xszheng2020/the_stack_dedup_python_hits_2 · Datasets at Hugging Face

d7e72c05c821b5b2aa9289c98ad93b19e168816c

1,487

py

Python

issue_order/migrations/0005_auto_20170211_0033.py

jiejiang/courier

6fdeaf041c77dba0f97e206adb7b0cded9674d3d

[ "Apache-2.0" ]

null

issue_order/migrations/0005_auto_20170211_0033.py

jiejiang/courier

6fdeaf041c77dba0f97e206adb7b0cded9674d3d

[ "Apache-2.0" ]

13

2020-02-12T02:56:24.000Z

2022-01-13T01:23:08.000Z

issue_order/migrations/0005_auto_20170211_0033.py

jiejiang/courier

6fdeaf041c77dba0f97e206adb7b0cded9674d3d

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Generated by Django 1.10.3 on 2017-02-11 00:33 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('issue_order', '0004_auto_20170210_2358'), ] operations = [ migrations.AlterField( model_name='courierbatch', name='credit', field=models.DecimalField(blank=True, decimal_places=2, max_digits=10, null=True, verbose_name='Credit'), ), migrations.AlterField( model_name='courierbatch', name='rate', field=models.DecimalField(blank=True, decimal_places=2, max_digits=10, null=True, verbose_name='Rate per Package'), ), migrations.AlterField( model_name='courierbatch', name='state', field=models.IntegerField(db_index=True, default=2, verbose_name='State'), ), migrations.AlterField( model_name='courierbatch', name='system', field=models.CharField(blank=True, choices=[('yunda', '\u97f5\u8fbe\u7ebf'), ('postal', '\u90ae\u653f\u7ebf')], db_index=True, max_length=32, null=True, verbose_name='System Name'), ), migrations.AlterField( model_name='courierbatch', name='uuid', field=models.CharField(blank=True, db_index=True, max_length=64, null=True, unique=True, verbose_name='UUID'), ), ]

36.268293

193

0.615333

162

1,487

5.475309

0.438272

0.11274

0.140924

0.163472

0.535513

0.425028

0.171364

0

0.049416

0.251513

1,487

40

194

37.175

0.747529

0.04573

0

0.454545

1

0

0.146893

0.016243

0

1

0

false

0

0.060606

0

0.151515

0

null

0

1

0

1

0

null

0

2

d7ec3af0754886496ab74d63932b32e5dda81ec2

547

py

Python

resources/__init__.py

tiralinka/amazon_fires

bda8cb2a6910be17e9cbbfb4f214a2b019efd145

[ "MIT" ]

1

2021-03-08T02:40:00.000Z

resources/__init__.py

tiralinka/amazon_fires

bda8cb2a6910be17e9cbbfb4f214a2b019efd145

[ "MIT" ]

null

resources/__init__.py

tiralinka/amazon_fires

bda8cb2a6910be17e9cbbfb4f214a2b019efd145

[ "MIT" ]

2

2021-01-17T13:51:31.000Z

2021-05-27T22:22:49.000Z

""" This package contains modules built specifically for the project in question. Below are decribed the modules and packages used in the notebooks of this project. Modules ----------- polynomials: | This module groups functions and classes for generating polynomials | whether fitting data or directly ortogonal polynomials | (Legendre polynomials). plotter: | This module groups functions for visualizations presented throughout the notebooks. functk: | This module exits outside this package and contains utilities functions. """

28.789474

87

0.778793

67

547

6.358209

0.597015

0.070423

0.075117

0.117371

0

0.162706

547

19

88

28.789474

0.930131

0.985375

0

null

0

null

0

null

0

null

1

null

true

0

null

0

null

0

1

0

null

0

1

0

2

d7f2887e18f1782d6580198e20f7cacc72ac9027

292

py

Python

elasticine/adapter.py

Drizzt1991/plasticine

be61baa88f53bdfa666d068a14f17ccc0cfe4d02

[ "MIT" ]

null

elasticine/adapter.py

Drizzt1991/plasticine

be61baa88f53bdfa666d068a14f17ccc0cfe4d02

[ "MIT" ]

null

elasticine/adapter.py

Drizzt1991/plasticine

be61baa88f53bdfa666d068a14f17ccc0cfe4d02

[ "MIT" ]

null

# -*- coding: utf-8 -*- from elasticsearch import Elasticsearch class ElasticAdapter(object): """ Abstraction in case we will need to add another or change elastic driver. """ def __init__(self, hosts, **es_params): self.es = Elasticsearch(hosts, **es_params)

22.461538

73

0.660959

35

292

5.342857

0.8

0.074866

0.139037

0

0.004425

0.226027

292

12

74

24.333333

0.823009

0.328767

0

1

0.25

false

0

0.25

0

0.75

0

null

0

null

0

1

0

1

0

2

cc0fa341d500758a4666f87a2715835852c484f0

12,526

py

Python

vb2py/PythonCard/tools/codeEditor/codeEditorR.rsrc.py

ceprio/xl_vb2py

899fec0301140fd8bd313e8c80b3fa839b3f5ee4

[ "BSD-3-Clause" ]

null

vb2py/PythonCard/tools/codeEditor/codeEditorR.rsrc.py

ceprio/xl_vb2py

899fec0301140fd8bd313e8c80b3fa839b3f5ee4

[ "BSD-3-Clause" ]

null

vb2py/PythonCard/tools/codeEditor/codeEditorR.rsrc.py

ceprio/xl_vb2py

899fec0301140fd8bd313e8c80b3fa839b3f5ee4

[ "BSD-3-Clause" ]

null

{'application':{'type':'Application', 'name':'codeEditor', 'backgrounds': [ {'type':'Background', 'name':'bgCodeEditor', 'title':'Code Editor R PythonCard Application', 'size':(400, 300), 'statusBar':1, 'visible':0, 'style':['resizeable'], 'visible':0, 'menubar': {'type':'MenuBar', 'menus': [ {'type':'Menu', 'name':'menuFile', 'label':'&File', 'items': [ {'type':'MenuItem', 'name':'menuFileNewWindow', 'label':'New Window', }, {'type':'MenuItem', 'name':'menuFileNew', 'label':'&New\tCtrl+N', }, {'type':'MenuItem', 'name':'menuFileOpen', 'label':'&Open\tCtrl+O', }, {'type':'MenuItem', 'name':'menuFileSave', 'label':'&Save\tCtrl+S', }, {'type':'MenuItem', 'name':'menuFileSaveAs', 'label':'Save &As...', }, {'type':'MenuItem', 'name':'fileSep1', 'label':'-', }, {'type':'MenuItem', 'name':'menuFileCheckSyntax', 'label':'&Check Syntax (Module)\tAlt+F5', 'command':'checkSyntax', }, {'type':'MenuItem', 'name':'menuFileRun', 'label':'&Run\tCtrl+R', 'command':'fileRun', }, {'type':'MenuItem', 'name':'menuFileRunWithInterpreter', 'label':'Run with &interpreter\tCtrl+Shift+R', 'command':'fileRunWithInterpreter', }, {'type':'MenuItem', 'name':'menuFileRunOptions', 'label':'Run Options...', 'command':'fileRunOptions', }, {'type':'MenuItem', 'name':'fileSep2', 'label':'-', }, {'type':'MenuItem', 'name':'menuFilePageSetup', 'label':'Page Set&up...', }, {'type':'MenuItem', 'name':'menuFilePrint', 'label':'&Print...\tCtrl+P', }, {'type':'MenuItem', 'name':'menuFilePrintPreview', 'label':'Print Pre&view', }, {'type':'MenuItem', 'name':'fileSep2', 'label':'-', }, {'type':'MenuItem', 'name':'menuFileExit', 'label':'E&xit\tAlt+X', 'command':'exit', }, ] }, {'type':'Menu', 'name':'Edit', 'label':'&Edit', 'items': [ {'type':'MenuItem', 'name':'menuEditUndo', 'label':'&Undo\tCtrl+Z', }, {'type':'MenuItem', 'name':'menuEditRedo', 'label':'&Redo\tCtrl+Y', }, {'type':'MenuItem', 'name':'editSep1', 'label':'-', }, {'type':'MenuItem', 'name':'menuEditCut', 'label':'Cu&t\tCtrl+X', }, {'type':'MenuItem', 'name':'menuEditCopy', 'label':'&Copy\tCtrl+C', }, {'type':'MenuItem', 'name':'menuEditPaste', 'label':'&Paste\tCtrl+V', }, {'type':'MenuItem', 'name':'editSep2', 'label':'-', }, {'type':'MenuItem', 'name':'menuEditFind', 'label':'&Find...\tCtrl+F', 'command':'doEditFind', }, {'type':'MenuItem', 'name':'menuEditFindNext', 'label':'&Find Next\tF3', 'command':'doEditFindNext', }, {'type':'MenuItem', 'name':'menuEditFindFiles', 'label':'Find in Files...\tAlt+F3', 'command':'findFiles', }, {'type':'MenuItem', 'name':'menuEditReplace', 'label':'&Replace...\tCtrl+H', 'command':'doEditFindReplace', }, {'type':'MenuItem', 'name':'menuEditGoTo', 'label':'&Go To...\tCtrl+G', 'command':'doEditGoTo', }, {'type':'MenuItem', 'name':'editSep3', 'label':'-', }, {'type':'MenuItem', 'name':'menuEditReplaceTabs', 'label':'&Replace tabs with spaces', 'command':'doEditReplaceTabs', }, {'type':'MenuItem', 'name':'editSep3', 'label':'-', }, {'type':'MenuItem', 'name':'menuEditClear', 'label':'Cle&ar\tDel', }, {'type':'MenuItem', 'name':'menuEditSelectAll', 'label':'Select A&ll\tCtrl+A', }, {'type':'MenuItem', 'name':'editSep4', 'label':'-', }, {'type':'MenuItem', 'name':'menuEditIndentRegion', 'label':'&Indent Region', 'command':'indentRegion', }, {'type':'MenuItem', 'name':'menuEditDedentRegion', 'label':'&Dedent Region', 'command':'dedentRegion', }, {'type':'MenuItem', 'name':'menuEditCommentRegion', 'label':'Comment &out region\tAlt+3', 'command':'commentRegion', }, {'type':'MenuItem', 'name':'menuEditUncommentRegion', 'label':'U&ncomment region\tShift+Alt+3', 'command':'uncommentRegion', }, ] }, {'type':'Menu', 'name':'menuView', 'label':'&View', 'items': [ {'type':'MenuItem', 'name':'menuViewWhitespace', 'label':'&Whitespace', 'checkable':1, }, {'type':'MenuItem', 'name':'menuViewIndentationGuides', 'label':'Indentation &guides', 'checkable':1, }, {'type':'MenuItem', 'name':'menuViewRightEdgeIndicator', 'label':'&Right edge indicator', 'checkable':1, }, {'type':'MenuItem', 'name':'menuViewEndOfLineMarkers', 'label':'&End-of-line markers', 'checkable':1, }, {'type':'MenuItem', 'name':'menuViewFixedFont', 'label':'&Fixed Font', 'enabled':0, 'checkable':1, }, {'type':'MenuItem', 'name':'viewSep1', 'label':'-', }, {'type':'MenuItem', 'name':'menuViewLineNumbers', 'label':'&Line Numbers', 'checkable':1, 'checked':1, }, {'type':'MenuItem', 'name':'menuViewCodeFolding', 'label':'&Code Folding', 'checkable':1, 'checked':0, }, ] }, {'type':'Menu', 'name':'menuFormat', 'label':'F&ormat', 'items': [ {'type':'MenuItem', 'name':'menuFormatStyles', 'label':'&Styles...', 'command':'doSetStyles', }, {'type':'MenuItem', 'name':'menuFormatWrap', 'label':'&Wrap Lines', 'checkable':1, }, ] }, {'type':'Menu', 'name':'menuScriptlet', 'label':'&Shell', 'items': [ {'type':'MenuItem', 'name':'menuScriptletShell', 'label':'&Shell Window\tF5', }, {'type':'MenuItem', 'name':'menuScriptletNamespace', 'label':'&Namespace Window\tF6', }, {'type':'MenuItem', 'name':'scriptletSep1', 'label':'-', }, {'type':'MenuItem', 'name':'menuScriptletSaveShellSelection', 'label':'Save Shell Selection...', }, {'type':'MenuItem', 'name':'menuScriptletRunScriptlet', 'label':'Run Scriptlet...', }, ] }, {'type':'Menu', 'name':'menuHelp', 'label':'&Help', 'items': [ {'type':'MenuItem', 'name':'menuShellDocumentation', 'label':'&Shell Documentation...', 'command':'showShellDocumentation', }, {'type':'MenuItem', 'name':'menuPythonCardDocumentation', 'label':'&PythonCard Documentation...\tF1', 'command':'showPythonCardDocumentation', }, {'type':'MenuItem', 'name':'menuPythonDocumentation', 'label':'Python &Documentation...', 'command':'showPythonDocumentation', }, {'type':'MenuItem', 'name':'helpSep1', 'label':'-', }, {'type':'MenuItem', 'name':'menuHelpAbout', 'label':'&About codeEditor...', 'command':'doHelpAbout', }, ] }, ] }, 'strings': { 'saveAs':'Save As', 'about':'About codeEditor...', 'saveAsWildcard':'All files (*.*)|*.*|Python scripts (*.py;*.pyw)|*.pyw;*.PY;*.PYW;*.py|Text files (*.txt;*.text)|*.text;*.TXT;*.TEXT;*.txt|HTML and XML files (*.htm;*.html;*.xml)|*.htm;*.xml;*.HTM;*.HTML;*.XML;*.html', 'chars':'chars', 'gotoLine':'Goto line', 'lines':'lines', 'gotoLineNumber':'Goto line number:', 'documentChangedPrompt':'The text in the %s file has changed.\n\nDo you want to save the changes?', 'untitled':'Untitled', 'sample':'codeEditor sample', 'codeEditor':'codeEditor', 'replaced':'Replaced %d occurances', 'words':'words', 'openFile':'Open file', 'scriptletWildcard':'Python files (*.py)|*.py|All Files (*.*)|*.*', 'document':'Document', }, 'components': [ {'type':'Choice', 'name':'popComponentNames', }, {'type':'Choice', 'name':'popComponentEvents', }, {'type':'CodeEditor', 'name':'document', 'position':(0, 0), 'size':(250, 100), }, ] # end components } # end background ] # end backgrounds } }

35.284507

228

0.345042

685

12,526

6.309489

0.370803

0.161037

0.214715

0.053447

0.071726

0.041647

0

0.00737

0.490899

12,526

354

229

35.384181

0.670378

0.003593

0

0.278736

0

0.002874

0.368117

0.046325

0

1

0

true

0

null

0

1

0

null

0

1

0

2

cc126dbbfecd1ff026b9c6b831a847190b8423eb

911

py

Python

unittest_reinvent/diversity_filter_tests/test_murcko_scaffold_superfluous_addition.py

MolecularAI/reinvent-scoring

f7e052ceeffd29e17e1672c33607189873c82a45

[ "MIT" ]

null

unittest_reinvent/diversity_filter_tests/test_murcko_scaffold_superfluous_addition.py

MolecularAI/reinvent-scoring

f7e052ceeffd29e17e1672c33607189873c82a45

[ "MIT" ]

2

2021-11-01T23:19:42.000Z

2021-11-22T23:41:39.000Z

unittest_reinvent/diversity_filter_tests/test_murcko_scaffold_superfluous_addition.py

MolecularAI/reinvent-scoring

f7e052ceeffd29e17e1672c33607189873c82a45

[ "MIT" ]

2

2021-11-18T13:14:22.000Z

2022-03-16T07:52:57.000Z

from reinvent_scoring.scoring.diversity_filters.curriculum_learning.update_diversity_filter_dto import \ UpdateDiversityFilterDTO from unittest_reinvent.diversity_filter_tests.test_murcko_scaffold_base import BaseMurckoScaffoldFilter from unittest_reinvent.diversity_filter_tests.fixtures import tanimoto_scaffold_filter_arrangement from unittest_reinvent.fixtures.test_data import ASPIRIN class TestMurckoScaffoldSuperfluousAddition(BaseMurckoScaffoldFilter): def setUp(self): super().setUp() # try to add a smile already present final_summary = tanimoto_scaffold_filter_arrangement([ASPIRIN], [1.0], [0]) self.update_dto = UpdateDiversityFilterDTO(final_summary, []) def test_superfluous_addition(self): self.scaffold_filter.update_score(self.update_dto) self.assertEqual(2, self.scaffold_filter._diversity_filter_memory.number_of_scaffolds())

45.55

104

0.815587

102

911

6.921569

0.490196

0.084986

0.082153

0.113314

0

0.004988

0.119649

911

19

105

47.947368

0.875312

0.037322

0

0.076923

1

0.153846

false

0

0.307692

0

0.538462

0

null

0

null

0

1

0

1

0

2

0bcce6782aa31e7dd2aa944b38edc0071b4e58f7

847

py

Python

boardgame/connectfour/connectfourviewer.py

suryaambrose/boardgame

459f9ae26ce571d34da88c295eb577b835f3ad13

[ "MIT" ]

null

boardgame/connectfour/connectfourviewer.py

suryaambrose/boardgame

459f9ae26ce571d34da88c295eb577b835f3ad13

[ "MIT" ]

null

boardgame/connectfour/connectfourviewer.py

suryaambrose/boardgame

459f9ae26ce571d34da88c295eb577b835f3ad13

[ "MIT" ]

null

import os import sys from ..gameviewer import GameViewer class ConnectFourViewer(GameViewer): def __init__(self): super(ConnectFourViewer, self).__init__([6,7]) def showState(self, state): os.system("clear") sys.stdout.write("x\y|") for k in range(0, self.map_width): sys.stdout.write("%d "%(k)) sys.stdout.write("\n") for i in range(0, self.map_height): sys.stdout.write(" %d "%(i)) for j in range(0, self.map_width): sys.stdout.write("|") if state._board[i][j] is not None: sys.stdout.write(self.symbol_map[state._board[i][j]]) else: sys.stdout.write(" ") sys.stdout.write("|\n") def waitForAMove(self): while True: try: played_column = raw_input("Type where you wish to play (e.g. 1 for column 1):") c = int(played_column) break except Exception, e: print e return c

25.666667

83

0.654073

133

847

4.037594

0.481203

0.134078

0.208566

0.067039

0.154562

0.126629

0

0.010145

0.18536

847

33

84

25.666667

0.768116

0

0.086085

0

null

0

0.1

null

0.033333

0

null

0

1

0

null

0

1

0

2

0bd3fe284b31a90b04c8a385e5ac021eadf08bd7

577

py

Python

tests/test_article.py

JohnKarima/news-hub

261969fe949bf7efbdc6dabb502b7b9b9eecabac

[ "MIT" ]

null

tests/test_article.py

JohnKarima/news-hub

261969fe949bf7efbdc6dabb502b7b9b9eecabac

[ "MIT" ]

null

tests/test_article.py

JohnKarima/news-hub

261969fe949bf7efbdc6dabb502b7b9b9eecabac

[ "MIT" ]

null

import unittest from app.models import Article class ArticleTest(unittest.TestCase): ''' Test Class to test the behaviour of the Article class ''' def setUp(self): ''' Set up method that will run before every Test ''' self.new_article = Article('NewsDaily', 'NewsDailyTrue','Larry Madowo', 'Hummus...thoughts?','Literally talking about hummus sir','www.newsdaily.net','www.newsdaily.net/picOfHummus6', '2020/2/3', 'lorem gang et all') def test_instance(self): self.assertTrue(isinstance(self.new_article,Article))

33.941176

224

0.679376

73

577

5.328767

0.671233

0.061697

0.071979

0.107969

0

0.015119

0.197574

577

16

225

36.0625

0.825054

0.171577

0

0.359909

0.068337

0

0.142857

1

0.285714

false

0

0.285714

0

0.714286

0

null

0

null

0

1

0

1

0

2

0bd5c6b04b7d3a4ccf8589e0b2129df29191d0f5

737

py

Python

miqa/core/models/image.py

davidshq/miqa-1

aeb5fbf40a65a6fdb82b6e3d3aff8fe47474792f

[ "Apache-2.0" ]

null

miqa/core/models/image.py

davidshq/miqa-1

aeb5fbf40a65a6fdb82b6e3d3aff8fe47474792f

[ "Apache-2.0" ]

null

miqa/core/models/image.py

davidshq/miqa-1

aeb5fbf40a65a6fdb82b6e3d3aff8fe47474792f

[ "Apache-2.0" ]

null

from pathlib import Path from uuid import uuid4 from django.db import models from django_extensions.db.models import TimeStampedModel class Image(TimeStampedModel, models.Model): class Meta: indexes = [models.Index(fields=['scan', 'name'])] ordering = ['name'] id = models.UUIDField(primary_key=True, default=uuid4, editable=False) scan = models.ForeignKey('Scan', related_name='images', on_delete=models.CASCADE) raw_path = models.CharField(max_length=500, blank=False, unique=True) name = models.CharField(max_length=255, blank=False) @property def path(self) -> Path: return Path(self.raw_path) @property def size(self) -> int: return self.path.stat().st_size

29.48

85

0.700136

96

737

5.28125

0.53125

0.039448

0.071006

0.094675

0

0.013289

0.183175

737

24

86

30.708333

0.828904

0

0.111111

0

0.029851

0

1

0.111111

false

0

0.222222

0.111111

0.777778

0

null

0

null

0

1

0

2

0bee95548e6fcafe6a5b00d7403872593616c0ae

11,892

py

Python

src/app/todos/routes.py

alexzanderr/metro.digital

71a58b417f6498808224a6de96578bde76f89c60

[ "MIT" ]

null

src/app/todos/routes.py

alexzanderr/metro.digital

71a58b417f6498808224a6de96578bde76f89c60

[ "MIT" ]

1

2021-12-16T22:11:25.000Z

src/app/todos/routes.py

alexzanderr/flask_web_app

71a58b417f6498808224a6de96578bde76f89c60

[ "MIT" ]

null

""" # type: ignore type ignore is to tell LSP-pyright to ignore the line because something it thinks that there are errors, but actually at runtime there are not """ from .validation import validate_password_check from .validation import validate_email from .validation import validate_password from .validation import validate_username from json import dumps from flask import render_template from flask import Blueprint from flask import request from flask import url_for from flask import redirect # mongo db client stuff from ..mongodb_client import mongodb from ..mongodb_client import CollectionInvalid from ..mongodb_client import ObjectId from ..mongodb_client import collection_exists from ..mongodb_client import get_db_name from ..mongodb_client import collection_create from ..mongodb_client import get_collection from ..mongodb_client import create_or_get_collection from ..routes_utils import json_response from string import ascii_letters, digits from random import choice, randint from datetime import datetime, timedelta import hashlib todos = Blueprint( "todos", __name__, url_prefix="/todos", # not working # template_folder="templates/todos" ) # document template # todo = { # text: 'yeaaah', # timestamp: 1639492801.10111, # datetime: '14.12.2021-16:40:01', # completed: false # } todos_collection_name = "todos" todos_collection = create_or_get_collection(todos_collection_name) # document template # user = { # "username": "alexzander", # "password": "37djw7dh237dh2yudhja1721hg2", # hashed # "eamil": "alexxander18360@gmail.com", # "creation_timestamp": datetime.timestamp(datetime.now()), # "creation_datetime": datetime.now().strftime("%d.%m.%Y-%H:%M:%S") # } users_collection_name = "users" users_collection = create_or_get_collection(users_collection_name) # ('_id', 1)]}, # 'username_1': {'v': 2, 'key': [('username', 1)], 'unique': True}} users_unique_keys = [{ "name": "username", "exists": False }] for _, value in users_collection.index_information().items(): for unique_key in value["key"]: for users_unique_key in users_unique_keys: if unique_key[0] == users_unique_key["name"]: users_unique_key["exists"] = True for users_unique_key in users_unique_keys: if not users_unique_key["exists"]: users_collection.create_index([ (users_unique_key["name"], 1) ], unique=True) register_tokens_collection_name = "register_tokens" register_tokens_collection = create_or_get_collection(register_tokens_collection_name) # ('_id', 1)]}, # 'username_1': {'v': 2, 'key': [('username', 1)], 'unique': True}} tokens_unique_keys = [{ "name": "token", "exists": False }] for _, value in users_collection.index_information().items(): for unique_key in value["key"]: for tokens_unique_key in tokens_unique_keys: if unique_key[0] == tokens_unique_key["name"]: tokens_unique_key["exists"] = True for tokens_unique_key in users_unique_keys: if not tokens_unique_key["exists"]: users_collection.create_index([ (tokens_unique_key["name"], 1) ], unique=True) # users_collection.create_index([("username", 1)], unique=True) @todos.route("/") def todos_root(): # TODO # add authentication with accounts todos_collection = get_collection(todos_collection_name) todo_list = todos_collection.find() return render_template("todos/index.html", todo_list=todo_list) def hash_password(password: str): # deci input pentru sha256 trebuie sa fie bytes return hashlib.sha256(password.encode()).hexdigest() def check_hash_of_password(username: str, password: str): _user = users_collection.find_one({"username": username}) _hashed_password = hash_password(password) return _user["password"] == _hashed_password # type: ignore @todos.route("/login", methods=["GET", "POST"]) def todos_login(): """ Function: todos_login Summary: this function returns a login page with a form Returns: render_template("todos/login.html") """ method = request.method if method == "POST": # then create a new user in database and encrypt # the password # then redirect to /todos based on the content that the user has in todos database # return render_template ? pass else: # GET # if the user is already authenticated # then redirect to /todos page # else # return below return render_template("todos/login.html") @todos.route("/mongo/add", methods=["POST"]) def mongo_add(): todos_collection.insert_one({ "text": request.form["text"], "timestamp": datetime.timestamp(datetime.now()), "datetime": datetime.now().strftime("%d.%m.%Y-%H:%M:%S"), "completed": False }) # return dict(todo), { # "Refresh": "1; url={}".format(url_for("todos")) # } return redirect("/todos") @todos.route("/mongo/complete/<oid>") def mongo_complete(oid): requested_todo = todos_collection.find_one({ "_id": ObjectId(oid) }) completed = True if requested_todo["completed"]: # type: ignore completed = False todos_collection.update_one( requested_todo, {"$set": {"completed": completed}}) # todos_collection.replace_one(requested_todo, {"something": "else"}) # 61b6247e165b109454a32c1b # 61b6247e165b109454a32c1b return redirect("/todos") @todos.route("/mongo/delete/<oid>") def mongo_delete(oid): requested_todo = todos_collection.find_one({ "_id": ObjectId(oid) }) todos_collection.delete_one(requested_todo) return redirect(url_for("todos")) @todos.route('/mongo/delete/all') def mongo_delete_all(): todos_collection.delete_many({}) return redirect(url_for('todos')) # @todos.route("/", methods=['POST']) # @todos.route("/<component_name>", methods=['POST']) # def graphql_query(component_name="app"): # return str(component_name) todos_api = Blueprint( "todos_api", __name__, url_prefix="/todos/api") @todos_api.route("/") def todos_api_root(): return {"message": "salutare"}, 200 @todos_api.route("/mongo/add", methods=["POST"]) def todos_api_mongo_add(): json_from_request = request.get_json() todo = { "text": json_from_request["text"], # type: ignore "timestamp": datetime.timestamp(datetime.now()), "datetime": datetime.now().strftime("%d.%m.%Y-%H:%M:%S"), "completed": False } todos_collection.insert_one(todo) # the above function insert a _id key todo["oid"] = str(todo["_id"]) del todo["_id"] return json_response(todo, 200) # PATCH request # The PATCH method applies partial modifications to a resource # meaning that in this case partial mods are todo completed == true @todos_api.route("/mongo/complete/<oid>", methods=["PATCH"]) def todos_api_mongo_complete(oid): requested_todo = todos_collection.find_one({ "_id": ObjectId(oid) }) completed = True if requested_todo["completed"]: # type: ignore completed = False todos_collection.update_one( requested_todo, {"$set": {"completed": completed}} ) requested_todo["oid"] = str(requested_todo["_id"]) # type: ignore requested_todo["completed"] = completed # type: ignore del requested_todo["_id"] # type: ignore return json_response(requested_todo, 200) # type: ignore # TODO add the oid in the post data body # instead of making it an url, so that no one can see # te oid @todos_api.route("/mongo/delete/<oid>", methods=["DELETE"]) def todos_api_mongo_delete(oid): requested_todo = todos_collection.find_one({ "_id": ObjectId(oid) }) todos_collection.delete_one(requested_todo) requested_todo["oid"] = str(requested_todo["_id"]) # type: ignore del requested_todo["_id"] # type: ignore return json_response(requested_todo, 200) # type: ignore def generate_random_register_token(): return "".join([choice(ascii_letters + digits) for _ in range(30)]) def get_new_register_token(): """ Function: get_new_token() Summary: gets new token based on whats in the db Returns: new token that is not the database """ brand_new_token = generate_random_register_token() while register_tokens_collection.find_one({"token": brand_new_token}): brand_new_token = generate_random_register_token() return brand_new_token @todos.route("/register", methods=["GET", "POST"]) def todos_register(): method = request.method if method == "POST": # then create a new user in database and encrypt # the password # then redirect to /todos based on the content that the user has in todos database # return render_template ? # get data and token from request data body json_from_request: dict = request.get_json() # type: ignore username = json_from_request["username"] email = json_from_request["email"] password = json_from_request["password"] password_check = json_from_request["password_check"] remember_me = json_from_request["remember_me"] register_token = json_from_request["register_token"] if not register_tokens_collection.find_one({"token": register_token}): return { "message": "cannot register, register token is not database" }, 403 users_collection.insert_one({ "username": username, "password": hash_password(password), # hashed "email": email, "creation_timestamp": datetime.timestamp(datetime.now()), "creation_datetime": datetime.now().strftime("%d.%m.%Y-%H:%M:%S") }) # you can redirect from POST request sorry # and you can render HTML from here because you # are making the request from ajax, not from firefox return {"message": "success", "redirectTo": "/todos"}, 200 # or you can redirect to login page # or you can automatically login the user after registration else: # GET # if the user is already authenticated # then redirect to /todos page # else # return below return render_template("todos/register.html") @todos_api.post("/register/validation") def todos_api_register(): """ Function: todos_api_register Returns: json with validated input """ json_from_request: dict = request.get_json() # type: ignore username = json_from_request["username"] email = json_from_request["email"] password = json_from_request["password"] password_check = json_from_request["password_check"] remember_me = json_from_request["remember_me"] # some examples results = { "username": validate_username(username), "password": validate_password(password), "email": validate_email(email), "password_check": validate_password_check(password, password_check), "register_token": None } all_passed = True for k, v in results.items(): if k != "register_token" and not v["passed"]: all_passed = False break if all_passed: new_token = get_new_register_token() results["register_token"] = new_token register_tokens_collection.insert_one({ "token": new_token, "expiration_timestamp": datetime.timestamp(datetime.now() + timedelta(minutes=2)) }) # TODO add check for username in database return json_response(results, 200) # return { # "username": username, # "email": email, # "password": password, # "password_check": password_check, # "remember_me": remember_me # }, 200

30.414322

93

0.670114

1,451

11,892

5.248794

0.168849

0.034139

0.029543

0.02416

0.464154

0.389049

0.353072

0.32261

0.318146

0.298845

0

0.013751

0.21115

11,892

390

94

30.492308

0.798103

0.255466

0

0.354839

0

0.116357

0.004848

0

0.017949

0

1

0.073733

false

0.087558

0.105991

0.013825

0.262673

0.013825

0

null

0

null

0

1

0

1

0

2

0bff94692e4bbe3d3e04ebd669ece2fd2be0847b

489

py

Python

nrm_django/nrm_site/settings/test.py

18F/NRM-Grants-Agreements

7b9016e034b75a2237f7c70ba539b542108c335e

[ "CC0-1.0" ]

5

2020-11-18T20:00:02.000Z

2021-04-16T23:50:07.000Z

nrm_django/nrm_site/settings/test.py

USDAForestService/NRM-Grants-Agreements

7b9016e034b75a2237f7c70ba539b542108c335e

[ "CC0-1.0" ]

210

2021-04-28T16:26:34.000Z

2022-03-14T16:31:21.000Z

nrm_django/nrm_site/settings/test.py

USDAForestService/NRM-Grants-Agreements

7b9016e034b75a2237f7c70ba539b542108c335e

[ "CC0-1.0" ]

2

2021-07-06T20:57:27.000Z

2021-07-07T13:06:46.000Z

import os from .base import * # noqa import dj_database_url SECRET_KEY = "test mode" database_url = os.getenv("DATABASE_URL") if database_url: DATABASES = {"default": dj_database_url.parse(database_url)} else: DATABASES = { "default": { "ENGINE": "django.db.backends.postgresql", "NAME": "nrm_test", "HOST": "postgres", "PORT": "5432", "USER": "postgres", "PASSWORD": "postgres", } }

21.26087

64

0.554192

50

489

5.22

0.62

0.252874

0.099617

0

0.01173

0.302658

489

22

65

22.227273

0.753666

0.00818

0

0.269151

0.060041

0

1

0

false

0.055556

0.166667

0

0.166667

0

null

1

0

null

0

1

0

2

042a1dff477ec006dda477d8738dfe23bcc7b467

9,358

py

Python

modules.py

callistachang/CycleGAN-Music-Transfer

928e87b4bebc4da1dcf7c43936d2c10fe76170f1

[ "MIT" ]

null

modules.py

callistachang/CycleGAN-Music-Transfer

928e87b4bebc4da1dcf7c43936d2c10fe76170f1

[ "MIT" ]

1

2021-07-07T13:36:18.000Z

modules.py

callistachang/CycleGAN-Music-Transfer

928e87b4bebc4da1dcf7c43936d2c10fe76170f1

[ "MIT" ]

null

import numpy as np import tensorflow as tf from tensorflow.keras import Model, layers, Input from collections import namedtuple def abs_criterion(pred, target): return tf.reduce_mean(tf.abs(pred - target)) def mae_criterion(pred, target): return tf.reduce_mean((pred - target) ** 2) def sce_criterion(logits, labels): return tf.reduce_mean( tf.nn.sigmoid_cross_entropy_with_logits(logits=logits, labels=labels) ) def softmax_criterion(logits, labels): return tf.reduce_mean( tf.nn.softmax_cross_entropy_with_logits(logits=logits, labels=labels) ) def padding(x, p=3): return tf.pad(x, [[0, 0], [p, p], [p, p], [0, 0]], "REFLECT") class InstanceNorm(layers.Layer): def __init__(self, input_shape): super(InstanceNorm, self).__init__() self.scale = tf.Variable( initial_value=np.random.normal(1.0, 0.02, input_shape), trainable=True, name="SCALE", dtype=tf.float32, ) self.offset = tf.Variable( initial_value=np.zeros(input_shape), trainable=True, name="OFFSET", dtype=tf.float32, ) def call(self, x, epsilon=1e-5): mean, variance = tf.nn.moments(x, axes=[1, 2], keepdims=True) inv = tf.math.rsqrt(variance + epsilon) normalized = (x - mean) * inv return self.scale * normalized + self.offset class Padding(layers.Layer): def __init__(self): super(Padding, self).__init__() def call(self, x, p=3): return tf.pad(x, [[0, 0], [p, p], [p, p], [0, 0]], "REFLECT") class ResNetBlock(layers.Layer): def __init__(self): super(ResNetBlock, self).__init__() def call(self, x, dim, k_init, ks=3, s=1): p = (ks - 1) // 2 # For ks = 3, p = 1 y = layers.Lambda(padding, arguments={"p": p}, name="PADDING_1")(x) # After first padding, (batch * 130 * 130 * 3) y = layers.Conv2D( filters=dim, kernel_size=ks, strides=s, padding="valid", kernel_initializer=k_init, use_bias=False, )(y) y = InstanceNorm(y.shape[-1:])(y) y = layers.ReLU()(y) # After first conv2d, (batch * 128 * 128 * 3) y = layers.Lambda(padding, arguments={"p": p}, name="PADDING_2")(y) # After second padding, (batch * 130 * 130 * 3) y = layers.Conv2D( filters=dim, kernel_size=ks, strides=s, padding="valid", kernel_initializer=k_init, use_bias=False, )(y) y = InstanceNorm(y.shape[-1:])(y) y = layers.ReLU()(y + x) # After second conv2d, (batch * 128 * 128 * 3) return y # def instance_norm(x, epsilon=1e-5): # scale = tf.Variable( # initial_value=np.random.normal(1.0, 0.02, x.shape[-1:]), # trainable=True, # name="SCALE", # dtype=tf.float32, # ) # offset = tf.Variable( # initial_value=np.zeros(x.shape[-1:]), # trainable=True, # name="OFFSET", # dtype=tf.float32, # ) # mean, variance = tf.nn.moments(x, axes=[1, 2], keepdims=True) # inv = tf.math.rsqrt(variance + epsilon) # normalized = (x - mean) * inv # return scale * normalized + offset def build_discriminator(options, name="Discriminator"): initializer = tf.random_normal_initializer(0.0, 0.02) inputs = Input(shape=(options.time_step, options.pitch_range, options.output_nc)) x = inputs x = layers.Conv2D( filters=options.df_dim, kernel_size=7, strides=2, padding="same", kernel_initializer=initializer, use_bias=False, name="CONV2D_1", )(x) x = layers.LeakyReLU(alpha=0.2)(x) # (batch * 32 * 42 * 64) x = layers.Conv2D( filters=options.df_dim * 4, kernel_size=7, strides=2, padding="same", kernel_initializer=initializer, use_bias=False, name="CONV2D_2", )(x) x = InstanceNorm(x.shape[-1:])(x) x = layers.LeakyReLU(alpha=0.2)(x) # (batch * 16 * 21 * 256) x = layers.Conv2D( filters=1, kernel_size=7, strides=1, padding="same", kernel_initializer=initializer, use_bias=False, name="CONV2D_3", )(x) # (batch * 16 * 21 * 1) outputs = x return Model(inputs=inputs, outputs=outputs, name=name) def build_generator(options, name="Generator"): initializer = tf.random_normal_initializer(0.0, 0.02) inputs = Input(shape=(options.time_step, options.pitch_range, options.output_nc)) x = inputs # (batch * 64 * 84 * 1) x = layers.Lambda(padding, name="PADDING_1")(x) # (batch * 70 * 90 * 1) x = layers.Conv2D( filters=options.gf_dim, kernel_size=7, strides=1, padding="valid", kernel_initializer=initializer, use_bias=False, name="CONV2D_1", )(x) x = InstanceNorm(x.shape[-1:])(x) x = layers.ReLU()(x) # (batch * 64 * 84 * 64) x = layers.Conv2D( filters=options.gf_dim * 2, kernel_size=3, strides=2, padding="same", kernel_initializer=initializer, use_bias=False, name="CONV2D_2", )(x) x = InstanceNorm(x.shape[-1:])(x) x = layers.ReLU()(x) # (batch * 32 * 42 * 128) x = layers.Conv2D( filters=options.gf_dim * 4, kernel_size=3, strides=2, padding="same", kernel_initializer=initializer, use_bias=False, name="CONV2D_3", )(x) x = InstanceNorm(x.shape[-1:])(x) x = layers.ReLU()(x) # (batch * 16 * 21 * 256) for i in range(10): # x = resnet_block(x, options.gf_dim * 4) x = ResNetBlock()(x, options.gf_dim * 4, initializer) # (batch * 16 * 21 * 256) x = layers.Conv2DTranspose( filters=options.gf_dim * 2, kernel_size=3, strides=2, padding="same", kernel_initializer=initializer, use_bias=False, name="DECONV2D_1", )(x) x = InstanceNorm(x.shape[-1:])(x) x = layers.ReLU()(x) # (batch * 32 * 42 * 128) x = layers.Conv2DTranspose( filters=options.gf_dim, kernel_size=3, strides=2, padding="same", kernel_initializer=initializer, use_bias=False, name="DECONV2D_2", )(x) x = InstanceNorm(x.shape[-1:])(x) x = layers.ReLU()(x) # (batch * 64 * 84 * 64) x = layers.Lambda(padding, name="PADDING_2")(x) # After padding, (batch * 70 * 90 * 64) x = layers.Conv2D( filters=options.output_nc, kernel_size=7, strides=1, padding="valid", kernel_initializer=initializer, activation="sigmoid", use_bias=False, name="CONV2D_4", )(x) # (batch * 64 * 84 * 1) outputs = x return Model(inputs=inputs, outputs=outputs, name=name) def build_discriminator_classifier(options, name="Discriminator_Classifier"): initializer = tf.random_normal_initializer(0.0, 0.02) inputs = Input(shape=(options.time_step, options.pitch_range, options.output_nc)) x = inputs # (batch * 64, 84, 1) x = layers.Conv2D( filters=options.df_dim, kernel_size=[1, 12], strides=[1, 12], padding="same", kernel_initializer=initializer, use_bias=False, name="CONV2D_1", )(x) x = layers.LeakyReLU(alpha=0.2)(x) # (batch * 64 * 7 * 64) x = layers.Conv2D( filters=options.df_dim * 2, kernel_size=[4, 1], strides=[4, 1], padding="same", kernel_initializer=initializer, use_bias=False, name="CONV2D_2", )(x) x = InstanceNorm(x.shape[-1:])(x) x = layers.LeakyReLU(alpha=0.2)(x) # (batch * 16 * 7 * 128) x = layers.Conv2D( filters=options.df_dim * 4, kernel_size=[2, 1], strides=[2, 1], padding="same", kernel_initializer=initializer, use_bias=False, name="CONV2D_3", )(x) x = InstanceNorm(x.shape[-1:])(x) x = layers.LeakyReLU(alpha=0.2)(x) # (batch * 8 * 7 * 256) x = layers.Conv2D( filters=options.df_dim * 8, kernel_size=[8, 1], strides=[8, 1], padding="same", kernel_initializer=initializer, use_bias=False, name="CONV2D_4", )(x) x = InstanceNorm(x.shape[-1:])(x) x = layers.LeakyReLU(alpha=0.2)(x) # (batch * 1 * 7 * 512) x = layers.Conv2D( filters=2, kernel_size=[1, 7], strides=[1, 7], padding="same", kernel_initializer=initializer, use_bias=False, name="CONV2D_5", )(x) # (batch * 1 * 1 * 2) x = tf.reshape(x, [-1, 2]) # (batch * 2) outputs = x return Model(inputs=inputs, outputs=outputs, name=name) if __name__ == "__main__": OPTIONS = namedtuple( "OPTIONS", "batch_size " "time_step " "input_nc " "output_nc " "pitch_range " "gf_dim " "df_dim ", ) options = OPTIONS._make((128, 64, 1, 1, 84, 64, 64)) model = build_generator(options) print(model.summary())

25.498638

85

0.556315

1,179

9,358

4.272265

0.124682

0.037522

0.038118

0.044471

0.797499

0.771491

0.725829

0.633313

0.626166

0.559659

0

0.051493

0.298568

9,358

366

86

25.568306

0.715874

0.131545

0

0.666667

0

0.047136

0.002969

0

1

0.054902

false

0

0.015686

0.023529

0.12549

0.003922

0

null

0

1

0

null

0

2

0436d3f10986a9986bb88f66529f9631838fc465

295

py

Python

class2/demo3.py

sanderslhc/python-learing

2769f72c9b6de24d768175bed1aa9851d0469d19

[ "MIT" ]

1

2021-07-20T09:52:55.000Z

class2/demo3.py

sanderslhc/python-learning

2769f72c9b6de24d768175bed1aa9851d0469d19

[ "MIT" ]

null

class2/demo3.py

sanderslhc/python-learning

2769f72c9b6de24d768175bed1aa9851d0469d19

[ "MIT" ]

null

#多分支结构 score=int(input('请输入成绩')) #判断 if score>=90 and score<=100: print('A') elif score>=80 and score<=89: print('B') elif score>=70 and score<=79: print('C') elif score>=60 and score<=69: print('D') elif score>=0 and score<=59: print('E') else: print('无效')

19.666667

30

0.572881

49

295

3.44898

0.55102

0.236686

0

0.087719

0.227119

295

15

31

19.666667

0.653509

0.023729

0

0.043956

0

1

0

false

0

0.461538

0

null

1

0

null

0

1

0

2

0447af988a6ba77384680fe4e01e6a7e24dba0af

2,253

py

Python

src/ch3/generatefeedvector.py

amolnayak311/Programming-Collective-Intelligence

eaa55c3989a8d36e7b766fbaba267b4cbaedf5be

[ "Apache-2.0" ]

null

src/ch3/generatefeedvector.py

amolnayak311/Programming-Collective-Intelligence

eaa55c3989a8d36e7b766fbaba267b4cbaedf5be

[ "Apache-2.0" ]

null

src/ch3/generatefeedvector.py

amolnayak311/Programming-Collective-Intelligence

eaa55c3989a8d36e7b766fbaba267b4cbaedf5be

[ "Apache-2.0" ]

null

''' Created on Sep 4, 2015 @author: Amol ''' from feedparser import parse import re from itertools import groupby #Remove HTML and get the remaining words def getwords(html): txt = re.compile(r'<[^>]+>').sub('', html) words = re.compile(r'[^A-Z^a-z]+').split(txt) return [word.lower() for word in words if word != ''] #Short implementation to count words, however, the performance is not something I have benchmarked #As this includesm sort, groupby and len(list(group)) def getwordcounts(url): d = parse(url) print "Getting feed from URL %s" % url feed_map = d['feed'] if 'title' in feed_map: res = [getwords(e['title'] + ' ' + e['summary' if 'summary' in e else 'description']) for e in d['entries']] word_count_map = dict((key, len(list(group))) for key, group in groupby(sorted([word for l in res for word in l]))) return feed_map['title'], word_count_map else: print "Warn: Unable to access data from feed %s" % url #Special handling for some URLs not found or Forbidden return 'NA', {} # TODO: Clean implementation of the following code # TODO: Experiment using Stopword filters apcount = {} wordcount = {} feedlist = 0 for feedurl in file('feedlist.txt'): title, wc = getwordcounts(feedurl) if title != 'NA' and len(wc) > 0: feedlist += 1 wordcount[title] = wc for word, count in wc.items(): apcount.setdefault(word, 0) if count > 1: apcount[word] += 1 print "Retrieved and parsed all words from the List of Blogs" wordlist = [] for w,bc in apcount.items(): frac = float(bc) / float(feedlist) if frac > 0.1 and frac < 0.5: wordlist.append(w) print "Writing to blogdata.txt" out = file('blogdata.txt', 'w') out.write('Blog') for word in wordlist: out.write('\t%s'% word) out.write('\n') for blog, wc in wordcount.items(): out.write(blog) for word in wordlist: word_count = wc[word] if word in wc else 0 out.write("\t%d" % word_count) out.write("\n") out.close() print "Successfully written to blogdata.txt" #Note that the output generated will not match the one given by the author. Some of the URLs dont even work now

31.732394

127

0.637816

341

2,253

4.187683

0.407625

0.033613

0.02521

0.021008

0.040616

0

0.009308

0.237017

2,253

71

128

31.732394

0.821408

0.195739

0

0.165247

0

0.014085

0

null

0

0.0625

null

0.104167

0

null

0

null

0

1

0

1

0

2

044bb9506b68dc9263b143fd71b62d2aa484539b

10,954

py

Python

0.17/_downloads/8c453dbbabf4b225611c41642ea9b1d5/plot_morph_stc.py

drammock/mne-tools.github.io

5d3a104d174255644d8d5335f58036e32695e85d

[ "BSD-3-Clause" ]

null

0.17/_downloads/8c453dbbabf4b225611c41642ea9b1d5/plot_morph_stc.py

drammock/mne-tools.github.io

5d3a104d174255644d8d5335f58036e32695e85d

[ "BSD-3-Clause" ]

null

0.17/_downloads/8c453dbbabf4b225611c41642ea9b1d5/plot_morph_stc.py

drammock/mne-tools.github.io

5d3a104d174255644d8d5335f58036e32695e85d

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- r""" ================================================================ Morphing source estimates: Moving data from one brain to another ================================================================ Morphing refers to the operation of transferring :ref:`source estimates <sphx_glr_auto_tutorials_plot_object_source_estimate.py>` from one anatomy to another. It is commonly referred as realignment in fMRI literature. This operation is necessary for group studies as one needs then data in a common space. In this tutorial we will morph different kinds of source estimation results between individual subject spaces using :class:`mne.SourceMorph` object. We will use precomputed data and morph surface and volume source estimates to a reference anatomy. The common space of choice will be FreeSurfer's 'fsaverage' See :ref:`sphx_glr_auto_tutorials_plot_background_freesurfer.py` for more information. Method used for cortical surface data in based on spherical registration [1]_ and Symmetric Diffeomorphic Registration (SDR) for volumic data [2]_. Furthermore we will convert our volume source estimate into a NIfTI image using :meth:`morph.apply(..., output='nifti1') <mne.SourceMorph.apply>`. In order to morph :class:`labels <mne.Label>` between subjects allowing the definition of labels in a one brain and transforming them to anatomically analogous labels in another use :func:`mne.Label.morph`. .. contents:: :local: Why morphing? ============= Modern neuroimaging techniques, such as source reconstruction or fMRI analyses, make use of advanced mathematical models and hardware to map brain activity patterns into a subject specific anatomical brain space. This enables the study of spatio-temporal brain activity. The representation of spatio-temporal brain data is often mapped onto the anatomical brain structure to relate functional and anatomical maps. Thereby activity patterns are overlaid with anatomical locations that supposedly produced the activity. Anatomical MR images are often used as such or are transformed into an inflated surface representations to serve as "canvas" for the visualization. In order to compute group level statistics, data representations across subjects must be morphed to a common frame, such that anatomically and functional similar structures are represented at the same spatial location for *all subjects equally*. Since brains vary, morphing comes into play to tell us how the data produced by subject A, would be represented on the brain of subject B. See also this :ref:`tutorial on surface source estimation <sphx_glr_auto_tutorials_plot_mne_solutions.py>` or this :ref:`example on volumetric source estimation <sphx_glr_auto_examples_inverse_plot_compute_mne_inverse_volume.py>`. Morphing **volume** source estimates ==================================== A volumetric source estimate represents functional data in a volumetric 3D space. The difference between a volumetric representation and a "mesh" ( commonly referred to as "3D-model"), is that the volume is "filled" while the mesh is "empty". Thus it is not only necessary to morph the points of the outer hull, but also the "content" of the volume. In MNE-Python, volumetric source estimates are represented as :class:`mne.VolSourceEstimate`. The morph was successful if functional data of Subject A overlaps with anatomical data of Subject B, in the same way it does for Subject A. Setting up :class:`mne.SourceMorph` for :class:`mne.VolSourceEstimate` ---------------------------------------------------------------------- Morphing volumetric data from subject A to subject B requires a non-linear registration step between the anatomical T1 image of subject A to the anatomical T1 image of subject B. MNE-Python uses the Symmetric Diffeomorphic Registration [2]_ as implemented in dipy_ [3]_ (See `tutorial <http://nipy.org/dipy/examples_built/syn_registration_3d.html>`_ from dipy_ for more details). :class:`mne.SourceMorph` uses segmented anatomical MR images computed using :ref:`FreeSurfer <sphx_glr_auto_tutorials_plot_background_freesurfer.py>` to compute the transformations. In order tell SourceMorph which MRIs to use, ``subject_from`` and ``subject_to`` need to be defined as the name of the respective folder in FreeSurfer's home directory. See :ref:`sphx_glr_auto_examples_inverse_plot_morph_volume_stc.py` usage and for more details on: - How to create a SourceMorph object for volumetric data - Apply it to VolSourceEstimate - Get the output is NIfTI format - Save a SourceMorph object to disk Morphing **surface** source estimates ===================================== A surface source estimate represents data relative to a 3-dimensional mesh of the cortical surface computed using FreeSurfer. This mesh is defined by its vertices. If we want to morph our data from one brain to another, then this translates to finding the correct transformation to transform each vertex from Subject A into a corresponding vertex of Subject B. Under the hood :ref:`FreeSurfer <sphx_glr_auto_tutorials_plot_background_freesurfer.py>` uses spherical representations to compute the morph, as relies on so called *morphing maps*. The morphing maps ----------------- The MNE software accomplishes morphing with help of morphing maps which can be either computed on demand or precomputed. The morphing is performed with help of the registered spherical surfaces (``lh.sphere.reg`` and ``rh.sphere.reg`` ) which must be produced in FreeSurfer. A morphing map is a linear mapping from cortical surface values in subject A (:math:`x^{(A)}`) to those in another subject B (:math:`x^{(B)}`) .. math:: x^{(B)} = M^{(AB)} x^{(A)}\ , where :math:`M^{(AB)}` is a sparse matrix with at most three nonzero elements on each row. These elements are determined as follows. First, using the aligned spherical surfaces, for each vertex :math:`x_j^{(B)}`, find the triangle :math:`T_j^{(A)}` on the spherical surface of subject A which contains the location :math:`x_j^{(B)}`. Next, find the numbers of the vertices of this triangle and set the corresponding elements on the *j* th row of :math:`M^{(AB)}` so that :math:`x_j^{(B)}` will be a linear interpolation between the triangle vertex values reflecting the location :math:`x_j^{(B)}` within the triangle :math:`T_j^{(A)}`. It follows from the above definition that in general .. math:: M^{(AB)} \neq (M^{(BA)})^{-1}\ , *i.e.*, .. math:: x_{(A)} \neq M^{(BA)} M^{(AB)} x^{(A)}\ , even if .. math:: x^{(A)} \approx M^{(BA)} M^{(AB)} x^{(A)}\ , *i.e.*, the mapping is *almost* a bijection. Morphing maps can be computed on the fly or read with :func:`mne.read_morph_map`. Precomputed maps are located in ``$SUBJECTS_DIR/morph-maps``. The names of the files in ``$SUBJECTS_DIR/morph-maps`` are of the form: <*A*> - <*B*> -``morph.fif`` , where <*A*> and <*B*> are names of subjects. These files contain the maps for both hemispheres, and in both directions, *i.e.*, both :math:`M^{(AB)}` and :math:`M^{(BA)}`, as defined above. Thus the files <*A*> - <*B*> -``morph.fif`` or <*B*> - <*A*> -``morph.fif`` are functionally equivalent. The name of the file produced depends on the role of <*A*> and <*B*> in the analysis. About smoothing --------------- The current estimates are normally defined only in a decimated grid which is a sparse subset of the vertices in the triangular tessellation of the cortical surface. Therefore, any sparse set of values is distributed to neighboring vertices to make the visualized results easily understandable. This procedure has been traditionally called smoothing but a more appropriate name might be smudging or blurring in accordance with similar operations in image processing programs. In MNE software terms, smoothing of the vertex data is an iterative procedure, which produces a blurred image :math:`x^{(N)}` from the original sparse image :math:`x^{(0)}` by applying in each iteration step a sparse blurring matrix: .. math:: x^{(p)} = S^{(p)} x^{(p - 1)}\ . On each row :math:`j` of the matrix :math:`S^{(p)}` there are :math:`N_j^{(p - 1)}` nonzero entries whose values equal :math:`1/N_j^{(p - 1)}`. Here :math:`N_j^{(p - 1)}` is the number of immediate neighbors of vertex :math:`j` which had non-zero values at iteration step :math:`p - 1`. Matrix :math:`S^{(p)}` thus assigns the average of the non-zero neighbors as the new value for vertex :math:`j`. One important feature of this procedure is that it tends to preserve the amplitudes while blurring the surface image. Once the indices non-zero vertices in :math:`x^{(0)}` and the topology of the triangulation are fixed the matrices :math:`S^{(p)}` are fixed and independent of the data. Therefore, it would be in principle possible to construct a composite blurring matrix .. math:: S^{(N)} = \prod_{p = 1}^N {S^{(p)}}\ . However, it turns out to be computationally more effective to do blurring with an iteration. The above formula for :math:`S^{(N)}` also shows that the smudging (smoothing) operation is linear. From theory to practice ----------------------- In MNE-Python, surface source estimates are represented as :class:`mne.SourceEstimate` or :class:`mne.VectorSourceEstimate`. Those can be used together with :class:`mne.SourceSpaces` or without. The morph was successful if functional data of Subject A overlaps with anatomical surface data of Subject B, in the same way it does for Subject A. See :ref:`sphx_glr_auto_examples_inverse_plot_morph_surface_stc.py` usage and for more details: - How to create a :class:`mne.SourceMorph` object using :func:`mne.compute_source_morph` for surface data - Apply it to :class:`mne.SourceEstimate` or :class:`mne.VectorSourceEstimate` - Save a :class:`mne.SourceMorph` object to disk Please see also Gramfort *et al.* (2013) [4]_. References ========== .. [1] Greve D. N., Van der Haegen L., Cai Q., Stufflebeam S., Sabuncu M. R., Fischl B., Brysbaert M. A Surface-based Analysis of Language Lateralization and Cortical Asymmetry. Journal of Cognitive Neuroscience 25(9), 1477-1492, 2013. .. [2] Avants, B. B., Epstein, C. L., Grossman, M., & Gee, J. C. (2009). Symmetric Diffeomorphic Image Registration with Cross- Correlation: Evaluating Automated Labeling of Elderly and Neurodegenerative Brain, 12(1), 26-41. .. [3] Garyfallidis E, Brett M, Amirbekian B, Rokem A, van der Walt S, Descoteaux M, Nimmo-Smith I and Dipy Contributors (2014). DIPY, a library for the analysis of diffusion MRI data. Frontiers in Neuroinformatics, vol.8, no.8. .. [4] Gramfort A., Luessi M., Larson E., Engemann D. A., Strohmeier D., Brodbeck C., Goj R., Jas. M., Brooks T., Parkkonen L. & Hämäläinen, M. (2013). MEG and EEG data analysis with MNE-Python. Frontiers in neuroscience, 7, 267. .. _dipy: http://nipy.org/dipy/ """ # noqa: E501

43.125984

80

0.726675

1,673

10,954

4.705918

0.304244

0.010161

0.011177

0.012702

0.142512

0.117363

0.088657

0.059698

0.053855

0.04344

0

0.00799

0.154464

10,954

253

81

43.296443

0.842043

0.998722

0

1

0

true

0

null

0

1

0

null

0

1

0

2

0453131e08ad9df3feb4129ffbeb4612445ebb21

763

py

Python

analysis/dbase/tracking/train.py

BrancoLab/FC_analysis

7124a7d998275bce6f7a18c264399c7dabfd430b

[ "MIT" ]

1

2018-08-20T14:47:09.000Z

analysis/dbase/tracking/train.py

BrancoLab/FC_analysis

7124a7d998275bce6f7a18c264399c7dabfd430b

[ "MIT" ]

null

analysis/dbase/tracking/train.py

BrancoLab/FC_analysis

7124a7d998275bce6f7a18c264399c7dabfd430b

[ "MIT" ]

1

2018-09-24T15:58:57.000Z

import deeplabcut as dlc import os from fcutils.file_io.utils import listdir # from fcutils.video.utils import trim_clip config_file = 'D:\\Dropbox (UCL - SWC)\\Rotation_vte\\Locomotion\\dlc\\locomotion-Federico\\config.yaml' dlc.train_network(config_file) # fld = 'D:\\Dropbox (UCL - SWC)\\Rotation_vte\\Locomotion\\dlc' # vids = [os.path.join(fld, '200203_CA8493_video_trim.mp4'), os.path.join(fld, '200204_CA8491_video_trim.mp4'), os.path.join(fld, '200204_CA8494_video_trim.mp4')] # dlc.extract_outlier_frames(config_file, vids, epsilon=40) # dlc.merge_datasets(config_file) # vids = [f for f in listdir(fld) if f.endswith('.mp4')] # for vid in vids: # savepath = vid.split(".")[0]+'_trim.mp4' # trim_clip(vid, savepath, start=0.25, stop=0.35)

34.681818

162

0.728702

121

763

4.404959

0.46281

0.075047

0.056285

0.073171

0.258912

0

0.064706

0.108781

763

22

163

34.681818

0.719118

0.686763

0

0.2

0.382609

0.3

0

1

0

false

0

0.6

0

0.6

0

null

0

null

0

1

0

1

0

2

f08b09f830197b622c222148be38b3159d8bff5d

6,346

py

Python

src/experimental_results/outdoor test/path_planning_analysis.py

NASLab/GroundROS

6673db009ffcff59500eb1e3d5873111282e7749

[ "MIT" ]

1

2017-12-17T11:11:55.000Z

src/experimental_results/outdoor test/path_planning_analysis.py

NASLab/GroundROS

6673db009ffcff59500eb1e3d5873111282e7749

[ "MIT" ]

2

2015-10-02T19:02:06.000Z

2015-10-02T19:02:36.000Z

src/experimental_results/outdoor test/path_planning_analysis.py

NASLab/GroundROS

6673db009ffcff59500eb1e3d5873111282e7749

[ "MIT" ]

null

# python experimental tests for Husky from numpy import sin, cos, pi, load import matplotlib.pyplot as plt from time import sleep yaw_bound = 2 * pi / 180 yaw_calibrate = pi / 180 * (0) x_offset_calibrate = 0 y_offset_calibrate = -.08 f0 = plt.figure() ax0 = f0.add_subplot(111) ax1 = f0.add_subplot(111) env_data = load('loginfo2.npy')[1:] x = [[]] * len(env_data) y = [[]] * len(env_data) m=2 # print len(env_data) for i in range(m, len(env_data) - m): if len(env_data[i]) > 0: x[i] = env_data[i][0] y[i] = env_data[i][1] print i, x[i], y[i] yaw = env_data[i][2] # filter some of the readings; comment to see the effect if len(env_data[i + m]) == 0 or abs(yaw - env_data[i - m][2]) > yaw_bound or abs(yaw - env_data[i + m][2]) > yaw_bound: continue readings = env_data[i][3] readings_x = [[]] * len(readings) readings_y = [[]] * len(readings) k = 0 for j in range(len(readings)): # lidar readings in lidar frame x_temp = readings[j][0] * cos(-readings[j][1]) y_temp = readings[j][0] * sin(-readings[j][1]) # lidar readings in robot frame x_temp2 = x_temp * \ cos(yaw_calibrate) - y_temp * \ sin(yaw_calibrate) + x_offset_calibrate y_temp2 = y_temp * \ cos(yaw_calibrate) + x_temp * \ sin(yaw_calibrate) + y_offset_calibrate # lidar readings in global frame readings_x[k] = x_temp2 * cos(yaw) - y_temp2 * sin(yaw) + x[i] readings_y[k] = y_temp2 * cos(yaw) + x_temp2 * sin(yaw) + y[i] k += 1 ax0.plot(readings_x, readings_y, 'r.') ax0.plot(x[i],y[i], 'go', lw=3) ax0.plot(0,-10,'ko') ax0.set_xlim([-50, 50]) ax0.set_ylim([-50, 50]) # ax0.axis('equal') plt.draw() plt.pause(.0001) ax0.clear() ax0.plot([], [], 'r.', label='Lidar Reading') # env_data = load('planner_of_agent_0.npy')[1:] # x = [[]] * len(env_data) # y = [[]] * len(env_data) # for i in range(1, len(env_data) - 1): # if len(env_data[i]) > 0: # x[i] = env_data[i][0] # y[i] = env_data[i][1] ax0.plot([value for value in x if value], [value for value in y if value], 'go', lw=3, label='Robot\'s Trajectory') # env_data = load('planner_of_agent_1.npy')[1:] # x = [[]] * len(env_data) # y = [[]] * len(env_data) # for i in range(1, len(env_data) - 1): # if len(env_data[i]) > 0: # x[i] = env_data[i][0] # y[i] = env_data[i][1] # ax0.plot([value for value in x if value], # [value for value in y if value], 'bo', lw=3, label='Robot\'s Trajectory') # ax0.legend() # ax0.axis('equal') # plt.draw() # plt.pause(.1) # raw_input("<Hit Enter To Close>") plt.close(f0) # yaw_bound = 3 * pi / 180 # yaw_calibrate = pi / 180 * (0) # x_offset_calibrate = .23 # y_offset_calibrate = -.08 # data = np.load('pos.npy')[1:] # print len(data) # error_long = data[:, 0] # error_lat = data[:, 1] # ref_x = [value for value in data[:, 2]] # print ref_x[:30] # ref_y = [value for value in data[:, 3]] # pos_x = [value for value in data[:, 4]][0::1] # pos_y = [value for value in data[:, 5]][0::1] # pos_theta = data[:, 6] # print data # time = data[:, 7] - data[0, 7] # vel = data[:, 8] # plt.plot(ref_x, ref_y, 'ro') # plt.gca().set_aspect('equal', adjustable='box') # f0 = plt.figure(1, figsize=(9, 9)) # ax0 = f0.add_subplot(111) # ax0.plot(ref_x, ref_y, '--', lw=3, label='Reference Trajectory') # ax0.plot(pos_x[0], pos_y[0], 'ms', markersize=10, label='Start Point') # ax0.plot(pos_x, pos_y, 'go', label='Robot Trajectory') # env_data = np.load('planner_of_agent_0.npy')[1:] # x = [[]] * len(env_data) # y = [[]] * len(env_data) # print len(env_data) # for i in range(1, len(env_data) - 1): # if len(env_data[i]) > 0: # x[i] = env_data[i][0] # y[i] = env_data[i][1] # yaw = env_data[i][2] # filter some of the readings; comment to see the effect # if len(env_data[i + 1]) == 0 or abs(yaw - env_data[i - 1][2]) > yaw_bound or abs(yaw - env_data[i + 1][2]) > yaw_bound: # continue # readings = env_data[i][3] # readings_x = [[]] * len(readings) # readings_y = [[]] * len(readings) # k = 0 # for j in range(len(readings)): # lidar readings in lidar frame # x_temp = readings[j][0] * cos(-readings[j][1]) # y_temp = readings[j][0] * sin(-readings[j][1]) # lidar readings in robot frame # x_temp2 = x_temp * \ # cos(yaw_calibrate) - y_temp * \ # sin(yaw_calibrate) + x_offset_calibrate # y_temp2 = y_temp * \ # cos(yaw_calibrate) + x_temp * \ # sin(yaw_calibrate) + y_offset_calibrate # lidar readings in global frame # readings_x[k] = x_temp2 * cos(yaw) - y_temp2 * sin(yaw) + x[i] # readings_y[k] = y_temp2 * cos(yaw) + x_temp2 * sin(yaw) + y[i] # k += 1 # ax0.plot(readings_x, readings_y, 'r.') # for i in range(len(env_data)): # if len(env_data[i])>0: # x[i] = env_data[i][0] # y[i] = env_data[i][1] # yaw = env_data[i][2] # print yaw # readings = env_data[i][3] # readings_x = [[]]*len(readings) # readings_y = [[]]*len(readings) # print len(readings),len(readings_x) # k=0 # for j in range(len(readings)): # if i<200: # print k,j,len(readings_x) # readings_x[k] = x[i] + readings[j][0]*sin(pi/2-yaw+readings[j][1]) # readings_y[k] = y[i] + readings[j][0]*cos(pi/2-yaw+readings[j][1]) # k+=1 # ax0.plot(readings_x, readings_y,'r.') # ax0.plot([], [], 'r.', label='Lidar Reading') # print x # ax0.plot([value for value in x if value], # [value for value in y if value], 'go', lw=3,label='Robot\'s Trajectory') # env_y = np.load('env.npy')[1] # env_x = [value for value in env_x if value] # env_y = [value for value in env_y if value] # ax0.plot(env_x, env_y, 'r.', ) # ax0.plot(-.5, 2.7, 'cs', markersize=10, label='Destination') # ax0.legend() # ax0.axis('equal') # ax0.set_xlim(-3.5, 3.5) # ax0.set_ylim(-3, 4) # ax0.set_xlabel('X (m)') # ax0.set_ylabel('Y (m)') # ax0.axis('equal') # plt.tight_layout() # plt.draw() # plt.pause(.1) # <------- # raw_input("<Hit Enter To Close>") # plt.close(f0)

30.956098

129

0.560668

1,051

6,346

3.226451

0.125595

0.094957

0.063698

0.053082

0.728104

0.690357

0.629018

0.616927

0.600708

0

0.043806

0.248188

6,346

204

130

31.107843

0.666946

0.656161

0

0.019932

0

null

0

0.06

null

0.02

0

null

0

1

0

null

0

1

0

2

f08ba58aa1ee5462b9589a7cefae921b8d9e4b35

477

py

Python

titan/react_pkg/prettier/__init__.py

mnieber/moonleap

2c951565c32f2e733a063b4a4f7b3d917ef1ec07

[ "MIT" ]

null

titan/react_pkg/prettier/__init__.py

mnieber/moonleap

2c951565c32f2e733a063b4a4f7b3d917ef1ec07

[ "MIT" ]

null

titan/react_pkg/prettier/__init__.py

mnieber/moonleap

2c951565c32f2e733a063b4a4f7b3d917ef1ec07

[ "MIT" ]

null

from pathlib import Path from moonleap import add, create from titan.project_pkg.service import Tool from titan.react_pkg.nodepackage import load_node_package_config class Prettier(Tool): pass base_tags = [("prettier", ["tool"])] @create("prettier") def create_prettier(term, block): prettier = Prettier(name="prettier") prettier.add_template_dir(Path(__file__).parent / "templates") add(prettier, load_node_package_config(__file__)) return prettier

22.714286

66

0.761006

62

477

5.532258

0.532258

0.052478

0.087464

0.122449

0

0.136268

477

20

67

23.85

0.832524

0

0.077568

0

1

0.076923

false

0.076923

0.307692

0

0.538462

0

null

0

null

0

1

0

2

f0935e4564c845dcf620246319af92237bea563f

167

py

Python

calvestbr/__init__.py

IsaacHiguchi/calvestbr

ebf702e9e67299c822a6cc21cad60b247446fcfa

[ "MIT" ]

null

calvestbr/__init__.py

IsaacHiguchi/calvestbr

ebf702e9e67299c822a6cc21cad60b247446fcfa

[ "MIT" ]

null

calvestbr/__init__.py

IsaacHiguchi/calvestbr

ebf702e9e67299c822a6cc21cad60b247446fcfa

[ "MIT" ]

null

"""Top-level package for Calendário dos Vestibulares do Brasil.""" __author__ = """Ana_Isaac_Marina""" __email__ = 'marinalara170303@gmail.com' __version__ = '0.0.1'

27.833333

66

0.742515

21

167

5.238095

0.952381

0

0.060403

0.107784

167

5

67

33.4

0.677852

0.359281

0

0.465347

0.257426

0

1

0

false

0

1

0

null

0

1

0

null

0

2

f0ad10d1d55fd2bdc2c491c48aba252ed553fa31

3,568

py

Python

srblib/__init__.py

srbcheema1/srblib

26146cb0d5586548da5f97a9fe3af355cd97f3ca

[ "MIT" ]

2

2019-04-03T00:51:54.000Z

2019-05-16T10:33:44.000Z

srblib/__init__.py

srbcheema1/srblib

26146cb0d5586548da5f97a9fe3af355cd97f3ca

[ "MIT" ]

null

srblib/__init__.py

srbcheema1/srblib

26146cb0d5586548da5f97a9fe3af355cd97f3ca

[ "MIT" ]

null

__version__ = '0.1.6' __mod_name__ = 'srblib' from .colour import Colour # A class with color names and a static print function which prints coloured output to stderr from .debugger import debug # a boolean whose value can be changed in ~/.config/srblib/debug.json from .debugger import on_appveyor # a boolean value which is true if code is running on appveyor from .debugger import on_ci # a boolean value which is true if it code is running on CI from .debugger import on_srbpc # a boolean value which is true if it is my PC i.e. srb-pc from .debugger import on_travis # a boolean value which is true if code is running on travis from .dependency import install_arg_complete # A function to append line of argcomplete in ~/.bashrc from .dependency import install_dependencies # A function that takes a special data-template to install dependencies from .dependency import install_dependencies_pkg # similar but based on package-managers (Recommended) from .dependency import is_installed # checks if the following application is installed on machine or not from .dependency import remove_dependencies # Opposite of install_dependencies from .dependency import remove_dependencies_pkg # Opposite of install_dependencies_pkg from .email import email # a function from .email import Email # a class to send email from .files import file_extension # returns back the extention of a file from filepath, may return '' if no ext from .files import file_name # returns filename from a filepath from .files import remove # removes a path recursively. it deletes all files and folders under that path from .files import verify_file # verify that a file exists. if not it will create one. also creates parents if needed from .files import verify_folder # verify that a folder exists. creates one if not there. also creates parents if needed from .file_importer import Module # a class to import modules # one cant declare more attributes in frozen class from .frozen import FrozenClass # A class to be inherited to make a class frozen. i.e. no more attributes can be added. from .path import abs_path # returns absolute path of a path given. works on windows as well as linux. from .path import is_child_of # returns if a given path is child(direct/indirect) of the second path given. from .path import parent_dir # returns Nth parent of a path. default it returns 1st parent from .path import relative_path # returns relative path if given absolute path from .requests import debug_res # print debug output of response. from .srb_bank import SrbBank # A class to store things for later use of a program. can act as a database from .srb_json import SrbJson # A class to use json file more easily from .srb_hash import path_hash # get hash of full path (recursively) from .srb_hash import str_hash # get hash of string from .soup import Soup # A class to make scrapping easier from .system import get_os_name # returns OS name. values are windows, linux or mac from .system import os_name # value of get_os_name from .system import on_windows # True if system is windows OS from .tabular import Tabular # A class to process dabular data from .util import line_adder # append a line if not present in a given file from .util import show_dependency_error_and_exit # display missing dependency error and exit from .util import similarity # returns percentage of similarity of two strings from .util import top # first element of list or set or dict(first key) from .util import dump_output # variable containing string value ` > /dev/null 2>&1 ` or ` > nul 2>&1 `.

60.474576

120

0.7912

597

3,568

4.638191

0.340034

0.019502

0.020224

0.028891

0.156013

0.071506

0.049837

0.029614

0

0.002695

0.168161

3,568

58

121

61.517241

0.930256

0.597534

0

0.007891

0

1

0

false

0

0.952381

0

0.952381

0

null

0

null

0

1

0

1

0

2

f0c3581446d85c97a243b1adbc5978391a877b8e

269

py

Python

src/app/buy_btc.py

simondorfman/hello_cb_pro

cdb96ee1390d22753630e24dac9bfdc5e47e788d

[ "MIT" ]

null

src/app/buy_btc.py

simondorfman/hello_cb_pro

cdb96ee1390d22753630e24dac9bfdc5e47e788d

[ "MIT" ]

null

src/app/buy_btc.py

simondorfman/hello_cb_pro

cdb96ee1390d22753630e24dac9bfdc5e47e788d

[ "MIT" ]

null

import os from cbt.private_client import PrivateClient from cbt.auth import get_new_private_connection if __name__ == "__main__": usd = os.getenv("USD_BUY") auth = get_new_private_connection() client = PrivateClient(auth) client.market_buy_btc(usd)

20.692308

47

0.754647

37

269

5

0.513514

0.075676

0.140541

0.248649

0

0.163569

269

12

48

22.416667

0.822222

0

0.055762

0

1

0

false

0

0.375

0

0.375

0

null

0

1

0

null

0

1

0

2

f0ca3d609391dc32aa46d1c4b4ec4ee3f9a34e0a

448

py

Python

cbandits/core/bayesian_nn.py

AlliedToasters/dev_bandits

7e3655bd5a91854951a52d0f037ee06aefb2922c

[ "MIT" ]

null

cbandits/core/bayesian_nn.py

AlliedToasters/dev_bandits

7e3655bd5a91854951a52d0f037ee06aefb2922c

[ "MIT" ]

null

cbandits/core/bayesian_nn.py

AlliedToasters/dev_bandits

7e3655bd5a91854951a52d0f037ee06aefb2922c

[ "MIT" ]

null

"""Define the abstract class for Bayesian Neural Networks.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function class BayesianNN(object): """A Bayesian neural network keeps a distribution over neural nets.""" def __init__(self, optimizer): pass def build_model(self): pass def train(self, data): pass def sample(self, steps): pass

21.333333

74

0.694196

55

448

5.309091

0.618182

0.10274

0.164384

0

0.234375

448

21

75

21.333333

0.851312

0.267857

0

0.333333

0

1

0.333333

false

0.333333

0.25

0

0.666667

0.083333

0

null

0

null

0

1

0

1

0

2

f0d87d7b32c42472be81003f06fe5e9c4bf5e20f

1,781

py

Python

e_secretary/migrations/0010_auto_20190329_2219.py

tsitsikas96/e-secretary

bdda95e17093da730af33acf4b15ed03331c7643

[ "MIT" ]

null

e_secretary/migrations/0010_auto_20190329_2219.py

tsitsikas96/e-secretary

bdda95e17093da730af33acf4b15ed03331c7643

[ "MIT" ]

null

e_secretary/migrations/0010_auto_20190329_2219.py

tsitsikas96/e-secretary

bdda95e17093da730af33acf4b15ed03331c7643

[ "MIT" ]

1

2020-03-08T16:12:34.000Z

# Generated by Django 2.1.7 on 2019-03-29 20:19 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('e_secretary', '0009_profile'), ] operations = [ migrations.AlterModelOptions( name='professor', options={'ordering': ['title']}, ), migrations.RemoveField( model_name='professor', name='email', ), migrations.RemoveField( model_name='professor', name='fname', ), migrations.RemoveField( model_name='professor', name='lname', ), migrations.RemoveField( model_name='student', name='email', ), migrations.RemoveField( model_name='student', name='fname', ), migrations.RemoveField( model_name='student', name='lname', ), migrations.AddField( model_name='profile', name='email', field=models.EmailField(default='test@email.com', max_length=254, null=True), ), migrations.AddField( model_name='profile', name='fname', field=models.CharField(default='First', help_text='First Name', max_length=50), ), migrations.AddField( model_name='profile', name='lname', field=models.CharField(default='Last', help_text='Last Name', max_length=50), ), migrations.AlterField( model_name='profile', name='grammateia', field=models.BooleanField(default=False), ), migrations.DeleteModel( name='Grammateia', ), ]

27.4

91

0.522179

150

1,781

6.086667

0.393333

0.098576

0.170865

0.197152

0.466594

0.422782

0

0.022589

0.353734

1,781

64

92

27.828125

0.770634

0.025267

0

0.689655

1

0

0.131488

0

1

0

false

0

0.017241

0

0.068966

0

null

0

1

0

1

0

null

0

2

f0db46fd26b0c7315a9b0cf93b8d1fbaf8362e97

2,743

py

Python

gender_converter/logger_aegender.py

roebel/DeepGC

03eee63ff9d9f4daa34435ddca530b262f097ea6

[ "MIT" ]

null

gender_converter/logger_aegender.py

roebel/DeepGC

03eee63ff9d9f4daa34435ddca530b262f097ea6

[ "MIT" ]

1

2021-08-11T06:41:56.000Z

gender_converter/logger_aegender.py

roebel/DeepGC

03eee63ff9d9f4daa34435ddca530b262f097ea6

[ "MIT" ]

null

import random from plotting_utils import plot_spectrogram_to_numpy, image_for_logger, plot_to_image import numpy as np import tensorflow as tf class GParrotLogger(): def __init__(self, logdir, ali_path='ali'): # super(ParrotLogger, self).__init__(logdir) self.writer = tf.summary.create_file_writer(logdir) def log_training(self, train_loss, loss_list, accuracy_list, grad_norm, learning_rate, duration, iteration): (speaker_encoder_loss, gender_autoencoder_loss, gender_classification_loss, gender_adv_loss, gender_autoencoder_destandardized_loss) = loss_list speaker_encoder_acc, gender_classification_acc = accuracy_list with self.writer.as_default(): tf.summary.scalar("training.loss", train_loss, iteration) tf.summary.scalar("training.loss.spenc", speaker_encoder_loss, iteration) tf.summary.scalar("training.loss.gauto", gender_autoencoder_loss, iteration) tf.summary.scalar("training.loss.gautotrue", gender_autoencoder_destandardized_loss, iteration) tf.summary.scalar("training.loss.gcla", gender_classification_loss, iteration) tf.summary.scalar("training.loss.gadv", gender_adv_loss, iteration) tf.summary.scalar('training.acc.spenc', speaker_encoder_acc, iteration) tf.summary.scalar('training.acc.gcla', gender_classification_acc, iteration) tf.summary.scalar("grad.norm", grad_norm, iteration) tf.summary.scalar("learning.rate", learning_rate, iteration) tf.summary.scalar("duration", duration, iteration) self.writer.flush() def log_validation(self, val_loss, loss_list, accuracy_list, iteration): (speaker_encoder_loss, gender_autoencoder_loss, gender_classification_loss, gender_adv_loss, gender_autoencoder_destandardized_loss) = loss_list speaker_encoder_acc, gender_classification_acc = accuracy_list with self.writer.as_default(): tf.summary.scalar("validation.loss", val_loss, iteration) tf.summary.scalar("validation.loss.spenc", speaker_encoder_loss, iteration) tf.summary.scalar("validation.loss.gauto", gender_autoencoder_loss, iteration) tf.summary.scalar("validation.loss.gautotrue", gender_autoencoder_destandardized_loss, iteration) tf.summary.scalar("validation.loss.gcla", gender_classification_loss, iteration) tf.summary.scalar("validation.loss.gadv", gender_adv_loss, iteration) tf.summary.scalar('validation.acc.spenc', speaker_encoder_acc, iteration) tf.summary.scalar('validation.acc.gcla', gender_classification_acc, iteration) self.writer.flush()

55.979592

112

0.728035

321

2,743

5.912773

0.190031

0.094837

0.150158

0.214963

0.758166

0.711275

0.651212

0.574289

0.305585

0

0.176085

2,743

48

113

57.145833

0.839823

0.015312

0

0.263158

0

0.125602

0.033346

0

1

0.078947

false

0

0.105263

0

0.210526

0

null

0

1

0

1

0

null

0

2

f0dc6c0f1ad89845b0333162183c190359534d22

906

py

Python

texel/keys.py

Xen0byte/texel

9dcfba163c66e9da5e9b0757c4e587f297b0cfcb

[ "MIT" ]

119

2022-02-06T21:47:55.000Z

2022-03-21T23:14:30.000Z

texel/keys.py

Xen0byte/texel

9dcfba163c66e9da5e9b0757c4e587f297b0cfcb

[ "MIT" ]

3

2022-02-07T08:47:20.000Z

2022-02-09T09:07:17.000Z

texel/keys.py

Xen0byte/texel

9dcfba163c66e9da5e9b0757c4e587f297b0cfcb

[ "MIT" ]

5

2022-02-07T08:13:11.000Z

2022-02-12T22:31:37.000Z

import curses class Key: def __init__(self, *values): self.values = values self._hash = hash(values) self._keyset = set(values) def __eq__(self, other): return self._hash == other._hash def __hash__(self): return self._hash class Keys: ESC = Key(27) TAB = Key(ord("\t"), ord("n")) SHIFT_TAB = Key(353, ord("N")) VISUAL = Key(ord("v"), ord("V")) COPY = Key(ord("c"), ord("y")) QUIT = Key(ord("q")) UP = Key(curses.KEY_UP, ord("k")) DOWN = Key(curses.KEY_DOWN, ord("j")) LEFT = Key(curses.KEY_LEFT, ord("h")) RIGHT = Key(curses.KEY_RIGHT, ord("l")) HELP = Key(ord("?")) ALL = [ESC, TAB, SHIFT_TAB, VISUAL, COPY, QUIT, UP, DOWN, LEFT, RIGHT, HELP] _id_to_key = {id: key for key in ALL for id in key.values} @staticmethod def to_key(key: int) -> Key: return Keys._id_to_key.get(key)

25.885714

80

0.572848

139

906

3.517986

0.33813

0.06135

0.09816

0

0.007396

0.253863

906

34

81

26.647059

0.715976

0

0.015453

0

1

0.148148

false

0

0.037037

0.111111

0.851852

0

null

0

null

0

1

0

2

f0e7d6bd1974b95ea4a8abd9c52fb010ef93328b

475

py

Python

app/converter/nsl/substance_cv_converter.py

c0d3m0nkey/xml-to-json-converter

9cf040b591f45031c80dc5bc64d6fbb2c4665d25

[ "BSD-2-Clause" ]

null

app/converter/nsl/substance_cv_converter.py

c0d3m0nkey/xml-to-json-converter

9cf040b591f45031c80dc5bc64d6fbb2c4665d25

[ "BSD-2-Clause" ]

null

app/converter/nsl/substance_cv_converter.py

c0d3m0nkey/xml-to-json-converter

9cf040b591f45031c80dc5bc64d6fbb2c4665d25

[ "BSD-2-Clause" ]

null

from lxml import objectify, etree from operator import itemgetter from ..xml_converter import XmlConverter class SubstanceCVConverter(XmlConverter): def convert(self, xml): item = {} item["term_english_equiv"] = str(xml.attrib["term-english-equiv"]) item["term_id"] = str(xml.attrib["term-id"]) item["term_lang"] = str(xml.attrib["term-lang"]) item["term_revision_num"] = str(xml.attrib["term-revision-num"]) return item

36.538462

74

0.671579

60

475

5.2

0.433333

0.102564

0.153846

0.205128

0

0.187368

475

12

75

39.583333

0.80829

0

0.214737

0

1

0.090909

false

0

0.272727

0

0.545455

0

null

0

1

0

null

0

1

0

2

f0f5116f620313599917f1b146e0c00251125aed

728

py

Python

prickly-pufferfish/python_questions/merge_ranges.py

Vthechamp22/summer-code-jam-2021

0a8bf1f22f6c73300891fd779da36efd8e1304c1

[ "MIT" ]

40

2020-08-02T07:38:22.000Z

2021-07-26T01:46:50.000Z

prickly-pufferfish/python_questions/merge_ranges.py

Vthechamp22/summer-code-jam-2021

0a8bf1f22f6c73300891fd779da36efd8e1304c1

[ "MIT" ]

134

2020-07-31T12:15:45.000Z

2020-12-13T04:42:19.000Z

prickly-pufferfish/python_questions/merge_ranges.py

Vthechamp22/summer-code-jam-2021

0a8bf1f22f6c73300891fd779da36efd8e1304c1

[ "MIT" ]

101

2020-07-31T12:00:47.000Z

2021-11-01T09:06:58.000Z

""" In HiCal, a meeting is stored as tuples of integers (start_time, end_time). / These integers represent the number of 30-minute blocks past 9:00am. / For example: / (2, 3) # meeting from 10:00 - 10:30 am / (6, 9) # meeting from 12:00 - 1:30 pm / Write a function merge_ranges() that / takes a list of meeting time ranges as a parameter / and returns a list of condensed ranges. / >>> merge_ranges([(3, 5), (4, 8), (10, 12), (9, 10), (0, 1)]) / [(0, 1), (3, 8), (9, 12)] / >>> merge_ranges([(0, 3), (3, 5), (4, 8), (10, 12), (9, 10)]) / [(0, 8), (9, 12)] / >>> merge_ranges([(0, 3), (3, 5)]) / [(0, 5)] / >>> merge_ranges([(0, 3), (3, 5), (7, 8)]) / [(0, 5), (7, 8)] / >>> merge_ranges([(1, 5), (2, 3)]) / [(1, 5)] / """

28

77

0.539835

131

728

2.938931

0.389313

0.171429

0.093506

0.101299

0.194805

0.155844

0

0.14433

0.200549

728

25

78

29.12

0.517182

0.987637

0

null

0

null

0

null

0

null

1

null

true

0

null

0

null

0

1

0

null

0

1

0

2

0b04b5673e663cf9c8fc8da92d1c7bd8d879657a

1,152

py

Python

Neural_Networks/Multilayer/Neural_Multi_pybrain.py

jeffreire/Deep_Learning

960142080dc63ea103b326ea3d6d17bd44ae0f51

[ "MIT" ]

null

Neural_Networks/Multilayer/Neural_Multi_pybrain.py

jeffreire/Deep_Learning

960142080dc63ea103b326ea3d6d17bd44ae0f51

[ "MIT" ]

null

Neural_Networks/Multilayer/Neural_Multi_pybrain.py

jeffreire/Deep_Learning

960142080dc63ea103b326ea3d6d17bd44ae0f51

[ "MIT" ]

null

# from pybrain.datasets import SupervisedDataSet # from pybrain.supervised.trainers import BackpropTrainer # from pybrain.structure.modules import SoftmaxLayer # from pybrain.structure.modules import SigmoidLayer # from pybrain.tools.s import buildNetwork # (x,y,z) = x é a quantidade de camadas de entrada, y é a quantidade de camada oculta, z é a quantidade de camada de saida # rede = buildNetwork(3,3,1) # (x,y) sao os previsores, dois atributos e uma class # base = SupervisedDataSet(2, 1) # queremos dizer que a entrada sera de (0,0) e queremos obter uma saida de (0, ) # base.addSample((0,0),(0, )) # base.addSample((0,1),(1, )) # base.addSample((1,0),(0, )) # base.addSample((1,1),(0, )) # print(base['input']) # treinamos a nossa rede passando por parametro rede, basa, taxa de aprendizagem e momento # treinamento = BackpropTrainer(rede, dataset = base, learningrate = 0.01, # momentum = 0.06) # o for é quantas epocas iremos calcular os nossos pesos # for i in range(1, 30000): # erro = treinamento.train() # if i % 1000 == 0: # print("Erro: %s" % erro)

39.724138

123

0.664931

165

1,152

4.642424

0.484848

0.071802

0.046997

0.05483

0.138381

0

0.04102

0.217014

1,152

29

124

39.724138

0.808204

0.923611

0

null

0

null

0

null

0

null

1

null

true

0

null

0

null

0

1

0

null

0

1

0

2

0b08ce05031842d1b1da5e73875c7ace68953124

6,040

py

Python

mydb/test_postgres.py

dappsunilabs/DB4SCI

54bdd03aaa12957e622c921b263e187740a8b2ae

[ "Apache-2.0" ]

7

2018-12-05T19:18:20.000Z

2020-11-21T07:27:54.000Z

mydb/test_postgres.py

dappsunilabs/DB4SCI

54bdd03aaa12957e622c921b263e187740a8b2ae

[ "Apache-2.0" ]

8

2018-04-25T06:02:41.000Z

2020-09-08T21:55:56.000Z

mydb/test_postgres.py

FredHutch/DB4SCI

cc950a36b6b678fe16c1c91925ec402581636fc0

[ "Apache-2.0" ]

2

2019-11-14T02:09:09.000Z

2021-12-28T19:05:51.000Z

#!/usr/bin/python import time import psycopg2 import argparse import postgres_util import container_util import admin_db import volumes from send_mail import send_mail from config import Config def full_test(params): admin_db.init_db() con_name = params['dbname'] dbtype = params['dbtype'] print('Starting %s Test; Container Name: %s' % (dbtype, con_name)) if container_util.container_exists(con_name): print(' Duplicate container: KILLING') result = container_util.kill_con(con_name, Config.accounts[dbtype]['admin'], Config.accounts[dbtype]['admin_pass'], params['username']) time.sleep(5) print(result) print(' removing old directories') volumes.cleanup_dirs(con_name) print(' Create container') result = postgres_util.create(params) print(' Create result: %s' % result) port = params['port'] # # Admin DB checking # print(' Check Admin DB log for "create"') admin_db.display_container_log(limit=1) print(' Check Admin DB for State entry') info = admin_db.get_container_state(con_name) print(' Name: %s ' % info.name), print('State: %s ' % info.state), print('TS: %s ' % info.ts), print('CID: %d' % info.c_id) print(' Check Admin DB for Container Info') info = admin_db.display_container_info(con_name) print('Info: %s' % info) print(' Postgres Show All') postgres_util.showall(params) print("\n=========") print(" - Test Accounts\n") print("=========") admin_user = Config.accounts[dbtype]['admin'] admin_pass = Config.accounts[dbtype]['admin_pass'] test_user = Config.accounts['test_user']['admin'] test_pass = Config.accounts['test_user']['admin_pass'] for dbuser, dbuserpass in [[test_user, test_pass], ['svc_'+test_user, params['longpass']], [admin_user, admin_pass]]: auth = postgres_util.auth_check(dbuser, dbuserpass, port) if auth: print('User %s verified!' % dbuser) else: print('user account not valid: %s' % dbuser) print(" - Test Complete") def populate(params): dbTestName = 'testdb' dbtype = params['dbtype'] conn_string = "dbname='%s' " % params['dbname'] conn_string += "user='%s' " % Config.accounts[dbtype]['admin'] conn_string += "host='%s' " % Config.container_host conn_string += "port='%d' " % params['port'] conn_string += "password='%s'" % Config.accounts[dbtype]['admin_pass'] print(' - Populate with test data: ') try: conn = psycopg2.connect(conn_string) except: print "I am unable to connect to the database" conn.set_isolation_level(0) cur = conn.cursor() print(' - Create DB: ' + dbTestName) cur.execute("CREATE TABLE t1 (id serial PRIMARY KEY, num integer, data varchar);") cur.execute("INSERT INTO t1 (num, data) VALUES (%s, %s)", (100, "table t1 in Primary database")) cur.execute("CREATE DATABASE " + dbTestName) conn.close() target = "dbname='%s'" % params['dbname'] testdb = "dbname='%s'" % dbTestName conn2 = conn_string.replace(target, testdb) print(' - Connect to new DB: ' + conn2) conn = psycopg2.connect(conn2) cur = conn.cursor() print(' - Create Table and Insert ') cur.execute("CREATE TABLE t2 (id serial PRIMARY KEY, num integer, data varchar);") cur.execute("INSERT INTO t2 (num, data) VALUES (%s, %s)", (100, "Important test data in t2")) conn.commit() cur.close() print(' - Populate Success') def delete_test_container(dbtype, con_name): print("\n=========") print(" - Removing Container") print("=========") result = container_util.kill_con(con_name, Config.accounts[dbtype]['admin'], Config.accounts[dbtype]['admin_pass']) print(result) def setup(dbtype, con_name): params = {'dbname': con_name, 'dbuser': Config.accounts['test_user']['admin'], 'dbtype': dbtype, 'dbuserpass': Config.accounts['test_user']['admin_pass'], 'support': 'Basic', 'owner': Config.accounts['test_user']['owner'], 'description': 'Test the Dev', 'contact': Config.accounts['test_user']['contact'], 'life': 'medium', 'backup_type': 'User', 'backup_freq': 'Daily', 'backup_life': '6', 'backup_window': 'any', 'pitr': 'n', 'maintain': 'standard', 'phi': 'No', 'pitr': 'n', 'username': Config.accounts['test_user']['admin'], 'image': Config.info[dbtype]['images'][1][1], 'db_vol': '/mydb/dbs_data', } return params if __name__ == "__main__": dbtype = 'Postgres' con_name = 'postgres-test' params = setup(dbtype, con_name) # paramd['db_vol'] = '/mydb/encrypt', parser = argparse.ArgumentParser(prog='test_postgres.py', description='Test %s routines' % dbtype) parser.add_argument('--purge', '-d', action='store_true', default=False, help='Delete test container') parser.add_argument('--backup', '-b', action='store_true', default=False, help='backup %s' % params['dbname']) args = parser.parse_args() if args.purge: delete_test_container(dbtype, con_name) elif args.backup: (cmd, mesg) = postgres_util.backup(params) print("Command: %s\nBackup result: %s" % (cmd, mesg)) else: full_test(params) populate(params) postgres_util.backup(params) print('- Tests Complete!')

36.606061

86

0.565728

672

6,040

4.93006

0.269345

0.063387

0.048295

0.060368

0.252943

0.167522

0.088138

0

0.005579

0.287748

6,040

164

87

36.829268

0.764528

0.011755

0

0.124138

0

0.264085

0

null

0.068966

null

0.227586

0

null

0

null

0

1

0

1

0

2

0b0f14dc9edd917b5943eaee8fa4e20472331f44

170

py

Python

src/matlab2cpp/node/__init__.py

neilferg/matlab2cpp

aa26671fc73dad297c977511053b076e05bdd2df

[ "BSD-3-Clause" ]

null

src/matlab2cpp/node/__init__.py

neilferg/matlab2cpp

aa26671fc73dad297c977511053b076e05bdd2df

[ "BSD-3-Clause" ]

null

src/matlab2cpp/node/__init__.py

neilferg/matlab2cpp

aa26671fc73dad297c977511053b076e05bdd2df

[ "BSD-3-Clause" ]

null

""" The module contains the following submodules. """ from .frontend import Node __all__ = ["Node"] if __name__ == "__main__": import doctest doctest.testmod()

15.454545

45

0.688235

19

170

5.526316

0.789474

0

0.188235

170

10

46

17

0.76087

0.264706

0

0.102564

0

1

0

false

0

0.4

0

0.4

0

1

0

null

0

null

0

1

0

2

9bd8035c6b3b5723ba2c49f36471229439b947c4

1,013

py

Python

gitrack/exceptions.py

AuHau/giTrack

802ee23513d60b2379f0f5968e595288d5b6c31d

[ "MIT" ]

5

2019-02-19T10:56:56.000Z

2020-11-28T11:37:45.000Z

gitrack/exceptions.py

AuHau/giTrack

802ee23513d60b2379f0f5968e595288d5b6c31d

[ "MIT" ]

63

2019-01-21T21:44:28.000Z

2022-03-21T14:01:11.000Z

gitrack/exceptions.py

AuHau/giTrack

802ee23513d60b2379f0f5968e595288d5b6c31d

[ "MIT" ]

2

2019-01-04T19:31:52.000Z

2020-12-10T21:40:09.000Z

class GitrackException(Exception): """ General giTrack's exception """ pass class ConfigException(GitrackException): """ Exception related to Config functionality. """ pass class InitializedRepoException(GitrackException): """ Raised when user tries to initialized repo that has been already initialized before. """ pass class UninitializedRepoException(GitrackException): """ Raised when giTrack invoke in Git repository that has not been initialized. """ pass class UnknownShell(GitrackException): pass class PromptException(GitrackException): pass class ProviderException(GitrackException): def __init__(self, provider_name, message, *args, **kwargs): self.message = message self.provider_name = provider_name super().__init__(*args, **kwargs) def __str__(self): return 'Provider \'{}\': {}'.format(self.provider_name, self.message) class RunningEntry(ProviderException): pass

19.862745

88

0.691017

96

1,013

7.125

0.479167

0.078947

0.070175

0

0.215202

1,013

50

89

20.26

0.860377

0.228036

0

0.333333

0

0.019444

0

1

0.095238

false

0.333333

0

0.047619

0.52381

0

null

0

null

0

1

0

1

0

2

501a6e4b0542dfab3ece831a797cbcd4d5a9b0c2

7,119

py

Python

oembed/migrations/0001_initial.py

EightMedia/djangoembed

ee325f7375c48405f9c3e7e2c0fa7f5a08fafd48

[ "MIT" ]

8

2015-02-06T19:18:49.000Z

2021-01-01T05:46:02.000Z

oembed/migrations/0001_initial.py

EightMedia/djangoembed

ee325f7375c48405f9c3e7e2c0fa7f5a08fafd48

[ "MIT" ]

null

oembed/migrations/0001_initial.py

EightMedia/djangoembed

ee325f7375c48405f9c3e7e2c0fa7f5a08fafd48

[ "MIT" ]

5

2015-03-15T11:41:26.000Z

2018-03-08T09:45:26.000Z

# encoding: utf-8 import datetime from south.db import db from south.v2 import SchemaMigration from django.conf import settings from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Adding model 'StoredOEmbed' db.create_table('oembed_storedoembed', ( ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)), ('match', self.gf('django.db.models.fields.TextField')()), ('response_json', self.gf('django.db.models.fields.TextField')()), ('resource_type', self.gf('django.db.models.fields.CharField')(max_length=8)), ('date_added', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, blank=True)), ('date_expires', self.gf('django.db.models.fields.DateTimeField')(null=True, blank=True)), ('maxwidth', self.gf('django.db.models.fields.IntegerField')(null=True, blank=True)), ('maxheight', self.gf('django.db.models.fields.IntegerField')(null=True, blank=True)), ('object_id', self.gf('django.db.models.fields.IntegerField')(null=True, blank=True)), ('content_type', self.gf('django.db.models.fields.related.ForeignKey')(blank=True, related_name='related_storedoembed', null=True, to=orm['contenttypes.ContentType'])), )) db.send_create_signal('oembed', ['StoredOEmbed']) # Adding unique constraint on 'StoredOEmbed', fields ['match', 'maxwidth', 'maxheight'] if 'mysql' not in settings.DATABASES['default']['ENGINE']: db.create_unique('oembed_storedoembed', ['match', 'maxwidth', 'maxheight']) # Adding model 'StoredProvider' db.create_table('oembed_storedprovider', ( ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)), ('endpoint_url', self.gf('django.db.models.fields.CharField')(max_length=255)), ('regex', self.gf('django.db.models.fields.CharField')(max_length=255)), ('wildcard_regex', self.gf('django.db.models.fields.CharField')(max_length=255, blank=True)), ('resource_type', self.gf('django.db.models.fields.CharField')(max_length=8)), ('active', self.gf('django.db.models.fields.BooleanField')(default=False, blank=True)), ('provides', self.gf('django.db.models.fields.BooleanField')(default=False, blank=True)), ('scheme_url', self.gf('django.db.models.fields.CharField')(max_length=255, blank=True)), )) db.send_create_signal('oembed', ['StoredProvider']) # Adding model 'AggregateMedia' db.create_table('oembed_aggregatemedia', ( ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True)), ('url', self.gf('django.db.models.fields.TextField')()), ('object_id', self.gf('django.db.models.fields.IntegerField')(null=True, blank=True)), ('content_type', self.gf('django.db.models.fields.related.ForeignKey')(blank=True, related_name='aggregate_media', null=True, to=orm['contenttypes.ContentType'])), )) db.send_create_signal('oembed', ['AggregateMedia']) def backwards(self, orm): # Deleting model 'StoredOEmbed' db.delete_table('oembed_storedoembed') # Removing unique constraint on 'StoredOEmbed', fields ['match', 'maxwidth', 'maxheight'] if 'mysql' not in settings.DATABASES['default']['ENGINE']: db.delete_unique('oembed_storedoembed', ['match', 'maxwidth', 'maxheight']) # Deleting model 'StoredProvider' db.delete_table('oembed_storedprovider') # Deleting model 'AggregateMedia' db.delete_table('oembed_aggregatemedia') models = { 'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, 'oembed.aggregatemedia': { 'Meta': {'object_name': 'AggregateMedia'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'aggregate_media'", 'null': 'True', 'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'object_id': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'url': ('django.db.models.fields.TextField', [], {}) }, 'oembed.storedoembed': { 'Meta': {'ordering': "('-date_added',)", 'unique_together': "(('match', 'maxwidth', 'maxheight'),)", 'object_name': 'StoredOEmbed'}, 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'related_storedoembed'", 'null': 'True', 'to': "orm['contenttypes.ContentType']"}), 'date_added': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}), 'date_expires': ('django.db.models.fields.DateTimeField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'match': ('django.db.models.fields.TextField', [], {}), 'maxheight': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'maxwidth': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'object_id': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}), 'resource_type': ('django.db.models.fields.CharField', [], {'max_length': '8'}), 'response_json': ('django.db.models.fields.TextField', [], {}) }, 'oembed.storedprovider': { 'Meta': {'ordering': "('endpoint_url', 'resource_type', 'wildcard_regex')", 'object_name': 'StoredProvider'}, 'active': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'blank': 'True'}), 'endpoint_url': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'provides': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'blank': 'True'}), 'regex': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'resource_type': ('django.db.models.fields.CharField', [], {'max_length': '8'}), 'scheme_url': ('django.db.models.fields.CharField', [], {'max_length': '255', 'blank': 'True'}), 'wildcard_regex': ('django.db.models.fields.CharField', [], {'max_length': '255', 'blank': 'True'}) } } complete_apps = ['oembed']

62.447368

197

0.606827

758

7,119

5.572559

0.131926

0.092803

0.159091

0.227273

0.735795

0.71875

0.680398

0.651989

0.622869

0.495265

0

0.006722

0.184998

7,119

113

198

63

0.721303

0.052114

0

0.229885

0

0.501633

0.293114

0

1

0.022989

false

0

0.057471

0

0.114943

0

null

0

1

0

1

0

null

0

2

5025f16dc15906f1c7c7af67d516b81c43cb2edb

967

bzl

Python

source/bazel/deps/libevent/get.bzl

luxe/CodeLang-compiler

78837d90bdd09c4b5aabbf0586a5d8f8f0c1e76a

[ "MIT" ]

1

2019-01-06T08:45:46.000Z

source/bazel/deps/libevent/get.bzl

luxe/CodeLang-compiler

78837d90bdd09c4b5aabbf0586a5d8f8f0c1e76a

[ "MIT" ]

264

2015-11-30T08:34:00.000Z

2018-06-26T02:28:41.000Z

source/bazel/deps/libevent/get.bzl

UniLang/compiler

c338ee92994600af801033a37dfb2f1a0c9ca897

[ "MIT" ]

null

# Do not edit this file directly. # It was auto-generated by: code/programs/reflexivity/reflexive_refresh load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive") load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_file") def libevent(): http_archive( name = "libevent", build_file = "//bazel/deps/libevent:build.BUILD", sha256 = "9b436b404793be621c6e01cea573e1a06b5db26dad25a11c6a8c6f8526ed264c", strip_prefix = "libevent-eee26deed38fc7a6b6780b54628b007a2810efcd", urls = [ "https://github.com/Unilang/libevent/archive/eee26deed38fc7a6b6780b54628b007a2810efcd.tar.gz", ], patches = [ "//bazel/deps/libevent/patches:p1.patch", ], patch_args = [ "-p1", ], patch_cmds = [ "find . -type f -name '*.c' -exec sed -i 's/#include <stdlib.h>/#include <stdlib.h>\n#include <stdint.h>\n/g' {} \\;", ], )

37.192308

130

0.623578

100

967

5.91

0.6

0.030457

0.047377

0.064298

0.145516

0

0.117962

0.228542

967

25

131

38.68

0.674263

0.104447

0

0.190476

1

0.047619

0.590962

0.31518

0

1

0.047619

true

0

0.047619

0

null

0

1

0

null

0

1

0

2

502f754cdffdb05797ba5ba3fc5cba7ad3499d41

250

py

Python

segitiga/hitung-luas-segitiga.py

Yurimahendra/latihan-big-data

5ea495bc1187c4d99a83654f8377d73e72eb63d2

[ "MIT" ]

null

segitiga/hitung-luas-segitiga.py

Yurimahendra/latihan-big-data

5ea495bc1187c4d99a83654f8377d73e72eb63d2

[ "MIT" ]

null

segitiga/hitung-luas-segitiga.py

Yurimahendra/latihan-big-data

5ea495bc1187c4d99a83654f8377d73e72eb63d2

[ "MIT" ]

null

# jumlah segitiga n = 123 # panjang alas sebuah segitiga alas = 30 # tinggi sebuah segitiga tinggi = 18 # hitung luas sebuah segitiga luas = alas * tinggi * 1/2 # hitung luas total luastotal = n * luas print('luas total : ', luastotal,'satuan luas')

20.833333

47

0.716

36

250

4.972222

0.5

0.234637

0.201117

0

0.044554

0.192

250

12

47

20.833333

0.841584

0.452

0

0.181818

0

1

0

false

0

0.166667

0

null

1

0

null

0

2

503945544f0f8af4e632fde69205e3dc522fc1a7

562

py

Python

kolejka/judge/tasks/list_files.py

zielinskit/kolejka-judge

571df05b12c5a4748d7a2ca4c217b0042acf6b48

[ "MIT" ]

null

kolejka/judge/tasks/list_files.py

zielinskit/kolejka-judge

571df05b12c5a4748d7a2ca4c217b0042acf6b48

[ "MIT" ]

null

kolejka/judge/tasks/list_files.py

zielinskit/kolejka-judge

571df05b12c5a4748d7a2ca4c217b0042acf6b48

[ "MIT" ]

null

import glob import itertools from functools import partial from typing import Tuple, Optional from kolejka.judge.tasks.base import TaskBase class ListFiles(TaskBase): def __init__(self, *args, variable_name): self.files = list(args) self.variable_name = variable_name def execute(self, environment) -> Tuple[Optional[str], Optional[object]]: files = list(itertools.chain.from_iterable(map(partial(glob.glob, recursive=True), self.files))) environment.set_variable(self.variable_name, files) return None, None

29.578947

104

0.729537

71

562

5.633803

0.507042

0.12

0.08

0

0.174377

562

18

105

31.222222

0.862069

0

1

0.153846

false

0

0.384615

0

0.692308

0

null

0

null

0

1

0

1

0

2

504170f7d179aab0a2ca38addb3c52b1e0a07920

519

py

Python

ExIt/Expert/BaseExpert.py

LarsChrWiik/Expert-Iteration-Algorithmic-Comparison

daed2972159c451be19892ee31c413d60dd2f987

[ "MIT" ]

1

2019-03-01T15:46:06.000Z

ExIt/Expert/BaseExpert.py

LarsChrWiik/Expert-Iteration

daed2972159c451be19892ee31c413d60dd2f987

[ "MIT" ]

null

ExIt/Expert/BaseExpert.py

LarsChrWiik/Expert-Iteration

daed2972159c451be19892ee31c413d60dd2f987

[ "MIT" ]

null

from ExIt.Apprentice import BaseApprentice from Games.GameLogic import BaseGame class BaseExpert: """ Class for the tree search algorithm used for policy improvement """ def __init__(self): self.__name__ = type(self).__name__ def search(self, state: BaseGame, predictor: BaseApprentice, search_time, use_exploration_policy): """ Do policy improvement for a given state. :return: a_explore, a_optimal, soft-z """ raise NotImplementedError("Please Implement this method")

32.4375

102

0.722543

62

519

5.774194

0.677419

0.094972

0

0.196532

519

15

103

34.6

0.858513

0.27553

0

0.07932

0

1

0.285714

false

0

0.285714

0

0.714286

0

null

0

null

0

1

0

1

0

2

5044725258a6a777f86c0f33b6d96e0f8f308a62

1,235

py

Python

monasca_common/kafka_lib/partitioner/base.py

zhangjm12/monasca-common

2ebc766534eba6163e98b94a1f114ece18739fff

[ "Apache-2.0" ]

26

2015-10-18T02:54:54.000Z

2022-02-15T01:36:41.000Z

monasca_common/kafka_lib/partitioner/base.py

zhangjm12/monasca-common

2ebc766534eba6163e98b94a1f114ece18739fff

[ "Apache-2.0" ]

18

2019-11-01T13:03:36.000Z

2022-02-16T02:28:52.000Z

monasca_common/kafka_lib/partitioner/base.py

zhangjm12/monasca-common

2ebc766534eba6163e98b94a1f114ece18739fff

[ "Apache-2.0" ]

22

2016-06-01T11:47:17.000Z

2020-02-11T14:41:45.000Z

# Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. class Partitioner(object): """ Base class for a partitioner """ def __init__(self, partitions): """ Initialize the partitioner Arguments: partitions: A list of available partitions (during startup) """ self.partitions = partitions def partition(self, key, partitions=None): """ Takes a string key and num_partitions as argument and returns a partition to be used for the message Arguments: key: the key to use for partitioning partitions: (optional) a list of partitions. """ raise NotImplementedError('partition function has to be implemented')

33.378378

77

0.680972

160

1,235

5.225

0.56875

0.07177

0.0311

0.038278

0

0.004334

0.252632

1,235

36

78

34.305556

0.901408

0.690688

0

0.152672

0

1

0.4

false

0

0.6

0

null

0

null

0

1

0

1

0

2

504a5158dee21a88d36bd8c0ab457b382a4195ba

143

py

Python

Python/CodingBat/string_times.py

dvt32/cpp-journey

afd7db7a1ad106c41601fb09e963902187ae36e6

[ "MIT" ]

1

2018-05-24T11:30:05.000Z

Python/CodingBat/string_times.py

dvt32/cpp-journey

afd7db7a1ad106c41601fb09e963902187ae36e6

[ "MIT" ]

null

Python/CodingBat/string_times.py

dvt32/cpp-journey

afd7db7a1ad106c41601fb09e963902187ae36e6

[ "MIT" ]

2

2017-08-11T06:53:30.000Z

2017-08-29T12:07:52.000Z

# http://codingbat.com/prob/p193507 def string_times(str, n): result = "" for i in range(0, n): result += str return result

14.3

35

0.601399

21

143

4.047619

0.809524

0.164706

0

0.066038

0.258741

143

9

36

15.888889

0.735849

0.230769

0

1

0.2

false

0

0.4

0

1

0

null

0

1

0

null

0

2

504e0deae6fdb470fcb220ab052c73d97c382d30

636

py

Python

recipe_server/recipeView.py

Shouyin/Recipe

dffaafdebefd7c39a1438444db910f5d7943cf1f

[ "MIT" ]

null

recipe_server/recipeView.py

Shouyin/Recipe

dffaafdebefd7c39a1438444db910f5d7943cf1f

[ "MIT" ]

null

recipe_server/recipeView.py

Shouyin/Recipe

dffaafdebefd7c39a1438444db910f5d7943cf1f

[ "MIT" ]

null

from django import http from django.shortcuts import render from django.shortcuts import render_to_response from . import settings from .scripts import logic import os import urllib import json def recipe_html(request): print(os.path.join(settings.BASE_DIR, "recipe_server/static")) return render_to_response("recipe.html") def recipe_api(request): fridge = request.GET["fridge"] reconstructed_string = "" for i in json.loads(fridge): reconstructed_string += i + "\n" recipe = request.GET["recipe"] print(reconstructed_string) return http.HttpResponse(logic.main(reconstructed_string, recipe))

28.909091

70

0.751572

84

636

5.547619

0.452381

0.16309

0.081545

0.107296

0.133047

0

0.154088

636

22

70

28.909091

0.866171

0

0.070644

0

1

0.105263

false

0

0.421053

0

0.631579

0.105263

0

null

0

null

0

1

0

1

0

2

504e2922325d5c9d9b0ab7cf89788990779e8e47

296

py

Python

ua_project_transfer/wf_steps_template.py

UACoreFacilitiesIT/UA-Project_Transfer

0360f20f54a6c9c49dcdb1568a1c961222cb1404

[ "MIT" ]

1

2020-07-14T16:27:25.000Z

ua_project_transfer/wf_steps_template.py

UACoreFacilitiesIT/UA-Project_Transfer

0360f20f54a6c9c49dcdb1568a1c961222cb1404

[ "MIT" ]

null

ua_project_transfer/wf_steps_template.py

UACoreFacilitiesIT/UA-Project_Transfer

0360f20f54a6c9c49dcdb1568a1c961222cb1404

[ "MIT" ]

null

"""A json-like master list of workflows and steps.""" # NOTE: Create a json-like dictionary in the form of: # WF_STEPS = { # env1: { # 1st condition defined in next_steps: { # 2nd condition defined in next_steps: (Workflow Name, Step Name), # }, # }, # } WF_STEPS = {}

24.666667

76

0.608108

40

296

4.4

0.625

0.056818

0.102273

0.25

0.306818

0

0.013761

0.263514

296

11

77

26.909091

0.793578

0.875

0

1

0

false

0

null

0

1

0

1

0

null

0

2

5050238035d838d374850823b3ad1446226e79b5

329

py

Python

tools/exploitation_tools.py

LucaRibeiro/pentestools

2e7a6b9bf51a84aec90944c50a23e882d184ccdc

[ "MIT" ]

1

2021-02-18T16:15:25.000Z

tools/exploitation_tools.py

LucaRibeiro/Pentools

2e7a6b9bf51a84aec90944c50a23e882d184ccdc

[ "MIT" ]

null

tools/exploitation_tools.py

LucaRibeiro/Pentools

2e7a6b9bf51a84aec90944c50a23e882d184ccdc

[ "MIT" ]

null

#!/usr/bin/python3 list = ["Armitage", "Backdoor Factory", "BeEF","cisco-auditing-tool", "cisco-global-exploiter","cisco-ocs","cisco-torch","Commix","crackle", "exploitdb","jboss-autopwn","Linux Exploit Suggester","Maltego Teeth", "Metasploit Framework","MSFPC","RouterSploit","SET","ShellNoob","sqlmap", "THC-IPV6","Yersinia"]

41.125

73

0.714286

38

329

6.184211

0.921053

0

0.00639

0.048632

329

7

74

47

0.744409

0.051672

0

0.742765

0.07074

0

1

0

false

0

null

0

1

0

1

0

null

0

2

50530270ca9767c3a423e4f06bb397a9db26bf9c

1,152

py

Python

web/api/serializer/foodComment.py

bounswe/bounswe2016group2

f5dbba9b78fc03e8fd6a1fc7548de6cd1177a5ad

[ "Apache-2.0" ]

10

2016-02-10T13:57:10.000Z

2021-04-01T14:34:33.000Z

web/api/serializer/foodComment.py

bounswe/bounswe2016group2

f5dbba9b78fc03e8fd6a1fc7548de6cd1177a5ad

[ "Apache-2.0" ]

203

2016-02-14T16:13:15.000Z

2016-12-23T21:27:08.000Z

web/api/serializer/foodComment.py

bounswe/bounswe2016group2

f5dbba9b78fc03e8fd6a1fc7548de6cd1177a5ad

[ "Apache-2.0" ]

2

2017-05-10T18:41:28.000Z

2019-02-27T21:01:18.000Z

from rest_framework import serializers from api.model.foodComment import FoodComment from api.model.food import Food from django.contrib.auth.models import User from api.serializer.user import UserSerializer class FoodCommentSerializer(serializers.ModelSerializer): comment = serializers.CharField(max_length=255) photo = serializers.CharField(max_length=255, allow_null=True, required=False) user = serializers.PrimaryKeyRelatedField(queryset=User.objects.all()) food = serializers.PrimaryKeyRelatedField(queryset=Food.objects.all()) class Meta: model = FoodComment fields = '__all__' depth = 1 class FoodCommentReadSerializer(serializers.ModelSerializer): user = UserSerializer() class Meta: model = FoodComment fields = '__all__' depth = 1 class FoodCommentPureSerializer(serializers.ModelSerializer): user = serializers.PrimaryKeyRelatedField(queryset=User.objects.all()) food = serializers.PrimaryKeyRelatedField(queryset=Food.objects.all()) class Meta: model = FoodComment fields = ('comment', 'user', 'food') depth = 1

27.428571

82

0.730903

115

1,152

7.217391

0.347826

0.077108

0.19759

0.090361

0.507229

0.43012

0.359036

0

0.009554

0.182292

1,152

41

83

28.097561

0.87155

0

0.555556

0

0.025174

0

1

0

false

0

0.185185

0

0.666667

0

null

0

1

0

null

0

1

0

2

505bbd3722c72235b1e0bdbc9e5ed0fb5d0411eb

780

py

Python

solutions/problem_122.py

ksvr444/daily-coding-problem

5d9f488f81c616847ee4e9e48974523ec2d598d7

[ "MIT" ]

1,921

2018-11-13T18:19:56.000Z

2021-11-15T14:25:41.000Z

solutions/problem_122.py

MohitIndian/daily-coding-problem

5d9f488f81c616847ee4e9e48974523ec2d598d7

[ "MIT" ]

2

2019-07-19T01:06:16.000Z

2019-08-01T22:21:36.000Z

solutions/problem_122.py

MohitIndian/daily-coding-problem

5d9f488f81c616847ee4e9e48974523ec2d598d7

[ "MIT" ]

1,066

2018-11-19T19:06:55.000Z

2021-11-13T12:33:56.000Z

def get_max_coins_helper(matrix, crow, ccol, rows, cols): cval = matrix[crow][ccol] if crow == rows - 1 and ccol == cols - 1: return cval down, right = cval, cval if crow < rows - 1: down += get_max_coins_helper( matrix, crow + 1, ccol, rows, cols) if ccol < cols - 1: right += get_max_coins_helper( matrix, crow, ccol + 1, rows, cols) return max(down, right) def get_max_coins(matrix): if matrix: return get_max_coins_helper( matrix, 0, 0, len(matrix), len(matrix[0])) coins = [[0, 3, 1, 1], [2, 0, 0, 4], [1, 5, 3, 1]] assert get_max_coins(coins) == 12 coins = [[0, 3, 1, 1], [2, 8, 9, 4], [1, 5, 3, 1]] assert get_max_coins(coins) == 25

23.636364

57

0.534615

120

780

3.325

0.233333

0.105263

0.192982

0.170426

0.466165

0.408521

0.290727

0.135338

0

0.069811

0.320513

780

32

58

24.375

0.683019

0

0.166667

0

0.083333

1

0.083333

false

0

0.208333

0

null

0

1

0

null

0

2

5060bae394ef43f65427b7889ebd8a488a199475

1,014

py

Python

toughradius/common/event_common.py

geosson/GSRadius

5870e3d055e8366f98b8e65220a1520b5da22f6d

[ "Apache-2.0" ]

1

2019-05-12T15:06:58.000Z

toughradius/common/event_common.py

geosson/GSRadius

5870e3d055e8366f98b8e65220a1520b5da22f6d

[ "Apache-2.0" ]

null

toughradius/common/event_common.py

geosson/GSRadius

5870e3d055e8366f98b8e65220a1520b5da22f6d

[ "Apache-2.0" ]

null

#!/usr/bin/env python # coding:utf-8 from toughlib import dispatch """触发邮件,短信发送公共方法""" def trigger_notify(obj, user_info, **kwargs): if int(obj.get_param_value("webhook_notify_enable", 0)) > 0 and kwargs.get('webhook_notify'): dispatch.pub(kwargs['webhook_notify'], user_info, async=False) if int(obj.get_param_value("mail_notify_enable", 0)) > 0: if obj.get_param_value("mail_mode", 'smtp') == 'toughcloud' and \ obj.get_param_value("toughcloud_license", None) and kwargs.get('toughcloud_mail'): dispatch.pub(kwargs['toughcloud_mail'], user_info, async=False) if obj.get_param_value("mail_mode", 'smtp') == 'smtp' and kwargs.get('smtp_mail'): dispatch.pub(kwargs['smtp_mail'], user_info, async=False) if int(obj.get_param_value("sms_notify_enable", 0)) > 0 and \ obj.get_param_value("toughcloud_license", None) and kwargs.get('toughcloud_sms'): dispatch.pub(kwargs['toughcloud_sms'], user_info, async=False)

39

98

0.68146

143

1,014

4.566434

0.272727

0.064319

0.117917

0.171516

0.526799

0.473201

0.401225

0.309342

0

0.008304

0.168639

1,014

25

99

40.56

0.766311

0.032544

0

0.246347

0.021921

0

null

0

0.076923

null

0

null

0

1

0

null

0

1

0

2

ac94d7600e1dceeb8d2024e62d34864ff7ca1d58

2,041

py

Python

app/models/admin.py

ShuaiGao/mini-shop-server

8a72b2d457bba8778e97637027ffa82bfa11e8a9

[ "MIT" ]

null

app/models/admin.py

ShuaiGao/mini-shop-server

8a72b2d457bba8778e97637027ffa82bfa11e8a9

[ "MIT" ]

1

2019-07-08T12:32:29.000Z

app/models/admin.py

ShuaiGao/mini-shop-server

8a72b2d457bba8778e97637027ffa82bfa11e8a9

[ "MIT" ]

null

# _*_ coding: utf-8 _*_ """ Created by Allen7D on 2018/6/16. """ import os.path as op from flask_admin import Admin, BaseView, expose from flask import render_template, redirect, url_for from flask_admin.contrib.sqla import ModelView from flask_admin.contrib.fileadmin import FileAdmin from flask_admin import form from app.models.base import db from app.models.user import User from app.models.banner import BannerView from app.models.user_address import UserAddressView from app.models.product import ProductView from app.models.category import CategoryView __author__ = 'Allen7D' from wtforms.fields import SelectField class HomeView(BaseView): @expose('/') def index(self): return self.render("admin.html") class MyView(ModelView): # Disable model creation # can_create = False can_delete = False # Override displayed fields column_exclude_list = ['delete_time', 'update_time', 'create_time', 'status'] column_list = ('email', 'nickname', 'auth') column_labels = { 'email': u"邮件", 'nickname':u"头像", 'auth':u"权限" } form_extra_fields = { 'auth':form.Select2Field('权限',choices=[('1','权限1'),('2','权限2')]) } # form_overrides = dict(auth=SelectField) # form_args = dict( # # Pass the choices to the `SelectField` # auth=dict( # choices=[(1, '超级管理员'), (10, '普通管理员'), (100, '普通用户')] # )) def __init__(self, session, **kwargs): # You can pass name add other parameters if you want to super(MyView, self).__init__(User, session, **kwargs) # @expose("/new/", methods=("GET", "POST")) # def create_view(self): # return self.render("create_user.html") def CreateAdminView(admin): path = op.join(op.dirname(__file__), u'../static') admin.add_view(FileAdmin(path, u'/static', name = '文件管理')) admin.add_view(BannerView(db.session, name=u'轮播图')) admin.add_view(MyView(db.session, name=u'用户管理')) admin.add_view(ProductView(db.session, name=u'商品管理')) admin.add_view(CategoryView(db.session, name=u'商品分类')) admin.add_view(UserAddressView(db.session, name=u'地址管理'))

27.958904

78

0.709456

284

2,041

4.929577

0.433099

0.03

0.055714

0.05

0

0.011986

0.141597

2,041

72

79

28.347222

0.7871

0.234199

0

0.097529

0

1

0.075

false

0

0.325

0.025

0.6

0

null

0

null

0

1

0

1

0

2

ac9516fa184eda7179ab54abc6a3a63da22f79c3

9,334

py

Python

MKCommand.py

the-snowwhite/Machinekit-Workbench

3e0c3ae55e67553bd599a3010ccf3a0392212333

[ "MIT" ]

8

2019-09-27T18:45:51.000Z

2020-02-27T09:58:10.000Z

MKCommand.py

the-snowwhite/Machinekit-Workbench

3e0c3ae55e67553bd599a3010ccf3a0392212333

[ "MIT" ]

null

MKCommand.py

the-snowwhite/Machinekit-Workbench

3e0c3ae55e67553bd599a3010ccf3a0392212333

[ "MIT" ]

3

2019-10-19T00:18:41.000Z

2019-11-17T19:58:44.000Z

# Classes implementing the different commands that can be sent to MK # The implemented classes do not cover the complete functional set of MK # but are what is required to implement a basic UI. import enum import machinetalk.protobuf.message_pb2 as MESSAGE import machinetalk.protobuf.status_pb2 as STATUS import machinetalk.protobuf.types_pb2 as TYPES class MKCommandStatus(enum.Enum): '''An enumeration used to track a command through its entire lifetime.''' Created = 0 Sent = 1 Executed = 2 Completed = 3 Obsolete = 4 class MKCommand(object): '''Base class for all commands implementing the general framework.''' def __init__(self, command): self.msg = MESSAGE.Container() self.msg.type = command self.state = MKCommandStatus.Created def __str__(self): return self.__class__.__name__ def expectsResponses(self): '''Overwrite and return False if the specific command does not get a response message. Most commands do get a response so the default is to return True''' return True def serializeToString(self): return self.msg.SerializeToString() def msgSent(self): '''Called by the framework when the command was sent to MK''' self.state = MKCommandStatus.Sent def msgExecuted(self): '''Called by the framework when the command was executed by MK''' self.state = MKCommandStatus.Executed def msgCompleted(self): '''Called by the framework when the command has completed''' self.state = MKCommandStatus.Completed def msgObsolete(self): '''Called by the framework when the command has become obsolete''' self.state = MKCommandStatus.Obsolete def isExecuted(self): '''Returns True if the command has been executed by MK''' return self.state in [MKCommandStatus.Executed, MKCommandStatus.Completed] def isCompleted(self): '''Returns True if the command has completed''' return self.state == MKCommandStatus.Completed def isObsolete(self): '''Returns True if the command is obsolete and can be removed''' return self.state == MKCommandStatus.Obsolete def statusString(self): '''Return command's status as string.''' return self.state.name class MKCommandExecute(MKCommand): '''Base class for all commands sent to the 'execute' interpreter.''' def __init__(self, command): MKCommand.__init__(self, command) self.msg.interp_name = 'execute' class MKCommandPreview(MKCommand): '''Base class for all commands sent to the 'preview' interpreter.''' def __init__(self, command): MKCommand.__init__(self, command) self.msg.interp_name = 'preview' class MKCommandTaskSetState(MKCommandExecute): '''Base class for setting the state of task variables.''' def __init__(self, state): MKCommandExecute.__init__(self, TYPES.MT_EMC_TASK_SET_STATE) self.msg.emc_command_params.task_state = state class MKCommandEstop(MKCommandTaskSetState): '''Command to engage or disengage the E-Stop. on=True means the E-Stop is pressed and MK will ignore all other commands.''' def __init__(self, on): MKCommandTaskSetState.__init__(self, STATUS.EMC_TASK_STATE_ESTOP if on else STATUS.EMC_TASK_STATE_ESTOP_RESET) class MKCommandPower(MKCommandTaskSetState): '''Command to power MK on or off.''' def __init__(self, on): MKCommandTaskSetState.__init__(self, STATUS.EMC_TASK_STATE_ON if on else STATUS.EMC_TASK_STATE_OFF) class MKCommandOpenFile(MKCommand): '''Command to open a file, either for 'executing' it or for 'previewing' it.''' def __init__(self, filename, preview): if preview: MKCommandPreview.__init__(self, TYPES.MT_EMC_TASK_PLAN_OPEN) else: MKCommandExecute.__init__(self, TYPES.MT_EMC_TASK_PLAN_OPEN) self.msg.emc_command_params.path = filename class MKCommandTaskRun(MKCommand): '''Command to start execution of the currently opened file - or to display its preview.''' def __init__(self, preview, line=0): if preview: MKCommandPreview.__init__(self, TYPES.MT_EMC_TASK_PLAN_RUN) else: MKCommandExecute.__init__(self, TYPES.MT_EMC_TASK_PLAN_RUN) self.msg.emc_command_params.line_number = line self.preview = preview def expectsResponses(self): return not self.preview class MKCommandTaskStep(MKCommandExecute): '''Command to execute a single step of the current task (from its current line).''' def __init__(self): MKCommandExecute.__init__(self, TYPES.MT_EMC_TASK_PLAN_STEP) class MKCommandTaskPause(MKCommandExecute): '''Command to pause execution of the current task.''' def __init__(self): MKCommandExecute.__init__(self, TYPES.MT_EMC_TASK_PLAN_PAUSE) class MKCommandTaskResume(MKCommandExecute): '''Command to resume a currently paused task.''' def __init__(self): MKCommandExecute.__init__(self, TYPES.MT_EMC_TASK_PLAN_RESUME) class MKCommandTaskReset(MKCommandExecute): '''Command to reset task execution. This clears any paused state and resets progress to line 0.''' def __init__(self, preview): if preview: MKCommandPreview.__init__(self, TYPES.MT_EMC_TASK_PLAN_INIT) else: MKCommandExecute.__init__(self, TYPES.MT_EMC_TASK_PLAN_INIT) class MKCommandAxisHome(MKCommand): '''Command to initiate homing (or unhoming) of a gifen axis. The homing itself is done by MK without any need of interaction. The staging and sequencing of homing multiple axes has to be orchestrated by the UI though.''' def __init__(self, index, home=True): MKCommand.__init__(self, TYPES.MT_EMC_AXIS_HOME if home else TYPES.MT_EMC_AXIS_UNHOME) self.msg.emc_command_params.index = index def __str__(self): return "MKCommandAxisHome[%d]" % (self.msg.emc_command_params.index) class MKCommandTaskExecute(MKCommandExecute): '''Command for executing arbitrary commands and command sequences.''' def __init__(self, cmd): MKCommandExecute.__init__(self, TYPES.MT_EMC_TASK_PLAN_EXECUTE) self.msg.emc_command_params.command = cmd class MKCommandTaskSetMode(MKCommandExecute): '''Command to set a specific task mode. Valid modes are: * STATUS.EmcTaskModeType.EMC_TASK_MODE_AUTO ... required for the execute interpreter to take control * STATUS.EmcTaskModeType.EMC_TASK_MODE_MDI ... required to issue individual g-code commands * STATUS.EmcTaskModeType.EMC_TASK_MODE_MANUAL ... required for jogging ''' def __init__(self, mode): MKCommandExecute.__init__(self, TYPES.MT_EMC_TASK_SET_MODE) self.msg.emc_command_params.task_mode = mode class MKCommandTaskAbort(MKCommandExecute): '''Command to abort the current task.''' def __init__(self): MKCommandExecute.__init__(self, TYPES.MT_EMC_TASK_ABORT) class MKCommandAxisAbort(MKCommandExecute): '''Command to abort the current axis command - mostly used to stop the active jogging command.''' def __init__(self, index): MKCommandExecute.__init__(self, TYPES.MT_EMC_AXIS_ABORT) self.msg.emc_command_params.index = index class MKCommandAxisJog(MKCommandExecute): '''Command to initiate jogging. There are two different types of jog, distance and incremental. Incremental jogging initiates the jog which will continue until either a new jog command is sent or a MKCommandAxisAbort command is sent. This puts some requirements on the UI's reliability and capability of sending that termination command. Distance jogging is marginally safer because MK will silently ignore a distance jog if it exceeds the axis' limit. There is no indication that the command was not executed and the tool is still at the same position as it was before, making the next jog a risky manouver. This is important for scripted jog sequences like a contour around the tasks boundaries. It is the UI's responsibility to extract proper values for velocity and distance. ''' def __init__(self, index, velocity, distance = None): self.index = index self.velocity = velocity self.distance = distance if distance is None: MKCommandExecute.__init__(self, TYPES.MT_EMC_AXIS_JOG) else: MKCommandExecute.__init__(self, TYPES.MT_EMC_AXIS_INCR_JOG) self.msg.emc_command_params.distance = distance self.msg.emc_command_params.index = index self.msg.emc_command_params.velocity = velocity def __str__(self): if self.distance: return "AxisJog(%d, %.2f, %.2f)" % (self.index, self.velocity, self.distance) return "AxisJog(%d, %.2f, -)" % (self.index, self.velocity) class MKCommandTrajSetScale(MKCommand): '''Command to overwrite the feed rate or rapid speed of the tool bit. scale is a multiplier of the configured speed.''' def __init__(self, scale, rapid=False): if rapid: MKCommand.__init__(self, TYPES.MT_EMC_TRAJ_SET_RAPID_SCALE) else: MKCommand.__init__(self, TYPES.MT_EMC_TRAJ_SET_SCALE) self.msg.emc_command_params.scale = scale

42.235294

123

0.714378

1,198

9,334

5.300501

0.234558

0.052913

0.031496

0.044882

0.367717

0.292913

0.251024

0.199213

0.165512

0.105039

0

0.001756

0.206985

9,334

220

124

42.427273

0.85612

0.349261

0

0.206107

0

0.013358

0.003597

0

1

0.251908

false

0

0.030534

0.557252

0

null

0

null

0

1

0

1

0

2

ac97d43733100708fa2b0d168201fd6612736104

2,185

py

Python

GearC/material.py

cfernandesFEUP/Gear-Calculation

c15249c23f97e1168e3316ad5e27ed747758353a

[ "Unlicense" ]

3

2020-09-01T13:19:10.000Z

2021-12-13T13:59:00.000Z

GearC/material.py

cfernandesFEUP/Gear-Calculation

c15249c23f97e1168e3316ad5e27ed747758353a

[ "Unlicense" ]

null

GearC/material.py

cfernandesFEUP/Gear-Calculation

c15249c23f97e1168e3316ad5e27ed747758353a

[ "Unlicense" ]

null

## LIBRARY OF MATERIALS ####################################################### def matp(mat, Tbulk, NL): import numpy as np E, v, cpg, kg, rohg, sigmaHlim, sigmaFlim = [np.zeros(2) for _ in range(7)] for i in range(len(E)): if mat[i] == 'POM': E[i] = 3.2e9 # 2900 MPa (min) - 3500 MPa (max) v[i] = 0.35 cpg[i] = 1465 # J/kg.K kg[i] = 0.3 # W/m.K (0.23 (min) 0.37 (max)) rohg[i] = 1415 # 1410 (min) - 1420 (max) sigmaHlim[i] = 36 - 0.0012*Tbulk**2 + (1000 - 0.025*Tbulk**2)*NL** - 0.21 sigmaFlim[i] = 26 - 0.0025*Tbulk**2 + 400*NL** - 0.2 elif mat[i] == 'PEEK': E[i] = 3.65e9 v[i] = 0.38 cpg[i] = 1472 # 1443 - 1501 kg[i] = 0.25 # W/m.K rohg[i] = 1320 sigmaHlim[i] = 36 - 0.0012*Tbulk**2 + (1000 - 0.025*Tbulk**2)*NL** - 0.21 # Nylon (PA66) sigmaFlim[i] = 30 - 0.22*Tbulk + (4600 - 900*Tbulk**0.3)*NL**( - 1/3) # Nylon (PA66) elif mat[i] == 'PA66': E[i] = 1.85e9 # 1700 MPa (min) - 2000 MPa (max) v[i] = 0.3 # 0.25 - 0.35 cpg[i] = 1670 # J/kg.K kg[i] = 0.26 # W/m.K (0.25 (min) 0.27 (max)) rohg[i] = 1140 # 1130 (min) - 1150 (max)) sigmaHlim[i] = 36 - 0.0012*Tbulk**2 + (1000 - 0.025*Tbulk**2)*NL** - 0.21 sigmaFlim[i] = 30 - 0.22*Tbulk + (4600 - 900*Tbulk**0.3)*NL**( - 1/3) elif mat[i] == 'ADI': E[i] = 210e9 v[i] = 0.26 # 0.22 (min) 0.30 (max) cpg[i] = 460.548 kg[i] = 55 # W/m.K rohg[i] = 7850 sigmaHlim[i] = 1500 sigmaFlim[i] = 430 elif mat[i] == 'STEEL': E[i] = 206e9 v[i] = 0.3 # 0.22 (min) 0.30 (max) cpg[i] = 465 kg[i] = 46 # W/m.K rohg[i] = 7830 sigmaHlim[i] = 1500 sigmaFlim[i] = 430 return E, v, cpg, kg, rohg, sigmaHlim, sigmaFlim

46.489362

101

0.381236

318

2,185

2.616352

0.295597

0.019231

0.018029

0.046875

0.512019

0.454327

0.370192

0.300481

0.262019

0

0.223632

0.422883

2,185

46

102

47.5

0.436162

0.150114

0

0.244444

0

0.010945

0

1

0.022222

false

0

0.022222

0

0.066667

0

null

0

1

0

1

0

null

0

2

aca120dbe457333e15ac5e2607f6815fc7e3bb5a

4,465

py

Python

deepchem/data/tests/test_shape.py

deloragaskins/deepchem

234ab699cdb997e5963966a8b6926cb2cda7c064

[ "MIT" ]

3,782

2016-02-21T03:53:11.000Z

2022-03-31T16:10:26.000Z

deepchem/data/tests/test_shape.py

deloragaskins/deepchem

234ab699cdb997e5963966a8b6926cb2cda7c064

[ "MIT" ]

2,666

2016-02-11T01:54:54.000Z

2022-03-31T11:14:33.000Z

deepchem/data/tests/test_shape.py

deloragaskins/deepchem

234ab699cdb997e5963966a8b6926cb2cda7c064

[ "MIT" ]

1,597

2016-02-21T03:10:08.000Z

2022-03-30T13:21:28.000Z

import deepchem as dc import numpy as np import os def test_numpy_dataset_get_shape(): """Test that get_shape works for numpy datasets.""" num_datapoints = 100 num_features = 10 num_tasks = 10 # Generate data X = np.random.rand(num_datapoints, num_features) y = np.random.randint(2, size=(num_datapoints, num_tasks)) w = np.random.randint(2, size=(num_datapoints, num_tasks)) ids = np.array(["id"] * num_datapoints) dataset = dc.data.NumpyDataset(X, y, w, ids) X_shape, y_shape, w_shape, ids_shape = dataset.get_shape() assert X_shape == X.shape assert y_shape == y.shape assert w_shape == w.shape assert ids_shape == ids.shape def test_disk_dataset_get_shape_single_shard(): """Test that get_shape works for disk dataset.""" num_datapoints = 100 num_features = 10 num_tasks = 10 # Generate data X = np.random.rand(num_datapoints, num_features) y = np.random.randint(2, size=(num_datapoints, num_tasks)) w = np.random.randint(2, size=(num_datapoints, num_tasks)) ids = np.array(["id"] * num_datapoints) dataset = dc.data.DiskDataset.from_numpy(X, y, w, ids) X_shape, y_shape, w_shape, ids_shape = dataset.get_shape() assert X_shape == X.shape assert y_shape == y.shape assert w_shape == w.shape assert ids_shape == ids.shape def test_disk_dataset_get_shape_multishard(): """Test that get_shape works for multisharded disk dataset.""" num_datapoints = 100 num_features = 10 num_tasks = 10 # Generate data X = np.random.rand(num_datapoints, num_features) y = np.random.randint(2, size=(num_datapoints, num_tasks)) w = np.random.randint(2, size=(num_datapoints, num_tasks)) ids = np.array(["id"] * num_datapoints) dataset = dc.data.DiskDataset.from_numpy(X, y, w, ids) # Should now have 10 shards dataset.reshard(shard_size=10) X_shape, y_shape, w_shape, ids_shape = dataset.get_shape() assert X_shape == X.shape assert y_shape == y.shape assert w_shape == w.shape assert ids_shape == ids.shape def test_disk_dataset_get_legacy_shape_single_shard(): """Test that get_shape works for legacy disk dataset.""" # This is the shape of legacy_data num_datapoints = 100 num_features = 10 num_tasks = 10 current_dir = os.path.dirname(os.path.abspath(__file__)) # legacy_dataset is a dataset in the legacy format kept around for testing # purposes. data_dir = os.path.join(current_dir, "legacy_dataset") dataset = dc.data.DiskDataset(data_dir) X_shape, y_shape, w_shape, ids_shape = dataset.get_shape() assert X_shape == (num_datapoints, num_features) assert y_shape == (num_datapoints, num_tasks) assert w_shape == (num_datapoints, num_tasks) assert ids_shape == (num_datapoints,) def test_disk_dataset_get_legacy_shape_multishard(): """Test that get_shape works for multisharded legacy disk dataset.""" # This is the shape of legacy_data_reshard num_datapoints = 100 num_features = 10 num_tasks = 10 # legacy_dataset_reshard is a sharded dataset in the legacy format kept # around for testing current_dir = os.path.dirname(os.path.abspath(__file__)) data_dir = os.path.join(current_dir, "legacy_dataset_reshard") dataset = dc.data.DiskDataset(data_dir) # Should now have 10 shards assert dataset.get_number_shards() == 10 X_shape, y_shape, w_shape, ids_shape = dataset.get_shape() assert X_shape == (num_datapoints, num_features) assert y_shape == (num_datapoints, num_tasks) assert w_shape == (num_datapoints, num_tasks) assert ids_shape == (num_datapoints,) def test_get_shard_size(): """ Test that using ids for getting the shard size does not break the method. The issue arises when attempting to load a dataset that does not have a labels column. The create_dataset method of the DataLoader class sets the y to None in this case, which causes the existing implementation of the get_shard_size() method to fail, as it relies on the dataset having a not None y column. This consequently breaks all methods depending on this, like the splitters for example. Note ---- DiskDatasets without labels cannot be resharded! """ current_dir = os.path.dirname(os.path.abspath(__file__)) file_path = os.path.join(current_dir, "reaction_smiles.csv") featurizer = dc.feat.DummyFeaturizer() loader = dc.data.CSVLoader( tasks=[], feature_field="reactions", featurizer=featurizer) dataset = loader.create_dataset(file_path) assert dataset.get_shard_size() == 4

33.074074

80

0.738186

695

4,465

4.48777

0.179856

0.1042

0.076948

0.067329

0.73421

0.714332

0.686759

0.678423

0.505931

0

0.01338

0.163046

4,465

134

81

33.320896

0.821247

0.253303

0

0.746835

0

0.021413

0.00673

0

0.278481

1

0.075949

false

0

0.037975

0

0.113924

0

null

0

1

0

1

0

null

0

2

acad836bb967db6d3ec59df7b4fb252d32176a06

905

py

Python

src/the_teleop/test_popout.py

NuenoB/TheTeleop

57e3f745d391743fac408fb44bf20ffad945aa19

[ "BSD-3-Clause" ]

null

src/the_teleop/test_popout.py

NuenoB/TheTeleop

57e3f745d391743fac408fb44bf20ffad945aa19

[ "BSD-3-Clause" ]

null

src/the_teleop/test_popout.py

NuenoB/TheTeleop

57e3f745d391743fac408fb44bf20ffad945aa19

[ "BSD-3-Clause" ]

null

#! /usr/bin/env python import os import rospy import rospkg from readbag import restore from qt_gui.plugin import Plugin from python_qt_binding.QtCore import Qt from python_qt_binding import loadUi from python_qt_binding.QtGui import QFileDialog, QGraphicsView, QIcon, QWidget from PyQt4 import QtGui, QtCore from example_ui import * from PyQt4 import QtGui from v2 import Ui_addbag class Form1(QtGui.QWidget, Ui_addbag): def __init__(self, parent=None): QtGui.QWidget.__init__(self, parent) self.setupUi(self) self.pushButton_2.clicked.connect(self.handleButton) self.window2 = None def handleButton(self): if self.window2 is None: self.window2 = Form1(self) self.window2.show() self.hide() def pop(): import sys app = QtGui.QApplication(sys.argv) window = Form1() window.show() sys.exit(app.exec_())

23.815789

78

0.709392

124

905

5.016129

0.427419

0.07074

0.057878

0.09164

0

0.015342

0.207735

905

38

79

23.815789

0.852162

0.023204

0

1

0.103448

false

0

0.448276

0

0.586207

0

null

0

null

0

1

0

1

0

2

acb17cfb85ffc305e2395079620b49264e4e9636

377

py

Python

active/setup.py

jordan-schneider/value-alignment-verification

f2c877b16dfefa7cd8089b7aa3fe084ab907235e

[ "MIT" ]

null

active/setup.py

jordan-schneider/value-alignment-verification

f2c877b16dfefa7cd8089b7aa3fe084ab907235e

[ "MIT" ]

2

2020-05-25T14:50:11.000Z

2021-01-18T20:23:30.000Z

active/setup.py

jordan-schneider/batch-active-preference-based-learning

f2c877b16dfefa7cd8089b7aa3fe084ab907235e

[ "MIT" ]

1

2021-08-24T18:22:13.000Z

from distutils.core import setup from pathlib import Path # TODO(joschnei): Add typing info setup( name="active", version="0.1", packages=["active",], install_requires=[ "scipy", "numpy", "driver @ git+https://github.com/jordan-schneider/driver-env.git#egg=driver", ], package_data = { 'active': ['py.typed'], }, )

19.842105

85

0.588859

43

377

5.116279

0.813953

0

0.007042

0.246684

377

18

86

20.944444

0.767606

0.082228

0

0.066667

0.328488

0

0.055556

0

1

0

true

0

0.133333

0

0.133333

0

null

0

null

0

1

0

1

0

2

ace2b1a29a3abb15aedb474de4948707e3d81eeb

416

py

Python

erpnext_feature_board/hook_events/review_request.py

akurungadam/erpnext_feature_board

8c99b4dfaa79d86d8e8b46fa1bf235d0bfa471e0

[ "MIT" ]

15

2021-05-31T16:29:22.000Z

2021-12-02T20:18:32.000Z

erpnext_feature_board/hook_events/review_request.py

akurungadam/erpnext_feature_board

8c99b4dfaa79d86d8e8b46fa1bf235d0bfa471e0

[ "MIT" ]

18

2021-06-01T07:39:08.000Z

2021-07-14T09:02:35.000Z

erpnext_feature_board/hook_events/review_request.py

akurungadam/erpnext_feature_board

8c99b4dfaa79d86d8e8b46fa1bf235d0bfa471e0

[ "MIT" ]

6

2021-06-01T07:19:53.000Z

2021-12-28T20:06:25.000Z

import frappe def delete_approved_build_requests(): """ Scheduled hook to delete approved Review Requests for changing site deployments. """ approved_build_requests = frappe.get_all( "Review Request", filters={ "request_type": ["in", ["Build", "Upgrade", "Delete"]], "request_status": "Approved", }, ) for request in approved_build_requests: frappe.delete_doc("Review Request", request.name)

21.894737

81

0.71875

49

416

5.877551

0.510204

0.135417

0.21875

0.1875

0

0.151442

416

18

82

23.111111

0.815864

0.192308

0

0.251534

0

1

0.090909

false

0

0.090909

0

0.181818

0

null

0

1

0

null

0

2

ace7ab1c03480ac4b4f41e3fb954c1d488666de5

247

py

Python

trustpayments/models/failure_category.py

TrustPayments/python-sdk

6fde6eb8cfce270c3612a2903a845c13018c3bb9

[ "Apache-2.0" ]

2

2020-01-16T13:24:06.000Z

2020-11-21T17:40:17.000Z

postfinancecheckout/models/failure_category.py

pfpayments/python-sdk

b8ef159ea3c843a8d0361d1e0b122a9958adbcb4

[ "Apache-2.0" ]

4

2019-10-14T17:33:23.000Z

2021-10-01T14:49:11.000Z

postfinancecheckout/models/failure_category.py

pfpayments/python-sdk

b8ef159ea3c843a8d0361d1e0b122a9958adbcb4

[ "Apache-2.0" ]

2

2019-10-15T14:17:10.000Z

2021-09-17T13:07:09.000Z

# coding: utf-8 from enum import Enum, unique @unique class FailureCategory(Enum): TEMPORARY_ISSUE = "TEMPORARY_ISSUE" INTERNAL = "INTERNAL" END_USER = "END_USER" CONFIGURATION = "CONFIGURATION" DEVELOPER = "DEVELOPER"

17.642857

39

0.688259

26

247

6.384615

0.615385

0.168675

0

0.005181

0.218623

247

13

40

19

0.854922

0.052632

0

0.229437

0

1

0

false

0

0.125

0

0.875

0

1

0

null

0

null

0

1

0

2

acee87269de38c5afcc9577b696b2d9e96852134

149

py

Python

Questoes/b1_q09_piso.py

viniciusm0raes/python

c4d4f1a08d1e4de105109e1f67fae9fcc20d7fce

[ "MIT" ]

null

Questoes/b1_q09_piso.py

viniciusm0raes/python

c4d4f1a08d1e4de105109e1f67fae9fcc20d7fce

[ "MIT" ]

null

Questoes/b1_q09_piso.py

viniciusm0raes/python

c4d4f1a08d1e4de105109e1f67fae9fcc20d7fce

[ "MIT" ]

null

metros = float(input('Quantos metros de piso vc deseja? ')) preco = 70 total = metros*preco print('O preço total do pedido é: R$ %.2f' % (total))

18.625

59

0.66443

24

149

4.125

0.791667

0

0.024793

0.187919

149

7

60

21.285714

0.793388

0

0.459459

0

1

0

false

0

0.25

1

0

null

0

1

0

null

0

2

acf995ba4adee5652bf497dcac8aaaa0df89b254

702

py

Python

tests/test_day22.py

arcadecoffee/advent-2021

57d24cd6ba6e2b4d7e68ea492b955b73eaad7b6a

[ "MIT" ]

null

tests/test_day22.py

arcadecoffee/advent-2021

57d24cd6ba6e2b4d7e68ea492b955b73eaad7b6a

[ "MIT" ]

null

tests/test_day22.py

arcadecoffee/advent-2021

57d24cd6ba6e2b4d7e68ea492b955b73eaad7b6a

[ "MIT" ]

null

""" Tests for Day 22 """ from day22.module import part_1, part_2, \ FULL_INPUT_FILE, TEST_INPUT_FILE_1, TEST_INPUT_FILE_2, TEST_INPUT_FILE_3 def test_part_1_1(): result = part_1(TEST_INPUT_FILE_1) assert result == 39 def test_part_1_2(): result = part_1(TEST_INPUT_FILE_2) assert result == 590784 def test_part_1_3(): result = part_1(TEST_INPUT_FILE_3) assert result == 474140 def test_part_1_full(): result = part_1(FULL_INPUT_FILE) assert result == 546724 def test_part_2(): result = part_2(TEST_INPUT_FILE_3) assert result == 2758514936282235 def test_part_2_full(): result = part_2(FULL_INPUT_FILE) assert result == 1346544039176841

18.972973

76

0.720798

114

702

3.982456

0.219298

0.198238

0.200441

0.123348

0.473568

0.244493

0

0.141093

0.192308

702

36

77

19.5

0.659612

0.022792

0

0.3

1

0.3

false

0

0.05

0

0.35

0

null

0

1

0

null

0

1

0

2

4a21f3279034131e287608aa7f238be08a6231f6

986

py

Python

project4github/largest_digit.py

chinkaih319/SC101

25c179c96e0a2bbc4e47768c029ee4bf49e06245

[ "MIT" ]

null

project4github/largest_digit.py

chinkaih319/SC101

25c179c96e0a2bbc4e47768c029ee4bf49e06245

[ "MIT" ]

null

project4github/largest_digit.py

chinkaih319/SC101

25c179c96e0a2bbc4e47768c029ee4bf49e06245

[ "MIT" ]

null

""" File: largest_digit.py Name: ---------------------------------- This file recursively prints the biggest digit in 5 different integers, 12345, 281, 6, -111, -9453 If your implementation is correct, you should see 5, 8, 6, 1, 9 on Console. """ def main(): print(find_largest_digit(12345)) # 5 print(find_largest_digit(281)) # 8 print(find_largest_digit(6)) # 6 print(find_largest_digit(-111)) # 1 print(find_largest_digit(-9453)) # 9 def find_largest_digit(n): """ :param n: :return: """ time = 0 bs = 0 return helper(n, time, bs) def helper(n, time, bs): if 0 <= n <= 10: return n else: if n < 10 ** (time+1): if n < 0: return helper(-n, time, bs) else: first = n // (10 ** time) if first > bs: return first else: return bs else: sq = n//(10 ** time) - (n//(10 ** (time + 1))) * 10 if sq > bs: bs = sq time += 1 return helper(n, time, bs) if __name__ == '__main__': main()

18.603774

54

0.558824

149

986

3.557047

0.315436

0.158491

0.181132

0.198113

0.143396

0.075472

0

0.085048

0.260649

986

52

55

18.961538

0.641975

0.271805

0

0.193548

0

0.011494

0

1

0.096774

false

0

0.290323

0.16129

0

null

0

1

0

null

0

2

c57cdef697b1ae7480e0770028e9b4a5e38b5778

2,155

py

Python

stock/migrations/0020_stockproductcds_stockproductdis.py

unicefburundi/paludisme

775af3c15349d4437e3780690eb6fa2ea8622ee7

[ "MIT" ]

1

2017-04-26T10:09:12.000Z

stock/migrations/0020_stockproductcds_stockproductdis.py

srugano/paludisme

775af3c15349d4437e3780690eb6fa2ea8622ee7

[ "MIT" ]

null

stock/migrations/0020_stockproductcds_stockproductdis.py

srugano/paludisme

775af3c15349d4437e3780690eb6fa2ea8622ee7

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Generated by Django 1.11.5 on 2017-09-10 20:53 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ("bdiadmin", "0013_auto_20170319_1415"), ("stock", "0019_stockproductprov"), ] operations = [ migrations.CreateModel( name="StockProductCDS", fields=[ ( "id", models.AutoField( auto_created=True, primary_key=True, serialize=False, verbose_name="ID", ), ), ("year", models.PositiveIntegerField(default=2017)), ("week", models.CharField(max_length=3)), ("product", models.CharField(max_length=50)), ("quantity", models.FloatField(default=0.0)), ( "cds", models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="bdiadmin.CDS" ), ), ], ), migrations.CreateModel( name="StockProductDis", fields=[ ( "id", models.AutoField( auto_created=True, primary_key=True, serialize=False, verbose_name="ID", ), ), ("year", models.PositiveIntegerField(default=2017)), ("week", models.CharField(max_length=3)), ("product", models.CharField(max_length=50)), ("quantity", models.FloatField(default=0.0)), ( "district", models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, to="bdiadmin.District", ), ), ], ), ]

32.164179

86

0.429234

155

2,155

5.832258

0.445161

0.035398

0.079646

0.106195

0.615044

0

0.047496

0.462645

2,155

66

87

32.651515

0.733161

0.031555

0

0.644068

1

0

0.086852

0.021113

0

1

0

false

0

0.050847

0

0.101695

0

null

0

1

0

1

0

null

0

2

c584ba722dcfc049b1e65f8d0be9570ef5cdc8bf

1,566

py

Python

KivyApp/login.py

yeltayzhastay/jadenapp

41f593fb897cb6b4e17aeeb1dff4287a9e89f4d9

[ "MIT" ]

null

KivyApp/login.py

yeltayzhastay/jadenapp

41f593fb897cb6b4e17aeeb1dff4287a9e89f4d9

[ "MIT" ]

null

KivyApp/login.py

yeltayzhastay/jadenapp

41f593fb897cb6b4e17aeeb1dff4287a9e89f4d9

[ "MIT" ]

null

import pandas as pd import numpy as np import pickle from sklearn.metrics.pairwise import linear_kernel from sklearn.feature_extraction.text import TfidfVectorizer import csv from kivy.app import App from kivy.uix.gridlayout import GridLayout from kivy.uix.label import Label from kivy.uix.textinput import TextInput class Jaden: _model = None _vector = None _vocabulary = None def __init__(self): self._model = pickle.load(open('_model.sav', 'rb')) self._vector = pickle.load(open('_vectorized.sav', 'rb')) with open('dataset/tarih.csv', newline='', encoding='utf8') as f: reader = csv.reader(f) _vocabulary = list(reader) self._vocabulary = _vocabulary def find_answer(self, question): _cos_sim = linear_kernel(_model.transform([question]), _vector).flatten() _cos_sim = np.ndarray.argsort(-_cos_sim)[:5] _result = [] for i in _cos_sim: _result.append(self._vocabulary[i+1][1]) return _result class LoginScreen(GridLayout): def __init__(self, **kwargs): super(LoginScreen, self).__init__(**kwargs) self.cols = 2 self.add_widget(Label(text='User Name')) self.username = TextInput(multiline=False) self.add_widget(self.username) self.add_widget(Label(text='password')) self.password = TextInput(password=True, multiline=False) self.add_widget(self.password) class MyApp(App): def build(self): return LoginScreen() MyApp().run()

27.473684

81

0.659642

193

1,566

5.124352

0.419689

0.032356

0.052578

0.0364

0.107179

0.06269

0

0.004143

0.229246

1,566

57

82

27.473684

0.815244

0

0.042757

0

1

0.095238

false

0.071429

0.238095

0.02381

0.52381

0

null

0

null

0

1

0

1

0

2

c5924e0b85cfa3c5247ec98d6988bcc8eef21a43

251

py

Python

1 - Beginner/1079.py

andrematte/uri-submissions

796e7fee56650d9e882880318d6e7734038be2dc

[ "MIT" ]

1

2020-09-09T12:48:09.000Z

1 - Beginner/1079.py

andrematte/uri-submissions

796e7fee56650d9e882880318d6e7734038be2dc

[ "MIT" ]

null

1 - Beginner/1079.py

andrematte/uri-submissions

796e7fee56650d9e882880318d6e7734038be2dc

[ "MIT" ]

null

# Uri Online Judge 1079 N = int(input()) for i in range(0,N): Numbers = input() num1 = float(Numbers.split()[0]) num2 = float(Numbers.split()[1]) num3 = float(Numbers.split()[2]) print(((2*num1+3*num2+5*num3)/10).__round__(1))

19.307692

51

0.59761

40

251

3.65

0.625

0.246575

0.349315

0

0.09901

0.195219

251

13

51

19.307692

0.623762

0.083665

0

1

0

false

0

0.142857

0

null

1

0

null

0

2

c597a65becfbb1c61ad0f698d1e6335d34dce5df

4,251

py

Python

viewcount.py

Peace1-zhwiki/MOSIW

13a97842ef53fd500296d3569e548a83e12698d1

[ "MIT" ]

null

viewcount.py

Peace1-zhwiki/MOSIW

13a97842ef53fd500296d3569e548a83e12698d1

[ "MIT" ]

null

viewcount.py

Peace1-zhwiki/MOSIW

13a97842ef53fd500296d3569e548a83e12698d1

[ "MIT" ]

null

import pywikibot from pywikibot import pagegenerators from urllib.request import urlopen import urllib.parse import regex as re #use this rather than "re" to avoid the "look-behind requires fixed-width pattern" error site = pywikibot.Site('zh','wikipedia') cat = pywikibot.Category(site,'Category:連結格式不正確的條目') page_to_write = pywikibot.Page(site, u"User:和平奮鬥救地球/MOSIW") gen = pagegenerators.CategorizedPageGenerator(cat, recurse=True) ilh='(?<!\{\{(Advtranslation|Plant\-translation|Translate|Translating|Translation[ _]+WIP|Translation|Trans|Tran|Voltranslation|Wptranslation|正在翻(譯|译)|(翻)?(譯|译)(中)?)[^\}]*)\[\[\:(aa|ab|ace|ady|af|ak|als|am|an|ang|ar|arc|arz|as|ast|av|ay|az|azb|ba|bar|bat-smg|bcl|be|be-tarask|be-x-old|bg|bh|bi|bjn|bm|bn|bo|bpy|br|bs|bug|bxr|ca|cbk-zam|cdo|ce|ceb|ch|cho|chr|chy|ckb|co|cr|crh|cs|csb|cu|cv|cy|da|de|diq|dsb|dv|dz|ee|egl|eml|el|en|eo|es|et|eu|ext|fa|ff|fi|fiu-vro|fj|fo|fr|frp|frr|fur|fy|ga|gag|gan|gd|gl|glk|gn|gom|got|gsw|als|gu|gv|ha|hak|haw|he|hi|hif|ho|hr|hsb|ht|hu|hy|hz|ia|id|ie|ig|ii|ik|ilo|io|is|it|iu|ja|jp|jam|jbo|jv|ka|kaa|kab|kbd|kg|ki|kj|kk|kl|km|kn|ko|koi|kr|krc|ks|ksh|ku|kv|kw|ky|la|lad|lb|lbe|lez|lg|li|lij|lmo|ln|lo|lrc|lt|ltg|lv|lzh|zh-classical|mai|map-bms|mdf|mg|mh|mhr|mi|min|mk|ml|mn|mo|mr|mrj|ms|mt|mus|mwl|my|myv|mzn|na|nah|nan|zh-min-nan|nap|nb|no|nds|nds-nl|ne|ne|new|ng|nl|nn|no|nov|nrm|nso|nv|ny|oc|olo|om|or|os|pa|pag|pam|pap|pcd|pdc|pfl|pi|pih|pl|pms|pnb|pnt|ps|pt|qu|rm|rmy|rn|ro|roa-rup|roa-tara|ru|rue|rup|rw|sa|sah|sc|scn|sco|sd|se|sg|sgs|sh|si|simple|sk|sl|sm|sn|so|sq|sr|srn|ss|st|stq|su|sv|sw|szl|ta|tcy|te|tet|tg|th|ti|tk|tl|tn|to|tpi|tr|ts|tt|tum|tw|ty|tyv|udm|ug|uk|ur|uz|ve|vec|vep|vi|vls|vo|vro|wa|war|wo|wuu|xal|xh|xmf|yi|yo|yue|zh-yue|za|zea|zu)\:(?!(wiktionary|wikt|wikinews|n|wikibooks|b|wikiquote|q|wikisource|s|oldwikisource|species|wikispecies|wikiversity|v|betawikiversity|wikimedia|foundation|wmf|wikivoyage|voy|commons|c|meta|metawikipedia|m|strategy|incubator|mediawikiwiki|mw|mediawiki|quality|otrswiki|otrs|ticket|phabricator|bugzilla|mediazilla|phab|nost|testwiki|wikidata|d|outreach|outreachwiki|toollabs|wikitech|dbdump|download|gerrit|mail|mailarchive|rev|spcom|sulutil|svn|tools|tswiki|wm2016|wm2017|wmania|User|Wikipedia|MediaWiki|File|Image|WP|Project|Template|Help|Special|U|利用者)\:)|\[\[(JP|JA|EN)\:\:' viewcount = 0 arts = [] views = [] ilh_count = [] edit_num = [] page_size = [] count = 0 html_start = "https://wikimedia.org/api/rest_v1/metrics/pageviews/per-article/zh.wikipedia/all-access/user/" html_end = "/monthly/2020100100/2020110100" tot_num = len(list(cat.articles(namespaces=0,recurse=True))) print(tot_num) for page in gen: count+=1 percentage = 100*count/tot_num art_name = page.title() html_url = html_start + urllib.parse.quote(art_name).replace('/','%2F') + html_end try: urlopen(html_url) except: continue html = urlopen(html_url).read() strhtml = str(html) viewcount = strhtml[strhtml.find('views')+7:-4] if(int(viewcount)<1000): continue art_txt = page.text ilh_num = len(re.findall(ilh,art_txt,re.I)) print(format(percentage, '0.3f'),'%:',art_name,viewcount,ilh_num,page.revision_count(),len(page.text.encode("utf8"))) arts.append(art_name) views.append(int(viewcount)) ilh_count.append(ilh_num) edit_num.append(page.revision_count()) page_size.append(len(page.text.encode("utf8"))) for i in range(len(views)): for j in range(len(views)-i-1): if views[j]<views[j+1]: views[j], views[j+1] = views[j+1], views[j] arts[j], arts[j+1] = arts[j+1], arts[j] ilh_count[j], ilh_count[j+1] = ilh_count[j+1], ilh_count[j] edit_num[j], edit_num[j+1] = edit_num[j+1], edit_num[j] page_size[j], page_size[j+1] = page_size[j+1], page_size[j] writestr = '[[:Category:連結格式不正確的條目]]當中前1,000高瀏覽量（2020年10月份數據）之條目\n\n' writestr += '最後更新時間：~~~~~\n\n' writestr += '{| class="wikitable sortable"\n! 條目名 !! 瀏覽量 !! 不合規跨語言連結總數（粗估） !! 頁面編輯次數 !! 頁面長度（位元組）\n' for i in range(len(views)): if i>=1000: break print(arts[i],views[i]) writestr += '|-\n|[[' + arts[i] + ']]||' + str(views[i]) + '||' + str(ilh_count[i]) + '||' + str(edit_num[i]) + '||' + str(page_size[i]) + '\n' writestr += '|}' page_to_write.text = writestr page_to_write.save(u"使用[[mw:Manual:Pywikibot/zh|Pywikibot]]更新數據") print('Done')

53.810127

1,865

0.717008

801

4,251

3.742821

0.64794

0.007338

0.012008

0.01501

0.073382

0.051368

0.038692

0

0.018369

0.065161

4,251

79

1,866

53.810127

0.736034

0.020466

0

0.032787

0

0.04918

0.54707

0.476945

0

1

0

false

0

0.081967

0

0.081967

0.065574

0

null

0

1

0

1

null

0

2

c5ae3a56e64e4529136d5912d32600637f06223a

417

py

Python

base/migrations/0006_profile_history.py

polarity-cf/arugo

530ea6092702916d63f36308d5a615d118b73850

[ "MIT" ]

34

2021-11-11T14:00:15.000Z

2022-03-16T12:30:04.000Z

base/migrations/0006_profile_history.py

polarity-cf/arugo

530ea6092702916d63f36308d5a615d118b73850

[ "MIT" ]

22

2021-11-11T23:18:14.000Z

2022-03-31T15:07:02.000Z

base/migrations/0006_profile_history.py

polarity-cf/arugo

530ea6092702916d63f36308d5a615d118b73850

[ "MIT" ]

1

2022-03-14T07:35:09.000Z

# Generated by Django 3.2.9 on 2021-11-13 14:43 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('base', '0005_authquery_password'), ] operations = [ migrations.AddField( model_name='profile', name='history', field=models.CharField(default='[]', max_length=1000), ), ]

21.947368

67

0.568345

42

417

5.547619

0.857143

0

0.080139

0.311751

417

18

68

23.166667

0.731707

0.107914

0

1

0

0.122159

0.065341

0

1

0

false

0.083333

0

0.333333

0

null

0

1

0

null

0

1

0

2

c5c4c83c0fcae56bd39628ba7e24ff40a480e5b9

3,553

py

Python

models/van_der_waals.py

HARSHAL-IITB/spa-design-tool

84d250a02cc3f4af56770550c9f559feb524cb07

[ "MIT" ]

null

models/van_der_waals.py

HARSHAL-IITB/spa-design-tool

84d250a02cc3f4af56770550c9f559feb524cb07

[ "MIT" ]

null

models/van_der_waals.py

HARSHAL-IITB/spa-design-tool

84d250a02cc3f4af56770550c9f559feb524cb07

[ "MIT" ]

null

#! /usr/bin/env python # The MIT License (MIT) # # Copyright (c) 2015, EPFL Reconfigurable Robotics Laboratory, # Philip Moseley, philip.moseley@gmail.com # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. import numpy as np #-------------------------------------------------------------------------------- # Material model name. #-------------------------------------------------------------------------------- def name(): return 'vdw' def pname(): return 'Van der Waals' def params(): return 'mu lambda_m alpha beta' def descr(): return 'Van der Waals Model.' #-------------------------------------------------------------------------------- # Function defining the uniaxial stress given strain. #-------------------------------------------------------------------------------- def stressU(x, u, Lm, a, B): L = 1.0+x I1 = np.power(L,2.0) + 2.0*np.power(L,-1.0) I2 = np.power(L,-2.0) + 2.0*L I = (1.0-B)*I1 + B*I2 n = np.sqrt((I-3.0)/(np.power(Lm,2.0)-3.0)) t1 = (1.0/(1.0-n)) - a * np.sqrt(0.5*(I-3.0)) t2 = L*(1.0-B) + B return u*(1.0-np.power(L,-3.0)) * t1 * t2 #-------------------------------------------------------------------------------- # Function defining the biaxial stress given strain. #-------------------------------------------------------------------------------- def stressB(x, u, Lm, a, B): L = 1.0+x I1 = 2.0*np.power(L,2.0) + np.power(L,-4.0) I2 = 2.0*np.power(L,-2.0) + np.power(L,4.0) I = (1.0-B)*I1 + B*I2 n = np.sqrt((I-3.0)/(np.power(Lm,2.0)-3.0)) t1 = (1.0/(1.0-n)) - a * np.sqrt(0.5*(I-3.0)) t2 = 1.0 - B + B*np.power(L,2.0) return u*(L-np.power(L,-5.0)) * t1 * t2 #-------------------------------------------------------------------------------- # Function defining the planar stress given strain. #-------------------------------------------------------------------------------- def stressP(x, u, Lm, a, B): L = 1.0+x I1 = np.power(L,2.0)+np.power(L,-2.0) + 1.0 I2 = I1 I = (1.0-B)*I1 + B*I2 n = np.sqrt((I-3.0)/(np.power(Lm,2.0)-3.0)) t1 = (1.0/(1.0-n)) - a * np.sqrt(0.5*(I-3.0)) return u*(L-np.power(L,-3.0)) * t1 #-------------------------------------------------------------------------------- # Calculate the Ds #-------------------------------------------------------------------------------- def compressibility(v, u, Lm, a, B): u0 = u D1 = 3.0*(1.0-2.0*v) / (u0*(1.0+v)) return [D1]

41.8

82

0.474529

507

3,553

3.323471

0.321499

0.022552

0.061721

0.037389

0.232641

0.222552

0.18635

0.15727

0.152522

0

0.046312

0.179567

3,553

84

83

42.297619

0.531732

0.612722

0

0.342857

0

0.046252

0

1

0.228571

false

0

0.028571

0.114286

0.371429

0

null

0

null

0

1

0

1

0

2

c5ca707dce77fad1c990e8395c01664a2f944aa1

4,980

py

Python

idfy_rest_client/models/person_person_information.py

dealflowteam/Idfy

fa3918a6c54ea0eedb9146578645b7eb1755b642

[ "MIT" ]

null

idfy_rest_client/models/person_person_information.py

dealflowteam/Idfy

fa3918a6c54ea0eedb9146578645b7eb1755b642

[ "MIT" ]

null

idfy_rest_client/models/person_person_information.py

dealflowteam/Idfy

fa3918a6c54ea0eedb9146578645b7eb1755b642

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ idfy_rest_client.models.person_person_information This file was automatically generated for Idfy by APIMATIC v2.0 ( https://apimatic.io ) """ from idfy_rest_client.api_helper import APIHelper class PersonPersonInformation(object): """Implementation of the 'Person.PersonInformation' model. TODO: type model description here. Attributes: firstname (string): TODO: type description here. middlename (string): TODO: type description here. lastname (string): TODO: type description here. date_of_birth (string): TODO: type description here. address (string): TODO: type description here. zip_code (string): TODO: type description here. city (string): TODO: type description here. mobile (string): TODO: type description here. phone (string): TODO: type description here. gender (string): TODO: type description here. raw_json (string): TODO: type description here. request_id (string): TODO: type description here. dead (datetime): TODO: type description here. source (string): TODO: type description here. """ # Create a mapping from Model property names to API property names _names = { "firstname":'Firstname', "middlename":'Middlename', "lastname":'Lastname', "date_of_birth":'DateOfBirth', "address":'Address', "zip_code":'ZipCode', "city":'City', "mobile":'Mobile', "phone":'Phone', "gender":'Gender', "raw_json":'RawJson', "request_id":'RequestId', "dead":'Dead', "source":'Source' } def __init__(self, firstname=None, middlename=None, lastname=None, date_of_birth=None, address=None, zip_code=None, city=None, mobile=None, phone=None, gender=None, raw_json=None, request_id=None, dead=None, source=None, additional_properties = {}): """Constructor for the PersonPersonInformation class""" # Initialize members of the class self.firstname = firstname self.middlename = middlename self.lastname = lastname self.date_of_birth = date_of_birth self.address = address self.zip_code = zip_code self.city = city self.mobile = mobile self.phone = phone self.gender = gender self.raw_json = raw_json self.request_id = request_id self.dead = APIHelper.RFC3339DateTime(dead) if dead else None self.source = source # Add additional model properties to the instance self.additional_properties = additional_properties @classmethod def from_dictionary(cls, dictionary): """Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the object as obtained from the deserialization of the server's response. The keys MUST match property names in the API description. Returns: object: An instance of this structure class. """ if dictionary is None: return None # Extract variables from the dictionary firstname = dictionary.get('Firstname') middlename = dictionary.get('Middlename') lastname = dictionary.get('Lastname') date_of_birth = dictionary.get('DateOfBirth') address = dictionary.get('Address') zip_code = dictionary.get('ZipCode') city = dictionary.get('City') mobile = dictionary.get('Mobile') phone = dictionary.get('Phone') gender = dictionary.get('Gender') raw_json = dictionary.get('RawJson') request_id = dictionary.get('RequestId') dead = APIHelper.RFC3339DateTime.from_value(dictionary.get("Dead")).datetime if dictionary.get("Dead") else None source = dictionary.get('Source') # Clean out expected properties from dictionary for key in cls._names.values(): if key in dictionary: del dictionary[key] # Return an object of this model return cls(firstname, middlename, lastname, date_of_birth, address, zip_code, city, mobile, phone, gender, raw_json, request_id, dead, source, dictionary)

34.109589

121

0.555823

481

4,980

5.644491

0.237006

0.044199

0.097974

0.1186

0.138858

0

0.003454

0.360442

4,980

145

122

34.344828

0.84898

0.324699

0

1

0

0.100295

0

0.103448

0

1

0.023256

false

0

0.011628

0

0.081395

0

null

0

1

0

null

0

1

0

2

c5d42cfeef185ddf6696d8600cebabde18dc035e

25,439

py

Python

odym/modules/test/DSM_test_known_results.py

DominikWiedenhofer/ODYM

89aca3706b34df02d745f5d76cffc9f50dc2c3e7

[ "MIT" ]

3

2019-04-01T09:35:29.000Z

2021-01-03T18:51:55.000Z

odym/modules/test/DSM_test_known_results.py

DominikWiedenhofer/ODYM

89aca3706b34df02d745f5d76cffc9f50dc2c3e7

[ "MIT" ]

null

odym/modules/test/DSM_test_known_results.py

DominikWiedenhofer/ODYM

89aca3706b34df02d745f5d76cffc9f50dc2c3e7

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Mon Aug 11 16:19:39 2014 """ import os import sys import imp # Put location of sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..\\..')) + '\\modules') # add ODYM module directory to system path #NOTE: Hidden variable __file__ must be know to script for the directory structure to work. # Therefore: When first using the model, run the entire script with F5 so that the __file__ variable can be created. import dynamic_stock_model as dsm # remove and import the class manually if this unit test is run as standalone script imp.reload(dsm) import numpy as np import unittest ############################################################################### """My Input for fixed lifetime""" Time_T_FixedLT = np.arange(0,10) Inflow_T_FixedLT = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] lifetime_FixedLT = {'Type': 'Fixed', 'Mean': np.array([5])} lifetime_FixedLT0 = {'Type': 'Fixed', 'Mean': np.array([0])} #lifetime_FixedLT = {'Type': 'Fixed', 'Mean': np.array([5,5,5,5,5,5,5,5,5,5])} lifetime_NormLT = {'Type': 'Normal', 'Mean': np.array([5]), 'StdDev': np.array([1.5])} lifetime_NormLT0 = {'Type': 'Normal', 'Mean': np.array([0]), 'StdDev': np.array([1.5])} ############################################################################### """My Output for fixed lifetime""" Outflow_T_FixedLT = np.array([0, 0, 0, 0, 0, 1, 2, 3, 4, 5]) Outflow_TC_FixedLT = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 3, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 4, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 5, 0, 0, 0, 0, 0]]) Stock_T_FixedLT = np.array([1, 3, 6, 10, 15, 20, 25, 30, 35, 40]) StockChange_T_FixedLT = np.array([1, 2, 3, 4, 5, 5, 5, 5, 5, 5]) Stock_TC_FixedLT = np.array([[1, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 2, 0, 0, 0, 0, 0, 0, 0, 0], [1, 2, 3, 0, 0, 0, 0, 0, 0, 0], [1, 2, 3, 4, 0, 0, 0, 0, 0, 0], [1, 2, 3, 4, 5, 0, 0, 0, 0, 0], [0, 2, 3, 4, 5, 6, 0, 0, 0, 0], [0, 0, 3, 4, 5, 6, 7, 0, 0, 0], [0, 0, 0, 4, 5, 6, 7, 8, 0, 0], [0, 0, 0, 0, 5, 6, 7, 8, 9, 0], [0, 0, 0, 0, 0, 6, 7, 8, 9, 10]]) Bal = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) """My Output for normally distributed lifetime""" Stock_TC_NormLT = np.array([[ 9.99570940e-01, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [ 9.96169619e-01, 1.99914188e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [ 9.77249868e-01, 1.99233924e+00, 2.99871282e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [ 9.08788780e-01, 1.95449974e+00, 2.98850886e+00, 3.99828376e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [ 7.47507462e-01, 1.81757756e+00, 2.93174960e+00, 3.98467848e+00, 4.99785470e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [ 5.00000000e-01, 1.49501492e+00, 2.72636634e+00, 3.90899947e+00, 4.98084810e+00, 5.99742564e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [ 2.52492538e-01, 1.00000000e+00, 2.24252239e+00, 3.63515512e+00, 4.88624934e+00, 5.97701772e+00, 6.99699658e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [ 9.12112197e-02, 5.04985075e-01, 1.50000000e+00, 2.99002985e+00, 4.54394390e+00, 5.86349921e+00, 6.97318734e+00, 7.99656752e+00, 0.00000000e+00, 0.00000000e+00], [ 2.27501319e-02, 1.82422439e-01, 7.57477613e-01, 2.00000000e+00, 3.73753731e+00, 5.45273268e+00, 6.84074908e+00, 7.96935696e+00, 8.99613846e+00, 0.00000000e+00], [ 3.83038057e-03, 4.55002639e-02, 2.73633659e-01, 1.00997015e+00, 2.50000000e+00, 4.48504477e+00, 6.36152146e+00, 7.81799894e+00, 8.96552657e+00, 9.99570940e+00]]) Stock_T_NormLT = np.array([ 0.99957094, 2.9953115 , 5.96830193, 9.85008113, 14.4793678 , 19.60865447, 24.99043368, 30.46342411, 35.95916467, 41.45873561]) Outflow_T_NormLT = np.array([ 4.29060333e-04, 4.25944090e-03, 2.70095728e-02, 1.18220793e-01, 3.70713330e-01, 8.70713330e-01, 1.61822079e+00, 2.52700957e+00, 3.50425944e+00, 4.50042906e+00]) Outflow_TC_NormLT = np.array([[ 4.29060333e-04, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [ 3.40132023e-03, 8.58120666e-04, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00], [ 1.89197514e-02, 6.80264047e-03, 1.28718100e-03, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00], [ 6.84610878e-02, 3.78395028e-02, 1.02039607e-02, 1.71624133e-03, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00], [ 1.61281318e-01, 1.36922176e-01, 5.67592541e-02, 1.36052809e-02, 2.14530167e-03, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00], [ 2.47507462e-01, 3.22562636e-01, 2.05383263e-01, 7.56790055e-02, 1.70066012e-02, 2.57436200e-03, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00], [ 2.47507462e-01, 4.95014925e-01, 4.83843953e-01, 2.73844351e-01, 9.45987569e-02, 2.04079214e-02, 3.00342233e-03, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00], [ 1.61281318e-01, 4.95014925e-01, 7.42522387e-01, 6.45125271e-01, 3.42305439e-01, 1.13518508e-01, 2.38092416e-02, 3.43248267e-03, -0.00000000e+00, -0.00000000e+00], [ 6.84610878e-02, 3.22562636e-01, 7.42522387e-01, 9.90029850e-01, 8.06406589e-01, 4.10766527e-01, 1.32438260e-01, 2.72105619e-02, 3.86154300e-03, -0.00000000e+00], [ 1.89197514e-02, 1.36922176e-01, 4.83843953e-01, 9.90029850e-01, 1.23753731e+00, 9.67687907e-01, 4.79227614e-01, 1.51358011e-01, 3.06118821e-02, 4.29060333e-03]]) StockChange_T_NormLT = np.array([ 0.99957094, 1.99574056, 2.97299043, 3.88177921, 4.62928667, 5.12928667, 5.38177921, 5.47299043, 5.49574056, 5.49957094]) """My Output for Weibull-distributed lifetime""" Stock_TC_WeibullLT = np.array([[1, 0, 0, 0, 0, 0, 0, 0, 0, 0], # computed with Excel and taken from there [0.367879441, 2, 0, 0, 0, 0, 0, 0, 0, 0], [0.100520187, 0.735758882, 3, 0, 0, 0, 0, 0, 0, 0], [0.023820879, 0.201040373, 1.103638324, 4, 0, 0, 0, 0, 0, 0], [0.005102464, 0.047641758, 0.30156056, 1.471517765,5, 0, 0, 0, 0, 0], [0.001009149, 0.010204929, 0.071462637, 0.402080746,1.839397206, 6, 0, 0, 0, 0], [0.000186736, 0.002018297, 0.015307393, 0.095283516, 0.502600933, 2.207276647, 7, 0, 0, 0], [3.26256E-05, 0.000373472, 0.003027446, 0.020409858, 0.119104394, 0.60312112, 2.575156088, 8, 0, 0], [5.41828E-06, 6.52513E-05, 0.000560208, 0.004036594, 0.025512322, 0.142925273, 0.703641306, 2.943035529, 9, 0], [8.59762E-07, 1.08366E-05, 9.78769E-05, 0.000746944, 0.005045743, 0.030614786, 0.166746152, 0.804161493, 3.310914971, 10]]) Stock_T_WeibullLT = np.array([1,2.367879441,3.836279069,5.328499576,6.825822547,8.324154666,9.822673522,11.321225,12.8197819,14.31833966]) Outflow_T_WeibullLT = np.array([0,0.632120559,1.531600372,2.507779493,3.502677029,4.50166788,5.501481144,6.501448519,7.5014431,8.501442241]) Outflow_TC_WeibullLT = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0.632120559, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0.267359255, 1.264241118, 0, 0, 0, 0, 0, 0, 0, 0], [0.076699308, 0.534718509, 1.896361676, 0, 0, 0, 0, 0, 0, 0], [0.018718414, 0.153398615, 0.802077764, 2.528482235, 0, 0, 0, 0, 0, 0], [0.004093316, 0.037436829, 0.230097923, 1.069437018, 3.160602794, 0, 0, 0, 0, 0], [0.000822413, 0.008186632, 0.056155243, 0.306797231, 1.336796273, 3.792723353, 0, 0, 0, 0], [0.00015411, 0.001644825, 0.012279947, 0.074873658, 0.383496539, 1.604155527, 4.424843912, 0, 0, 0], [2.72074E-05, 0.000308221, 0.002467238, 0.016373263, 0.093592072, 0.460195846, 1.871514782, 5.056964471, 0, 0], [4.55852E-06, 5.44147E-05 , 0.000462331 , 0.00328965, 0.020466579, 0.112310487, 0.536895154, 2.138874037, 5.689085029, 0]]) StockChange_T_WeibullLT = np.array([1,1.367879441,1.468399628,1.492220507,1.497322971,1.49833212,1.498518856,1.498551481,1.4985569,1.498557759]) lifetime_WeibullLT = {'Type': 'Weibull', 'Shape': np.array([1.2]), 'Scale': np.array([1])} InitialStock_WB = np.array([0.01, 0.01, 0.08, 0.2, 0.2, 2, 2, 3, 4, 7.50]) Inflow_WB = np.array([11631.1250671964, 1845.6048709861, 2452.0593141014, 1071.0305279511, 198.1868742385, 391.9674590243, 83.9599583940, 29.8447516023, 10.8731273138, 7.5000000000]) # We need 10 digits AFTER the . to get a 9 digits after the . overlap with np.testing. # The total number of counting digits is higher, because there are up to 5 digits before the . # For the stock-driven model with initial stock, colculated with Excel Sc_InitialStock_2_Ref = np.array([[ 3.29968072, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ], [ 3.28845263, 5.1142035 , 0. , 0. , 0. , 0. , 0. , 0. , 0. ], [ 3.2259967 , 5.09680099, 2.0068288 , 0. , 0. , 0. , 0. , 0. , 0. ], [ 3. , 5. , 2. , 4. , 0. , 0. , 0. , 0. , 0. ], [ 2.46759471, 4.64972578, 1.962015 , 3.98638888, 4.93427563, 0. , 0. , 0. , 0. ], [ 1.65054855, 3.82454624, 1.82456634, 3.91067739, 4.91748538, 3.8721761 , 0. , 0. , 0. ], [ 0.83350238, 2.55819937, 1.50076342, 3.63671549, 4.82409004, 3.85899993, 2.78772936, 0. , 0. ], [ 0.30109709, 1.2918525 , 1.00384511, 2.9913133 , 4.48613916, 3.78570788, 2.77824333, 3.36180162, 0. ], [ 0.07510039, 0.46667297, 0.5069268 , 2.00085849, 3.68999109, 3.5205007 , 2.72547754, 3.35036215, 3.66410986]]) Sc_InitialStock_2_Ref_Sum = np.array([ 3.29968072, 8.40265614, 10.32962649, 14. , 18. , 20. , 20. , 20. , 20. ]) Oc_InitialStock_2_Ref = np.array([[ 1.41636982e-03, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00], [ 1.12280883e-02, 2.19524375e-03, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00], [ 6.24559363e-02, 1.74025106e-02, 8.61420234e-04, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00], [ 2.25996698e-01, 9.68009922e-02, 6.82879736e-03, 1.71697802e-03, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00], [ 5.32405289e-01, 3.50274224e-01, 3.79849998e-02, 1.36111209e-02, 2.11801070e-03, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00], [ 8.17046165e-01, 8.25179532e-01, 1.37448656e-01, 7.57114903e-02, 1.67902556e-02, 1.66211031e-03, -0.00000000e+00, -0.00000000e+00, -0.00000000e+00], [ 8.17046165e-01, 1.26634687e+00, 3.23802924e-01, 2.73961897e-01, 9.33953405e-02, 1.31761643e-02, 1.19661751e-03, -0.00000000e+00, -0.00000000e+00], [ 5.32405289e-01, 1.26634687e+00, 4.96918311e-01, 6.45402188e-01, 3.37950879e-01, 7.32920558e-02, 9.48603036e-03, 1.44303487e-03, -0.00000000e+00], [ 2.25996698e-01, 8.25179532e-01, 4.96918311e-01, 9.90454815e-01, 7.96148072e-01, 2.65207178e-01, 5.27657861e-02, 1.14394721e-02, 1.57279902e-03]]) I_InitialStock_2_Ref = np.array([ 3.30109709, 5.11639875, 2.00769022, 4.00171698, 4.93639364, 3.87383821, 2.78892598, 3.36324466, 3.66568266]) """ Test case with fixed lifetime for initial stock""" Time_T_FixedLT_X = np.arange(1, 9, 1) lifetime_FixedLT_X = {'Type': 'Fixed', 'Mean': np.array([5])} InitialStock_X = np.array([0, 0, 0, 7, 5, 4, 3, 2]) Inflow_X = np.array([0, 0, 0, 7, 5, 4, 3, 2]) Time_T_FixedLT_XX = np.arange(1, 11, 1) lifetime_NormLT_X = {'Type': 'Normal', 'Mean': np.array([5]), 'StdDev': np.array([1.5])} InitialStock_XX = np.array([0.01, 0.01, 0.08, 0.2, 0.2, 2, 2, 3, 4, 7.50]) Inflow_XX = np.array([ 2.61070664, 0.43955789, 0.87708508, 0.79210262, 0.4, 2.67555857, 2.20073139, 3.06983925, 4.01538044, 7.50321933]) """ Test case with normally distributed lifetime for initial stock and stock-driven model""" Time_T_FixedLT_2 = np.arange(1, 10, 1) lifetime_NormLT_2 = {'Type': 'Normal', 'Mean': np.array([5]), 'StdDev': np.array([1.5])} InitialStock_2 = np.array([3,5,2,4]) FutureStock_2 = np.array([0,0,0,0,18,20,20,20,20]) ThisSwitchTime = 5 # First year with future stock curve, start counting from 1. Inflow_2 = np.array([3.541625588, 5.227890554,2.01531097,4]) ############################################################################### """Create Dynamic Stock Models and hand over the pre-defined values.""" # For zero lifetime: border case myDSM0 = dsm.DynamicStockModel(t=Time_T_FixedLT, i=Inflow_T_FixedLT, lt=lifetime_FixedLT0) # For fixed LT myDSM = dsm.DynamicStockModel(t=Time_T_FixedLT, i=Inflow_T_FixedLT, lt=lifetime_FixedLT) myDSM2 = dsm.DynamicStockModel(t=Time_T_FixedLT, s=Stock_T_FixedLT, lt=lifetime_FixedLT) myDSMx = dsm.DynamicStockModel(t=Time_T_FixedLT_X, lt=lifetime_FixedLT_X) TestInflow_X = myDSMx.compute_i_from_s(InitialStock=InitialStock_X) myDSMxy = dsm.DynamicStockModel(t=Time_T_FixedLT_X, i=TestInflow_X, lt=lifetime_FixedLT_X) # For zero normally distributed lifetime: border case myDSM0n = dsm.DynamicStockModel(t=Time_T_FixedLT, i=Inflow_T_FixedLT, lt=lifetime_NormLT0) # For normally distributed Lt myDSM3 = dsm.DynamicStockModel(t=Time_T_FixedLT, i=Inflow_T_FixedLT, lt=lifetime_NormLT) myDSM4 = dsm.DynamicStockModel(t=Time_T_FixedLT, s=Stock_T_NormLT, lt=lifetime_NormLT) myDSMX = dsm.DynamicStockModel(t=Time_T_FixedLT_XX, lt=lifetime_NormLT_X) TestInflow_XX = myDSMX.compute_i_from_s(InitialStock=InitialStock_XX) myDSMXY = dsm.DynamicStockModel(t=Time_T_FixedLT_XX, i=TestInflow_XX, lt=lifetime_NormLT_X) # Test compute_stock_driven_model_initialstock: TestDSM_IntitialStock = dsm.DynamicStockModel(t=Time_T_FixedLT_2, s=FutureStock_2, lt=lifetime_NormLT_2) Sc_InitialStock_2,Oc_InitialStock_2,I_InitialStock_2 = TestDSM_IntitialStock.compute_stock_driven_model_initialstock(InitialStock = InitialStock_2, SwitchTime = ThisSwitchTime) # Compute stock back from inflow TestDSM_IntitialStock_Verify = dsm.DynamicStockModel(t=Time_T_FixedLT_2, i=I_InitialStock_2, lt=lifetime_NormLT_2) Sc_Stock_2 = TestDSM_IntitialStock_Verify.compute_s_c_inflow_driven() Sc_Stock_2_Sum = Sc_Stock_2.sum(axis =1) Sc_Stock_Sum = TestDSM_IntitialStock_Verify.compute_stock_total() Sc_Outflow_t_c = TestDSM_IntitialStock_Verify.compute_o_c_from_s_c() # For Weibull-distributed Lt myDSMWB1 = dsm.DynamicStockModel(t=Time_T_FixedLT, i=Inflow_T_FixedLT, lt=lifetime_WeibullLT) myDSMWB2 = dsm.DynamicStockModel(t=Time_T_FixedLT, s=Stock_T_WeibullLT, lt=lifetime_WeibullLT) myDSMWB3 = dsm.DynamicStockModel(t=Time_T_FixedLT_XX, lt=lifetime_WeibullLT) TestInflow_WB = myDSMWB3.compute_i_from_s(InitialStock=InitialStock_XX) myDSMWB4 = dsm.DynamicStockModel(t=Time_T_FixedLT_XX, i=TestInflow_WB, lt=lifetime_WeibullLT) # Compute full stock model in correct order ############################################################################### """Unit Test Class""" class KnownResultsTestCase(unittest.TestCase): def test_inflow_driven_model_fixedLifetime_0(self): """Test Inflow Driven Model with Fixed product lifetime of 0.""" np.testing.assert_array_equal(myDSM0.compute_s_c_inflow_driven(), np.zeros(Stock_TC_FixedLT.shape)) np.testing.assert_array_equal(myDSM0.compute_stock_total(), np.zeros((Stock_TC_FixedLT.shape[0]))) np.testing.assert_array_equal(myDSM0.compute_stock_change(), np.zeros((Stock_TC_FixedLT.shape[0]))) np.testing.assert_array_equal(myDSM0.compute_outflow_mb(), Inflow_T_FixedLT) np.testing.assert_array_equal(myDSM0.check_stock_balance(), Bal.transpose()) def test_inflow_driven_model_fixedLifetime(self): """Test Inflow Driven Model with Fixed product lifetime.""" np.testing.assert_array_equal(myDSM.compute_s_c_inflow_driven(), Stock_TC_FixedLT) np.testing.assert_array_equal(myDSM.compute_stock_total(),Stock_T_FixedLT) np.testing.assert_array_equal(myDSM.compute_o_c_from_s_c(), Outflow_TC_FixedLT) np.testing.assert_array_equal(myDSM.compute_outflow_total(), Outflow_T_FixedLT) np.testing.assert_array_equal(myDSM.compute_stock_change(), StockChange_T_FixedLT) np.testing.assert_array_equal(myDSM.check_stock_balance(), Bal.transpose()) def test_stock_driven_model_fixedLifetime(self): """Test Stock Driven Model with Fixed product lifetime.""" np.testing.assert_array_equal(myDSM2.compute_stock_driven_model()[0], Stock_TC_FixedLT) np.testing.assert_array_equal(myDSM2.compute_stock_driven_model()[1], Outflow_TC_FixedLT) np.testing.assert_array_equal(myDSM2.compute_stock_driven_model()[2], Inflow_T_FixedLT) np.testing.assert_array_equal(myDSM2.compute_outflow_total(), Outflow_T_FixedLT) np.testing.assert_array_equal(myDSM2.compute_stock_change(), StockChange_T_FixedLT) np.testing.assert_array_equal(myDSM2.check_stock_balance(), Bal.transpose()) def test_inflow_driven_model_normallyDistrLifetime_0(self): """Test Inflow Driven Model with Fixed product lifetime of 0.""" np.testing.assert_array_equal(myDSM0n.compute_s_c_inflow_driven(), np.zeros(Stock_TC_FixedLT.shape)) np.testing.assert_array_equal(myDSM0n.compute_stock_total(), np.zeros((Stock_TC_FixedLT.shape[0]))) np.testing.assert_array_equal(myDSM0n.compute_stock_change(), np.zeros((Stock_TC_FixedLT.shape[0]))) np.testing.assert_array_equal(myDSM0n.compute_outflow_mb(), Inflow_T_FixedLT) np.testing.assert_array_equal(myDSM0n.check_stock_balance(), Bal.transpose()) def test_inflow_driven_model_normallyDistLifetime(self): """Test Inflow Driven Model with normally distributed product lifetime.""" np.testing.assert_array_almost_equal(myDSM3.compute_s_c_inflow_driven(), Stock_TC_NormLT, 8) np.testing.assert_array_almost_equal(myDSM3.compute_stock_total(), Stock_T_NormLT, 8) np.testing.assert_array_almost_equal(myDSM3.compute_o_c_from_s_c(), Outflow_TC_NormLT, 8) np.testing.assert_array_almost_equal(myDSM3.compute_outflow_total(), Outflow_T_NormLT, 8) np.testing.assert_array_almost_equal(myDSM3.compute_stock_change(), StockChange_T_NormLT, 8) np.testing.assert_array_almost_equal(myDSM3.check_stock_balance(), Bal.transpose(), 12) def test_stock_driven_model_normallyDistLifetime(self): """Test Stock Driven Model with normally distributed product lifetime.""" np.testing.assert_array_almost_equal( myDSM4.compute_stock_driven_model()[0], Stock_TC_NormLT, 8) np.testing.assert_array_almost_equal( myDSM4.compute_stock_driven_model()[1], Outflow_TC_NormLT, 8) np.testing.assert_array_almost_equal( myDSM4.compute_stock_driven_model()[2], Inflow_T_FixedLT, 8) np.testing.assert_array_almost_equal(myDSM4.compute_outflow_total(), Outflow_T_NormLT, 8) np.testing.assert_array_almost_equal( myDSM4.compute_stock_change(), StockChange_T_NormLT, 8) np.testing.assert_array_almost_equal(myDSM4.check_stock_balance(), Bal.transpose(), 12) def test_inflow_driven_model_WeibullDistLifetime(self): """Test Inflow Driven Model with Weibull-distributed product lifetime.""" np.testing.assert_array_almost_equal( myDSMWB1.compute_s_c_inflow_driven(), Stock_TC_WeibullLT, 9) np.testing.assert_array_almost_equal(myDSMWB1.compute_stock_total(), Stock_T_WeibullLT, 8) np.testing.assert_array_almost_equal(myDSMWB1.compute_o_c_from_s_c(), Outflow_TC_WeibullLT, 9) np.testing.assert_array_almost_equal(myDSMWB1.compute_outflow_total(), Outflow_T_WeibullLT, 9) np.testing.assert_array_almost_equal( myDSMWB1.compute_stock_change(), StockChange_T_WeibullLT, 9) np.testing.assert_array_almost_equal(myDSMWB1.check_stock_balance(), Bal.transpose(), 12) def test_stock_driven_model_WeibullDistLifetime(self): """Test Stock Driven Model with Weibull-distributed product lifetime.""" np.testing.assert_array_almost_equal( myDSMWB1.compute_stock_driven_model()[0], Stock_TC_WeibullLT, 8) np.testing.assert_array_almost_equal( myDSMWB1.compute_stock_driven_model()[1], Outflow_TC_WeibullLT, 8) np.testing.assert_array_almost_equal( myDSMWB1.compute_stock_driven_model()[2], Inflow_T_FixedLT, 8) np.testing.assert_array_almost_equal(myDSMWB1.compute_outflow_total(), Outflow_T_WeibullLT, 9) np.testing.assert_array_almost_equal( myDSMWB1.compute_stock_change(), StockChange_T_WeibullLT, 8) np.testing.assert_array_almost_equal(myDSMWB1.check_stock_balance(), Bal.transpose(), 12) def test_inflow_from_stock_fixedLifetime(self): """Test computation of inflow from stock with Fixed product lifetime.""" np.testing.assert_array_equal(TestInflow_X, Inflow_X) np.testing.assert_array_equal(myDSMxy.compute_s_c_inflow_driven()[-1, :], InitialStock_X) def test_inflow_from_stock_normallyDistLifetime(self): """Test computation of inflow from stock with normally distributed product lifetime.""" np.testing.assert_array_almost_equal(TestInflow_XX, Inflow_XX, 8) np.testing.assert_array_almost_equal(myDSMXY.compute_s_c_inflow_driven()[-1, :], InitialStock_XX, 9) def test_inflow_from_stock_WeibullDistLifetime(self): """Test computation of inflow from stock with Weibull-distributed product lifetime.""" np.testing.assert_array_almost_equal(TestInflow_WB, Inflow_WB, 9) np.testing.assert_array_almost_equal(myDSMWB4.compute_s_c_inflow_driven()[-1, :], InitialStock_WB, 9) def test_compute_stock_driven_model_initialstock(self): """Test stock-driven model with initial stock given.""" np.testing.assert_array_almost_equal(I_InitialStock_2, I_InitialStock_2_Ref, 8) np.testing.assert_array_almost_equal(Sc_InitialStock_2, Sc_InitialStock_2_Ref, 8) np.testing.assert_array_almost_equal(Sc_InitialStock_2.sum(axis =1), Sc_InitialStock_2_Ref_Sum, 8) np.testing.assert_array_almost_equal(Oc_InitialStock_2, Oc_InitialStock_2_Ref, 8) if __name__ == '__main__': unittest.main()

59.576112

182

0.626243

3,649

25,439

4.179775

0.160866

0.037372

0.04701

0.051665

0.591922

0.541372

0.498951

0.460858

0.436992

0.385654

0

0.301661

0.225952

25,439

426

183

59.715962

0.472906

0.073706

0

0.208723

0

0.007163

0

0.174455

1

0.037383

false

0

0.018692

0

0.05919

0

null

0

1

0

1

0

null

0

2

c5d6d1a64a423018703822d97798dfe358235126

1,081

py

Python

HLTrigger/Configuration/python/HLT_75e33/paths/HLT_DoublePFPuppiJets128_DoublePFPuppiBTagDeepCSV_2p4_cfi.py

PKUfudawei/cmssw

8fbb5ce74398269c8a32956d7c7943766770c093

[ "Apache-2.0" ]

1

2021-11-30T16:24:46.000Z

HLTrigger/Configuration/python/HLT_75e33/paths/HLT_DoublePFPuppiJets128_DoublePFPuppiBTagDeepCSV_2p4_cfi.py

PKUfudawei/cmssw

8fbb5ce74398269c8a32956d7c7943766770c093

[ "Apache-2.0" ]

4

2021-11-29T13:57:56.000Z

2022-03-29T06:28:36.000Z

HLTrigger/Configuration/python/HLT_75e33/paths/HLT_DoublePFPuppiJets128_DoublePFPuppiBTagDeepCSV_2p4_cfi.py

PKUfudawei/cmssw

8fbb5ce74398269c8a32956d7c7943766770c093

[ "Apache-2.0" ]

1

2021-11-30T16:16:05.000Z

import FWCore.ParameterSet.Config as cms from ..modules.hltBTagPFPuppiDeepCSV0p865DoubleEta2p4_cfi import * from ..modules.hltDoublePFPuppiJets128Eta2p4MaxDeta1p6_cfi import * from ..modules.hltDoublePFPuppiJets128MaxEta2p4_cfi import * from ..modules.l1tDoublePFPuppiJet112offMaxEta2p4_cfi import * from ..modules.l1tDoublePFPuppiJets112offMaxDeta1p6_cfi import * from ..sequences.HLTAK4PFPuppiJetsReconstruction_cfi import * from ..sequences.HLTBeginSequence_cfi import * from ..sequences.HLTBtagDeepCSVSequencePFPuppiModEta2p4_cfi import * from ..sequences.HLTEndSequence_cfi import * from ..sequences.HLTParticleFlowSequence_cfi import * HLT_DoublePFPuppiJets128_DoublePFPuppiBTagDeepCSV_2p4 = cms.Path( HLTBeginSequence + l1tDoublePFPuppiJet112offMaxEta2p4 + l1tDoublePFPuppiJets112offMaxDeta1p6 + HLTParticleFlowSequence + HLTAK4PFPuppiJetsReconstruction + hltDoublePFPuppiJets128MaxEta2p4 + hltDoublePFPuppiJets128Eta2p4MaxDeta1p6 + HLTBtagDeepCSVSequencePFPuppiModEta2p4 + hltBTagPFPuppiDeepCSV0p865DoubleEta2p4 + HLTEndSequence )

41.576923

68

0.848289

72

1,081

12.555556

0.347222

0.099558

0.129425

0.121681

0

0.073045

0.100833

1,081

25

69

43.24

0.856996

0

1

0

false

0

0.478261

0

0.478261

0

1

null

0

null

0

1

0

2

c5de930741f4d8551e11905355564ca78fd72a62

320

py

Python

alertmanager_telegram/config.py

medeirosjrm/alertmanager-telegram

ff9701936ec766b7992399fd741d8a8a4dab3957

[ "Apache-2.0" ]

5

2020-05-20T11:37:37.000Z

2021-11-23T09:04:14.000Z

alertmanager_telegram/config.py

medeirosjrm/alertmanager-telegram

ff9701936ec766b7992399fd741d8a8a4dab3957

[ "Apache-2.0" ]

null

alertmanager_telegram/config.py

medeirosjrm/alertmanager-telegram

ff9701936ec766b7992399fd741d8a8a4dab3957

[ "Apache-2.0" ]

3

2021-01-31T17:57:08.000Z

2021-11-24T13:33:31.000Z

import os TELEGRAM_CHAT_ID = os.environ.get("TELEGRAM_CHAT_ID") if not TELEGRAM_CHAT_ID: raise ValueError("No TELEGRAM_CHAT_ID set for application") TELEGRAM_TOKEN = os.environ.get("TELEGRAM_TOKEN") if not TELEGRAM_TOKEN: raise ValueError("No TELEGRAM_TOKEN set for application") TEMPLATES_AUTO_RELOAD = True

26.666667

63

0.796875

48

320

5.020833

0.416667

0.19917

0.232365

0.165975

0

0.125

320

11

64

29.090909

0.860714

0

0.33125

0

1

0

false

0

0.125

0

0.125

0

null

0

1

0

null

0

2

c5e00eaee5bf1dc4f3ef2430a8612b17e78c2729

282

py

Python

appexemple/__main__.py

yoannmos/Inupdater-AppExemple

ac62430a8ca02505eb73afaff698500b7f46ea31

[ "MIT" ]

null

appexemple/__main__.py

yoannmos/Inupdater-AppExemple

ac62430a8ca02505eb73afaff698500b7f46ea31

[ "MIT" ]

null

appexemple/__main__.py

yoannmos/Inupdater-AppExemple

ac62430a8ca02505eb73afaff698500b7f46ea31

[ "MIT" ]

null

import sys from pathlib import Path from appexemple import __version__ print( f""" Hello you are in App Exemple version {__version__}\n sys.argv[-1] : {sys.argv[-1]}\n Path().cwd() : {Path().cwd()}\n Path(__file__) : {Path(__file__)},\n """ ) input("Press [Enter] to quit.")

17.625

52

0.663121

43

282

3.976744

0.581395

0.081871

0.093567

0

0.008333

0.148936

282

15

53

18.8

0.704167

0

0.62766

0

1

0

true

0

0.25

0

0.25

0.083333

0

null

0

1

0

null

0

1

0

2

c5e73f85a5d535b9725cdc5daf85b03ea7c65ebb

904

py

Python

venv/lib/python3.7/site-packages/webdriver_manager/microsoft.py

wayshon/pylogin

12ecfddc3ceaf552a42f62608027924541c63254

[ "Apache-2.0" ]

null

venv/lib/python3.7/site-packages/webdriver_manager/microsoft.py

wayshon/pylogin

12ecfddc3ceaf552a42f62608027924541c63254

[ "Apache-2.0" ]

7

2019-12-04T23:08:08.000Z

2022-02-10T12:47:38.000Z

venv/lib/python3.7/site-packages/webdriver_manager/microsoft.py

wayshon/pylogin

12ecfddc3ceaf552a42f62608027924541c63254

[ "Apache-2.0" ]

null

from webdriver_manager.driver import EdgeDriver, IEDriver from webdriver_manager.manager import DriverManager from webdriver_manager import utils class EdgeDriverManager(DriverManager): def __init__(self, version=None, os_type=utils.os_name()): super(EdgeDriverManager, self).__init__() self.driver = EdgeDriver(version=version, os_type=os_type) def install(self, path=None): # type: () -> str return self._file_manager.download_binary(self.driver, path).path class IEDriverManager(DriverManager): def __init__(self, version=None, os_type=utils.os_type()): super(IEDriverManager, self).__init__() self.driver = IEDriver(version=version, os_type=os_type) def install(self, path=None): # type: () -> str return self._file_manager.download_driver(self.driver, path).path

34.769231

73

0.683628

104

904

5.625

0.269231

0.071795

0.102564

0.082051

0.451282

0

0.215708

904

25

74

36.16

0.825106

0.034292

0

0.117647

0

1

0.235294

false

0

0.176471

0.117647

0.647059

0

null

0

null

0

1

0

1

0

2

c5ef8d7c1493136be617512f99564772f9d404af

1,354

py

Python

Python/sir_cost.py

Wasim5620/SIRmodel

bbca1431673dc5450f290db1235eb73e92e74979

[ "MIT" ]

26

2018-08-08T20:40:21.000Z

2022-01-13T19:46:40.000Z

Python/sir_cost.py

Wasim5620/SIRmodel

bbca1431673dc5450f290db1235eb73e92e74979

[ "MIT" ]

24

2020-03-25T19:35:43.000Z

2022-02-10T11:46:50.000Z

Python/sir_cost.py

Wasim5620/SIRmodel

bbca1431673dc5450f290db1235eb73e92e74979

[ "MIT" ]

9

2017-07-22T04:23:15.000Z

2021-03-19T09:42:35.000Z

# cost function for the SIR model for python 2.7 # Marisa Eisenberg (marisae@umich.edu) # Yu-Han Kao (kaoyh@umich.edu) -7-9-17 import numpy as np import sir_ode from scipy.stats import poisson from scipy.stats import norm from scipy.integrate import odeint as ode def NLL(params, data, times): #negative log likelihood params = np.abs(params) data = np.array(data) res = ode(sir_ode.model, sir_ode.x0fcn(params,data), times, args=(params,)) y = sir_ode.yfcn(res, params) nll = sum(y) - sum(data*np.log(y)) # note this is a slightly shortened version--there's an additive constant term missing but it # makes calculation faster and won't alter the threshold. Alternatively, can do: # nll = -sum(np.log(poisson.pmf(np.round(data),np.round(y)))) # the round is b/c Poisson is for (integer) count data # this can also barf if data and y are too far apart because the dpois will be ~0, which makes the log angry # ML using normally distributed measurement error (least squares) # nll = -sum(np.log(norm.pdf(data,y,0.1*np.mean(data)))) # example WLS assuming sigma = 0.1*mean(data) # nll = sum((y - data)**2) # alternatively can do OLS but note this will mess with the thresholds # for the profile! This version of OLS is off by a scaling factor from # actual LL units. return nll

46.689655

117

0.697194

230

1,354

4.086957

0.53913

0.025532

0.029787

0.042553

0

0.012015

0.200886

1,354

28

118

48.357143

0.856747

0.693501

0

1

0.083333

false

0

0.416667

0

0.583333

0

null

0

null

0

1

0

1

0

2

c5f1d3547439c81f976d6e6a8b962ce796bdbe68

125

py

Python

fhirbug/constants.py

VerdantAI/fhirbug

8a8e2555c0edfeee0a7edbc8d67f2fcb2edd3c2d

[ "MIT" ]

8

2019-01-06T18:11:20.000Z

2022-02-24T02:06:55.000Z

fhirbug/constants.py

VerdantAI/fhirbug

8a8e2555c0edfeee0a7edbc8d67f2fcb2edd3c2d

[ "MIT" ]

5

2019-01-25T14:15:35.000Z

2021-06-01T23:22:41.000Z

fhirbug/constants.py

VerdantAI/fhirbug

8a8e2555c0edfeee0a7edbc8d67f2fcb2edd3c2d

[ "MIT" ]

3

2020-10-14T23:09:29.000Z

2021-08-09T19:27:31.000Z

# Audit Event Outcomes AUDIT_SUCCESS = "0" AUDIT_MINOR_FAILURE = "4" AUDIT_SERIOUS_FAILURE = "8" AUDIT_MAJOR_FAILURE = "12"

17.857143

27

0.76

18

125

4.888889

0.666667

0

0.046296

0.136

125

6

28

20.833333

0.768519

0.16

0

0.04902

0

1

0

false

0

1

0

null

0

1

0

null

0

2

c5f32783266b0ae2f58b621ca0211597718a479a

323

py

Python

task_queue/management/commands/run_scheduler.py

2600box/harvest

57264c15a3fba693b4b58d0b6d4fbf4bd5453bbd

[ "Apache-2.0" ]

9

2019-03-26T14:50:00.000Z

2020-11-10T16:44:08.000Z

task_queue/management/commands/run_scheduler.py

2600box/harvest

57264c15a3fba693b4b58d0b6d4fbf4bd5453bbd

[ "Apache-2.0" ]

22

2019-03-02T23:16:13.000Z

2022-02-27T10:36:36.000Z

task_queue/management/commands/run_scheduler.py

2600box/harvest

57264c15a3fba693b4b58d0b6d4fbf4bd5453bbd

[ "Apache-2.0" ]

5

2019-04-24T00:51:30.000Z

2020-11-06T18:31:49.000Z

import asyncio from django.core.management.base import BaseCommand from Harvest.utils import get_logger from task_queue.scheduler import QueueScheduler logger = get_logger(__name__) class Command(BaseCommand): help = "Run the queue consumer" def handle(self, *args, **options): QueueScheduler().run()

20.1875

51

0.755418

40

323

5.925

0.7

0.075949

0

0.160991

323

15

52

21.533333

0.874539

0

0.068111

0

1

0.111111

false

0

0.444444

0

0.777778

0

null

0

null

0

1

0

1

0

2

c5f43a8aa085560b1c95a6c088b9ec19d6141f65

2,005

py

Python

examples/example2.py

alenaizan/resp

41c58f465f9f3c00225dba9dfa54e5269a970240

[ "BSD-3-Clause" ]

10

2019-03-15T20:33:02.000Z

2021-12-15T02:05:28.000Z

examples/example2.py

alenaizan/resp

41c58f465f9f3c00225dba9dfa54e5269a970240

[ "BSD-3-Clause" ]

18

2018-06-13T04:10:39.000Z

2022-03-18T08:17:33.000Z

examples/example2.py

alenaizan/resp

41c58f465f9f3c00225dba9dfa54e5269a970240

[ "BSD-3-Clause" ]

5

2018-06-13T02:57:28.000Z

2021-06-08T15:43:15.000Z

import psi4 import resp # Initialize two different conformations of ethanol geometry = """C 0.00000000 0.00000000 0.00000000 C 1.48805540 -0.00728176 0.39653260 O 2.04971655 1.37648153 0.25604810 H 3.06429978 1.37151670 0.52641124 H 1.58679428 -0.33618761 1.43102358 H 2.03441010 -0.68906454 -0.25521028 H -0.40814044 -1.00553466 0.10208540 H -0.54635470 0.68178278 0.65174288 H -0.09873888 0.32890585 -1.03449097 """ mol1 = psi4.geometry(geometry) mol1.update_geometry() mol1.set_name('conformer1') geometry = """C 0.00000000 0.00000000 0.00000000 C 1.48013500 -0.00724300 0.39442200 O 2.00696300 1.29224100 0.26232800 H 2.91547900 1.25572900 0.50972300 H 1.61500700 -0.32678000 1.45587700 H 2.07197500 -0.68695100 -0.26493400 H -0.32500012 1.02293415 -0.30034094 H -0.18892141 -0.68463906 -0.85893815 H -0.64257065 -0.32709111 0.84987482 """ mol2 = psi4.geometry(geometry) mol2.update_geometry() mol2.set_name('conformer2') molecules = [mol1, mol2] # Specify options options = {'VDW_SCALE_FACTORS' : [1.4, 1.6, 1.8, 2.0], 'VDW_POINT_DENSITY' : 1.0, 'RESP_A' : 0.0005, 'RESP_B' : 0.1, 'RESTRAINT' : True, 'IHFREE' : False, 'WEIGHT' : [1, 1], } # Call for first stage fit charges1 = resp.resp(molecules, options) print("Restrained Electrostatic Potential Charges") print(charges1[1]) options['RESP_A'] = 0.001 resp.set_stage2_constraint(molecules[0], charges1[1], options) # Add constraint for atoms fixed in second stage fit options['grid'] = [] options['esp'] = [] for mol in range(len(molecules)): options['grid'].append('%i_%s_grid.dat' %(mol+1, molecules[mol].name())) options['esp'].append('%i_%s_grid_esp.dat' %(mol+1, molecules[mol].name())) # Call for second stage fit charges2 = resp.resp(molecules, options) print("\nStage Two\n") print("RESP Charges") print(charges2[1])

30.378788

79

0.653367

293

2,005

4.409556

0.419795

0.041796

0.03096

0.055728

0.139319

0.094427

0.058824

0

0.336484

0.208479

2,005

65

80

30.846154

0.477631

0.083292

0

0.078431

0

0.505459

0

1

0

false

0

0.039216

0

0.039216

0.098039

0

null

0

1

0

1

0

null

0

2

a84380c1f97670fcb660541a388530604b2cd9bd

1,180

py

Python

bot/audio_trial2.py

Nova-Striker/discord-bot

1c977711f348467bd73e1886c27ad4a9a93c779b

[ "Apache-2.0" ]

1

2020-11-10T06:33:49.000Z

bot/audio_trial2.py

Nova-Striker/discord-bot

1c977711f348467bd73e1886c27ad4a9a93c779b

[ "Apache-2.0" ]

null

bot/audio_trial2.py

Nova-Striker/discord-bot

1c977711f348467bd73e1886c27ad4a9a93c779b

[ "Apache-2.0" ]

1

2020-11-13T17:12:00.000Z

##incompleted yt tuitorial ##import discord ##import json ##import asyncio ##import youtube_dl ##import shell ##import os ##from discord.utils import get ##from discord.ext import commands ## ##@client.command(pass_context=True) ##async def join(ctx): ## global voice ## channel=ctx.message.author.voice.channel ## voice=get(client.voice_clients,guild=ctx.guild) ## ## if voice and voice.is_connected(): ## await voice.move_to(channel) ## else: ## voice=await chqannel.connect() ## await ctx.send(f"Joined {channel}") ## ##@client.command(pass_context=True) ##async def leave(ctx): ## channel=ctx.message.author.voice.channel ## voice=get(client.voice_clients,guild=ctx.guild) ## ## if voice and voice.is_connected(): ## await voice.disconnect() ## await ctx.send(f"Left {channel}") ## ##@client.command(pass_context=True,aliases=["p"]) ##async def play(ctx,url:str): ## def check_queue(): ## Queue_infile=os.path.indir("./Queue") ## if Queue_infile is True: ## DIR =os.path.abspath(os.path.realpath("Queue")) ## length=len(os. ##

28.095238

62

0.626271

149

1,180

4.879195

0.422819

0.053645

0.070151

0.099037

0.459422

0.401651

0.302613

0

0.207627

1,180

41

63

28.780488

0.77754

0.854237

0

null

0

null

0

null

0

null

1

null

true

0

null

0

null

0

1

0

null

0

1

0

2

a8487bc9414b8343a3c74e1a9dd0ffa5bd1bc6e4

1,012

py

Python

algs4/max_pq.py

dumpmemory/algs4-py

8555076b554583b5438ed5180e2815cf049fb233

[ "MIT" ]

230

2018-02-27T02:26:44.000Z

2022-03-29T10:26:57.000Z

algs4/max_pq.py

dumpmemory/algs4-py

8555076b554583b5438ed5180e2815cf049fb233

[ "MIT" ]

5

2018-04-06T12:08:56.000Z

2021-12-19T09:44:58.000Z

algs4/max_pq.py

dumpmemory/algs4-py

8555076b554583b5438ed5180e2815cf049fb233

[ "MIT" ]

55

2018-02-27T02:26:45.000Z

2022-03-30T03:51:41.000Z

class MaxPQ: def __init__(self): self.pq = [] def insert(self, v): self.pq.append(v) self.swim(len(self.pq) - 1) def max(self): return self.pq[0] def del_max(self, ): m = self.pq[0] self.pq[0], self.pq[-1] = self.pq[-1], self.pq[0] self.pq = self.pq[:-1] self.sink(0) return m def is_empty(self, ): return not self.pq def size(self, ): return len(self.pq) def swim(self, k): while k > 0 and self.pq[(k - 1) // 2] < self.pq[k]: self.pq[k], self.pq[ (k - 1) // 2] = self.pq[(k - 1) // 2], self.pq[k] k = k // 2 def sink(self, k): N = len(self.pq) while 2 * k + 1 <= N - 1: j = 2 * k + 1 if j < N - 1 and self.pq[j] < self.pq[j + 1]: j += 1 if self.pq[k] > self.pq[j]: break self.pq[k], self.pq[j] = self.pq[j], self.pq[k] k = j

23

65

0.414032

162

1,012

2.549383

0.185185

0.40678

0.152542

0.106538

0.348668

0.234867

0.099274

0

0.042017

0.412055

1,012

43

66

23.534884

0.652101

0

1

0.242424

false

0

0.090909

0.393939

0

null

1

0

null

0

1

0

2

a84ba5a5805b33c3b1ad0afc0fc822a27f2c5d05

2,926

py

Python

tests/test_python.py

sfeltman/libsmf

a70eb477732d2e8584af59389b4909541cf5bc98

[ "BSD-2-Clause" ]

1

2019-04-15T01:37:55.000Z

tests/test_python.py

sfeltman/libsmf

a70eb477732d2e8584af59389b4909541cf5bc98

[ "BSD-2-Clause" ]

null

tests/test_python.py

sfeltman/libsmf

a70eb477732d2e8584af59389b4909541cf5bc98

[ "BSD-2-Clause" ]

null

import os import unittest import tempfile from gi.repository import Smf class Test(unittest.TestCase): def setUp(self): self.path = os.path.dirname(__file__) def compare_smf_files(self, a, b): self.assertEqual(a.format, b.format) self.assertEqual(a.ppqn, b.ppqn) self.assertEqual(a.frames_per_second, b.frames_per_second) self.assertEqual(a.resolution, b.resolution) self.assertEqual(a.number_of_tracks, b.number_of_tracks) self.assertEqual(len(a.tracks_array), len(b.tracks_array)) for i in range(a.number_of_tracks): tracka = a.tracks_array[i] trackb = b.tracks_array[i] self.assertEqual(tracka.smf, a) self.assertEqual(trackb.smf, b) self.assertEqual(tracka.track_number, trackb.track_number) self.assertEqual(tracka.number_of_events, trackb.number_of_events) self.assertEqual(tracka.file_buffer_length, trackb.file_buffer_length) self.assertEqual(tracka.last_status, trackb.last_status) self.assertEqual(tracka.next_event_offset, trackb.next_event_offset) #self.assertEqual(tracka.next_event_number, trackb.next_event_number) #self.assertEqual(tracka.time_of_next_event, trackb.time_of_next_event) tracka_events = tracka.events_array trackb_events = trackb.events_array for j in range(tracka.number_of_events): eventa = tracka_events[j] eventb = trackb_events[j] self.assertEqual(tracka, eventa.track) self.assertEqual(trackb, eventb.track) self.assertEqual(eventa.event_number, eventb.event_number) self.assertEqual(eventa.delta_time_pulses, eventb.delta_time_pulses) self.assertEqual(eventa.time_pulses, eventb.time_pulses) self.assertEqual(eventa.time_seconds, eventb.time_seconds) self.assertEqual(eventa.track_number, eventb.track_number) self.assertEqual(eventa.midi_buffer_length, eventb.midi_buffer_length) self.assertEqual(eventa.get_buffer(), eventb.get_buffer()) @unittest.expectedFailure def test_tempo_ref_counts(self): bach = Smf.File.load(os.path.join(self.path, 'chpn_op53.mid')) tempo = bach.get_last_tempo() #self.assertEqual(tempo.ref_count, 2) bach.remove_tempo(tempo) self.assertEqual(tempo.ref_count, 1) def test_file_ref_count(self): pass def test_bach_read_write_read_compare(self): orig = Smf.File.load(os.path.join(self.path, 'chpn_op53.mid')) handle, temp_filename = tempfile.mkstemp('mid') os.close(handle) orig.save(temp_filename) new = Smf.File.load(temp_filename) self.compare_smf_files(orig, new) if __name__ == '__main__': unittest.main()

38

86

0.669515

369

2,926

5.02981

0.230352

0.210129

0.101832

0.016164

0.148707

0.116379

0.043103

0

0.002677

0.234108

2,926

76

87

38.5

0.825524

0.059467

0

0.013464

0

0.418182

1

0.090909

false

0.018182

0.072727

0

0.181818

0

null

1

0

null

0

1

0

2

a855889fb82fea703cc4439aa3a13845ae7ffaa9

1,903

py

Python

examples/ADT.py

SophiaZhyrovetska/Music_analizer

9454aa1df9a75b25526a972c620a4aea3f30541f

[ "MIT" ]

2

2018-06-26T21:49:49.000Z

2018-06-26T21:49:53.000Z

examples/ADT.py

SophiaZhyrovetska/Music_analizer

9454aa1df9a75b25526a972c620a4aea3f30541f

[ "MIT" ]

1

2018-06-20T23:17:52.000Z

2018-06-27T08:43:49.000Z

examples/ADT.py

SophiaZhyrovetska/Music_analizer

9454aa1df9a75b25526a972c620a4aea3f30541f

[ "MIT" ]

1

2018-06-26T21:49:52.000Z

class Song: "A class for representing a song" def __init__(self, name, singer): """ Initialize a new song with it's name and singer :param name: str :param singer: str """ self.name = name self.singer = singer self.mood = self.mood() def text(self): """ Returns a text of a song :return: str """ pass def mood(self): """ Returns a mood of a song :return: str """ pass def theme(self): """ Returns a theme of a song :return: str """ pass def key_words(self): """ Returns key words of a song :return: list """ pass class Singer: "A class for representing a singer" def __init__(self, name): """ Initialize a new singer with it's name :param name: str """ self.name = name class Discography: "A class for representing a discography of a singer. Uses Singer() and Song() instances" def __init__(self, singer): """ Initialize a new discography :param singer: Singer() instance """ self.singer = singer self.songs = [] def add_song(self, song): """ Adds a song to discography (self.songs) :param song: Song() instance :return: None """ pass def number_of_songs(self): """ Returns a number of songs in this discography :return: int """ pass def mood(self): """ Returns a a dictionary, with moods as keys and number of songs as values :return: dict """ pass def themes(self): """ Returns most popular themes of songs in this discography :return: list """ pass

20.462366

92

0.504467

217

1,903

4.35023

0.230415

0.081568

0.063559

0.055085

0.247881

0.177966

0.073093

0

0.405675

1,903

92

93

20.684783

0.83466

0.426169

0

0.451613

0

0.169109

0

1

0.354839

false

0.258065

0

0.451613

0

null

0

null

0

1

0

1

0

2

a87a0c58e2acdc88f9a0c4132a845c88665fa4ac

1,531

py

Python

stubs.min/Autodesk/Revit/DB/__init___parts/BRepBuilderGeometryId.py

denfromufa/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

1

2017-07-07T11:15:45.000Z

stubs.min/Autodesk/Revit/DB/__init___parts/BRepBuilderGeometryId.py

hdm-dt-fb/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

null

stubs.min/Autodesk/Revit/DB/__init___parts/BRepBuilderGeometryId.py

hdm-dt-fb/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

null

class BRepBuilderGeometryId(object,IDisposable): """ This class is used by the BRepBuilder class to identify objects it creates (faces,edges,etc.). BRepBuilderGeometryId(other: BRepBuilderGeometryId) """ def Dispose(self): """ Dispose(self: BRepBuilderGeometryId) """ pass @staticmethod def InvalidGeometryId(): """ InvalidGeometryId() -> BRepBuilderGeometryId Returns an invalid BRepBuilderGeometryId,used as a return value to indicate an error. """ pass def ReleaseUnmanagedResources(self,*args): """ ReleaseUnmanagedResources(self: BRepBuilderGeometryId,disposing: bool) """ pass def __enter__(self,*args): """ __enter__(self: IDisposable) -> object """ pass def __exit__(self,*args): """ __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """ pass def __init__(self,*args): """ x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """ pass @staticmethod def __new__(self,other): """ __new__(cls: type,other: BRepBuilderGeometryId) """ pass def __repr__(self,*args): """ __repr__(self: object) -> str """ pass IsValidObject=property(lambda self: object(),lambda self,v: None,lambda self: None) """Specifies whether the .NET object represents a valid Revit entity. Get: IsValidObject(self: BRepBuilderGeometryId) -> bool """

33.282609

215

0.701502

165

1,531

6.054545

0.412121

0.035035

0.048048

0.057057

0.113113

0

0.171783

1,531

45

216

34.022222

0.787855

0.525147

0

0.5

0

1

0.4

false

0.4

0

0.5

0

null

0

null

0

1

0

1

0

2

a8803c766a451bb61117713eb202084c40d7750f

1,435

py

Python

students/k3343/laboratory_works/Berezhnova_Marina/laboratory_work_1/django_project_flights/flights_app/models.py

TonikX/ITMO_ICT_-WebProgramming_2020

ba566c1b3ab04585665c69860b713741906935a0

[ "MIT" ]

10

2020-03-20T09:06:12.000Z

2021-07-27T13:06:02.000Z

students/k3343/laboratory_works/Berezhnova_Marina/laboratory_work_1/django_project_flights/flights_app/models.py

TonikX/ITMO_ICT_-WebProgramming_2020

ba566c1b3ab04585665c69860b713741906935a0

[ "MIT" ]

134

2020-03-23T09:47:48.000Z

2022-03-12T01:05:19.000Z

students/k3343/laboratory_works/Berezhnova_Marina/laboratory_work_1/django_project_flights/flights_app/models.py

TonikX/ITMO_ICT_-WebProgramming_2020

ba566c1b3ab04585665c69860b713741906935a0

[ "MIT" ]

71

2020-03-20T12:45:56.000Z

2021-10-31T19:22:25.000Z

from django.db import models from django.contrib.auth.models import User # Create your models here. class Companies(models.Model): name = models.CharField(max_length=30) def __str__(self): return "{}".format(self.name) class Gates(models.Model): name = models.CharField(max_length=30) def __str__(self): return "{}".format(self.name) class Flights(models.Model): company = models.ForeignKey(Companies, on_delete=models.CASCADE) gate = models.ForeignKey(Gates, on_delete=models.CASCADE) def __str__(self): return "Company: {} | Gate: {}".format(self.company, self.gate) class FlightActivities(models.Model): ACTIVITY = [ ('0', 'arrival'), ('1', 'departure') ] flight = models.ForeignKey(Flights, on_delete=models.CASCADE) activity = models.CharField(choices=ACTIVITY, default='0', max_length=1) time = models.DateField() def __str__(self): return "{} | Arrival/departure: {} | Date {}".format(self.flight, self.get_activity_display(), self.time) class FlightComments(models.Model): flight = models.ForeignKey(FlightActivities, on_delete=models.CASCADE) COMMENT_TYPE = [ ('0', 'Gate changing'), ('1', 'Lateness'), ('2', 'Other') ] com_type = models.CharField(choices=COMMENT_TYPE, default='0', max_length=1) com_text = models.CharField(max_length=1024) author = models.ForeignKey(User, on_delete=models.CASCADE)

27.075472

110

0.687108

175

1,435

5.451429

0.325714

0.057652

0.073375

0.110063

0.197065

0.159329

0

0.014202

0.165854

1,435

52

111

27.596154

0.78279

0.016725

0

0.228571

0

0.078779

0

1

0.114286

false

0

0.057143

0.114286

0.8

0

null

0

null

0

1

0

2

a883398d1013f82065fdcd6cb3f64c0a32a024f7

743

py

Python

membership/urls.py

kay-han/building-blog

2bdbee68b484193c636ed869b2de605df67b2a48

[ "Unlicense" ]

null

membership/urls.py

kay-han/building-blog

2bdbee68b484193c636ed869b2de605df67b2a48

[ "Unlicense" ]

null

membership/urls.py

kay-han/building-blog

2bdbee68b484193c636ed869b2de605df67b2a48

[ "Unlicense" ]

null

from django.urls import path from .views import UserRegisterView, UserEditView, PasswordsChangeView from django.contrib.auth import views as auth_views #It allows using some of the views that come with the authentication system comes with django from . import views urlpatterns = [ path('registeration/', UserRegisterView.as_view(), name='registeration'), path('edit_profile/', UserEditView.as_view(), name='edit-profile'), #path('password/', auth_views.PasswordsChangeView.as_view(template_name='registration/change-password.html')), path('password/', PasswordsChangeView.as_view(template_name='registration/change-password.html')), path('password_success/', views.password_success, name='password_success.html'), ]

57.153846

146

0.776581

90

743

6.277778

0.4

0.042478

0.035398

0.116814

0.279646

0

0.106326

743

12

147

61.916667

0.850904

0.270525

0

0.244444

0.1

0

1

0

false

0.3

0.4

0

0.4

0

null

0

null

0

1

0

2

a89d5ea301daab707e4e307ee463a9e25963e7c1

7,626

py

Python

tests/epc_schemes/test_giai.py

nedap/retail-epcpy

f5a454f2a06053f64bc42e6c6411fbd6cb47e745

[ "MIT" ]

2

2022-03-21T08:22:30.000Z

2022-03-22T12:32:29.000Z

tests/epc_schemes/test_giai.py

nedap/retail-epcpy

f5a454f2a06053f64bc42e6c6411fbd6cb47e745

[ "MIT" ]

1

2022-03-28T14:48:52.000Z

tests/epc_schemes/test_giai.py

nedap/retail-epcpy

f5a454f2a06053f64bc42e6c6411fbd6cb47e745

[ "MIT" ]

null

import unittest from epcpy.epc_schemes.giai import GIAI, GIAIFilterValue from tests.epc_schemes.test_base_scheme import ( TestEPCSchemeInitMeta, TestGS1ElementMeta, TestTagEncodableMeta, ) class TestGIAIInit( unittest.TestCase, metaclass=TestEPCSchemeInitMeta, scheme=GIAI, valid_data=[ { "name": "test_valid_giai_1", "uri": "urn:epc:id:giai:0614141.12345400", }, { "name": "test_valid_giai_2", "uri": "urn:epc:id:giai:0614141.0", }, { "name": "test_valid_giai_3", "uri": "urn:epc:id:giai:0614141.1ABc%2FD", }, { "name": "test_valid_giai_4", "uri": "urn:epc:id:giai:061411.01ABc%2FD", }, { "name": "test_valid_giai_5", "uri": "urn:epc:id:giai:012345.012345678901234567890123", }, { "name": "test_valid_giai_6", "uri": "urn:epc:id:giai:012345678901.012345678901234567", }, ], invalid_data=[ { "name": "test_invalid_giai_identifier", "uri": "urn:epc:id:gai:061411.01ABc%2FD", }, { "name": "test_invalid_giai_company_prefix_1", "uri": "urn:epc:id:giai:06141.1ABc%2FD", }, { "name": "test_invalid_giai_company_prefix_2", "uri": "urn:epc:id:giai:0614111111111.1ABc%2FD", }, { "name": "test_invalid_giai_serial_too_long_1", "uri": "urn:epc:id:giai:012345.0123456789012345678901234", }, { "name": "test_invalid_giai_serial_too_long_1", "uri": "urn:epc:id:giai:012345.0123456789012345678901234", }, { "name": "test_invalid_giai_serial_too_long_2", "uri": "urn:epc:id:giai:012345678901.0123456789012345678", }, ], ): pass class TestGIAIGS1Key( unittest.TestCase, metaclass=TestGS1ElementMeta, scheme=GIAI, valid_data=[ { "name": "test_valid_giai_gs1_key_1", "uri": "urn:epc:id:giai:0614141.12345400", "gs1_key": "061414112345400", "gs1_element_string": "(8004)061414112345400", "company_prefix_length": 7, }, { "name": "test_valid_giai_gs1_key_2", "uri": "urn:epc:id:giai:0614141.0", "gs1_key": "06141410", "gs1_element_string": "(8004)06141410", "company_prefix_length": 7, }, { "name": "test_valid_giai_gs1_key_3", "uri": "urn:epc:id:giai:0614141.1ABc%2FD", "gs1_key": "06141411ABc/D", "gs1_element_string": "(8004)06141411ABc/D", "company_prefix_length": 7, }, { "name": "test_valid_giai_gs1_key_4", "uri": "urn:epc:id:giai:061411.01ABc%2FD", "gs1_key": "06141101ABc/D", "gs1_element_string": "(8004)06141101ABc/D", "company_prefix_length": 6, }, { "name": "test_valid_giai_gs1_key_5", "uri": "urn:epc:id:giai:012345.012345678901234567890123", "gs1_key": "012345012345678901234567890123", "gs1_element_string": "(8004)012345012345678901234567890123", "company_prefix_length": 6, }, { "name": "test_valid_giai_gs1_key_6", "uri": "urn:epc:id:giai:012345678901.012345678901234567", "gs1_key": "012345678901012345678901234567", "gs1_element_string": "(8004)012345678901012345678901234567", "company_prefix_length": 12, }, ], invalid_data=[], ): pass class TestGIAITagEncodable( unittest.TestCase, metaclass=TestTagEncodableMeta, scheme=GIAI, valid_data=[ { "name": "test_valid_giai_tag_encodable_1", "uri": "urn:epc:id:giai:0614141.12345400", "kwargs": { "binary_coding_scheme": GIAI.BinaryCodingScheme.GIAI_202, "filter_value": GIAIFilterValue.RAIL_VEHICLE, }, "tag_uri": "urn:epc:tag:giai-202:1.0614141.12345400", "hex": "3834257BF58B266D1AB460C00000000000000000000000000000", }, { "name": "test_valid_giai_tag_encodable_2", "uri": "urn:epc:id:giai:0614141.0", "kwargs": { "binary_coding_scheme": GIAI.BinaryCodingScheme.GIAI_96, "filter_value": GIAIFilterValue.RAIL_VEHICLE, }, "tag_uri": "urn:epc:tag:giai-96:1.0614141.0", "hex": "3434257BF400000000000000", }, { "name": "test_valid_giai_tag_encodable_3", "uri": "urn:epc:id:giai:0614141.1ABc%2FD", "kwargs": { "binary_coding_scheme": GIAI.BinaryCodingScheme.GIAI_202, "filter_value": GIAIFilterValue.ALL_OTHERS, }, "tag_uri": "urn:epc:tag:giai-202:0.0614141.1ABc%2FD", "hex": "3814257BF58C1858D7C400000000000000000000000000000000", }, { "name": "test_valid_giai_tag_encodable_4", "uri": "urn:epc:id:giai:061411.01ABc%2FD", "kwargs": { "binary_coding_scheme": GIAI.BinaryCodingScheme.GIAI_202, "filter_value": GIAIFilterValue.RESERVED_4, }, "tag_uri": "urn:epc:tag:giai-202:4.061411.01ABc%2FD", "hex": "38983BF8D831830B1AF880000000000000000000000000000000", }, { "name": "test_valid_giai_tag_encodable_5", "uri": "urn:epc:id:giai:012345.012345678901234567890123", "kwargs": { "binary_coding_scheme": GIAI.BinaryCodingScheme.GIAI_202, "filter_value": GIAIFilterValue.RAIL_VEHICLE, }, "tag_uri": "urn:epc:tag:giai-202:1.012345.012345678901234567890123", "hex": "38380C0E583164CDA356CDDC3960C593368D5B3770E583164CC0", }, { "name": "test_valid_giai_tag_encodable_6", "uri": "urn:epc:id:giai:0614141.12345400", "kwargs": { "binary_coding_scheme": GIAI.BinaryCodingScheme.GIAI_96, "filter_value": GIAIFilterValue.RAIL_VEHICLE, }, "tag_uri": "urn:epc:tag:giai-96:1.0614141.12345400", "hex": "3434257BF400000000BC6038", }, { "name": "test_valid_giai_tag_encodable_7", "uri": "urn:epc:id:giai:0614141.02", "kwargs": { "binary_coding_scheme": GIAI.BinaryCodingScheme.GIAI_202, "filter_value": GIAIFilterValue.RAIL_VEHICLE, }, "tag_uri": "urn:epc:tag:giai-202:1.0614141.02", "hex": "3834257BF5832000000000000000000000000000000000000000", }, ], invalid_data=[ { "name": "test_invalid_giai_tag_encodable_invalid_serial_1", "uri": "urn:epc:id:giai:0614141.02", "kwargs": { "binary_coding_scheme": GIAI.BinaryCodingScheme.GIAI_96, "filter_value": GIAIFilterValue.RAIL_VEHICLE, }, }, { "name": "test_invalid_giai_tag_encodable_invalid_serial_2", "uri": "urn:epc:id:giai:061411.11ABc%2FD", "kwargs": { "binary_coding_scheme": GIAI.BinaryCodingScheme.GIAI_96, "filter_value": GIAIFilterValue.RESERVED_4, }, }, ], ): pass

34.663636

80

0.550747

720

7,626

5.527778

0.134722

0.051256

0.076884

0.074623

0.682915

0.656533

0.574372

0.545477

0.403769

0.36005

0

0.216465

0.31668

7,626

219

81

34.821918

0.547304

0

0.363208

0

0.450433

0.325334

0

1

0

true

0.014151

0

0.028302

0

null

0

1

0

null

0

1

0

2

a89fa94a38be0f7ff83779a36c140bcbf11011b7

1,422

py

Python

publicacion/migrations/0002_remove_publicacion_user_publicacion_autor_and_more.py

chelocastillo1/test

b783e64dbd3071c3ed074e9ce23da047e9bad97d

[ "CC0-1.0" ]

1

2021-12-12T22:27:52.000Z

publicacion/migrations/0002_remove_publicacion_user_publicacion_autor_and_more.py

chelocastillo1/test

b783e64dbd3071c3ed074e9ce23da047e9bad97d

[ "CC0-1.0" ]

null

publicacion/migrations/0002_remove_publicacion_user_publicacion_autor_and_more.py

chelocastillo1/test

b783e64dbd3071c3ed074e9ce23da047e9bad97d

[ "CC0-1.0" ]

null

# Generated by Django 4.0 on 2021-12-15 02:51 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('cuenta', '0001_initial'), ('publicacion', '0001_initial'), ] operations = [ migrations.RemoveField( model_name='publicacion', name='user', ), migrations.AddField( model_name='publicacion', name='autor', field=models.ForeignKey(default=0, on_delete=django.db.models.deletion.DO_NOTHING, to='cuenta.usuario'), ), migrations.AddField( model_name='publicacion', name='destacado', field=models.BooleanField(default=False), ), migrations.AddField( model_name='publicacion', name='imagen', field=models.ImageField(default=None, upload_to=''), ), migrations.AlterField( model_name='publicacion', name='fechaCreacion', field=models.DateTimeField(), ), migrations.AlterField( model_name='publicacion', name='fechaEdicion', field=models.DateTimeField(), ), migrations.AlterField( model_name='publicacion', name='titulo', field=models.CharField(max_length=100), ), ]

28.44

116

0.561181

123

1,422

6.382114

0.447154

0.080255

0.178344

0.214013

0.389809

0.173248

0

0.026887

0.319972

1,422

49

117

29.020408

0.784902

0.030239

0

0.511628

1

0

0.135802

0

1

0

false

0

0.046512

0

0.116279

0

null

0

1

0

1

0

null

0

2

a8a48dba10dc8bcece98d956d127819f587eacf1

13,796

py

Python

src/main/java/nl/Ipsen5Server/Service/kik-bot-api-unofficial/examples/kik_unofficial/protobuf/common/v2/model_pb2.py

anthonyscheeres/Ipen5BackendGroep11

e2675c2ac6580f0a6f1d9e5f755f19405d17e514

[ "Apache-2.0" ]

null

src/main/java/nl/Ipsen5Server/Service/kik-bot-api-unofficial/examples/kik_unofficial/protobuf/common/v2/model_pb2.py

anthonyscheeres/Ipen5BackendGroep11

e2675c2ac6580f0a6f1d9e5f755f19405d17e514

[ "Apache-2.0" ]

null

src/main/java/nl/Ipsen5Server/Service/kik-bot-api-unofficial/examples/kik_unofficial/protobuf/common/v2/model_pb2.py

anthonyscheeres/Ipen5BackendGroep11

e2675c2ac6580f0a6f1d9e5f755f19405d17e514

[ "Apache-2.0" ]

null

# Generated by the protocol buffer compiler. DO NOT EDIT! # source: common/v2/model.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 from google.protobuf import descriptor_pb2 # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() import kik_unofficial.protobuf.kik_options_pb2 as kik__options__pb2 import kik_unofficial.protobuf.protobuf_validation_pb2 as protobuf__validation__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='common/v2/model.proto', package='common.v2', syntax='proto3', serialized_pb=_b('\n\x15\x63ommon/v2/model.proto\x12\tcommon.v2\x1a\x11kik_options.proto\x1a\x19protobuf_validation.proto\"K\n\tAccountId\x12>\n\nlocal_part\x18\x01 \x01(\tB*\xca\x9d%&\x08\x01\x12\"^[a-z_0-9\\.]{2,30}(_[a-z0-9]{3})?$\")\n\tPersonaId\x12\x1c\n\traw_value\x18\x01 \x01(\x0c\x42\t\xca\x9d%\x05\x08\x01\x30\x80\x01\"(\n\x06\x43hatId\x12\x1e\n\traw_value\x18\x01 \x01(\x0c\x42\x0b\xca\x9d%\x07\x08\x01(\x01\x30\x80\x04\"A\n\nOneToOneId\x12\x33\n\x08personas\x18\x01 \x03(\x0b\x32\x14.common.v2.PersonaIdB\x0b\xca\x9d%\x07\x08\x01x\x02\x80\x01\x02\"/\n\x10\x43lientInstanceId\x12\x1b\n\traw_value\x18\x01 \x01(\x0c\x42\x08\xca\x9d%\x04\x08\x01\x30\x64\"%\n\x04Uuid\x12\x1d\n\traw_value\x18\x01 \x01(\x0c\x42\n\xca\x9d%\x06\x08\x01(\x10\x30\x10\"\x82\x01\n\x05\x45mail\x12y\n\x05\x65mail\x18\x01 \x01(\tBj\xca\x9d%f\x08\x01\x12_^[\\w\\-+]+(\\.[\\w\\-+]+)*@[A-Za-z0-9][A-Za-z0-9\\-]*(\\.[A-Za-z0-9][A-Za-z0-9\\-]*)*(\\.[A-Za-z]{2,})$0\xf8\x07\"4\n\x08Username\x12(\n\x08username\x18\x02 \x01(\tB\x16\xca\x9d%\x12\x08\x01\x12\x0e^[\\w\\.]{2,30}$B~\n\x15\x63om.kik.gen.common.v2P\x01ZLgithub.com/kikinteractive/xiphias-model-common/generated/go/common/v2;common\xa0\x01\x01\xa2\x02\x0bKPBCommonV2\xaa\xa3*\x02\x08\x01\x62\x06proto3') , dependencies=[kik__options__pb2.DESCRIPTOR,protobuf__validation__pb2.DESCRIPTOR,]) _sym_db.RegisterFileDescriptor(DESCRIPTOR) _ACCOUNTID = _descriptor.Descriptor( name='AccountId', full_name='common.v2.AccountId', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='local_part', full_name='common.v2.AccountId.local_part', 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, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%&\010\001\022\"^[a-z_0-9\\.]{2,30}(_[a-z0-9]{3})?$'))), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=82, serialized_end=157, ) _PERSONAID = _descriptor.Descriptor( name='PersonaId', full_name='common.v2.PersonaId', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='raw_value', full_name='common.v2.PersonaId.raw_value', index=0, number=1, type=12, cpp_type=9, label=1, has_default_value=False, default_value=_b(""), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\005\010\0010\200\001'))), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=159, serialized_end=200, ) _CHATID = _descriptor.Descriptor( name='ChatId', full_name='common.v2.ChatId', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='raw_value', full_name='common.v2.ChatId.raw_value', index=0, number=1, type=12, cpp_type=9, label=1, has_default_value=False, default_value=_b(""), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\007\010\001(\0010\200\004'))), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=202, serialized_end=242, ) _ONETOONEID = _descriptor.Descriptor( name='OneToOneId', full_name='common.v2.OneToOneId', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='personas', full_name='common.v2.OneToOneId.personas', 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, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\007\010\001x\002\200\001\002'))), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=244, serialized_end=309, ) _CLIENTINSTANCEID = _descriptor.Descriptor( name='ClientInstanceId', full_name='common.v2.ClientInstanceId', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='raw_value', full_name='common.v2.ClientInstanceId.raw_value', index=0, number=1, type=12, cpp_type=9, label=1, has_default_value=False, default_value=_b(""), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\004\010\0010d'))), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=311, serialized_end=358, ) _UUID = _descriptor.Descriptor( name='Uuid', full_name='common.v2.Uuid', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='raw_value', full_name='common.v2.Uuid.raw_value', index=0, number=1, type=12, cpp_type=9, label=1, has_default_value=False, default_value=_b(""), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\006\010\001(\0200\020'))), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=360, serialized_end=397, ) _EMAIL = _descriptor.Descriptor( name='Email', full_name='common.v2.Email', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='email', full_name='common.v2.Email.email', 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, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%f\010\001\022_^[\\w\\-+]+(\\.[\\w\\-+]+)*@[A-Za-z0-9][A-Za-z0-9\\-]*(\\.[A-Za-z0-9][A-Za-z0-9\\-]*)*(\\.[A-Za-z]{2,})$0\370\007'))), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=400, serialized_end=530, ) _USERNAME = _descriptor.Descriptor( name='Username', full_name='common.v2.Username', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='username', full_name='common.v2.Username.username', index=0, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=_descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\022\010\001\022\016^[\\w\\.]{2,30}$'))), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=532, serialized_end=584, ) _ONETOONEID.fields_by_name['personas'].message_type = _PERSONAID DESCRIPTOR.message_types_by_name['AccountId'] = _ACCOUNTID DESCRIPTOR.message_types_by_name['PersonaId'] = _PERSONAID DESCRIPTOR.message_types_by_name['ChatId'] = _CHATID DESCRIPTOR.message_types_by_name['OneToOneId'] = _ONETOONEID DESCRIPTOR.message_types_by_name['ClientInstanceId'] = _CLIENTINSTANCEID DESCRIPTOR.message_types_by_name['Uuid'] = _UUID DESCRIPTOR.message_types_by_name['Email'] = _EMAIL DESCRIPTOR.message_types_by_name['Username'] = _USERNAME AccountId = _reflection.GeneratedProtocolMessageType('AccountId', (_message.Message,), dict( DESCRIPTOR = _ACCOUNTID, __module__ = 'common.v2.model_pb2' # @@protoc_insertion_point(class_scope:common.v2.AccountId) )) _sym_db.RegisterMessage(AccountId) PersonaId = _reflection.GeneratedProtocolMessageType('PersonaId', (_message.Message,), dict( DESCRIPTOR = _PERSONAID, __module__ = 'common.v2.model_pb2' # @@protoc_insertion_point(class_scope:common.v2.PersonaId) )) _sym_db.RegisterMessage(PersonaId) ChatId = _reflection.GeneratedProtocolMessageType('ChatId', (_message.Message,), dict( DESCRIPTOR = _CHATID, __module__ = 'common.v2.model_pb2' # @@protoc_insertion_point(class_scope:common.v2.ChatId) )) _sym_db.RegisterMessage(ChatId) OneToOneId = _reflection.GeneratedProtocolMessageType('OneToOneId', (_message.Message,), dict( DESCRIPTOR = _ONETOONEID, __module__ = 'common.v2.model_pb2' # @@protoc_insertion_point(class_scope:common.v2.OneToOneId) )) _sym_db.RegisterMessage(OneToOneId) ClientInstanceId = _reflection.GeneratedProtocolMessageType('ClientInstanceId', (_message.Message,), dict( DESCRIPTOR = _CLIENTINSTANCEID, __module__ = 'common.v2.model_pb2' # @@protoc_insertion_point(class_scope:common.v2.ClientInstanceId) )) _sym_db.RegisterMessage(ClientInstanceId) Uuid = _reflection.GeneratedProtocolMessageType('Uuid', (_message.Message,), dict( DESCRIPTOR = _UUID, __module__ = 'common.v2.model_pb2' # @@protoc_insertion_point(class_scope:common.v2.Uuid) )) _sym_db.RegisterMessage(Uuid) Email = _reflection.GeneratedProtocolMessageType('Email', (_message.Message,), dict( DESCRIPTOR = _EMAIL, __module__ = 'common.v2.model_pb2' # @@protoc_insertion_point(class_scope:common.v2.Email) )) _sym_db.RegisterMessage(Email) Username = _reflection.GeneratedProtocolMessageType('Username', (_message.Message,), dict( DESCRIPTOR = _USERNAME, __module__ = 'common.v2.model_pb2' # @@protoc_insertion_point(class_scope:common.v2.Username) )) _sym_db.RegisterMessage(Username) DESCRIPTOR.has_options = True DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\n\025com.kik.gen.common.v2P\001ZLgithub.com/kikinteractive/xiphias-model-common/generated/go/common/v2;common\240\001\001\242\002\013KPBCommonV2\252\243*\002\010\001')) _ACCOUNTID.fields_by_name['local_part'].has_options = True _ACCOUNTID.fields_by_name['local_part']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%&\010\001\022\"^[a-z_0-9\\.]{2,30}(_[a-z0-9]{3})?$')) _PERSONAID.fields_by_name['raw_value'].has_options = True _PERSONAID.fields_by_name['raw_value']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\005\010\0010\200\001')) _CHATID.fields_by_name['raw_value'].has_options = True _CHATID.fields_by_name['raw_value']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\007\010\001(\0010\200\004')) _ONETOONEID.fields_by_name['personas'].has_options = True _ONETOONEID.fields_by_name['personas']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\007\010\001x\002\200\001\002')) _CLIENTINSTANCEID.fields_by_name['raw_value'].has_options = True _CLIENTINSTANCEID.fields_by_name['raw_value']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\004\010\0010d')) _UUID.fields_by_name['raw_value'].has_options = True _UUID.fields_by_name['raw_value']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\006\010\001(\0200\020')) _EMAIL.fields_by_name['email'].has_options = True _EMAIL.fields_by_name['email']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%f\010\001\022_^[\\w\\-+]+(\\.[\\w\\-+]+)*@[A-Za-z0-9][A-Za-z0-9\\-]*(\\.[A-Za-z0-9][A-Za-z0-9\\-]*)*(\\.[A-Za-z]{2,})$0\370\007')) _USERNAME.fields_by_name['username'].has_options = True _USERNAME.fields_by_name['username']._options = _descriptor._ParseOptions(descriptor_pb2.FieldOptions(), _b('\312\235%\022\010\001\022\016^[\\w\\.]{2,30}$')) # @@protoc_insertion_point(module_scope)

37.79726

1,243

0.711293

1,781

13,796

5.211679

0.130264

0.032752

0.021978

0.071429

0.65794

0.577031

0.551605

0.538246

0.512821

0

0.072892

0.125906

13,796

364

1,244

37.901099

0.696824

0.044796

0

0.574132

1

0.025237

0.25123

0.190688

0

1

0

false

0

0.025237

0

0.025237

0

null

0

1

0

1

0

null

0

2

a8a830fc1bf61dcb27f3d46222c49301867517cd

1,216

py

Python

woodstock/auth_backends.py

allink/woodstock

afafecb7c4454f96e51c051044ed8ed74853c048

[ "BSD-3-Clause" ]

null

woodstock/auth_backends.py

allink/woodstock

afafecb7c4454f96e51c051044ed8ed74853c048

[ "BSD-3-Clause" ]

null

woodstock/auth_backends.py

allink/woodstock

afafecb7c4454f96e51c051044ed8ed74853c048

[ "BSD-3-Clause" ]

null

from woodstock.models import Invitee, Participant from woodstock import settings from django.core.exceptions import ObjectDoesNotExist class PersonBackend(object): supports_object_permissions = False supports_anonymous_user = False supports_inactive_user = False def authenticate(self, username=None, password=None, user=None): if user: return user try: if settings.USERNAME_FIELD: get_filter = {settings.USERNAME_FIELD: username} user = self.model.objects.get(**get_filter) if user.check_password(password): return user else: return self.model.objects.get(password=password) except ObjectDoesNotExist: return None def get_user(self, user_id): try: return self.model.objects.get(pk=user_id) except ObjectDoesNotExist: return None class InviteeBackend(PersonBackend): """ Authenticates against woodstock.models.Invitee. """ model = Invitee class ParticipantBackend(PersonBackend): """ Authenticates against woodstock.models.Participant. """ model = Participant

27.636364

68

0.649671

120

1,216

6.466667

0.358333

0.05799

0.061856

0.073454

0.188144

0

0.279605

1,216

43

69

28.27907

0.885845

0.081414

0

0.275862

0

1

0.068966

false

0.103448

0

0.655172

0

null

0

null

0

1

0

1

0

2

a8b7116ef65af10b72e0c07da19900a3a9d62e85

48,908

py

Python

deep_disfluency/corpus/tree_pos_map_writer.py

askender/deep_disfluency

bea8403ed954df8eadd3e2b9d98bb7c2b416a665

[ "MIT" ]

null

deep_disfluency/corpus/tree_pos_map_writer.py

askender/deep_disfluency

bea8403ed954df8eadd3e2b9d98bb7c2b416a665

[ "MIT" ]

null

deep_disfluency/corpus/tree_pos_map_writer.py

askender/deep_disfluency

bea8403ed954df8eadd3e2b9d98bb7c2b416a665

[ "MIT" ]

null

# -*- coding: utf-8 -*- from collections import defaultdict import re from nltk import tree from swda import CorpusReader from tree_pos_map import TreeMapCorpus from tree_pos_map import POSMapCorpus possibleMistranscription = [("its", "it's"), ("Its", "It's"), ("it's", "its"), ("It's", "Its"), ("whose", "who's"), ("Whose", "Who's"), ("who's", "whose"), ("Who's", "Whose"), ("you're", "your"), ("You're", "Your"), ("your", "you're"), ("Your", "You're"), ("their", "they're"), ("Their", "They're"), ("they're", "their"), ("They're", "Their"), ("programme", "program"), ("program", "programme"), ("centre", "center"), ("center", "centre"), ("travelling", "traveling"), ("traveling", "travelling"), ("colouring", "coloring"), ("coloring", "colouring")] class TreeMapWriter: """Object which writes mappings from the words in utterances to the nodes of the corresponding trees in a treebank """ def __init__(self, corpus_path="../swda", metadata_path="swda-metadata.csv", target_folder_path="Maps", ranges=None, errorLog=None): print "started TreeMapWriting" self.write_to_file(corpus_path, metadata_path, target_folder_path, ranges, errorLog) def write_to_file(self, corpus_path, metadata_path, target_folder_path, ranges, errorLog): """Writes files to a target folder with the mappings from words in utterances to tree nodes in trees. """ if errorLog: errorLog = open(errorLog, 'w') corpus = CorpusReader(corpus_path, metadata_path) # Iterate through all transcripts incorrectTrees = 0 folder = None corpus_file = None for trans in corpus.iter_transcripts(): # print "iterating",trans.conversation_no if not trans.has_pos(): continue # print "has pos" if ranges and not trans.conversation_no in ranges: continue # print "in range" # just look at transcripts WITH trees as compliment to the # below models if not trans.has_trees(): continue end = trans.swda_filename.rfind("/") start = trans.swda_filename.rfind("/", 0, end) c_folder = trans.swda_filename[start + 1:end] if c_folder != folder: # for now splitting the maps by folder folder = c_folder if corpus_file: corpus_file.close() corpus_file = open(target_folder_path + "/Tree_map_{0}.csv.text".format(folder), 'w') wordTreeMapList = TreeMapCorpus(False, errorLog) print "new map for folder", folder translist = trans.utterances translength = len(translist) count = 0 # iterating through transcript utterance by utterance # create list of tuples i.e. map from word to the index(ices) # (possibly multiple or null) of the relevant leaf/ves # of a given tree i.e. utt.tree[0].leaves[0] would be a pair (0,0)) while count < translength: utt = trans.utterances[count] words = utt.text_words() wordTreeMap = [] # [((word), (List of LeafIndices))] forwardtrack = 0 backtrack = 0 continued = False # print "\n COUNT" + str(count) # print utt.damsl_act_tag() if len(utt.trees) == 0 or utt.damsl_act_tag() == "x": wordTreeMap.append((utt, [])) # just dummy value # errormessage = "WARNING: NO TREE for file/utt: " +\ # str(utt.swda_filename) + " " + utt.caller + "." + \ # str(utt.utterance_index) + "." + \ #str(utt.subutterance_index) + " " + utt.text # print(errormessage) count += 1 continue # raw_input() # indices for which tree and leaf we're at: i = 0 # tree j = 0 # leaf # initialise pairs of trees and ptb pairs trees = [] for l in range(0, len(utt.trees)): trees.append( (utt.ptb_treenumbers[l], count, l, utt.trees[l])) # print "TREES = " # for tree in trees: # print tree origtrees = list(trees) origcount = count # overcoming the problem of previous utterances contributing # to the tree at this utterance, we need to add the words from # the previous utt add in all the words from previous utterance # with a dialogue act tag/or the same tree? # check that the last tree in the previous utterance # is the same as the previous one previousUttSame = trans.previous_utt_same_speaker(utt) # print previousUttSame lastTreeMap = None if previousUttSame: # print "search for previous full act utt # for " + str(utt.swda_filename) + # str(utt.transcript_index) lastTreeMap = wordTreeMapList.get_treemap( trans, previousUttSame) if ((not lastTreeMap) or (len(lastTreeMap) == 0) or (len(lastTreeMap) == 1 and lastTreeMap[0][1] == [])): # print "no last tree map, backwards searching" while previousUttSame and \ ((not lastTreeMap) or (len(lastTreeMap) == 0) or (len(lastTreeMap) == 1 and lastTreeMap[0][1] == [])): previousUttSame = trans.previous_utt_same_speaker( previousUttSame) # go back one more lastTreeMap = wordTreeMapList.get_treemap(trans, previousUttSame) if previousUttSame: pass # print previousUttSame.transcript_index if not lastTreeMap: pass # print "no last treemap found for:" # print utt.swda_filename # print utt.transcript_index if lastTreeMap and \ (utt.damsl_act_tag() == "+" or (len(lastTreeMap.treebank_numbers) > 0 and lastTreeMap.treebank_numbers[-1] == utt.ptb_treenumbers[0])): continued = True # might have to backtrack # now checking for wrong trees lastPTB = lastTreeMap.treebank_numbers lastIndexes = lastTreeMap.transcript_numbers lastTreesTemp = lastTreeMap.get_trees(trans) lastTrees = [] for i in range(0, len(lastPTB)): lastTrees.append([lastPTB[i], lastIndexes[i][0], lastIndexes[i][1], lastTreesTemp[i]]) if not (lastPTB[-1] == utt.ptb_treenumbers[0]): # print "not same, need to correct!" # print words # print trees # print "last one" # print previousUttSame.text_words() # print lastTrees if utt.ptb_treenumbers[0] - lastPTB[-1] > 1: # backtrack and redo the antecedent count = count - (count - lastIndexes[-1][0]) utt = previousUttSame words = utt.text_words() mytrees = [] for i in range(0, len(lastTrees) - 1): mytrees.append(lastTrees[i]) trees = mytrees + [origtrees[0]] # print "\n(1)backtrack to with new trees:" backtrack = 1 # print utt.transcript_index # print words # print trees # raw_input() # alternately, this utt's tree may be further back # than its antecdent's, rare mistake elif utt.ptb_treenumbers[0] < lastTrees[-1][0]: # continue with this utterance and trees # (if there are any), but replace its first # tree with its antecdents last one forwardtrack = 1 trees = [lastTrees[-1]] + origtrees[1:] # print "\n(2)replacing first one to lasttreemap's:" # print words # print trees # raw_input() if backtrack != 1: # we should have no match found_treemap = False # resetting # for t in wordTreeMapList.keys(): # print t # print wordTreeMapList[t] for t in range(len(lastTreeMap) - 1, -1, -1): # print lastTreeMap[t][1] # if there is a leafIndices for the # word being looked at, gets last mapped one if len(lastTreeMap[t][1]) > 0: # print "last treemapping of last # caller utterance = # " + str(lastTreeMap[t][1][-1]) j = lastTreeMap[t][1][-1][1] + 1 found_treemap = True # print "found last mapping, j -1 = " + str(j-1) # raw_input() break if not found_treemap: pass # print "NO matched last TREEMAP found for \ # previous Utt Same Speaker of " + \ # str(trans.swda_filename) + " " + \ # str(utt.transcript_index) # print lastTreeMap # for tmap in wordTreeMapList.keys(): # print tmap # print wordTreeMapList[tmap] # raw_input() possibleComment = False # can have comments, flag mistranscribe = False LeafIndices = [] # possibly empty list of leaf indices word = words[0] # loop until no more words left to be matched in utterance while len(words) > 0: # print "top WORD:" + word if not mistranscribe: wordtest = re.sub(r"[\.\,\?\"\!]", "", word) wordtest = wordtest.replace("(", "").replace(")", "") match = False LeafIndices = [] # possibly empty list of leaf indices if (possibleComment or word[0:1] in ["{", "}", "-"] or word in ["/", ".", ",", "]"] or wordtest == "" or any([x in word for x in ["<", ">", "*", "[", "+", "]]", "...", "#", "="]])): # no tree equivalent for {D } type annotations if (word[0:1] == "-" or any([x in word for x in ["*", "<<", "<+", "[[", "<"]])) \ and not possibleComment: possibleComment = True if possibleComment: #print("match COMMENT!:" + word) # raw_input() LeafIndices = [] match = True #wordTreeMap.append((word, LeafIndices)) if any([x in word for x in [">>", "]]", ">"]]) or \ word[0] == "-": # turn off comment possibleComment = False #del words[0] # LeadIndices will be null here wordTreeMap.append((word, LeafIndices)) LeafIndices = [] match = True # print "match annotation!:" + word del words[0] # word is consumed, should always be one if len(words) > 0: word = words[0] wordtest = re.sub(r"[\.\,\?\/\)\(\"\!]", "", word) wordtest = wordtest.replace("(", "") wordtest = wordtest.replace(")", "") else: break continue # carry on to next word without updating indices? else: while i < len(trees): # print "i number of trees :" + str(len(utt.trees)) # print "i tree number :" + str(i) # print "i loop word :" + word tree = trees[i][3] # print "looking at ptb number " + str(trees[i][0]) # print "looking at index number " \ #+ str(trees[i][1])+","+str(trees[i][2]) while j < len(tree.leaves()): leaf = tree.leaves()[j] # print "j number of leaves : " \ #+ str(len(tree.leaves())) # print "j loop word : " + word # print "j loop wordtest : " + wordtest # print "j leaf : " + str(j) + " " + leaf breaker = False # exact match if wordtest == leaf or word == leaf: LeafIndices.append((i, j)) wordTreeMap.append((word, LeafIndices)) # print("match!:" + word + " " + \ # str(utt.swda_filename) + " " + \ # utt.caller + "." + \ # str(utt.utterance_index) + \ # "." + str(utt.subutterance_index)) del words[0] # word is consumed if len(words) > 0: word = words[0] # next word wordtest = re.sub( r"[\.\,\?\/\)$\"\!]", "", word) wordtest = wordtest.replace("(", "") wordtest = wordtest.replace(")", "") LeafIndices = [] j += 1 # increment loop to next leaf match = True breaker = True # raw_input() break elif leaf in wordtest or \ leaf in word and not leaf == ",": testleaf = leaf LeafIndices.append((i, j)) j += 1 for k in range(j, j + 3): # 3 beyond if (k >= len(tree.leaves())): j = 0 i += 1 #breaker = True breaker = True break # got to next tree if (testleaf + tree.leaves()[k]) \ in wordtest or (testleaf + tree.leaves()[k])\ in word: testleaf += tree.leaves()[k] LeafIndices.append((i, k)) j += 1 # concatenation if testleaf == wordtest or \ testleaf == word: # word matched wordTreeMap.append((word, LeafIndices)) del words[0] # remove word # print "match!:" + word +\ #str(utt.swda_filename) + " "\ # + utt.caller + "." + \ # str(utt.utterance_index) +\ # "." + \ # str(utt.subutterance_index)) if len(words) > 0: word = words[0] wordtest = re.sub( r"[\.\,\?\/$\(\"\!]", "", word) wordtest = wordtest.\ replace("(", "") wordtest = wordtest.\ replace(")", "") # reinitialise leaves LeafIndices = [] j = k + 1 match = True breaker = True # raw_input() break else: # otherwise go on j += 1 if breaker: break if match: break if j >= len(tree.leaves()): j = 0 i += 1 if match: break # could not match word! try mistranscriptions first: if not match: if not mistranscribe: # one final stab at matching! mistranscribe = True for pair in possibleMistranscription: if pair[0] == wordtest: wordtest = pair[1] if len(wordTreeMap) > 0: if len(wordTreeMap[-1][1]) > 0: i = wordTreeMap[-1][1][-1][0] j = wordTreeMap[-1][1][-1][1] else: # go back to beginning of # tree search i = 0 j = 0 else: i = 0 # go back to beginning j = 0 break # matched elif continued: # possible lack of matching up of words in # previous utterance same caller and same # tree// not always within same tree!! errormessage = "Possible bad start for \ CONTINUED UTT ''" + words[0] + "'' in file/utt: "\ + str(utt.swda_filename) + "\n " + utt.caller + \ "." + str(utt.utterance_index) + "." + \ str(utt.subutterance_index) + \ "POSSIBLE COMMENT = " + str(possibleComment) # print errormessage if not errorLog is None: errorLog.write(errormessage + "\n") # raw_input() if backtrack == 1: backtrack += 1 elif backtrack == 2: # i.e. we've done two loops and # still haven't found it, try the other way count = origcount utt = trans.utterances[count] words = utt.text_words() word = words[0] trees = [lastTrees[-1]] + origtrees[1:] # print "\nSECOND PASS(2)replacing \ # first one to lasttreemap's:" # print words # print trees backtrack += 1 # mistranscribe = False #TODO perhaps needed wordTreeMap = [] # switch to forward track this is # the only time we want to try # from the previous mapped leaf in the # other tree foundTreemap = False for t in range(len(lastTreeMap) - 1, -1, -1): # backwards iteration through words # print lastTreeMap[t][1] if len(lastTreeMap[t][1]) > 0: # print "last treemapping of last \ # caller utterance = " + \ # str(lastTreeMap[t][1][-1]) j = lastTreeMap[t][1][-1][1] + 1 foundTreemap = True # print "found last mapping, j = " \ #+ str(j) # raw_input() # break when last tree # mapped word from this caller is found break if not foundTreemap: # print "NO matched last TREEMAP found\ # for previous Utt Same Speaker of " + \ # str(utt.swda_filename) + " " + \ # utt.caller + "." + \ # str(utt.utterance_index) + "." +\ # str(utt.subutterance_index) j = 0 # for tmap in wordTreeMapList.keys(): # print tmap # print wordTreeMapList[tmap] # raw_input() i = 0 # go back to first tree continue elif forwardtrack == 1: forwardtrack += 1 elif forwardtrack == 2: count = count - (count - lastIndexes[-1][0]) utt = previousUttSame words = utt.text_words() word = words[0] mytrees = [] for i in range(0, len(lastTrees) - 1): mytrees.append(lastTrees[i]) trees = mytrees + [origtrees[0]] # print "\nSECOND PASS(1)backtrack to \ # with new trees:" # print utt.transcript_index # print words # print trees forwardtrack += 1 # mistranscribe = False #TODO maybe needed wordTreeMap = [] # raw_input() elif forwardtrack == 3 or backtrack == 3: # if this hasn't worked reset to old trees # print "trying final reset" count = origcount utt = trans.utterances[count] words = utt.text_words() word = words[0] trees = origtrees forwardtrack = 0 backtrack = 0 # mistranscribe = False #TODO maybe needed wordTreeMap = [] # raw_input() else: pass # print "resetting search" # raw_input() # unless forward tracking now, # just go back to beginning i = 0 # go back to beginning of tree search j = 0 else: mistranscribe = False LeafIndices = [] wordTreeMap.append((word, LeafIndices)) errormessage = "WARNING: 440 no/partial tree \ mapping for ''" + words[0] + "'' in file/utt: "\ + str(utt.swda_filename) + " \n" + utt.caller\ + "." + str(utt.utterance_index) + "." + \ str(utt.subutterance_index) + \ "POSSIBLE COMMENT = " + str(possibleComment) # print utt.text_words() del words[0] # remove word # for trip in wordTreeMap: # print "t",trip if len(words) > 0: word = words[0] wordtest = re.sub(r"[\.\,\?\/\)\(\"\!]", "", word) wordtest = wordtest.replace("(", "") wordtest = wordtest.replace(")", "") # print errormessage if errorLog: errorLog.write("possible wrong tree mapping:" + errormessage + "\n") raw_input() # end of while loop (words) mytreenumbers = [] for treemap in trees: # the whole list but the tree mytreenumbers.append(treemap[:-1]) if not len(utt.text_words()) == len(wordTreeMap): print "ERROR. uneven lengths!" print utt.text_words() print wordTreeMap print trans.swda_filename print utt.transcript_index raw_input() count += 1 continue # add the treemap wordTreeMapList.append(trans.conversation_no, utt.transcript_index, tuple(mytreenumbers), tuple(wordTreeMap)) count += 1 # rewrite after each transcript filedict = defaultdict(str) for key in wordTreeMapList.keys(): csv_string = '"' + str(list(wordTreeMapList[key])) + '"' mytreenumbers = wordTreeMapList[key].transcript_numbers myptbnumbers = wordTreeMapList[key].treebank_numbers tree_list_string = '"' for i in range(0, len(mytreenumbers)): treemap = [myptbnumbers[i]] + mytreenumbers[i] tree_list_string += str(treemap) + ";" tree_list_string = tree_list_string[:-1] + '"' filename = '"' + key[0:key.rfind(':')] + '"' transindex = key[key.rfind(':') + 1:] filedict[int(transindex)] = filename \ + "\t" + transindex + '\t' + csv_string + "\t" \ + tree_list_string + "\n" for key in sorted(filedict.keys()): corpus_file.write(filedict[key]) wordTreeMapList = TreeMapCorpus(False, errorLog) # reset each time print "\n" + str(incorrectTrees) + " incorrect trees" corpus_file.close() if not errorLog is None: errorLog.close() class POSMapWriter: """Object which writes mappings from the words in utterances to the corresponding POS tags. """ def __init__(self, corpus_path="../swda", metadata_path="swda-metadata.csv", target_folder_path="Maps", ranges=None, errorLog=None): print "started MapWriting" self.write_to_file(corpus_path, metadata_path, target_folder_path, ranges, errorLog) def write_to_file(self, corpus_path, metadata_path, target_folder_path, ranges, errorLog): """Writes files to a target folder with the mappings from words in utterances to corresponding POS tags. """ if errorLog: errorLog = open(errorLog, 'w') corpus = CorpusReader(corpus_path, metadata_path) folder = None corpus_file = None for trans in corpus.iter_transcripts(): # print "iterating",trans.conversation_no if not trans.has_pos(): continue # print "has pos" if ranges and not trans.conversation_no in ranges: continue # print "in range" # just look at transcripts WITHOUT trees as compliment to the # above models if trans.has_trees(): continue end = trans.swda_filename.rfind("/") start = trans.swda_filename.rfind("/", 0, end) c_folder = trans.swda_filename[start + 1:end] if c_folder != folder: # for now splitting the maps by folder folder = c_folder if corpus_file: corpus_file.close() corpus_file = open(target_folder_path + "/POS_map_{0}.csv.text".format(folder), 'w') wordPOSMapList = POSMapCorpus(False, errorLog) print "new map for folder", folder translist = trans.utterances translength = len(translist) count = 0 # iterating through transcript utterance by utterance while count < translength: utt = trans.utterances[count] words = utt.text_words() wordPOSMap = [] if len(utt.pos) == 0: # no POS wordPOSMap.append((utt, [])) # just dummy value wordPOSMapList.append(trans.conversation_no, utt.transcript_index, list(wordPOSMap)) errormessage = "WARNING: NO POS for file/utt: " +\ str(utt.swda_filename) + " " + utt.caller + "." + \ str(utt.utterance_index) + "." + \ str(utt.subutterance_index) + " " + utt.text # print errormessage # raw_input() else: # indices for which POS we're at j = 0 possibleComment = False # can have comments, flag mistranscribe = False word = words[0] # loop until no more words left to be matched in utterance while len(words) > 0: word = words[0] # print "top WORD:" + word if not mistranscribe: wordtest = re.sub(r"[\.\,\?\/\)\(\"\!\\]", "", word) wordtest = wordtest.replace("(", "").\ replace(")", "").replace("/", "") match = False POSIndices = [] if (possibleComment or word[0:1] in ["{", "}", "-"] or word in ["/", ".", ",", "]"] or wordtest == "" or any([x in word for x in ["<", ">", "*", "[", "+", "]]", "...", "#", "="]])): # no tree equivalent for {D } type annotations if (word[0:1] == "-" or any([x in word for x in ["*", "<<", "<+", "[[", "<"]])) \ and not possibleComment: possibleComment = True if possibleComment: # print "match COMMENT!:" + word # raw_input() POSIndices = [] match = True if (any([x in word for x in [">>", "]]", "))", ">"]]) or word[0] == "-") \ and not word == "->": # turn off comment possibleComment = False if (">>" in word or "]]" in word or "))" in word or ">" in word and not word == "->"): # turn off comment possibleComment = False #del words[0] wordPOSMap.append((word, POSIndices)) POSIndices = [] match = True # print "match annotation!:" + word del words[0] # word is consumed if len(words) > 0: word = words[0] wordtest = re.sub(r"[\.\,\?\/\)$\"\!\\]", "", word) wordtest = wordtest.replace("(", "") wordtest = wordtest.replace(")", "") else: break continue # carry on to next word else: myPOS = utt.regularize_pos_lemmas() while j < len(myPOS): pos = myPOS[j][0] # pair of (word,POS) # print "j number of pos : " + str(len(myPOS)) # print "j loop word : " + word # print "j loop wordtest : " + wordtest # print "j pos : " + str(j) + " " + str(pos) # raw_input() breaker = False if wordtest == pos or word == pos: # exact match POSIndices.append(j) wordPOSMap.append((word, POSIndices)) # print "match!:" + word + " in file/utt: "\ # + str(utt.swda_filename) + \ # str(utt.transcript_index)) del words[0] # word is consumed if len(words) > 0: word = words[0] # next word wordtest = re.sub( r"[\.\,\?\/$$\"\!\\]", "", word) wordtest = wordtest.replace("(", "").\ replace(")", "").replace("/", "") POSIndices = [] j += 1 # increment lead number match = True breaker = True # raw_input() break elif (pos in wordtest or pos in word) \ and not pos in [",", "."]: # substring relation testpos = pos POSIndices.append(j) j += 1 if wordtest[-1] == "-" and \ pos == wordtest[0:-1]: wordPOSMap.append((word, POSIndices)) del words[0] # remove word # print "match!:" + word + " in \ # file/utt: " + str(utt.swda_filename) \ #+ str(utt.transcript_index) if len(words) > 0: word = words[0] wordtest = re.sub( r"[\.\,\?\/$$\"\!\\]", "", word) wordtest = wordtest.\ replace("(", "").\ replace(")", "").\ replace("/", "") POSIndices = [] match = True breaker = True break for k in range(j, j + 3): if (k >= len(myPOS)): breaker = True break if (testpos + myPOS[k][0]) in wordtest\ or (testpos + myPOS[k][0]) in word: testpos += myPOS[k][0] POSIndices.append(k) j += 1 # concatenation if testpos == wordtest or \ testpos == word: # matched wordPOSMap.append((word, POSIndices)) del words[0] # remove word # print "match!:" +\ # word + " in file/utt: " + \ # str(utt.swda_filename) +\ # str(utt.transcript_index)) if len(words) > 0: word = words[0] wordtest = re.sub( r"[\.\,\?\/$\(\"\!\\]", "", word) wordtest = wordtest.\ replace("(", "") wordtest = wordtest.\ replace(")", "") POSIndices = [] j = k + 1 match = True breaker = True break else: j += 1 # otherwise go on if breaker: break if match: break # could not match word! Could be mistransription if not match: # print "false checking other options" # print j # print word # print wordtest if not mistranscribe: mistranscribe = True for pair in possibleMistranscription: if pair[0] == wordtest: wordtest = pair[1] break # matched if wordtest[-1] == "-": # partial words wordtest = wordtest[0:-1] if "'" in wordtest: wordtest = wordtest.replace("'", "") if len(wordPOSMap) > 0: found = False for n in range( len(wordPOSMap) - 1, -1, -1): if len(wordPOSMap[n][1]) > 0: j = wordPOSMap[n][1][-1] + 1 # print j found = True break if not found: # if not possible go back to # the beginning! j = 0 else: j = 0 # print j else: mistranscribe = False wordPOSMap.append((word, POSIndices)) errormessage = "WARNING: no/partial POS \ mapping for ''" + words[0] + "'' in file/utt:"\ + str(utt.swda_filename) + "-" + \ str(utt.transcript_index) + \ "POSSIBLE COMMENT = " + \ str(possibleComment) del words[0] # remove word if len(words) > 0: word = words[0] wordtest = re.sub(r"[\.\,\?\/\)\(\"\!\\]", "", word) wordtest = wordtest.replace("(", "").\ replace(")", "").replace("/", "") # print errormessage if errorLog: errorLog.write("possible wrong POS : " + errormessage + "\n") # raw_input() # end of while loop (words) if not len(wordPOSMap) == len(utt.text_words()): print "Error " print "Length mismatch in file/utt: " + \ str(utt.swda_filename) + str(utt.transcript_index) print utt.text_words() print wordPOSMap raw_input() wordPOSMapList.append(trans.conversation_no, str(utt.transcript_index), list(wordPOSMap)) # print "\nadded POSmap " + str(trans.swda_filename) + \ #"." + str(utt.transcript_index) + "\n" csv_string = '"' + str(wordPOSMap) + '"' corpus_file.write('"' + str(utt.conversation_no) + '"\t' + str(utt.transcript_index) + '\t' + csv_string + "\n") count += 1 corpus_file.close() if errorLog: errorLog.close() if __name__ == '__main__': t = TreeMapWriter()

53.393013

86

0.329598

3,344

48,908

4.752093

0.111842

0.015103

0.026052

0.014725

0.574036

0.526273

0.496445

0.46454

0.415959

0.40073

0

0.011476

0.588431

48,908

915

87

53.451366

0.777982

0.154719

0

0.633491

0

0.025872

0.00106

0

0.001093

0

null

0.006319

0.009479

null

0.022117

0

null

0

1

0

null

0

1

0

2

a8c4ef65d4167eae76cb55b333d7586f25c61d43

169

py

Python

base/NeighborResult.py

Holly-Jiang/QCTSA

b90136b9df18fc21ae53b431f1e5e0c6ef786fae

[ "MIT" ]

null

base/NeighborResult.py

Holly-Jiang/QCTSA

b90136b9df18fc21ae53b431f1e5e0c6ef786fae

[ "MIT" ]

null

base/NeighborResult.py

Holly-Jiang/QCTSA

b90136b9df18fc21ae53b431f1e5e0c6ef786fae

[ "MIT" ]

null

class NeighborResult: def __init__(self): self.solutions = [] self.choose_path = [] self.current_num = 0 self.curr_solved_gates = []

24.142857

35

0.585799

18

169

5.055556

0.777778

0

0.008547

0.307692

169

6

36

28.166667

0.769231

0

1

0.166667

false

0

0.333333

0

1

0

null

0

1

0

null

0

2

a8c77d5a50c3e402e1747bc1dedba092e6e2fa50

4,131

py

Python

machine/EventCase.py

technosvitman/sm_gene

243d060fec7c642ce74843776a016ded13a68855

[ "MIT" ]

null

machine/EventCase.py

technosvitman/sm_gene

243d060fec7c642ce74843776a016ded13a68855

[ "MIT" ]

9

2021-08-11T07:25:53.000Z

2021-09-01T11:10:33.000Z

machine/EventCase.py

technosvitman/sm_gene

243d060fec7c642ce74843776a016ded13a68855

[ "MIT" ]

null

''' @brief this class reflect action decision regarding condition ''' class EventAction(): ''' @brief build event action @param cond the conditions to perform the action @param to the target state if any @param job the job to do if any ''' def __init__(self, cond="", to="", job=""): self.__to = to self.__job = job self.__cond = cond ''' @brief get action state target @return state name ''' def getState(self) : return self.__to ''' @brief has transition condition @return true if not empty ''' def hasCond(self) : return ( self.__cond != "" ) ''' @brief get action conditions @return condition ''' def getCond(self) : return self.__cond ''' @brief get action job @return job ''' def getJob(self) : return self.__job ''' @brief string represtation for state action @return the string ''' def __str__(self): return "Act( %s, %s, %s )"%(self.__to, self.__job, self.__cond) ''' @brief this class reflect the output switch on event received regarding condition and action to perform ''' class EventCase(): ''' @brief build event case @param event the event title ''' def __init__(self, event): self.__event = event self.__acts = [] ''' @brief get iterator ''' def __iter__(self): return iter(self.__acts) ''' @brief equality implementation @param other the other element to compare with ''' def __eq__(self, other): if isinstance(other, str): return self.__event == other if not isinstance(other, EventCase): return False if self.__event != other.getEvent(): return False return True ''' @brief get action event @return event ''' def getEvent(self) : return self.__event ''' @brief add action @param act the new action ''' def addAct(self, act) : if act not in self.__acts: self.__acts.append(act) ''' @brief string represtation for state action @return the string ''' def __str__(self): output = "Event( %s ) { "%self.__event if len(self.__acts): output += "\n" for act in self.__acts: output += "%s\n"%str(act) return output + "}" ''' @brief this class store all event case for a state ''' class EventCaseList(): ''' @brief build event case list ''' def __init__(self): self.__events = [] ''' @brief get iterator ''' def __iter__(self): return iter(self.__events) ''' @brief append from StateAction @param act the state action ''' def append(self, act): for cond in act.getConds(): evt = None a = EventAction(cond=cond.getCond(),\ to=act.getState(),\ job=act.getJob()) for e in self.__events: if e == cond.getEvent(): evt = e break if not evt: evt = EventCase(cond.getEvent()) self.__events.append(evt) evt.addAct(a) ''' @brief append from State @param state the state ''' def appendState(self, state): for act in state.getActions(): self.append(act) ''' @brief string represtation for state action @return the string ''' def __str__(self): output = "{ " if len(self.__events): output += "\n" for e in self.__events: output += "%s\n"%str(e) return output + "}"

25.189024

107

0.487775

422

4,131

4.561611

0.206161

0.041558

0.036364

0.028052

0.204675

0.188052

0.154805

0.112208

0

0.41007

4,131

164

108

25.189024

0.789906

0.068748

0

0.185714

0

0.018643

0

1

0.242857

false

0

0.114286

0.485714

0

null

0

null

0

1

0

1

0

2

764382ce910f9b78f0afeeafad12a7ae05b25d0c

2,879

py

Python

lib/ezdxf/sections/abstract.py

tapnair/DXFer

8ec957d80c2f251bb78440147d1478106f99b3eb

[ "MIT" ]

4

2019-03-31T00:41:13.000Z

2021-07-31T05:09:07.000Z

lib/ezdxf/sections/abstract.py

tapnair/DXFer

8ec957d80c2f251bb78440147d1478106f99b3eb

[ "MIT" ]

null

lib/ezdxf/sections/abstract.py

tapnair/DXFer

8ec957d80c2f251bb78440147d1478106f99b3eb

[ "MIT" ]

5

2018-03-29T06:28:07.000Z

2021-07-31T05:09:08.000Z

# Purpose: entity section # Created: 13.03.2011 # Copyright (C) 2011, Manfred Moitzi # License: MIT License from __future__ import unicode_literals __author__ = "mozman <mozman@gmx.at>" from itertools import islice from ..lldxf.tags import TagGroups, DXFStructureError from ..lldxf.classifiedtags import ClassifiedTags, get_tags_linker from ..query import EntityQuery class AbstractSection(object): name = 'abstract' def __init__(self, entity_space, tags, drawing): self._entity_space = entity_space self.drawing = drawing if tags is not None: self._build(tags) @property def dxffactory(self): return self.drawing.dxffactory @property def entitydb(self): return self.drawing.entitydb def get_entity_space(self): return self._entity_space def _build(self, tags): if tags[0] != (0, 'SECTION') or tags[1] != (2, self.name.upper()) or tags[-1] != (0, 'ENDSEC'): raise DXFStructureError("Critical structure error in {} section.".format(self.name.upper())) if len(tags) == 3: # empty entities section return linked_tags = get_tags_linker() store_tags = self._entity_space.store_tags entitydb = self.entitydb fix_tags = self.dxffactory.modify_tags for group in TagGroups(islice(tags, 2, len(tags)-1)): tags = ClassifiedTags(group) fix_tags(tags) # post read tags fixer for VERTEX! handle = entitydb.add_tags(tags) if not linked_tags(tags, handle): # also creates the link structure as side effect store_tags(tags) # add to entity space def write(self, stream): stream.write(" 0\nSECTION\n 2\n%s\n" % self.name.upper()) self._entity_space.write(stream) stream.write(" 0\nENDSEC\n") def create_new_dxf_entity(self, _type, dxfattribs): """ Create new DXF entity add it to th entity database and add it to the entity space. """ dxf_entity = self.dxffactory.create_db_entry(_type, dxfattribs) self._entity_space.add_handle(dxf_entity.dxf.handle) return dxf_entity def add_handle(self, handle): self._entity_space.add_handle(handle) def remove_handle(self, handle): self._entity_space.remove(handle) def delete_entity(self, entity): self.remove_handle(entity.dxf.handle) self.entitydb.delete_entity(entity) # start of public interface def __len__(self): return len(self._entity_space) def __contains__(self, handle): return handle in self._entity_space def query(self, query='*'): return EntityQuery(iter(self), query) def delete_all_entities(self): """ Delete all entities. """ self._entity_space.delete_all_entities() # end of public interface

31.293478

104

0.658909

367

2,879

4.948229

0.313352

0.090859

0.029736

0.052313

0.034141

0

0.011009

0.242793

2,879

91

105

31.637363

0.822018

0.134422

0

0.033898

0

0.048178

0

1

0.237288

false

0

0.084746

0.101695

0.491525

0

null

0

null

0

1

0

1

0

2

764937dbe3389486664886c5dde62290994457f4

551

py

Python

lessweb/__init__.py

qorzj/lessweb

d21473d724216c3afa1101729137573ff21b7015

[ "MIT" ]

17

2017-11-02T02:07:35.000Z

2020-07-23T06:33:36.000Z

lessweb/__init__.py

qorzj/lessweb

d21473d724216c3afa1101729137573ff21b7015

[ "MIT" ]

12

2018-02-06T05:52:04.000Z

2021-02-07T14:43:35.000Z

lessweb/__init__.py

qorzj/lessweb

d21473d724216c3afa1101729137573ff21b7015

[ "MIT" ]

2

2018-06-06T09:30:44.000Z

2018-09-19T02:03:16.000Z

"""lessweb: 用最python3的方法创建web apps""" __version__ = '0.3.3' __author__ = [ 'qorzj <inull@qq.com>', ] __license__ = "MIT" # from . import application, context, model, storage, webapi from .application import interceptor, Application from .context import Context, Request, Response from .storage import Storage from .bridge import uint, ParamStr, MultipartFile, Jsonizable from .webapi import BadParamError, NotFoundError, Cookie, HttpStatus, ResponseStatus from .utils import _nil, eafp from .client import Client from .service import Service

26.238095

84

0.771325

64

551

6.4375

0.59375

0

0.008421

0.137931

551

20

85

27.55

0.858947

0.165154

0

0.061674

0

1

0

false

0

0.615385

0

0.615385

0

null

0

null

0

1

0

1

0

2

765bdbd234fb42e7aa71522393ad38a642d864a9

13,184

py

Python

web/adoption_stories/adopteeStories/models.py

CuriousG102/Chinese-Adoption

8aa487b859ee330bd524381e8688aae68c225437

[ "MIT" ]

null

web/adoption_stories/adopteeStories/models.py

CuriousG102/Chinese-Adoption

8aa487b859ee330bd524381e8688aae68c225437

[ "MIT" ]

null

web/adoption_stories/adopteeStories/models.py

CuriousG102/Chinese-Adoption

8aa487b859ee330bd524381e8688aae68c225437

[ "MIT" ]

null

from django.db import models from django.utils.encoding import force_text from django.utils.translation import ugettext_lazy as _ from embed_video.fields import EmbedYoutubeField, EmbedSoundcloudField from .custom_model_fields import RestrictedImageField from .default_settings import ADOPTEE_STORIES_CONFIG as config class NamesToStringMixin(): NAME_ATTRIBUTES = ['english_name', 'pinyin_name', 'chinese_name'] @property def name(self): s = [] for name in self.NAME_ATTRIBUTES: name_string = getattr(self, name, None) if name_string: s.append(name_string) return ' '.join(s) class Adoptee(models.Model, NamesToStringMixin): # english_name must have a value || (pinyin_name && chinese_name) # must have a value implemented form level english_name = models.CharField(max_length=150, null=True, blank=True, # Translators: Name of a field in the admin page db_index=True, verbose_name=_('English Name')) pinyin_name = models.CharField(max_length=150, null=True, blank=True, # Translators: Name of a field in the admin page db_index=True, verbose_name=_('Pinyin Name')) chinese_name = models.CharField(max_length=50, null=True, blank=True, # Translators: Name of a field in the admin page db_index=True, verbose_name=_('Chinese Name')) photo_front_story = RestrictedImageField(maximum_size=config['PHOTO_FRONT_STORY_MAX_SIZE'], required_width=config['PHOTO_FRONT_STORY_WIDTH'], required_height=config['PHOTO_FRONT_STORY_HEIGHT'], required_formats=config['FORMATS'], null=True, blank=True, # Translators: Name of a field in the admin page verbose_name=_('Photo Front Story')) # Translators: Name of a field in the admin page front_story = models.ForeignKey('StoryTeller', null=True, verbose_name=_('Front Story'), blank=True, limit_choices_to={'approved': True}) # Translators: Name of a field in the admin page created = models.DateTimeField(auto_now_add=True, verbose_name=_('Created At')) # Translators: Name of a field in the admin page updated = models.DateTimeField(auto_now=True, verbose_name=_('Updated At')) class Meta: ordering = ['-created'] # Translators: Name of a field in the admin page verbose_name = _('Adoptee') # Translators: Name of a field in the admin page verbose_name_plural = _('Adoptees') def __str__(self): string = ' '.join([force_text(self._meta.verbose_name), self.name]) return string class MultimediaItem(models.Model): # english_caption || chinese_caption must have a value implemented # form level english_caption = models.CharField(max_length=200, null=True, blank=True, # Translators: Name of a field in the admin page verbose_name=_('English Caption')) chinese_caption = models.CharField(max_length=200, null=True, blank=True, # Translators: Name of a field in the admin page verbose_name=_('Chinese Caption')) # Translators: Name of a field in the admin page approved = models.BooleanField(default=False, verbose_name=_('Approved')) # Translators: Name of a field in the admin page story_teller = models.ForeignKey('StoryTeller', null=True, verbose_name=_('Story Teller')) # Translators: Name of a field in the admin pages created = models.DateTimeField(auto_now_add=True, verbose_name=_('Created At')) # Translators: Name of a field in the admin page updated = models.DateTimeField(auto_now=True, verbose_name=_('Updated At')) class Meta: verbose_name = _('Multimedia Item') abstract = True ordering = ['-created'] def __str__(self): return ' '.join([force_text(self._meta.verbose_name), self.story_teller.name, force_text(self.created)]) class Audio(MultimediaItem): # Translators: name of field in the admin page audio = EmbedSoundcloudField(verbose_name=_('Audio Soundcloud Embed')) class Meta(MultimediaItem.Meta): abstract = False # Translators: Name of a field in the admin page verbose_name = _('Audio item') # Translators: Name of a field in the admin page verbose_name_plural = _('Audio items') class Video(MultimediaItem): # Translators: name of field in the admin page video = EmbedYoutubeField(verbose_name=_('Video Youtube Embed')) class Meta(MultimediaItem.Meta): abstract = False # Translators: Name of a field in the admin page verbose_name = _('Video item') # Translators: Name of a field in the admin page verbose_name_plural = _('Video items') class Photo(MultimediaItem): # file size and type checking added on form level # Translators: Name of a field in the admin page photo_file = models.ImageField(verbose_name=_('Photo File')) class Meta(MultimediaItem.Meta): abstract = False # Translators: Name of a field in the admin page verbose_name = _('Photo') # Translators: Name of a field in the admin page verbose_name_plural = _('Photos') class RelationshipCategory(models.Model, NamesToStringMixin): # english_name must have a value || chinese name must have a value at first # but to publish both must have a value or all stories with an untranslated # category must only show up english side/chinese side # Translators: Name of a field in the admin page english_name = models.CharField(max_length=30, null=True, verbose_name=_('English Name'), blank=True) # Translators: Name of a field in the admin page chinese_name = models.CharField(max_length=30, null=True, verbose_name=_('Chinese Name'), blank=True) # Translators: Name of a field in the admin page approved = models.BooleanField(default=False, verbose_name=_('Approved')) # Translators: Name of a field in the admin page created = models.DateTimeField(auto_now_add=True, verbose_name=_('Created At')) # Translators: Name of a field in the admin page updated = models.DateTimeField(auto_now=True, verbose_name=_('Updated At')) # Translators: Label for the number determining the order of the relationship category for admins order = models.IntegerField(null=True, blank=True, verbose_name=_('Position of relationship category')) class Meta: ordering = ['order'] # Translators: Name of a field in the admin page verbose_name = _('Relationship Category') # Translators: Name of a field in the admin page verbose_name_plural = _('Relationship Categories') def __str__(self): string = ' '.join([force_text(self._meta.verbose_name), self.name]) return string class StoryTeller(models.Model, NamesToStringMixin): relationship_to_story = models.ForeignKey('RelationshipCategory', # Translators: Name of a field in the admin page verbose_name=_('Relationship to Story')) # One version of story text because I don't want adoptee's stories to be different between who is viewing it # Translators: Name of a field in the admin page story_text = models.TextField(verbose_name=_('Story Text')) # Translators: Name of a field in the admin page email = models.EmailField(verbose_name=_('Email')) # Translators: Name of a field in the admin page approved = models.BooleanField(default=False, verbose_name=_('Approved')) related_adoptee = models.ForeignKey('Adoptee', related_name='stories', # Translators: Name of a field in the admin page verbose_name=_('Related Adoptee')) # english_name must have a value || (pinyin_name && chinese_name) # must have a value implemented form level english_name = models.CharField(max_length=150, null=True, # Translators: Name of a field in the admin page verbose_name=_('English Name'), blank=True) chinese_name = models.CharField(max_length=50, null=True, # Translators: Name of a field in the admin page verbose_name=_('Chinese Name'), blank=True) pinyin_name = models.CharField(max_length=150, null=True, # Translators: Name of a field in the admin page verbose_name=_('Pinyin Name'), blank=True) created = models.DateTimeField(auto_now_add=True, # Translators: Name of a field in the admin page verbose_name=_('Created At')) updated = models.DateTimeField(auto_now=True, # Translators: Name of a field in the admin page verbose_name=_('Updated At')) class Meta: ordering = ['-updated', '-created'] # Translators: Name of a field in the admin page verbose_name = _('Story Teller') # Translators: Name of a field in the admin page verbose_name_plural = _('Story Tellers') def __str__(self): string = ' '.join([force_text(self._meta.verbose_name), self.name]) return string class AboutPerson(models.Model, NamesToStringMixin): photo = RestrictedImageField(maximum_size=config['PHOTO_FRONT_STORY_MAX_SIZE'], required_height=config['ABOUT_PHOTO_HEIGHT'], required_width=config['ABOUT_PHOTO_WIDTH'], required_formats=config['FORMATS'], verbose_name=_('Picture of person on about page')) english_caption = models.CharField(max_length=200, null=True, blank=True, # Translators: Name of a field in the admin page verbose_name=_('English Caption')) chinese_caption = models.CharField(max_length=200, null=True, blank=True, # Translators: Name of a field in the admin page verbose_name=_('Chinese Caption')) about_text_english = models.TextField(verbose_name=_('About text for that person in English.'), help_text=_('Should include paragraph markup:' 'e.g. This is a paragraph' 'This is a different paragraph'), null=True, blank=True) about_text_chinese = models.TextField(verbose_name=_('About text for that person in Chinese.'), help_text=_('Should include paragraph markup:' 'e.g. This is a paragraph' 'This is a different paragraph'), null=True, blank=True) published = models.BooleanField(verbose_name=_('Published status')) english_name = models.CharField(max_length=150, null=True, # Translators: Name of a field in the admin page verbose_name=_('English Name'), blank=True) chinese_name = models.CharField(max_length=50, null=True, # Translators: Name of a field in the admin page verbose_name=_('Chinese Name'), blank=True) pinyin_name = models.CharField(max_length=150, null=True, # Translators: Name of a field in the admin page verbose_name=_('Pinyin Name'), blank=True) order = models.IntegerField(verbose_name=_('Position of person in about page')) class Meta: ordering = ['order'] verbose_name = _('About Person') verbose_name_plural = _('About People') def __str__(self): string = ' '.join([force_text(self._meta.verbose_name), self.name]) return string

51.701961

112

0.586999

1,463

13,184

5.101846

0.122351

0.091372

0.109325

0.096463

0.708467

0.700831

0.689309

0.669078

0.6597

0.609593

0

0.004548

0.332828

13,184

254

113

51.905512

0.84402

0.22679

0

0.515924

0

0.127504

0.00977

0

1

0.038217

false

0

0.038217

0.006369

0.496815

0

null

0

1

0

1

0

null

0

2

765c85c98a88ed131ecd9f838f2186d4fb82671f

169

py

Python

core/utils/gpu_check.py

andregri/keras-segmentation

699043adc4dd74b97cbed3d3e5b8d8aafb03b71c

[ "Apache-2.0" ]

null

core/utils/gpu_check.py

andregri/keras-segmentation

699043adc4dd74b97cbed3d3e5b8d8aafb03b71c

[ "Apache-2.0" ]

null

core/utils/gpu_check.py

andregri/keras-segmentation

699043adc4dd74b97cbed3d3e5b8d8aafb03b71c

[ "Apache-2.0" ]

null

import tensorflow as tf def check_gpu(): n_gpus = len(tf.config.experimental.list_physical_devices('GPU')) print("Num GPUs Available: ", n_gpus) check_gpu()

16.9

69

0.715976

25

169

4.6

0.72

0.13913

0

0.159763

169

9

70

18.777778

0.809859

0

0.136095

0

1

0.2

false

0

0.2

0

0.4

0.2

1

0

null

0

1

0

null

0

2

766aab70e53fbf30d766b2eb2c674ed0d93615eb

604

py

Python

cavoke_server/tasks.py

cavoke-project/cavoke_server

5d2e39ca760e140ab9a8b0c50b45a6d4b22e21b5

[ "MIT" ]

null

cavoke_server/tasks.py

cavoke-project/cavoke_server

5d2e39ca760e140ab9a8b0c50b45a6d4b22e21b5

[ "MIT" ]

1

2020-01-06T17:47:03.000Z

cavoke_server/tasks.py

cavoke-project/cavoke-server

5d2e39ca760e140ab9a8b0c50b45a6d4b22e21b5

[ "MIT" ]

null

# from celery.schedules import crontab # from celery.task import periodic_task # from django.utils import timezone # from cavoke_app.models import GameSession # # # @periodic_task(run_every=crontab(minute='*/1')) # def delete_old_foos(): # # Query all the foos in our database # gss = GameSession.objects.all() # # # Iterate through them # for gs in gss: # # # If the expiration date is bigger than now delete it # if gs.expiresOn < timezone.now(): # gs.delete() # # log deletion # return "completed deleting foos at {}".format(timezone.now())

30.2

67

0.655629

78

604

5

0.653846

0.051282

0

0.002165

0.235099

604

19

68

31.789474

0.841991

0.928808

0

null

0

null

0

null

0

null

1

null

true

0

null

0

null

0

1

0

null

0

1

0

2

767abb3e3d12d3c5ac07f73a70a0a54a78206ee1

302

py

Python

packages/models-library/src/models_library/__init__.py

elisabettai/osparc-simcore

ad7b6e05111b50fe95e49306a992170490a7247f

[ "MIT" ]

null

packages/models-library/src/models_library/__init__.py

elisabettai/osparc-simcore

ad7b6e05111b50fe95e49306a992170490a7247f

[ "MIT" ]

55

2018-05-15T09:47:00.000Z

2022-03-31T06:56:50.000Z

packages/models-library/src/models_library/__init__.py

mrnicegyu11/osparc-simcore

b6fa6c245dbfbc18cc74a387111a52de9b05d1f4

[ "MIT" ]

1

2020-04-22T15:06:58.000Z

""" osparc's service models library """ # # NOTE: # - "examples" = [ ...] keyword and NOT "example". See https://json-schema.org/understanding-json-schema/reference/generic.html#annotations # import pkg_resources __version__: str = pkg_resources.get_distribution("simcore-models-library").version

25.166667

141

0.738411

36

302

6

0.805556

0.12037

0

0.109272

302

11

142

27.454545

0.802974

0.586093

0

0.196429

0

1

0

true

0

0.5

0

0.5

0

null

0

null

0

1

0

1

0

2

76803418e7c483c10d751d87b7054156573f1939

586

py

Python

src/waldur_ansible/python_management/migrations/0004_removed_virtual_env_field_from_global_requests.py

opennode/waldur-ansible

c81c5f0491be02fa9a55a6d5bf9d845750fd1ba9

[ "MIT" ]

1

2017-09-05T08:09:47.000Z

src/waldur_ansible/python_management/migrations/0004_removed_virtual_env_field_from_global_requests.py

opennode/waldur-ansible

c81c5f0491be02fa9a55a6d5bf9d845750fd1ba9

[ "MIT" ]

null

src/waldur_ansible/python_management/migrations/0004_removed_virtual_env_field_from_global_requests.py

opennode/waldur-ansible

c81c5f0491be02fa9a55a6d5bf9d845750fd1ba9

[ "MIT" ]

3

2017-09-24T03:13:19.000Z

2018-08-12T07:44:38.000Z

# -*- coding: utf-8 -*- # Generated by Django 1.11.9 on 2018-03-27 14:01 from __future__ import unicode_literals from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('python_management', '0003_added_unique_constraint'), ] operations = [ migrations.RemoveField( model_name='pythonmanagementdeleterequest', name='virtual_env_name', ), migrations.RemoveField( model_name='pythonmanagementfindvirtualenvsrequest', name='virtual_env_name', ), ]

24.416667

64

0.645051

55

586

6.6

0.709091

0.115702

0.143251

0.165289

0

0.048165

0.255973

586

23

65

25.478261

0.784404

0.116041

0

0.375

1

0

0.279612

0.184466

0

1

0

false

0

0.125

0

0.3125

0

null

0

1

0

1

0

null

0

2

76adf99c53be9fdd9abcf7404d34ffbbdbf4e9ae

1,422

py

Python

api-reference-examples/python/pytx/pytx/threat_descriptor.py

b-bold/ThreatExchange

6f8d0dc803faccf576c9398569bb52d54a4f9a87

[ "BSD-3-Clause" ]

997

2015-03-13T18:04:03.000Z

2022-03-30T12:09:10.000Z

api-reference-examples/python/pytx/pytx/threat_descriptor.py

b-bold/ThreatExchange

6f8d0dc803faccf576c9398569bb52d54a4f9a87

[ "BSD-3-Clause" ]

444

2015-03-26T17:28:49.000Z

2022-03-28T19:34:05.000Z

api-reference-examples/python/pytx/pytx/threat_descriptor.py

b-bold/ThreatExchange

6f8d0dc803faccf576c9398569bb52d54a4f9a87

[ "BSD-3-Clause" ]

294

2015-03-13T22:19:43.000Z

2022-03-30T08:42:45.000Z

# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved from .common import Common from .vocabulary import ThreatDescriptor as td from .vocabulary import ThreatExchange as t class ThreatDescriptor(Common): _URL = t.URL + t.VERSION + t.THREAT_DESCRIPTORS _DETAILS = t.URL + t.VERSION _RELATED = t.URL + t.VERSION _fields = [ td.ADDED_ON, td.CONFIDENCE, td.DESCRIPTION, td.EXPIRED_ON, td.FIRST_ACTIVE, td.ID, td.INDICATOR, td.LAST_ACTIVE, td.LAST_UPDATED, td.METADATA, td.MY_REACTIONS, td.OWNER, td.PRECISION, td.PRIVACY_MEMBERS, td.PRIVACY_TYPE, td.RAW_INDICATOR, td.REVIEW_STATUS, td.SEVERITY, td.SHARE_LEVEL, td.SOURCE_URI, td.STATUS, td.TAGS, td.TYPE, ] _default_fields = [ td.ADDED_ON, td.CONFIDENCE, td.DESCRIPTION, td.EXPIRED_ON, td.FIRST_ACTIVE, td.ID, td.INDICATOR, td.LAST_ACTIVE, td.LAST_UPDATED, td.METADATA, td.MY_REACTIONS, td.OWNER, td.PRECISION, td.RAW_INDICATOR, td.REVIEW_STATUS, td.SEVERITY, td.SHARE_LEVEL, td.SOURCE_URI, td.STATUS, td.TAGS, td.TYPE, ] _connections = [ ] _unique = [ ]

20.911765

70

0.553446

162

1,422

4.666667

0.358025

0.021164

0.019841

0.047619

0.600529

0

0.357947

1,422

67

71

21.223881

0.828039

0.04782

0

0.711864

0

1

0

false

0

0.050847

0

0.186441

0

null

0

1

0

1

0

null

0

2

76bbc2598c25fd191128e41eb9c547440be4a5b9

86

py

Python

src/integ_test_resources/common/platforms.py

kaichengyan/amplify-ci-support

5a56acd7fa8fb37ec7db975e080be6ba838dcec7

[ "Apache-2.0" ]

9

2020-06-09T21:59:02.000Z

2021-06-27T07:15:18.000Z

src/integ_test_resources/common/platforms.py

kaichengyan/amplify-ci-support

5a56acd7fa8fb37ec7db975e080be6ba838dcec7

[ "Apache-2.0" ]

27

2020-05-06T13:48:06.000Z

2022-02-14T10:10:33.000Z

src/integ_test_resources/common/platforms.py

kaichengyan/amplify-ci-support

5a56acd7fa8fb37ec7db975e080be6ba838dcec7

[ "Apache-2.0" ]

12

2020-05-15T11:51:41.000Z

2022-02-11T18:07:15.000Z

from enum import Enum class Platform(Enum): IOS = "ios" ANDROID = "android"

12.285714

23

0.639535

11

86

5

0.636364

0

0.255814

86

6

24

14.333333

0.859375

0

0.116279

0

1

0

false

0

0.25

0

1

0

1

0

null

0

1

0

null

0

2

4f1d60a2d4237bbd3efae93314b622ddcfa12232

408

py

Python

examples/ivis_job/docker_build.py

smartarch/qoscloud

13b11b0baaad0d9b234d7defccdbd8756c2618a1

[ "MIT" ]

2

2021-02-20T13:53:02.000Z

2021-11-15T16:11:32.000Z

examples/ivis_job/docker_build.py

smartarch/qoscloud

13b11b0baaad0d9b234d7defccdbd8756c2618a1

[ "MIT" ]

null

examples/ivis_job/docker_build.py

smartarch/qoscloud

13b11b0baaad0d9b234d7defccdbd8756c2618a1

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ This script builds the docker images of image client and recognizer server and pushes them to dockerhub. """ from subprocess import call print("Building the default docker image") call("docker build -t d3srepo/qoscloud-default -f Dockerfile ../..", shell=True) print("Pushing images to DockerHub") call("docker push d3srepo/qoscloud-default", shell=True)

31.384615

104

0.742647

58

408

5.224138

0.689655

0.072607

0.145215

0

0.011268

0.129902

408

12

105

34

0.842254

0.362745

0

0.621514

0.191235

0

1

0

true

0

0.2

0

0.2

0.4

0

null

0

1

0

null

0

1

0

2

4f24e90f804e495cead994aea15903dbefcdaca4

141

py

Python

Semana 07/frequencia.py

heltonricardo/grupo-estudos-maratonas-programacao

0c07d84a900858616647d07574ec56b0533cddfb

[ "MIT" ]

null

Semana 07/frequencia.py

heltonricardo/grupo-estudos-maratonas-programacao

0c07d84a900858616647d07574ec56b0533cddfb

[ "MIT" ]

null

Semana 07/frequencia.py

heltonricardo/grupo-estudos-maratonas-programacao

0c07d84a900858616647d07574ec56b0533cddfb

[ "MIT" ]

null

n = int(input()) v = [] for i in range(n): v.append(int(input())) s = sorted(set(v)) for i in s: print(f'{i} aparece {v.count(i)} vez (es)')

23.5

55

0.574468

30

141

2.7

0.6

0.197531

0.123457

0.17284

0

0.163121

141

5

56

28.2

0.686441

0

0.234043

0

1

0

false

0

0.2

0

null

0

1

0

1

0

null

0

2

4f42f0318bdc9f9e318bf4c6ab8ff73477869c44

1,337

py

Python

tests/core/test_base_component.py

strickvl/zenml

f1499e9c3fee00fd1d66de14cab66c4472c0085d

[ "Apache-2.0" ]

1,275

2020-11-19T14:18:25.000Z

2021-08-13T07:31:39.000Z

tests/core/test_base_component.py

strickvl/zenml

f1499e9c3fee00fd1d66de14cab66c4472c0085d

[ "Apache-2.0" ]

62

2020-11-30T16:06:14.000Z

2021-08-10T08:34:52.000Z

tests/core/test_base_component.py

strickvl/zenml

f1499e9c3fee00fd1d66de14cab66c4472c0085d

[ "Apache-2.0" ]

75

2020-12-22T19:15:08.000Z

2021-08-13T03:07:50.000Z

# Copyright (c) ZenML GmbH 2021. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at: # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express # or implied. See the License for the specific language governing # permissions and limitations under the License. from typing import Text from zenml.core.base_component import BaseComponent class MockComponent(BaseComponent): """Mocking the base component for testing.""" tmp_path: str def get_serialization_dir(self) -> Text: """Mock serialization dir""" return self.tmp_path def test_base_component_serialization_logic(tmp_path): """Tests the UUID serialization logic of BaseComponent""" # Application of the monkeypatch to replace Path.home # with the behavior of mockreturn defined above. # mc = MockComponent(tmp_path=str(tmp_path)) # Calling getssh() will use mockreturn in place of Path.home # for this test with the monkeypatch. # print(mc.get_serialization_dir())

33.425

70

0.735228

188

1,337

5.154255

0.569149

0.06192

0.026832

0.033024

0

0.007394

0.190726

1,337

39

71

34.282051

0.88817

0.727001

0

1

0.285714

false

0

0.285714

0

1

0

null

0

null

0

1

0

1

0

2

4f43d6d7f8cc17aa055442affd0c29f290e5addd

591

py

Python

courses/migrations/0009_alter_skills_program_duration_and_more.py

sisekelohub/sisekelo

7e1b0de6abf07e65ed746d0d929c3de37fb421c3

[ "MIT" ]

1

2022-02-20T16:03:04.000Z

courses/migrations/0009_alter_skills_program_duration_and_more.py

sisekelohub/sisekelo

7e1b0de6abf07e65ed746d0d929c3de37fb421c3

[ "MIT" ]

null

courses/migrations/0009_alter_skills_program_duration_and_more.py

sisekelohub/sisekelo

7e1b0de6abf07e65ed746d0d929c3de37fb421c3

[ "MIT" ]

null

# Generated by Django 4.0 on 2022-01-02 21:51 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('courses', '0008_alter_learnership_duration'), ] operations = [ migrations.AlterField( model_name='skills_program', name='duration', field=models.CharField(max_length=50, null=True), ), migrations.AlterField( model_name='specialized_course', name='duration', field=models.CharField(max_length=50, null=True), ), ]

24.625

61

0.602369

60

591

5.783333

0.65

0.115274

0.144092

0.167147

0.293948

0

0.052257

0.287648

591

23

62

25.695652

0.771972

0.072758

0

0.470588

1

0

0.157509

0.056777

0

1

0

false

0

0.058824

0

0.235294

0

null

0

1

0

1

0

null

0

2

4f54da94c5e8d003456c1c27b57ad6a8d761118e

355

py

Python

ocdskingfisher/sources/digiwhist_germany.py

odscjames/lhs-alpha

d882cadfcf3464fd29529cb862567dc311d892e2

[ "BSD-3-Clause" ]

null

ocdskingfisher/sources/digiwhist_germany.py

odscjames/lhs-alpha

d882cadfcf3464fd29529cb862567dc311d892e2

[ "BSD-3-Clause" ]

null

ocdskingfisher/sources/digiwhist_germany.py

odscjames/lhs-alpha

d882cadfcf3464fd29529cb862567dc311d892e2

[ "BSD-3-Clause" ]

null

from ocdskingfisher.sources.digiwhist_base import DigiwhistBaseSource class DigiwhistGermanyRepublicSource(DigiwhistBaseSource): publisher_name = 'Digiwhist Germany' url = 'https://opentender.eu/download' source_id = 'digiwhist_germany' def get_data_url(self): return 'https://opentender.eu/data/files/DE_ocds_data.json.tar.gz'

32.272727

74

0.771831

40

355

6.65

0.75

0.120301

0.12782

0

0.132394

355

10

75

35.5

0.863636

0

0.340845

0

1

0.142857

false

0

0.142857

1

0

null

0

null

0

1

0

2

4f5645014936668c159ef7897d13239bafc29c34

209

py

Python

reagent/core/fb_checker.py

alexnikulkov/ReAgent

e404c5772ea4118105c2eb136ca96ad5ca8e01db

[ "BSD-3-Clause" ]

1

2021-05-03T15:18:58.000Z

reagent/core/fb_checker.py

alexnikulkov/ReAgent

e404c5772ea4118105c2eb136ca96ad5ca8e01db

[ "BSD-3-Clause" ]

null

reagent/core/fb_checker.py

alexnikulkov/ReAgent

e404c5772ea4118105c2eb136ca96ad5ca8e01db

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python3 import importlib.util def is_fb_environment(): if importlib.util.find_spec("fblearner") is not None: return True return False IS_FB_ENVIRONMENT = is_fb_environment()

17.416667

57

0.727273

30

209

4.833333

0.666667

0.082759

0.310345

0

0.005848

0.181818

209

11

58

19

0.842105

0.100478

0

0.048128

0

1

0.166667

false

0

0.333333

0

0.833333

0

null

0

1

0

null

0

1

0

2

4f7749d7fdeb213a71c50fac2777773a4cae4cde

982

py

Python

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/_sweep/search_space/randint.py

dubiety/azure-sdk-for-python

62ffa839f5d753594cf0fe63668f454a9d87a346

[ "MIT" ]

1

2022-02-01T18:50:12.000Z

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/_sweep/search_space/randint.py

ellhe-blaster/azure-sdk-for-python

82193ba5e81cc5e5e5a5239bba58abe62e86f469

[ "MIT" ]

null

sdk/ml/azure-ai-ml/azure/ai/ml/_schema/_sweep/search_space/randint.py

ellhe-blaster/azure-sdk-for-python

82193ba5e81cc5e5e5a5239bba58abe62e86f469

[ "MIT" ]

null

# --------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # --------------------------------------------------------- from azure.ai.ml.constants import SearchSpace from marshmallow import fields, post_load, pre_dump, ValidationError from azure.ai.ml._schema.core.fields import StringTransformedEnum from azure.ai.ml._schema.core.schema import PatchedSchemaMeta class RandintSchema(metaclass=PatchedSchemaMeta): type = StringTransformedEnum(required=True, allowed_values=SearchSpace.RANDINT) upper = fields.Integer(required=True) @post_load def make(self, data, **kwargs): from azure.ai.ml.sweep import Randint return Randint(**data) @pre_dump def predump(self, data, **kwargs): from azure.ai.ml.sweep import Randint if not isinstance(data, Randint): raise ValidationError("Cannot dump non-Randint object into RandintSchema") return data

35.071429

86

0.649695

105

982

6.009524

0.495238

0.071315

0.087163

0.103011

0.215531

0.142631

0

0.158859

982

27

87

36.37037

0.763923

0.176171

0

0.117647

0

0.06087

0

1

0.117647

false

0

0.352941

0

0.764706

0

null

0

null

0

1

0

1

0

2