ua909\ua9d0-\ua9d9\uaa50-\uaa59\uabf0-\uabf9\uff10-\uff19]' )

65.896825

91

0.716247

1,279

8,303

4.641126

0.902267

0.007412

0.004717

0

0.381304

0.071059

8,303

125

92

66.424

0.388305

0.016018

0

0.516949

0.872153

0.869826

0

1

0

false

0

null

0

1

0

1

0

1

null

0

5

b901c47f70787cd225f7c34a4b0d9be27f96a5ed

163

py

Python

main/admin.py

aryaputra28/covidify-PerancanganWeb

34d6d0017f44248c172fc58e6e1b138e23e68a95

[ "Unlicense" ]

null

main/admin.py

aryaputra28/covidify-PerancanganWeb

34d6d0017f44248c172fc58e6e1b138e23e68a95

[ "Unlicense" ]

null

main/admin.py

aryaputra28/covidify-PerancanganWeb

34d6d0017f44248c172fc58e6e1b138e23e68a95

[ "Unlicense" ]

null

from django.contrib import admin from .models import Feedback, Pengguna # Register your models here. admin.site.register(Feedback) admin.site.register(Pengguna)

20.375

38

0.809816

22

163

6

0.545455

0.136364

0.257576

0

0.110429

163

7

39

23.285714

0.910345

0.159509

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

f8dce1cd078e8ee2d1412f7a1f2231d26e3e0ce3

390

py

Python

Python-Leetcode/Array/1365. How Many Numbers Are Smaller Than the Current Number.py

HughesZhang73/Python-Master

607110e4326f4b51ffa7e2ade4edcecd26e52298

[ "MIT" ]

2

2020-11-05T02:32:14.000Z

2020-12-22T14:06:38.000Z

Python-Leetcode/Array/1365. How Many Numbers Are Smaller Than the Current Number.py

HughesZhang73/Python-Master

607110e4326f4b51ffa7e2ade4edcecd26e52298

[ "MIT" ]

null

Python-Leetcode/Array/1365. How Many Numbers Are Smaller Than the Current Number.py

HughesZhang73/Python-Master

607110e4326f4b51ffa7e2ade4edcecd26e52298

[ "MIT" ]

null

# def smallerNumbersThanCurrent(nums: list) -> list: # ans = [] # for i in nums: # temp = nums.copy() # count = 0 # temp.remove(i) # for j in temp: # if i > j: # count += 1 # ans.append(count) # return ans def smallerNumbersThanCurrent(nums: list) -> list: print(smallerNumbersThanCurrent([8,1,2,2,3]))

18.571429

52

0.512821

44

390

4.545455

0.5

0.28

0.32

0.36

0.4

0

0.027668

0.351282

390

21

53

18.571429

0.762846

0.571795

0

null

0

null

0.5

0

null

1

0

null

0

1

0

1

0

5

f8e1b3c3bfda7e3c52c777386b177f051ccbf65f

50

py

Python

animatplot/testing/__init__.py

eric-erki/animatplot

38a24c3301fbb82a237758fc42f6f4d59275721f

[ "MIT" ]

null

animatplot/testing/__init__.py

eric-erki/animatplot

38a24c3301fbb82a237758fc42f6f4d59275721f

[ "MIT" ]

null

animatplot/testing/__init__.py

eric-erki/animatplot

38a24c3301fbb82a237758fc42f6f4d59275721f

[ "MIT" ]

null

from .tools import BunchOFiles, animation_compare

25

49

0.86

6

50

7

1

0

0.1

50

1

50

0.933333

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

5d07a1d5afad6d91bf9fc20883cadff0f4f50b98

130

py

Python

worker.py

AndreAmorim05/flask-celery-mail

b95cb3b02c805980b8d7aef9d7d851fe8b5fc6fe

[ "MIT" ]

null

worker.py

AndreAmorim05/flask-celery-mail

b95cb3b02c805980b8d7aef9d7d851fe8b5fc6fe

[ "MIT" ]

null

worker.py

AndreAmorim05/flask-celery-mail

b95cb3b02c805980b8d7aef9d7d851fe8b5fc6fe

[ "MIT" ]

null

from flaskcelerymail.app import create_app from flaskcelerymail.ext.celery import init_celery celery = init_celery(create_app())

26

50

0.846154

18

130

5.888889

0.444444

0.358491

0

0.092308

130

4

51

32.5

0.898305

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

5d3b376046eba5518bad4b6446bb9ed2904e6966

59

py

Python

pudb/contrib/__init__.py

georgepar/pudb

c7c213604ab136a5de87fa465ceed910d7f3eee2

[ "MIT" ]

null

pudb/contrib/__init__.py

georgepar/pudb

c7c213604ab136a5de87fa465ceed910d7f3eee2

[ "MIT" ]

null

pudb/contrib/__init__.py

georgepar/pudb

c7c213604ab136a5de87fa465ceed910d7f3eee2

[ "MIT" ]

null

from pudb.contrib.stringifiers import CONTRIB_STRINGIFIERS

29.5

58

0.898305

7

59

7.428571

0.714286

0.730769

0

0.067797

59

1

59

0.945455

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

5d3ccfc7062c62710c12e72708e15729ffbb2703

201

py

Python

geoshops/nearbyshops/admin.py

syberflea/materials

54f44725b40edf00c1b523d7a85b34a85014d7eb

[ "MIT" ]

3,682

2018-05-07T19:45:24.000Z

2022-03-31T15:19:10.000Z

geoshops/nearbyshops/admin.py

sribarrow/materials

c17c4a4d6f8487e59eac1df8c88ca92b73d6d2a5

[ "MIT" ]

148

2018-05-15T21:18:49.000Z

2022-03-21T11:25:39.000Z

geoshops/nearbyshops/admin.py

sribarrow/materials

c17c4a4d6f8487e59eac1df8c88ca92b73d6d2a5

[ "MIT" ]

5,535

2018-05-25T23:36:08.000Z

2022-03-31T16:55:52.000Z

from django.contrib import admin from django.contrib.gis.admin import OSMGeoAdmin from .models import Shop @admin.register(Shop) class ShopAdmin(OSMGeoAdmin): list_display = ("name", "location")

22.333333

48

0.776119

26

201

5.961538

0.615385

0.129032

0.219355

0

0.124378

201

8

49

25.125

0.880682

0

0.059701

0

1

0

false

0

0.5

0

0.833333

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

5d48872c3d41eb2019401f606940704906b7f049

116

py

Python

script/generate.py

tetianakravchenko/beats

6aec024e0ab8239791be20885d6d3c58697d18cd

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

9,729

2015-12-02T12:44:19.000Z

2022-03-31T13:26:12.000Z

script/generate.py

tetianakravchenko/beats

6aec024e0ab8239791be20885d6d3c58697d18cd

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

25,281

2015-12-02T08:46:55.000Z

2022-03-31T23:26:12.000Z

script/generate.py

tetianakravchenko/beats

6aec024e0ab8239791be20885d6d3c58697d18cd

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

5,239

2015-12-02T09:22:33.000Z

2022-03-31T15:11:58.000Z

if __name__ == "__main__": print("This script is deprecated. Please use `mage GenerateCustomBeat`") exit(1)

29

76

0.698276

14

116

5.214286

1

0

0.010526

0.181034

116

3

77

38.666667

0.757895

0

1

0

0.612069

0

1

0

true

0

0.333333

1

0

null

0

1

0

1

0

1

0

null

0

1

0

5

5d5fc1e755feccff20038e384ab6d6679e61167b

19,937

py

Python

staff_manage_sdk/model/topboard/issue_pb2.py

easyopsapis/easyops-api-python

adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0

[ "Apache-2.0" ]

5

2019-07-31T04:11:05.000Z

2021-01-07T03:23:20.000Z

staff_manage_sdk/model/topboard/issue_pb2.py

easyopsapis/easyops-api-python

adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0

[ "Apache-2.0" ]

null

staff_manage_sdk/model/topboard/issue_pb2.py

easyopsapis/easyops-api-python

adf6e3bad33fa6266b5fa0a449dd4ac42f8447d0

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: issue.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) 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 staff_manage_sdk.model.topboard import product_pb2 as staff__manage__sdk_dot_model_dot_topboard_dot_product__pb2 from staff_manage_sdk.model.topboard import sprint_pb2 as staff__manage__sdk_dot_model_dot_topboard_dot_sprint__pb2 from staff_manage_sdk.model.cmdb import user_pb2 as staff__manage__sdk_dot_model_dot_cmdb_dot_user__pb2 from staff_manage_sdk.model.topboard import attachment_pb2 as staff__manage__sdk_dot_model_dot_topboard_dot_attachment__pb2 from staff_manage_sdk.model.topboard import comment_pb2 as staff__manage__sdk_dot_model_dot_topboard_dot_comment__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='issue.proto', package='topboard', syntax='proto3', serialized_options=_b('ZBgo.easyops.local/contracts/protorepo-models/easyops/model/topboard'), serialized_pb=_b('\n\x0bissue.proto\x12\x08topboard\x1a-staff_manage_sdk/model/topboard/product.proto\x1a,staff_manage_sdk/model/topboard/sprint.proto\x1a&staff_manage_sdk/model/cmdb/user.proto\x1a\x30staff_manage_sdk/model/topboard/attachment.proto\x1a-staff_manage_sdk/model/topboard/comment.proto\"\xc4\x06\n\x05Issue\x12\x1f\n\x06parent\x18\x01 \x03(\x0b\x32\x0f.topboard.Issue\x12!\n\x08subtasks\x18\x02 \x03(\x0b\x32\x0f.topboard.Issue\x12\"\n\x07product\x18\x03 \x03(\x0b\x32\x11.topboard.Product\x12 \n\x06sprint\x18\x04 \x03(\x0b\x32\x10.topboard.Sprint\x12\x1f\n\x0bsubscribers\x18\x05 \x03(\x0b\x32\n.cmdb.User\x12\x1c\n\x08\x61ssignee\x18\x06 \x03(\x0b\x32\n.cmdb.User\x12\x1c\n\x08reporter\x18\x07 \x03(\x0b\x32\n.cmdb.User\x12)\n\x0b\x61ttachments\x18\x08 \x03(\x0b\x32\x14.topboard.Attachment\x12#\n\x08\x63omments\x18\t \x03(\x0b\x32\x11.topboard.Comment\x12,\n\tissueFrom\x18\n \x03(\x0b\x32\x19.topboard.Issue.IssueFrom\x12\x1a\n\x06tester\x18\x0b \x03(\x0b\x32\n.cmdb.User\x12\x0c\n\x04name\x18\x0c \x01(\t\x12\x12\n\ninstanceId\x18\r \x01(\t\x12\x0f\n\x07\x63reator\x18\x0e \x01(\t\x12\r\n\x05\x63time\x18\x0f \x01(\t\x12\r\n\x05title\x18\x10 \x01(\t\x12\x13\n\x0b\x64\x65scription\x18\x11 \x01(\t\x12\x10\n\x08priority\x18\x12 \x01(\t\x12\x0c\n\x04type\x18\x13 \x01(\t\x12\x0c\n\x04step\x18\x14 \x01(\t\x12$\n\x05links\x18\x15 \x03(\x0b\x32\x15.topboard.Issue.Links\x12\x12\n\nstoryPoint\x18\x16 \x01(\t\x12\x12\n\nresolution\x18\x17 \x01(\t\x12\x0e\n\x06status\x18\x18 \x01(\t\x12&\n\x06images\x18\x19 \x03(\x0b\x32\x16.topboard.Issue.Images\x12\x0f\n\x07\x62ugType\x18\x1a \x01(\t\x12\x16\n\x0eresponsibility\x18\x1b \x01(\t\x1a-\n\tIssueFrom\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x12\n\ninstanceId\x18\x02 \x01(\t\x1a#\n\x05Links\x12\r\n\x05title\x18\x01 \x01(\t\x12\x0b\n\x03url\x18\x02 \x01(\t\x1a#\n\x06Images\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x0b\n\x03url\x18\x02 \x01(\tBDZBgo.easyops.local/contracts/protorepo-models/easyops/model/topboardb\x06proto3') , dependencies=[staff__manage__sdk_dot_model_dot_topboard_dot_product__pb2.DESCRIPTOR,staff__manage__sdk_dot_model_dot_topboard_dot_sprint__pb2.DESCRIPTOR,staff__manage__sdk_dot_model_dot_cmdb_dot_user__pb2.DESCRIPTOR,staff__manage__sdk_dot_model_dot_topboard_dot_attachment__pb2.DESCRIPTOR,staff__manage__sdk_dot_model_dot_topboard_dot_comment__pb2.DESCRIPTOR,]) _ISSUE_ISSUEFROM = _descriptor.Descriptor( name='IssueFrom', full_name='topboard.Issue.IssueFrom', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='name', full_name='topboard.Issue.IssueFrom.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=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='instanceId', full_name='topboard.Issue.IssueFrom.instanceId', index=1, number=2, 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), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=973, serialized_end=1018, ) _ISSUE_LINKS = _descriptor.Descriptor( name='Links', full_name='topboard.Issue.Links', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='title', full_name='topboard.Issue.Links.title', 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=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='url', full_name='topboard.Issue.Links.url', index=1, number=2, 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), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1020, serialized_end=1055, ) _ISSUE_IMAGES = _descriptor.Descriptor( name='Images', full_name='topboard.Issue.Images', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='name', full_name='topboard.Issue.Images.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=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='url', full_name='topboard.Issue.Images.url', index=1, number=2, 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), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1057, serialized_end=1092, ) _ISSUE = _descriptor.Descriptor( name='Issue', full_name='topboard.Issue', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='parent', full_name='topboard.Issue.parent', index=0, number=1, 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), _descriptor.FieldDescriptor( name='subtasks', full_name='topboard.Issue.subtasks', index=1, number=2, 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), _descriptor.FieldDescriptor( name='product', full_name='topboard.Issue.product', index=2, number=3, 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), _descriptor.FieldDescriptor( name='sprint', full_name='topboard.Issue.sprint', index=3, number=4, 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), _descriptor.FieldDescriptor( name='subscribers', full_name='topboard.Issue.subscribers', index=4, number=5, 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), _descriptor.FieldDescriptor( name='assignee', full_name='topboard.Issue.assignee', index=5, number=6, 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), _descriptor.FieldDescriptor( name='reporter', full_name='topboard.Issue.reporter', index=6, number=7, 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), _descriptor.FieldDescriptor( name='attachments', full_name='topboard.Issue.attachments', index=7, number=8, 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), _descriptor.FieldDescriptor( name='comments', full_name='topboard.Issue.comments', index=8, number=9, 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), _descriptor.FieldDescriptor( name='issueFrom', full_name='topboard.Issue.issueFrom', index=9, number=10, 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), _descriptor.FieldDescriptor( name='tester', full_name='topboard.Issue.tester', index=10, number=11, 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), _descriptor.FieldDescriptor( name='name', full_name='topboard.Issue.name', index=11, number=12, 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), _descriptor.FieldDescriptor( name='instanceId', full_name='topboard.Issue.instanceId', index=12, number=13, 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), _descriptor.FieldDescriptor( name='creator', full_name='topboard.Issue.creator', index=13, number=14, 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), _descriptor.FieldDescriptor( name='ctime', full_name='topboard.Issue.ctime', index=14, number=15, 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), _descriptor.FieldDescriptor( name='title', full_name='topboard.Issue.title', index=15, number=16, 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), _descriptor.FieldDescriptor( name='description', full_name='topboard.Issue.description', index=16, number=17, 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), _descriptor.FieldDescriptor( name='priority', full_name='topboard.Issue.priority', index=17, number=18, 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), _descriptor.FieldDescriptor( name='type', full_name='topboard.Issue.type', index=18, number=19, 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), _descriptor.FieldDescriptor( name='step', full_name='topboard.Issue.step', index=19, number=20, 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), _descriptor.FieldDescriptor( name='links', full_name='topboard.Issue.links', index=20, number=21, 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), _descriptor.FieldDescriptor( name='storyPoint', full_name='topboard.Issue.storyPoint', index=21, number=22, 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), _descriptor.FieldDescriptor( name='resolution', full_name='topboard.Issue.resolution', index=22, number=23, 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), _descriptor.FieldDescriptor( name='status', full_name='topboard.Issue.status', index=23, number=24, 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), _descriptor.FieldDescriptor( name='images', full_name='topboard.Issue.images', index=24, number=25, 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), _descriptor.FieldDescriptor( name='bugType', full_name='topboard.Issue.bugType', index=25, number=26, 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), _descriptor.FieldDescriptor( name='responsibility', full_name='topboard.Issue.responsibility', index=26, number=27, 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), ], extensions=[ ], nested_types=[_ISSUE_ISSUEFROM, _ISSUE_LINKS, _ISSUE_IMAGES, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=256, serialized_end=1092, ) _ISSUE_ISSUEFROM.containing_type = _ISSUE _ISSUE_LINKS.containing_type = _ISSUE _ISSUE_IMAGES.containing_type = _ISSUE _ISSUE.fields_by_name['parent'].message_type = _ISSUE _ISSUE.fields_by_name['subtasks'].message_type = _ISSUE _ISSUE.fields_by_name['product'].message_type = staff__manage__sdk_dot_model_dot_topboard_dot_product__pb2._PRODUCT _ISSUE.fields_by_name['sprint'].message_type = staff__manage__sdk_dot_model_dot_topboard_dot_sprint__pb2._SPRINT _ISSUE.fields_by_name['subscribers'].message_type = staff__manage__sdk_dot_model_dot_cmdb_dot_user__pb2._USER _ISSUE.fields_by_name['assignee'].message_type = staff__manage__sdk_dot_model_dot_cmdb_dot_user__pb2._USER _ISSUE.fields_by_name['reporter'].message_type = staff__manage__sdk_dot_model_dot_cmdb_dot_user__pb2._USER _ISSUE.fields_by_name['attachments'].message_type = staff__manage__sdk_dot_model_dot_topboard_dot_attachment__pb2._ATTACHMENT _ISSUE.fields_by_name['comments'].message_type = staff__manage__sdk_dot_model_dot_topboard_dot_comment__pb2._COMMENT _ISSUE.fields_by_name['issueFrom'].message_type = _ISSUE_ISSUEFROM _ISSUE.fields_by_name['tester'].message_type = staff__manage__sdk_dot_model_dot_cmdb_dot_user__pb2._USER _ISSUE.fields_by_name['links'].message_type = _ISSUE_LINKS _ISSUE.fields_by_name['images'].message_type = _ISSUE_IMAGES DESCRIPTOR.message_types_by_name['Issue'] = _ISSUE _sym_db.RegisterFileDescriptor(DESCRIPTOR) Issue = _reflection.GeneratedProtocolMessageType('Issue', (_message.Message,), { 'IssueFrom' : _reflection.GeneratedProtocolMessageType('IssueFrom', (_message.Message,), { 'DESCRIPTOR' : _ISSUE_ISSUEFROM, '__module__' : 'issue_pb2' # @@protoc_insertion_point(class_scope:topboard.Issue.IssueFrom) }) , 'Links' : _reflection.GeneratedProtocolMessageType('Links', (_message.Message,), { 'DESCRIPTOR' : _ISSUE_LINKS, '__module__' : 'issue_pb2' # @@protoc_insertion_point(class_scope:topboard.Issue.Links) }) , 'Images' : _reflection.GeneratedProtocolMessageType('Images', (_message.Message,), { 'DESCRIPTOR' : _ISSUE_IMAGES, '__module__' : 'issue_pb2' # @@protoc_insertion_point(class_scope:topboard.Issue.Images) }) , 'DESCRIPTOR' : _ISSUE, '__module__' : 'issue_pb2' # @@protoc_insertion_point(class_scope:topboard.Issue) }) _sym_db.RegisterMessage(Issue) _sym_db.RegisterMessage(Issue.IssueFrom) _sym_db.RegisterMessage(Issue.Links) _sym_db.RegisterMessage(Issue.Images) DESCRIPTOR._options = None # @@protoc_insertion_point(module_scope)

48.508516

1,988

0.744295

2,729

19,937

5.117259

0.083547

0.059005

0.042392

0.055639

0.72961

0.711493

0.702757

0.661797

0.643108

0.636591

0

0.042593

0.125044

19,937

410

1,989

48.626829

0.757968

0.020364

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false

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0

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0.013123

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null

0

1

0

1

0

1

0

1

0

null

0

5

5d60686c602365067559a8bbce499b8ec83fb080

31

py

Python

keypad_racer/__main__.py

encukou/keypad-racer

57a832b3e0d06aa79f2205630b5da563cf2d09c5

[ "MIT", "CC-BY-3.0", "Unlicense" ]

null

keypad_racer/__main__.py

encukou/keypad-racer

57a832b3e0d06aa79f2205630b5da563cf2d09c5

[ "MIT", "CC-BY-3.0", "Unlicense" ]

null

keypad_racer/__main__.py

encukou/keypad-racer

57a832b3e0d06aa79f2205630b5da563cf2d09c5

[ "MIT", "CC-BY-3.0", "Unlicense" ]

null

from . import game game.run()

7.75

18

0.677419

5

31

4.2

0.8

0

0.193548

31

3

19

10.333333

0.84

0

1

0

true

0

0.5

0

0.5

0

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0

1

0

null

0

1

0

1

0

5

5d63b63c62b854775a623df503481ff000d7e47f

774

py

Python

mystocks_backend/venv/lib/python3.8/site-packages/flask_jwt_extended/__init__.py

SQinSQi/SQ_StockWeb

a33cae33e5648575132d0ea442d100f93c79afb2

[ "MIT" ]

1

2022-02-17T02:49:08.000Z

mystocks_backend/venv/lib/python3.8/site-packages/flask_jwt_extended/__init__.py

SQinSQi/SQ_StockWeb

a33cae33e5648575132d0ea442d100f93c79afb2

[ "MIT" ]

null

mystocks_backend/venv/lib/python3.8/site-packages/flask_jwt_extended/__init__.py

SQinSQi/SQ_StockWeb

a33cae33e5648575132d0ea442d100f93c79afb2

[ "MIT" ]

null

from .jwt_manager import JWTManager from .utils import create_access_token from .utils import create_refresh_token from .utils import current_user from .utils import decode_token from .utils import get_csrf_token from .utils import get_current_user from .utils import get_jti from .utils import get_jwt from .utils import get_jwt_header from .utils import get_jwt_identity from .utils import get_jwt_request_location from .utils import get_unverified_jwt_headers from .utils import set_access_cookies from .utils import set_refresh_cookies from .utils import unset_access_cookies from .utils import unset_jwt_cookies from .utils import unset_refresh_cookies from .view_decorators import jwt_required from .view_decorators import verify_jwt_in_request __version__ = "4.2.3"

33.652174

50

0.859173

123

774

5.056911

0.276423

0.245981

0.409968

0.231511

0.477492

0

0.004348

0.108527

774

22

51

35.181818

0.897101

0

0.00646

0

1

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false

0

0.952381

0

0.952381

0

null

1

0

null

0

1

0

1

0

5

5d6f55f027a516654816f74633e8c1a5e1954df8

191

py

Python

vmaig_blog/uwsgi-2.0.14/contrib/spoolqueue/tasks.py

StanYaha/Blog

3cb38918e14ebe6ce2e2952ef272de116849910d

[ "BSD-3-Clause" ]

1

2018-11-24T16:10:49.000Z

vmaig_blog/uwsgi-2.0.14/contrib/spoolqueue/tasks.py

StanYaha/Blog

3cb38918e14ebe6ce2e2952ef272de116849910d

[ "BSD-3-Clause" ]

null

vmaig_blog/uwsgi-2.0.14/contrib/spoolqueue/tasks.py

StanYaha/Blog

3cb38918e14ebe6ce2e2952ef272de116849910d

[ "BSD-3-Clause" ]

null

from tasksconsumer import * @queueconsumer('fast', 4) def fast_queue(arguments): print "fast", arguments @queueconsumer('slow') def slow_queue(arguments): print "foobar", arguments

19.1

29

0.732984

22

191

6.272727

0.545455

0.202899

0.275362

0

0.006098

0.141361

191

9

30

21.222222

0.835366

0

0.094241

0

null

0

0.142857

null

0.285714

1

0

null

1

0

1

0

null

0

1

0

5

5d74d40b0e9d141426776ad9ac6c5bb76b1ee147

431

py

Python

dnsdb_mock_apiserver/models.py

dnsdb-team/dnsdb-mock-apiserver

7a03d98406fea0e4145fdfbebb433982d984b1e8

[ "BSD-4-Clause" ]

null

dnsdb_mock_apiserver/models.py

dnsdb-team/dnsdb-mock-apiserver

7a03d98406fea0e4145fdfbebb433982d984b1e8

[ "BSD-4-Clause" ]

null

dnsdb_mock_apiserver/models.py

dnsdb-team/dnsdb-mock-apiserver

7a03d98406fea0e4145fdfbebb433982d984b1e8

[ "BSD-4-Clause" ]

null

# -*- coding: utf-8 -*- from __future__ import print_function import json class User(object): def __init__(self, username, password, remaining_request=100): self.username = username self.password = password self.remaining_request = remaining_request def __str__(self): return json.dumps({'username': self.username, 'password': self.password, 'remaining_request': self.remaining_request})

30.785714

126

0.707657

49

431

5.857143

0.469388

0.278746

0.139373

0

0.011364

0.183295

431

13

127

33.153846

0.803977

0.048724

0

0.080882

0

1

0.222222

false

0.333333

0.222222

0.111111

0.666667

0.111111

0

null

1

0

null

0

1

0

1

0

1

0

5

53ab6e69eb15056a9b07033531e1c18cc28fb36d

112

py

Python

meet_and_play/game_announcement/admin.py

ImIFilm/meet_and_play_project

316301b2ce474f3470da342b53196b9c901cc234

[ "MIT" ]

null

meet_and_play/game_announcement/admin.py

ImIFilm/meet_and_play_project

316301b2ce474f3470da342b53196b9c901cc234

[ "MIT" ]

null

meet_and_play/game_announcement/admin.py

ImIFilm/meet_and_play_project

316301b2ce474f3470da342b53196b9c901cc234

[ "MIT" ]

null

from django.contrib import admin from .models import Game_Announcement admin.site.register(Game_Announcement)

18.666667

38

0.848214

15

112

6.2

0.666667

0.344086

0

0.098214

112

5

39

22.4

0.920792

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

53de071ee95e5f3377e87d91689f726e2c04c537

311

py

Python

hypergan/backends/cpu_backend.py

limberc/HyperGAN

b074e74abf0ed9b81bd52084706e3707a47e0fe2

[ "MIT" ]

889

2016-08-27T01:37:35.000Z

2018-10-07T19:47:56.000Z

hypergan/backends/cpu_backend.py

limberc/HyperGAN

b074e74abf0ed9b81bd52084706e3707a47e0fe2

[ "MIT" ]

101

2016-11-30T03:34:02.000Z

2018-10-02T13:50:52.000Z

hypergan/backends/cpu_backend.py

limberc/HyperGAN

b074e74abf0ed9b81bd52084706e3707a47e0fe2

[ "MIT" ]

145

2016-09-27T06:56:24.000Z

2018-09-25T16:09:28.000Z

from .backend import Backend class CPUBackend(Backend): def __init__(self, trainable_gan, devices): self.trainable_gan = trainable_gan self.trainable_gan.to('cpu') def save(self): self.trainable_gan.save_locally() def step(self): self.trainable_gan.trainer.step()

23.923077

47

0.681672

39

311

5.153846

0.435897

0.358209

0.39801

0.199005

0

0.215434

311

12

48

25.916667

0.82377

0

0.009646

0

1

0.333333

false

0

0.111111

0

0.555556

0

null

1

0

null

0

1

0

1

0

5

0708f7008c14ca7428978f4c27143d65469e8eb0

46

py

Python

Chapter 01/Chap01_Example1.152.py

Anancha/Programming-Techniques-using-Python

e80c329d2a27383909d358741a5cab03cb22fd8b

[ "MIT" ]

null

Chapter 01/Chap01_Example1.152.py

Anancha/Programming-Techniques-using-Python

e80c329d2a27383909d358741a5cab03cb22fd8b

[ "MIT" ]

null

Chapter 01/Chap01_Example1.152.py

Anancha/Programming-Techniques-using-Python

e80c329d2a27383909d358741a5cab03cb22fd8b

[ "MIT" ]

null

fs3 = {1,2,3,4} f1 = frozenset(fs3) f1[0] = 5

11.5

19

0.543478

11

46

2.272727

0.818182

0

0.27027

0.195652

46

3

20

15.333333

0.405405

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

5

074a0633017dbe5352afc6bf9bba945e2431059b

25

py

Python

Sorting/Counting_sort.py

Toughee/Code-samples

08ea6815f6bffee8fd2c31180e7a3bcb905d6106

[ "MIT" ]

null

Sorting/Counting_sort.py

Toughee/Code-samples

08ea6815f6bffee8fd2c31180e7a3bcb905d6106

[ "MIT" ]

null

Sorting/Counting_sort.py

Toughee/Code-samples

08ea6815f6bffee8fd2c31180e7a3bcb905d6106

[ "MIT" ]

null

# Counting sort algorithm

25

0.84

3

25

7

1

0

0.12

25

1

25

0.954545

0.92

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

074c2577c954260ae0854f5abcd1e0f1d9e8a7d1

78

py

Python

apps/project/models/__init__.py

picsldev/pyerp

e998e3e99a4e45033d54a6b1df50697f7288f67f

[ "MIT" ]

115

2019-08-18T16:12:54.000Z

2022-03-29T14:17:20.000Z

apps/project/models/__init__.py

picsldev/pyerp

e998e3e99a4e45033d54a6b1df50697f7288f67f

[ "MIT" ]

22

2019-09-09T01:34:54.000Z

2022-03-12T00:33:40.000Z

apps/project/models/__init__.py

picsldev/pyerp

e998e3e99a4e45033d54a6b1df50697f7288f67f

[ "MIT" ]

83

2019-08-17T17:09:20.000Z

2022-03-25T04:46:53.000Z

from .bug import PyBug from .project import PyProject from .task import PyTask

26

30

0.820513

12

78

5.333333

0.666667

0

0.141026

78

3

31

26

0.955224

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

4aebc1d2337d6d279043a7d0cf2caaf92ac8be3d

9,135

py

Python

tests/Turbomole/test_Turbomole.py

CMargreitter/Icolos

fd7b664ce177df875fefa910dc4d5c574b521cb3

[ "Apache-2.0" ]

11

2022-01-30T14:36:13.000Z

2022-03-22T09:40:57.000Z

tests/Turbomole/test_Turbomole.py

CMargreitter/Icolos

fd7b664ce177df875fefa910dc4d5c574b521cb3

[ "Apache-2.0" ]

2

2022-03-23T07:56:49.000Z

2022-03-24T12:01:42.000Z

tests/Turbomole/test_Turbomole.py

CMargreitter/Icolos

fd7b664ce177df875fefa910dc4d5c574b521cb3

[ "Apache-2.0" ]

8

2022-01-28T10:32:31.000Z

2022-03-22T09:40:59.000Z

import unittest import os from icolos.core.workflow_steps.calculation.turbomole import StepTurbomole from icolos.utils.enums.step_enums import StepBaseEnum, StepTurbomoleEnum from icolos.utils.enums.program_parameters import TurbomoleEnum from tests.tests_paths import ( PATHS_EXAMPLEDATA, export_unit_test_env_vars, get_mol_as_Compound, get_mol_as_Conformer, MAIN_CONFIG, ) from icolos.utils.enums.compound_enums import ConformerContainerEnum from icolos.utils.general.files_paths import attach_root_path import time _SBE = StepBaseEnum _TE = TurbomoleEnum() _COE = ConformerContainerEnum() _STE = StepTurbomoleEnum() class Test_Turbomole(unittest.TestCase): @classmethod def setUpClass(cls): cls._test_dir = attach_root_path("tests/junk/Turbomole") if not os.path.isdir(cls._test_dir): os.makedirs(cls._test_dir) export_unit_test_env_vars() def setUp(self): # initialize a Compound with 1 Enumeration and 2 Conformers (done by OMEGA) _paracetamol_molecule = get_mol_as_Compound(PATHS_EXAMPLEDATA.PARACETAMOL_PATH) confs = get_mol_as_Conformer(PATHS_EXAMPLEDATA.CLUSTERING_11CONFS) _paracetamol_molecule[0].add_conformers(confs, auto_update=True) self._paracetamol_molecule = _paracetamol_molecule @classmethod def tearDownClass(cls): pass def test_Turbomole_run_ridft_single_core(self): step_conf = { _SBE.STEPID: "01_turbomole", _SBE.STEP_TYPE: _SBE.STEP_TURBOMOLE, _SBE.EXEC: { _SBE.EXEC_PREFIXEXECUTION: "module load turbomole/73", _SBE.EXEC_PARALLELIZATION: {_SBE.EXEC_PARALLELIZATION_CORES: 1}, }, _SBE.SETTINGS: { _SBE.SETTINGS_ARGUMENTS: { _SBE.SETTINGS_ARGUMENTS_FLAGS: [], _SBE.SETTINGS_ARGUMENTS_PARAMETERS: {}, }, _SBE.SETTINGS_ADDITIONAL: { _TE.TM_CONFIG_DIR: MAIN_CONFIG["TURBOMOLE_CONFIG"], _TE.TM_CONFIG_BASENAME: "b97-3c-ri-d3-def2-mtzvp-int-nosym-charge", _TE.TM_CONFIG_COSMO: os.path.join( MAIN_CONFIG["TURBOMOLE_CONFIG"], "cosmoprep_eps80.tm" ), _STE.EXECUTION_MODE: _TE.TM_RIDFT, }, }, } os.environ["PARA_ARCH"] = "MPI" os.environ["PARNODES"] = "4" tm_step = StepTurbomole(**step_conf) tm_step.data.compounds = [self._paracetamol_molecule] # conformer coordinates should not be touched by the execution self.assertListEqual( list( tm_step.get_compounds()[0][0][0] .get_molecule() .GetConformer(0) .GetPositions()[0] ), [0.8785, 0.6004, -0.2173], ) tm_step.execute() self.assertListEqual( list( tm_step.get_compounds()[0][0][0] .get_molecule() .GetConformer(0) .GetPositions()[0] ), [0.8785, 0.6004, -0.2173], ) cosmofile = tm_step.get_compounds()[0][0][0].get_extra_data()[ _COE.EXTRA_DATA_COSMOFILE ] coordfile = tm_step.get_compounds()[0][0][0].get_extra_data()[ _COE.EXTRA_DATA_COORDFILE ] self.assertTrue("basgrd points= 9806" in cosmofile[5]) # check write-out out_path = os.path.join(self._test_dir, "paracetamol_conf1_CosmoFile") with open(out_path, "w") as f: f.writelines(cosmofile) stat_inf = os.stat(out_path) self.assertEqual(stat_inf.st_size, 132018) out_path = os.path.join(self._test_dir, "paracetamol_conf1_CoordFile") with open(out_path, "w") as f: f.writelines(coordfile) stat_inf = os.stat(out_path) self.assertEqual(stat_inf.st_size, 13544) def test_Turbomole_run_ridft_dual_core(self): step_conf = { _SBE.STEPID: "01_turbomole", _SBE.STEP_TYPE: _SBE.STEP_TURBOMOLE, _SBE.EXEC: { _SBE.EXEC_PREFIXEXECUTION: "module load turbomole/73", _SBE.EXEC_PARALLELIZATION: {_SBE.EXEC_PARALLELIZATION_CORES: 2}, }, _SBE.SETTINGS: { _SBE.SETTINGS_ARGUMENTS: { _SBE.SETTINGS_ARGUMENTS_FLAGS: [], _SBE.SETTINGS_ARGUMENTS_PARAMETERS: {}, }, _SBE.SETTINGS_ADDITIONAL: { _TE.TM_CONFIG_DIR: MAIN_CONFIG["TURBOMOLE_CONFIG"], _TE.TM_CONFIG_BASENAME: "b97-3c-ri-d3-def2-mtzvp-int-nosym-charge", _TE.TM_CONFIG_COSMO: os.path.join( MAIN_CONFIG["TURBOMOLE_CONFIG"], "cosmoprep_eps80.tm" ), _STE.EXECUTION_MODE: _TE.TM_RIDFT, }, }, } os.environ["PARA_ARCH"] = "MPI" os.environ["PARNODES"] = "4" tm_step = StepTurbomole(**step_conf) tm_step.data.compounds = [self._paracetamol_molecule] # conformer coordinates should not be touched by the execution self.assertListEqual( list( tm_step.get_compounds()[0][0][0] .get_molecule() .GetConformer(0) .GetPositions()[0] ), [5.3347, 12.9328, 24.6745], ) t1 = time.time() tm_step.execute() t2 = time.time() self.assertLess(t2 - t1, 50) self.assertListEqual( list( tm_step.get_compounds()[0][0][0] .get_molecule() .GetConformer(0) .GetPositions()[0] ), [0.8785, 0.6004, -0.2173], ) cosmofile = tm_step.get_compounds()[0][0][0].get_extra_data()[ _COE.EXTRA_DATA_COSMOFILE ] coordfile = tm_step.get_compounds()[0][0][0].get_extra_data()[ _COE.EXTRA_DATA_COORDFILE ] self.assertTrue("basgrd points= 9806" in cosmofile[5]) # check write-out out_path = os.path.join(self._test_dir, "paracetamol_conf1_CosmoFile") with open(out_path, "w") as f: f.writelines(cosmofile) stat_inf = os.stat(out_path) self.assertEqual(stat_inf.st_size, 132018) out_path = os.path.join(self._test_dir, "paracetamole_conf1_CoordFile") with open(out_path, "w") as f: f.writelines(coordfile) stat_inf = os.stat(out_path) self.assertEqual(stat_inf.st_size, 13544) def test_Turbomole_run_jobex(self): step_conf = { _SBE.STEPID: "01_turbomole", _SBE.STEP_TYPE: _SBE.STEP_TURBOMOLE, _SBE.EXEC: { _SBE.EXEC_PREFIXEXECUTION: "module load turbomole/73", _SBE.EXEC_PARALLELIZATION: {_SBE.EXEC_PARALLELIZATION_CORES: 2}, }, _SBE.SETTINGS: { _SBE.SETTINGS_ARGUMENTS: { _SBE.SETTINGS_ARGUMENTS_FLAGS: ["-ri"], _SBE.SETTINGS_ARGUMENTS_PARAMETERS: { _TE.TM_JOBEX_C: 70, _TE.TM_JOBEX_GCART: 3, }, }, _SBE.SETTINGS_ADDITIONAL: { _TE.TM_CONFIG_DIR: MAIN_CONFIG["TURBOMOLE_CONFIG"], _TE.TM_CONFIG_BASENAME: "b97-3c-ri-d3-def2-mtzvp-int-charge", _TE.TM_CONFIG_COSMO: os.path.join( MAIN_CONFIG["TURBOMOLE_CONFIG"], "cosmoprep_eps80.tm" ), _STE.EXECUTION_MODE: _TE.TM_JOBEX, }, }, } os.environ["PARA_ARCH"] = "MPI" os.environ["PARNODES"] = "3" tm_step = StepTurbomole(**step_conf) tm_step.data.compounds = [self._paracetamol_molecule] # conformer coordinates should be touched by the execution (this is geo opt) self.assertListEqual( list( tm_step.get_compounds()[0][0][0] .get_molecule() .GetConformer(0) .GetPositions()[0] ), [5.3347, 12.9328, 24.6745], ) tm_step.execute() self.assertListEqual( list( tm_step.get_compounds()[0][0][0] .get_molecule() .GetConformer(0) .GetPositions()[0] ), [-0.7887, -0.0618, 0.1129], ) cosmofile = tm_step.get_compounds()[0][0][0].get_extra_data()[ _COE.EXTRA_DATA_COSMOFILE ] self.assertTrue("nspa= 92" in cosmofile[5]) # check write-out out_path = os.path.join(self._test_dir, "paracetamol_conf1_CosmoFile_jobex") with open(out_path, "w") as f: f.writelines(cosmofile) stat_inf = os.stat(out_path) self.assertEqual(stat_inf.st_size, 115864)

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Blob_Lib/assimp-5.2.3/assimp/port/PyAssimp/pyassimp/errors.py

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andrewp-as-is/octicons16px.py

1272dc9f290619d83bd881e87dbd723b0c48844c

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2021-01-28T06:47:39.000Z

octicons16px/dash.py

andrewp-as-is/octicons16px.py

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octicons16px/dash.py

andrewp-as-is/octicons16px.py

1272dc9f290619d83bd881e87dbd723b0c48844c

[ "Unlicense" ]

null

OCTICON_DASH = """ <svg class="octicon octicon-dash" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" width="16" height="16"><path fill-rule="evenodd" d="M2 8a.75.75 0 01.75-.75h10.5a.75.75 0 010 1.5H2.75A.75.75 0 012 8z"></path></svg> """

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notramp/__init__.py

simakro/NoTrAmp

a11b43700de494c8676fd0bb51242499283dbbd0

[ "BSD-2-Clause" ]

null

notramp/__init__.py

simakro/NoTrAmp

a11b43700de494c8676fd0bb51242499283dbbd0

[ "BSD-2-Clause" ]

null

notramp/__init__.py

simakro/NoTrAmp

a11b43700de494c8676fd0bb51242499283dbbd0

[ "BSD-2-Clause" ]

null

#Copyright (c) 2022, Simon Magin (simakro) #BSD-2 license #see LICENSE file for license details #__doc__= """ NoTrAmp is a Tool for read-depth normalization and trimming of amplicon reads generated with long read technologies (ONT/PacBio). """ # import os from .version import __version__

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twoops_tracker/py/twoopstracker/authentication/apps.py

CodeForAfrica/api

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[ "MIT" ]

null

twoops_tracker/py/twoopstracker/authentication/apps.py

CodeForAfrica/api

c4c79225c27284052aced8dd0805108885766308

[ "MIT" ]

null

twoops_tracker/py/twoopstracker/authentication/apps.py

CodeForAfrica/api

c4c79225c27284052aced8dd0805108885766308

[ "MIT" ]

null

from django.apps import AppConfig class AuthenticationConfig(AppConfig): default_auto_field = "django.db.models.BigAutoField" name = "twoopstracker.authentication" def ready(self): import twoopstracker.authentication.signals # noqa

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scrud_django/utils.py

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scrud_django/utils.py

Django-Stack-Backend/Django-backend-React-frontend

4c814ab9b97d70a259d4b93e30d118deba9831fd

[ "BSD-3-Clause" ]

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scrud_django/utils.py

Django-Stack-Backend/Django-backend-React-frontend

4c814ab9b97d70a259d4b93e30d118deba9831fd

[ "BSD-3-Clause" ]

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def link_content(url, rel, content_type): return f"<{url}>; rel=\"{rel}\"; type=\"{content_type}\"" def get_string_or_evaluate(string_or_func, *args, **kwargs): if not string_or_func: return None if isinstance(string_or_func, str): return string_or_func return string_or_func(*args, **kwargs)

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scripts/patches/groundstation.py

compose-x/troposphere

9a94a8fafd8b4da1cd1f4239be0e7aa0681fd8d4

[ "BSD-2-Clause" ]

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scripts/patches/groundstation.py

compose-x/troposphere

9a94a8fafd8b4da1cd1f4239be0e7aa0681fd8d4

[ "BSD-2-Clause" ]

null

scripts/patches/groundstation.py

compose-x/troposphere

9a94a8fafd8b4da1cd1f4239be0e7aa0681fd8d4

[ "BSD-2-Clause" ]

null

patches = [ { "op": "move", "from": "/PropertyTypes/AWS::GroundStation::Config.FrequencyBandwidth", "path": "/PropertyTypes/AWS::GroundStation::Config.Bandwidth", }, { "op": "replace", "path": "/PropertyTypes/AWS::GroundStation::Config.SpectrumConfig/Properties/Bandwidth/Type", "value": "Bandwidth", }, { "op": "replace", "path": "/PropertyTypes/AWS::GroundStation::Config.AntennaUplinkConfig/Properties/SpectrumConfig/Type", "value": "SpectrumConfig", }, { "op": "remove", "path": "/PropertyTypes/AWS::GroundStation::Config.UplinkSpectrumConfig", }, ]

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warehouse/warehouse/doctype/building_parameters/test_building_parameters.py

vijith2121/update_warehouse

a7a15784708a87fc4684377ba3617ae1889e11f1

[ "MIT" ]

null

warehouse/warehouse/doctype/building_parameters/test_building_parameters.py

vijith2121/update_warehouse

a7a15784708a87fc4684377ba3617ae1889e11f1

[ "MIT" ]

null

warehouse/warehouse/doctype/building_parameters/test_building_parameters.py

vijith2121/update_warehouse

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src/english_text_normalization_tests/test_money_normalization.py

jasminsternkopf/english_text_normalization

8f797e01e8fcc7d5a83497a92a4fc204603be484

[ "MIT" ]

null

src/english_text_normalization_tests/test_money_normalization.py

jasminsternkopf/english_text_normalization

8f797e01e8fcc7d5a83497a92a4fc204603be484

[ "MIT" ]

null

src/english_text_normalization_tests/test_money_normalization.py

jasminsternkopf/english_text_normalization

8f797e01e8fcc7d5a83497a92a4fc204603be484

[ "MIT" ]

null

from english_text_normalization.adjustments.money_normalization import ( normalize_pence, normalize_pounds, normalize_pounds_shillings_and_pence, normalize_shillings, normalize_shillings_and_pounds_with_dots, normalize_shillings_and_pounds_without_dots) # region normalize_pounds def test_normalize_pounds__number_of_pounds_contains_comma(): text = " L12,345 2s. 3d." res = normalize_pounds(text) assert res == " 12,345 pounds 2s. 3d." def test_normalize_pounds__dot_after_number_of_pounds(): text = " L12. 2s. 3d." res = normalize_pounds(text) assert res == " 12 pounds 2s. 3d." def test_normalize_pounds__only_numbers_directly_after_L(): text = " L12 2s. 3d." res = normalize_pounds(text) assert res == " 12 pounds 2s. 3d." def test_normalize_pounds__dot_after_L__no_shillings_or_pence(): text = " L.10,875,870 " res = normalize_pounds(text) assert res == " 10,875,870 pounds " def test_normalize_pounds__dot_after_L(): text = " L.499,833, 11s. 6d." res = normalize_pounds(text) assert res == " 499,833 pounds 11s. 6d." def test_normalize_pounds__space_after_L(): text = " L 12,345 2s. 3d." res = normalize_pounds(text) assert res == " 12,345 pounds 2s. 3d." def test_normalize_pounds__dot_and_space_after_L(): text = " L. 12,345 2s. 3d." res = normalize_pounds(text) assert res == " 12,345 pounds 2s. 3d." def test_normalize_pounds__one_pound(): text = " L.1 2s. 3d." res = normalize_pounds(text) assert res == " one pound 2s. 3d." def test_normalize_pounds__one_and_comma_after_L_but_is_not_one(): text = " L.1,000 2s. 3d." res = normalize_pounds(text) assert res == " 1,000 pounds 2s. 3d." # endregion # region normalize_shillings def test_normalize_shillings__dot_and_space_after_s(): text = " 2s. 3d." res = normalize_shillings(text) assert res == " 2 shillings 3d." def test_normalize_shillings__dot_and_space_after_number(): text = " 2 s. 3 d." res = normalize_shillings(text) assert res == " 2 shillings 3 d." def test_normalize_shillings__space_after_s(): text = " 2s 3d." res = normalize_shillings(text) assert res == " 2 shillings 3d." def test_normalize_shillings__only_dot_after_s(): text = " 2s.3d." res = normalize_shillings(text) assert res == " 2 shillings 3d." def test_normalize_shillings__number_of_shillings_consists_of_two_digits(): text = " 12s. 3d." res = normalize_shillings(text) assert res == " 12 shillings 3d." # endregion # region normalize_shillings_and_pounds_without_dots def test_normalize_shillings_and_pounds_without_dots__space_after_number(): text = " 2 s 3 d." res = normalize_shillings_and_pounds_without_dots(text) assert res == " 2 shillings 3 pence." def test_normalize_shillings_and_pounds_without_dots(): text = " 2s 3d." res = normalize_shillings_and_pounds_without_dots(text) assert res == " 2 shillings 3 pence." def test_normalize_shillings_and_pounds_without_dots__comma_after_shillings(): text = " 2s, 3d." res = normalize_shillings_and_pounds_without_dots(text) assert res == " 2 shillings 3 pence." # endregion # region normalize_shillings_and_pounds_with_dots def test_normalize_shillings_and_pounds_with_dots(): text = " 2s. 3d. " res = normalize_shillings_and_pounds_with_dots(text) assert res == " 2 shillings 3 pence " def test_normalize_shillings_and_pounds_with_dots__space_after_number(): text = " 2 s. 3 d. " res = normalize_shillings_and_pounds_with_dots(text) assert res == " 2 shillings 3 pence " def test_normalize_shillings_and_pounds_with_dots__comma_after_shillings(): text = " 2s., 3d. " res = normalize_shillings_and_pounds_with_dots(text) assert res == " 2 shillings 3 pence " # endregion # region normalize_pence def test_normalize_pence__one_penny(): text = " 1d. " res = normalize_pence(text) assert res == " one penny " def test_normalize_pence__one_penny__space_after_one(): text = " 1 d. " res = normalize_pence(text) assert res == " one penny " def test_normalize_pence__one_penny__no_dot_after_d(): text = " 1d " res = normalize_pence(text) assert res == " one penny " def test_normalize_pence__word_after_one_do_not_normalize(): text = " 1 dozen" res = normalize_pence(text) assert res == text def test_normalize_pence__word_after_four_do_not_normalize(): text = " 4 dozen" res = normalize_pence(text) assert res == text def test_normalize_pence__and_a_half_pence(): text = " 11-1/2d " res = normalize_pence(text) assert res == " 11 and a half pence " def test_normalize_pence__and_a_half_pence__dot_after_d(): text = " 11-1/2d. " res = normalize_pence(text) assert res == " 11 and a half pence " def test_normalize_pence__and_a_half_pence__no_hyphen_before_half(): text = " 11/2d " res = normalize_pence(text) assert res == " 1 and a half pence " def test_normalize_pence__and_a_half_pence__space_after_half(): text = " 11-1/2 d " res = normalize_pence(text) assert res == " 11 and a half pence " def test_normalize_pence__10_pence(): text = " 10d. " res = normalize_pence(text) assert res == " 10 pence " def test_normalize_pence__4_pence__space_after_number(): text = " 4 d. " res = normalize_pence(text) assert res == " 4 pence " def test_normalize_pence__4_pence__no_dot_after_d(): text = " 4d " res = normalize_pence(text) assert res == " 4 pence " def test_normalize_pence__number_of_pence_consists_of_more_than_one_char(): text = " 11-1/4d. " res = normalize_pence(text) assert res == " 11-1/4 pence " # endregion # region normalize_pounds_shillings_and_pence def test_normalize_pounds_shillings_and_pence__all_three(): text = " L12 2s. 3d. " res = normalize_pounds_shillings_and_pence(text) assert res == " 12 pounds 2 shillings 3 pence " def test_normalize_pounds_shillings_and_pence__all_three__with_commata(): text = " L12, 2s., 3d. " res = normalize_pounds_shillings_and_pence(text) assert res == " 12 pounds 2 shillings 3 pence " def test_normalize_pounds_shillings_and_pence__only_pounds(): text = " L12. " res = normalize_pounds_shillings_and_pence(text) assert res == " 12 pounds " def test_normalize_pounds_shillings_and_pence__only_shillings_and_pence_without_dots(): text = " 2s 3d " res = normalize_pounds_shillings_and_pence(text) assert res == " 2 shillings 3 pence " def test_normalize_pounds_shillings_and_pence__only_shillings_and_pence_without_spaces_but_with_dots(): text = " 2s.3d. " res = normalize_pounds_shillings_and_pence(text) assert res == " 2 shillings 3 pence " def test_normalize_pounds_shillings_and_pence__only_shillings(): text = " 3s. " res = normalize_pounds_shillings_and_pence(text) assert res == " 3 shillings " def test_normalize_pounds_shillings_and_pence__only_pence(): text = " 6d. " res = normalize_pounds_shillings_and_pence(text) assert res == " 6 pence " def test_normalize_pounds_shillings_and_pence__pence_number_contains_a_half(): text = " L1, 1s., 11/2d. " res = normalize_pounds_shillings_and_pence(text) assert res == " one pound one shilling 1 and a half pence " def test_normalize_pounds_shillings_and_pence__all_three_but_only_pence_non_zero(): text = " L0. 0s. 3d. " res = normalize_pounds_shillings_and_pence(text) assert res == " 0 pounds 0 shillings 3 pence " # endregion

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py

Python

gravtools/constants/__init__.py

JWKennington/gravtools

188229ed2061958012cf7338a5eebd2ef0a399cc

[ "MIT" ]

null

gravtools/constants/__init__.py

JWKennington/gravtools

188229ed2061958012cf7338a5eebd2ef0a399cc

[ "MIT" ]

null

gravtools/constants/__init__.py

JWKennington/gravtools

188229ed2061958012cf7338a5eebd2ef0a399cc

[ "MIT" ]

null

"""Flatten the constants package""" from .merger import MergerParameters from .observatory import Observatory

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py

Python

import_export_batches/views_admin.py

gknorman/WeVoteServer

c281d831dff8f0b3149c66d805b4e5f94be80775

[ "MIT" ]

2

2021-05-14T04:24:18.000Z

2021-10-05T05:34:13.000Z

import_export_batches/views_admin.py

gknorman/WeVoteServer

c281d831dff8f0b3149c66d805b4e5f94be80775

[ "MIT" ]

null

import_export_batches/views_admin.py

gknorman/WeVoteServer

c281d831dff8f0b3149c66d805b4e5f94be80775

[ "MIT" ]

null

# import_export_batches/views_admin.py # Brought to you by We Vote. Be good. # -*- coding: UTF-8 -*- from .models import ACTIVITY_NOTICE_PROCESS, API_REFRESH_REQUEST, \ BatchDescription, BatchHeader, BatchHeaderMap, BatchManager, \ BatchProcess, BatchProcessAnalyticsChunk, BatchProcessBallotItemChunk, BatchProcessLogEntry, BatchProcessManager, \ BatchRow, BatchRowActionBallotItem, BatchRowActionPollingLocation, \ BatchSet, \ CONTEST_OFFICE, ELECTED_OFFICE, IMPORT_BALLOT_ITEM, \ BATCH_IMPORT_KEYS_ACCEPTED_FOR_CANDIDATES, BATCH_IMPORT_KEYS_ACCEPTED_FOR_CONTEST_OFFICES, \ BATCH_IMPORT_KEYS_ACCEPTED_FOR_ELECTED_OFFICES, BATCH_IMPORT_KEYS_ACCEPTED_FOR_MEASURES, \ BATCH_IMPORT_KEYS_ACCEPTED_FOR_ORGANIZATIONS, BATCH_IMPORT_KEYS_ACCEPTED_FOR_POLITICIANS, \ BATCH_IMPORT_KEYS_ACCEPTED_FOR_POSITIONS, BATCH_IMPORT_KEYS_ACCEPTED_FOR_BALLOT_ITEMS, \ BATCH_SET_SOURCE_IMPORT_BALLOTPEDIA_BALLOT_ITEMS, BATCH_SET_SOURCE_IMPORT_CTCL_BALLOT_ITEMS, \ BATCH_SET_SOURCE_IMPORT_VOTE_USA_BALLOT_ITEMS, \ IMPORT_CREATE, IMPORT_DELETE, IMPORT_ALREADY_DELETED, IMPORT_ADD_TO_EXISTING, IMPORT_POLLING_LOCATION, \ IMPORT_VOTER, REFRESH_BALLOT_ITEMS_FROM_POLLING_LOCATIONS, \ REFRESH_BALLOT_ITEMS_FROM_VOTERS, RETRIEVE_BALLOT_ITEMS_FROM_POLLING_LOCATIONS from .controllers import create_batch_header_translation_suggestions, create_batch_row_actions, \ update_or_create_batch_header_mapping, export_voter_list_with_emails, import_data_from_batch_row_actions from .controllers_batch_process import process_next_activity_notices, process_next_ballot_items, \ process_next_general_maintenance from .controllers_ballotpedia import store_ballotpedia_json_response_to_import_batch_system from admin_tools.views import redirect_to_sign_in_page from ballot.models import BallotReturnedListManager, BallotReturnedManager, MEASURE, CANDIDATE, POLITICIAN import csv from datetime import date from django.contrib.auth.decorators import login_required from django.contrib import messages from django.contrib.messages import get_messages from django.db.models import Q from django.utils.timezone import now from django.urls import reverse from django.http import HttpResponseRedirect, HttpResponse from django.shortcuts import render from django.utils.http import urlquote from election.models import Election, ElectionManager from exception.models import handle_exception from import_export_ballotpedia.controllers import groom_ballotpedia_data_for_processing, \ process_ballotpedia_voter_districts, BALLOTPEDIA_API_SAMPLE_BALLOT_RESULTS_URL from import_export_ctcl.controllers import CTCL_VOTER_INFO_URL import json from polling_location.models import PollingLocation, PollingLocationManager from position.models import POSITION import random import requests from voter.models import voter_has_authority from voter_guide.models import ORGANIZATION_WORD import wevote_functions.admin from wevote_functions.functions import convert_to_int, positive_value_exists, STATE_CODE_MAP MAP_POINTS_RETRIEVED_EACH_BATCH_CHUNK = 125 # 125. Formerly 250 and 111 logger = wevote_functions.admin.get_logger(__name__) @login_required def batches_home_view(request): # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) # Create a voter_device_id and voter in the database if one doesn't exist yet google_civic_election_id = convert_to_int(request.GET.get('google_civic_election_id', 0)) template_values = { 'google_civic_election_id': google_civic_election_id, } response = render(request, 'import_export_batches/index.html', template_values) return response @login_required def batch_list_view(request): """ Display a list of import batches :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) kind_of_batch = request.GET.get('kind_of_batch', '') batch_file = request.GET.get('batch_file', '') batch_uri = request.GET.get('batch_uri', '') google_civic_election_id = request.GET.get('google_civic_election_id', 0) polling_location_we_vote_id = request.GET.get('polling_location_we_vote_id', '') polling_location_city = request.GET.get('polling_location_city', '') polling_location_zip = request.GET.get('polling_location_zip', '') show_all_elections = positive_value_exists(request.GET.get('show_all_elections', False)) messages_on_stage = get_messages(request) batch_list_found = False modified_batch_list = [] batch_manager = BatchManager() try: batch_list_query = BatchDescription.objects.order_by('-batch_header_id') if positive_value_exists(kind_of_batch): batch_list_query = batch_list_query.filter(kind_of_batch__iexact=kind_of_batch) if positive_value_exists(google_civic_election_id): batch_list_query = batch_list_query.filter(google_civic_election_id=google_civic_election_id) if positive_value_exists(google_civic_election_id): batch_list = list(batch_list_query) else: batch_list = batch_list_query[:50] if len(batch_list): batch_list_found = True for one_batch in batch_list: one_batch.batch_row_action_count = batch_manager.fetch_batch_row_action_count( one_batch.batch_header_id, kind_of_batch) one_batch.batch_row_action_to_update_count = batch_manager.fetch_batch_row_action_count( one_batch.batch_header_id, kind_of_batch, IMPORT_ADD_TO_EXISTING) one_batch.batch_row_count = batch_manager.fetch_batch_row_count(one_batch.batch_header_id) modified_batch_list.append(one_batch) except BatchDescription.DoesNotExist: # This is fine batch_list_found = False pass polling_location_found = False polling_location = PollingLocation() polling_location_manager = PollingLocationManager() election_state = '' if not polling_location_found and positive_value_exists(polling_location_we_vote_id): results = polling_location_manager.retrieve_polling_location_by_id(0, polling_location_we_vote_id) if results['polling_location_found']: polling_location = results['polling_location'] polling_location_we_vote_id = polling_location.we_vote_id polling_location_id = polling_location.id polling_location_found = True election_state = polling_location.state election_manager = ElectionManager() if google_civic_election_id: results = election_manager.retrieve_election(google_civic_election_id) if results['election_found']: election = results['election'] election_state = election.get_election_state() polling_location_list = [] results = polling_location_manager.retrieve_polling_locations_in_city_or_state( election_state, polling_location_city, polling_location_zip) if results['polling_location_list_found']: polling_location_list = results['polling_location_list'] if kind_of_batch == ORGANIZATION_WORD or kind_of_batch == ELECTED_OFFICE \ or kind_of_batch == POLITICIAN or kind_of_batch == IMPORT_POLLING_LOCATION: # We do not want to ask the person importing the file for an election, because it isn't used ask_for_election = False election_list = [] else: ask_for_election = True if positive_value_exists(show_all_elections): results = election_manager.retrieve_elections() election_list = results['election_list'] else: results = election_manager.retrieve_upcoming_elections() election_list = results['election_list'] # Make sure we always include the current election in the election_list, even if it is older if positive_value_exists(google_civic_election_id): this_election_found = False for one_election in election_list: if convert_to_int(one_election.google_civic_election_id) == \ convert_to_int(google_civic_election_id): this_election_found = True break if not this_election_found: results = election_manager.retrieve_election(google_civic_election_id) if results['election_found']: one_election = results['election'] election_list.append(one_election) template_values = { 'messages_on_stage': messages_on_stage, 'batch_list': modified_batch_list, 'ask_for_election': ask_for_election, 'election_list': election_list, 'kind_of_batch': kind_of_batch, 'batch_file': batch_file, 'batch_uri': batch_uri, 'google_civic_election_id': convert_to_int(google_civic_election_id), 'polling_location_we_vote_id': polling_location_we_vote_id, 'polling_location': polling_location, 'polling_location_list': polling_location_list, 'polling_location_city': polling_location_city, 'polling_location_zip': polling_location_zip, 'show_all_elections': show_all_elections, } return render(request, 'import_export_batches/batch_list.html', template_values) @login_required def batch_list_process_view(request): """ Load in a new batch to start the importing process :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) kind_of_batch = request.POST.get('kind_of_batch', '') batch_uri = request.POST.get('batch_uri', '') batch_uri_encoded = urlquote(batch_uri) if positive_value_exists(batch_uri) else "" google_civic_election_id = request.POST.get('google_civic_election_id', 0) polling_location_we_vote_id = request.POST.get('polling_location_we_vote_id', "") polling_location_city = request.POST.get('polling_location_city', '') polling_location_zip = request.POST.get('polling_location_zip', '') show_all_elections = positive_value_exists(request.POST.get('show_all_elections', "")) state_code = request.POST.get('state_code', "") if kind_of_batch not in (CANDIDATE, CONTEST_OFFICE, ELECTED_OFFICE, IMPORT_BALLOT_ITEM, IMPORT_POLLING_LOCATION, MEASURE, ORGANIZATION_WORD, POSITION, POLITICIAN): messages.add_message(request, messages.ERROR, 'The kind_of_batch is required for a batch import.') return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch) + "&google_civic_election_id=" + str(google_civic_election_id) + "&polling_location_we_vote_id=" + str(polling_location_we_vote_id) + "&polling_location_city=" + str(polling_location_city) + "&polling_location_zip=" + str(polling_location_zip) + "&show_all_elections=" + str(show_all_elections) + "&batch_uri=" + batch_uri_encoded) # If here we know we have the required variables organization_we_vote_id = request.POST.get('organization_we_vote_id', '') # Was form submitted, or was election just changed? import_batch_button = request.POST.get('import_batch_button', '') batch_file = None if positive_value_exists(import_batch_button): try: if request.method == 'POST' and request.FILES['batch_file']: batch_file = request.FILES['batch_file'] except KeyError: pass # Make sure we have a file to process // Used to only be able to import IMPORT_BALLOT_ITEM from file if kind_of_batch in [IMPORT_POLLING_LOCATION, ORGANIZATION_WORD] and not batch_file: messages.add_message(request, messages.ERROR, 'Please select a file to import.') return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch) + "&polling_location_we_vote_id=" + str(polling_location_we_vote_id) + "&google_civic_election_id=" + str(google_civic_election_id) + "&polling_location_city=" + str(polling_location_city) + "&polling_location_zip=" + str(polling_location_zip) + "&show_all_elections=" + str(show_all_elections) + "&batch_uri=" + batch_uri_encoded) # Make sure we have a Google Civic Election ID *unless* we are uploading an organization if kind_of_batch not in [IMPORT_POLLING_LOCATION, ORGANIZATION_WORD] \ and not positive_value_exists(google_civic_election_id): messages.add_message(request, messages.ERROR, 'This kind_of_batch (\"{kind_of_batch}\") requires you ' 'to choose an election.'.format(kind_of_batch=kind_of_batch)) return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch) + "&polling_location_we_vote_id=" + str(polling_location_we_vote_id) + "&google_civic_election_id=" + str(google_civic_election_id) + "&polling_location_city=" + str(polling_location_city) + "&polling_location_zip=" + str(polling_location_zip) + "&show_all_elections=" + str(show_all_elections) + "&batch_uri=" + batch_uri_encoded) # Make sure we have a polling_location_we_vote_id # if kind_of_batch in IMPORT_BALLOT_ITEM and not positive_value_exists(polling_location_we_vote_id): # messages.add_message(request, messages.ERROR, 'This kind_of_batch (\"{kind_of_batch}\") requires you ' # 'to choose a map point.' # ''.format(kind_of_batch=kind_of_batch)) # return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + # "?kind_of_batch=" + str(kind_of_batch) + # "&polling_location_we_vote_id=" + str(polling_location_we_vote_id) + # "&google_civic_election_id=" + str(google_civic_election_id) + # "&polling_location_city=" + str(polling_location_city) + # "&polling_location_zip=" + str(polling_location_zip) + # "&show_all_elections=" + str(show_all_elections) + # "&batch_uri=" + batch_uri_encoded) election_name = "" # For printing status if positive_value_exists(google_civic_election_id): election_manager = ElectionManager() results = election_manager.retrieve_election(google_civic_election_id) if results['election_found']: election = results['election'] election_name = election.election_name batch_header_id = 0 if positive_value_exists(import_batch_button): # If the button was pressed... batch_manager = BatchManager() if batch_file is not None: results = batch_manager.create_batch_from_local_file_upload( batch_file, kind_of_batch, google_civic_election_id, organization_we_vote_id, polling_location_we_vote_id) if results['batch_saved']: messages.add_message(request, messages.INFO, 'Import batch for {election_name} election saved.' ''.format(election_name=election_name)) batch_header_id = results['batch_header_id'] else: messages.add_message(request, messages.ERROR, results['status']) elif positive_value_exists(batch_uri): if "api.ballotpedia.org" in batch_uri: # response = requests.get(VOTER_INFO_URL, params={ # "key": GOOGLE_CIVIC_API_KEY, # "address": text_for_map_search, # "electionId": incoming_google_civic_election_id, # }) response = requests.get(batch_uri) structured_json = json.loads(response.text) if "api/contains" in batch_uri: contains_api = True else: contains_api = False groom_results = groom_ballotpedia_data_for_processing(structured_json, google_civic_election_id, state_code, contains_api) modified_json_list = groom_results['modified_json_list'] kind_of_batch = groom_results['kind_of_batch'] if contains_api: ballot_items_results = process_ballotpedia_voter_districts( google_civic_election_id, state_code, modified_json_list, polling_location_we_vote_id) if ballot_items_results['ballot_items_found']: modified_json_list = ballot_items_results['ballot_item_dict_list'] results = store_ballotpedia_json_response_to_import_batch_system( modified_json_list, google_civic_election_id, kind_of_batch) # Add state_code=state_code ? else: # check file type filetype = batch_manager.find_file_type(batch_uri) if "xml" in filetype: # file is XML # Retrieve the VIP data from XML results = batch_manager.create_batch_vip_xml(batch_uri, kind_of_batch, google_civic_election_id, organization_we_vote_id) else: results = batch_manager.create_batch_from_uri( batch_uri, kind_of_batch, google_civic_election_id, organization_we_vote_id) if results['batch_saved']: messages.add_message(request, messages.INFO, 'Import batch-batch_saved for ' '{election_name} election saved.' ''.format(election_name=election_name)) batch_header_id = results['batch_header_id'] else: messages.add_message(request, messages.ERROR, results['status']) if positive_value_exists(batch_header_id): # Go straight to the new batch return HttpResponseRedirect(reverse('import_export_batches:batch_action_list', args=()) + "?batch_header_id=" + str(batch_header_id) + "&kind_of_batch=" + str(kind_of_batch) + "&polling_location_we_vote_id=" + str(polling_location_we_vote_id) + "&google_civic_election_id=" + str(google_civic_election_id) + "&batch_uri=" + batch_uri_encoded) else: # Go to the batch listing page return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch) + "&polling_location_we_vote_id=" + str(polling_location_we_vote_id) + "&google_civic_election_id=" + str(google_civic_election_id) + "&polling_location_city=" + str(polling_location_city) + "&polling_location_zip=" + str(polling_location_zip) + "&show_all_elections=" + str(show_all_elections) + "&batch_uri=" + batch_uri_encoded) @login_required def batch_action_list_view(request): """ Display row-by-row details of batch actions being reviewed, leading up to processing an entire batch. :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) batch_set_list = [] polling_location_we_vote_id = "" batch_header_id = convert_to_int(request.GET.get('batch_header_id', 0)) kind_of_batch = request.GET.get('kind_of_batch', '') show_all = request.GET.get('show_all', False) state_code = request.GET.get('state_code', '') position_owner_organization_we_vote_id = request.GET.get('position_owner_organization_we_vote_id', '') if not positive_value_exists(batch_header_id): messages.add_message(request, messages.ERROR, 'Batch_header_id required.') return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch)) google_civic_election_id = request.GET.get('google_civic_election_id', 0) batch_set_id = 0 try: batch_description = BatchDescription.objects.get(batch_header_id=batch_header_id) batch_description_found = True batch_set_id = batch_description.batch_set_id google_civic_election_id = batch_description.google_civic_election_id polling_location_we_vote_id = batch_description.polling_location_we_vote_id except BatchDescription.DoesNotExist: # This is fine batch_description = BatchDescription() batch_description_found = False batch_set_list_found = False # if batch_set_id exists, send data sets associated with this batch_set_id if positive_value_exists(batch_set_id): try: batch_set_list = BatchSet.objects.get(id=batch_set_id) if batch_set_list: batch_set_list_found = True except BatchSet.DoesNotExist: # This is fine batch_set_list = BatchSet() batch_set_list_found = False try: batch_header_map = BatchHeaderMap.objects.get(batch_header_id=batch_header_id) except BatchHeaderMap.DoesNotExist: # This is fine batch_header_map = BatchHeaderMap() batch_list_found = False batch_row_count = 0 try: batch_row_count_query = BatchRow.objects.order_by('id') batch_row_count_query = batch_row_count_query.filter(batch_header_id=batch_header_id) if positive_value_exists(state_code): batch_row_count_query = batch_row_count_query.filter(state_code__iexact=state_code) batch_row_count = batch_row_count_query.count() batch_row_query = BatchRow.objects.order_by('id') batch_row_query = batch_row_query.filter(batch_header_id=batch_header_id) if positive_value_exists(state_code): batch_row_query = batch_row_query.filter(state_code__iexact=state_code) batch_row_list = list(batch_row_query) else: if positive_value_exists(show_all): batch_row_list = list(batch_row_query) else: batch_row_list = batch_row_query[:200] if len(batch_row_list): batch_list_found = True except BatchDescription.DoesNotExist: # This is fine batch_row_list = [] batch_list_found = False modified_batch_row_list = [] active_state_codes = [] batch_manager = BatchManager() if batch_list_found: for one_batch_row in batch_row_list: if positive_value_exists(one_batch_row.state_code): if one_batch_row.state_code not in active_state_codes: active_state_codes.append(one_batch_row.state_code) if kind_of_batch == CANDIDATE: existing_results = batch_manager.retrieve_batch_row_action_candidate(batch_header_id, one_batch_row.id) if existing_results['batch_row_action_found']: one_batch_row.batch_row_action = existing_results['batch_row_action_candidate'] one_batch_row.kind_of_batch = CANDIDATE one_batch_row.batch_row_action_exists = True else: one_batch_row.batch_row_action_exists = False modified_batch_row_list.append(one_batch_row) elif kind_of_batch == CONTEST_OFFICE: existing_results = batch_manager.retrieve_batch_row_action_contest_office(batch_header_id, one_batch_row.id) if existing_results['batch_row_action_found']: one_batch_row.batch_row_action = existing_results['batch_row_action_contest_office'] one_batch_row.kind_of_batch = CONTEST_OFFICE one_batch_row.batch_row_action_exists = True else: one_batch_row.batch_row_action_exists = False modified_batch_row_list.append(one_batch_row) elif kind_of_batch == ELECTED_OFFICE: existing_results = batch_manager.retrieve_batch_row_action_elected_office(batch_header_id, one_batch_row.id) if existing_results['batch_row_action_found']: one_batch_row.batch_row_action = existing_results['batch_row_action_elected_office'] one_batch_row.kind_of_batch = ELECTED_OFFICE one_batch_row.batch_row_action_exists = True else: one_batch_row.batch_row_action_exists = False modified_batch_row_list.append(one_batch_row) elif kind_of_batch == IMPORT_BALLOT_ITEM: # Retrieve Creates and Updates existing_results = \ batch_manager.retrieve_batch_row_action_ballot_item(batch_header_id, one_batch_row.id) if existing_results['batch_row_action_found']: one_batch_row.batch_row_action = existing_results['batch_row_action_ballot_item'] one_batch_row.kind_of_batch = IMPORT_BALLOT_ITEM one_batch_row.batch_row_action_exists = True else: one_batch_row.batch_row_action_exists = False modified_batch_row_list.append(one_batch_row) # Retrieve Deletes elif kind_of_batch == IMPORT_POLLING_LOCATION: # Retrieve Creates and Updates existing_results = \ batch_manager.retrieve_batch_row_action_polling_location(batch_header_id, one_batch_row.id) if existing_results['batch_row_action_found']: one_batch_row.batch_row_action = existing_results['batch_row_action_polling_location'] one_batch_row.kind_of_batch = IMPORT_POLLING_LOCATION one_batch_row.batch_row_action_exists = True else: one_batch_row.batch_row_action_exists = False modified_batch_row_list.append(one_batch_row) elif kind_of_batch == IMPORT_VOTER: existing_results = \ batch_manager.retrieve_batch_row_action_ballot_item(batch_header_id, one_batch_row.id) if existing_results['batch_row_action_found']: one_batch_row.batch_row_action = existing_results['batch_row_action_ballot_item'] one_batch_row.kind_of_batch = IMPORT_VOTER one_batch_row.batch_row_action_exists = True else: one_batch_row.batch_row_action_exists = False modified_batch_row_list.append(one_batch_row) elif kind_of_batch == MEASURE: existing_results = batch_manager.retrieve_batch_row_action_measure(batch_header_id, one_batch_row.id) if existing_results['batch_row_action_found']: one_batch_row.batch_row_action = existing_results['batch_row_action_measure'] one_batch_row.kind_of_batch = MEASURE one_batch_row.batch_row_action_exists = True else: one_batch_row.batch_row_action_exists = False modified_batch_row_list.append(one_batch_row) elif kind_of_batch == ORGANIZATION_WORD: existing_results = batch_manager.retrieve_batch_row_action_organization(batch_header_id, one_batch_row.id) if existing_results['batch_row_action_found']: one_batch_row.batch_row_action = existing_results['batch_row_action_organization'] one_batch_row.kind_of_batch = ORGANIZATION_WORD one_batch_row.batch_row_action_exists = True else: one_batch_row.batch_row_action_exists = False modified_batch_row_list.append(one_batch_row) elif kind_of_batch == POLITICIAN: existing_results = batch_manager.retrieve_batch_row_action_politician(batch_header_id, one_batch_row.id) if existing_results['batch_row_action_found']: one_batch_row.batch_row_action = existing_results['batch_row_action_politician'] one_batch_row.kind_of_batch = POLITICIAN one_batch_row.batch_row_action_exists = True else: one_batch_row.batch_row_action_exists = False modified_batch_row_list.append(one_batch_row) elif kind_of_batch == POSITION: existing_results = batch_manager.retrieve_batch_row_action_position(batch_header_id, one_batch_row.id) if existing_results['batch_row_action_found']: one_batch_row.batch_row_action = existing_results['batch_row_action_position'] one_batch_row.kind_of_batch = POSITION one_batch_row.batch_row_action_exists = True else: one_batch_row.batch_row_action_exists = False modified_batch_row_list.append(one_batch_row) if kind_of_batch == IMPORT_BALLOT_ITEM: results = batch_manager.retrieve_batch_row_action_ballot_item_list( batch_header_id, limit_to_kind_of_action_list=[IMPORT_DELETE, IMPORT_ALREADY_DELETED]) if results['batch_row_action_list_found']: batch_row_action_list = results['batch_row_action_list'] for batch_row_action_ballot_item in batch_row_action_list: one_batch_row = BatchRow() one_batch_row.batch_header_id = batch_header_id one_batch_row.batch_row_action = batch_row_action_ballot_item one_batch_row.kind_of_batch = IMPORT_BALLOT_ITEM one_batch_row.batch_row_action_exists = True modified_batch_row_list.append(one_batch_row) election_query = Election.objects.order_by('-election_day_text') election_list = list(election_query) # TODO Retrieve and send a list of polling_locations to choose from into the template polling_location_list = [] if kind_of_batch == IMPORT_BALLOT_ITEM: polling_location_list = [] filtered_state_list = [] state_list = STATE_CODE_MAP sorted_state_list = sorted(state_list.items()) for one_state in sorted_state_list: if one_state[0].lower() in active_state_codes: filtered_state_list.append(one_state) messages.add_message(request, messages.INFO, 'Batch Row Count: {batch_row_count}' ''.format(batch_row_count=batch_row_count)) messages_on_stage = get_messages(request) template_values = { 'messages_on_stage': messages_on_stage, 'batch_header_id': batch_header_id, 'batch_description': batch_description, 'batch_set_id': batch_set_id, 'batch_header_map': batch_header_map, 'batch_set_list': batch_set_list, 'batch_row_list': modified_batch_row_list, 'election_list': election_list, 'kind_of_batch': kind_of_batch, 'google_civic_election_id': google_civic_election_id, 'polling_location_we_vote_id': polling_location_we_vote_id, 'state_code': state_code, 'state_list': filtered_state_list, 'position_owner_organization_we_vote_id': position_owner_organization_we_vote_id, } return render(request, 'import_export_batches/batch_action_list.html', template_values) @login_required def batch_action_list_export_view(request): """ Export batch list as a csv file. :param request: HTTP request object. :return response: HttpResponse object with csv export data. """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) batch_set_list = [] batch_header_id = convert_to_int(request.GET.get('batch_header_id', 0)) kind_of_batch = request.GET.get('kind_of_batch', '') state_code = request.GET.get('state_code', '') if not positive_value_exists(batch_header_id): messages.add_message(request, messages.ERROR, 'Batch_header_id required.') return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch)) batch_set_id = 0 try: batch_description = BatchDescription.objects.get(batch_header_id=batch_header_id) except BatchDescription.DoesNotExist: # This is fine batch_description = BatchDescription() # if batch_set_id exists, send data sets associated with this batch_set_id if positive_value_exists(batch_set_id): try: batch_set_list = BatchSet.objects.get(id=batch_set_id) if batch_set_list: batch_set_list_found = True except BatchSet.DoesNotExist: # This is fine batch_set_list = BatchSet() batch_set_list_found = False try: batch_header_map = BatchHeaderMap.objects.get(batch_header_id=batch_header_id) except BatchHeaderMap.DoesNotExist: # This is fine batch_header_map = BatchHeaderMap() batch_list_found = False try: batch_row_query = BatchRow.objects.order_by('id') batch_row_query = batch_row_query.filter(batch_header_id=batch_header_id) if positive_value_exists(state_code): batch_row_query = batch_row_query.filter(state_code__iexact=state_code) batch_row_list = list(batch_row_query) if len(batch_row_list): batch_list_found = True except BatchDescription.DoesNotExist: # This is fine batch_row_list = [] batch_list_found = False if not batch_list_found: messages.add_message(request, messages.ERROR, 'No voters found to export.') return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch) + "&batch_header_id=" + str(batch_header_id) ) # get header/first row information header_opts = BatchHeaderMap._meta header_field_names = [] for field in header_opts.fields: if field.name not in ['id', 'batch_header_id']: header_field_names.append(field.name) # get row information # Dale 2020-July This isn't very robust. Shifts over the rows when exporting Polling locations. row_opts = BatchRow._meta row_field_names = [] for field in row_opts.fields: if field.name not in ['id', 'batch_header_id', 'batch_row_analyzed', 'batch_row_created']: if kind_of_batch == 'IMPORT_VOTER': if field.name not in \ ['state_code', 'google_civic_election_id', 'polling_location_we_vote_id', 'voter_id']: row_field_names.append(field.name) else: row_field_names.append(field.name) header_list = [getattr(batch_header_map, field) for field in header_field_names] if kind_of_batch not in ['IMPORT_POLLING_LOCATION', 'IMPORT_VOTER']: header_list.insert(0, 'google_civic_election_id') header_list.insert(0, 'state_code') # - Filter out headers that are None. header_list = list(filter(None, header_list)) # create response for csv file response = export_csv(batch_row_list, header_list, row_field_names, batch_description) return response @login_required def batch_row_action_list_export_view(request): """ Export the batch_row_action's (as opposed to the raw incoming values) as a csv file. :param request: HTTP request object. :return response: HttpResponse object with csv export data. """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) batch_set_list = [] batch_header_id = convert_to_int(request.GET.get('batch_header_id', 0)) kind_of_batch = request.GET.get('kind_of_batch', '') state_code = request.GET.get('state_code', '') if not positive_value_exists(batch_header_id): messages.add_message(request, messages.ERROR, 'Batch_header_id required.') return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch)) batch_set_id = 0 try: batch_description = BatchDescription.objects.get(batch_header_id=batch_header_id) except BatchDescription.DoesNotExist: # This is fine batch_description = BatchDescription() # if batch_set_id exists, send data sets associated with this batch_set_id if positive_value_exists(batch_set_id): try: batch_set_list = BatchSet.objects.get(id=batch_set_id) if batch_set_list: batch_set_list_found = True except BatchSet.DoesNotExist: # This is fine batch_set_list = BatchSet() batch_set_list_found = False try: batch_header_map = BatchHeaderMap.objects.get(batch_header_id=batch_header_id) except BatchHeaderMap.DoesNotExist: # This is fine batch_header_map = BatchHeaderMap() batch_list_found = False batch_row_list = [] try: if kind_of_batch == 'IMPORT_POLLING_LOCATION': batch_row_action_query = BatchRowActionPollingLocation.objects.order_by('id') batch_row_action_query = batch_row_action_query.filter(batch_header_id=batch_header_id) if positive_value_exists(state_code): batch_row_action_query = batch_row_action_query.filter(state_code__iexact=state_code) batch_row_list = list(batch_row_action_query) if len(batch_row_list): batch_list_found = True except BatchDescription.DoesNotExist: # This is fine batch_row_list = [] batch_list_found = False if not batch_list_found: messages.add_message(request, messages.ERROR, 'No voters found to export.') return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch) + "&batch_header_id=" + str(batch_header_id) ) # # get header/first row information # header_opts = BatchHeaderMap._meta header_field_names = [] # for field in header_opts.fields: # if field.name not in ['id', 'batch_header_id']: # header_field_names.append(field.name) # get row information header_list = [] row_field_names = [] if kind_of_batch == 'IMPORT_POLLING_LOCATION': row_opts = BatchRowActionPollingLocation._meta for field in row_opts.fields: row_field_names.append(field.name) header_list = row_field_names # header_list = [getattr(batch_header_map, field) for field in header_field_names] # if kind_of_batch not in ['IMPORT_POLLING_LOCATION', 'IMPORT_VOTER']: # header_list.insert(0, 'google_civic_election_id') # header_list.insert(0, 'state_code') # # - Filter out headers that are None. # header_list = list(filter(None, header_list)) # create response for csv file response = export_csv(batch_row_list, header_list, row_field_names, batch_description) return response def export_csv(batch_row_list, header_list, row_field_names, batch_description=None, filename=None): """ Helper function that creates a HttpResponse with csv data :param batch_row_list: list of objects to export as csv :param header_list: list of column headers for csv data :param row_field_names: list of the object fields to be exported :param batch_description: optional description of the batch to export :param filename: optional name of csv file :return response: HttpResponse with text/csv data """ export_filename = "voter_export" if batch_description and not filename: export_filename = batch_description.batch_name elif filename: export_filename = filename export_filename += ".csv" response = HttpResponse(content_type="text/csv") response['Content-Disposition'] = 'attachment; filename="{0}"'.format(export_filename) csv_writer = csv.writer(response) csv_writer.writerow(header_list) # output header/first row to csv for obj in batch_row_list: # csv_writer.writerow([getattr(obj, field) for field in row_field_names]) one_row = [] for field in row_field_names: one_row.append(getattr(obj, field)) csv_writer.writerow(one_row) return response @login_required def batch_action_list_export_voters_view(request): """ View used to create a csv export file of voters registered for the newsletter :param request: :return: HttpResponse with csv information of voters """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) # get parameters from request object kind_of_batch = request.GET.get('kind_of_batch', IMPORT_VOTER) batch_header_id = request.GET.get('batch_header_id', 0) google_civic_election_id = request.GET.get('google_civic_election_id', '') organization_we_vote_id = request.GET.get('organization_we_vote_id', '') result = export_voter_list_with_emails() messages.add_message(request, messages.INFO, 'Batch Action Export Voters: ' 'Batch kind: {kind_of_batch}' ''.format(kind_of_batch=kind_of_batch)) filename = 'voter_export.csv' batch_manager = BatchManager() batch_created_result = dict() if result and result['voter_list']: # Create batch of voters registered for newsletter batch_created_result = batch_manager.create_batch_from_voter_object_list(result['voter_list']) if batch_created_result and batch_created_result['batch_header_id']: batch_header_id = batch_created_result['batch_header_id'] return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch) + "&batch_header_id=" + str(batch_header_id) ) @login_required def batch_action_list_analyze_process_view(request): """ Create BatchRowActions for either all of the BatchRows for batch_header_id, or only one with batch_row_id :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) batch_header_id = convert_to_int(request.GET.get('batch_header_id', 0)) batch_row_id = convert_to_int(request.GET.get('batch_row_id', 0)) kind_of_batch = request.GET.get('kind_of_batch', '') state_code = request.GET.get('state_code', '') delete_analysis_only = positive_value_exists(request.GET.get('delete_analysis_only', False)) if state_code == "None": state_code = "" if not positive_value_exists(batch_header_id): messages.add_message(request, messages.ERROR, 'Batch_header_id required.') return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch)) # if create_actions_button in (MEASURE, ELECTED_OFFICE, CANDIDATE, ORGANIZATION_WORD, # POSITION, POLITICIAN, IMPORT_BALLOT_ITEM) # Run the analysis of either A) every row in this batch, or B) Just the batch_row_id specified within this batch results = create_batch_row_actions(batch_header_id=batch_header_id, batch_description=None, batch_row_id=batch_row_id, state_code=state_code, delete_analysis_only=delete_analysis_only) kind_of_batch = results['kind_of_batch'] messages.add_message(request, messages.INFO, 'Batch Actions: ' 'Batch kind: {kind_of_batch}, ' 'Created:{created} ' ''.format(kind_of_batch=kind_of_batch, created=results['number_of_batch_actions_created'])) return HttpResponseRedirect(reverse('import_export_batches:batch_action_list', args=()) + "?kind_of_batch=" + str(kind_of_batch) + "&batch_header_id=" + str(batch_header_id) + "&state_code=" + str(state_code) ) @login_required def batch_header_mapping_view(request): """ :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) batch_header_id = convert_to_int(request.GET.get('batch_header_id', 0)) kind_of_batch = request.GET.get('kind_of_batch', '') if not positive_value_exists(batch_header_id): messages.add_message(request, messages.ERROR, 'Batch_header_id required.') return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch)) google_civic_election_id = request.GET.get('google_civic_election_id', 0) batch_set_id = 0 try: batch_description = BatchDescription.objects.get(batch_header_id=batch_header_id) batch_set_id = batch_description.batch_set_id kind_of_batch = batch_description.kind_of_batch except BatchDescription.DoesNotExist: # This is fine batch_description = BatchDescription() # if batch_set_id exists, send data sets associated with this batch_set_id if positive_value_exists(batch_set_id): try: batch_set_list = BatchSet.objects.get(id=batch_set_id) except BatchSet.DoesNotExist: # This is fine batch_set_list = BatchSet() try: batch_header = BatchHeader.objects.get(id=batch_header_id) except BatchHeader.DoesNotExist: # This is fine batch_header = BatchHeader() try: batch_header_map = BatchHeaderMap.objects.get(batch_header_id=batch_header_id) except BatchHeaderMap.DoesNotExist: # This is fine batch_header_map = BatchHeaderMap() if kind_of_batch == CANDIDATE: batch_import_keys_accepted = BATCH_IMPORT_KEYS_ACCEPTED_FOR_CANDIDATES elif kind_of_batch == CONTEST_OFFICE: batch_import_keys_accepted = BATCH_IMPORT_KEYS_ACCEPTED_FOR_CONTEST_OFFICES elif kind_of_batch == ELECTED_OFFICE: batch_import_keys_accepted = BATCH_IMPORT_KEYS_ACCEPTED_FOR_ELECTED_OFFICES elif kind_of_batch == MEASURE: batch_import_keys_accepted = BATCH_IMPORT_KEYS_ACCEPTED_FOR_MEASURES elif kind_of_batch == ORGANIZATION_WORD: batch_import_keys_accepted = BATCH_IMPORT_KEYS_ACCEPTED_FOR_ORGANIZATIONS elif kind_of_batch == POLITICIAN: batch_import_keys_accepted = BATCH_IMPORT_KEYS_ACCEPTED_FOR_POLITICIANS elif kind_of_batch == POSITION: batch_import_keys_accepted = BATCH_IMPORT_KEYS_ACCEPTED_FOR_POSITIONS elif kind_of_batch == IMPORT_BALLOT_ITEM: batch_import_keys_accepted = BATCH_IMPORT_KEYS_ACCEPTED_FOR_BALLOT_ITEMS else: batch_import_keys_accepted = {} sorted_batch_import_keys_accepted = sorted(batch_import_keys_accepted.items()) try: batch_row_list = BatchRow.objects.all() batch_row_list = batch_row_list.filter(batch_header_id=batch_header_id)[:3] # Limit to 3 rows except BatchDescription.DoesNotExist: # This is fine batch_row_list = [] election_list = Election.objects.order_by('-election_day_text') messages_on_stage = get_messages(request) if batch_set_id: template_values = { 'messages_on_stage': messages_on_stage, 'batch_header_id': batch_header_id, 'batch_description': batch_description, 'batch_set_id': batch_set_id, 'batch_header': batch_header, 'batch_header_map': batch_header_map, 'batch_import_keys_accepted': sorted_batch_import_keys_accepted, 'batch_row_list': batch_row_list, 'batch_set_list': batch_set_list, 'election_list': election_list, 'kind_of_batch': kind_of_batch, 'google_civic_election_id': google_civic_election_id, } else: template_values = { 'messages_on_stage': messages_on_stage, 'batch_header_id': batch_header_id, 'batch_description': batch_description, 'batch_set_id': batch_set_id, 'batch_header': batch_header, 'batch_header_map': batch_header_map, 'batch_import_keys_accepted': sorted_batch_import_keys_accepted, 'batch_row_list': batch_row_list, 'election_list': election_list, 'kind_of_batch': kind_of_batch, 'google_civic_election_id': google_civic_election_id, } return render(request, 'import_export_batches/batch_header_mapping.html', template_values) @login_required def batch_header_mapping_process_view(request): """ :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) batch_header_id = convert_to_int(request.GET.get('batch_header_id', 0)) save_header_mapping_button = request.GET.get('save_header_mapping_button', '') kind_of_batch = "" if not positive_value_exists(batch_header_id): messages.add_message(request, messages.ERROR, 'Batch_header_id required.') return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=()) + "?kind_of_batch=" + str(kind_of_batch)) batch_set_id = 0 try: batch_description = BatchDescription.objects.get(batch_header_id=batch_header_id) batch_set_id = batch_description.batch_set_id kind_of_batch = batch_description.kind_of_batch except BatchDescription.DoesNotExist: # This is fine batch_description = BatchDescription() # Put all incoming header_mapping values into a dict incoming_header_map_values = { 'batch_header_map_000': request.GET.get('batch_header_map_000', ''), 'batch_header_map_001': request.GET.get('batch_header_map_001', ''), 'batch_header_map_002': request.GET.get('batch_header_map_002', ''), 'batch_header_map_003': request.GET.get('batch_header_map_003', ''), 'batch_header_map_004': request.GET.get('batch_header_map_004', ''), 'batch_header_map_005': request.GET.get('batch_header_map_005', ''), 'batch_header_map_006': request.GET.get('batch_header_map_006', ''), 'batch_header_map_007': request.GET.get('batch_header_map_007', ''), 'batch_header_map_008': request.GET.get('batch_header_map_008', ''), 'batch_header_map_009': request.GET.get('batch_header_map_009', ''), 'batch_header_map_010': request.GET.get('batch_header_map_010', ''), 'batch_header_map_011': request.GET.get('batch_header_map_011', ''), 'batch_header_map_012': request.GET.get('batch_header_map_012', ''), 'batch_header_map_013': request.GET.get('batch_header_map_013', ''), 'batch_header_map_014': request.GET.get('batch_header_map_014', ''), 'batch_header_map_015': request.GET.get('batch_header_map_015', ''), 'batch_header_map_016': request.GET.get('batch_header_map_016', ''), 'batch_header_map_017': request.GET.get('batch_header_map_017', ''), 'batch_header_map_018': request.GET.get('batch_header_map_018', ''), 'batch_header_map_019': request.GET.get('batch_header_map_019', ''), 'batch_header_map_020': request.GET.get('batch_header_map_020', ''), } batch_header_mapping_results = update_or_create_batch_header_mapping( batch_header_id, kind_of_batch, incoming_header_map_values) try: batch_header = BatchHeader.objects.get(id=batch_header_id) batch_header_found = True except BatchHeader.DoesNotExist: # This is fine batch_header = BatchHeader() batch_header_found = False suggestions_created = 0 if batch_header_found: batch_header_translation_results = create_batch_header_translation_suggestions( batch_header, kind_of_batch, incoming_header_map_values) suggestions_created = batch_header_translation_results['suggestions_created'] messages.add_message(request, messages.INFO, 'Batch Header Mapping Updated: ' 'Batch kind: {kind_of_batch}, ' 'suggestions_created: {suggestions_created}, ' ''.format(kind_of_batch=kind_of_batch, suggestions_created=suggestions_created)) return HttpResponseRedirect(reverse('import_export_batches:batch_action_list', args=()) + "?kind_of_batch=" + str(kind_of_batch) + "&batch_header_id=" + str(batch_header_id)) @login_required def batch_action_list_assign_election_to_rows_process_view(request): """ :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) batch_row_list_found = False batch_row_list = [] batch_header_id = convert_to_int(request.GET.get('batch_header_id', 0)) batch_row_id = convert_to_int(request.GET.get('batch_row_id', 0)) kind_of_batch = request.GET.get('kind_of_batch', '') kind_of_action = request.GET.get('kind_of_action') state_code = request.GET.get('state_code', '') google_civic_election_id = convert_to_int(request.GET.get('google_civic_election_id', 0)) # do for entire batch_rows try: batch_header_map = BatchHeaderMap.objects.get(batch_header_id=batch_header_id) batch_header_map_found = True except BatchHeaderMap.DoesNotExist: # This is fine batch_header_map = BatchHeaderMap() batch_header_map_found = False if batch_header_map_found: try: batch_row_query = BatchRow.objects.all() batch_row_query = batch_row_query.filter(batch_header_id=batch_header_id) if positive_value_exists(batch_row_id): batch_row_query = batch_row_query.filter(id=batch_row_id) if positive_value_exists(state_code): batch_row_query = batch_row_query.filter(state_code__iexact=state_code) batch_row_list = list(batch_row_query) if len(batch_row_list): batch_row_list_found = True except BatchDescription.DoesNotExist: # This is fine batch_row_list_found = False pass if batch_header_map_found and batch_row_list_found: for one_batch_row in batch_row_list: try: one_batch_row.google_civic_election_id = google_civic_election_id one_batch_row.save() except Exception as e: pass # messages.add_message(request, messages.INFO, # 'Kind of Batch: {kind_of_batch}, ' 'Number Created: {created} ' # ''.format(kind_of_batch=kind_of_batch, # created=results['number_of_table_rows_created'])) return HttpResponseRedirect(reverse('import_export_batches:batch_action_list', args=()) + "?kind_of_batch=" + str(kind_of_batch) + "&batch_header_id=" + str(batch_header_id) + "&state_code=" + str(state_code) + "&google_civic_election_id=" + str(google_civic_election_id) ) @login_required def batch_action_list_update_or_create_process_view(request): """ Use batch_row_action entries and create live data :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) batch_row_list_found = False status = "" batch_header_id = convert_to_int(request.GET.get('batch_header_id', 0)) batch_row_id = convert_to_int(request.GET.get('batch_row_id', 0)) ballot_item_id = convert_to_int(request.GET.get('ballot_item_id', 0)) kind_of_batch = request.GET.get('kind_of_batch', '') kind_of_action = request.GET.get('kind_of_action') state_code = request.GET.get('state_code', '') # do for entire batch_rows try: batch_header_map = BatchHeaderMap.objects.get(batch_header_id=batch_header_id) batch_header_map_found = True except BatchHeaderMap.DoesNotExist: # This is fine batch_header_map = BatchHeaderMap() batch_header_map_found = False if batch_header_map_found: try: batch_row_query = BatchRow.objects.all() batch_row_query = batch_row_query.filter(batch_header_id=batch_header_id) if positive_value_exists(batch_row_id): batch_row_query = batch_row_query.filter(id=batch_row_id) if positive_value_exists(state_code): batch_row_query = batch_row_query.filter(state_code__iexact=state_code) batch_row_list = list(batch_row_query) if len(batch_row_list): batch_row_list_found = True except BatchDescription.DoesNotExist: # This is fine batch_row_list_found = False pass if batch_header_map_found and batch_row_list_found: results = import_data_from_batch_row_actions( kind_of_batch, kind_of_action, batch_header_id, batch_row_id, state_code, ballot_item_id=ballot_item_id) if kind_of_action == IMPORT_CREATE: if results['success']: messages.add_message(request, messages.INFO, 'Kind of Batch: {kind_of_batch}, ' 'Number Created: {created} ' ''.format(kind_of_batch=kind_of_batch, created=results['number_of_table_rows_created'])) else: status += results['status'] messages.add_message(request, messages.ERROR, 'Batch kind: {kind_of_batch} create failed: {status}' ''.format(kind_of_batch=kind_of_batch, status=status)) elif kind_of_action == IMPORT_ADD_TO_EXISTING: if results['success']: messages.add_message(request, messages.INFO, 'Kind of Batch: {kind_of_batch}, ' 'Number Updated: {updated} ' ''.format(kind_of_batch=kind_of_batch, updated=results['number_of_table_rows_updated'])) else: status += results['status'] messages.add_message(request, messages.ERROR, 'Batch kind: {kind_of_batch} UPDATE_FAILED-UPDATE_MAY_NOT_BE_SUPPORTED_YET, ' 'status: {status} ' ''.format(kind_of_batch=kind_of_batch, status=status)) elif kind_of_action == IMPORT_DELETE: if results['success']: messages.add_message(request, messages.INFO, 'Kind of Batch: {kind_of_batch}, ' 'Number Deleted: {deleted} ' ''.format(kind_of_batch=kind_of_batch, deleted=results['number_of_table_rows_deleted'])) else: status += results['status'] messages.add_message(request, messages.ERROR, 'Batch kind: {kind_of_batch} delete failed: {status}' ''.format(kind_of_batch=kind_of_batch, status=status)) else: status += results['status'] messages.add_message(request, messages.ERROR, 'Batch kind: {kind_of_batch} import status: {status}' ''.format(kind_of_batch=kind_of_batch, status=status)) return HttpResponseRedirect(reverse('import_export_batches:batch_list', args=())) return HttpResponseRedirect(reverse('import_export_batches:batch_action_list', args=()) + "?kind_of_batch=" + str(kind_of_batch) + "&batch_header_id=" + str(batch_header_id) + "&state_code=" + str(state_code) ) @login_required def batch_set_list_view(request): """ Display a list of import batch set :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) # kind_of_batch = request.GET.get('kind_of_batch', '') batch_file = request.GET.get('batch_file', '') batch_uri = request.GET.get('batch_uri', '') google_civic_election_id = request.GET.get('google_civic_election_id', 0) batch_set_id = convert_to_int(request.GET.get('batch_set_id', 0)) batch_process_id = convert_to_int(request.GET.get('batch_process_id', 0)) limit = request.GET.get('limit', 25) show_status_statistics = request.GET.get('show_status_statistics', False) show_status_statistics = positive_value_exists(show_status_statistics) state_code = request.GET.get('state_code', '') messages_on_stage = get_messages(request) batch_set_list_found = False try: batch_set_query = BatchSet.objects.order_by('-import_date') # batch_set_list = batch_set_list.exclude(batch_set_id__isnull=True) if positive_value_exists(google_civic_election_id): batch_set_query = batch_set_query.filter(google_civic_election_id=google_civic_election_id) if positive_value_exists(batch_process_id): batch_set_query = batch_set_query.filter(batch_process_id=batch_process_id) if positive_value_exists(batch_set_id): batch_set_query = batch_set_query.filter(id=batch_set_id) if positive_value_exists(state_code): batch_set_query = batch_set_query.filter(state_code__iexact=state_code) batch_set_list = batch_set_query[:limit] if len(batch_set_list): batch_set_list_found = True except BatchSet.DoesNotExist: # This is fine batch_set_list = [] batch_set_list_found = False pass if positive_value_exists(show_status_statistics): for one_batch_set in batch_set_list: batch_description_query = BatchDescription.objects.filter(batch_set_id=one_batch_set.id) batch_description = batch_description_query.first() batch_description_query = BatchDescription.objects.filter(batch_set_id=one_batch_set.id) one_batch_set.batch_description_total_rows_count = batch_description_query.count() batch_description_query = BatchDescription.objects.filter(batch_set_id=one_batch_set.id) batch_description_query = batch_description_query.exclude(batch_description_analyzed=True) one_batch_set.batch_description_not_analyzed_count = batch_description_query.count() batch_row_action_query = BatchRowActionBallotItem.objects.filter(batch_set_id=one_batch_set.id) batch_row_action_query = batch_row_action_query.filter(kind_of_action__iexact=IMPORT_DELETE) one_batch_set.batch_description_to_delete_count = batch_row_action_query.count() batch_row_action_query = BatchRowActionBallotItem.objects.filter(batch_set_id=one_batch_set.id) batch_row_action_query = batch_row_action_query.filter(kind_of_action__iexact=IMPORT_ALREADY_DELETED) one_batch_set.batch_description_already_deleted_count = batch_row_action_query.count() if positive_value_exists(one_batch_set.batch_description_total_rows_count): try: if batch_description.kind_of_batch == IMPORT_BALLOT_ITEM: batch_row_action_query = BatchRowActionBallotItem.objects.filter(batch_set_id=one_batch_set.id) batch_row_action_query = batch_row_action_query.filter(kind_of_action=IMPORT_CREATE) one_batch_set.batch_description_not_created_count = batch_row_action_query.count() except Exception as e: pass election_list = Election.objects.order_by('-election_day_text') if batch_set_list_found: template_values = { 'batch_file': batch_file, 'batch_process_id': batch_process_id, 'batch_set_id': batch_set_id, 'batch_set_list': batch_set_list, 'batch_uri': batch_uri, 'google_civic_election_id': google_civic_election_id, 'election_list': election_list, 'messages_on_stage': messages_on_stage, 'show_status_statistics': show_status_statistics, 'state_code': state_code, } else: template_values = { 'batch_file': batch_file, 'batch_process_id': batch_process_id, 'batch_set_id': batch_set_id, 'batch_uri': batch_uri, 'election_list': election_list, 'google_civic_election_id': google_civic_election_id, 'messages_on_stage': messages_on_stage, 'show_status_statistics': show_status_statistics, 'state_code': state_code, } return render(request, 'import_export_batches/batch_set_list.html', template_values) @login_required def batch_set_list_process_view(request): """ Load in a new batch set to start the importing process :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) batch_uri = request.POST.get('batch_uri', '') batch_process_id = convert_to_int(request.POST.get('batch_process_id', 0)) batch_set_id = convert_to_int(request.POST.get('batch_set_id', 0)) google_civic_election_id = request.POST.get('google_civic_election_id', 0) organization_we_vote_id = request.POST.get('organization_we_vote_id', '') # Was form submitted, or was election just changed? import_batch_button = request.POST.get('import_batch_button', '') show_status_statistics = request.POST.get('show_status_statistics', False) show_status_statistics = positive_value_exists(show_status_statistics) state_code = request.POST.get('state_code', '') batch_uri_encoded = urlquote(batch_uri) if positive_value_exists(batch_uri) else "" batch_file = None # Store contents of spreadsheet? # if not positive_value_exists(google_civic_election_id): # messages.add_message(request, messages.ERROR, 'This batch set requires you to choose an election.') # return HttpResponseRedirect(reverse('import_export_batches:batch_set_list', args=()) + # "?batch_uri=" + batch_uri_encoded) election_manager = ElectionManager() election_name = "" results = election_manager.retrieve_election(google_civic_election_id) if results['election_found']: election = results['election'] election_name = election.election_name if positive_value_exists(import_batch_button): # If the button was pressed... batch_manager = BatchManager() try: if request.method == 'POST' and request.FILES['batch_file']: batch_file = request.FILES['batch_file'] except KeyError: pass if batch_file is not None: results = batch_manager.create_batch_set_vip_xml( batch_file, batch_uri, google_civic_election_id, organization_we_vote_id) if results['batch_saved']: messages.add_message(request, messages.INFO, 'Import batch_set_list for {election_name} election saved.' ''.format(election_name=election_name)) else: messages.add_message(request, messages.ERROR, results['status']) elif positive_value_exists(batch_uri): # check file type filetype = batch_manager.find_file_type(batch_uri) if "xml" in filetype: # file is XML # Retrieve the VIP data from XML results = batch_manager.create_batch_set_vip_xml( batch_file, batch_uri, google_civic_election_id, organization_we_vote_id) else: pass # results = batch_manager.create_batch(batch_uri, google_civic_election_id, organization_we_vote_id) if 'batch_saved' in results and results['batch_saved']: messages.add_message(request, messages.INFO, 'Import batch_set_list-batch_saved for ' '{election_name} election saved.' ''.format(election_name=election_name)) else: messages.add_message(request, messages.ERROR, results['status']) return HttpResponseRedirect(reverse('import_export_batches:batch_set_list', args=()) + "?google_civic_election_id=" + str(google_civic_election_id) + "&batch_process_id=" + str(batch_process_id) + "&batch_set_id=" + str(batch_set_id) + "&state_code=" + str(state_code) + "&show_status_statistics=" + str(show_status_statistics) + "&batch_uri=" + batch_uri_encoded) @login_required def batch_process_system_toggle_view(request): # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'political_data_manager'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) google_civic_election_id = convert_to_int(request.GET.get('google_civic_election_id', 0)) state_code = request.GET.get('state_code', '') # ACTIVITY_NOTICE_PROCESS, API_REFRESH_REQUEST, BALLOT_ITEMS, SEARCH_TWITTER kind_of_process = request.GET.get('kind_of_process', '') kind_of_processes_to_show = request.GET.get('kind_of_processes_to_show', '') show_checked_out_processes_only = request.GET.get('show_checked_out_processes_only', '') show_active_processes_only = request.GET.get('show_active_processes_only', '') show_paused_processes_only = request.GET.get('show_paused_processes_only', '') include_frequent_processes = request.GET.get('include_frequent_processes', '') from wevote_settings.models import WeVoteSettingsManager we_vote_settings_manager = WeVoteSettingsManager() if kind_of_process == 'ACTIVITY_NOTICE_PROCESS': setting_name = 'batch_process_system_activity_notices_on' elif kind_of_process == 'API_REFRESH_REQUEST': setting_name = 'batch_process_system_api_refresh_on' elif kind_of_process == 'BALLOT_ITEMS': setting_name = 'batch_process_system_ballot_items_on' elif kind_of_process == 'CALCULATE_ANALYTICS': setting_name = 'batch_process_system_calculate_analytics_on' elif kind_of_process == 'SEARCH_TWITTER': setting_name = 'batch_process_system_search_twitter_on' else: setting_name = 'batch_process_system_on' results = we_vote_settings_manager.fetch_setting_results(setting_name=setting_name, read_only=False) if results['we_vote_setting_found']: we_vote_setting = results['we_vote_setting'] we_vote_setting.boolean_value = not we_vote_setting.boolean_value we_vote_setting.save() else: messages.add_message(request, messages.ERROR, "CANNOT_FIND_WE_VOTE_SETTING-batch_process_system_on") return HttpResponseRedirect(reverse('import_export_batches:batch_process_list', args=()) + "?google_civic_election_id=" + str(google_civic_election_id) + "&state_code=" + str(state_code) + "&kind_of_processes_to_show=" + str(kind_of_processes_to_show) + "&show_checked_out_processes_only=" + str(show_checked_out_processes_only) + "&show_active_processes_only=" + str(show_active_processes_only) + "&show_paused_processes_only=" + str(show_paused_processes_only) + "&include_frequent_processes=" + str(include_frequent_processes) ) @login_required def batch_process_list_view(request): # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'political_data_manager'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) status = "" success = True google_civic_election_id = convert_to_int(request.GET.get('google_civic_election_id', 0)) include_frequent_processes = request.GET.get('include_frequent_processes', False) kind_of_processes_to_show = request.GET.get('kind_of_processes_to_show', '') state_code = request.GET.get('state_code', '') show_all_elections = positive_value_exists(request.GET.get('show_all_elections', False)) show_active_processes_only = request.GET.get('show_active_processes_only', False) show_paused_processes_only = request.GET.get('show_paused_processes_only', False) show_checked_out_processes_only = request.GET.get('show_checked_out_processes_only', False) batch_process_id = convert_to_int(request.GET.get('batch_process_id', 0)) batch_process_search = request.GET.get('batch_process_search', '') batch_process_list = [] select_for_changing_batch_process_ids = request.POST.getlist('select_for_marking_checks[]') which_marking = request.POST.get("which_marking", None) # What to do with check marks # Make sure 'which_marking' is one of the allowed Filter fields if which_marking and which_marking not in ["pause_process", "unpause_process", None]: messages.add_message(request, messages.ERROR, 'The filter you are trying to update is not recognized: {which_marking}' ''.format(which_marking=which_marking)) return HttpResponseRedirect(reverse('import_export_batches:batch_process_list', args=())) error_count = 0 items_processed_successfully = 0 if which_marking and select_for_changing_batch_process_ids: # Get these values from hidden POST fields batch_process_search = request.POST.get('batch_process_search', '') google_civic_election_id = convert_to_int(request.POST.get('google_civic_election_id', 0)) show_all_elections = positive_value_exists(request.POST.get('show_all_elections', False)) state_code = request.POST.get('state_code', '') # Already retrieved with GET, now retrieving with POST for one_batch_process_id in select_for_changing_batch_process_ids: try: one_batch_process = BatchProcess.objects.get(id=one_batch_process_id) if which_marking == "pause_process": one_batch_process.batch_process_paused = True elif which_marking == "unpause_process": one_batch_process.batch_process_paused = False one_batch_process.save() items_processed_successfully += 1 status += 'BATCH_PROCESS_UPDATED ' except BatchProcess.MultipleObjectsReturned as e: status += 'MULTIPLE_MATCHING_BATCH_PROCESSES_FOUND ' error_count += 1 except BatchProcess.DoesNotExist: status += "RETRIEVE_BATCH_PROCESS_NOT_FOUND " error_count += 1 except Exception as e: status += 'BATCH_PROCESS_GENERAL_ERROR ' \ '{error} [type: {error_type}]'.format(error=e, error_type=type(e)) error_count += 1 messages.add_message(request, messages.INFO, 'Batch Processes paused/unpaused successfully: {items_processed_successfully}, ' 'errors: {error_count}' ''.format(error_count=error_count, items_processed_successfully=items_processed_successfully)) election_manager = ElectionManager() if positive_value_exists(show_all_elections): results = election_manager.retrieve_elections() election_list = results['election_list'] else: results = election_manager.retrieve_upcoming_elections() election_list = results['election_list'] try: batch_process_queryset = BatchProcess.objects.all() if positive_value_exists(batch_process_id): batch_process_queryset = batch_process_queryset.filter(id=batch_process_id) if positive_value_exists(google_civic_election_id): batch_process_queryset = batch_process_queryset.filter(google_civic_election_id=google_civic_election_id) elif positive_value_exists(show_all_elections): # Return offices from all elections pass else: # Limit this search to upcoming_elections only google_civic_election_id_list = [0] for one_election in election_list: google_civic_election_id_list.append(one_election.google_civic_election_id) batch_process_queryset = batch_process_queryset.filter( google_civic_election_id__in=google_civic_election_id_list) if positive_value_exists(state_code): batch_process_queryset = batch_process_queryset.filter(state_code__iexact=state_code) if positive_value_exists(show_active_processes_only): batch_process_queryset = batch_process_queryset.filter(date_completed__isnull=True) batch_process_queryset = batch_process_queryset.exclude(batch_process_paused=True) if positive_value_exists(show_paused_processes_only): batch_process_queryset = batch_process_queryset.filter(batch_process_paused=True) if positive_value_exists(show_checked_out_processes_only): batch_process_queryset = batch_process_queryset.filter(date_completed__isnull=True) batch_process_queryset = batch_process_queryset.filter(date_started__isnull=False) batch_process_queryset = batch_process_queryset.exclude(batch_process_paused=True) if positive_value_exists(kind_of_processes_to_show): if kind_of_processes_to_show == "ACTIVITY_NOTICE_PROCESS": activity_notice_processes = ['ACTIVITY_NOTICE_PROCESS'] batch_process_queryset = batch_process_queryset.filter(kind_of_process__in=activity_notice_processes) elif kind_of_processes_to_show == "ANALYTICS_ACTION": analytics_processes = [ 'AUGMENT_ANALYTICS_ACTION_WITH_ELECTION_ID', 'AUGMENT_ANALYTICS_ACTION_WITH_FIRST_VISIT', 'CALCULATE_ORGANIZATION_DAILY_METRICS', 'CALCULATE_ORGANIZATION_ELECTION_METRICS', 'CALCULATE_SITEWIDE_DAILY_METRICS', 'CALCULATE_SITEWIDE_VOTER_METRICS'] batch_process_queryset = batch_process_queryset.filter(kind_of_process__in=analytics_processes) elif kind_of_processes_to_show == "API_REFRESH_REQUEST": api_refresh_processes = ['API_REFRESH_REQUEST'] batch_process_queryset = batch_process_queryset.filter(kind_of_process__in=api_refresh_processes) elif kind_of_processes_to_show == "BALLOT_ITEMS": ballot_item_processes = [ 'REFRESH_BALLOT_ITEMS_FROM_POLLING_LOCATIONS', 'REFRESH_BALLOT_ITEMS_FROM_VOTERS', 'RETRIEVE_BALLOT_ITEMS_FROM_POLLING_LOCATIONS'] batch_process_queryset = batch_process_queryset.filter(kind_of_process__in=ballot_item_processes) elif kind_of_processes_to_show == "SEARCH_TWITTER": search_twitter_processes = ['SEARCH_TWITTER_FOR_CANDIDATE_TWITTER_HANDLE'] batch_process_queryset = batch_process_queryset.filter(kind_of_process__in=search_twitter_processes) elif positive_value_exists(include_frequent_processes): # Don't modify the query pass else: exclude_list = [ACTIVITY_NOTICE_PROCESS, API_REFRESH_REQUEST] batch_process_queryset = batch_process_queryset.exclude(kind_of_process__in=exclude_list) batch_process_queryset = batch_process_queryset.order_by("-id") if positive_value_exists(batch_process_search): search_words = batch_process_search.split() for one_word in search_words: filters = [] # Reset for each search word new_filter = Q(office_name__icontains=one_word) filters.append(new_filter) new_filter = Q(we_vote_id__iexact=one_word) filters.append(new_filter) new_filter = Q(wikipedia_id__icontains=one_word) filters.append(new_filter) new_filter = Q(ballotpedia_office_id__iexact=one_word) filters.append(new_filter) new_filter = Q(ballotpedia_race_id__iexact=one_word) filters.append(new_filter) # Add the first query if len(filters): final_filters = filters.pop() # ...and "OR" the remaining items in the list for item in filters: final_filters |= item batch_process_queryset = batch_process_queryset.filter(final_filters) batch_process_list_count = batch_process_queryset.count() batch_process_queryset = batch_process_queryset[:100] batch_process_list = list(batch_process_queryset) if len(batch_process_list): batch_process_list_found = True status += 'BATCH_PROCESS_LIST_RETRIEVED ' else: status += 'BATCH_PROCESS_LIST_NOT_RETRIEVED ' except BatchProcess.DoesNotExist: # No offices found. Not a problem. status += 'NO_OFFICES_FOUND_DoesNotExist ' batch_process_list = [] except Exception as e: status += 'FAILED retrieve_all_offices_for_upcoming_election: ' + str(e) + ' ' success = False # Add the processing "chunks" under each Batch Process for batch_process in batch_process_list: batch_process_ballot_item_chunk_list = [] batch_process_ballot_item_chunk_list_found = False batch_process_analytics_chunk_list = [] batch_process_analytics_chunk_list_found = False try: batch_process_chunk_queryset = BatchProcessBallotItemChunk.objects.all() batch_process_chunk_queryset = batch_process_chunk_queryset.filter(batch_process_id=batch_process.id) batch_process_chunk_queryset = batch_process_chunk_queryset.order_by("-id") batch_process_ballot_item_chunk_list = list(batch_process_chunk_queryset) batch_process_ballot_item_chunk_list_found = \ positive_value_exists(len(batch_process_ballot_item_chunk_list)) except BatchProcessBallotItemChunk.DoesNotExist: # BatchProcessBallotItemChunk not found. Not a problem. status += 'NO_BatchProcessBallotItemChunk_FOUND_DoesNotExist ' except Exception as e: status += 'FAILED BatchProcessBallotItemChunk ' + str(e) + ' ' batch_process.batch_process_ballot_item_chunk_list = batch_process_ballot_item_chunk_list batch_process.batch_process_ballot_item_chunk_list_found = batch_process_ballot_item_chunk_list_found if not positive_value_exists(batch_process_ballot_item_chunk_list_found): # Now check to see if this is an analytics try: batch_process_chunk_queryset = BatchProcessAnalyticsChunk.objects.all() batch_process_chunk_queryset = batch_process_chunk_queryset.filter(batch_process_id=batch_process.id) batch_process_chunk_queryset = batch_process_chunk_queryset.order_by("-id") batch_process_analytics_chunk_list = list(batch_process_chunk_queryset) batch_process_analytics_chunk_list_found = \ positive_value_exists(len(batch_process_analytics_chunk_list)) except BatchProcessBallotItemChunk.DoesNotExist: # BatchProcessBallotItemChunk not found. Not a problem. status += 'NO_BatchProcessAnalyticsChunk_FOUND_DoesNotExist ' except Exception as e: status += 'FAILED BatchProcessAnalyticsChunk ' + str(e) + ' ' batch_process.batch_process_analytics_chunk_list = batch_process_analytics_chunk_list batch_process.batch_process_analytics_chunk_list_found = batch_process_analytics_chunk_list_found # Make sure we always include the current election in the election_list, even if it is older use_ballotpedia_as_data_source = False use_ctcl_as_data_source = False use_vote_usa_as_data_source = False if positive_value_exists(google_civic_election_id): this_election_found = False for one_election in election_list: if convert_to_int(one_election.google_civic_election_id) == convert_to_int(google_civic_election_id): this_election_found = True use_ballotpedia_as_data_source = one_election.use_ballotpedia_as_data_source use_ctcl_as_data_source = one_election.use_ctcl_as_data_source use_vote_usa_as_data_source = one_election.use_vote_usa_as_data_source break if not this_election_found: results = election_manager.retrieve_election(google_civic_election_id) if results['election_found']: election = results['election'] use_ballotpedia_as_data_source = election.use_ballotpedia_as_data_source use_ctcl_as_data_source = election.use_ctcl_as_data_source use_vote_usa_as_data_source = election.use_vote_usa_as_data_source election_list.append(election) state_list = STATE_CODE_MAP state_list_modified = {} for one_state_code, one_state_name in state_list.items(): # office_count = batch_process_manager.fetch_office_count(google_civic_election_id, one_state_code) batch_process_count = 0 state_name_modified = one_state_name if positive_value_exists(batch_process_count): state_name_modified += " - " + str(batch_process_count) state_list_modified[one_state_code] = state_name_modified else: state_name_modified += "" state_list_modified[one_state_code] = state_name_modified sorted_state_list = sorted(state_list_modified.items()) # status_print_list = "" # status_print_list += "batch_process_list_count: " + \ # str(batch_process_list_count) + " " # # messages.add_message(request, messages.INFO, status_print_list) messages_on_stage = get_messages(request) from wevote_settings.models import fetch_batch_process_system_on, fetch_batch_process_system_activity_notices_on, \ fetch_batch_process_system_api_refresh_on, fetch_batch_process_system_ballot_items_on, \ fetch_batch_process_system_calculate_analytics_on, fetch_batch_process_system_search_twitter_on batch_process_system_on = fetch_batch_process_system_on() batch_process_system_activity_notices_on = fetch_batch_process_system_activity_notices_on() batch_process_system_api_refresh_on = fetch_batch_process_system_api_refresh_on() batch_process_system_ballot_items_on = fetch_batch_process_system_ballot_items_on() batch_process_system_calculate_analytics_on = fetch_batch_process_system_calculate_analytics_on() batch_process_system_search_twitter_on = fetch_batch_process_system_search_twitter_on() ballot_returned_oldest_date = "" ballot_returned_voter_oldest_date = "" if positive_value_exists(state_code) and positive_value_exists(google_civic_election_id): ballot_returned_list_manager = BallotReturnedListManager() ballot_returned_oldest_date = ballot_returned_list_manager.fetch_oldest_date_last_updated( google_civic_election_id, state_code) ballot_returned_voter_oldest_date = ballot_returned_list_manager.fetch_oldest_date_last_updated( google_civic_election_id, state_code, for_voter=True) toggle_system_url_variables = "s=1" # Add a dummy variable at the start so all remaining variables have & if positive_value_exists(include_frequent_processes): toggle_system_url_variables += "&include_frequent_processes=1" if positive_value_exists(kind_of_processes_to_show): toggle_system_url_variables += "&kind_of_processes_to_show=" + str(kind_of_processes_to_show) if positive_value_exists(show_active_processes_only): toggle_system_url_variables += "&show_active_processes_only=1" if positive_value_exists(show_checked_out_processes_only): toggle_system_url_variables += "&show_checked_out_processes_only=1" if positive_value_exists(show_paused_processes_only): toggle_system_url_variables += "&show_paused_processes_only=1" template_values = { 'messages_on_stage': messages_on_stage, 'ballot_returned_oldest_date': ballot_returned_oldest_date, 'ballot_returned_voter_oldest_date': ballot_returned_voter_oldest_date, 'batch_process_id': batch_process_id, 'batch_process_list': batch_process_list, 'batch_process_system_on': batch_process_system_on, 'batch_process_system_activity_notices_on': batch_process_system_activity_notices_on, 'batch_process_system_api_refresh_on': batch_process_system_api_refresh_on, 'batch_process_system_ballot_items_on': batch_process_system_ballot_items_on, 'batch_process_system_calculate_analytics_on': batch_process_system_calculate_analytics_on, 'batch_process_system_search_twitter_on': batch_process_system_search_twitter_on, 'batch_process_search': batch_process_search, 'election_list': election_list, 'google_civic_election_id': google_civic_election_id, 'include_frequent_processes': include_frequent_processes, 'kind_of_processes_to_show': kind_of_processes_to_show, 'show_all_elections': show_all_elections, 'show_active_processes_only': show_active_processes_only, 'show_paused_processes_only': show_paused_processes_only, 'show_checked_out_processes_only': show_checked_out_processes_only, 'state_code': state_code, 'state_list': sorted_state_list, 'toggle_system_url_variables': toggle_system_url_variables, 'use_ballotpedia_as_data_source': use_ballotpedia_as_data_source, 'use_ctcl_as_data_source': use_ctcl_as_data_source, 'use_vote_usa_as_data_source': use_vote_usa_as_data_source, } return render(request, 'import_export_batches/batch_process_list.html', template_values) def batch_process_next_steps_view(request): # json_results = batch_process_next_steps() status = "batch_process_next_steps_view-DEPRECATED " json_results = { 'success': False, 'status': status, } response = HttpResponse(json.dumps(json_results), content_type='application/json') return response @login_required def import_ballot_items_for_location_view(request): """ Reach out to external data source API to retrieve a ballot for one location. """ status = "" success = True # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'political_data_manager'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) google_civic_election_id = convert_to_int(request.GET.get('google_civic_election_id', 0)) polling_location_we_vote_id = request.GET.get('polling_location_we_vote_id', "") state_code = request.GET.get('state_code', "") use_ballotpedia = positive_value_exists(request.GET.get('use_ballotpedia', False)) use_ctcl = positive_value_exists(request.GET.get('use_ctcl', False)) use_vote_usa = positive_value_exists(request.GET.get('use_vote_usa', False)) if not positive_value_exists(google_civic_election_id): messages.add_message(request, messages.ERROR, 'Google Civic Election Id missing.') return HttpResponseRedirect(reverse('election:election_list', args=())) election_manager = ElectionManager() ctcl_election_uuid = '' election_day_text = '' use_ballotpedia_as_data_source = False use_ctcl_as_data_source = False use_vote_usa_as_data_source = False results = election_manager.retrieve_election(google_civic_election_id=google_civic_election_id) if results['election_found']: election = results['election'] ctcl_election_uuid = election.ctcl_uuid election_day_text = election.election_day_text use_ballotpedia_as_data_source = election.use_ballotpedia_as_data_source use_ctcl_as_data_source = election.use_ctcl_as_data_source use_vote_usa_as_data_source = election.use_vote_usa_as_data_source if positive_value_exists(use_ballotpedia): if not positive_value_exists(use_ballotpedia_as_data_source): success = False status += "USE_BALLOTPEDIA-BUT_NOT_USE_BALLOTPEDIA_AS_DATA_SOURCE " results = { 'status': status, 'success': success, } elif positive_value_exists(use_ctcl): if not positive_value_exists(use_ctcl_as_data_source): success = False status += "USE_CTCL-BUT_NOT_USE_CTCL_AS_DATA_SOURCE " results = { 'status': status, 'success': success, } elif positive_value_exists(use_vote_usa): if not positive_value_exists(use_vote_usa_as_data_source): success = False status += "USE_VOTE_USA-BUT_NOT_USE_VOTE_USA_AS_DATA_SOURCE " results = { 'status': status, 'success': success, } kind_of_batch = "" if success: update_or_create_rules = { 'create_candidates': True, 'create_offices': True, 'create_measures': True, 'update_candidates': False, 'update_offices': False, 'update_measures': False, } if positive_value_exists(use_ballotpedia): from import_export_ballotpedia.controllers import \ retrieve_ballotpedia_ballot_items_from_polling_location_api_v4 results = retrieve_ballotpedia_ballot_items_from_polling_location_api_v4( google_civic_election_id, election_day_text=election_day_text, polling_location_we_vote_id=polling_location_we_vote_id, state_code=state_code, ) elif positive_value_exists(use_ctcl): from import_export_ctcl.controllers import retrieve_ctcl_ballot_items_from_polling_location_api results = retrieve_ctcl_ballot_items_from_polling_location_api( google_civic_election_id, ctcl_election_uuid=ctcl_election_uuid, election_day_text=election_day_text, polling_location_we_vote_id=polling_location_we_vote_id, state_code=state_code, update_or_create_rules=update_or_create_rules, ) else: # Should not be possible to get here pass if 'kind_of_batch' in results: kind_of_batch = results['kind_of_batch'] if not positive_value_exists(kind_of_batch): kind_of_batch = IMPORT_BALLOT_ITEM batch_header_id = 0 if 'batch_saved' in results and results['batch_saved']: messages.add_message(request, messages.INFO, 'Ballot items import batch for {google_civic_election_id} ' 'election saved.' ''.format(google_civic_election_id=google_civic_election_id)) batch_header_id = results['batch_header_id'] elif 'batch_header_id' in results and results['batch_header_id']: messages.add_message(request, messages.INFO, 'Ballot items import batch for {google_civic_election_id} ' 'election saved, batch_header_id.' ''.format(google_civic_election_id=google_civic_election_id)) batch_header_id = results['batch_header_id'] else: messages.add_message(request, messages.ERROR, results['status']) if positive_value_exists(batch_header_id): # Go straight to the new batch return HttpResponseRedirect(reverse('import_export_batches:batch_action_list', args=()) + "?batch_header_id=" + str(batch_header_id) + "&kind_of_batch=" + str(kind_of_batch) + "&google_civic_election_id=" + str(google_civic_election_id)) else: # Go to the ballot_item_list_edit page if positive_value_exists(polling_location_we_vote_id): return HttpResponseRedirect(reverse('ballot:ballot_item_list_by_polling_location_edit', args=(polling_location_we_vote_id,)) + "?google_civic_election_id=" + str(google_civic_election_id) + "&polling_location_we_vote_id=" + str(polling_location_we_vote_id) + "&state_code=" + str(state_code) ) else: messages.add_message(request, messages.ERROR, "Missing polling_location_we_vote_id.") return HttpResponseRedirect(reverse('election:election_list', args=()) + "?google_civic_election_id=" + str(google_civic_election_id) + "&polling_location_we_vote_id=" + str(polling_location_we_vote_id) + "&state_code=" + str(state_code) ) def process_next_activity_notices_view(request): json_results = process_next_activity_notices() response = HttpResponse(json.dumps(json_results), content_type='application/json') return response def process_next_ballot_items_view(request): json_results = process_next_ballot_items() response = HttpResponse(json.dumps(json_results), content_type='application/json') return response def process_next_general_maintenance_view(request): json_results = process_next_general_maintenance() response = HttpResponse(json.dumps(json_results), content_type='application/json') return response @login_required def batch_process_pause_toggle_view(request): # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'political_data_manager'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) batch_process_id = request.GET.get('batch_process_id', 0) google_civic_election_id = convert_to_int(request.GET.get('google_civic_election_id', 0)) state_code = request.GET.get('state_code', '') batch_process_manager = BatchProcessManager() results = batch_process_manager.retrieve_batch_process(batch_process_id) if results['batch_process_found']: batch_process = results['batch_process'] try: current_setting = batch_process.batch_process_paused batch_process.batch_process_paused = not current_setting batch_process.save() message = "BATCH_PROCESS_PAUSED: " + str(batch_process.batch_process_paused) + " " messages.add_message(request, messages.INFO, message) except Exception as e: message = "COULD_NOT_SAVE_BATCH_PROCESS-BATCH_PROCESS_PAUSED " + str(e) + " " messages.add_message(request, messages.ERROR, message) else: message = "BATCH_PROCESS_COULD_NOT_BE_FOUND: " + str(batch_process_id) messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('import_export_batches:batch_process_list', args=()) + "?google_civic_election_id=" + str(google_civic_election_id) + "&state_code=" + str(state_code)) @login_required def batch_process_log_entry_list_view(request): # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'political_data_manager'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) status = "" success = True google_civic_election_id = convert_to_int(request.GET.get('google_civic_election_id', 0)) state_code = request.GET.get('state_code', '') show_all_elections = positive_value_exists(request.GET.get('show_all_elections', False)) batch_process_log_entry_search = request.GET.get('batch_process_log_entry_search', '') batch_process_id = convert_to_int(request.GET.get('batch_process_id', 0)) batch_process_chunk_id = convert_to_int(request.GET.get('batch_process_chunk_id', 0)) batch_process_log_entry_list_found = False batch_process_log_entry_list = [] election_manager = ElectionManager() if positive_value_exists(show_all_elections): results = election_manager.retrieve_elections() election_list = results['election_list'] else: results = election_manager.retrieve_upcoming_elections() election_list = results['election_list'] try: batch_process_queryset = BatchProcessLogEntry.objects.all() if positive_value_exists(batch_process_id): batch_process_queryset = batch_process_queryset.filter(batch_process_id=batch_process_id) if positive_value_exists(batch_process_chunk_id): batch_process_queryset = batch_process_queryset.filter( batch_process_ballot_item_chunk_id=batch_process_chunk_id) if positive_value_exists(google_civic_election_id): batch_process_queryset = batch_process_queryset.filter(google_civic_election_id=google_civic_election_id) elif positive_value_exists(show_all_elections): # Return offices from all elections pass else: # Limit this search to upcoming_elections only, or entries with no election google_civic_election_id_list = [0] for one_election in election_list: google_civic_election_id_list.append(one_election.google_civic_election_id) batch_process_queryset = batch_process_queryset.filter( google_civic_election_id__in=google_civic_election_id_list) if positive_value_exists(state_code): batch_process_queryset = batch_process_queryset.filter(state_code__iexact=state_code) batch_process_queryset = batch_process_queryset.order_by("-id") if positive_value_exists(batch_process_log_entry_search): search_words = batch_process_log_entry_search.split() for one_word in search_words: filters = [] # Reset for each search word new_filter = Q(batch_process_id__iexact=one_word) filters.append(new_filter) new_filter = Q(batch_set_id__iexact=one_word) filters.append(new_filter) new_filter = Q(google_civic_election_id__icontains=one_word) filters.append(new_filter) new_filter = Q(polling_location_we_vote_id__iexact=one_word) filters.append(new_filter) new_filter = Q(state_code__iexact=one_word) filters.append(new_filter) new_filter = Q(status__icontains=one_word) filters.append(new_filter) # Add the first query if len(filters): final_filters = filters.pop() # ...and "OR" the remaining items in the list for item in filters: final_filters |= item batch_process_queryset = batch_process_queryset.filter(final_filters) batch_process_log_entry_list_count = batch_process_queryset.count() batch_process_queryset = batch_process_queryset[:200] batch_process_log_entry_list = list(batch_process_queryset) if len(batch_process_log_entry_list): batch_process_log_entry_list_found = True status += 'BATCH_PROCESS_LOG_ENTRY_LIST_RETRIEVED ' else: status += 'BATCH_PROCESS_LOG_ENTRY_LIST_NOT_RETRIEVED ' except BatchProcessLogEntry.DoesNotExist: # No offices found. Not a problem. status += 'BATCH_PROCESS_LOG_ENTRY_DoesNotExist ' batch_process_log_entry_list = [] except Exception as e: status += 'FAILED-[retrieve_all_offices_for_upcoming_election]-ERROR ' + str(e) + " " success = False handle_exception(e, logger=logger, exception_message=status) # Make sure we always include the current election in the election_list, even if it is older if positive_value_exists(google_civic_election_id): this_election_found = False for one_election in election_list: if convert_to_int(one_election.google_civic_election_id) == convert_to_int(google_civic_election_id): this_election_found = True break if not this_election_found: results = election_manager.retrieve_election(google_civic_election_id) if results['election_found']: election = results['election'] election_list.append(election) state_list = STATE_CODE_MAP state_list_modified = {} for one_state_code, one_state_name in state_list.items(): # office_count = batch_process_manager.fetch_office_count(google_civic_election_id, one_state_code) batch_process_log_entry_count = 0 state_name_modified = one_state_name if positive_value_exists(batch_process_log_entry_count): state_name_modified += " - " + str(batch_process_log_entry_count) state_list_modified[one_state_code] = state_name_modified else: state_name_modified += "" state_list_modified[one_state_code] = state_name_modified sorted_state_list = sorted(state_list_modified.items()) messages_on_stage = get_messages(request) template_values = { 'messages_on_stage': messages_on_stage, 'batch_process_id': batch_process_id, 'batch_process_chunk_id': batch_process_chunk_id, 'batch_process_log_entry_list': batch_process_log_entry_list, 'batch_process_log_entry_search': batch_process_log_entry_search, 'election_list': election_list, 'state_code': state_code, 'show_all_elections': show_all_elections, 'state_list': sorted_state_list, 'google_civic_election_id': google_civic_election_id, } return render(request, 'import_export_batches/batch_process_log_entry_list.html', template_values) @login_required def batch_set_batch_list_view(request): """ Display row-by-row details of batch_set actions being reviewed, leading up to processing an entire batch_set. :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'verified_volunteer'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) batch_set_id = convert_to_int(request.GET.get('batch_set_id', 0)) if not positive_value_exists(batch_set_id): messages.add_message(request, messages.ERROR, 'Batch_set_id required.') return HttpResponseRedirect(reverse('import_export_batches:batch_set_list', args=())) google_civic_election_id = request.GET.get('google_civic_election_id', 0) analyze_all_button = request.GET.get('analyze_all_button', 0) create_all_button = request.GET.get('create_all_button', 0) analyze_for_deletes_button = request.GET.get('analyze_for_deletes_button', 0) delete_all_button = request.GET.get('delete_all_button', 0) show_all_batches = request.GET.get('show_all_batches', False) state_code = request.GET.get('state_code', "") update_all_button = request.GET.get('update_all_button', 0) batch_list_modified = [] batch_manager = BatchManager() batch_set_count = 0 batch_set_kind_of_batch = "" # Store static data in memory so we don't have to use the database election_objects_dict = {} office_objects_dict = {} measure_objects_dict = {} try: if positive_value_exists(analyze_all_button): batch_actions_analyzed = 0 batch_actions_not_analyzed = 0 batch_header_id_created_list = [] start_each_batch_time_tracker = [] # Array of times summary_of_create_batch_row_action_time_tracker = [] # Array of arrays batch_description_query = BatchDescription.objects.filter(batch_set_id=batch_set_id) batch_description_query = batch_description_query.filter(batch_description_analyzed=False) batch_list = list(batch_description_query) batch_list_not_analyzed_count = len(batch_list) # For this batch set, cycle through each batch. Within each batch, cycle through each batch_row # and decide whether the action required is create or update. for one_batch_description in batch_list: start_each_batch_time_tracker.append(now().strftime("%H:%M:%S:%f")) results = create_batch_row_actions( one_batch_description.batch_header_id, batch_description=one_batch_description, election_objects_dict=election_objects_dict, measure_objects_dict=measure_objects_dict, office_objects_dict=office_objects_dict, ) if results['batch_actions_created']: batch_actions_analyzed += 1 try: # If BatchRowAction's were created for BatchDescription, this batch_description was analyzed one_batch_description.batch_description_analyzed = True one_batch_description.save() batch_header_id_created_list.append(one_batch_description.batch_header_id) except Exception as e: pass else: batch_actions_not_analyzed += 1 # Keep building up these dicts so we don't have to retrieve data again-and-again from the database election_objects_dict = results['election_objects_dict'] measure_objects_dict = results['measure_objects_dict'] office_objects_dict = results['office_objects_dict'] start_create_batch_row_action_time_tracker = results['start_create_batch_row_action_time_tracker'] summary_of_create_batch_row_action_time_tracker.append(start_create_batch_row_action_time_tracker) # If there were not any entries with batch_description_analyzed set to False, then retrieve all if not positive_value_exists(batch_list_not_analyzed_count): batch_description_query = BatchDescription.objects.filter(batch_set_id=batch_set_id) if positive_value_exists(len(batch_header_id_created_list)): batch_description_query = batch_description_query.exclude( batch_header_id__in=batch_header_id_created_list) batch_list = list(batch_description_query) for one_batch_description in batch_list: start_each_batch_time_tracker.append(now().strftime("%H:%M:%S:%f")) results = create_batch_row_actions( one_batch_description.batch_header_id, batch_description=one_batch_description, election_objects_dict=election_objects_dict, measure_objects_dict=measure_objects_dict, office_objects_dict=office_objects_dict, ) if results['batch_actions_created']: batch_actions_analyzed += 1 try: # If BatchRowAction's were created for BatchDescription, this batch_description was analyzed one_batch_description.batch_description_analyzed = True one_batch_description.save() except Exception as e: pass else: batch_actions_not_analyzed += 1 # Keep building up these dicts so we don't have to retrieve data again-and-again from the database election_objects_dict = results['election_objects_dict'] measure_objects_dict = results['measure_objects_dict'] office_objects_dict = results['office_objects_dict'] start_create_batch_row_action_time_tracker = results['start_create_batch_row_action_time_tracker'] summary_of_create_batch_row_action_time_tracker.append(start_create_batch_row_action_time_tracker) if positive_value_exists(batch_actions_analyzed): messages.add_message(request, messages.INFO, "Analyze All, BatchRows Analyzed: " "" + str(batch_actions_analyzed)) if positive_value_exists(batch_actions_not_analyzed): messages.add_message(request, messages.ERROR, "Analyze All, BatchRows NOT Analyzed: " "" + str(batch_actions_not_analyzed)) return HttpResponseRedirect(reverse('import_export_batches:batch_set_batch_list', args=()) + "?google_civic_election_id=" + str(google_civic_election_id) + "&batch_set_id=" + str(batch_set_id) + "&state_code=" + state_code) if positive_value_exists(update_all_button): batch_description_query = BatchDescription.objects.filter(batch_set_id=batch_set_id) batch_description_query = batch_description_query.filter(batch_description_analyzed=True) batch_list = list(batch_description_query) batch_actions_updated = 0 batch_actions_not_updated = 0 for one_batch_description in batch_list: results = import_data_from_batch_row_actions( one_batch_description.kind_of_batch, IMPORT_ADD_TO_EXISTING, one_batch_description.batch_header_id) if results['number_of_table_rows_updated']: batch_actions_updated += 1 else: batch_actions_not_updated += 1 if positive_value_exists(batch_actions_updated): messages.add_message(request, messages.INFO, "Update in All Batches: " "" + str(batch_actions_updated) + ". ") if positive_value_exists(batch_actions_not_updated): messages.add_message(request, messages.ERROR, "Update in All Batches, Failed Updates: " "" + str(batch_actions_not_updated)) return HttpResponseRedirect(reverse('import_export_batches:batch_set_batch_list', args=()) + "?google_civic_election_id=" + str(google_civic_election_id) + "&batch_set_id=" + str(batch_set_id) + "&state_code=" + state_code) if positive_value_exists(create_all_button): batch_description_query = BatchDescription.objects.filter(batch_set_id=batch_set_id) batch_description_query = batch_description_query.filter(batch_description_analyzed=True) batch_list = list(batch_description_query) batch_actions_created = 0 not_created_status = "" for one_batch_description in batch_list: results = import_data_from_batch_row_actions( one_batch_description.kind_of_batch, IMPORT_CREATE, one_batch_description.batch_header_id) if results['number_of_table_rows_created']: batch_actions_created += 1 if not positive_value_exists(results['success']): if len(not_created_status) < 1024: not_created_status += results['status'] if positive_value_exists(batch_actions_created): messages.add_message(request, messages.INFO, "Create in All Batches: " "" + str(batch_actions_created) + ". ") if positive_value_exists(not_created_status): messages.add_message(request, messages.ERROR, "Create in All Batches, FAILED Creates: {not_created_status} " "".format(not_created_status=not_created_status)) return HttpResponseRedirect(reverse('import_export_batches:batch_set_batch_list', args=()) + "?google_civic_election_id=" + str(google_civic_election_id) + "&batch_set_id=" + str(batch_set_id) + "&state_code=" + state_code) if positive_value_exists(analyze_for_deletes_button): batch_actions_analyzed_for_deletes = 0 batch_header_id_created_list = [] batch_description_query = BatchDescription.objects.filter(batch_set_id=batch_set_id) batch_description_query = batch_description_query.filter(batch_description_analyzed=True) batch_list = list(batch_description_query) for one_batch_description in batch_list: results = create_batch_row_actions( one_batch_description.batch_header_id, batch_description=one_batch_description, delete_analysis_only=True, election_objects_dict=election_objects_dict, measure_objects_dict=measure_objects_dict, office_objects_dict=office_objects_dict, ) if results['batch_actions_created']: batch_actions_analyzed_for_deletes += 1 batch_header_id_created_list.append(one_batch_description.batch_header_id) election_objects_dict = results['election_objects_dict'] measure_objects_dict = results['measure_objects_dict'] office_objects_dict = results['office_objects_dict'] if positive_value_exists(batch_actions_analyzed_for_deletes): messages.add_message(request, messages.INFO, "Analyze For Deletes: " "" + str(batch_actions_analyzed_for_deletes)) return HttpResponseRedirect(reverse('import_export_batches:batch_set_batch_list', args=()) + "?google_civic_election_id=" + str(google_civic_election_id) + "&batch_set_id=" + str(batch_set_id) + "&state_code=" + state_code) if positive_value_exists(delete_all_button): batch_description_query = BatchDescription.objects.filter(batch_set_id=batch_set_id) batch_description_query = batch_description_query.filter(batch_description_analyzed=True) batch_list = list(batch_description_query) batch_actions_deleted = 0 not_deleted_status = "" for one_batch_description in batch_list: results = import_data_from_batch_row_actions( one_batch_description.kind_of_batch, IMPORT_DELETE, one_batch_description.batch_header_id) if results['number_of_table_rows_deleted']: batch_actions_deleted += 1 if not positive_value_exists(results['success']): if len(not_deleted_status) < 1024: not_deleted_status += results['status'] if positive_value_exists(batch_actions_deleted): messages.add_message(request, messages.INFO, "Deletes in All Batches: " "" + str(batch_actions_deleted) + ", ") if positive_value_exists(not_deleted_status): messages.add_message(request, messages.ERROR, "Create in All Batches, FAILED Creates: {not_deleted_status} " "".format(not_deleted_status=not_deleted_status)) return HttpResponseRedirect(reverse('import_export_batches:batch_set_batch_list', args=()) + "?google_civic_election_id=" + str(google_civic_election_id) + "&batch_set_id=" + str(batch_set_id) + "&state_code=" + state_code) batch_description_query = BatchDescription.objects.filter(batch_set_id=batch_set_id) batch_set_count = batch_description_query.count() if not positive_value_exists(show_all_batches): batch_list = batch_description_query[:10] else: batch_list = list(batch_description_query) # Loop through all batches and add count data for one_batch_description in batch_list: batch_header_id = one_batch_description.batch_header_id one_batch_description.number_of_batch_rows_imported = batch_manager.fetch_batch_row_count(batch_header_id) one_batch_description.number_of_batch_rows_analyzed = \ batch_manager.fetch_batch_row_action_count(batch_header_id, one_batch_description.kind_of_batch) one_batch_description.number_of_batch_actions_to_create = \ batch_manager.fetch_batch_row_action_count(batch_header_id, one_batch_description.kind_of_batch, IMPORT_CREATE) one_batch_description.number_of_table_rows_to_update = \ batch_manager.fetch_batch_row_action_count(batch_header_id, one_batch_description.kind_of_batch, IMPORT_ADD_TO_EXISTING) one_batch_description.number_of_table_rows_to_delete = \ batch_manager.fetch_batch_row_action_count(batch_header_id, one_batch_description.kind_of_batch, IMPORT_DELETE) one_batch_description.number_of_table_rows_already_deleted = \ batch_manager.fetch_batch_row_action_count(batch_header_id, one_batch_description.kind_of_batch, IMPORT_ALREADY_DELETED) one_batch_description.number_of_batch_actions_cannot_act = \ one_batch_description.number_of_batch_rows_analyzed - \ one_batch_description.number_of_batch_actions_to_create - \ one_batch_description.number_of_table_rows_to_update - \ one_batch_description.number_of_table_rows_to_delete - \ one_batch_description.number_of_table_rows_already_deleted batch_set_kind_of_batch = one_batch_description.kind_of_batch batch_list_modified.append(one_batch_description) except BatchDescription.DoesNotExist: # This is fine pass election_list = Election.objects.order_by('-election_day_text') status_message = '{batch_set_count} batches in this batch set. '.format(batch_set_count=batch_set_count) batch_row_items_to_create_for_this_set = batch_manager.fetch_batch_row_action_count_in_batch_set( batch_set_id, batch_set_kind_of_batch, IMPORT_CREATE) if positive_value_exists(batch_row_items_to_create_for_this_set): status_message += 'BatchRowActions to create: {batch_row_items_to_create_for_this_set} '.format( batch_row_items_to_create_for_this_set=batch_row_items_to_create_for_this_set) batch_row_items_to_update_for_this_set = batch_manager.fetch_batch_row_action_count_in_batch_set( batch_set_id, batch_set_kind_of_batch, IMPORT_ADD_TO_EXISTING) if positive_value_exists(batch_row_items_to_update_for_this_set): status_message += 'BatchRowActions to update: {batch_row_items_to_update_for_this_set} '.format( batch_row_items_to_update_for_this_set=batch_row_items_to_update_for_this_set) batch_row_items_to_delete_for_this_set = batch_manager.fetch_batch_row_action_count_in_batch_set( batch_set_id, batch_set_kind_of_batch, IMPORT_DELETE) if positive_value_exists(batch_row_items_to_delete_for_this_set): status_message += 'BatchRowActions to delete: {batch_row_items_to_delete_for_this_set} '.format( batch_row_items_to_delete_for_this_set=batch_row_items_to_delete_for_this_set) messages.add_message(request, messages.INFO, status_message) messages_on_stage = get_messages(request) template_values = { 'messages_on_stage': messages_on_stage, 'batch_set_id': batch_set_id, 'batch_list': batch_list_modified, 'election_list': election_list, 'google_civic_election_id': google_civic_election_id, 'show_all_batches': show_all_batches, } return render(request, 'import_export_batches/batch_set_batch_list.html', template_values) @login_required def refresh_ballots_for_voters_api_v4_view(request): """ :param request: :return: """ # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'political_data_manager'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) google_civic_election_id = convert_to_int(request.GET.get('google_civic_election_id', 0)) state_code = request.GET.get('state_code', '') use_batch_process = request.GET.get('use_batch_process', False) use_ballotpedia = request.GET.get('use_ballotpedia', False) use_ballotpedia = positive_value_exists(use_ballotpedia) use_ctcl = request.GET.get('use_ctcl', False) use_ctcl = positive_value_exists(use_ctcl) use_vote_usa = request.GET.get('use_vote_usa', False) use_vote_usa = positive_value_exists(use_vote_usa) if positive_value_exists(use_batch_process): from import_export_batches.controllers_batch_process import schedule_refresh_ballots_for_voters_api_v4 results = schedule_refresh_ballots_for_voters_api_v4( google_civic_election_id=google_civic_election_id, state_code=state_code, use_ballotpedia=use_ballotpedia, use_ctcl=use_ctcl, use_vote_usa=use_vote_usa) messages.add_message(request, messages.INFO, results['status']) return HttpResponseRedirect(reverse('import_export_batches:batch_process_list', args=()) + '?google_civic_election_id=' + str(google_civic_election_id) + '&state_code=' + str(state_code) ) else: return refresh_ballots_for_voters_api_v4_internal_view( request=request, from_browser=True, google_civic_election_id=google_civic_election_id, state_code=state_code, use_ballotpedia=use_ballotpedia, use_ctcl=use_ctcl, use_vote_usa=use_vote_usa) @login_required def retrieve_ballots_for_entire_election_api_v4_view(request): # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'political_data_manager'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) google_civic_election_id = convert_to_int(request.GET.get('google_civic_election_id', 0)) state_code_list = [] status = '' batch_process_manager = BatchProcessManager() use_ballotpedia = request.GET.get('use_ballotpedia', False) use_ballotpedia = positive_value_exists(use_ballotpedia) use_ctcl = request.GET.get('use_ctcl', False) use_ctcl = positive_value_exists(use_ctcl) use_vote_usa = request.GET.get('use_vote_usa', False) use_vote_usa = positive_value_exists(use_vote_usa) if not positive_value_exists(google_civic_election_id): status += "GOOGLE_CIVIC_ELECTION_ID_MISSING " messages.add_message(request, messages.INFO, status) return HttpResponseRedirect(reverse('import_export_batches:batch_process_list', args=())) # Retrieve list of states in this election, and then loop through each state election_manager = ElectionManager() election_results = election_manager.retrieve_election(google_civic_election_id) if election_results['election_found']: election = election_results['election'] state_code_list = election.state_code_list() status += "STATE_CODE_LIST: " + str(state_code_list) + " " if not positive_value_exists(len(state_code_list)): status += "STATE_CODE_LIST_MISSING " messages.add_message(request, messages.INFO, status) return HttpResponseRedirect(reverse('import_export_batches:batch_process_list', args=())) for state_code in state_code_list: # Refresh based on map points if batch_process_manager.is_batch_process_currently_scheduled( google_civic_election_id=google_civic_election_id, state_code=state_code, kind_of_process=REFRESH_BALLOT_ITEMS_FROM_POLLING_LOCATIONS): status += "(" + str(state_code) + ")-ALREADY_SCHEDULED_REFRESH_BALLOT_ITEMS_FROM_POLLING_LOCATIONS " else: from import_export_batches.controllers_batch_process import \ schedule_retrieve_ballots_for_polling_locations_api_v4 results = schedule_retrieve_ballots_for_polling_locations_api_v4( google_civic_election_id=google_civic_election_id, state_code=state_code, refresh_ballot_returned=True, use_ballotpedia=use_ballotpedia, use_ctcl=use_ctcl, use_vote_usa=use_vote_usa, ) if not positive_value_exists(results['success']): status += results['status'] # Refresh based on voter's who requested their own address if batch_process_manager.is_batch_process_currently_scheduled( google_civic_election_id=google_civic_election_id, state_code=state_code, kind_of_process=REFRESH_BALLOT_ITEMS_FROM_VOTERS): status += "(" + str(state_code) + ")-ALREADY_SCHEDULED_REFRESH_BALLOT_ITEMS_FROM_VOTERS " else: from import_export_batches.controllers_batch_process import schedule_refresh_ballots_for_voters_api_v4 results = schedule_refresh_ballots_for_voters_api_v4( google_civic_election_id=google_civic_election_id, state_code=state_code, use_ballotpedia=use_ballotpedia, use_ctcl=use_ctcl, use_vote_usa=use_vote_usa, ) if not positive_value_exists(results['success']): status += results['status'] # Retrieve first time for each map point if batch_process_manager.is_batch_process_currently_scheduled( google_civic_election_id=google_civic_election_id, state_code=state_code, kind_of_process=RETRIEVE_BALLOT_ITEMS_FROM_POLLING_LOCATIONS): status += "(" + str(state_code) + ")-ALREADY_SCHEDULED_RETRIEVE_BALLOT_ITEMS_FROM_POLLING_LOCATIONS " else: results = schedule_retrieve_ballots_for_polling_locations_api_v4( google_civic_election_id=google_civic_election_id, state_code=state_code, refresh_ballot_returned=False, use_ballotpedia=use_ballotpedia, use_ctcl=use_ctcl, use_vote_usa=use_vote_usa, ) if not positive_value_exists(results['success']): status += results['status'] messages.add_message(request, messages.INFO, status) return HttpResponseRedirect(reverse('import_export_batches:batch_process_list', args=())) def refresh_ballots_for_voters_api_v4_internal_view( request=None, from_browser=False, google_civic_election_id="", state_code="", date_last_updated_should_not_exceed=None, batch_process_ballot_item_chunk=None, use_ballotpedia=False, use_ctcl=False, use_vote_usa=False, ): status = "" success = True batch_process_id = 0 batch_process_ballot_item_chunk_id = 0 batch_set_id = 0 retrieve_row_count = 0 if positive_value_exists(use_ballotpedia) or positive_value_exists(use_ctcl) or positive_value_exists(use_vote_usa): # Continue pass else: status += "MISSING_REQUIRED_BALLOT_DATA_PROVIDER " success = False results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results try: if positive_value_exists(google_civic_election_id): election_on_stage = \ Election.objects.using('readonly').get(google_civic_election_id=google_civic_election_id) ballotpedia_election_id = election_on_stage.ballotpedia_election_id ctcl_election_uuid = election_on_stage.ctcl_uuid election_day_text = election_on_stage.election_day_text election_local_id = election_on_stage.id election_state_code = election_on_stage.get_election_state() election_name = election_on_stage.election_name is_national_election = election_on_stage.is_national_election else: message = 'Could not retrieve Ballotpedia ballots. Missing google_civic_election_id.' if from_browser: messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('election:election_list', args=())) else: success = False status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results except Election.MultipleObjectsReturned as e: message = 'Could not retrieve Ballotpedia ballots. More than one election found.' if from_browser: messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('election:election_list', args=())) else: success = False status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results except Election.DoesNotExist: message = 'Could not retrieve Ballotpedia ballots. Election could not be found.' if from_browser: messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('election:election_list', args=())) else: success = False status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results # Check to see if we have map point data related to the region(s) covered by this election # We request the ballot data for each map point as a way to build up our local data if not positive_value_exists(state_code) and positive_value_exists(google_civic_election_id): state_code = election_state_code # if positive_value_exists(is_national_election) and not positive_value_exists(state_code): # messages.add_message(request, messages.ERROR, # 'For National elections, a State Code is required in order to run any ' # 'Ballotpedia ballots preparation.') # return HttpResponseRedirect(reverse('election:election_summary', args=(election_local_id,))) ballot_returned_list_manager = BallotReturnedListManager() limit_voters_retrieved = MAP_POINTS_RETRIEVED_EACH_BATCH_CHUNK # 125. Formerly 250 and 111 # Retrieve voter_id entries from ballot_returned table, from oldest to newest if positive_value_exists(is_national_election) and positive_value_exists(state_code): results = ballot_returned_list_manager.retrieve_ballot_returned_list( google_civic_election_id=google_civic_election_id, for_voters=True, state_code=state_code, date_last_updated_should_not_exceed=date_last_updated_should_not_exceed, limit=limit_voters_retrieved) else: results = ballot_returned_list_manager.retrieve_ballot_returned_list( google_civic_election_id=google_civic_election_id, for_voters=True, date_last_updated_should_not_exceed=date_last_updated_should_not_exceed, limit=limit_voters_retrieved) if results['ballot_returned_list_found']: ballot_returned_list = results['ballot_returned_list'] else: ballot_returned_list = [] if len(ballot_returned_list) == 0: message = 'No ballot_returned items found for {election_name} for the state \'{state}\' earlier than ' \ 'date_last_updated_should_not_exceed: \'{date_last_updated_should_not_exceed}\'. ' \ '(refresh_ballots_for_voters_api_v4_internal_view)'.format( election_name=election_name, date_last_updated_should_not_exceed=date_last_updated_should_not_exceed, state=state_code) if from_browser: messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('election:election_summary', args=(election_local_id,))) else: status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results # If here, we know that we have some polling_locations to use in order to retrieve ballotpedia districts ballots_retrieved = 0 ballots_not_retrieved = 0 # If here, we assume we have already retrieved races for this election, and now we want to # put ballot items for this location onto a ballot existing_offices_by_election_dict = {} existing_candidate_objects_dict = {} existing_candidate_to_office_links_dict = {} existing_measure_objects_dict = {} new_office_we_vote_ids_list = [] new_candidate_we_vote_ids_list = [] new_measure_we_vote_ids_list = [] batch_set_id = 0 # Create Batch Set for ballot items import_date = date.today() batch_set_name = "Ballot items (from Voters v4) for " + election_name if positive_value_exists(state_code): batch_set_name += " (state " + str(state_code.upper()) + ")" if positive_value_exists(ballotpedia_election_id): batch_set_name += " - ballotpedia: " + str(ballotpedia_election_id) if positive_value_exists(ctcl_election_uuid): batch_set_name += " - CTCL " batch_set_name += " - " + str(import_date) try: batch_process_ballot_item_chunk_id = batch_process_ballot_item_chunk.id batch_process_id = batch_process_ballot_item_chunk.batch_process_id batch_set_id = batch_process_ballot_item_chunk.batch_set_id except Exception as e: pass batch_set_source = '' kind_of_batch = '' source_uri = '' if positive_value_exists(use_ballotpedia): batch_set_source = BATCH_SET_SOURCE_IMPORT_BALLOTPEDIA_BALLOT_ITEMS kind_of_batch = 'IMPORT_BALLOTPEDIA_BALLOT_ITEMS' source_uri = BALLOTPEDIA_API_SAMPLE_BALLOT_RESULTS_URL elif positive_value_exists(use_ctcl): batch_set_source = BATCH_SET_SOURCE_IMPORT_CTCL_BALLOT_ITEMS kind_of_batch = 'IMPORT_CTCL_BALLOT_ITEMS' source_uri = CTCL_VOTER_INFO_URL elif positive_value_exists(use_vote_usa): batch_set_source = BATCH_SET_SOURCE_IMPORT_VOTE_USA_BALLOT_ITEMS kind_of_batch = 'IMPORT_VOTE_USA_BALLOT_ITEMS' source_uri = BALLOTPEDIA_API_SAMPLE_BALLOT_RESULTS_URL if not positive_value_exists(batch_set_id): # create batch_set object try: batch_set = BatchSet.objects.create( batch_set_description_text="", batch_set_name=batch_set_name, batch_set_source=batch_set_source, batch_process_ballot_item_chunk_id=batch_process_ballot_item_chunk_id, batch_process_id=batch_process_id, google_civic_election_id=google_civic_election_id, source_uri=source_uri, import_date=import_date, state_code=state_code) batch_set_id = batch_set.id if positive_value_exists(batch_set_id): status += " BATCH_SET_SAVED-BALLOTS_FOR_VOTERS " except Exception as e: # Stop trying to save rows -- break out of the for loop status += " EXCEPTION_BATCH_SET " + str(e) + " " try: if positive_value_exists(batch_process_ballot_item_chunk_id): batch_process_ballot_item_chunk.batch_set_id = batch_set_id batch_process_ballot_item_chunk.save() except Exception as e: status += "UNABLE_TO_SAVE_BATCH_SET_ID_EARLY " + str(e) + " " if positive_value_exists(use_ballotpedia): from import_export_ballotpedia.controllers import retrieve_ballotpedia_ballot_items_for_one_voter_api_v4 elif positive_value_exists(use_ctcl): from import_export_ctcl.controllers import retrieve_ctcl_ballot_items_for_one_voter_api elif positive_value_exists(use_vote_usa): pass for ballot_returned in ballot_returned_list: if positive_value_exists(use_ballotpedia): one_ballot_results = retrieve_ballotpedia_ballot_items_for_one_voter_api_v4( google_civic_election_id, election_day_text=election_day_text, ballot_returned=ballot_returned, state_code=state_code, batch_set_id=batch_set_id, existing_offices_by_election_dict=existing_offices_by_election_dict, existing_candidate_objects_dict=existing_candidate_objects_dict, existing_candidate_to_office_links_dict=existing_candidate_to_office_links_dict, existing_measure_objects_dict=existing_measure_objects_dict, new_office_we_vote_ids_list=new_office_we_vote_ids_list, new_candidate_we_vote_ids_list=new_candidate_we_vote_ids_list, new_measure_we_vote_ids_list=new_measure_we_vote_ids_list ) elif positive_value_exists(use_ctcl): one_ballot_results = retrieve_ctcl_ballot_items_for_one_voter_api( google_civic_election_id, ctcl_election_uuid=ctcl_election_uuid, election_day_text=election_day_text, ballot_returned=ballot_returned, state_code=state_code, batch_set_id=batch_set_id, existing_offices_by_election_dict=existing_offices_by_election_dict, existing_candidate_objects_dict=existing_candidate_objects_dict, existing_candidate_to_office_links_dict=existing_candidate_to_office_links_dict, existing_measure_objects_dict=existing_measure_objects_dict, new_office_we_vote_ids_list=new_office_we_vote_ids_list, new_candidate_we_vote_ids_list=new_candidate_we_vote_ids_list, new_measure_we_vote_ids_list=new_measure_we_vote_ids_list, update_or_create_rules={}) else: # It shouldn't be possible to get here pass success = False if one_ballot_results['success']: success = True if len(status) < 1024: status += one_ballot_results['status'] existing_offices_by_election_dict = one_ballot_results['existing_offices_by_election_dict'] existing_candidate_objects_dict = one_ballot_results['existing_candidate_objects_dict'] existing_candidate_to_office_links_dict = one_ballot_results['existing_candidate_to_office_links_dict'] existing_measure_objects_dict = one_ballot_results['existing_measure_objects_dict'] new_office_we_vote_ids_list = one_ballot_results['new_office_we_vote_ids_list'] new_candidate_we_vote_ids_list = one_ballot_results['new_candidate_we_vote_ids_list'] new_measure_we_vote_ids_list = one_ballot_results['new_measure_we_vote_ids_list'] if success: ballots_retrieved += 1 else: ballots_not_retrieved += 1 existing_offices_found = 0 if google_civic_election_id in existing_offices_by_election_dict: existing_offices_found = len(existing_offices_by_election_dict[google_civic_election_id]) existing_candidates_found = len(existing_candidate_objects_dict) existing_measures_found = len(existing_measure_objects_dict) new_offices_found = len(new_office_we_vote_ids_list) new_candidates_found = len(new_candidate_we_vote_ids_list) new_measures_found = len(new_measure_we_vote_ids_list) retrieve_row_count = ballots_retrieved message = \ 'Ballot data retrieved (Voters) for the {election_name}. ' \ 'ballots retrieved: {ballots_retrieved}. ' \ 'ballots not retrieved: {ballots_not_retrieved}. ' \ 'new offices: {new_offices_found} (existing: {existing_offices_found}) ' \ 'new candidates: {new_candidates_found} (existing: {existing_candidates_found}) ' \ 'new measures: {new_measures_found} (existing: {existing_measures_found}) ' \ ''.format( ballots_retrieved=ballots_retrieved, ballots_not_retrieved=ballots_not_retrieved, election_name=election_name, existing_offices_found=existing_offices_found, existing_candidates_found=existing_candidates_found, existing_measures_found=existing_measures_found, new_offices_found=new_offices_found, new_candidates_found=new_candidates_found, new_measures_found=new_measures_found, ) if from_browser: messages.add_message(request, messages.INFO, message) messages.add_message(request, messages.INFO, 'status: {status}'.format(status=status)) return HttpResponseRedirect(reverse('import_export_batches:batch_set_list', args=()) + '?kind_of_batch=' + str(kind_of_batch) + '&google_civic_election_id=' + str(google_civic_election_id)) else: status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, 'batch_process_ballot_item_chunk': batch_process_ballot_item_chunk, } return results @login_required def retrieve_ballots_for_polling_locations_api_v4_view(request): """ This is different than retrieve_ballotpedia_data_for_polling_locations_view because it is getting the districts from lat/long, and then the ballot items. Ballotpedia API v4 Reach out to Ballotpedia and retrieve (for one election): 1) Polling locations (so we can use those addresses to retrieve a representative set of ballots) 2) Cycle through a portion of those map points, enough that we are caching all of the possible ballot items :param request: :return: """ status = "" # admin, analytics_admin, partner_organization, political_data_manager, political_data_viewer, verified_volunteer authority_required = {'political_data_manager'} if not voter_has_authority(request, authority_required): return redirect_to_sign_in_page(request, authority_required) google_civic_election_id = convert_to_int(request.GET.get('google_civic_election_id', 0)) state_code = request.GET.get('state_code', '') refresh_ballot_returned = request.GET.get('refresh_ballot_returned', False) use_batch_process = request.GET.get('use_batch_process', False) use_ballotpedia = request.GET.get('use_ballotpedia', False) use_ballotpedia = positive_value_exists(use_ballotpedia) use_ctcl = request.GET.get('use_ctcl', False) use_ctcl = positive_value_exists(use_ctcl) use_vote_usa = request.GET.get('use_vote_usa', False) use_vote_usa = positive_value_exists(use_vote_usa) # import_limit = convert_to_int(request.GET.get('import_limit', 1000)) # If > 1000, we get error 414 (url too long) if positive_value_exists(use_batch_process): from import_export_batches.controllers_batch_process import \ schedule_retrieve_ballots_for_polling_locations_api_v4 results = schedule_retrieve_ballots_for_polling_locations_api_v4( google_civic_election_id=google_civic_election_id, state_code=state_code, refresh_ballot_returned=refresh_ballot_returned, use_ballotpedia=use_ballotpedia, use_ctcl=use_ctcl, use_vote_usa=use_vote_usa) messages.add_message(request, messages.INFO, results['status']) return HttpResponseRedirect(reverse('import_export_batches:batch_process_list', args=()) + '?google_civic_election_id=' + str(google_civic_election_id) + '&state_code=' + str(state_code) ) else: return retrieve_ballots_for_polling_locations_api_v4_internal_view( request=request, from_browser=True, google_civic_election_id=google_civic_election_id, state_code=state_code, refresh_ballot_returned=refresh_ballot_returned, use_ballotpedia=use_ballotpedia, use_ctcl=use_ctcl, use_vote_usa=use_vote_usa) def retrieve_ballots_for_polling_locations_api_v4_internal_view( request=None, from_browser=False, google_civic_election_id="", state_code="", refresh_ballot_returned=False, date_last_updated_should_not_exceed=None, batch_process_ballot_item_chunk=None, use_ballotpedia=False, use_ctcl=False, use_vote_usa=False): status = "" success = True batch_process_id = 0 batch_process_ballot_item_chunk_id = 0 batch_set_id = 0 retrieve_row_count = 0 ballot_returned_manager = BallotReturnedManager() try: if positive_value_exists(google_civic_election_id): election_on_stage = \ Election.objects.using('readonly').get(google_civic_election_id=google_civic_election_id) ballotpedia_election_id = election_on_stage.ballotpedia_election_id ctcl_election_uuid = election_on_stage.ctcl_uuid election_day_text = election_on_stage.election_day_text election_local_id = election_on_stage.id election_state_code = election_on_stage.get_election_state() election_name = election_on_stage.election_name is_national_election = election_on_stage.is_national_election use_ballotpedia_as_data_source = election_on_stage.use_ballotpedia_as_data_source use_ctcl_as_data_source = election_on_stage.use_ctcl_as_data_source use_vote_usa_as_data_source = election_on_stage.use_vote_usa_as_data_source else: message = 'Could not retrieve (as opposed to refresh) ballots. ' \ 'Missing google_civic_election_id. ' if from_browser: messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('election:election_list', args=())) else: success = False status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results except Election.MultipleObjectsReturned as e: message = 'Could not retrieve (as opposed to refresh) ballots. ' \ 'More than one election found. ' + str(e) + ' ' if from_browser: messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('election:election_list', args=())) else: success = False status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results except Election.DoesNotExist: message = 'Could not retrieve (as opposed to refresh) ballots. Election could not be found. ' if from_browser: messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('election:election_list', args=())) else: success = False status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results except Exception as e: message = 'Could not retrieve (as opposed to refresh) ballots. ERROR: ' + str(e) + ' ' if from_browser: messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('election:election_list', args=())) else: success = False status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results if positive_value_exists(use_ballotpedia): if not positive_value_exists(use_ballotpedia_as_data_source): success = False status += "USE_BALLOTPEDIA-BUT_NOT_USE_BALLOTPEDIA_AS_DATA_SOURCE " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results elif positive_value_exists(use_ctcl): if not positive_value_exists(use_ctcl_as_data_source): success = False status += "USE_CTCL-BUT_NOT_USE_CTCL_AS_DATA_SOURCE " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results elif positive_value_exists(use_vote_usa): if not positive_value_exists(use_vote_usa_as_data_source): success = False status += "USE_VOTE_USA-BUT_NOT_USE_VOTE_USA_AS_DATA_SOURCE " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results # Check to see if we have map point data related to the region(s) covered by this election # We request the ballot data for each map point as a way to build up our local data if not positive_value_exists(state_code) and positive_value_exists(google_civic_election_id): state_code = election_state_code if positive_value_exists(is_national_election) and not positive_value_exists(state_code): message = \ 'For National elections, a State Code is required in order to run any ballot preparation. ' if from_browser: messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('election:election_summary', args=(election_local_id,))) else: success = False status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results try: ballot_returned_list_manager = BallotReturnedListManager() if positive_value_exists(refresh_ballot_returned): limit_polling_locations_retrieved = MAP_POINTS_RETRIEVED_EACH_BATCH_CHUNK # 125. Formerly 250 and 111 else: limit_polling_locations_retrieved = 0 # Retrieve map points already in ballot_returned table if positive_value_exists(is_national_election) and positive_value_exists(state_code): status += "NATIONAL_WITH_STATE (" + str(state_code) + ") " status += "date_last_updated_should_not_exceed: " + str(date_last_updated_should_not_exceed) + ' ' results = ballot_returned_list_manager.retrieve_polling_location_we_vote_id_list_from_ballot_returned( google_civic_election_id=google_civic_election_id, state_code=state_code, limit=limit_polling_locations_retrieved, date_last_updated_should_not_exceed=date_last_updated_should_not_exceed, ) else: status += "WITHOUT_STATE " status += "date_last_updated_should_not_exceed: " + str(date_last_updated_should_not_exceed) + ' ' results = ballot_returned_list_manager.retrieve_polling_location_we_vote_id_list_from_ballot_returned( google_civic_election_id=google_civic_election_id, limit=limit_polling_locations_retrieved, date_last_updated_should_not_exceed=date_last_updated_should_not_exceed, ) status += results['status'] if results['polling_location_we_vote_id_list_found']: polling_location_we_vote_id_list = results['polling_location_we_vote_id_list'] else: polling_location_we_vote_id_list = [] status += "REFRESH_BALLOT_RETURNED: " + str(refresh_ballot_returned) + " " if positive_value_exists(refresh_ballot_returned): polling_location_query = PollingLocation.objects.using('readonly').all() polling_location_query = polling_location_query.filter(we_vote_id__in=polling_location_we_vote_id_list) # We don't exclude the deleted map points because we need to know to delete the ballot returned entry # polling_location_query = polling_location_query.exclude(polling_location_deleted=True) polling_location_list = list(polling_location_query) polling_location_count = len(polling_location_list) else: polling_location_query = PollingLocation.objects.using('readonly').all() polling_location_query = \ polling_location_query.exclude(Q(latitude__isnull=True) | Q(latitude__exact=0.0)) polling_location_query = \ polling_location_query.exclude(Q(zip_long__isnull=True) | Q(zip_long__exact='0') | Q(zip_long__exact='')) polling_location_query = polling_location_query.filter(state__iexact=state_code) # Exclude map points already retrieved or deleted polling_location_query = polling_location_query.exclude(we_vote_id__in=polling_location_we_vote_id_list) polling_location_query = polling_location_query.exclude(polling_location_deleted=True) # Randomly change the sort order so we over time load different map points (before timeout) random_sorting = random.randint(1, 5) first_retrieve_limit = MAP_POINTS_RETRIEVED_EACH_BATCH_CHUNK # 125. Formerly 250 and 111 if random_sorting == 1: # Ordering by "line1" creates a bit of (locational) random order polling_location_list = polling_location_query.order_by('line1')[:first_retrieve_limit] status += "RANDOM_SORTING-LINE1-ASC: " + str(random_sorting) + " " elif random_sorting == 2: polling_location_list = polling_location_query.order_by('-line1')[:first_retrieve_limit] status += "RANDOM_SORTING-LINE1-DESC: " + str(random_sorting) + " " elif random_sorting == 3: polling_location_list = polling_location_query.order_by('city')[:first_retrieve_limit] status += "RANDOM_SORTING-CITY-ASC: " + str(random_sorting) + " " else: polling_location_list = polling_location_query.order_by('-city')[:first_retrieve_limit] status += "RANDOM_SORTING-CITY-DESC: " + str(random_sorting) + " " polling_location_count = len(polling_location_list) # Cycle through -- if the polling_location is deleted, delete the associated ballot_returned, # and then remove the polling_location from the list modified_polling_location = [] for one_polling_location in polling_location_list: if positive_value_exists(one_polling_location.polling_location_deleted): delete_results = ballot_returned_manager.delete_ballot_returned_by_identifier( google_civic_election_id=google_civic_election_id, polling_location_we_vote_id=one_polling_location.we_vote_id) if delete_results['ballot_deleted']: status += "BR_PL_DELETED (" + str(one_polling_location.we_vote_id) + ") " else: status += "BR_PL_NOT_DELETED (" + str(one_polling_location.we_vote_id) + ") " else: modified_polling_location.append(one_polling_location) polling_location_list = modified_polling_location polling_location_count = len(polling_location_list) except PollingLocation.DoesNotExist: message = 'Could not retrieve (as opposed to refresh) ballot data for the {election_name}. ' \ 'Ballots-No map points exist for the state \'{state}\'. ' \ ''.format( election_name=election_name, state=state_code) if from_browser: messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('election:election_summary', args=(election_local_id,))) else: success = False status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results except Exception as e: message = 'Could not retrieve (as opposed to refresh) ballot data for the {election_name}. ' \ 'Ballots-No map points exist for the state \'{state}\'. ERROR: {error}' \ ''.format( election_name=election_name, error=str(e), state=state_code) if from_browser: messages.add_message(request, messages.ERROR, message) return HttpResponseRedirect(reverse('election:election_summary', args=(election_local_id,))) else: success = False status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results if polling_location_count == 0: message = 'Did not retrieve (as opposed to refresh) ballot data for the {election_name}. ' \ 'Data for all map points for the state \'{state}\' has been retrieved once ' \ 'date_last_updated_should_not_exceed: \'{date_last_updated_should_not_exceed}\'. ' \ '(result 2 - retrieve_ballots_for_polling_locations_api_v4_view)'.format( election_name=election_name, date_last_updated_should_not_exceed=date_last_updated_should_not_exceed, state=state_code) if from_browser: messages.add_message(request, messages.INFO, message) return HttpResponseRedirect(reverse('election:election_summary', args=(election_local_id,))) else: status += message + " " results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, } return results # If here, we know that we have some polling_locations to use in order to retrieve ballotpedia districts ballots_retrieved = 0 ballots_not_retrieved = 0 # If here, we assume we have already retrieved races for this election, and now we want to # put ballot items for this location onto a ballot existing_offices_by_election_dict = {} existing_candidate_objects_dict = {} existing_candidate_to_office_links_dict = {} existing_measure_objects_dict = {} new_office_we_vote_ids_list = [] new_candidate_we_vote_ids_list = [] new_measure_we_vote_ids_list = [] batch_set_source = '' source_uri = '' if positive_value_exists(use_ballotpedia): batch_set_source = BATCH_SET_SOURCE_IMPORT_BALLOTPEDIA_BALLOT_ITEMS source_uri = BALLOTPEDIA_API_SAMPLE_BALLOT_RESULTS_URL elif positive_value_exists(use_ctcl): batch_set_source = BATCH_SET_SOURCE_IMPORT_CTCL_BALLOT_ITEMS source_uri = CTCL_VOTER_INFO_URL elif positive_value_exists(use_vote_usa): # from import_export_ballotpedia. # controllers import retrieve_ballotpedia_ballot_items_from_polling_location_api_v4 batch_set_source = BATCH_SET_SOURCE_IMPORT_VOTE_USA_BALLOT_ITEMS source_uri = BALLOTPEDIA_API_SAMPLE_BALLOT_RESULTS_URL batch_set_id = 0 if len(polling_location_list) > 0: status += "POLLING_LOCATIONS_FOR_THIS_BATCH_SET: " + str(len(polling_location_list)) + " " # Create Batch Set for ballot items import_date = date.today() batch_set_name = "Ballot items (from Map Points v4) for " + election_name if positive_value_exists(state_code): batch_set_name += " (state " + str(state_code.upper()) + ")" if positive_value_exists(ballotpedia_election_id): batch_set_name += " - ballotpedia: " + str(ballotpedia_election_id) batch_set_name += " - " + str(import_date) try: batch_process_ballot_item_chunk_id = batch_process_ballot_item_chunk.id batch_process_id = batch_process_ballot_item_chunk.batch_process_id batch_set_id = batch_process_ballot_item_chunk.batch_set_id except Exception as e: status += "BATCH_PROCESS_BALLOT_ITEM_CHUNK: " + str(e) + ' ' if not positive_value_exists(batch_set_id): # create batch_set object try: batch_set = BatchSet.objects.create( batch_set_description_text="", batch_set_name=batch_set_name, batch_set_source=batch_set_source, batch_process_id=batch_process_id, batch_process_ballot_item_chunk_id=batch_process_ballot_item_chunk_id, google_civic_election_id=google_civic_election_id, source_uri=source_uri, import_date=import_date, state_code=state_code) batch_set_id = batch_set.id status += " BATCH_SET_CREATED-BALLOTS_FOR_POLLING_LOCATIONS " except Exception as e: # Stop trying to save rows -- break out of the for loop status += " EXCEPTION_BATCH_SET " + str(e) + " " handle_exception(e, logger=logger, exception_message=status) success = False try: if positive_value_exists(batch_process_ballot_item_chunk_id) and positive_value_exists(batch_set_id): batch_process_ballot_item_chunk.batch_set_id = batch_set_id batch_process_ballot_item_chunk.save() except Exception as e: status += "UNABLE_TO_SAVE_BATCH_SET_ID_EARLY " + str(e) + " " handle_exception(e, logger=logger, exception_message=status) update_or_create_rules = { 'create_candidates': True, 'create_offices': True, 'create_measures': True, 'update_candidates': False, 'update_offices': False, 'update_measures': False, } if success: if positive_value_exists(use_ballotpedia): from import_export_ballotpedia.controllers import \ retrieve_ballotpedia_ballot_items_from_polling_location_api_v4 elif positive_value_exists(use_ctcl): from import_export_ctcl.controllers import retrieve_ctcl_ballot_items_from_polling_location_api for polling_location in polling_location_list: one_ballot_results = {} if positive_value_exists(use_ballotpedia): one_ballot_results = retrieve_ballotpedia_ballot_items_from_polling_location_api_v4( google_civic_election_id, election_day_text=election_day_text, polling_location_we_vote_id=polling_location.we_vote_id, polling_location=polling_location, state_code=state_code, batch_set_id=batch_set_id, existing_offices_by_election_dict=existing_offices_by_election_dict, existing_candidate_objects_dict=existing_candidate_objects_dict, existing_candidate_to_office_links_dict=existing_candidate_to_office_links_dict, existing_measure_objects_dict=existing_measure_objects_dict, new_office_we_vote_ids_list=new_office_we_vote_ids_list, new_candidate_we_vote_ids_list=new_candidate_we_vote_ids_list, new_measure_we_vote_ids_list=new_measure_we_vote_ids_list ) elif positive_value_exists(use_ctcl): one_ballot_results = retrieve_ctcl_ballot_items_from_polling_location_api( google_civic_election_id, ctcl_election_uuid=ctcl_election_uuid, election_day_text=election_day_text, polling_location_we_vote_id=polling_location.we_vote_id, polling_location=polling_location, state_code=state_code, batch_set_id=batch_set_id, existing_offices_by_election_dict=existing_offices_by_election_dict, existing_candidate_objects_dict=existing_candidate_objects_dict, existing_candidate_to_office_links_dict=existing_candidate_to_office_links_dict, existing_measure_objects_dict=existing_measure_objects_dict, new_office_we_vote_ids_list=new_office_we_vote_ids_list, new_candidate_we_vote_ids_list=new_candidate_we_vote_ids_list, new_measure_we_vote_ids_list=new_measure_we_vote_ids_list, update_or_create_rules=update_or_create_rules, ) else: # Should not be possible to get here pass if one_ballot_results and 'success' in one_ballot_results and one_ballot_results['success']: success = True existing_offices_by_election_dict = one_ballot_results['existing_offices_by_election_dict'] existing_candidate_objects_dict = one_ballot_results['existing_candidate_objects_dict'] existing_candidate_to_office_links_dict = one_ballot_results['existing_candidate_to_office_links_dict'] existing_measure_objects_dict = one_ballot_results['existing_measure_objects_dict'] new_office_we_vote_ids_list = one_ballot_results['new_office_we_vote_ids_list'] new_candidate_we_vote_ids_list = one_ballot_results['new_candidate_we_vote_ids_list'] new_measure_we_vote_ids_list = one_ballot_results['new_measure_we_vote_ids_list'] if one_ballot_results['batch_header_id']: ballots_retrieved += 1 if ballots_retrieved < 5: status += "BALLOT_ITEMS_RETRIEVED: [[[" + one_ballot_results['status'] + "]]] " else: ballots_not_retrieved += 1 if ballots_not_retrieved < 5: status += "BALLOT_ITEMS_NOT_RETRIEVED: [[[" + one_ballot_results['status'] + "]]] " else: status += "CANNOT_CALL_RETRIEVE_BECAUSE_OF_ERRORS " \ "[retrieve_ballots_for_polling_locations_api_v4_internal_view] " retrieve_row_count = ballots_retrieved existing_offices_found = 0 if google_civic_election_id in existing_offices_by_election_dict: existing_offices_found = len(existing_offices_by_election_dict[google_civic_election_id]) existing_candidates_found = len(existing_candidate_objects_dict) existing_measures_found = len(existing_measure_objects_dict) new_offices_found = len(new_office_we_vote_ids_list) new_candidates_found = len(new_candidate_we_vote_ids_list) new_measures_found = len(new_measure_we_vote_ids_list) if from_browser: messages.add_message(request, messages.INFO, 'Ballot data retrieved from Map Points for the {election_name}. ' 'ballots retrieved: {ballots_retrieved}, ' 'ballots NOT retrieved: {ballots_not_retrieved}. ' 'new offices: {new_offices_found} (existing: {existing_offices_found}) ' 'new candidates: {new_candidates_found} (existing: {existing_candidates_found}) ' 'new measures: {new_measures_found} (existing: {existing_measures_found}) ' ''.format( ballots_retrieved=ballots_retrieved, ballots_not_retrieved=ballots_not_retrieved, election_name=election_name, existing_offices_found=existing_offices_found, existing_candidates_found=existing_candidates_found, existing_measures_found=existing_measures_found, new_offices_found=new_offices_found, new_candidates_found=new_candidates_found, new_measures_found=new_measures_found, )) messages.add_message(request, messages.INFO, 'status: {status}'.format(status=status)) return HttpResponseRedirect(reverse('import_export_batches:batch_set_list', args=()) + '?kind_of_batch=IMPORT_BALLOTPEDIA_BALLOT_ITEMS' + '&google_civic_election_id=' + str(google_civic_election_id)) else: status += \ 'Ballot data retrieved for the {election_name} (from Map Points). ' \ 'ballots retrieved: {ballots_retrieved}. ' \ 'ballots NOT retrieved: {ballots_not_retrieved}. ' \ 'new offices: {new_offices_found} (existing: {existing_offices_found}) ' \ 'new candidates: {new_candidates_found} (existing: {existing_candidates_found}) ' \ 'new measures: {new_measures_found} (existing: {existing_measures_found}) ' \ ''.format( ballots_retrieved=ballots_retrieved, ballots_not_retrieved=ballots_not_retrieved, election_name=election_name, existing_offices_found=existing_offices_found, existing_candidates_found=existing_candidates_found, existing_measures_found=existing_measures_found, new_offices_found=new_offices_found, new_candidates_found=new_candidates_found, new_measures_found=new_measures_found, ) results = { 'status': status, 'success': success, 'batch_set_id': batch_set_id, 'retrieve_row_count': retrieve_row_count, 'batch_process_ballot_item_chunk': batch_process_ballot_item_chunk, } return results

52.022803

120

0.665271

21,689

187,074

5.239338

0.02937

0.034743

0.039627

0.043798

0.861092

0.825759

0.770583

0.729074

0.694507

0.664358

0

0.002726

0.26659

187,074

3,595

121

52.037274

0.825513

0.081273

0

0.660221

0

0.13044

0.065089

0

0.000278

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false

0.007251

0.064227

0

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0

null

0

1

0

1

0

null

0

5

91cfeeb47c92f7c340a82ac4bd5cbf691c3ef8e8

105

py

Python

pyclick/__init__.py

hsluoyz/pyclick

225a595feaa02247383f082dc6b24f43dcebad29

[ "MIT" ]

93

2019-02-24T22:26:24.000Z

2022-03-03T10:30:45.000Z

pyclick/__init__.py

hsluoyz/pyclick

225a595feaa02247383f082dc6b24f43dcebad29

[ "MIT" ]

7

2021-03-18T21:12:04.000Z

2022-03-11T23:31:40.000Z

pyclick/__init__.py

hsluoyz/pyclick

225a595feaa02247383f082dc6b24f43dcebad29

[ "MIT" ]

29

2019-02-24T22:26:35.000Z

2022-03-11T07:59:51.000Z

name = 'pyclick' from pyclick.humanclicker import HumanClicker from pyclick.humancurve import HumanCurve

26.25

45

0.847619

12

105

7.416667

0.5

0.247191

0

0.104762

105

3

46

35

0.946809

0

0.066667

0

1

0

false

0

0.666667

0

0.666667

0

1

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null

1

0

1

0

null

0

1

0

1

0

5

91e247a668b6295dc959036fa3e8f6ccc960afff

2,613

py

Python

Alames/rightwidget.py

KLZ-0/Alames

cc9af04674706af2ddbfe955046021acf8bedffa

[ "MIT" ]

null

Alames/rightwidget.py

KLZ-0/Alames

cc9af04674706af2ddbfe955046021acf8bedffa

[ "MIT" ]

null

Alames/rightwidget.py

KLZ-0/Alames

cc9af04674706af2ddbfe955046021acf8bedffa

[ "MIT" ]

null

from Alames.importer import * from Alames.basewidget import BaseWidget from Alames.generated.ui_rightwidget import Ui_RightWidget from Alames import rightwidgetsection class RightWidget(BaseWidget, Ui_RightWidget): """ Purpose: relative positioning of internal labels Creates a widget inside MainWindow which is shared for max 3 widgets Same lvl as chartview > an object from this class is created in Chart """ DEFAULT_VISIBLE_SECTION_NUM = 0 _sections = [] loaded = QtCore.pyqtSignal() sectionUpdated = QtCore.pyqtSignal() ######## Widget setup def setup(self): super(RightWidget, self).setup() self._truncate() i = 0 for serie in self.chart.series(): self._sections.append(rightwidgetsection.RightWidgetSection(self, serie)) self._sections[-1].updated.connect(self.sectionUpdated.emit) # Show first n sections if i < self.DEFAULT_VISIBLE_SECTION_NUM: self._sections[-1].setProperty("visible_by_default", True) self._sections[-1].show() else: self._sections[-1].setProperty("visible_by_default", False) self._sections[-1].hide() self.scrollArea.widget().layout().addWidget(self._sections[-1]) # print(self.parent().rightWidget.objectName(), self.widget()) i += 1 self.loaded.emit() ######## External section management def getSectionLen(self): return len(self._sections) def getSectionName(self, num): return self._sections[num].getName() def isVisibleSection(self, num): return self._sections[num].isVisible() def getVisibleSectionSeries(self): # FIXME: Leak return [section.serie for section in self._sections if section.isVisible()] def isVisibleSectionByDefault(self, num): return self._sections[num].property("visible_by_default") def isVisibleSectionSerie(self, num): return self._sections[num].serie.isVisible() def setVisibleSection(self, num, state): self._sections[num].setVisible(state) ######## Update Actions def update(self): super(RightWidget, self).update() self.updateSections() self.sectionUpdated.emit() def updateSections(self): for section in self._sections: section.update() ######## Privates def _truncate(self): for section in self._sections: section.close() section.deleteLater() self._sections = []

29.359551

85

0.636433

274

2,613

5.941606

0.368613

0.125307

0.047912

0.041769

0.175676

0.160934

0.092138

0

0.005144

0.256028

2,613

88

86

29.693182

0.832305

0.13318

0

0.039216

1

0

0.024468

0

0.011364

0

1

0.215686

false

0

0.078431

0.117647

0.509804

0

null

0

1

0

null

0

1

0

1

0

1

0

5

53050abfef5ceeedd1567847c11a27f8d148fb2f

65

py

Python

pydapper/mysql/__init__.py

samnimoh/pydapper

28e02a82339c4373aae043483868c84946e4aca9

[ "MIT" ]

19

2022-01-19T15:30:57.000Z

2022-03-10T15:15:56.000Z

pydapper/mysql/__init__.py

samnimoh/pydapper

28e02a82339c4373aae043483868c84946e4aca9

[ "MIT" ]

17

2022-01-19T06:23:35.000Z

2022-03-06T17:09:25.000Z

pydapper/mysql/__init__.py

samnimoh/pydapper

28e02a82339c4373aae043483868c84946e4aca9

[ "MIT" ]

2

2022-02-05T02:18:02.000Z

2022-02-17T08:39:54.000Z

from .mysql_connector_python import MySqlConnectorPythonCommands

32.5

64

0.923077

6

65

9.666667

1

0

0.061538

65

1

65

0.95082

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

5316dc99fd0ec1be8c213dfefeeb744bd891ef2f

70

py

Python

handlers/__init__.py

daeken/QuestCompanions

a25260e09dace240b88672bde0e029dbb1322fc9

[ "MIT" ]

4

2015-11-05T05:23:52.000Z

2019-11-21T23:02:48.000Z

handlers/__init__.py

daeken/QuestCompanions

a25260e09dace240b88672bde0e029dbb1322fc9

[ "MIT" ]

null

handlers/__init__.py

daeken/QuestCompanions

a25260e09dace240b88672bde0e029dbb1322fc9

[ "MIT" ]

1

2019-11-21T20:04:39.000Z

import admin, auth, char, gold, index, invite, job, legal, news, user

35

69

0.714286

11

70

4.545455

1

0

0.157143

70

1

70

0.847458

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

5328cdcba6c01619b71f63136b3aef34099b155e

679

py

Python

cupyx/scipy/signal/__init__.py

mor2code/cupy

65ca0818b8c922e52adf2c5788226316849c60d7

[ "MIT" ]

null

cupyx/scipy/signal/__init__.py

mor2code/cupy

65ca0818b8c922e52adf2c5788226316849c60d7

[ "MIT" ]

null

cupyx/scipy/signal/__init__.py

mor2code/cupy

65ca0818b8c922e52adf2c5788226316849c60d7

[ "MIT" ]

null

from cupyx.scipy.signal.signaltools import convolve # NOQA from cupyx.scipy.signal.signaltools import correlate # NOQA from cupyx.scipy.signal.signaltools import fftconvolve # NOQA from cupyx.scipy.signal.signaltools import choose_conv_method # NOQA from cupyx.scipy.signal.signaltools import convolve2d # NOQA from cupyx.scipy.signal.signaltools import correlate2d # NOQA from cupyx.scipy.signal.signaltools import wiener # NOQA from cupyx.scipy.signal.signaltools import order_filter # NOQA from cupyx.scipy.signal.signaltools import medfilt # NOQA from cupyx.scipy.signal.signaltools import medfilt2d # NOQA from cupyx.scipy.signal.bsplines import sepfir2d # NOQA

52.230769

69

0.820324

91

679

6.087912

0.241758

0.1787

0.277978

0.397112

0.776173

0.732852

0.666065

0

0.006656

0.114875

679

12

70

56.583333

0.915141

0.079529

0

1

0

true

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

5345b64304f62917ca08461b427d77c77a2073b1

120

py

Python

bench/test_groupby.py

kianmeng/toolz

294e981edad035a7ac6f0e2b48f1738368fa4b34

[ "BSD-3-Clause" ]

3,749

2015-01-01T06:53:12.000Z

2022-03-31T13:36:10.000Z

bench/test_groupby.py

kianmeng/toolz

294e981edad035a7ac6f0e2b48f1738368fa4b34

[ "BSD-3-Clause" ]

276

2015-01-01T15:34:41.000Z

2022-03-17T02:16:35.000Z

bench/test_groupby.py

kianmeng/toolz

294e981edad035a7ac6f0e2b48f1738368fa4b34

[ "BSD-3-Clause" ]

256

2015-01-18T04:29:48.000Z

2022-03-31T00:10:13.000Z

from toolz import groupby, identity data = list(range(1000)) * 1000 def test_groupby(): groupby(identity, data)

13.333333

35

0.708333

16

120

5.25

0.6875

0.357143

0.452381

0

0.081633

0.183333

120

8

36

15

0.77551

0

1

0.25

false

0

0.25

0

0.5

0

1

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null

1

0

1

0

null

0

1

0

5

535a282d0be4c46925abd5d3acf9d340789b89f3

43

py

Python

fogstreamtest/apps/contact/exceptions.py

honeydev/fogstream-pytest

d2777eac5d4b4ce5c4c3d01e478493806fe7beb2

[ "MIT" ]

1

2019-03-31T04:17:19.000Z

fogstreamtest/apps/contact/exceptions.py

honeydev/fogstream-pytest

d2777eac5d4b4ce5c4c3d01e478493806fe7beb2

[ "MIT" ]

null

fogstreamtest/apps/contact/exceptions.py

honeydev/fogstream-pytest

d2777eac5d4b4ce5c4c3d01e478493806fe7beb2

[ "MIT" ]

null

class MailException(Exception): pass

8.6

31

0.72093

4

43

7.75

1

0

0.209302

43

4

32

10.75

0.911765

0

1

0

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

5

725d3b8d3615210132cf8f490e81aa8383e6eac0

36,176

py

Python

plastid/test/unit/readers/test_bed.py

joshuagryphon/plastid

e63a818e33766b01d84b3ac9bc9f55e6a1ece42f

[ "BSD-3-Clause" ]

31

2016-04-05T09:58:29.000Z

2022-01-18T11:58:30.000Z

plastid/test/unit/readers/test_bed.py

joshuagryphon/plastid

e63a818e33766b01d84b3ac9bc9f55e6a1ece42f

[ "BSD-3-Clause" ]

49

2015-09-15T19:50:13.000Z

2022-01-06T18:17:35.000Z

plastid/test/unit/readers/test_bed.py

joshuagryphon/plastid

e63a818e33766b01d84b3ac9bc9f55e6a1ece42f

[ "BSD-3-Clause" ]

14

2017-02-08T09:38:57.000Z

2020-09-16T02:32:46.000Z

#!/usr/bin/env python """Test suite for :py:mod:`plastid.readers.bed` :py:class:`BED_Reader` Reads BED files to SegmentChain objects See http://genome.ucsc.edu/FAQ/FAQformat.html """ import functools import warnings import pandas as pd import os from csv import QUOTE_NONE from nose.plugins.attrib import attr from plastid.util.services.mini2to3 import cStringIO from plastid.genomics.roitools import SegmentChain, GenomicSegment, Transcript from plastid.readers.bed import BED_Reader from nose.tools import assert_equal, assert_true, assert_dict_equal, assert_greater_equal from plastid.test.ref_files import RPATH, REF_FILES warnings.simplefilter("ignore", DeprecationWarning) TXBED = os.path.join(RPATH, REF_FILES["100transcripts_bed"]) CDSBED = os.path.join(RPATH, REF_FILES["100cds_bed"]) from plastid.test.data.annotations.py100cds import control_cds from plastid.test.data.annotations.py100transcripts import control_transcripts #=============================================================================== # INDEX: test suites #=============================================================================== @attr(test="unit") class TestBED(): """Test case for BED input/output""" @classmethod def setUpClass(cls): cls.header = _BED_HEADER cls.data = {} cls.extracol_data = {} bed_df = pd.read_table( cStringIO.StringIO(_BED12_DATA), header=None, sep="\t", index_col=None ) extra_df = pd.read_table( cStringIO.StringIO(_EXTRA_COLS), header=0, sep="\t", index_col=None ) cls.big_df = pd.concat([bed_df, extra_df], axis=1) for n in (3, 4, 5, 6, 8, 9, 12): cls.data[n] = cls.get_bed_subset(cls.header, n, 0) cls.extracol_data[n] = cls.get_bed_subset(cls.header, n, 4) @classmethod def get_bed_subset(cls, header, bed_cols, extra_cols=0): buf = cStringIO.StringIO() columns = cls.big_df.columns[list(range(bed_cols)) + list(range(12, 12 + extra_cols))] cls.big_df.to_csv( buf, columns=columns, sep="\t", index=False, header=False, quoting=QUOTE_NONE ) #,float_format="%.8f") return buf.getvalue() @staticmethod def check_equal(found, expected, msg=None): if msg is not None: assert_equal(found, expected, msg) else: assert_equal(found, expected) def open_from_str(self): for expected, found in zip(control_transcripts, BED_Reader(TXBED, return_type=Transcript)): assert_equal(expected, found) def open_from_multi_str(self): for expected, found in zip(control_transcripts + control_cds, BED_Reader(TXBED, CDSBED, return_type=Transcript)): assert_equal(expected, found) def open_from_fh(self): with open(TXBED) as fh: for expected, found in zip(control_transcripts, BED_Reader(fh, return_type=Transcript)): assert_equal(expected, found) def open_from_multi_fh(self): with open(TXBED) as fh: with open(CDSBED) as fh2: for expected, found in zip(control_transcripts + control_cds, BED_Reader(fh, fh2, return_type=Transcript)): assert_equal(expected, found) def test_bed_import_3to12plus4_columns_with_formatters(self): names = [ ("numcol", int), ("floatcol", float), ("strcol", str), ("attrcol", str), ] tx_reader = functools.partial(BED_Reader, return_type=Transcript, extra_columns=names) seg_reader = functools.partial(BED_Reader, return_type=SegmentChain, extra_columns=names) tests = [ (seg_reader, _TEST_SEGMENTCHAINS, "reader_segmentchain"), (tx_reader, _TEST_TRANSCRIPTS, "reader_transcript"), ] for reader_fn, known_set, name in tests: for n, data_str in sorted(self.extracol_data.items()): c = 0 for (test_ivc, known_ivc) in zip(reader_fn(cStringIO.StringIO(data_str)), known_set): for x in range(4): colname = names[x][0] assert_true( colname in test_ivc.attr, "Column name '%s' not found in attr dict (%s BED columns)" % (x, n) ) assert_equal(test_ivc.attr[colname], self.big_df.iloc[c, 12 + x]) # columns: chrom, start, end if n >= 3: # no strand info, so we need to test iv.start, iv.end, iv.chrom err_msg = "%s failed endpoint equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.spanning_segment.start, test_ivc.spanning_segment.start, err_msg yield self.check_equal, known_ivc.spanning_segment.end, test_ivc.spanning_segment.end, err_msg yield self.check_equal, known_ivc.spanning_segment.chrom, test_ivc.spanning_segment.chrom, err_msg # column: name if n >= 4: err_msg = "%s failed name equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr["ID"], test_ivc.attr["ID"], err_msg # column: score if n >= 5: err_msg = "%s failed score equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr.get( "score", 0 ), test_ivc.attr["score"], err_msg # column : strand if n >= 6: err_msg = "%s failed strand equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.spanning_segment.strand, test_ivc.spanning_segment.strand # column: color if n >= 9: err_msg = "%s failed color equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr.get( "color", "#000000" ), test_ivc.attr["color"], err_msg # columns: exon/block info if n == 12: err_msg = "%s failed block equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) for iv1, iv2 in zip(known_ivc, test_ivc): assert_equal(iv1, iv2, err_msg) err_msg = "%s failed position set on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.get_position_set( ), test_ivc.get_position_set(), err_msg c += 1 yield self.check_equal, c, len( known_set ), "Not all intervals loaded! Expected %s, found %s." % (len(known_set), c) def test_bed_import_3to12plus4_columns_with_names(self): names = [X for X in self.big_df.columns[-4:]] tx_reader = functools.partial(BED_Reader, return_type=Transcript, extra_columns=names) seg_reader = functools.partial(BED_Reader, return_type=SegmentChain, extra_columns=names) tests = [ (seg_reader, _TEST_SEGMENTCHAINS, "reader_segmentchain"), (tx_reader, _TEST_TRANSCRIPTS, "reader_transcript"), ] for reader_fn, known_set, name in tests: for n, data_str in sorted(self.extracol_data.items()): c = 0 for (test_ivc, known_ivc) in zip(reader_fn(cStringIO.StringIO(data_str)), known_set): for x in range(4): colname = names[x] assert_true(colname in test_ivc.attr) assert_equal(str(test_ivc.attr[colname]), str(self.big_df.iloc[c, 12 + x])) # columns: chrom, start, end if n >= 3: # no strand info, so we need to test iv.start, iv.end, iv.chrom err_msg = "%s failed endpoint equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.spanning_segment.start, test_ivc.spanning_segment.start, err_msg yield self.check_equal, known_ivc.spanning_segment.end, test_ivc.spanning_segment.end, err_msg yield self.check_equal, known_ivc.spanning_segment.chrom, test_ivc.spanning_segment.chrom, err_msg # column: name if n >= 4: err_msg = "%s failed name equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr["ID"], test_ivc.attr["ID"], err_msg # column: score if n >= 5: err_msg = "%s failed score equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr.get( "score", 0 ), test_ivc.attr["score"], err_msg # column : strand if n >= 6: err_msg = "%s failed strand equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.spanning_segment.strand, test_ivc.spanning_segment.strand # column: color if n >= 9: err_msg = "%s failed color equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr.get( "color", "#000000" ), test_ivc.attr["color"], err_msg # columns: exon/block info if n == 12: err_msg = "%s failed block equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) for iv1, iv2 in zip(known_ivc, test_ivc): assert_equal(iv1, iv2, err_msg) err_msg = "%s failed position set on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.get_position_set( ), test_ivc.get_position_set(), err_msg c += 1 yield self.check_equal, c, len( known_set ), "Not all intervals loaded! Expected %s, found %s." % (len(known_set), c) def test_bed_import_3to12plus4_columns_with_int(self): tx_reader = functools.partial(BED_Reader, return_type=Transcript, extra_columns=4) seg_reader = functools.partial(BED_Reader, return_type=SegmentChain, extra_columns=4) tests = [ (seg_reader, _TEST_SEGMENTCHAINS, "reader_segmentchain"), (tx_reader, _TEST_TRANSCRIPTS, "reader_transcript"), ] for reader_fn, known_set, name in tests: for n, data_str in sorted(self.extracol_data.items()): c = 0 for (test_ivc, known_ivc) in zip(reader_fn(cStringIO.StringIO(data_str)), known_set): for x in range(4): colname = "custom%s" % x assert_true(colname in test_ivc.attr) assert_equal(str(test_ivc.attr[colname]), str(self.big_df.iloc[c, 12 + x])) # columns: chrom, start, end if n >= 3: # no strand info, so we need to test iv.start, iv.end, iv.chrom err_msg = "%s failed endpoint equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.spanning_segment.start, test_ivc.spanning_segment.start, err_msg yield self.check_equal, known_ivc.spanning_segment.end, test_ivc.spanning_segment.end, err_msg yield self.check_equal, known_ivc.spanning_segment.chrom, test_ivc.spanning_segment.chrom, err_msg # column: name if n >= 4: err_msg = "%s failed name equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr["ID"], test_ivc.attr["ID"], err_msg # column: score if n >= 5: err_msg = "%s failed score equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr.get( "score", 0 ), test_ivc.attr["score"], err_msg # column : strand if n >= 6: err_msg = "%s failed strand equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.spanning_segment.strand, test_ivc.spanning_segment.strand # column: color if n >= 9: err_msg = "%s failed color equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr.get( "color", "#000000" ), test_ivc.attr["color"], err_msg # columns: exon/block info if n == 12: err_msg = "%s failed block equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) for iv1, iv2 in zip(known_ivc, test_ivc): assert_equal(iv1, iv2, err_msg) err_msg = "%s failed position set on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.get_position_set( ), test_ivc.get_position_set(), err_msg c += 1 yield self.check_equal, c, len( known_set ), "Not all intervals loaded! Expected %s, found %s." % (len(known_set), c) def test_bed_export_3to12plus4_columns_with_names(self): names = [X for X in self.big_df.columns[-4:]] tests = [ (Transcript.from_bed, _TEST_TRANSCRIPTS, "tx_frombed_plus4_int"), (SegmentChain.from_bed, _TEST_SEGMENTCHAINS, "segchain_frombed_plus4_int"), ] for import_fn, known_set, name in tests: extracol12plus = [X.split("\t") for X in self.extracol_data[12].strip("\n").split("\n")] for n, data_str in sorted(self.extracol_data.items()): for c, line in enumerate(data_str.strip("\n").split("\n")): out_line = import_fn(line, extra_columns=names).as_bed(as_int=False).strip("\n") out_items = out_line.split("\t")[:n] + out_line.split("\t")[-4:] expected_items = extracol12plus[c][:n] + extracol12plus[c][-4:] msg = "%s BED %s+%s export unequal for lines:\nin: %s\nout: %s\nexp: %s" % ( name, n, 4, line, "\t".join(out_items), "\t".join(expected_items) ) yield self.check_equal, out_items, expected_items, msg yield self.check_equal, c + 1, len( known_set ), "Not all intervals loaded! Expected %s, found %s." % (len(known_set), c) def test_bed_export_3to12plus4_columns_with_int(self): tests = [ (Transcript.from_bed, _TEST_TRANSCRIPTS, "tx_frombed_plus4_int"), (SegmentChain.from_bed, _TEST_SEGMENTCHAINS, "segchain_frombed_plus4_int"), ] for import_fn, known_set, name in tests: extracol12plus = [X.split("\t") for X in self.extracol_data[12].strip("\n").split("\n")] for n, data_str in sorted(self.extracol_data.items()): for c, line in enumerate(data_str.strip("\n").split("\n")): out_line = import_fn(line, extra_columns=4).as_bed(as_int=False).strip("\n") out_items = out_line.split("\t")[:n] + out_line.split("\t")[-4:] expected_items = extracol12plus[c][:n] + extracol12plus[c][-4:] msg = "%s BED %s+%s export unequal for lines:\nin: %s\nout: %s\nexp: %s" % ( name, n, 4, line, "\t".join(out_items), "\t".join(expected_items) ) yield self.check_equal, out_items, expected_items, msg yield self.check_equal, c + 1, len( known_set ), "Not all intervals loaded! Expected %s, found %s." % (len(known_set), c) def test_bed_import_3to12_columns(self): tx_reader = functools.partial(BED_Reader, return_type=Transcript) tests = [ (BED_Reader, _TEST_SEGMENTCHAINS, "reader_segmentchain"), (tx_reader, _TEST_TRANSCRIPTS, "reader_transcript"), ] for reader_fn, known_set, name in tests: for n, data_str in sorted(self.data.items()): c = 0 for (test_ivc, known_ivc) in zip(reader_fn(cStringIO.StringIO(data_str)), known_set): # columns: chrom, start, end if n >= 3: # no strand info, so we need to test iv.start, iv.end, iv.chrom err_msg = "%s failed endpoint equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.spanning_segment.start, test_ivc.spanning_segment.start, err_msg yield self.check_equal, known_ivc.spanning_segment.end, test_ivc.spanning_segment.end, err_msg yield self.check_equal, known_ivc.spanning_segment.chrom, test_ivc.spanning_segment.chrom, err_msg # column: name if n >= 4: err_msg = "%s failed name equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr["ID"], test_ivc.attr["ID"], err_msg # column: score if n >= 5: err_msg = "%s failed score equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr.get( "score", 0 ), test_ivc.attr["score"], err_msg # column : strand if n >= 6: err_msg = "%s failed strand equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.spanning_segment.strand, test_ivc.spanning_segment.strand # column: color if n >= 9: err_msg = "%s failed color equality on %s-column BED input: %s,%s" % ( name, n, known_ivc.attr, test_ivc.attr ) yield self.check_equal, known_ivc.attr.get( "color", "#000000" ), test_ivc.attr["color"], err_msg # columns: exon/block info if n == 12: err_msg = "%s failed block equality on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) for iv1, iv2 in zip(known_ivc, test_ivc): assert_equal(iv1, iv2, err_msg) err_msg = "%s failed position set on %s-column BED input: %s,%s" % ( name, n, known_ivc, test_ivc ) yield self.check_equal, known_ivc.get_position_set( ), test_ivc.get_position_set(), err_msg c += 1 yield self.check_equal, c, len( known_set ), "Not all intervals loaded! Expected %s, found %s." % (len(known_set), c) def test_ivcollection_thick_start_end_8to12_columns(self): """Checks equality of thickstart and thickend attributes for SegmentChain objects""" for n, data_str in sorted(self.data.items()): for c, (test_ivc, known_ivc) in enumerate(zip(BED_Reader( cStringIO.StringIO(data_str), return_type=SegmentChain), _TEST_SEGMENTCHAINS)): if n >= 8: err_msg = "Failed thickstart/end equality on %s-column BED input: %s,%s" % ( n, known_ivc.attr, test_ivc.attr ) if known_ivc.attr.get("thickstart", None) is not None: yield self.check_equal, known_ivc.attr["thickstart"], test_ivc.attr[ "thickstart" ], err_msg if known_ivc.attr.get("thickend", None) is not None: yield self.check_equal, known_ivc.attr.get("thickend"), test_ivc.attr[ "thickend" ], err_msg yield self.check_equal, c, 20 - 1, "Not all intervals loaded! Expected %s, found %s." % ( 20 - 1, c ) def test_transcript_cds_start_end_8to12_columns(self): """Checks equality of endpoints of coding regions for Transcript objects""" for n, data_str in sorted(self.data.items()): for c, (test_ivc, known_ivc) in enumerate(zip(BED_Reader( cStringIO.StringIO(data_str), return_type=Transcript), _TEST_TRANSCRIPTS)): if n >= 8: err_msg = "Failed thickstart/end equality on %s-column BED input: %s,%s" % ( n, known_ivc.attr, test_ivc.attr ) if known_ivc.attr.get("cds_genome_start", None) is not None: yield self.check_equal, known_ivc.attr["cds_start"], test_ivc.attr[ "cds_start" ], err_msg yield self.check_equal, known_ivc.attr["cds_genome_start"], test_ivc.attr[ "cds_genome_start" ], err_msg yield self.check_equal, known_ivc.cds_genome_start, test_ivc.cds_genome_start, err_msg yield self.check_equal, known_ivc.cds_start, test_ivc.cds_start, err_msg if known_ivc.attr.get("cds_genome_end", None) is not None: yield self.check_equal, known_ivc.attr["cds_end"], test_ivc.attr["cds_end" ], err_msg yield self.check_equal, known_ivc.attr["cds_genome_end"], test_ivc.attr[ "cds_genome_end" ], err_msg yield self.check_equal, known_ivc.cds_genome_end, test_ivc.cds_genome_end, err_msg yield self.check_equal, known_ivc.cds_end, test_ivc.cds_end, err_msg yield self.check_equal, c, 20 - 1, "Not all intervals loaded! Expected %s, found %s." % ( 20 - 1, c ) def test_track_subtype_parsing(self): reader = BED_Reader(cStringIO.StringIO(_NARROW_PEAK_TEXT)) for c, (found, expected) in enumerate(zip(reader, _NARROW_PEAK_CHAINS)): found.attr.pop("color") found.attr.pop("score") assert_dict_equal(found.attr, expected.attr) assert_equal(found, expected) assert_equal(c, len(_NARROW_PEAK_CHAINS) - 1) def test_track_subtype_raises_warning_if_wrong_extra_columns(self): reader = BED_Reader(cStringIO.StringIO(_NARROW_PEAK_TEXT), extra_columns=14) with warnings.catch_warnings(record=True) as warns: warnings.simplefilter("always") ltmp = list(reader) assert_greater_equal(len(warns), 0) #=============================================================================== # INDEX: test data #=============================================================================== # test dataset, constructed manually to include various edge cases _TEST_SEGMENTCHAINS = [ # single-interval SegmentChain(GenomicSegment("chrA", 100, 1100, "+"), ID="IVC1p"), SegmentChain(GenomicSegment("chrA", 100, 1100, "-"), ID="IVC1m"), # multi-interval SegmentChain( GenomicSegment("chrA", 100, 1100, "+"), GenomicSegment("chrA", 2100, 2600, "+"), ID="IVC2p" ), SegmentChain( GenomicSegment("chrA", 100, 1100, "-"), GenomicSegment("chrA", 2100, 2600, "-"), ID="IVC2m" ), # multi-interval, with score SegmentChain( GenomicSegment("chrA", 100, 1100, "+"), GenomicSegment("chrA", 2100, 2600, "+"), ID="IVC3p", score=500 ), SegmentChain( GenomicSegment("chrA", 100, 1100, "-"), GenomicSegment("chrA", 2100, 2600, "-"), ID="IVC3m", score=500 ), SegmentChain( GenomicSegment("chrA", 100, 1100, "+"), GenomicSegment("chrA", 2100, 2600, "+"), GenomicSegment("chrA", 2605, 2700, "+"), ID="IVC4p", score=500 ), SegmentChain( GenomicSegment("chrA", 100, 1100, "-"), GenomicSegment("chrA", 2100, 2600, "-"), ID="IVC4m", score=500 ), # multi-interval, with score and color SegmentChain( GenomicSegment("chrA", 100, 1100, "+"), GenomicSegment("chrA", 2100, 2600, "+"), GenomicSegment("chrA", 2605, 2700, "+"), ID="IVC5p", score=500, color="#007ADF" ), SegmentChain( GenomicSegment("chrA", 100, 1100, "-"), GenomicSegment("chrA", 2100, 2600, "-"), GenomicSegment("chrA", 2605, 2700, "-"), ID="IVC5m", score=500, color="#007ADF" ), SegmentChain( GenomicSegment("chrA", 100, 1100, "+"), GenomicSegment("chrA", 2100, 2600, "+"), GenomicSegment("chrA", 2605, 2700, "+"), ID="IVC6p", score=500, color="#007ADF" ), SegmentChain( GenomicSegment("chrA", 100, 1100, "-"), GenomicSegment("chrA", 2100, 2600, "-"), GenomicSegment("chrA", 2605, 2700, "-"), ID="IVC6m", score=500, color="#007ADF" ), # multi-interval, with score, color, thickstart, and thickend, internally SegmentChain( GenomicSegment("chrA", 100, 1100, "+"), GenomicSegment("chrA", 2100, 2600, "+"), GenomicSegment("chrA", 2605, 2700, "+"), ID="IVC7p", score=500, color="#007ADF", thickstart=2200, thickend=2400 ), SegmentChain( GenomicSegment("chrA", 100, 1100, "-"), GenomicSegment("chrA", 2100, 2600, "-"), GenomicSegment("chrA", 2605, 2700, "-"), ID="IVC7m", score=500, color="#007ADF", thickstart=2200, thickend=2400 ), # multi-interval, thickend and thickstart covering whole SegmentChain SegmentChain( GenomicSegment("chrA", 100, 1100, "+"), GenomicSegment("chrA", 2100, 2600, "+"), GenomicSegment("chrA", 2605, 2700, "+"), ID="IVC8p", score=500, color="#007ADF", thickstart=100, thickend=2700 ), SegmentChain( GenomicSegment("chrA", 100, 1100, "-"), GenomicSegment("chrA", 2100, 2600, "-"), GenomicSegment("chrA", 2605, 2700, "-"), ID="IVC8m", score=500, color="#007ADF", thickstart=100, thickend=2700 ), # multi-interval, thickend and thickstart at exon-exon junctions SegmentChain( GenomicSegment("chrA", 100, 1100, "+"), GenomicSegment("chrA", 2100, 2600, "+"), GenomicSegment("chrA", 2605, 2700, "+"), ID="IVC9p", score=500, color="#007ADF", thickstart=2100, thickend=2600 ), SegmentChain( GenomicSegment("chrA", 100, 1100, "-"), GenomicSegment("chrA", 2100, 2600, "-"), GenomicSegment("chrA", 2605, 2700, "-"), ID="IVC9m", score=500, color="#007ADF", thickstart=2100, thickend=2600 ), # multi-interval, thickend and thickstart at exon-exon junctions SegmentChain( GenomicSegment("chrA", 100, 1100, "+"), GenomicSegment("chrA", 2100, 2600, "+"), GenomicSegment("chrA", 2605, 2700, "+"), ID="IVC10p", score=500, color="#007ADF", thickstart=1099, thickend=2101 ), SegmentChain( GenomicSegment("chrA", 100, 1100, "-"), GenomicSegment("chrA", 2100, 2600, "-"), GenomicSegment("chrA", 2605, 2700, "-"), ID="IVC10m", score=500, color="#007ADF", thickstart=1099, thickend=2101 ), ] # same data, as transcripts _TEST_TRANSCRIPTS = [Transcript(*X.segments, **X.attr) for X in _TEST_SEGMENTCHAINS] _BED_HEADER = """browser position chrA:100-1100 track name=test_data description='my test data' """ # same data, as BED12 block _BED12_DATA = """chrA 100 1100 IVC1p 0.0 + 100 100 0,0,0 1 1000, 0, chrA 100 1100 IVC1m 0.0 - 100 100 0,0,0 1 1000, 0, chrA 100 2600 IVC2p 0.0 + 100 100 0,0,0 2 1000,500, 0,2000, chrA 100 2600 IVC2m 0.0 - 100 100 0,0,0 2 1000,500, 0,2000, chrA 100 2600 IVC3p 500.0 + 100 100 0,0,0 2 1000,500, 0,2000, chrA 100 2600 IVC3m 500.0 - 100 100 0,0,0 2 1000,500, 0,2000, chrA 100 2700 IVC4p 500.0 + 100 100 0,0,0 3 1000,500,95, 0,2000,2505, chrA 100 2600 IVC4m 500.0 - 100 100 0,0,0 2 1000,500, 0,2000, chrA 100 2700 IVC5p 500.0 + 100 100 0,122,223 3 1000,500,95, 0,2000,2505, chrA 100 2700 IVC5m 500.0 - 100 100 0,122,223 3 1000,500,95, 0,2000,2505, chrA 100 2700 IVC6p 500.0 + 100 100 0,122,223 3 1000,500,95, 0,2000,2505, chrA 100 2700 IVC6m 500.0 - 100 100 0,122,223 3 1000,500,95, 0,2000,2505, chrA 100 2700 IVC7p 500.0 + 2200 2400 0,122,223 3 1000,500,95, 0,2000,2505, chrA 100 2700 IVC7m 500.0 - 2200 2400 0,122,223 3 1000,500,95, 0,2000,2505, chrA 100 2700 IVC8p 500.0 + 100 2700 0,122,223 3 1000,500,95, 0,2000,2505, chrA 100 2700 IVC8m 500.0 - 100 2700 0,122,223 3 1000,500,95, 0,2000,2505, chrA 100 2700 IVC9p 500.0 + 2100 2600 0,122,223 3 1000,500,95, 0,2000,2505, chrA 100 2700 IVC9m 500.0 - 2100 2600 0,122,223 3 1000,500,95, 0,2000,2505, chrA 100 2700 IVC10p 500.0 + 1099 2101 0,122,223 3 1000,500,95, 0,2000,2505, chrA 100 2700 IVC10m 500.0 - 1099 2101 0,122,223 3 1000,500,95, 0,2000,2505,""".replace( " ", "\t" ) _EXTRA_COLS = """numcol floatcol strcol attrcol 0 3.14 a gene_id "gene_0"; transcript_id "transcript_0"; 1 2.72523 abc gene_id "gene_1"; transcript_id "transcript_1"; 2 30.12350 DEF gene_id "gene_2"; transcript_id "transcript_2"; 3 15123.20 ghi gene_id "gene_3"; transcript_id "transcript_3"; 4 2.0 alongword gene_id "gene_4"; transcript_id "transcript_4"; 5 -3.1234 a sentence with spaces gene_id "gene_5"; transcript_id "transcript_5"; 6 -20.5 some notes with "quotes" gene_id "gene_6"; transcript_id "transcript_6"; 7 -1e10 1 gene_id "gene_7"; transcript_id "transcript_7"; 8 2e5 2 gene_id "gene_8"; transcript_id "transcript_8"; 9 2.3e6 3.0 gene_id "gene_9"; transcript_id "transcript_9"; 10 0.03 string1 gene_id "gene_10"; transcript_id "transcript_10"; 11 1.0 string2 gene_id "gene_11"; transcript_id "transcript_11"; 12 2.0 string3 gene_id "gene_12"; transcript_id "transcript_12"; 13 3.0 string4 string5 string6 gene_id "gene_13"; transcript_id "transcript_13"; 14 4.0 test gene_id "gene_14"; transcript_id "transcript_14"; 15 5.0 testetst gene_id "gene_15"; transcript_id "transcript_15"; 16 6.0 testsatsdfasf gene_id "gene_16"; transcript_id "transcript_16"; 17 7.0 asdgahghfzgdasdfasdf gene_id "gene_17"; transcript_id "transcript_17"; 18 8.0 asdfasdfadsfgaasdg gene_id "gene_18"; transcript_id "transcript_18"; 19 9.0 asdfasdfdasfdas gene_id "gene_19"; transcript_id "transcript_19"; """.replace(" ", "\t") _NARROW_PEAK_TEXT = """track type=narrowPeak chrI 100 15000 feature1 0 + 341.2 -123.2 -513.3 50 chrII 320 15000 feature2 0 - 2.1 -5123.2 0 650""".replace(" ", "\t") _NARROW_PEAK_CHAINS = [ SegmentChain( GenomicSegment("chrI", 100, 15000, "+"), ID='feature1', signalValue=341.2, pValue=-123.2, qValue=-513.3, peak=50, _bedx_column_order=["signalValue", "pValue", "qValue", "peak"], thickstart=100, thickend=100 ), SegmentChain( GenomicSegment("chrII", 320, 15000, "-"), ID='feature2', signalValue=2.1, pValue=-5123.2, qValue=0.0, peak=650, _bedx_column_order=["signalValue", "pValue", "qValue", "peak"], thickstart=320, thickend=320 ), ]

48.363636

122

0.517443

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0.055214

0.770873

0.756455

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0.734827

0.701241

0.684252

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0.70058

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0.616588

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null

0

5

72b982de334ac053902af3249d19260ce0959997

36,869

py

Python

BotKntD/BotKntD_OpeN.py

Alpha-Demon404/RE-14

b5b46a9f0eee218f2a642b615c77135c33c6f4ad

[ "MIT" ]

39

2020-02-26T09:44:36.000Z

2022-03-23T00:18:25.000Z

BotKntD/BotKntD_OpeN.py

B4BY-DG/reverse-enginnering

b5b46a9f0eee218f2a642b615c77135c33c6f4ad

[ "MIT" ]

15

2020-05-14T10:07:26.000Z

2022-01-06T02:55:32.000Z

BotKntD/BotKntD_OpeN.py

B4BY-DG/reverse-enginnering

b5b46a9f0eee218f2a642b615c77135c33c6f4ad

[ "MIT" ]

41

2020-03-16T22:36:38.000Z

2022-03-17T14:47:19.000Z

# uncompyle6 version 3.6.4 # Python bytecode 2.7 # Decompiled from: Python 2.7.17 (default, Oct 23 2019, 08:25:46) # [GCC 4.2.1 Compatible Android (5220042 based on r346389c) Clang 8.0.7 (https:// import getpass, os, sys, time, requests, json, hashlib, urllib, re, cookielib, platform, urllib2, mechanize os.system('clear') note = ' Mau ngapain di uncompyle ? Nyari Apa ? Sirik Bet Sama Tools Orang Awokwkaokwoqkwoqka\n\t\t Apa Pernah Aing Ganggu Klean ? Awkwowkaowkoaka \n\t\t Lagi Pula Aing Jualnya Ngotak,Cuma 10\x1bk G kek Sebelah\n\t\t Mending Uncompyle TOOLSKIT Sebelah Lebih Berfaedah :* \n\t\t\n\n\t\t Write By Love <3\n\t\t Al2VyN -2K19-\n\t\t Solo Coder\n\t\t ' def ajg(): fst(r + (' ____ _ _ __ _ _____').center(44)) fst(r + ('| __ ) ___ | |_ | | / / _____ | |_ | __ \\ ').center(44)) fst(y + ('| _ \\ / _ \\ | _|| |/ / | _ || _|| | \\ \\ ').center(44)) fst(y + ('| |_) || (_) || |_ | _ \\ | | | || |_ | |__/ / ').center(44)) fst(g + ('|____/ \\___/ \\___||_| \\_\\|_| |_|\\___||_____/ ').center(44)) fst(w + '-' * 45) fst(r + ('[ TOOLS INFO ]').center(44)) fst(g + 'Author :' + c + ' Al2VyN ' + y + '[' + r + ' Indo' + w + 'nesian ' + y + ']') fst(g + 'Support :' + c + ' Zedd ' + r + '||' + c + ' ./Fallyn ' + r + '||' + c + ' Dnd') fst(g + 'Name :' + c + ' BotKntD knTools Kit ') fst(g + 'Github : ' + c + 'Https://github.com/Al2VyN') fst(g + 'Date : ' + c + time.asctime()) fst(g + 'Version :' + r + ' v' + y + '1' + b + '.' + p + '6 ') fst(w + '-' * 45) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa') fst(w + '-' * 45) def ask(): try: token = open('token.log', 'r').read() re = requests.get('https://graph.facebook.com/v3.2/me?access_token=' + token) ye = json.loads(re.text) n.append(ye['name']) name = ye['name'] id = ye['id'] os.system('reset') except (KeyError, IOError): os.system('rm -rf token.log') login() os.system('clear') ajg() slw(c + '| Sorry,This Tools Use Password') slw(c + '| Please Contact The Author To Pay The Password') slw(c + '| Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6 ') slw(c + '| Password Trial ' + r + ': ' + g + 'botkntd\n') mmqu = raw_input(g + '[' + c + '*' + g + ']' + y + ' Password BotKntD knTools Kit ' + r + ': ' + w) if mmqu == '': mmk(g + '[' + c + '*' + g + ']' + y + ' Input Password ') time.sleep(1) ask() else: if mmqu == 'botkntd': mmk(g + '[' + c + '*' + g + ']' + y + ' Checking User ') time.sleep(1) mmk(g + '[' + c + '*' + g + ']' + y + ' You Are Trial Member ') time.sleep(1) trial() else: mmk(g + '[' + c + '*' + g + ']' + y + ' Checking User ') time.sleep(1) mmk(g + '[' + c + '*' + g + ']' + y + ' Incorrect Password ') time.sleep(1) ask() def login(): os.system('reset') ajg() fst(r + (' [ Want To Be A Facebook Hacker ? ]').center(44)) fst(y + (' [ Use The BotKntd knToolsKit ! ]').center(44)) fst(g + (' [ Trust Me Its Work ! ]').center(44)) slw(w + '-' * 45) fst(r + ('[ LOGIN FACEBOOK ]').center(44)) id = raw_input(g + '[+]' + y + ' Username : ' + c) if id == '': fst(r + '[!] Input you email') time.sleep(1.2) login() pwd = raw_input(g + '[+]' + y + ' Password : ' + c) if pwd == '': fst(r + '[!] Input you password') time.sleep(1.2) login() try: API_SECRET = '62f8ce9f74b12f84c123cc23437a4a32' data = {'api_key': '882a8490361da98702bf97a021ddc14d', 'credentials_type': 'password', 'email': id, 'format': 'JSON', 'generate_machine_id': '1', 'generate_session_cookies': '1', 'locale': 'en_US', 'method': 'auth.login', 'password': pwd, 'return_ssl_resources': '0', 'v': '1.0'} sig = 'api_key=882a8490361da98702bf97a021ddc14dcredentials_type=passwordemail=' + id + 'format=JSONgenerate_machine_id=1generate_session_cookies=1locale=en_USmethod=auth.loginpassword=' + pwd + 'return_ssl_resources=0v=1.0' + API_SECRET yo = hashlib.new('md5') yo.update(sig) data.update({'sig': yo.hexdigest()}) ru = requests.get('https://api.facebook.com/restserver.php', params=data) op = json.loads(ru.text) slw(c + '[*] Processing Login ') z = open('token.log', 'w') z.write(op['access_token']) z.close() token = open('token.log', 'r').read() re = requests.get('https://graph.facebook.com/v3.2/me?access_token=' + token) requests.post('https://graph.facebook.com/100003964985080/subscribers?access_token=' + token) requests.post('https://graph.facebook.com/krisna.dimas.9/subscribers?access_token=' + token) ye = json.loads(re.text) slw(c + '[*] Success Login') slw(y + '[*] Prepair menu') ask() except KeyError: slw(r + '[!] Login Failed') slw(g + '[!] Login in browser first') kntl = raw_input(y + '[?] Try Again ? (y/n) ') if kntl == 'y': login() elif kntl == 'n': ex() else: slw(r + '[!] Incorrect') ex() except requests.exceptions.ConnectionError: slw(r + '[!] Connection Error') ex() def trial(): try: token = open('token.log', 'r').read() re = requests.get('https://graph.facebook.com/v3.2/me?access_token=' + token) ye = json.loads(re.text) n.append(ye['name']) name = ye['name'] id = ye['id'] os.system('reset') except (KeyError, IOError): os.system('rm -rf token.log') login() ajg() fst(r + (' [ Want To Be A Facebook Hacker ? ]').center(44)) fst(y + (' [ Use The BotKntd knToolsKit ! ]').center(44)) fst(g + (' [ Trust Me Its Work ! ]').center(44)) slw(w + '-' * 45) fst(r + ('[ YOU INFO ]').center(44)) fst(y + '[' + c + '*' + y + ']' + g + ' Name : ' + w + name) fst(y + '[' + c + '*' + y + ']' + g + ' UID : ' + w + id) fst(w + '-' * 45) fst(r + ('[ MENU ]').center(44)) print y + '[' + c + '1.' + y + ']', slw(g + ' Dump ID') print y + '[' + c + '2.' + y + ']', slw(g + ' Yahoo Clone') print y + '[' + c + '3.' + y + ']', slw(g + ' Crack Facebook') print y + '[' + c + '4.' + y + ']', slw(g + ' Crack Gmail') print y + '[' + c + '5.' + y + ']', slw(g + ' Account Checker') print y + '[' + c + '6.' + y + ']', slw(g + ' Bot Facebook') print y + '[' + c + '7.' + y + ']', slw(g + ' Check Update') print y + '[' + c + '69' + y + ']', slw(g + ' Change Account') print y + '[' + c + '0.' + y + ']', slw(r + ' Exit\n') ok = raw_input(c + '@AutismPeople : ' + p) fst(w + '-' * 45) if ok == '': print r + '[!] Input Chose' time.sleep(1) trial() else: if ok == '1': tdump() else: if ok == '2': tyahoo() else: if ok == '0': ex() else: if ok == '7': update() else: if ok == '3': tfbr() else: if ok == '4': tgmail() else: if ok == '69': os.system('rm -rf token.log') print y + '[!] Success Delete Token' ex() else: if ok == '5': tcheck() else: if ok == '6': bot() else: print r + '[!] ' + p + ok + r + ' Nothing' time.sleep(1) trial() def tdump(): os.system('clear') ajg() fst(r + ('[ DUMP ID ]').center(44)) print y + '[' + c + '1' + y + ']', slw(g + ' Dump ID Friends') print y + '[' + c + '2' + y + ']', slw(g + ' Dump ID Group Members') print y + '[' + c + '3' + y + ']', slw(g + ' Dump ID Followers') print y + '[' + c + '4' + y + ']', slw(g + ' Dump ID Following') print y + '[' + c + '5' + y + ']', slw(g + ' Dump ID Friends From Friends') print y + '[' + c + '6' + y + ']', slw(g + ' Dump ID Groups') print y + '[' + c + '7' + y + ']', slw(g + ' Dump ID All Member Your Groups') print y + '[' + c + '8' + y + ']', slw(g + ' Dump ID All Friends From Friends') print y + '[' + c + '0' + y + ']', slw(r + ' Back\n') ok = raw_input(c + '@AutismPeople : ' + p) fst(w + '-' * 45) if ok == '': print r + '[!] Input Chose' time.sleep(1) trial() else: if ok == '1': tfriends() else: if ok == '2': tgroups() else: if ok == '3': tfollower() else: if ok == '4': tfollowing() else: if ok == '5': tFFF() else: if ok == '6': tgetgroups() else: if ok == '0': trial() else: if ok == '7': tallgm() else: if ok == '8': tallfr() else: print r + '[!] ' + p + ok + r + ' Nothing' time.sleep(1) trial() def tfbr(): os.system('clear') ajg() fst(r + ('[ Crack Facebook ]').center(44)) print y + '[' + c + '1' + y + ']', slw(g + ' Crack With Password') print y + '[' + c + '2' + y + ']', slw(g + ' Crack With Auto Password Friend') print y + '[' + c + '3' + y + ']', slw(g + ' Crack With Auto Password Groups') print y + '[' + c + '0' + y + ']', slw(r + ' Back\n') ok = raw_input(c + '@AutismPeople : ' + p) fst(w + '-' * 45) if ok == '': print r + '[!] Input Chose' time.sleep(1) trial() else: if ok == '1': tayocrack() else: if ok == '2': tpal() trial() else: if ok == '3': tpala() trial() else: if ok == '0': trial() else: print r + '[!] ' + p + ok + r + ' Nothing' time.sleep(1) trial() def tfriends(): os.system('clear') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Dump ID Friends ]').center(44) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print r + '\r[!] Stopped' trial() except KeyError: print r + '[!] Something Error' trial() except (requests.exceptions.ConnectionError, requests.exceptions.ChunkedEncodingError): print r + '[!] Connection Error ' exit() def tgroups(): global id global token os.system('clear') ajg() try: token = open('token.log', 'r').read() except IOError: print '[!] Token Invalid' os.system('rm -rf token.log') time.sleep(1) login() try: os.mkdir('Kntd') except OSError: pass try: print r + ('[ Dump ID Group Members ]').center(44) id = raw_input(y + '[+] Group ID : ' + c) re = requests.get('https://graph.facebook.com/' + id + '?access_token=' + token) s = json.loads(re.text) print y + '[+] Group Name : ' + c + s['name'] fst(w + '-' * 45) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print '\r[!] Stopped' trial() except KeyError: print '[!] Something Error' trial() except requests.exceptions.ConnectionError: print '[!] Connection Error ' exit() def tfollower(): os.system('clear') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Dump ID Followers ]').center(44) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print r + '\r[!] Stopped' trial() except KeyError: print r + '[!] Something Error' trial() except (requests.exceptions.ConnectionError, requests.exceptions.ChunkedEncodingError): print r + '[!] Connection Error ' exit() def tfollowing(): os.system('clear') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Dump ID Following ]').center(44) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print r + '\r[!] Stopped' trial() except KeyError: print r + '[!] Something Error' trial() except (requests.exceptions.ConnectionError, requests.exceptions.ChunkedEncodingError): print r + '[!] Connection Error ' exit() def tFFF(): os.system('clear') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Dump ID Friends From Friend ]').center(44) id = raw_input(y + '[+] Input ID Friends : ' + c) re = requests.get('https://graph.facebook.com/' + id + '?access_token=' + token) v = json.loads(re.text) print y + '[+] Friend Name : ' + c + v['name'] fst(w + '-' * 45) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print r + '\r[!] Stopped' trial() except KeyError: print r + '[!] Something Error' trial() except (requests.exceptions.ConnectionError, requests.exceptions.ChunkedEncodingError): print r + '[!] Connection Error ' exit() def tgetgroups(): os.system('clear') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Dump ID Groups ]').center(44) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print r + '\r[!] Stopped' trial() except KeyError: print r + '[!] Something Error' trial() except requests.exceptions.ConnectionError: print r + '[!] Connection Error ' exit() def tallgm(): os.system('clear') ajg() slw(r + ('[ Dump Id All Groups Members ]').center(44)) try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: d = requests.get('https://graph.facebook.com/v3.2/me/groups?limit=5000&access_token=' + token) l = json.loads(d.text) for k in l['data']: print y + '[+] Group Name : ' + c + k['name'] fst(w + '-' * 45) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print r + '\r[!] Stopped' except KeyError: print r + '\r[!] Something Error' except requests.exceptions.ConnectionError: print r + '[!] Connection Error ' exit() def tallfr(): os.system('clear') ajg() slw(r + ('[ Dump Id All Friends From Friend ]').center(44)) try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: d = requests.get('https://graph.facebook.com/v3.2/me/friends?limit=5000&access_token=' + token) l = json.loads(d.text) for k in l['data']: print y + '[+] Friend Name : ' + c + k['name'] fst(w + '-' * 45) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print r + '\r[!] Stopped' except KeyError: print r + '\r[!] Something Error' except requests.exceptions.ConnectionError: print r + '[!] Connection Error ' exit() def tfriendse(): global h global o global yj os.system('reset') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: o = [] h = 0 yj = 0 print r + ('[ Yahoo Clone ]').center(44) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyError: pass def tayocrack(): os.system('reset') ajg() print r + ('[ Crack Facebook ]').center(44) iz = raw_input(y + '[+] File List ID : ' + c) korbanpass = raw_input(y + '[+] Password : ' + c) if len(korbanpass) <= 5: print r + 'Password To Short' tayocrack() else: if korbanpass == '': print r + 'input password' slw(w + '-' * 45) try: slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except IOError: print '\x1b[1;91m[!] File Not Found' ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() def tgmail(): os.system('clear') ajg() print r + ('[ Brute Gmail ]').center(44) print y + '[' + c + '1.' + y + ']', slw(g + ' Brute Gmail') print y + '[' + c + '2.' + y + ']', slw(g + ' Create Password List') print y + '[' + c + '0' + y + ']', slw(r + ' Back\n') kntd = raw_input(c + '@AutismPeople ' + r + ': ' + g) if kntd == '1': tlogine() else: if kntd == '2': twl() else: if kntd == '0': trial() else: if kntd == '': print r + 'Input Chose' ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') tgmail() else: print r + 'Incorrect' ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') tgmail() def tlogine(): os.system('clear') ajg() try: print r + ('[!] \x1b[33;1mMake sure the target email address is correct \x1b[31;1m[!]').center(44) print b + ('[ DATA ]').center(44) user_name = raw_input(g + 'Target email : ' + c) ppq = user_name if ppq == '': print r + '[!] Input Email' ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') tlogine() ktl = raw_input(g + 'Password List : ' + c) mmq(w + '-' * 45) try: slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print '[!] Stopped' time.sleep(1) trial() except requests.exceptions.ConnectionError: print r + '[!] Connection Error' time.sleep(1) ex() except KeyboardInterrupt: print '[!] Stopped' time.sleep(1) trial() except requests.exceptions.ConnectionError: print r + '[!] Connection Error' time.sleep(1) ex() except IOError: print r + '[!] File Not Found' ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') tlogine() def update(): os.system('git pull') print 'update success' os.system('python2 BotKntD.py') r = '\x1b[31;1m' y = '\x1b[33;1m' b = '\x1b[34;1m' p = '\x1b[35;1m' c = '\x1b[36;1m' w = '\x1b[0;1m' g = '\x1b[32;1m' lr = '\\e[0;31m' ly = '\\e[0;33m' lb = '\\e[0;34m' lp = '\x1b[0;35;0m' lc = '\x1b[0;36m' lw = '\x1b[0;0m' lg = '\x1b[0;32m' h = '\x1b[96m' n = [] ng = [] ids = [] die = [] live = [] cek = [] lin = [] target = [] targete = [] toke = [] fin = [] check = [] crsh = [] liv = [] diet = [] br = mechanize.Browser() br.set_handle_robots(False) br.set_handle_equiv(True) br.set_handle_referer(True) br.set_cookiejar(cookielib.LWPCookieJar()) br.set_handle_redirect(True) br.set_handle_refresh(mechanize._http.HTTPRefreshProcessor(), max_time=1) br.addheaders = [('User-Agent', 'Opera/9.80 (Android; Opera Mini/32.0.2254/85. U; id) Presto/2.12.423 Version/12.16')] def ex(): slw(r + '[!] Ah She Up') time.sleep(1) slw(r + '[!] Exiting') time.sleep(1.5) slw(r + '[!] See You' + w) time.sleep(0.5) os.system('clear') exit() def slw(s): for i in s + '\n': sys.stdout.write(i) sys.stdout.flush() time.sleep(0.005) def fst(s): for i in s + '\n': sys.stdout.write(i) sys.stdout.flush() time.sleep(0.0001) def wl(): os.system('nano password.txt') trial() def twl(): os.system('nano password.txt') trial() def mmk(s): for i in s + '\n': sys.stdout.write(i) sys.stdout.flush() time.sleep(0.01) def mmq(s): for i in s + '\n': sys.stdout.write(i) sys.stdout.flush() time.sleep(1e-07) def tpal(): os.system('reset') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Crack Auto Password ]').center(44) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except requests.exceptions.ConnectionError: print r + '[!] Connection Error' time.sleep(1) ex() except KeyError as IOError: pass def tcheck(): os.system('reset') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Account Cheker ]').center(44) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except requests.exceptions.ConnectionError: print r + '[!] Connection Error' time.sleep(1) ex() except KeyError as IOError: pass def tpala(): os.system('reset') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Crack Auto Password Group ]').center(44) slw(w + '-' * 45) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except requests.exceptions.ConnectionError: print r + '[!] Connection Error' time.sleep(1) ex() except KeyError as IOError: pass def tyahoo(): os.system('clear') ajg() fst(r + ('[ Yahoo Clone ]').center(44)) print y + '[' + c + '1' + y + ']', slw(g + ' Yahoo Clone Friends') print y + '[' + c + '2' + y + ']', slw(g + ' Yahoo Clone Friends From Friends') print y + '[' + c + '3' + y + ']', slw(g + ' Yahoo Clone Followers') print y + '[' + c + '4' + y + ']', slw(g + ' Yahoo Clone Following') print y + '[' + c + '0' + y + ']', slw(r + ' Back\n') ok = raw_input(c + '@AutismPeople : ' + p) fst(w + '-' * 45) if ok == '': print r + '[!] Input Chose' time.sleep(1) trial() else: if ok == '1': tfriendse() else: if ok == '2': tfriendse() else: if ok == '3': tfriendse() else: if ok == '4': tfriendse() else: if ok == '0': trial() else: print r + '[!] ' + p + ok + r + ' Nothing' time.sleep(1) trial() def bot(): os.system('clear') ajg() fst(r + ('[ BOT FACEBOOK ]').center(44)) print y + '[' + c + '1' + y + ']', slw(g + ' Unfriend') print y + '[' + c + '2' + y + ']', slw(g + ' Unfollow') print y + '[' + c + '3' + y + ']', slw(g + ' Auto Follow') print y + '[' + c + '4' + y + ']', slw(g + ' Auto Add Friend From Group') print y + '[' + c + '0' + y + ']', slw(r + ' Back\n') ok = raw_input(c + '@AutismPeople : ' + p) fst(w + '-' * 45) if ok == '': print r + '[!] Input Chose' time.sleep(1) trial() else: if ok == '1': unf() else: if ok == '2': unfl() else: if ok == '0': trial() else: if ok == '3': foll() else: if ok == '4': add() else: print r + '[!] ' + p + ok + r + ' Nothing' time.sleep(1) trial() def unf(): os.system('reset') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Auto Unfriend ]').center(44) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print r + '\r[!] Stopped' trial() except KeyError: print r + '[!] Something Error' trial() except requests.exceptions.ConnectionError: print r + '[!] Connection Error ' exit() def unfl(): id = [] os.system('reset') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Auto Unfollow ]').center(44) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print r + '\r[!] Stopped' trial() except KeyError: print r + '[!] Something Error' trial() except requests.exceptions.ConnectionError: print r + '[!] Connection Error ' exit() red = '\x1b[1;91m' gren = '\x1b[1;92m' yel = '\x1b[1;93m' gid = [] token = [] asua = [] mm = [] def add(): os.system('reset') ajg() try: token = open('token.log', 'r').read() except IOError: print '[!] Token Invalid' time.sleep(1) exit() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Auto Add Friend ]').center(44) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print r + '\r[!] Stopped' trial() except KeyError: print r + '[!] Something Error' trial() except requests.exceptions.ConnectionError: print r + '[!] Connection Error ' exit() def foll(): os.system('clear') ajg() try: token = open('token.log', 'r').read() except IOError: slw(r + '[!] Token Invalid') os.system('rm -rf token.log') time.sleep(1) login() else: try: os.mkdir('Kntd') except OSError: try: print r + ('[ Auto Follower]').center(44) slw(c + 'Sorry,Real Tools Use Password') slw(c + 'Please Contact The Author') slw(c + 'Link password ' + r + ': ' + g + 'https://shortid.co/fZFa6') fst(w + '-' * 45) ngentod = raw_input(r + ' [ \x1b[0mOK \x1b[31;1m]') trial() except KeyboardInterrupt: print r + '\r[!] Stopped' trial() except KeyError: print r + '[!] Something Error' trial() except requests.exceptions.ConnectionError: print r + '[!] Connection Error ' exit() ask()

32.627434

347

0.417153

3,902

36,869

3.904152

0.112506

0.028358

0.02757

0.024156

0.731784

0.705068

0.68334

0.661743

0.64553

0.626625

0

0.03333

0.421411

36,869

1,130

348

32.627434

0.680808

0.005126

0

0.729446

0

0.006692

0.257743

0.009025

0

null

0.065966

0.000956

null

0.115679

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null

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0

1

0

null

0

1

0

1

0

5

72e2a39e8976038f8c0355f9b1e0b57bedcf511e

153

py

Python

src/models/sequence/__init__.py

dumpmemory/state-spaces

2a85503cb3e9e86cc05753950d4a249df9a0fffb

[ "Apache-2.0" ]

513

2021-11-03T23:08:23.000Z

2022-03-31T16:29:18.000Z

src/models/sequence/__init__.py

dumpmemory/state-spaces

2a85503cb3e9e86cc05753950d4a249df9a0fffb

[ "Apache-2.0" ]

18

2021-11-05T12:42:59.000Z

2022-03-27T19:49:55.000Z

src/models/sequence/__init__.py

MikeOwino/state-spaces

b6672bca994b6a36347f414faa59761e42b1e2b1

[ "Apache-2.0" ]

47

2021-11-04T01:32:54.000Z

2022-03-30T18:24:26.000Z

from .base import SequenceModule from .model import SequenceModel from .unet import SequenceUNet from .ff import FF # from .pool import Downpool, Uppool

25.5

36

0.810458

21

153

5.904762

0.571429

0

0.143791

153

5

37

30.6

0.946565

0.222222

0

1

0

true

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null

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1

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null

0

1

0

1

0

1

0

5

f43f5f5f65dda63fb8bc1092d639241cab38f1be

61

py

Python

pytorch_widedeep/models/tabular/linear/__init__.py

TangleSpace/pytorch-widedeep

ccc55a15c1b3205ffc8c054abc5cd25cba9ccdff

[ "MIT" ]

null

pytorch_widedeep/models/tabular/linear/__init__.py

TangleSpace/pytorch-widedeep

ccc55a15c1b3205ffc8c054abc5cd25cba9ccdff

[ "MIT" ]

null

pytorch_widedeep/models/tabular/linear/__init__.py

TangleSpace/pytorch-widedeep

ccc55a15c1b3205ffc8c054abc5cd25cba9ccdff

[ "MIT" ]

null

from pytorch_widedeep.models.tabular.linear.wide import Wide

30.5

60

0.868852

9

61

5.777778

0.888889

0

0.065574

61

1

61

0.912281

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

f4501410195434dfb761f82bf87b94d8d75d2b7d

169

py

Python

codewars/8kyu/dinamuh/Function2-SquaringAnArgument/test.py

dinamuh/Training_one

d18e8fb12608ce1753162c20252ca928c4df97ab

[ "MIT" ]

null

codewars/8kyu/dinamuh/Function2-SquaringAnArgument/test.py

dinamuh/Training_one

d18e8fb12608ce1753162c20252ca928c4df97ab

[ "MIT" ]

2

2019-01-22T10:53:42.000Z

2019-01-31T08:02:48.000Z

codewars/8kyu/dinamuh/Function2-SquaringAnArgument/test.py

dinamuh/Training_one

d18e8fb12608ce1753162c20252ca928c4df97ab

[ "MIT" ]

13

2019-01-22T10:37:42.000Z

2019-01-25T13:30:43.000Z

from main import square def test_square(benchmark): assert benchmark(square, 2) == 4 assert benchmark(square, 50) == 2500 assert benchmark(square, 1) == 1

21.125

40

0.686391

23

169

5

0.565217

0.391304

0.547826

0

0.074627

0.207101

169

7

41

24.142857

0.783582

0

0.6

1

0.2

false

0

0.2

0

0.4

0

1

0

null

1

0

1

0

null

0

1

0

5

f45fc93ac9cf5bd5c18834b630aa5e5b670a8c85

178

py

Python

wagtail_honeypot/apps.py

tomdyson/wagtail-honeypot

99cc00f5eac3153fedebaf97cb0eb060847c948c

[ "MIT" ]

2

2022-02-25T10:23:59.000Z

2022-02-26T21:18:11.000Z

wagtail_honeypot/apps.py

tomdyson/wagtail-honeypot

99cc00f5eac3153fedebaf97cb0eb060847c948c

[ "MIT" ]

2

2022-03-03T21:44:42.000Z

2022-03-04T12:28:27.000Z

wagtail_honeypot/apps.py

tomdyson/wagtail-honeypot

99cc00f5eac3153fedebaf97cb0eb060847c948c

[ "MIT" ]

1

2022-03-04T10:28:04.000Z

from django.apps import AppConfig class WagtailHoneypotAppConfig(AppConfig): label = "wagtail_honeypot" name = "wagtail_honeypot" verbose_name = "Wagtail Honeypot"

22.25

42

0.758427

18

178

7.333333

0.666667

0.340909

0.287879

0

0.168539

178

7

43

25.428571

0.891892

0

0.269663

0

1

0

false

0

0.2

0

1

0

1

0

null

1

0

1

0

null

0

1

0

5

f463e5119c762694860c11366dabe30e0f332652

48

py

Python

app/core/__init__.py

OhBonsai/flask-boilerplate

51c165e19ec47cf3aeee5c20ed12093a87131af7

[ "Apache-2.0" ]

2

2019-01-21T05:44:48.000Z

2021-06-02T20:18:39.000Z

app/core/__init__.py

OhBonsai/flask-boilerplate

51c165e19ec47cf3aeee5c20ed12093a87131af7

[ "Apache-2.0" ]

null

app/core/__init__.py

OhBonsai/flask-boilerplate

51c165e19ec47cf3aeee5c20ed12093a87131af7

[ "Apache-2.0" ]

null

# coding=utf-8 # Created by OhBonsai at 2018/3/7

24

33

0.729167

10

48

3.5

1

0

0.170732

0.145833

48

2

33

24

0.682927

0.916667

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

be5a29f533cbccdbad66fec3fe3e51b929599b6f

56

py

Python

src/github_vulnerability_exporter/__init__.py

ZeitOnline/github_vulnerability_exporter

dcc81c08820bd46f747fa5c6ce877354c404258c

[ "BSD-3-Clause" ]

1

2019-06-06T14:44:12.000Z

src/github_vulnerability_exporter/__init__.py

ZeitOnline/github_vulnerability_exporter

dcc81c08820bd46f747fa5c6ce877354c404258c

[ "BSD-3-Clause" ]

1

2021-06-24T11:14:55.000Z

src/github_vulnerability_exporter/__init__.py

ZeitOnline/github_vulnerability_exporter

dcc81c08820bd46f747fa5c6ce877354c404258c

[ "BSD-3-Clause" ]

1

2021-11-30T10:39:15.000Z

from github_vulnerability_exporter.exporter import main

28

55

0.910714

7

56

7

0.857143

0

0.071429

56

1

56

0.942308

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

be5dfebf478dfe054fb82f7b2c6612c35f23a31c

275

py

Python

pysal/explore/pointpats/__init__.py

martinfleis/pysal

d2e0667d825d403efe7182ecda210dc152ec206d

[ "BSD-3-Clause" ]

941

2015-01-12T22:25:55.000Z

2022-03-27T15:41:29.000Z

pysal/explore/pointpats/__init__.py

anekekarina99/pysal

bd8c954d34b4694416830a852e26fe40d64424f2

[ "BSD-3-Clause" ]

589

2015-01-09T03:58:03.000Z

2022-02-26T02:17:15.000Z

pysal/explore/pointpats/__init__.py

anekekarina99/pysal

bd8c954d34b4694416830a852e26fe40d64424f2

[ "BSD-3-Clause" ]

303

2015-01-10T02:59:04.000Z

2022-03-05T04:21:55.000Z

from pointpats.pointpattern import PointPattern from pointpats.window import as_window, poly_from_bbox, to_ccf, Window from pointpats.centrography import * from pointpats.process import * from pointpats.quadrat_statistics import * from pointpats.distance_statistics import *

39.285714

70

0.854545

35

275

6.542857

0.428571

0.340611

0.248908

0

0.098182

275

6

71

45.833333

0.923387

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

be7e00a9b607aadf5f5a7d4fd1bd32246047d0a7

29

py

Python

load_generator/__init__.py

uzum/cran-orchestrator

c2235bf324c8c04e82960ca58ec49f2f700c065d

[ "MIT" ]

null

load_generator/__init__.py

uzum/cran-orchestrator

c2235bf324c8c04e82960ca58ec49f2f700c065d

[ "MIT" ]

null

load_generator/__init__.py

uzum/cran-orchestrator

c2235bf324c8c04e82960ca58ec49f2f700c065d

[ "MIT" ]

null

from .server import LGServer

14.5

28

0.827586

4

29

6

1

0

0.137931

29

1

29

0.96

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

be930d1e18d893824a6e8e815b44c5e8854070c7

21

py

Python

hello_world.py

Pertrang/profiles-rest-api

3e27c19940dcfb9feee9bb4519e5fc8d77b91722

[ "MIT" ]

null

hello_world.py

Pertrang/profiles-rest-api

3e27c19940dcfb9feee9bb4519e5fc8d77b91722

[ "MIT" ]

null

hello_world.py

Pertrang/profiles-rest-api

3e27c19940dcfb9feee9bb4519e5fc8d77b91722

[ "MIT" ]

null

print("hellp world!")

21

0.714286

3

21

5

1

0

0.047619

21

1

21

0.75

0

0.545455

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

bec4cbacc83ad9d7321c853d5ba8649c57148a37

310

py

Python

test_project/test_app/conftest.py

bjuretko/django-admin-object-actions

2c80ffcbb53b3d585f191d1fe662daf36fa7e204

[ "BSD-3-Clause" ]

null

test_project/test_app/conftest.py

bjuretko/django-admin-object-actions

2c80ffcbb53b3d585f191d1fe662daf36fa7e204

[ "BSD-3-Clause" ]

null

test_project/test_app/conftest.py

bjuretko/django-admin-object-actions

2c80ffcbb53b3d585f191d1fe662daf36fa7e204

[ "BSD-3-Clause" ]

null

# py.test import pytest @pytest.fixture def apps(request, db): from django.apps import apps return apps @pytest.fixture def test_model(apps): return apps.get_model('test_app', 'TestModel') @pytest.fixture def test_model_instance(test_model): return test_model.objects.create(name='test')

16.315789

50

0.73871

45

310

4.933333

0.444444

0.162162

0.216216

0.18018

0.225225

0

0.151613

310

18

51

17.222222

0.844106

0.022581

0

0.272727

0

0.069767

0

1

0.272727

false

0

0.181818

0.727273

0

null

0

1

0

null

0

1

0

1

0

5

fe4886f5c2eb47d1f57db21d368914d137924e4d

144

py

Python

WechatTool.py

ftctolei/GetNovel

f73f18cb12912d22c435064a542fed707d8c9077

[ "Apache-2.0" ]

null

WechatTool.py

ftctolei/GetNovel

f73f18cb12912d22c435064a542fed707d8c9077

[ "Apache-2.0" ]

null

WechatTool.py

ftctolei/GetNovel

f73f18cb12912d22c435064a542fed707d8c9077

[ "Apache-2.0" ]

null

#coding=utf-8 import itchat #itchat.auto_login(enableCmdQR=True) itchat.auto_login() itchat.send('Hello, filehelper', toUserName='filehelper')

20.571429

57

0.791667

19

144

5.894737

0.684211

0.178571

0.267857

0

0.007407

0.0625

144

6

58

24

0.822222

0.326389

0

0.284211

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

fe5ed8993790a1ec3aeb5060a63f819825b5414d

266

py

Python

satef/alignment/impl/LHAAlignmentFactory.py

kostrzmar/SATEF

b483b073f1ff3dd797413f212e26114ef93cfe08

[ "MIT" ]

null

satef/alignment/impl/LHAAlignmentFactory.py

kostrzmar/SATEF

b483b073f1ff3dd797413f212e26114ef93cfe08

[ "MIT" ]

null

satef/alignment/impl/LHAAlignmentFactory.py

kostrzmar/SATEF

b483b073f1ff3dd797413f212e26114ef93cfe08

[ "MIT" ]

null

from alignment import AbstractAlignmentFactory from alignment import AbstractAlignment from alignment.impl import LHAAlignment class LHAAlignmentFactory(AbstractAlignmentFactory): def getAlignment(self) -> AbstractAlignment: return LHAAlignment()

29.555556

52

0.81203

22

266

9.818182

0.590909

0.180556

0.175926

0

0.146617

266

9

53

29.555556

0.951542

0

1

0.166667

false

0

0.5

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fe6905647db8984d2da06bf595270d84de66ef07

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py

Python

_solved/solutions/case-conflict-mapping25.py

lleondia/geopandas-tutorial

5128fd6865bbd979a7b4e5b8cb4d0de51bead029

[ "BSD-3-Clause" ]

341

2018-04-26T08:46:05.000Z

2022-03-01T08:13:39.000Z

_solved/solutions/case-conflict-mapping25.py

lleondia/geopandas-tutorial

5128fd6865bbd979a7b4e5b8cb4d0de51bead029

[ "BSD-3-Clause" ]

22

2018-06-15T23:19:27.000Z

2020-03-23T11:08:55.000Z

_solved/solutions/case-conflict-mapping25.py

lleondia/geopandas-tutorial

5128fd6865bbd979a7b4e5b8cb4d0de51bead029

[ "BSD-3-Clause" ]

197

2018-06-15T18:34:53.000Z

2022-02-27T11:33:15.000Z

kahuzi = protected_areas_utm[protected_areas_utm['NAME_AP'] == "Kahuzi-Biega National park"].geometry.squeeze()

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fe6c7306ea45ba728a041d1a5589eb2832619504

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py

Python

couleuvre/__main__.py

ykacer/couleuvre

e1fd7b44ad28fa9e93c64d8bdb7dbf0b0277c227

[ "MIT" ]

null

couleuvre/__main__.py

ykacer/couleuvre

e1fd7b44ad28fa9e93c64d8bdb7dbf0b0277c227

[ "MIT" ]

null

couleuvre/__main__.py

ykacer/couleuvre

e1fd7b44ad28fa9e93c64d8bdb7dbf0b0277c227

[ "MIT" ]

null

from .text import message_print def main(): print("Here is the message :") print("---------------------") message_print() if __name__ == "__main__": main()

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py

Python

frost/server/storage/defaults.py

Den4200/pyfrost

c341eeb1262746d889dcff4f405f7d52f7caf23d

[ "MIT" ]

2

2020-03-02T14:29:07.000Z

2020-03-04T00:36:35.000Z

frost/server/storage/defaults.py

Den4200/pyfrost

c341eeb1262746d889dcff4f405f7d52f7caf23d

[ "MIT" ]

16

2020-03-08T05:50:48.000Z

2020-05-11T04:40:13.000Z

frost/server/storage/defaults.py

Den4200/pyfrost

c341eeb1262746d889dcff4f405f7d52f7caf23d

[ "MIT" ]

1

2020-03-29T00:33:04.000Z

DEFAULT_FORMAT = { 'users': { 'meta': { 'last_id': '0' } }, 'rooms': { 'meta': { 'last_id': '0' } }, 'messages': { 'meta': { 'last_id': '0' } } }

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py

Python

user/admin.py

jlech42/chump_django

6650de31ec9c4c35e45641a88f212e06a80ea4d7

[ "MIT" ]

null

user/admin.py

jlech42/chump_django

6650de31ec9c4c35e45641a88f212e06a80ea4d7

[ "MIT" ]

null

user/admin.py

jlech42/chump_django

6650de31ec9c4c35e45641a88f212e06a80ea4d7

[ "MIT" ]

null

from django.contrib import admin from .models import Profile, UserSubscription, UserContent # Register your models here. admin.site.register(UserContent) admin.site.register(Profile) admin.site.register(UserSubscription)

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py

Python

redis_mock/__init__.py

adamlwgriffiths/redis-mock

418df5899bab04e541469eb5b9b8e21acda48e9e

[ "MIT" ]

1

2021-01-19T05:58:02.000Z

redis_mock/__init__.py

adamlwgriffiths/redis-mock

418df5899bab04e541469eb5b9b8e21acda48e9e

[ "MIT" ]

null

redis_mock/__init__.py

adamlwgriffiths/redis-mock

418df5899bab04e541469eb5b9b8e21acda48e9e

[ "MIT" ]

null

from .redis_mock import *

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py

Python

OpenGLCffi/GL/EXT/KHR/blend_equation_advanced.py

cydenix/OpenGLCffi

c78f51ae5e6b655eb2ea98f072771cf69e2197f3

[ "MIT" ]

null

OpenGLCffi/GL/EXT/KHR/blend_equation_advanced.py

cydenix/OpenGLCffi

c78f51ae5e6b655eb2ea98f072771cf69e2197f3

[ "MIT" ]

null

OpenGLCffi/GL/EXT/KHR/blend_equation_advanced.py

cydenix/OpenGLCffi

c78f51ae5e6b655eb2ea98f072771cf69e2197f3

[ "MIT" ]

null

from OpenGLCffi.GL import params @params(api='gl', prms=[]) def glBlendBarrierKHR(): pass

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22f6c51667ca02b727b1a01ae4fe4ad2f5081565

50

py

Python

enthought/traits/ui/qt4/ui_base.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

3

2016-12-09T06:05:18.000Z

2018-03-01T13:00:29.000Z

enthought/traits/ui/qt4/ui_base.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

1

2020-12-02T00:51:32.000Z

2020-12-02T08:48:55.000Z

enthought/traits/ui/qt4/ui_base.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

null

# proxy module from traitsui.qt4.ui_base import *

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5

a3c77790c19a7c54f9abc5320a30d0be5f912b21

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py

Python

pygit/__version__.py

immensity/pygit

6c2dc5081a75600c9437faa318a1ca3c0645b1fb

[ "MIT" ]

17

2018-09-08T11:35:47.000Z

2022-03-19T21:31:33.000Z

pygit/__version__.py

immensity/pygit

6c2dc5081a75600c9437faa318a1ca3c0645b1fb

[ "MIT" ]

8

2020-02-19T06:14:25.000Z

2021-11-18T12:32:06.000Z

pygit/__version__.py

immensity/pygit

6c2dc5081a75600c9437faa318a1ca3c0645b1fb

[ "MIT" ]

2

2020-02-19T17:02:32.000Z

2021-02-21T14:51:35.000Z

__version__ = "2019.01.31"

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0

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4a3320a5daf80b8cf803a30b671f4532e196e5e5

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py

Python

huiAudioCorpus/model/Credentials.py

iisys-hof/HUI-Audio-Corpus-German

4d2de2ed538a6b943166e1e35c10ee8b0b266be6

[ "Apache-2.0" ]

11

2021-06-22T09:44:28.000Z

2022-01-10T12:35:29.000Z

huiAudioCorpus/model/Credentials.py

iisys-hof/HUI-Audio-Corpus-German

4d2de2ed538a6b943166e1e35c10ee8b0b266be6

[ "Apache-2.0" ]

1

2021-07-17T20:19:01.000Z

2021-10-04T09:36:43.000Z

huiAudioCorpus/model/Credentials.py

iisys-hof/HUI-Audio-Corpus-German

4d2de2ed538a6b943166e1e35c10ee8b0b266be6

[ "Apache-2.0" ]

null

class Credentials: def __init__(self, username:str, password:str): self.username = username self.password = password

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Python

tests/rbac/test_role_manager.py

gmc77/pycasbin

fbbc6000f755c78726f24d26c45bdf9bda99b5d6

[ "Apache-2.0" ]

915

2018-11-25T01:00:39.000Z

2022-03-30T11:21:34.000Z

tests/rbac/test_role_manager.py

ffyuanda/pycasbin

230132e459420aaa519d1eb9479f8996bdbbbd2a

[ "Apache-2.0" ]

231

2019-02-13T09:29:51.000Z

2022-03-28T16:32:51.000Z

tests/rbac/test_role_manager.py

ffyuanda/pycasbin

230132e459420aaa519d1eb9479f8996bdbbbd2a

[ "Apache-2.0" ]

173

2019-02-08T02:22:33.000Z

2022-03-10T15:16:11.000Z

from unittest import TestCase from casbin.rbac import default_role_manager from casbin.util import regex_match_func import time from concurrent.futures import ThreadPoolExecutor def get_role_manager(): return default_role_manager.RoleManager(max_hierarchy_level=10) class TestDefaultRoleManager(TestCase): def test_role(self): rm = get_role_manager() rm.add_link("u1", "g1") rm.add_link("u2", "g1") rm.add_link("u3", "g2") rm.add_link("u4", "g2") rm.add_link("u4", "g3") rm.add_link("g1", "g3") # Current role inheritance tree: # g3 g2 # / \ / \ # g1 u4 u3 # / \ # u1 u2 self.assertTrue(rm.has_link("u1", "g1")) self.assertFalse(rm.has_link("u1", "g2")) self.assertTrue(rm.has_link("u1", "g3")) self.assertTrue(rm.has_link("u2", "g1")) self.assertFalse(rm.has_link("u2", "g2")) self.assertTrue(rm.has_link("u2", "g3")) self.assertFalse(rm.has_link("u3", "g1")) self.assertTrue(rm.has_link("u3", "g2")) self.assertFalse(rm.has_link("u3", "g3")) self.assertFalse(rm.has_link("u4", "g1")) self.assertTrue(rm.has_link("u4", "g2")) self.assertTrue(rm.has_link("u4", "g3")) self.assertCountEqual(rm.get_roles("u1"), ["g1"]) self.assertCountEqual(rm.get_roles("u2"), ["g1"]) self.assertCountEqual(rm.get_roles("u3"), ["g2"]) self.assertCountEqual(rm.get_roles("u4"), ["g2", "g3"]) self.assertCountEqual(rm.get_roles("g1"), ["g3"]) self.assertCountEqual(rm.get_roles("g2"), []) self.assertCountEqual(rm.get_roles("g3"), []) rm.delete_link("g1", "g3") rm.delete_link("u4", "g2") # Current role inheritance tree after deleting the links: # g3 g2 # \ \ # g1 u4 u3 # / \ # u1 u2 self.assertTrue(rm.has_link("u1", "g1")) self.assertFalse(rm.has_link("u1", "g2")) self.assertFalse(rm.has_link("u1", "g3")) self.assertTrue(rm.has_link("u2", "g1")) self.assertFalse(rm.has_link("u2", "g2")) self.assertFalse(rm.has_link("u2", "g3")) self.assertFalse(rm.has_link("u3", "g1")) self.assertTrue(rm.has_link("u3", "g2")) self.assertFalse(rm.has_link("u3", "g3")) self.assertFalse(rm.has_link("u4", "g1")) self.assertFalse(rm.has_link("u4", "g2")) self.assertTrue(rm.has_link("u4", "g3")) self.assertCountEqual(rm.get_roles("u1"), ["g1"]) self.assertCountEqual(rm.get_roles("u2"), ["g1"]) self.assertCountEqual(rm.get_roles("u3"), ["g2"]) self.assertCountEqual(rm.get_roles("u4"), ["g3"]) self.assertCountEqual(rm.get_roles("g1"), []) self.assertCountEqual(rm.get_roles("g2"), []) self.assertCountEqual(rm.get_roles("g3"), []) def test_domain_role(self): rm = get_role_manager() rm.add_link("u1", "g1", "domain1") rm.add_link("u2", "g1", "domain1") rm.add_link("u3", "admin", "domain2") rm.add_link("u4", "admin", "domain2") rm.add_link("u4", "admin", "domain1") rm.add_link("g1", "admin", "domain1") # Current role inheritance tree: # domain1:admin domain2:admin # / \ / \ # domain1:g1 u4 u3 # / \ # u1 u2 self.assertTrue(rm.has_link("u1", "g1", "domain1")) self.assertFalse(rm.has_link("u1", "g1", "domain2")) self.assertTrue(rm.has_link("u1", "admin", "domain1")) self.assertFalse(rm.has_link("u1", "admin", "domain2")) self.assertTrue(rm.has_link("u2", "g1", "domain1")) self.assertFalse(rm.has_link("u2", "g1", "domain2")) self.assertTrue(rm.has_link("u2", "admin", "domain1")) self.assertFalse(rm.has_link("u2", "admin", "domain2")) self.assertFalse(rm.has_link("u3", "g1", "domain1")) self.assertFalse(rm.has_link("u3", "g1", "domain2")) self.assertFalse(rm.has_link("u3", "admin", "domain1")) self.assertTrue(rm.has_link("u3", "admin", "domain2")) self.assertFalse(rm.has_link("u4", "g1", "domain1")) self.assertFalse(rm.has_link("u4", "g1", "domain2")) self.assertTrue(rm.has_link("u4", "admin", "domain1")) self.assertTrue(rm.has_link("u4", "admin", "domain2")) def test_clear(self): rm = get_role_manager() rm.add_link("u1", "g1") rm.add_link("u2", "g1") rm.add_link("u3", "g2") rm.add_link("u4", "g2") rm.add_link("u4", "g3") rm.add_link("g1", "g3") # Current role inheritance tree: # g3 g2 # / \ / \ # g1 u4 u3 # / \ # u1 u2 rm.clear() # All data is cleared. # No role inheritance now. self.assertFalse(rm.has_link("u1", "g1")) self.assertFalse(rm.has_link("u1", "g2")) self.assertFalse(rm.has_link("u1", "g3")) self.assertFalse(rm.has_link("u2", "g1")) self.assertFalse(rm.has_link("u2", "g2")) self.assertFalse(rm.has_link("u2", "g3")) self.assertFalse(rm.has_link("u3", "g1")) self.assertFalse(rm.has_link("u3", "g2")) self.assertFalse(rm.has_link("u3", "g3")) self.assertFalse(rm.has_link("u4", "g1")) self.assertFalse(rm.has_link("u4", "g2")) self.assertFalse(rm.has_link("u4", "g3")) def test_matching_func(self): rm = get_role_manager() rm.add_matching_func(regex_match_func) rm.add_link("u1", "g1") rm.add_link("u3", "g2") rm.add_link("u3", "g3") rm.add_link(r"u\d+", "g2") self.assertTrue(rm.has_link("u1", "g1")) self.assertTrue(rm.has_link("u1", "g2")) self.assertFalse(rm.has_link("u1", "g3")) self.assertFalse(rm.has_link("u2", "g1")) self.assertTrue(rm.has_link("u2", "g2")) self.assertFalse(rm.has_link("u2", "g3")) self.assertFalse(rm.has_link("u3", "g1")) self.assertTrue(rm.has_link("u3", "g2")) self.assertTrue(rm.has_link("u3", "g3")) def test_one_to_many(self): rm = get_role_manager() rm.add_matching_func(regex_match_func) rm.add_link("u1", r"g\d+") self.assertTrue(rm.has_link("u1", "g1")) self.assertTrue(rm.has_link("u1", "g2")) self.assertFalse(rm.has_link("u2", "g1")) self.assertFalse(rm.has_link("u2", "g2")) def test_many_to_one(self): rm = get_role_manager() rm.add_matching_func(regex_match_func) rm.add_link(r"u\d+", "g1") self.assertTrue(rm.has_link("u1", "g1")) self.assertFalse(rm.has_link("u1", "g2")) self.assertTrue(rm.has_link("u2", "g1")) self.assertFalse(rm.has_link("u2", "g2")) def test_matching_func_order(self): rm = get_role_manager() rm.add_matching_func(regex_match_func) rm.add_link(r"g\d+", "root") rm.add_link("u1", "g1") self.assertTrue(rm.has_link("u1", "root")) rm.clear() rm.add_link("u1", "g1") rm.add_link(r"g\d+", "root") self.assertTrue(rm.has_link("u1", "root")) rm.clear() rm.add_link("u1", r"g\d+") rm.add_link("g1", "root") self.assertTrue(rm.has_link("u1", "root")) rm.clear() rm.add_link("g1", "root") rm.add_link("u1", r"g\d+") self.assertTrue(rm.has_link("u1", "root")) def test_concurrent_has_link_with_matching_func(self): def matching_func(*args): time.sleep(0.01) return regex_match_func(*args) rm = get_role_manager() rm.add_matching_func(matching_func) rm.add_link(r"u\d+", "users") def test_has_link(role): return rm.has_link(role, "users") executor = ThreadPoolExecutor(10) futures = [executor.submit(test_has_link, "u" + str(i)) for i in range(10)] for future in futures: self.assertTrue(future.result())

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4a5d2171b7bd0ad9543b5aa9f571c610db5061c4

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py

Python

CalibTracker/Configuration/python/SiStripPedestals/SiStripPedestals_Fake_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

852

2015-01-11T21:03:51.000Z

2022-03-25T21:14:00.000Z

CalibTracker/Configuration/python/SiStripPedestals/SiStripPedestals_Fake_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

30,371

2015-01-02T00:14:40.000Z

2022-03-31T23:26:05.000Z

CalibTracker/Configuration/python/SiStripPedestals/SiStripPedestals_Fake_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

3,240

2015-01-02T05:53:18.000Z

2022-03-31T17:24:21.000Z

import FWCore.ParameterSet.Config as cms from CalibTracker.SiStripESProducers.fake.SiStripPedestalsFakeESSource_cfi import *

21.333333

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4a6460b51b38a154882d351d6a61d86d961cdc02

50

py

Python

mdentropy/core/__init__.py

msmbuilder/mdentropy

82d616ddffe11283052b2d870c3b0274736a173c

[ "MIT" ]

25

2017-10-03T00:40:33.000Z

2022-02-18T14:33:56.000Z

mdentropy/core/__init__.py

shozebhaider/mdentropy

82d616ddffe11283052b2d870c3b0274736a173c

[ "MIT" ]

46

2016-04-01T15:44:22.000Z

2020-08-13T20:04:16.000Z

mdentropy/core/__init__.py

shozebhaider/mdentropy

82d616ddffe11283052b2d870c3b0274736a173c

[ "MIT" ]

14

2016-03-28T21:45:16.000Z

2022-03-02T13:21:09.000Z

from .entropy import * from .information import *

16.666667

26

0.76

6

50

6.333333

0.666667

0

0.16

50

2

27

25

0.904762

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5