ytzi/the-stack-dedup-python-filtered · Datasets at Hugging Face

e1aafb58eef941757b45eb7221687eebd5c2e5ea

799

py

Python

app.py

mwinel/python-cicd-assignement

c4c08772094f983f8105090f0d91dfef5be042aa

[ "MIT" ]

null

app.py

mwinel/python-cicd-assignement

c4c08772094f983f8105090f0d91dfef5be042aa

[ "MIT" ]

null

app.py

mwinel/python-cicd-assignement

c4c08772094f983f8105090f0d91dfef5be042aa

[ "MIT" ]

null

import os import logging from flask import Flask app = Flask(__name__) if __name__ == "__main__": ## stream logs to a file logging.basicConfig(filename='app.log', level=logging.DEBUG) app.run(debug=True, host='0.0.0.0', port=int(os.environ.get('PORT', 8080)))

22.828571

79

0.673342

e1ad6793329afb999758e7af4b085f4de8b95b33

93

py

Python

Configuration/StandardSequences/python/L1Reco_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

852

2015-01-11T21:03:51.000Z

2022-03-25T21:14:00.000Z

Configuration/StandardSequences/python/L1Reco_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

30,371

2015-01-02T00:14:40.000Z

2022-03-31T23:26:05.000Z

Configuration/StandardSequences/python/L1Reco_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

3,240

2015-01-02T05:53:18.000Z

2022-03-31T17:24:21.000Z

import FWCore.ParameterSet.Config as cms from L1Trigger.Configuration.L1TReco_cff import *

18.6

49

0.83871

e1af67620fb53577d386b7ebbfdc3bab9dc25e7c

2,347

py

Python

pysrc/common/dataset_mod.py

Hibiki1020/classification_attitude_estimator

7f7435c2ed5b5b5c8d0219df2da0426b108ff3aa

[ "MIT" ]

null

pysrc/common/dataset_mod.py

Hibiki1020/classification_attitude_estimator

7f7435c2ed5b5b5c8d0219df2da0426b108ff3aa

[ "MIT" ]

null

pysrc/common/dataset_mod.py

Hibiki1020/classification_attitude_estimator

7f7435c2ed5b5b5c8d0219df2da0426b108ff3aa

[ "MIT" ]

null

import torch.utils.data as data from PIL import Image import numpy as np import math import csv

28.621951

111

0.611845

e1b1063d345266bc6d42ef8301d5659cc8f0a43d

1,846

py

Python

scripts/darias_energy_control/moveit_traj_baseline/repulsive_potential_field.py

hjw-1014/Multi-Objective-Reactive-Motion-Planning-in-Mobile-Manipulators

9a8801e9c663174b753c4852b2313c5a3f302434

[ "MIT" ]

null

scripts/darias_energy_control/moveit_traj_baseline/repulsive_potential_field.py

hjw-1014/Multi-Objective-Reactive-Motion-Planning-in-Mobile-Manipulators

9a8801e9c663174b753c4852b2313c5a3f302434

[ "MIT" ]

null

scripts/darias_energy_control/moveit_traj_baseline/repulsive_potential_field.py

hjw-1014/Multi-Objective-Reactive-Motion-Planning-in-Mobile-Manipulators

9a8801e9c663174b753c4852b2313c5a3f302434

[ "MIT" ]

null

import numpy as np import torch import matplotlib.pyplot as plt from icecream import ic w = 5 Y, X = np.mgrid[-w:w:5j, -w:w:5j] ic(Y) ic(X) import numpy as np import matplotlib.pyplot as plt # # Creating dataset # x = np.arange(0, 10) # y = np.arange(0, 10) # # # Creating grids # X, Y = np.meshgrid(x, y) # # ic(X) # # ic(Y) # # # x-component to the right # u = np.ones((15, 10)) # # # y-component zero # v = -np.ones((10, 10)) # # fig = plt.figure(figsize=(12, 7)) # # # Plotting stream plot # plt.streamplot(X, Y, u, v, density=0.5) # # # show plot # # plt.show() import numpy as np import matplotlib.pyplot as plt # Creating data set w = 3 Y, X = np.mgrid[-w:w:100j, -w:w:100j] U1 = -1 - X ** 2 + Y ic(type(U1)) ic(np.shape(U1)) V1 = 1 + X - Y ** 2 ic(np.shape(V1)) U2 = -1.1 - X ** 2 + Y ic(np.shape(U1)) V2 = 2.1 + X - Y ** 2 # speed = np.sqrt(U ** 2 + V ** 2) # Creating plot fig = plt.figure(figsize=(12, 7)) plt.streamplot(X, Y, U1, V1, density=1) plt.streamplot(X, Y, U2, V2, density=0.8) # show plot plt.show()

20.977273

84

0.594258

e1b18b46651e9f66ff6958a9025b0bc1b9f9aca5

3,793

py

Python

capa/features/extractors/ida/extractor.py

pombredanne/capa

b41d23930189c269608d4b705533fa45cf3c064c

[ "Apache-2.0" ]

null

capa/features/extractors/ida/extractor.py

pombredanne/capa

b41d23930189c269608d4b705533fa45cf3c064c

[ "Apache-2.0" ]

null

capa/features/extractors/ida/extractor.py

pombredanne/capa

b41d23930189c269608d4b705533fa45cf3c064c

[ "Apache-2.0" ]

null

# Copyright (C) 2020 FireEye, Inc. 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: [package root]/LICENSE.txt # Unless required by applicable law or agreed to in writing, software distributed under the License # is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and limitations under the License. import idaapi import capa.ida.helpers import capa.features.extractors.elf import capa.features.extractors.ida.file import capa.features.extractors.ida.insn import capa.features.extractors.ida.global_ import capa.features.extractors.ida.function import capa.features.extractors.ida.basicblock from capa.features.extractors.base_extractor import FeatureExtractor

33.566372

111

0.714474

e1b1b1bf75362e9f77713c3b8bcaddbf1477de81

55

py

Python

Tests/playground.py

mbtaPredict/Main

e1c3320ff08b61355ac96f51be9e20c57372f13b

[ "MIT" ]

null

Tests/playground.py

mbtaPredict/Main

e1c3320ff08b61355ac96f51be9e20c57372f13b

[ "MIT" ]

null

Tests/playground.py

mbtaPredict/Main

e1c3320ff08b61355ac96f51be9e20c57372f13b

[ "MIT" ]

null

import matplotlib.pyplot as plt plt.plot() plt.show()

11

31

0.745455

e1b370db317e8d54c9c290cf01cbebc1cac20378

1,373

py

Python

flex/extensions/jsondata.py

AWehrhahn/flex-format

7fcc985559cd90e54d3ebde7946455aedc7293d7

[ "MIT" ]

null

flex/extensions/jsondata.py

AWehrhahn/flex-format

7fcc985559cd90e54d3ebde7946455aedc7293d7

[ "MIT" ]

null

flex/extensions/jsondata.py

AWehrhahn/flex-format

7fcc985559cd90e54d3ebde7946455aedc7293d7

[ "MIT" ]

null

# -*- coding: utf-8 -*- from __future__ import annotations from tarfile import TarInfo from typing import BinaryIO, Tuple from ..base import FlexExtension

31.930233

78

0.640932

e1b37b3b7be2be9f06bdec60a631822373a8b7f7

185

py

Python

awards/forms.py

danalvin/Django-IP3

6df0adaddf998fd4195b23ee97f81938e741215a

[ "MIT" ]

null

awards/forms.py

danalvin/Django-IP3

6df0adaddf998fd4195b23ee97f81938e741215a

[ "MIT" ]

4

2020-06-05T19:20:59.000Z

2021-09-08T00:32:49.000Z

awards/forms.py

danalvin/Django-IP3

6df0adaddf998fd4195b23ee97f81938e741215a

[ "MIT" ]

null

from django import forms from .models import Project

18.5

52

0.67027

e1b43999f4dbbac898da1e996502f381b7896fa5

72,341

py

Python

src/tale/syntax/grammar/TaleParser.py

tale-lang/tale

1779f94aa13545e58a1d5a8819b85ad02ada4144

[ "MIT" ]

17

2020-02-11T10:38:19.000Z

2020-09-22T16:36:25.000Z

src/tale/syntax/grammar/TaleParser.py

tale-lang/tale

1779f94aa13545e58a1d5a8819b85ad02ada4144

[ "MIT" ]

18

2020-02-14T20:36:25.000Z

2020-05-26T21:52:46.000Z

src/tale/syntax/grammar/TaleParser.py

tale-lang/tale

1779f94aa13545e58a1d5a8819b85ad02ada4144

[ "MIT" ]

1

2020-02-16T12:04:07.000Z

# Generated from tale/syntax/grammar/Tale.g4 by ANTLR 4.8 # encoding: utf-8 from antlr4 import * from io import StringIO import sys if sys.version_info[1] > 5: from typing import TextIO else: from typing.io import TextIO

34.317362

239

0.590868

e1b490b033e953f1585ccd81fdcb489a598e5706

353

py

Python

004.py

gabrieleliasdev/python-cev

45390963b5112a982e673f6a6866da422bf9ae6d

[ "MIT" ]

null

004.py

gabrieleliasdev/python-cev

45390963b5112a982e673f6a6866da422bf9ae6d

[ "MIT" ]

null

004.py

gabrieleliasdev/python-cev

45390963b5112a982e673f6a6866da422bf9ae6d

[ "MIT" ]

null

print('Ol, Mundo!') print(7+4) print('7'+'4') print('Ol', 5) # Toda varivel um objeto # Um objeto mais do que uma varivel nome = 'Gabriel' idade = 30 peso = 79 print(nome,idade,peso) nome = input('>>> Nome ') idade = input('>>> Idade ') peso = input('>>> Peso ') print(nome,idade,peso) print(f'Nome:{nome} ,Idade:{idade} ,Peso:{peso}')

14.12

49

0.620397

e1b5d39efe358fd9f5a0abeb927321f0eef6f285

680

py

Python

examples/create_mac_table_entry.py

open-switch/opx-docs

f448f3f3dc0de38822bbf16c1e173eb108925a40

[ "CC-BY-4.0" ]

122

2017-02-10T01:47:04.000Z

2022-03-23T20:11:11.000Z

examples/create_mac_table_entry.py

open-switch/opx-docs

f448f3f3dc0de38822bbf16c1e173eb108925a40

[ "CC-BY-4.0" ]

37

2017-03-01T07:07:22.000Z

2021-11-11T16:47:42.000Z

examples/create_mac_table_entry.py

open-switch/opx-docs

f448f3f3dc0de38822bbf16c1e173eb108925a40

[ "CC-BY-4.0" ]

39

2017-01-18T16:22:58.000Z

2020-11-18T13:23:43.000Z

#Python code block to configure MAC address table entry import cps_utils #Register the attribute type cps_utils.add_attr_type('base-mac/table/mac-address', 'mac') #Define the MAC address, interface index and VLAN attributes d = {'mac-address': '00:0a:0b:cc:0d:0e', 'ifindex': 18, 'vlan': '100'} #Create a CPS object obj = cps_utils.CPSObject('base-mac/table', data=d) #Associate the operation to the CPS object tr_obj = ('create', obj.get()) #Create a transaction object transaction = cps_utils.CPSTransaction([tr_obj]) #Check for failure ret = transaction.commit() if not ret: raise RuntimeError('Error creating MAC Table Entry') print 'Successfully created'

27.2

70

0.738235

e1b62639aea1ec0a6c6d66e1d90f5f610c374034

4,397

py

Python

win/GUI/Configuration.py

WeAreAVP/mdqc

3130a713c70017bc54d8e5da6bb5766ba9d97423

[ "Apache-2.0" ]

8

2019-01-18T08:58:02.000Z

2021-05-20T16:51:14.000Z

osx/GUI/Configuration.py

WeAreAVP/mdqc

3130a713c70017bc54d8e5da6bb5766ba9d97423

[ "Apache-2.0" ]

7

2016-02-25T21:50:03.000Z

2017-12-13T14:27:29.000Z

osx/GUI/Configuration.py

WeAreAVP/mdqc

3130a713c70017bc54d8e5da6bb5766ba9d97423

[ "Apache-2.0" ]

2

2020-02-13T16:00:07.000Z

2020-08-12T16:31:49.000Z

# -*- coding: UTF-8 -*- ''' Created on May 14, 2014 @author: Furqan Wasi <furqan@avpreserve.com> ''' import os, datetime, sys, platform, base64

31.407143

139

0.596771

e1b62abc8e468748316b85f828dfc8de03775be8

17,306

py

Python

MainController.py

samuelvp360/Microbiological-Assay-Calculator

36317e266bf499f24f7e7d3f59328864a8723aa4

[ "FSFAP" ]

null

MainController.py

samuelvp360/Microbiological-Assay-Calculator

36317e266bf499f24f7e7d3f59328864a8723aa4

[ "FSFAP" ]

null

MainController.py

samuelvp360/Microbiological-Assay-Calculator

36317e266bf499f24f7e7d3f59328864a8723aa4

[ "FSFAP" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- import sys import os from pathlib import Path from datetime import datetime from PyQt5 import QtCore as qtc from PyQt5 import QtWidgets as qtw from PyQt5 import uic import numpy as np from Models import AssaysModel, SamplesModel from DB.AssaysDB import MyZODB import matplotlib from matplotlib import pyplot as plt from matplotlib.figure import Figure from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg, NavigationToolbar2QT as NavigationToolbar from WellProcessor import WellProcessor from Assay import Assay matplotlib.use('Qt5Agg') p = Path(__file__) print(p) isLink = os.path.islink(p) if isLink: theLink = os.readlink(p) path = Path(theLink).resolve().parent path = f'{path}/' print('linked') else: path = '' print('unlinked') if __name__ == '__main__': app = qtw.QApplication(sys.argv) window = MainWindow(path) window.show() sys.exit(app.exec_())

42.836634

108

0.596729

e1b6ebd37b97bc9b109f511037c684ea5fa2de9b

225

py

Python

events/defaults.py

bozbalci/cython-experiments

a675571e09297e3cda9154e8b611562bb8b14f7e

[ "Unlicense" ]

1

2018-06-23T17:52:20.000Z

events/defaults.py

bozbalci/cython-experiments

a675571e09297e3cda9154e8b611562bb8b14f7e

[ "Unlicense" ]

null

events/defaults.py

bozbalci/cython-experiments

a675571e09297e3cda9154e8b611562bb8b14f7e

[ "Unlicense" ]

null

# defaults.py: contains the built-in variables, events and methods # used for scripting the C program import event events = {} _event_names = ["on_start", "on_exit"] for evt in _event_names: events[evt] = event.Event()

22.5

66

0.724444

e1b7011c0667fc12e337dc4c85e26236aa831c39

15,526

py

Python

src/parse_text.py

rflieshman/BOLSTM

be7551957001a9bdaab6051145f96ad9d7415209

[ "Apache-2.0" ]

13

2019-04-11T02:20:49.000Z

2021-03-26T11:00:10.000Z

src/parse_text.py

rflieshman/BOLSTM

be7551957001a9bdaab6051145f96ad9d7415209

[ "Apache-2.0" ]

5

2018-12-05T14:38:40.000Z

2021-12-13T19:46:53.000Z

src/parse_text.py

lasigeBioTM/BOLSTM

c33a8b2a7722acb5e3ff55c3735591aea4f76f49

[ "Apache-2.0" ]

2

2019-10-13T13:47:19.000Z

2021-01-16T10:43:33.000Z

from itertools import combinations import numpy as np import spacy import sys from spacy.tokenizer import Tokenizer import re from subprocess import PIPE, Popen import os import logging import networkx as nx import en_core_web_sm import string from neg_gv import neg_gv_list SSTDIR = "sst-light-0.4/" TEMP_DIR = "temp/" nlp = en_core_web_sm.load(disable=["ner"]) nlp.add_pipe(prevent_sentence_segmentation, name="prevent-sbd", before="parser") # https://stackoverflow.com/a/41817795/3605086 def get_network_graph_spacy(document): """ Convert the dependencies of the spacy document object to a networkX graph :param document: spacy parsed document object :return: networkX graph object and nodes list """ edges = [] nodes = [] # ensure that every token is connected # edges.append(("ROOT", '{0}-{1}'.format(list(document)[0].lower_, list(document)[0].i))) for s in document.sents: edges.append(("ROOT", "{0}-{1}".format(s.root.lower_, s.root.i))) for token in document: nodes.append("{0}-{1}".format(token.lower_, token.i)) # edges.append(("ROOT", '{0}-{1}'.format(token.lower_, token.i))) # print('{0}-{1}'.format(token.lower_, token.i)) # FYI https://spacy.io/docs/api/token for child in token.children: # print("----", '{0}-{1}'.format(child.lower_, child.i)) edges.append( ( "{0}-{1}".format(token.lower_, token.i), "{0}-{1}".format(child.lower_, child.i), ) ) return nx.Graph(edges), nodes def get_head_tokens(entities, sentence): """ :param entities: dictionary mapping entity IDs to (offset, text) :param sentence: sentence parsed by spacy :return: dictionary mapping head tokens word-idx to entity IDs """ sentence_head_tokens = {} for eid in entities: offset = (entities[eid][0][0], entities[eid][0][-1]) # starts = {tok.i: tok.idx for tok in doc} # entity_tokens = sentence.char_span(offset[0], offset[1]) entity_tokens = [ (t, i) for i, t in enumerate(sentence.token) if t.beginChar == offset[0] ] # if not entity_tokens: # try to include the next char # entity_tokens = sentence.char_span(offset[0], offset[1] + 1) # entity_tokens = [t for t in sentence.token if t.beginChar == offset[0]] if not entity_tokens: logging.warning( ( "no tokens found:", entities[eid], sentence.text, "|".join( [ "{}({}-{})".format(t.word, t.beginChar, t.endChar) for t in sentence.token ] ), ) ) # sys.exit() else: head_token = "{0}-{1}".format( entity_tokens[0][0].word.lower(), entity_tokens[0][1] ) if head_token in sentence_head_tokens: logging.warning( ( "head token conflict:", sentence_head_tokens[head_token], entities[eid], ) ) sentence_head_tokens[head_token] = eid return sentence_head_tokens def get_head_tokens_spacy(entities, sentence, positive_entities): """ :param entities: dictionary mapping entity IDs to (offset, text) :param sentence: sentence parsed by spacy :return: dictionary mapping head tokens word-idx to entity IDs """ sentence_head_tokens = {} pos_gv = set() neg_gv = set() for eid in entities: offset = (entities[eid][0][0], entities[eid][0][-1]) # starts = {tok.i: tok.idx for tok in doc} entity_tokens = sentence.char_span(offset[0], offset[1]) # if not entity_tokens: # try to include the next char # entity_tokens = sentence.char_span(offset[0], offset[1] + 1) i = 1 while not entity_tokens and i + offset[1] < len(sentence.text) + 1: entity_tokens = sentence.char_span(offset[0], offset[1] + i) i += 1 i = 0 while not entity_tokens and offset[0] - i > 0: entity_tokens = sentence.char_span(offset[0] - i, offset[1]) i += 1 if not entity_tokens: logging.warning( ( "no tokens found:", entities[eid], sentence.text, "|".join([t.text for t in sentence]), ) ) else: head_token = "{0}-{1}".format( entity_tokens.root.lower_, entity_tokens.root.i ) if eid in positive_entities: pos_gv.add(entity_tokens.root.head.lower_) else: neg_gv.add(entity_tokens.root.head.lower_) if head_token in sentence_head_tokens: logging.warning( ( "head token conflict:", sentence_head_tokens[head_token], entities[eid], ) ) sentence_head_tokens[head_token] = eid return sentence_head_tokens, pos_gv, neg_gv def process_sentence_spacy( sentence, sentence_entities, sentence_pairs, positive_entities, wordnet_tags=None, mask_entities=True, min_sdp_len=0, max_sdp_len=15, ): """ Process sentence to obtain labels, instances and classes for a ML classifier :param sentence: sentence processed by spacy :param sentence_entities: dictionary mapping entity ID to ((e_start, e_end), text, paths_to_root) :param sentence_pairs: dictionary mapping pairs of known entities in this sentence to pair types :return: labels of each pair (according to sentence_entities, word vectors and classes (pair types according to sentence_pairs) """ left_word_vectors = [] right_word_vectors = [] left_wordnets = [] right_wordnets = [] classes = [] labels = [] graph, nodes_list = get_network_graph_spacy(sentence) sentence_head_tokens, pos_gv, neg_gv = get_head_tokens_spacy( sentence_entities, sentence, positive_entities ) # print(neg_gv - pos_gv) entity_offsets = [sentence_entities[x][0][0] for x in sentence_entities] # print(sentence_head_tokens) for (e1, e2) in combinations(sentence_head_tokens, 2): # print() # print(sentence_head_tokens[e1], e1, sentence_head_tokens[e2], e2) # reorder according to entity ID if int(sentence_head_tokens[e1].split("e")[-1]) > int( sentence_head_tokens[e2].split("e")[-1] ): e1, e2 = e2, e1 e1_text = sentence_entities[sentence_head_tokens[e1]] e2_text = sentence_entities[sentence_head_tokens[e2]] if e1_text[1].lower() == e2_text[1].lower(): # logging.debug("skipped same text: {} {}".format(e1_text, e2_text)) continue middle_text = sentence.text[e1_text[0][-1] : e2_text[0][0]] # if middle_text.strip() == "or" or middle_text.strip() == "and": # logging.debug("skipped entity list: {} {} {}".format(e1_text, middle_text, e2_text)) # continue if middle_text.strip() in string.punctuation: # logging.debug("skipped punctuation: {} {} {}".format(e1_text, middle_text, e2_text)) continue # if len(middle_text) < 3: # logging.debug("skipped entity list: {} {} {}".format(e1_text, middle_text, e2_text)) # continue head_token1_idx = int(e1.split("-")[-1]) head_token2_idx = int(e2.split("-")[-1]) try: sdp = nx.shortest_path(graph, source=e1, target=e2) if len(sdp) < min_sdp_len or len(sdp) > max_sdp_len: # logging.debug("skipped short sdp: {} {} {}".format(e1_text, str(sdp), e2_text)) continue neg = False is_neg_gv = False for i, element in enumerate(sdp): token_idx = int(element.split("-")[-1]) # get the index of the token token_text = element.split("-")[0] if (i == 1 or i == len(sdp) - 2) and token_text in neg_gv_list: logging.info("skipped gv {} {}:".format(token_text, str(sdp))) # is_neg_gv = True sdp_token = sentence[token_idx] # get the token obj # if any(c.dep_ == 'neg' for c in sdp_token.children): # neg = True if neg or is_neg_gv: continue # if len(sdp) < 3: # len=2, just entities # sdp = [sdp[0]] + nodes_list[head_token1_idx-2:head_token1_idx] # sdp += nodes_list[head_token2_idx+1:head_token2_idx+3] + [sdp[-1]] # print(e1_text[1:], e2_text[1:], sdp) # if len(sdp) == 2: # add context words vector = [] wordnet_vector = [] negations = 0 head_token_position = None for i, element in enumerate(sdp): if element != "ROOT": token_idx = int( element.split("-")[-1] ) # get the index of the token sdp_token = sentence[token_idx] # get the token obj # if any(c.dep_ == 'neg' for c in sdp_token.children): # token is negated! # vector.append("not") # negations += 1 # logging.info("negated!: {}<->{} {}: {}".format(e1_text, e2_text, sdp_token.text, sentence.text)) if mask_entities and sdp_token.idx in entity_offsets: vector.append("drug") else: vector.append(sdp_token.text) if wordnet_tags: wordnet_vector.append(wordnet_tags[token_idx]) # print(element, sdp_token.text, head_token, sdp) head_token = "{}-{}".format( sdp_token.head.lower_, sdp_token.head.i ) # get the key of head token # head token must not have its head in the path, otherwise that would be the head token # in some cases the token is its own head if head_token not in sdp or head_token == element: # print("found head token of:", e1_text, e2_text, sdp_token.text, sdp) head_token_position = i + negations # vector.append(parsed[token_idx].text) # print(vector) if head_token_position is None: print("head token not found:", e1_text, e2_text, sdp) sys.exit() else: left_vector = vector[: head_token_position + 1] right_vector = vector[head_token_position:] left_wordnet = wordnet_vector[: head_token_position + 1] right_wordnet = wordnet_vector[head_token_position:] # word_vectors.append(vector) left_word_vectors.append(left_vector) right_word_vectors.append(right_vector) left_wordnets.append(left_wordnet) right_wordnets.append(right_wordnet) # if (sentence_head_tokens[e1], sentence_head_tokens[e2]) in sentence_pairs: # print(sdp, e1, e2, sentence_text) # print(e1_text, e2_text, sdp, sentence_text) # instances.append(sdp) except nx.exception.NetworkXNoPath: # pass logging.warning("no path:", e1_text, e2_text, graph.nodes()) left_word_vectors.append([]) right_word_vectors.append([]) left_wordnets.append([]) right_wordnets.append([]) # print("no path:", e1_text, e2_text, sentence_text, parsed.print_tree(light=True)) # sys.exit() except nx.NodeNotFound: logging.warning( ( "node not found:", e1_text, e2_text, e1, e2, list(sentence), graph.nodes(), ) ) left_word_vectors.append([]) right_word_vectors.append([]) left_wordnets.append([]) right_wordnets.append([]) labels.append((sentence_head_tokens[e1], sentence_head_tokens[e2])) # print(sentence_head_tokens[e1], sentence_head_tokens[e2]) if (sentence_head_tokens[e1], sentence_head_tokens[e2]) in sentence_pairs: classes.append( sentence_pairs[(sentence_head_tokens[e1], sentence_head_tokens[e2])] ) else: classes.append(0) return ( labels, (left_word_vectors, right_word_vectors), (left_wordnets, right_wordnets), classes, pos_gv, neg_gv, )

37.502415

119

0.550818

e1b73e252109287a68039d70bc02eba7d5e821da

1,049

py

Python

metadata-ingestion/examples/library/dataset_set_tag.py

cuong-pham/datahub

cb4eb001758f55622add0f4dc3650cf483609cba

[ "Apache-2.0" ]

1,603

2016-03-03T17:21:03.000Z

2020-01-22T22:12:02.000Z

metadata-ingestion/examples/library/dataset_set_tag.py

cuong-pham/datahub

cb4eb001758f55622add0f4dc3650cf483609cba

[ "Apache-2.0" ]

1,157

2016-03-03T19:29:22.000Z

2020-01-20T14:41:59.000Z

metadata-ingestion/examples/library/dataset_set_tag.py

cuong-pham/datahub

cb4eb001758f55622add0f4dc3650cf483609cba

[ "Apache-2.0" ]

570

2016-03-03T17:21:05.000Z

2020-01-21T06:54:10.000Z

# Imports for urn construction utility methods import logging from datahub.emitter.mce_builder import make_dataset_urn, make_tag_urn from datahub.emitter.mcp import MetadataChangeProposalWrapper from datahub.emitter.rest_emitter import DatahubRestEmitter # Imports for metadata model classes from datahub.metadata.schema_classes import ( ChangeTypeClass, GlobalTagsClass, TagAssociationClass, ) log = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO) dataset_urn = make_dataset_urn(platform="hive", name="realestate_db.sales", env="PROD") tag_urn = make_tag_urn("purchase") event: MetadataChangeProposalWrapper = MetadataChangeProposalWrapper( entityType="dataset", changeType=ChangeTypeClass.UPSERT, entityUrn=dataset_urn, aspectName="globalTags", aspect=GlobalTagsClass(tags=[TagAssociationClass(tag=tag_urn)]), ) # Create rest emitter rest_emitter = DatahubRestEmitter(gms_server="http://localhost:8080") rest_emitter.emit(event) log.info(f"Set tags to {tag_urn} for dataset {dataset_urn}")

32.78125

87

0.804576

e1b7f693b03922194b579f49635c8089ae32b745

517

py

Python

examples/Old Format/matrix_latex.py

waldyrious/galgebra

b5eb070340434d030dd737a5656fbf709538b0b1

[ "BSD-3-Clause" ]

151

2018-09-18T12:30:14.000Z

2022-03-16T08:02:48.000Z

examples/Old Format/matrix_latex.py

abrombo/galgebra

5ae058c9ba2c17b1baf46c58f77124e82eaf428a

[ "BSD-3-Clause" ]

454

2018-09-19T01:42:30.000Z

2022-01-18T14:02:00.000Z

examples/Old Format/matrix_latex.py

abrombo/galgebra

5ae058c9ba2c17b1baf46c58f77124e82eaf428a

[ "BSD-3-Clause" ]

30

2019-02-22T08:25:50.000Z

2022-01-15T05:20:22.000Z

from __future__ import print_function from sympy import symbols, Matrix from galgebra.printer import xpdf, Format if __name__ == "__main__": main()

19.884615

65

0.475822

e1b88db11881c00abc4ca3f31868a0861378a947

780

py

Python

hopsapp/__init__.py

mrahman013/Hope4Hops-web-applcation

d5bde1463c6fbc1ea5424cb656504119393c6ce2

[ "MIT" ]

null

hopsapp/__init__.py

mrahman013/Hope4Hops-web-applcation

d5bde1463c6fbc1ea5424cb656504119393c6ce2

[ "MIT" ]

null

hopsapp/__init__.py

mrahman013/Hope4Hops-web-applcation

d5bde1463c6fbc1ea5424cb656504119393c6ce2

[ "MIT" ]

null

"""Implements a basic flask app that provides hashes of text.""" from flask import Flask from flask_sqlalchemy import SQLAlchemy import flask_login #pylint: disable=invalid-name app = Flask(__name__) app.config['DEBUG'] = True app.config['SQLALCHEMY_DATABASE_URI'] = 'postgres://yjjuylsytqewni:d0d63322c6abd33e2dadeafd7ef2501f73af54cf2d39596e464ea2c18b0234a3@ec2-23-23-78-213.compute-1.amazonaws.com:5432/d3gdnt7fkmonn1' #pylint: disable=line-too-long app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = True app.secret_key = 'HGTYNVK123LOL908973' db = SQLAlchemy(app) login_manager = flask_login.LoginManager() login_manager.init_app(app) # This import need to be here that's why disabling pylint #pylint: disable=wrong-import-position import hopsapp.models import hopsapp.routes

35.454545

224

0.815385

e1b8fdfc631946eef5fedb38c2e25e5e6c2e1add

800

py

Python

npytoImage.py

x35yao/camera

0ee77f5de72d785ba68bef44a557470ec425d702

[ "MIT" ]

null

npytoImage.py

x35yao/camera

0ee77f5de72d785ba68bef44a557470ec425d702

[ "MIT" ]

null

npytoImage.py

x35yao/camera

0ee77f5de72d785ba68bef44a557470ec425d702

[ "MIT" ]

null

import numpy as np; import cv2; n = 428671 img_RS_color = np.load('/home/p4bhattachan/gripper/3DCameraServer/testImages/npyFiles/{}_RS_color.npy'.format(n)) cv2.imshow('RS Color Image {}'.format(n), img_RS_color) # # # img_RS_depth = np.load('/home/p4bhattachan/gripper/3DCameraServer/testImages/npyFiles/{}_RS_depth.npy'.format(n)) # # cv2.imshow('RS Depth Image {}'.format(n), img_RS_depth) # # img_ZED_color = np.load('/home/p4bhattachan/gripper/3DCameraServer/testImages/npyFiles/{}_ZED_color.npy'.format(n)) # cv2.imshow('ZED Color Image {}'.format(n), img_ZED_color) # # # img_ZED_depth = np.load('/home/p4bhattachan/gripper/3DCameraServer/testImages/npyFiles/{}_ZED_depth.npy'.format(n)) # # cv2.imshow('ZED Depth Image {}'.format(n), img_ZED_depth) cv2.waitKey(0) cv2.destroyAllWindows()

38.095238

119

0.7475

e1b94f246fa698d25573d863b176f320113a2877

11,217

py

Python

magenta/music/sequences_lib.py

jellysquider/magenta

0fc8188870f5d1c988b76dae434b21e58362516c

[ "Apache-2.0" ]

null

magenta/music/sequences_lib.py

jellysquider/magenta

0fc8188870f5d1c988b76dae434b21e58362516c

[ "Apache-2.0" ]

null

magenta/music/sequences_lib.py

jellysquider/magenta

0fc8188870f5d1c988b76dae434b21e58362516c

[ "Apache-2.0" ]

null

# Copyright 2016 Google Inc. 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. """Defines sequence of notes objects for creating datasets.""" import collections import copy # internal imports from magenta.music import constants from magenta.protobuf import music_pb2 # Set the quantization cutoff. # Note events before this cutoff are rounded down to nearest step. Notes # above this cutoff are rounded up to nearest step. The cutoff is given as a # fraction of a step. # For example, with quantize_cutoff = 0.75 using 0-based indexing, # if .75 < event <= 1.75, it will be quantized to step 1. # If 1.75 < event <= 2.75 it will be quantized to step 2. # A number close to 1.0 gives less wiggle room for notes that start early, # and they will be snapped to the previous step. QUANTIZE_CUTOFF = 0.5 # Shortcut to chord symbol text annotation type. CHORD_SYMBOL = music_pb2.NoteSequence.TextAnnotation.CHORD_SYMBOL def extract_subsequence(sequence, start_time, end_time): """Extracts a subsequence from a NoteSequence. Notes starting before `start_time` are not included. Notes ending after `end_time` are truncated. Args: sequence: The NoteSequence to extract a subsequence from. start_time: The float time in seconds to start the subsequence. end_time: The float time in seconds to end the subsequence. Returns: A new NoteSequence that is a subsequence of `sequence` in the specified time range. """ subsequence = music_pb2.NoteSequence() subsequence.CopyFrom(sequence) del subsequence.notes[:] for note in sequence.notes: if note.start_time < start_time or note.start_time >= end_time: continue new_note = subsequence.notes.add() new_note.CopyFrom(note) new_note.end_time = min(note.end_time, end_time) subsequence.total_time = min(sequence.total_time, end_time) return subsequence def is_power_of_2(x): return x and not x & (x - 1)

38.67931

80

0.692788

e1ba5c72da56a9dbf7ee8bd79a41429f11457824

8,404

py

Python

tests/index_jsonurl_test.py

Stidsty/dismantle

26fb8fe7ba97349a67498715bb47a19329b1a4c7

[ "Apache-2.0" ]

null

tests/index_jsonurl_test.py

Stidsty/dismantle

26fb8fe7ba97349a67498715bb47a19329b1a4c7

[ "Apache-2.0" ]

null

tests/index_jsonurl_test.py

Stidsty/dismantle

26fb8fe7ba97349a67498715bb47a19329b1a4c7

[ "Apache-2.0" ]

null

# Copyright 2021 Gary Stidston-Broadbent # # 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 hashlib import md5 from json import JSONDecodeError from shutil import copy2 import pytest from pytest_httpserver import HTTPServer from pytest_httpserver.httpserver import HandlerType from requests import ConnectionError from dismantle.index import IndexHandler, JsonUrlIndexHandler

42.02

79

0.707996

e1ba723285119341020fa35acb08aec8be4bb131

200

py

Python

src/resdk/__init__.py

AGregorc/resolwe-bio-py

62304e5d4c54c917575421701c6977dc63fc3a8f

[ "Apache-2.0" ]

4

2016-09-28T16:00:05.000Z

2018-08-16T16:14:10.000Z

src/resdk/__init__.py

AGregorc/resolwe-bio-py

62304e5d4c54c917575421701c6977dc63fc3a8f

[ "Apache-2.0" ]

229

2016-03-28T19:41:00.000Z

2022-03-16T15:02:15.000Z

src/resdk/__init__.py

AGregorc/resolwe-bio-py

62304e5d4c54c917575421701c6977dc63fc3a8f

[ "Apache-2.0" ]

18

2016-03-10T16:11:57.000Z

2021-06-01T10:01:49.000Z

"""Resolwe SDK for Python.""" from .collection_tables import CollectionTables # noqa from .resdk_logger import log_to_stdout, start_logging # noqa from .resolwe import Resolwe, ResolweQuery # noqa

40

62

0.79

e1bade04e7403e544b5faa2f08e7005733a09b95

4,842

py

Python

helper/validation_scripts/launch-lm-profile.py

NanoMembers/DeepFlow

0235fe460d15a95f90202a1fdb3d3405d774511a

[ "Apache-2.0" ]

3

2020-10-29T19:00:29.000Z

2020-12-21T12:24:28.000Z

helper/validation_scripts/launch-lm-profile.py

NanoMembers/DeepFlow

0235fe460d15a95f90202a1fdb3d3405d774511a

[ "Apache-2.0" ]

null

helper/validation_scripts/launch-lm-profile.py

NanoMembers/DeepFlow

0235fe460d15a95f90202a1fdb3d3405d774511a

[ "Apache-2.0" ]

null

#!/tools/python/python3.8.3/bin/python import os import shutil import subprocess import numpy as np batch_list=[i*1024 for i in range(2,7)] seq_list=[10] hidden_list=[i*1024 for i in range(2,7)] vocab_list=[2048] #[int(i) for i in (2**np.linspace(10,13,20)//2*2)] layer_list=[1] bpe_list=[10] epoch_list=[3] output_dir="/mnt/home/newsha/baidu/developement/MechaFlow/validation/benchmarks/rnnlm/profile_gemm" result_file="{}/result.csv".format(output_dir) if os.path.exists(output_dir): shutil.rmtree(output_dir, ignore_errors=True) os.makedirs(output_dir) print("Created {}".format(output_dir)) with open(result_file, "w") as f: f.write("Batch Seq Hidden Vocab Layers Epoch BPE core_util dram_util l2_util dram_read dram_write l2_access fp16_inst fma_inst\n\n") print("Batch Seq Hidden Vocab Layers Epoch BPE core_util dram_util l2_util dram_read dram_write l2_access fp16_inst fma_inst\n\n") for b in batch_list: for s in seq_list: for d in hidden_list: for v in vocab_list: for l in layer_list: for bpe in bpe_list: for e in epoch_list: bpe = min(bpe, 25000//b) fname = "B{}-S{}-D{}-V{}-L{}-E{}-P{}".format(b,s,d,v,l,e,bpe) output_file = "{}/{}.out".format(output_dir, fname) command1="/tools/cuda/cuda-11.0.1/bin/ncu --metrics \"regex:.*\" -k volta_fp16_s884gemm_fp16_... -s 0 -c 1 '/tools/venvs/tensorflow/tensorflow-2.2.0/bin/python' lm-fp16.py -m train -train data/test-index.txt -test data/test-index.txt -valid data/test-index.txt -b{} -s{} -d{} -v{} -l{} -p{} -e{} > {} 2>&1".format(b, s, d, v, l, bpe, e, output_file) #command1 = "/tools/cuda/cuda-11.0.1/bin/nsys profile -t cuda,osrt,cudnn,cublas,nvtx,mpi -o profile/{} --stats=true -f true python lm-fp16.py -b{} -s{} -d{} -v{} -l{} -p{} -e{} -m train -train data/test-index.txt -test data/test-index.txt -valid data/test-index.txt > {} 2>&1".format(fname, b, s, d, v, l, bpe, e, output_file) command2 = "cat {} | grep \"sm__pipe_tensor_op_hmma_cycles_active.avg.pct_of_peak_sustained_active\"| awk {{'print $3'}}".format(output_file) #unit command3 = "cat {} | grep \"dram__throughput.avg.pct_of_peak_sustained_active\"| awk {{'print $3'}}".format(output_file) #unit command4 = "cat {} | grep lts__t_sectors.avg.pct_of_peak_sustained_active | awk {{'print $3'}}".format(output_file) #unit command5 = "cat {} | grep dram_read_bytes | grep sum | head -n 1 | awk {{'print $3'}}".format(output_file) #unit command6 = "cat {} | grep dram_write_bytes | grep sum | head -n 1 | awk {{'print $3'}}".format(output_file) #unit command7 = "cat {} | grep lts__t_bytes.sum | head -n 1 | awk {{'print $3'}}".format(output_file) #unit command8 = "cat {} | grep sm__sass_thread_inst_executed_op_fp16_pred_on.sum | head -n 1 | awk {{'print $3'}}".format(output_file) #unit command9 = "cat {} | grep sm__sass_thread_inst_executed_ops_fadd_fmul_ffma_pred_on.sum | head -n 1 | awk {{'print $3'}}".format(output_file) #unit result = {'ncu':-1, 'core_util':-1, 'dram_util':-1, 'l2_util':-1, 'dram_read':-1, 'dram_write':-1, 'l2_access':-1, 'fp16_inst':-1, 'fma_inst':-1} run_command(command1, 'ncu', result) run_command(command2, 'core_util', result) run_command(command3, 'dram_util', result) run_command(command4, 'l2_util', result) run_command(command5, 'dram_read', result) run_command(command6, 'dram_write', result) run_command(command7, 'l2_access', result) run_command(command8, 'fp16_inst', result) run_command(command9, 'fma_inst', result) with open(result_file, "a+") as f: f.write("{0:d} {1:d} {2:d} {3:d} {4:d} {5:d} {6:d} {7:.2f} {8:.2f} {9:.2f} {10:,} {11:,} {12:,} {13:,} {14:,}\n".format(b, s, d, v, l, e, bpe, result['core_util'], result['dram_util'], result['l2_util'], result['dram_read'], result['dram_write'], result['l2_access'], int(result['fp16_inst']), int(result['fma_inst']))) print("{0:d} {1:d} {2:d} {3:d} {4:d} {5:d} {6:d} {7:.2f} {8:.2f} {9:.2f} {10:,} {11:,} {12:,} {13:,} {14:,}\n".format(b, s, d, v, l, e, bpe, result['core_util'], result['dram_util'], result['l2_util'], result['dram_read'], result['dram_write'], result['l2_access'], int(result['fp16_inst']), int(result['fma_inst'])))

63.710526

363

0.621437

e1bb9b6b3739ef931135cf1fd4f2fa3e0d1cab30

8,171

py

Python

src/planet_box_extractor/extractor.py

V-AI-S/planet-box-extractor

5404bc97e7a2e1f6d90c7503d9106973038e4387

[ "MIT" ]

6

2021-05-31T14:51:55.000Z

2022-01-27T14:44:04.000Z

src/planet_box_extractor/extractor.py

V-AI-S/planet-box-extractor

5404bc97e7a2e1f6d90c7503d9106973038e4387

[ "MIT" ]

null

src/planet_box_extractor/extractor.py

V-AI-S/planet-box-extractor

5404bc97e7a2e1f6d90c7503d9106973038e4387

[ "MIT" ]

null

from .geo_utils import boundingBox import time import PIL.Image import urllib.request import mercantile import numpy as np if __name__ == '__main__': latitude, longitude = 5, 20 zoom = 15 radius = 0.2 API_KEY = '' map_id = '' extractor = PlanetBoxExtractor(radius, zoom, map_id, API_KEY) image = extractor.Process(latitude, longitude)

41.060302

153

0.598947

e1bbdc48371fed473f16ae3afb93373be31ead4e

21,365

py

Python

Kai/python/modules/mctruth.py

NJManganelli/FourTopNAOD

9743d5b49bdbad27a74abb7b2d5b7295f678a0e3

[ "Apache-2.0" ]

1

2022-01-17T17:29:38.000Z

Kai/python/modules/mctruth.py

NJManganelli/FourTopNAOD

9743d5b49bdbad27a74abb7b2d5b7295f678a0e3

[ "Apache-2.0" ]

null

Kai/python/modules/mctruth.py

NJManganelli/FourTopNAOD

9743d5b49bdbad27a74abb7b2d5b7295f678a0e3

[ "Apache-2.0" ]

1

2021-12-15T10:56:50.000Z

from __future__ import (division, print_function) import os import ROOT #import numpy as np #import itertools #from collections import OrderedDict ROOT.PyConfig.IgnoreCommandLineOptions = True from PhysicsTools.NanoAODTools.postprocessing.framework.datamodel import Collection, Object from PhysicsTools.NanoAODTools.postprocessing.framework.eventloop import Module from PhysicsTools.NanoAODTools.postprocessing.tools import * #deltaR, deltaPhi, etc. _rootLeafType2rootBranchType = { 'UChar_t':'b', 'Char_t':'B', 'UInt_t':'i', 'Int_t':'I', 'Float_t':'F', 'Double_t':'D', 'ULong64_t':'l', 'Long64_t':'L', 'Bool_t':'O' }

54.088608

192

0.539246

e1bced98ae2a678cded5046d18c92e44944d6925

1,214

py

Python

skimpy/utils/namespace.py

AQ18/skimpy

435fc50244f2ca815bbb39d525a82a4692f5c0ac

[ "Apache-2.0" ]

13

2020-11-05T10:59:13.000Z

2022-03-21T01:38:31.000Z

skimpy/utils/namespace.py

AQ18/skimpy

435fc50244f2ca815bbb39d525a82a4692f5c0ac

[ "Apache-2.0" ]

4

2022-01-27T10:23:40.000Z

2022-03-10T18:16:06.000Z

skimpy/utils/namespace.py

AQ18/skimpy

435fc50244f2ca815bbb39d525a82a4692f5c0ac

[ "Apache-2.0" ]

6

2020-08-04T17:01:33.000Z

2022-03-21T01:38:32.000Z

# -*- coding: utf-8 -*- """ .. module:: pytfa :platform: Unix, Windows :synopsis: Simple Kinetic Models in Python .. moduleauthor:: SKiMPy team [---------] Copyright 2017 Laboratory of Computational Systems Biotechnology (LCSB), Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland 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. """ """ Simulation types """ QSSA = 'qssa' TQSSA = 'tqssa' MCA = 'mca' ODE = 'ode' ELEMENTARY = 'elementary' """ Jacobian Types""" NUMERICAL = 'numerical' SYMBOLIC = 'symbolic' """ MCA Types """ NET = 'net' SPLIT = 'split' """ Item types """ PARAMETER = 'parameter' VARIABLE = 'variable' """ Units """ KCAL = 'kcal' KJ = 'kJ' JOULE = 'JOULE' """ OTHER """ WATER_FORMULA = 'H2O'

21.298246

72

0.702636

e1be426bfe54febaaf2747236ba29b8bea95325e

2,897

py

Python

designate/storage/impl_sqlalchemy/migrate_repo/versions/051_scoped_tsig.py

cneill/designate-testing

7bf320062d85a12bff2aee8d26c133941a289fc4

[ "Apache-2.0" ]

null

designate/storage/impl_sqlalchemy/migrate_repo/versions/051_scoped_tsig.py

cneill/designate-testing

7bf320062d85a12bff2aee8d26c133941a289fc4

[ "Apache-2.0" ]

null

designate/storage/impl_sqlalchemy/migrate_repo/versions/051_scoped_tsig.py

cneill/designate-testing

7bf320062d85a12bff2aee8d26c133941a289fc4

[ "Apache-2.0" ]

null

# Copyright 2015 Hewlett-Packard Development Company, L.P. # # Author: Kiall Mac Innes <kiall@hp.com> # # 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 oslo_config import cfg from sqlalchemy import Enum from sqlalchemy.schema import Table, MetaData, Column from migrate.changeset.constraint import UniqueConstraint from designate.sqlalchemy.types import UUID meta = MetaData() # Get the default pool_id from the config file default_pool_id = cfg.CONF['service:central'].default_pool_id.replace('-', '') TSIG_SCOPES = ['POOL', 'ZONE']

36.2125

78

0.713497

e1bf68076ea2cc2d9234c0759575b80d167f8b2e

680

py

Python

geomat/stein/migrations/0060_remove_mineraltype_mohs_scale.py

mimischi/django-geomat

8c5bc4c9ba9759b58b52ddf339ccaec40ec5f6ea

[ "BSD-3-Clause" ]

3

2017-01-13T15:53:39.000Z

2017-05-05T11:57:55.000Z

geomat/stein/migrations/0060_remove_mineraltype_mohs_scale.py

mimischi/django-geomat

8c5bc4c9ba9759b58b52ddf339ccaec40ec5f6ea

[ "BSD-3-Clause" ]

233

2016-11-05T15:19:48.000Z

2021-09-07T23:33:47.000Z

geomat/stein/migrations/0060_remove_mineraltype_mohs_scale.py

GeoMatDigital/django-geomat

8c5bc4c9ba9759b58b52ddf339ccaec40ec5f6ea

[ "BSD-3-Clause" ]

null

# Generated by Django 2.0.2 on 2018-05-04 07:33 from django.db import migrations from django.db import models

26.153846

106

0.632353

e1c057aa5119875fed8dba5a07e37ff673709a2b

14,420

py

Python

bamboo/core/calculator.py

pld/bamboo

a0fc77aebd6ff6b1087ba46896b0ce705fbb25a3

[ "BSD-3-Clause" ]

27

2015-01-14T15:57:54.000Z

2020-12-27T19:34:41.000Z

bamboo/core/calculator.py

biswapanda/bamboo

72fc260822a27ce52cbe65de178f8fa1b60311f3

[ "BSD-3-Clause" ]

2

2015-08-06T15:23:28.000Z

2016-01-28T00:05:25.000Z

bamboo/core/calculator.py

biswapanda/bamboo

72fc260822a27ce52cbe65de178f8fa1b60311f3

[ "BSD-3-Clause" ]

10

2015-08-07T01:50:39.000Z

2019-05-15T21:41:18.000Z

from collections import defaultdict from celery.task import task from pandas import concat, DataFrame from bamboo.core.aggregator import Aggregator from bamboo.core.frame import add_parent_column, join_dataset from bamboo.core.parser import Parser from bamboo.lib.datetools import recognize_dates from bamboo.lib.jsontools import df_to_jsondict from bamboo.lib.mongo import MONGO_ID from bamboo.lib.parsing import parse_columns from bamboo.lib.query_args import QueryArgs from bamboo.lib.utils import combine_dicts, flatten, to_list def calculate_columns(dataset, calculations): """Calculate and store new columns for `calculations`. The new columns are join t othe Calculation dframe and replace the dataset's observations. .. note:: This can result in race-conditions when: - deleting ``controllers.Datasets.DELETE`` - updating ``controllers.Datasets.POST([dataset_id])`` Therefore, perform these actions asychronously. :param dataset: The dataset to calculate for. :param calculations: A list of calculations. """ new_cols = None for c in calculations: if c.aggregation: aggregator = __create_aggregator( dataset, c.formula, c.name, c.groups_as_list) aggregator.save(dataset) else: columns = parse_columns(dataset, c.formula, c.name) if new_cols is None: new_cols = DataFrame(columns[0]) else: new_cols = new_cols.join(columns[0]) if new_cols is not None: dataset.update_observations(new_cols) # propagate calculation to any merged child datasets [__propagate_column(x, dataset) for x in dataset.merged_datasets] def dframe_from_update(dataset, new_data): """Make a DataFrame for the `new_data`. :param new_data: Data to add to dframe. :type new_data: List. """ filtered_data = [] columns = dataset.columns labels_to_slugs = dataset.schema.labels_to_slugs num_columns = len(columns) num_rows = dataset.num_rows dframe_empty = not num_columns if dframe_empty: columns = dataset.schema.keys() for row in new_data: filtered_row = dict() for col, val in row.iteritems(): # special case for reserved keys (e.g. _id) if col == MONGO_ID: if (not num_columns or col in columns) and\ col not in filtered_row.keys(): filtered_row[col] = val else: # if col is a label take slug, if it's a slug take col slug = labels_to_slugs.get( col, col if col in labels_to_slugs.values() else None) # if slug is valid or there is an empty dframe if (slug or col in labels_to_slugs.keys()) and ( dframe_empty or slug in columns): filtered_row[slug] = dataset.schema.convert_type( slug, val) filtered_data.append(filtered_row) index = range(num_rows, num_rows + len(filtered_data)) new_dframe = DataFrame(filtered_data, index=index) return new_dframe def __calculation_data(dataset): """Create a list of aggregate calculation information. Builds a list of calculation information from the current datasets aggregated datasets and aggregate calculations. """ calcs_to_data = defaultdict(list) calculations = dataset.calculations(only_aggs=True) names_to_formulas = {c.name: c.formula for c in calculations} names = set(names_to_formulas.keys()) for group, dataset in dataset.aggregated_datasets: labels_to_slugs = dataset.schema.labels_to_slugs calculations_for_dataset = list(set( labels_to_slugs.keys()).intersection(names)) for calc in calculations_for_dataset: calcs_to_data[calc].append(( names_to_formulas[calc], labels_to_slugs[calc], group, dataset)) return flatten(calcs_to_data.values()) def __update_is_valid(dataset, new_dframe): """Check if the update is valid. Check whether this is a right-hand side of any joins and deny the update if the update would produce an invalid join as a result. :param dataset: The dataset to check if update valid for. :param new_dframe: The update dframe to check. :returns: True is the update is valid, False otherwise. """ select = {on: 1 for on in dataset.on_columns_for_rhs_of_joins if on in new_dframe.columns and on in dataset.columns} dframe = dataset.dframe(query_args=QueryArgs(select=select)) for on in select.keys(): merged_join_column = concat([new_dframe[on], dframe[on]]) if len(merged_join_column) != merged_join_column.nunique(): return False return True def __propagate_column(dataset, parent_dataset): """Propagate columns in `parent_dataset` to `dataset`. When a new calculation is added to a dataset this will propagate the new column to all child (merged) datasets. :param dataset: THe child dataet. :param parent_dataset: The dataset to propagate. """ # delete the rows in this dataset from the parent dataset.remove_parent_observations(parent_dataset.dataset_id) # get this dataset without the out-of-date parent rows dframe = dataset.dframe(keep_parent_ids=True) # create new dframe from the upated parent and add parent id parent_dframe = add_parent_column(parent_dataset.dframe(), parent_dataset.dataset_id) # merge this new dframe with the existing dframe updated_dframe = concat([dframe, parent_dframe]) # save new dframe (updates schema) dataset.replace_observations(updated_dframe) dataset.clear_summary_stats() # recur into merged dataset [__propagate_column(x, dataset) for x in dataset.merged_datasets] def __update_aggregate_dataset(dataset, formula, new_dframe, name, groups, a_dataset, reducible): """Update the aggregated dataset built for `dataset` with `calculation`. Proceed with the following steps: - delete the rows in this dataset from the parent - recalculate aggregated dataframe from aggregation - update aggregated dataset with new dataframe and add parent id - recur on all merged datasets descending from the aggregated dataset :param formula: The formula to execute. :param new_dframe: The DataFrame to aggregate on. :param name: The name of the aggregation. :param groups: A column or columns to group on. :type group: String, list of strings, or None. :param a_dataset: The DataSet to store the aggregation in. """ # parse aggregation and build column arguments aggregator = __create_aggregator( dataset, formula, name, groups, dframe=new_dframe) new_agg_dframe = aggregator.update(dataset, a_dataset, formula, reducible) # jsondict from new dframe new_data = df_to_jsondict(new_agg_dframe) for merged_dataset in a_dataset.merged_datasets: # remove rows in child from this merged dataset merged_dataset.remove_parent_observations(a_dataset.dataset_id) # calculate updates for the child calculate_updates(merged_dataset, new_data, parent_dataset_id=a_dataset.dataset_id) def __update_joined_datasets(dataset, update): """Update any joined datasets.""" if 'add' in update: new_dframe = update['add'] for direction, other_dataset, on, j_dataset in dataset.joined_datasets: if 'add' in update: if direction == 'left': # only proceed if on in new dframe if on in new_dframe.columns: left_dframe = other_dataset.dframe(padded=True) # only proceed if new on value is in on column in lhs if len(set(new_dframe[on]).intersection( set(left_dframe[on]))): merged_dframe = join_dataset(left_dframe, dataset, on) j_dataset.replace_observations(merged_dframe) # TODO is it OK not to propagate the join here? else: # if on in new data join with existing data if on in new_dframe: new_dframe = join_dataset(new_dframe, other_dataset, on) calculate_updates(j_dataset, df_to_jsondict(new_dframe), parent_dataset_id=dataset.dataset_id) elif 'delete' in update: j_dataset.delete_observation(update['delete']) elif 'edit' in update: j_dataset.update_observation(*update['edit'])

35.343137

78

0.676283

e1c0ee31e7c392fd9a301672456d03f86541b8f3

265

py

Python

modules/python3/tests/unittests/scripts/glm.py

ImagiaViz/inviwo

a00bb6b0551bc1cf26dc0366c827c1a557a9603d

[ "BSD-2-Clause" ]

349

2015-01-30T09:21:52.000Z

2022-03-25T03:10:02.000Z

modules/python3/tests/unittests/scripts/glm.py

ImagiaViz/inviwo

a00bb6b0551bc1cf26dc0366c827c1a557a9603d

[ "BSD-2-Clause" ]

641

2015-09-23T08:54:06.000Z

2022-03-23T09:50:55.000Z

modules/python3/tests/unittests/scripts/glm.py

ImagiaViz/inviwo

a00bb6b0551bc1cf26dc0366c827c1a557a9603d

[ "BSD-2-Clause" ]

124

2015-02-27T23:45:02.000Z

2022-02-21T09:37:14.000Z

import inviwopy from inviwopy.glm import * v1 = vec3(1,2,3) v2 = size2_t(4,5) m1 = mat4(1) m2 = mat3(0,1,0,-1,0,0,0,0,2) v3 = m2 * v1 v4 = vec4(1,2,3,4) w = v4.w a = v4.a q = v4.q z = v4.z b = v4.b p = v4.p y = v4.y g = v4.g t = v4.t x = v4.x r = v4.r s = v4.s

10.6

29

0.532075

e1c1c2a4c0c8d49965261747c7efaf839f60298c

7,538

py

Python

djangoexample/thumbs/views.py

arneb/sorethumb

5b224fbf30eaeb83640510d11a0dea40592e76ad

[ "BSD-3-Clause" ]

null

djangoexample/thumbs/views.py

arneb/sorethumb

5b224fbf30eaeb83640510d11a0dea40592e76ad

[ "BSD-3-Clause" ]

null

djangoexample/thumbs/views.py

arneb/sorethumb

5b224fbf30eaeb83640510d11a0dea40592e76ad

[ "BSD-3-Clause" ]

null

from django.http import HttpResponse from django.shortcuts import render_to_response from django.template import RequestContext from django.conf import settings from models import ThumbTest from sorethumb.filters.defaultfilters import * from sorethumb.filters.drawfilters import * from sorethumb.djangothumbnail import DjangoThumbnail thumb_examples = [ { 'thumb':'small_thumb', 'title':'Basic thumbnail', 'description':"""Here we have a basic thumbnail that uses PIL's thumbnail operation to reduce an image to fit in a defined dimensions.""", 'code' : '''class SmallThumb(DjangoThumbnail): filters = [ThumbnailFilter(120, 100)]''' }, { 'thumb':'square', 'title':'Square', 'description':'As above, but cropped to be square. Since uploaded images can be any old size, they can tend to look ragged when presented in rows. Square thumbs look better in rows, at the expense of a little cropping', 'code':"""class Square(DjangoThumbnail): filters = [ThumbnailFilter(100, 100), SquareFilter()] """ }, { 'thumb':'rounded_corners5', 'title':'5 pixels rounded corner', 'description':"""Rounded corners without CSS3, on a transparent background. What is it with designers and rounded corners anyway?""", 'code':"""class RoundedCorners5(DjangoThumbnail): format = 'png' filters = [ThumbnailFilter(120, 100), RoundedCornerFilter(5)] """, }, { 'thumb':'rounded_corners10', 'title':'10 pixels rounded corner', 'description':'As above, but 10 pixels.', }, { 'thumb':'rounded_corners20', 'title':'20 pixels rounded corner', 'description':'Even more rounded corners', }, { 'thumb':'rounded_corners_edged', 'title':'Rounded corners with a border', 'description':'The rounded corner filter also supports a coloured border', 'code':"""class RoundedCornersEdged(DjangoThumbnail): format = 'png' filters = [ThumbnailFilter(120, 100), RoundedCornerFilter(10, border='#333')]""", }, { 'thumb':'rounded_corners_background', 'title':"Rounded corners on an opaque background", 'description':"Rounded corners on an opaque backround for browsers with poor support for per-pixel transparency — IE6 I'm looking at you!", 'code':"""class RoundedCornersBackground(DjangoThumbnail): format = 'png' filters = [ThumbnailFilter(120, 100), RoundedCornerFilter(10, border='#333'), ResizeCanvasFilter(130, 110, '#fff'), OpaqueFilter('#fff')] """ }, { 'thumb':'rounded_corners_background_gradient', 'title':"Rounded corners on a gadient", 'description':"As above, but on a gradient background. The vertical gradient filter replaces transparent areas with a smooth gradient between two colours.", 'code':"""class RoundedCornersBackgroundGradient(DjangoThumbnail): format = 'png' filters = [ThumbnailFilter(120, 100), RoundedCornerFilter(10, border='#000'), ResizeCanvasFilter(130, 110, '#e2e2ff', background_opacity=0), VerticalGradientFilter('#fff', '#88e')] """ }, {'thumb':'mask_thumb', 'title':'Masked thumbnail', 'description': 'This thumbnail uses MaskFilter which replaces the alpha channel with another image, to create some interesting effects.', 'code':"""class MaskThumb(DjangoThumbnail): format = 'png' filters = [ThumbnailFilter(120, 100), ResizeCanvasFilter(120, 100, '#000', background_opacity=0), MaskFilter(settings.MEDIA_ROOT+'/alpha.png')] """ }, { 'thumb':'gray_thumb', 'title':'Grayscale', 'description':'A grayscale thumb, could be used as a hover state.', 'code':"""class GrayThumb(DjangoThumbnail): filters = [ThumbnailFilter(120, 100), GrayscaleFilter()]""" }, { 'thumb':'faded_thumb', 'title':'50% opacity', 'description':'The OpacityFilter sets the opacity of the thumbnail.', 'code':"""class FadedThumb(DjangoThumbnail): format = 'png' filters = [ThumbnailFilter(120, 100), OpacityFilter(.5)] """ }, { 'thumb':'overlay_thumb', 'title':'Thumbnail with overlay', 'description':"""A thumbnail with an overlayed transparent png. Could be used to indicate online status.""", 'code' : '''class OverlayThumb(DjangoThumbnail): format = 'png' filters = [ThumbnailFilter(120, 100), OverlayFilter(settings.MEDIA_ROOT+'/user.png')]''' }, ]

31.805907

223

0.602282

e1c3efdf6d1bcb608ddb86a4384fd1aed1e4458f

117

py

Python

hello_world.py

michaeljamieson/Python01

96777e5252aaf58e5b424dd5b39186b395d9d859

[ "Apache-2.0" ]

null

hello_world.py

michaeljamieson/Python01

96777e5252aaf58e5b424dd5b39186b395d9d859

[ "Apache-2.0" ]

null

hello_world.py

michaeljamieson/Python01

96777e5252aaf58e5b424dd5b39186b395d9d859

[ "Apache-2.0" ]

null

print ('hello world') print ('hey i did something') print ('what happens if i do a ;'); print ('apparently nothing')

23.4

35

0.683761

e1c41ef577f4a05e6ab921f39322d64330728ff4

1,688

py

Python

start.py

AndrewJanuary/PM-Monitor

43548c805d2ee11ac54f8df874cc06be458454a8

[ "MIT" ]

null

start.py

AndrewJanuary/PM-Monitor

43548c805d2ee11ac54f8df874cc06be458454a8

[ "MIT" ]

6

2021-01-28T22:04:45.000Z

2021-12-20T20:59:03.000Z

start.py

AndrewJanuary/PM-Monitor

43548c805d2ee11ac54f8df874cc06be458454a8

[ "MIT" ]

null

from app.sensor import Sensor from app.uploader import Uploader from app.offline import Offline import time, logging, argparse, sys, random, datetime logging.basicConfig(filename='airquality.log', level=logging.DEBUG, filemode='a', format='%(asctime)s - %(name)s - %(levelname)s - %(message)s') sen = Sensor('PM Sensor 1', '/dev/ttyUSB0', b'\xaa', b'0xAB', b'\xc0')

30.690909

82

0.64455

e1c4600d073fba00b0a31f0113ee9536694f12a6

3,364

py

Python

py_trees_ros/visitors.py

geoc1234/py_trees_ros

65a055624f9261d67f0168ef419aa650302f96d0

[ "BSD-3-Clause" ]

65

2019-05-01T08:21:42.000Z

2022-03-23T15:49:55.000Z

py_trees_ros/visitors.py

geoc1234/py_trees_ros

65a055624f9261d67f0168ef419aa650302f96d0

[ "BSD-3-Clause" ]

62

2019-02-27T14:27:42.000Z

2022-02-08T03:54:30.000Z

py_trees_ros/visitors.py

geoc1234/py_trees_ros

65a055624f9261d67f0168ef419aa650302f96d0

[ "BSD-3-Clause" ]

23

2019-03-03T17:09:59.000Z

2022-01-06T03:07:59.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- # # License: BSD # https://raw.githubusercontent.com/splintered-reality/py_trees_ros/devel/LICENSE # ############################################################################## # Documentation ############################################################################## """ ROS Visitors are entities that can be passed to a ROS tree implementation (e.g. :class:`~py_trees_ros.trees.BehaviourTree`) and used to either visit each and every behaviour in the tree, or visit behaviours as the tree is traversed in an executing tick. At each behaviour, the visitor runs its own method on the behaviour to do as it wishes - logging, introspecting). .. warning:: Visitors should not modify the behaviours they visit. .. seealso:: The base interface and core visitors in :mod:`py_trees.visitors` """ ############################################################################## # Imports ############################################################################## import py_trees.visitors import py_trees_ros_interfaces.msg as py_trees_msgs import rclpy import time from . import conversions ############################################################################## # Visitors ##############################################################################

31.735849

92

0.568668

e1c8c4baec324f5e5f8e13e03541f29a1a32842d

11,394

py

Python

Jarvis/features/Friday_Blueprint.py

faizeraza/Jarvis-Virtual-Assistant-

da88fc0124e6020aff1030317dc3dc918f7aa017

[ "MIT" ]

1

2021-12-14T00:18:10.000Z

Jarvis/features/Friday_Blueprint.py

faizeraza/Jarvis-Virtual-Assistant-

da88fc0124e6020aff1030317dc3dc918f7aa017

[ "MIT" ]

null

Jarvis/features/Friday_Blueprint.py

faizeraza/Jarvis-Virtual-Assistant-

da88fc0124e6020aff1030317dc3dc918f7aa017

[ "MIT" ]

1

2021-12-29T05:01:02.000Z

# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'Friday_Blueprint.ui' # # Created by: PyQt5 UI code generator 5.15.4 # # WARNING: Any manual changes made to this file will be lost when pyuic5 is # run again. Do not edit this file unless you know what you are doing. from PyQt5 import QtCore, QtGui, QtWidgets if __name__ == "__main__": import sys app = QtWidgets.QApplication(sys.argv) MainWindow = QtWidgets.QMainWindow() ui = Ui_MainWindow() ui.setupUi(MainWindow) MainWindow.show() sys.exit(app.exec_())

49.755459

121

0.722924

e1c8d5b0e59bc3cff42a51e6c70986bae9cb73c9

3,201

py

Python

pints/toy/_logistic_model.py

iamleeg/pints

bd1c11472ff3ec0990f3d55f0b2f20d92397926d

[ "BSD-3-Clause" ]

null

pints/toy/_logistic_model.py

iamleeg/pints

bd1c11472ff3ec0990f3d55f0b2f20d92397926d

[ "BSD-3-Clause" ]

null

pints/toy/_logistic_model.py

iamleeg/pints

bd1c11472ff3ec0990f3d55f0b2f20d92397926d

[ "BSD-3-Clause" ]

null

# # Logistic toy model. # # This file is part of PINTS. # Copyright (c) 2017-2019, University of Oxford. # For licensing information, see the LICENSE file distributed with the PINTS # software package. # from __future__ import absolute_import, division from __future__ import print_function, unicode_literals import numpy as np import pints from . import ToyModel

34.419355

79

0.555764

e1cc98556e1e617de9737efeaed139473d56ebaf

426

py

Python

homeworks/vecutil.py

JediKoder/coursera-CodeMatrix

1ac461d22ebaf2777eabdcf31d76d709c33f472a

[ "MIT" ]

3

2018-01-11T07:48:06.000Z

2020-04-27T20:49:02.000Z

homeworks/vecutil.py

JediKoder/coursera-CodeMatrix

1ac461d22ebaf2777eabdcf31d76d709c33f472a

[ "MIT" ]

null

homeworks/vecutil.py

JediKoder/coursera-CodeMatrix

1ac461d22ebaf2777eabdcf31d76d709c33f472a

[ "MIT" ]

1

2021-01-26T07:25:48.000Z

# Copyright 2013 Philip N. Klein from vec import Vec def list2vec(L): """Given a list L of field elements, return a Vec with domain {0...len(L)-1} whose entry i is L[i] >>> list2vec([10, 20, 30]) Vec({0, 1, 2},{0: 10, 1: 20, 2: 30}) """ return Vec(set(range(len(L))), {k:L[k] for k in range(len(L))}) def zero_vec(D): """Returns a zero vector with the given domain """ return Vec(D, {})

25.058824

80

0.577465

e1ccdf7c98befd87dd0fafb60f1dfb6a4f453f5f

59,998

py

Python

squidpy/im/_container.py

Emberwhirl/squidpy

456c49ac9149e16562617a8a4236a9faa2c0480d

[ "BSD-3-Clause" ]

1

2022-02-02T13:41:36.000Z

squidpy/im/_container.py

Emberwhirl/squidpy

456c49ac9149e16562617a8a4236a9faa2c0480d

[ "BSD-3-Clause" ]

null

squidpy/im/_container.py

Emberwhirl/squidpy

456c49ac9149e16562617a8a4236a9faa2c0480d

[ "BSD-3-Clause" ]

null

from __future__ import annotations from copy import copy, deepcopy from types import MappingProxyType from typing import ( Any, Union, Mapping, TypeVar, Callable, Iterable, Iterator, Sequence, TYPE_CHECKING, ) from pathlib import Path from functools import partial from itertools import chain from typing_extensions import Literal import re import validators from scanpy import logging as logg from anndata import AnnData from scanpy.plotting.palettes import default_102 as default_palette from dask import delayed import numpy as np import xarray as xr import dask.array as da from matplotlib.colors import ListedColormap import matplotlib as mpl import matplotlib.pyplot as plt from skimage.util import img_as_float from skimage.transform import rescale from squidpy._docs import d, inject_docs from squidpy._utils import NDArrayA, singledispatchmethod from squidpy.im._io import _lazy_load_image, _infer_dimensions, _assert_dims_present from squidpy.gr._utils import ( _assert_in_range, _assert_positive, _assert_non_negative, _assert_spatial_basis, _assert_non_empty_sequence, ) from squidpy.im._coords import ( CropCoords, CropPadding, _NULL_COORDS, _NULL_PADDING, TupleSerializer, _update_attrs_scale, _update_attrs_coords, ) from squidpy.im._feature_mixin import FeatureMixin from squidpy._constants._constants import InferDimensions from squidpy._constants._pkg_constants import Key FoI_t = Union[int, float] Pathlike_t = Union[str, Path] Arraylike_t = Union[NDArrayA, xr.DataArray] InferDims_t = Union[Literal["default", "prefer_channels", "prefer_z"], Sequence[str]] Input_t = Union[Pathlike_t, Arraylike_t, "ImageContainer"] Interactive = TypeVar("Interactive") # cannot import because of cyclic dependencies _ERROR_NOTIMPLEMENTED_LIBID = f"It seems there are multiple `library_id` in `adata.uns[{Key.uns.spatial!r}]`.\n \ Loading multiple images is not implemented (yet), please specify a `library_id`." __all__ = ["ImageContainer"]

37.173482

120

0.561252

e1cd563f597751eb051e125f9959363e2f96050c

397

py

Python

users/forms.py

kurosh-wss/Personal-Finance-Management

9c7c467b95999974492df19a0f0286809f877c87

[ "MIT" ]

null

users/forms.py

kurosh-wss/Personal-Finance-Management

9c7c467b95999974492df19a0f0286809f877c87

[ "MIT" ]

null

users/forms.py

kurosh-wss/Personal-Finance-Management

9c7c467b95999974492df19a0f0286809f877c87

[ "MIT" ]

null

from django import forms from django.contrib.auth.forms import UserCreationForm from crispy_bootstrap5.bootstrap5 import FloatingField from crispy_forms.layout import Layout from crispy_forms.helper import FormHelper

30.538462

58

0.806045

e1cdbef2e0091f3d12ceeeebb7a6739477ce69ea

1,214

py

Python

tutorzzz_reminder/reminder.py

xiebei1108/tools

8a3141e5d97305f4438e828c62eb7be512767aa9

[ "Apache-2.0" ]

null

tutorzzz_reminder/reminder.py

xiebei1108/tools

8a3141e5d97305f4438e828c62eb7be512767aa9

[ "Apache-2.0" ]

null

tutorzzz_reminder/reminder.py

xiebei1108/tools

8a3141e5d97305f4438e828c62eb7be512767aa9

[ "Apache-2.0" ]

null

import json import requests import config assignedIdList = list()

25.829787

93

0.528007

e1ce81097515faf4dfa5b55142281e9cb5ff0a2c

3,315

py

Python

invoicing/crud/invoice_crud.py

dnegreira/Invoicing

0bc8133e989f095c10151f67482e249416274947

[ "MIT" ]

null

invoicing/crud/invoice_crud.py

dnegreira/Invoicing

0bc8133e989f095c10151f67482e249416274947

[ "MIT" ]

null

invoicing/crud/invoice_crud.py

dnegreira/Invoicing

0bc8133e989f095c10151f67482e249416274947

[ "MIT" ]

null

from invoicing.crud.base_crud import BaseCrud from invoicing.latex.latex_invoice import LatexInvoice from invoicing.models.invoice_model import InvoiceModel from invoicing.repository.invoice_repository import InvoiceRepository from invoicing.repository.job_repository import JobRepository from invoicing.ui.date import Date from invoicing.ui.menu import Menu from invoicing.ui.style import Style from invoicing.value_validation.value_validation import Validation

44.2

103

0.650075

e1cfe37a6f7f6e565038ee9ac5851b8cdd75207b

946

py

Python

ds3225_client.py

kim-tom/dbus_server

b16d1b47dfe4d699ef0177592ba528ba988f17be

[ "MIT" ]

null

ds3225_client.py

kim-tom/dbus_server

b16d1b47dfe4d699ef0177592ba528ba988f17be

[ "MIT" ]

null

ds3225_client.py

kim-tom/dbus_server

b16d1b47dfe4d699ef0177592ba528ba988f17be

[ "MIT" ]

null

from ds3225 import DS3225 import dbus import dbus.mainloop.glib import dbus.service from gi.repository import GObject, GLib UNLOCKED_DEG = 175 dbus.mainloop.glib.DBusGMainLoop(set_as_default=True) BUS_NAME = 'jp.kimura.DS3225Service' OBJECT_PATH = '/jp/kimura/DS3225Server' INTERFACE = 'jp.kimura.DS3225' if __name__ == '__main__': import time ds3225_client = DS3225Client() while True: ds3225_client.set_pos(UNLOCKED_DEG) time.sleep(2) ds3225_client.set_pos(UNLOCKED_DEG-90) time.sleep(2)

27.823529

65

0.701903

e1d05a453d3d0e33ff80baf493eec26c3cbe59f9

437

py

Python

Extra kunskap/Kod/Farmen.py

abbindustrigymnasium/Programmering-1-Slutuppgift

679069ebb632ee59f6b4ee3035c18ae204cde145

[ "Apache-2.0" ]

null

Extra kunskap/Kod/Farmen.py

abbindustrigymnasium/Programmering-1-Slutuppgift

679069ebb632ee59f6b4ee3035c18ae204cde145

[ "Apache-2.0" ]

null

Extra kunskap/Kod/Farmen.py

abbindustrigymnasium/Programmering-1-Slutuppgift

679069ebb632ee59f6b4ee3035c18ae204cde145

[ "Apache-2.0" ]

1

2020-03-09T12:04:31.000Z

import openpyxl wb= openpyxl.load_workbook('Farmen.xlsx') # sheet= wb.active # print(wb.get_sheet_names()) # Deltagar_sheet= wb.get_sheet_by_name('Deltagare') # artists=[{"Namn":sheet.cell(row=i, column=2).value, # "Sng":sheet.cell(row=i, column=3).value, # "Pong":sheet.cell(row=i, column=6).value, # "Rst":sheet.cell(row=i, column=5).value # } for i in range(2,sheet.max_row) ] # print(artists)

33.615385

54

0.649886

e1d12741ffdd5338667faa2590522d4debf232f5

3,437

py

Python

archive/simple_nn.py

petebond/MarketPlaceML

347ea5eab84673b846c85c58ce6c525e3f1dd0ff

[ "CC0-1.0" ]

null

archive/simple_nn.py

petebond/MarketPlaceML

347ea5eab84673b846c85c58ce6c525e3f1dd0ff

[ "CC0-1.0" ]

null

archive/simple_nn.py

petebond/MarketPlaceML

347ea5eab84673b846c85c58ce6c525e3f1dd0ff

[ "CC0-1.0" ]

null

from os import access import torch import torch.nn as nn import torch.optim as optim import torch.nn.functional as F from torch.utils.data import DataLoader from torchvision import datasets, transforms import numpy as np import matplotlib.pyplot as plt # Create fully connected neural network model = CNN(784, 10) x = torch.randn(64, 784) print(model(x).shape) # Set device device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') # Hyperparameters batch_size = 64 learning_rate = 1e-3 num_epochs = 10 input_size = 784 num_classes = 10 # Load data train_dataset = datasets.MNIST(root='dataset/', train=True, download=True, transform=transforms.ToTensor()) train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) test_dataset = datasets.MNIST(root='dataset/', train=False, download=True, transform=transforms.ToTensor()) test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=True) # Initialize model model = NN(input_size=input_size, num_classes=num_classes).to(device) # Define loss and optimizer criterion = nn.CrossEntropyLoss() optimizer = optim.Adam(model.parameters(), lr=learning_rate) # Train model for epoch in range(num_epochs): for batch_idx, (data, target) in enumerate(train_loader): data, target = data.to(device), target.to(device) # Correct shape data = data.reshape(data.shape[0], -1) # Forward pass scores = model(data) loss = criterion(scores, target) # Backward pass optimizer.zero_grad() loss.backward() # Gradient descent step optimizer.step() # Check accuracy check_accuracy(train_loader, model) check_accuracy(test_loader, model)

30.6875

112

0.647949

becbc66bb4d180935eed7f6a49ea9b7ed75ae703

998

py

Python

plot_loss.py

ngachago/tabular_comp

799a1e0dbf7a51bb04454f1f14a57f883dbd2da7

[ "MIT" ]

null

plot_loss.py

ngachago/tabular_comp

799a1e0dbf7a51bb04454f1f14a57f883dbd2da7

[ "MIT" ]

null

plot_loss.py

ngachago/tabular_comp

799a1e0dbf7a51bb04454f1f14a57f883dbd2da7

[ "MIT" ]

null

import matplotlib.pyplot as plt

26.972973

51

0.635271

becc2f00075040cb4b100c7b8d0736d719593862

18,695

py

Python

hotkey.py

RMPiria/painelContreole

bd07def485981456a7e7390f2b18db71740ce8da

[ "Unlicense" ]

null

hotkey.py

RMPiria/painelContreole

bd07def485981456a7e7390f2b18db71740ce8da

[ "Unlicense" ]

null

hotkey.py

RMPiria/painelContreole

bd07def485981456a7e7390f2b18db71740ce8da

[ "Unlicense" ]

null

# -*- coding: utf-8 -*- import os from os.path import dirname, join, normpath import sys from sys import platform from config import config if platform == 'darwin': import objc from AppKit import NSApplication, NSWorkspace, NSBeep, NSSound, NSEvent, NSKeyDown, NSKeyUp, NSFlagsChanged, NSKeyDownMask, NSFlagsChangedMask, NSShiftKeyMask, NSControlKeyMask, NSAlternateKeyMask, NSCommandKeyMask, NSNumericPadKeyMask, NSDeviceIndependentModifierFlagsMask, NSF1FunctionKey, NSF35FunctionKey, NSDeleteFunctionKey, NSClearLineFunctionKey elif platform == 'win32': import atexit import ctypes from ctypes.wintypes import * import threading import winsound RegisterHotKey = ctypes.windll.user32.RegisterHotKey UnregisterHotKey = ctypes.windll.user32.UnregisterHotKey MOD_ALT = 0x0001 MOD_CONTROL = 0x0002 MOD_SHIFT = 0x0004 MOD_WIN = 0x0008 MOD_NOREPEAT = 0x4000 GetMessage = ctypes.windll.user32.GetMessageW TranslateMessage = ctypes.windll.user32.TranslateMessage DispatchMessage = ctypes.windll.user32.DispatchMessageW PostThreadMessage = ctypes.windll.user32.PostThreadMessageW WM_QUIT = 0x0012 WM_HOTKEY = 0x0312 WM_APP = 0x8000 WM_SND_GOOD = WM_APP + 1 WM_SND_BAD = WM_APP + 2 GetKeyState = ctypes.windll.user32.GetKeyState MapVirtualKey = ctypes.windll.user32.MapVirtualKeyW VK_BACK = 0x08 VK_CLEAR = 0x0c VK_RETURN = 0x0d VK_SHIFT = 0x10 VK_CONTROL = 0x11 VK_MENU = 0x12 VK_CAPITAL = 0x14 VK_MODECHANGE= 0x1f VK_ESCAPE = 0x1b VK_SPACE = 0x20 VK_DELETE = 0x2e VK_LWIN = 0x5b VK_RWIN = 0x5c VK_NUMPAD0 = 0x60 VK_DIVIDE = 0x6f VK_F1 = 0x70 VK_F24 = 0x87 VK_OEM_MINUS = 0xbd VK_NUMLOCK = 0x90 VK_SCROLL = 0x91 VK_PROCESSKEY= 0xe5 VK_OEM_CLEAR = 0xfe GetForegroundWindow = ctypes.windll.user32.GetForegroundWindow GetWindowText = ctypes.windll.user32.GetWindowTextW GetWindowText.argtypes = [HWND, LPWSTR, ctypes.c_int] GetWindowTextLength = ctypes.windll.user32.GetWindowTextLengthW SendInput = ctypes.windll.user32.SendInput SendInput.argtypes = [ctypes.c_uint, ctypes.POINTER(INPUT), ctypes.c_int] INPUT_MOUSE = 0 INPUT_KEYBOARD = 1 INPUT_HARDWARE = 2 else: # Linux # singleton hotkeymgr = HotkeyMgr()

44.300948

424

0.589462

becc66adc74c550995995f2d2b08dfaa9d6845d1

3,530

py

Python

Chapter10/ch10_r1_grover_aqua.py

georgekorpas/Quantum-Computing-in-Practice-with-Qiskit-and-IBM-Quantum-Experience

938123d051c5bab72110011b3a05e515bb69ca09

[ "MIT" ]

24

2020-11-21T20:33:51.000Z

2022-03-26T06:41:27.000Z

Chapter10/ch10_r1_grover_aqua.py

videomover/Quantum-Computing-in-Practice-with-Qiskit-and-IBM-Quantum-Experience

938123d051c5bab72110011b3a05e515bb69ca09

[ "MIT" ]

2

2021-02-07T14:32:12.000Z

2022-03-25T07:23:46.000Z

Chapter10/ch10_r1_grover_aqua.py

videomover/Quantum-Computing-in-Practice-with-Qiskit-and-IBM-Quantum-Experience

938123d051c5bab72110011b3a05e515bb69ca09

[ "MIT" ]

16

2020-11-03T07:49:11.000Z

2022-03-26T06:41:29.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created Nov 2020 @author: hassi """ from qiskit import Aer, IBMQ # Do the necessary import for our program from qiskit.aqua.algorithms import Grover from qiskit.aqua.components.oracles import LogicalExpressionOracle, TruthTableOracle # Import basic plot tools from qiskit.tools.visualization import plot_histogram from IPython.core.display import display global oracle_method, oracle_type # Main loop if __name__ == '__main__': main()

34.950495

120

0.703116

becc7d9f66f89922de66fb46f1bec24640debbb3

1,428

py

Python

setup_pre-commit.py

fierte-product-development/Setups

d6151888ecc82a94e894b5d926c85eb193a5b97c

[ "MIT" ]

1

2021-07-06T09:26:48.000Z

setup_pre-commit.py

fierte-product-development/Setups

d6151888ecc82a94e894b5d926c85eb193a5b97c

[ "MIT" ]

3

2022-01-26T05:29:04.000Z

2022-02-16T10:16:02.000Z

setup_pre-commit.py

fierte-product-development/Setups

d6151888ecc82a94e894b5d926c85eb193a5b97c

[ "MIT" ]

1

2020-11-11T01:23:01.000Z

import sys import os import subprocess from subprocess import PIPE, STDOUT from pathlib import Path proc_arg = { 'shell': True, 'stdout': PIPE, 'text': True } if __name__ == "__main__": main()

21.969231

65

0.579832

bece2e0f8b2de4615e59523ec76f70e91828684b

889

py

Python

5-buscar.py

gustavodp22/TP_DE_-CRUD-create-read-update-delete-

8edfba57cbbad37f8fb1af2d42d1d601301e8dd6

[ "MIT" ]

null

5-buscar.py

gustavodp22/TP_DE_-CRUD-create-read-update-delete-

8edfba57cbbad37f8fb1af2d42d1d601301e8dd6

[ "MIT" ]

null

5-buscar.py

gustavodp22/TP_DE_-CRUD-create-read-update-delete-

8edfba57cbbad37f8fb1af2d42d1d601301e8dd6

[ "MIT" ]

null

""" CRUD de SQLite3 con Python 3 """ import sqlite3 try: bd = sqlite3.connect("libros.db") cursor = bd.cursor() busqueda = input("Escribe tu bsqueda: ") if not busqueda: print("Bsqueda invlida") exit() sentencia = "SELECT * FROM libros WHERE titulo LIKE ?;" cursor.execute(sentencia, [ "%{}%".format(busqueda) ]) libros = cursor.fetchall() print("+{:-<20}+{:-<20}+{:-<10}+{:-<50}+".format("", "", "", "")) print("|{:^20}|{:^20}|{:^10}|{:^50}|".format("Autor", "Gnero", "Precio", "Ttulo")) print("+{:-<20}+{:-<20}+{:-<10}+{:-<50}+".format("", "", "", "")) for autor, genero, precio, titulo in libros: print("|{:^20}|{:^20}|{:^10}|{:^50}|".format(autor, genero, precio, titulo)) print("+{:-<20}+{:-<20}+{:-<10}+{:-<50}+".format("", "", "", "")) except sqlite3.OperationalError as error: print("Error al abrir:", error)

27.78125

86

0.533183

becf153d29dc0bf9abcbf500a0d578ce48e9150a

4,686

py

Python

tests/advanced_tests/regressors.py

amlanbanerjee/auto_ml

db8e1d2cfa93f13a21e55739acfc8d99837e91b0

[ "MIT" ]

1,671

2016-08-09T04:44:48.000Z

2022-03-27T01:29:23.000Z

tests/advanced_tests/regressors.py

amlanbanerjee/auto_ml

db8e1d2cfa93f13a21e55739acfc8d99837e91b0

[ "MIT" ]

428

2016-08-08T00:13:04.000Z

2022-01-19T10:09:05.000Z

tests/advanced_tests/regressors.py

amlanbanerjee/auto_ml

db8e1d2cfa93f13a21e55739acfc8d99837e91b0

[ "MIT" ]

334

2016-08-29T12:34:18.000Z

2022-01-31T09:14:30.000Z

import datetime import os import random import sys sys.path = [os.path.abspath(os.path.dirname(__file__))] + sys.path from auto_ml import Predictor from auto_ml.utils_models import load_ml_model import dill from nose.tools import assert_equal, assert_not_equal, with_setup import numpy as np from sklearn.model_selection import train_test_split import utils_testing as utils

31.877551

146

0.712761

bed0237d9ebc522d5a4384033d2b57c729cc7ede

39

py

Python

__init__.py

amueller/information-theoretic-mst

178fd4396bc9a9a499ec3d18d5047b320a5c32f2

[ "Unlicense" ]

20

2016-05-03T13:29:09.000Z

2021-10-06T20:41:36.000Z

__init__.py

amueller/information-theoretic-mst

178fd4396bc9a9a499ec3d18d5047b320a5c32f2

[ "Unlicense" ]

1

2018-04-21T15:32:07.000Z

2020-05-19T00:28:52.000Z

__init__.py

amueller/information-theoretic-mst

178fd4396bc9a9a499ec3d18d5047b320a5c32f2

[ "Unlicense" ]

5

2015-04-21T00:27:49.000Z

2019-02-23T20:46:33.000Z

from itm import ITM __all__ = ['ITM']

9.75

19

0.666667

bed3d451e4686403bc8880395163b3b1b1569208

2,827

py

Python

scripts/left_right_hemisphere_data/hemisphere_asymmetry.py

mwinding/connectome_analysis

dbc747290891805863c9481921d8080dc2043d21

[ "MIT" ]

1

2021-06-10T05:48:16.000Z

left_right_hemisphere_data/hemisphere_asymmetry.py

mwinding/connectome_tools

0392f6b1e924194299ea7760d8386eb01f3371a3

[ "MIT" ]

2

2022-01-21T11:48:45.000Z

scripts/left_right_hemisphere_data/hemisphere_asymmetry.py

mwinding/connectome_analysis

dbc747290891805863c9481921d8080dc2043d21

[ "MIT" ]

1

2022-02-02T15:39:52.000Z

import pandas as pd import numpy as np import csv # import synapses divided across hemispheres hemisphere_data = pd.read_csv('left_right_hemisphere_data/brain_hemisphere_membership.csv', header = 0) #print(hemisphere_data) # import pair list CSV, manually generated #pairs = pd.read_csv('data/bp-pairs-2020-01-28.csv', header = 0) # import skids of neurons that cross commissure commissure_neurons = pd.read_json('left_right_hemisphere_data/cross_commissure-2020-3-2.json')['skeleton_id'].values #print(type(commissure_neurons[0])) #print(type(hemisphere_data['skeleton'][0])) ipsi_neurons = np.setdiff1d(hemisphere_data['skeleton'], commissure_neurons) ipsi_neurons_bool = pd.Series(hemisphere_data['skeleton'].values).isin(ipsi_neurons) contra_neurons_bool = ~pd.Series(hemisphere_data['skeleton'].values).isin(ipsi_neurons) print("IPSI") print("Postsynaptic Sites") print(sum(hemisphere_data[ipsi_neurons_bool]['n_inputs_left'].values)) print(sum(hemisphere_data[ipsi_neurons_bool]['n_inputs_right'].values)) print(sum(hemisphere_data[ipsi_neurons_bool]['n_inputs_left'].values)/sum(hemisphere_data[ipsi_neurons_bool]['n_inputs_right'].values)) print("") print("Presynaptic Sites") print(sum(hemisphere_data[ipsi_neurons_bool]['n_outputs_left'].values)) print(sum(hemisphere_data[ipsi_neurons_bool]['n_outputs_right'].values)) print(sum(hemisphere_data[ipsi_neurons_bool]['n_outputs_left'].values)/sum(hemisphere_data[ipsi_neurons_bool]['n_outputs_right'].values)) print("") print("Treenodes") print(sum(hemisphere_data[ipsi_neurons_bool]['n_treenodes_left'].values)) print(sum(hemisphere_data[ipsi_neurons_bool]['n_treenodes_right'].values)) print(sum(hemisphere_data[ipsi_neurons_bool]['n_treenodes_left'].values)/sum(hemisphere_data[ipsi_neurons_bool]['n_treenodes_right'].values)) print("") print("") print("") print("CONTRA") print("Postsynaptic Sites") print(sum(hemisphere_data[contra_neurons_bool]['n_inputs_left'].values)) print(sum(hemisphere_data[contra_neurons_bool]['n_inputs_right'].values)) print(sum(hemisphere_data[contra_neurons_bool]['n_inputs_left'].values)/sum(hemisphere_data[contra_neurons_bool]['n_inputs_right'].values)) print("") print("Presynaptic Sites") print(sum(hemisphere_data[contra_neurons_bool]['n_outputs_left'].values)) print(sum(hemisphere_data[contra_neurons_bool]['n_outputs_right'].values)) print(sum(hemisphere_data[contra_neurons_bool]['n_outputs_left'].values)/sum(hemisphere_data[contra_neurons_bool]['n_outputs_right'].values)) print("") print("Treenodes") print(sum(hemisphere_data[contra_neurons_bool]['n_treenodes_left'].values)) print(sum(hemisphere_data[contra_neurons_bool]['n_treenodes_right'].values)) print(sum(hemisphere_data[contra_neurons_bool]['n_treenodes_left'].values)/sum(hemisphere_data[contra_neurons_bool]['n_treenodes_right'].values)) print("")

45.596774

145

0.812168

bed4073b9e79a28ea38d1cc06f6e14cb5d4efcb7

777

py

Python

__determineTripplesSumToZeroFromList.py

simdevex/01.Basics

cf4f372384e66f4b26e4887d2f5d815a1f8e929c

[ "MIT" ]

null

__determineTripplesSumToZeroFromList.py

simdevex/01.Basics

cf4f372384e66f4b26e4887d2f5d815a1f8e929c

[ "MIT" ]

null

__determineTripplesSumToZeroFromList.py

simdevex/01.Basics

cf4f372384e66f4b26e4887d2f5d815a1f8e929c

[ "MIT" ]

null

''' Python program to determine which triples sum to zero from a given list of lists. Input: [[1343532, -2920635, 332], [-27, 18, 9], [4, 0, -4], [2, 2, 2], [-20, 16, 4]] Output: [False, True, True, False, True] Input: [[1, 2, -3], [-4, 0, 4], [0, 1, -5], [1, 1, 1], [-2, 4, -1]] Output: [True, True, False, False, False] ''' #License: https://bit.ly/3oLErEI nums = [[1343532, -2920635, 332], [-27, 18, 9], [4, 0, -4], [2, 2, 2], [-20, 16, 4]] print("Original list of lists:",nums) print("Determine which triples sum to zero:") print(test(nums)) nums = [[1, 2, -3], [-4, 0, 4], [0, 1, -5], [1, 1, 1], [-2, 4, -1]] print("\nOriginal list of lists:",nums) print("Determine which triples sum to zero:") print(test(nums))

32.375

84

0.574003

bed6c276e3757d89c0d4a20b188e77bced930a94

701

py

Python

fastNLP/modules/encoder/lstm.py

h00Jiang/fastNLP

79ddb469d81946c87a3d066122a8a3aba6e40f3a

[ "Apache-2.0" ]

null

fastNLP/modules/encoder/lstm.py

h00Jiang/fastNLP

79ddb469d81946c87a3d066122a8a3aba6e40f3a

[ "Apache-2.0" ]

null

fastNLP/modules/encoder/lstm.py

h00Jiang/fastNLP

79ddb469d81946c87a3d066122a8a3aba6e40f3a

[ "Apache-2.0" ]

null

import torch.nn as nn

29.208333

98

0.636234

bed723c002fdd1ab37526c62f785025bbbd1fbd1

838

py

Python

geoLocApp/signals.py

KKWaxy/geoLoc

23e33b9fd7cb3b1031bd11475612dcc324680975

[ "Apache-2.0" ]

null

geoLocApp/signals.py

KKWaxy/geoLoc

23e33b9fd7cb3b1031bd11475612dcc324680975

[ "Apache-2.0" ]

null

geoLocApp/signals.py

KKWaxy/geoLoc

23e33b9fd7cb3b1031bd11475612dcc324680975

[ "Apache-2.0" ]

null

from django.db.models.signals import pre_save,post_save from django.dispatch import receiver import geoLocApp.models import geoLocApp.distance # @receiver(post_save,sender=geoLocApp.models.Position,dispatch_uid="only_before_registered") # def setDistance(sender, **kwargs): # position = kwargs["instance"] # coordonnees = position.coordonnees.all() # print(coordonnees) # for coordonnee in coordonnees: # coordonnee.distance = geoLocApp.distance.distance(coordonnee.latitude,position.latitude,coordonnee.longitude,position.longitude) # print(coordonnee.distance) # @receiver(post_save,sender=geoLocApp.models.Position,dispatch_uid="new_position_added") # def new_position(sender,**kwargs): # if kwargs['created']==True: # return ['intance'] # else: # return 0

39.904762

139

0.72673

bed7a7f211ac4ca2170057d5dae27d3248efc33a

2,198

py

Python

src/main/python/shabda/data/iterators/internal/data_iterator_base.py

dhiraa/sabdha

f428418962dcc76f49e0a451ffc0545fda9b6b59

[ "Apache-2.0" ]

4

2018-10-26T07:00:34.000Z

2020-10-07T01:03:08.000Z

src/main/python/shabda/data/iterators/internal/data_iterator_base.py

dhiraa/sabdha

f428418962dcc76f49e0a451ffc0545fda9b6b59

[ "Apache-2.0" ]

null

src/main/python/shabda/data/iterators/internal/data_iterator_base.py

dhiraa/sabdha

f428418962dcc76f49e0a451ffc0545fda9b6b59

[ "Apache-2.0" ]

1

2018-10-26T07:00:38.000Z

# Copyright 2018 The Shabda Authors. 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. """ Iterator that creates features for LSTM based models """ from __future__ import absolute_import from __future__ import division from __future__ import print_function from shabda.hyperparams.hyperparams import HParams

28.179487

83

0.670155

bed7c4898d58c738f63aa212ff888514735a6694

441

py

Python

app/filters.py

dakhnovskaya/organization

72fb6f0a2daf03e7f7ce4dfb2cb3c3eaf1c40851

[ "Apache-2.0" ]

null

app/filters.py

dakhnovskaya/organization

72fb6f0a2daf03e7f7ce4dfb2cb3c3eaf1c40851

[ "Apache-2.0" ]

null

app/filters.py

dakhnovskaya/organization

72fb6f0a2daf03e7f7ce4dfb2cb3c3eaf1c40851

[ "Apache-2.0" ]

null

import django_filters from app.models import Company

33.923077

102

0.750567

bed83cf2a356ae3011eb19bade5063e46f89b28c

6,598

py

Python

reaction/rpc/rabbitmq.py

Inkln/reaction

7a57bd642ac3db15012717130a5f2655c3b7b177

[ "Apache-2.0" ]

73

2019-10-01T15:59:57.000Z

2021-06-29T11:59:16.000Z

reaction/rpc/rabbitmq.py

Inkln/reaction

7a57bd642ac3db15012717130a5f2655c3b7b177

[ "Apache-2.0" ]

2

2020-06-25T10:26:38.000Z

2022-02-21T06:20:47.000Z

reaction/rpc/rabbitmq.py

Inkln/reaction

7a57bd642ac3db15012717130a5f2655c3b7b177

[ "Apache-2.0" ]

7

2019-10-08T05:46:22.000Z

2020-07-27T12:58:18.000Z

from typing import List import asyncio import inspect import logging import uuid import aio_pika import aio_pika.exceptions from .base import BaseRPC from .common import RPCError, RPCHandler, RPCRequest, RPCResponse

34.910053

78

0.543346

bed8ffa1e73ffa405bfc1005a04f4f722ab41812

2,069

py

Python

api/migrations/0005_auto_20200906_1951.py

sh2MAN/yamdb_final

17f84bacd832237d88d3389605cf2acdf2a590f5

[ "BSD-3-Clause" ]

null

api/migrations/0005_auto_20200906_1951.py

sh2MAN/yamdb_final

17f84bacd832237d88d3389605cf2acdf2a590f5

[ "BSD-3-Clause" ]

null

api/migrations/0005_auto_20200906_1951.py

sh2MAN/yamdb_final

17f84bacd832237d88d3389605cf2acdf2a590f5

[ "BSD-3-Clause" ]

12

2021-02-11T16:39:00.000Z

2022-03-30T19:18:24.000Z

# Generated by Django 3.0.5 on 2020-09-06 19:51 from django.db import migrations, models import django.db.models.deletion

34.483333

177

0.585307

bed9a7c33d1cf837bf05eedf9e2389f71612ac64

1,104

py

Python

user_activity/models.py

adithya-bhat-b/user-activity

d2577bbb295ac381e08a31e296e3d681da7ab036

[ "MIT" ]

null

user_activity/models.py

adithya-bhat-b/user-activity

d2577bbb295ac381e08a31e296e3d681da7ab036

[ "MIT" ]

3

2021-04-08T22:04:18.000Z

2021-06-09T19:14:16.000Z

user_activity/models.py

adithya-bhat-b/user-activity

d2577bbb295ac381e08a31e296e3d681da7ab036

[ "MIT" ]

null

import pytz from django.db import models # Create your models here. def _get_time_zones(): """ Function to get all the timezones """ timezone_choices = [(tz, tz) for tz in pytz.all_timezones] return timezone_choices # Model for user # Model for user

25.674419

74

0.646739

bedad5c3db81102c82212833e871a369686befc7

1,992

py

Python

Learning/python_data_analysis1.py

VictoriaGuXY/MCO-Menu-Checker-Online

706e2e1bf7395cc344f382ea2ac53d964d459f86

[ "MIT" ]

null

Learning/python_data_analysis1.py

VictoriaGuXY/MCO-Menu-Checker-Online

706e2e1bf7395cc344f382ea2ac53d964d459f86

[ "MIT" ]

null

Learning/python_data_analysis1.py

VictoriaGuXY/MCO-Menu-Checker-Online

706e2e1bf7395cc344f382ea2ac53d964d459f86

[ "MIT" ]

null

import pandas as pd # pandas provides us lots of data frame and functions that we can quickly use # to analyze data. """ output """ # This file contains notes of basic data analyzing strategies using Python. # I will introduce two ways to read a csv file: pathway and URL. # Also, I will introduce how to output data and save them into a csv file. # ------------------------------------------------------------------------------ # read a csv file using the pathway # This is based on the pathway that we saved the file. # In python, to represent a pathway, we should either use / or //. df = pd.read_csv('E:\\tips.csv') # ------------------------------------------------------------------------------ # read data online using a URL data_url = "https://raw.githubusercontent.com/mwaskom/seaborn-data/master/tips.csv" df = pd.read_csv(data_url) # same output for the above two methods # output is shown below """ total_bill tip sex smoker day time size 0 16.99 1.01 Female No Sun Dinner 2 1 10.34 1.66 Male No Sun Dinner 3 2 21.01 3.50 Male No Sun Dinner 3 3 23.68 3.31 Male No Sun Dinner 2 4 24.59 3.61 Female No Sun Dinner 4 5 25.29 4.71 Male No Sun Dinner 4 .. ... ... ... ... ... ... ... 240 27.18 2.00 Female Yes Sat Dinner 2 241 22.67 2.00 Male Yes Sat Dinner 2 242 17.82 1.75 Male No Sat Dinner 2 243 18.78 3.00 Female No Thur Dinner 2 [244 rows x 7 columns] """ # ------------------------------------------------------------------------------ # output data and save them into a csv file df.to_csv('E:\\demo.csv', encoding='utf-8', index=False) # When index = False, when output as a csv file, the name of each line will be # removed. # If we contain some special characters in data, encoding will treat it as # utf-8.

36.888889

84

0.533133

bedb078b9701b035a6b7ffcad6706445ac8dade2

768

py

Python

InvoiceItemModel.py

kevinyjiang/cpa-generator

c21cd1f898cf068daff8a6937d6cefc591b16ab1

[ "MIT" ]

2

2018-09-26T19:18:45.000Z

2018-11-14T00:38:28.000Z

InvoiceItemModel.py

kevinyjiang/cpa-generator

c21cd1f898cf068daff8a6937d6cefc591b16ab1

[ "MIT" ]

null

InvoiceItemModel.py

kevinyjiang/cpa-generator

c21cd1f898cf068daff8a6937d6cefc591b16ab1

[ "MIT" ]

null

import config

30.72

68

0.453125

bedb1dc2f3fdaeceb37c80ae1a87e69944c3c668

1,725

py

Python

lambda/populateDB/lambda_function.py

aws-samples/amazon-connect-dynamic-ivr-menus

911f5d04cf78d3097cfe7e169bd0062459d61ec4

[ "MIT-0" ]

4

2021-06-24T14:42:42.000Z

2021-12-13T07:08:48.000Z

lambda/populateDB/lambda_function.py

aws-samples/amazon-connect-dynamic-ivr-menus

911f5d04cf78d3097cfe7e169bd0062459d61ec4

[ "MIT-0" ]

1

2021-12-13T06:53:39.000Z

lambda/populateDB/lambda_function.py

aws-samples/amazon-connect-dynamic-ivr-menus

911f5d04cf78d3097cfe7e169bd0062459d61ec4

[ "MIT-0" ]

2

2021-06-10T18:54:03.000Z

2021-12-13T08:07:05.000Z

import json import boto3 import os

28.278689

176

0.584348

bedcd44ac29b275e927dc09d0e22f32d04f7138a

59

py

Python

pyds/heap/__init__.py

nitinkatyal1314/data-structures

2e7f5b99a6b09cea48f729682d9431b72afbfd7a

[ "MIT" ]

6

2021-04-06T18:14:59.000Z

2021-07-18T03:26:03.000Z

pyds/heap/__init__.py

nitinkatyal1314/data-structures

2e7f5b99a6b09cea48f729682d9431b72afbfd7a

[ "MIT" ]

null

pyds/heap/__init__.py

nitinkatyal1314/data-structures

2e7f5b99a6b09cea48f729682d9431b72afbfd7a

[ "MIT" ]

null

from .api import HeapAPI as Heap from .api import HeapType

19.666667

32

0.79661

bedeaa04e3aa523fae916c1f3ad83805bf94106f

2,849

py

Python

examples/s5b_transfer/s5b_receiver.py

isabella232/slixmpp

e15e6735f1dbfc66a5d43efe9fa9e7f5c9d1610a

[ "BSD-3-Clause" ]

null

examples/s5b_transfer/s5b_receiver.py

isabella232/slixmpp

e15e6735f1dbfc66a5d43efe9fa9e7f5c9d1610a

[ "BSD-3-Clause" ]

1

2021-02-24T07:58:40.000Z

examples/s5b_transfer/s5b_receiver.py

isabella232/slixmpp

e15e6735f1dbfc66a5d43efe9fa9e7f5c9d1610a

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Slixmpp: The Slick XMPP Library Copyright (C) 2015 Emmanuel Gil Peyrot This file is part of Slixmpp. See the file LICENSE for copying permission. """ import asyncio import logging from getpass import getpass from argparse import ArgumentParser import slixmpp if __name__ == '__main__': # Setup the command line arguments. parser = ArgumentParser() # Output verbosity options. parser.add_argument("-q", "--quiet", help="set logging to ERROR", action="store_const", dest="loglevel", const=logging.ERROR, default=logging.INFO) parser.add_argument("-d", "--debug", help="set logging to DEBUG", action="store_const", dest="loglevel", const=logging.DEBUG, default=logging.INFO) # JID and password options. parser.add_argument("-j", "--jid", dest="jid", help="JID to use") parser.add_argument("-p", "--password", dest="password", help="password to use") parser.add_argument("-o", "--out", dest="filename", help="file to save to") args = parser.parse_args() # Setup logging. logging.basicConfig(level=args.loglevel, format='%(levelname)-8s %(message)s') if args.jid is None: args.jid = input("Username: ") if args.password is None: args.password = getpass("Password: ") if args.filename is None: args.filename = input("File path: ") # Setup the S5BReceiver and register plugins. Note that while plugins may # have interdependencies, the order in which you register them does # not matter. xmpp = S5BReceiver(args.jid, args.password, args.filename) xmpp.register_plugin('xep_0030') # Service Discovery xmpp.register_plugin('xep_0065', { 'auto_accept': True }) # SOCKS5 Bytestreams # Connect to the XMPP server and start processing XMPP stanzas. xmpp.connect() xmpp.process(forever=False)

31.307692

77

0.630046

bedfb697a1311d179da9b0d371384f0a26973131

2,170

py

Python

api/app/routers/weather_models.py

bcgov/wps

71df0de72de9cd656dc9ebf8461ffe47cfb155f6

[ "Apache-2.0" ]

19

2020-01-31T21:51:31.000Z

2022-01-07T14:40:03.000Z

api/app/routers/weather_models.py

bcgov/wps

71df0de72de9cd656dc9ebf8461ffe47cfb155f6

[ "Apache-2.0" ]

1,680

2020-01-24T23:25:08.000Z

2022-03-31T23:50:27.000Z

api/app/routers/weather_models.py

bcgov/wps

71df0de72de9cd656dc9ebf8461ffe47cfb155f6

[ "Apache-2.0" ]

6

2020-04-28T22:41:08.000Z

2021-05-05T18:16:06.000Z

""" Routers for weather_models. """ import logging from fastapi import APIRouter, Depends from app.auth import authentication_required, audit from app.weather_models import ModelEnum from app.schemas.weather_models import ( WeatherModelPredictionSummaryResponse, WeatherStationsModelRunsPredictionsResponse) from app.schemas.shared import WeatherDataRequest from app.weather_models.fetch.summaries import fetch_model_prediction_summaries from app.weather_models.fetch.predictions import ( fetch_model_run_predictions_by_station_code) logger = logging.getLogger(__name__) router = APIRouter( prefix="/weather_models", dependencies=[Depends(audit), Depends(authentication_required)], )

38.070175

109

0.765438

bee066a8fc595636f1ed42106327e650d743c5d7

1,529

py

Python

155.min-stack.py

elfgzp/leetCode

964c6574d310a9a6c486bf638487fd2f72b83b3f

[ "MIT" ]

3

2019-04-12T06:22:56.000Z

2019-05-04T04:25:01.000Z

155.min-stack.py

elfgzp/Leetcode

964c6574d310a9a6c486bf638487fd2f72b83b3f

[ "MIT" ]

null

155.min-stack.py

elfgzp/Leetcode

964c6574d310a9a6c486bf638487fd2f72b83b3f

[ "MIT" ]

null

# # @lc app=leetcode.cn id=155 lang=python3 # # [155] # # https://leetcode-cn.com/problems/min-stack/description/ # # algorithms # Easy (47.45%) # Total Accepted: 19.4K # Total Submissions: 40.3K # Testcase Example: '["MinStack","push","push","push","getMin","pop","top","getMin"]\n[[],[-2],[0],[-3],[],[],[],[]]' # # pushpoptop # # # push(x)-- x # pop()-- # top()-- # getMin() -- # # # : # # MinStack minStack = new MinStack(); # minStack.push(-2); # minStack.push(0); # minStack.push(-3); # minStack.getMin(); --> -3. # minStack.pop(); # minStack.top(); --> 0. # minStack.getMin(); --> -2. # # # # Your MinStack object will be instantiated and called as such: # obj = MinStack() # obj.push(x) # obj.pop() # param_3 = obj.top() # param_4 = obj.getMin()

19.602564

118

0.530412

bee082fd43d018efe615e1efde05a3a482204b84

48,845

py

Python

demisto_client/demisto_api/models/investigation_playbook_task.py

guytest/demisto-py

8ca4f56a6177668151b5656cbe675a377003c0e9

[ "Apache-2.0" ]

1

2020-04-08T14:36:06.000Z

demisto_client/demisto_api/models/investigation_playbook_task.py

guytest/demisto-py

8ca4f56a6177668151b5656cbe675a377003c0e9

[ "Apache-2.0" ]

null

demisto_client/demisto_api/models/investigation_playbook_task.py

guytest/demisto-py

8ca4f56a6177668151b5656cbe675a377003c0e9

[ "Apache-2.0" ]

null

# coding: utf-8 """ Demisto API This is the public REST API to integrate with the demisto server. HTTP request can be sent using any HTTP-client. For an example dedicated client take a look at: https://github.com/demisto/demisto-py. Requests must include API-key that can be generated in the Demisto web client under 'Settings' -> 'Integrations' -> 'API keys' Optimistic Locking and Versioning\\: When using Demisto REST API, you will need to make sure to work on the latest version of the item (incident, entry, etc.), otherwise, you will get a DB version error (which not allow you to override a newer item). In addition, you can pass 'version\\: -1' to force data override (make sure that other users data might be lost). Assume that Alice and Bob both read the same data from Demisto server, then they both changed the data, and then both tried to write the new versions back to the server. Whose changes should be saved? Alices? Bobs? To solve this, each data item in Demisto has a numeric incremental version. If Alice saved an item with version 4 and Bob trying to save the same item with version 3, Demisto will rollback Bob request and returns a DB version conflict error. Bob will need to get the latest item and work on it so Alice work will not get lost. Example request using 'curl'\\: ``` curl 'https://hostname:443/incidents/search' -H 'content-type: application/json' -H 'accept: application/json' -H 'Authorization: <API Key goes here>' --data-binary '{\"filter\":{\"query\":\"-status:closed -category:job\",\"period\":{\"by\":\"day\",\"fromValue\":7}}}' --compressed ``` # noqa: E501 OpenAPI spec version: 2.0.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ import pprint import re # noqa: F401 import six from demisto_client.demisto_api.models.advance_arg import AdvanceArg # noqa: F401,E501 from demisto_client.demisto_api.models.data_collection_form import DataCollectionForm # noqa: F401,E501 from demisto_client.demisto_api.models.evidence_data import EvidenceData # noqa: F401,E501 from demisto_client.demisto_api.models.field_mapping import FieldMapping # noqa: F401,E501 from demisto_client.demisto_api.models.inv_playbook_task_complete_data import InvPlaybookTaskCompleteData # noqa: F401,E501 # from demisto_client.demisto_api.models.investigation_playbook import InvestigationPlaybook # noqa: F401,E501 from demisto_client.demisto_api.models.notifiable_item import NotifiableItem # noqa: F401,E501 from demisto_client.demisto_api.models.reputation_calc_alg import ReputationCalcAlg # noqa: F401,E501 from demisto_client.demisto_api.models.sla import SLA # noqa: F401,E501 from demisto_client.demisto_api.models.task import Task # noqa: F401,E501 from demisto_client.demisto_api.models.task_condition import TaskCondition # noqa: F401,E501 from demisto_client.demisto_api.models.task_loop import TaskLoop # noqa: F401,E501 from demisto_client.demisto_api.models.task_state import TaskState # noqa: F401,E501 from demisto_client.demisto_api.models.task_type import TaskType # noqa: F401,E501 from demisto_client.demisto_api.models.task_view import TaskView # noqa: F401,E501 from demisto_client.demisto_api.models.timer_trigger import TimerTrigger # noqa: F401,E501 def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, InvestigationPlaybookTask): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

32.498337

1,584

0.649381

bee216da141df68c9f7b41ae5761fcf6bc3e34f4

36,274

py

Python

make.py

beefoo/subway-inequality

a93bdbf81ea3753b0d2ec85d028f816adcc2f6f9

[ "MIT" ]

1

2021-03-08T01:44:10.000Z

make.py

beefoo/subway-inequality

a93bdbf81ea3753b0d2ec85d028f816adcc2f6f9

[ "MIT" ]

null

make.py

beefoo/subway-inequality

a93bdbf81ea3753b0d2ec85d028f816adcc2f6f9

[ "MIT" ]

1

2021-11-02T21:55:39.000Z

# -*- coding: utf-8 -*- # python3 make.py -loc "data/lines/1.csv" -width 3840 -height 2160 -overwrite # python3 make.py -loc "data/lines/1.csv" -width 3840 -height 2160 -rtl -overwrite # python3 combine.py # python3 make.py -data "data/lines/A_LEF.csv" -width 3840 -height 2160 -loc "data/lines/C.csv" -img "img/A.png" -sw 0.1405 -tw 0.145 -overwrite # python3 make.py -data "data/lines/A_LEF.csv" -width 3840 -height 2160 -loc "data/lines/C.csv" -img "img/A.png" -sw 0.1405 -tw 0.145 -rtl -overwrite # python3 combine.py -in "output/subway_line_A.mp4,output/subway_line_A_rtl.mp4" -out "output/subway_line_A_loop.mp4" # python3 make.py -data "data/lines/7.csv" -width 3840 -height 2160 -img "img/7.png" -sw 0.11725 -tw 0.135625 -reverse -overwrite # python3 make.py -data "data/lines/7.csv" -width 3840 -height 2160 -img "img/7.png" -sw 0.11725 -tw 0.135625 -reverse -rtl -overwrite # python3 combine.py -in "output/subway_line_7.mp4,output/subway_line_7_rtl.mp4" -out "output/subway_line_7_loop.mp4" import argparse import numpy as np import os from pprint import pprint import sys from lib import * # input parser = argparse.ArgumentParser() parser.add_argument('-data', dest="DATA_FILE", default="data/lines/2.csv", help="Input csv file with preprocessed data") parser.add_argument('-loc', dest="DATA_LOCAL_FILE", default="", help="Input csv file with preprocessed data of a local train that should 'fill in' stations in-between express trains") parser.add_argument('-img', dest="IMAGE_FILE", default="img/2.png", help="Subway bullet image") parser.add_argument('-instruments', dest="INSTRUMENTS_FILE", default="data/instruments.csv", help="Input csv file with instruments config") parser.add_argument('-dir', dest="MEDIA_DIRECTORY", default="audio/", help="Input media directory") parser.add_argument('-width', dest="WIDTH", default=1920, type=int, help="Output video width") parser.add_argument('-height', dest="HEIGHT", default=1080, type=int, help="Output video height") parser.add_argument('-pad0', dest="PAD_START", default=2000, type=int, help="Pad start in ms") parser.add_argument('-pad1', dest="PAD_END", default=2000, type=int, help="Pad end in ms") parser.add_argument('-fps', dest="FPS", default=30, type=int, help="Output video frames per second") parser.add_argument('-outframe', dest="OUTPUT_FRAME", default="tmp/line_%s/frame.%s.png", help="Output frames pattern") parser.add_argument('-aout', dest="AUDIO_OUTPUT_FILE", default="output/subway_line_%s.mp3", help="Output audio file") parser.add_argument('-dout', dest="DATA_OUTPUT_FILE", default="output/subway_line_%s.csv", help="Output data file") parser.add_argument('-out', dest="OUTPUT_FILE", default="output/subway_line_%s.mp4", help="Output media file") parser.add_argument('-overwrite', dest="OVERWRITE", action="store_true", help="Overwrite existing files?") parser.add_argument('-probe', dest="PROBE", action="store_true", help="Just view statistics?") parser.add_argument('-reverse', dest="REVERSE", action="store_true", help="Reverse the line?") parser.add_argument('-rtl', dest="RIGHT_TO_LEFT", action="store_true", help="Play from right to left?") parser.add_argument('-ao', dest="AUDIO_ONLY", action="store_true", help="Only output audio?") parser.add_argument('-vo', dest="VIDEO_ONLY", action="store_true", help="Only output video?") parser.add_argument('-do', dest="DATA_ONLY", action="store_true", help="Only output data?") parser.add_argument('-viz', dest="VISUALIZE_SEQUENCE", action="store_true", help="Output a visualization of the sequence") parser.add_argument('-plot', dest="PLOT_SEQUENCE", action="store_true", help="Display a plot chart of the sequence") parser.add_argument('-frame', dest="SINGLE_FRAME", default=-1, type=int, help="Output just a single frame") # Music config parser.add_argument('-db', dest="MASTER_DB", type=float, default=-2.4, help="Master +/- decibels to be applied to final audio") parser.add_argument('-bpm', dest="BPM", type=int, default=120, help="Beats per minute, e.g. 60, 75, 100, 120, 150") parser.add_argument('-mpb', dest="METERS_PER_BEAT", type=int, default=75, help="Higher numbers creates shorter songs") parser.add_argument('-dpb', dest="DIVISIONS_PER_BEAT", type=int, default=4, help="e.g. 4 = quarter notes, 8 = eighth notes") parser.add_argument('-pm', dest="PRICE_MULTIPLIER", type=float, default=1.3, help="Makes instruments more expensive; higher numbers = less instruments playing") parser.add_argument('-vdur', dest="VARIANCE_MS", type=int, default=20, help="+/- milliseconds an instrument note should be off by to give it a little more 'natural' feel") # Visual design config parser.add_argument('-sw', dest="STATION_WIDTH", type=float, default=0.125, help="Minimum station width as a percent of the screen width; adjust this to change the overall visual speed") parser.add_argument('-tw', dest="TEXT_WIDTH", type=float, default=0.15, help="Station text width as a percent of the screen width") parser.add_argument('-cy', dest="CENTER_Y", type=float, default=0.475, help="Center y as a percent of screen height") parser.add_argument('-bty', dest="BOROUGH_TEXT_Y", type=float, default=0.55, help="Borough text center y as a percent of screen height") parser.add_argument('-sty', dest="STATION_TEXT_Y", type=float, default=0.375, help="Station text center y as a percent of screen height") parser.add_argument('-cw', dest="CIRCLE_WIDTH", type=int, default=60, help="Circle radius in pixels assuming 1920x1080") parser.add_argument('-lh', dest="LINE_HEIGHT", type=int, default=24, help="Height of horizontal line in pixels assuming 1920x1080") parser.add_argument('-bh', dest="BOUNDARY_HEIGHT", type=int, default=166, help="Height of boundary line in pixels assuming 1920x1080") parser.add_argument('-bw', dest="BOUNDARY_WIDTH", type=int, default=3, help="Width of boundary line in pixels assuming 1920x1080") parser.add_argument('-bm', dest="BOUNDARY_MARGIN", type=int, default=48, help="Horizontal margin of boundary line in pixels assuming 1920x1080") parser.add_argument('-mw', dest="MARKER_WIDTH", type=int, default=8, help="Height of horizontal line in pixels assuming 1920x1080") parser.add_argument('-sts', dest="STATION_TEXT_SIZE", type=int, default=30, help="Station text size in pixels assuming 1920x1080") parser.add_argument('-stm', dest="STATION_TEXT_MARGIN", type=int, default=20, help="Station text bottom margin in pixels assuming 1920x1080") parser.add_argument('-slm', dest="STATION_LETTER_MARGIN", type=int, default=1, help="Space after each station text letter in pixels assuming 1920x1080") parser.add_argument('-bts', dest="BOROUGH_TEXT_SIZE", type=int, default=24, help="Borough text size in pixels assuming 1920x1080") parser.add_argument('-blm', dest="BOROUGH_LETTER_MARGIN", type=int, default=1, help="Space after each borough text letter in pixels assuming 1920x1080") parser.add_argument('-bthresh', dest="BOROUGH_THRESHOLD", type=float, default=0.375, help="Minimum width available for displaying borough dividers") parser.add_argument('-dw', dest="DIVIDER_WIDTH", type=int, default=28, help="Line divider in pixels assuming 1920x1080") parser.add_argument('-dd', dest="DIVIDER_DISTANCE", type=float, default=0.333, help="Distance between dividers as a percent of screen width") parser.add_argument('-dc', dest="DIVIDER_COLOR", default="#666666", help="Distance between dividers as a percent of screen width") parser.add_argument('-bg', dest="BG_COLOR", default="#000000", help="Background color") parser.add_argument('-tc', dest="TEXT_COLOR", default="#eeeeee", help="Text color") parser.add_argument('-atc', dest="ALT_TEXT_COLOR", default="#aaaaaa", help="Secondary text color") parser.add_argument('-mc', dest="MARKER_COLOR", default="#dddddd", help="Marker color") parser.add_argument('-sfont', dest="STATION_FONT", default="fonts/OpenSans-Bold.ttf", help="Station font") parser.add_argument('-bfont', dest="BOROUGH_FONT", default="fonts/OpenSans-SemiBold.ttf", help="Borough font") parser.add_argument('-map', dest="MAP_IMAGE", default="img/nyc.png", help="Station font") parser.add_argument('-mcoord', dest="MAP_COORDS", default=" -74.1261,40.9087,-73.7066,40.5743", help="Top left, bottom right point") parser.add_argument('-mapm', dest="MAP_MARGIN", type=int, default=30, help="Margin of map in pixels assuming 1920x1080") parser.add_argument('-mapw', dest="MAP_W", type=int, default=260, help="Map width in pixels assuming 1920x1080") parser.add_argument('-mlw', dest="MAP_LINE_WIDTH", type=int, default=4, help="Map line in pixels assuming 1920x1080") parser.add_argument('-mlc', dest="MAP_LINE_COLOR", default="#eeeeee", help="Secondary text color") a = parser.parse_args() if not a.AUDIO_ONLY: import gizeh from PIL import Image, ImageDraw, ImageFont startTime = logTime() # Calculations BEAT_MS = roundInt(60.0 / a.BPM * 1000) ROUND_TO_NEAREST = roundInt(1.0 * BEAT_MS / a.DIVISIONS_PER_BEAT) basename = getBasename(a.DATA_FILE) if "_" in basename: basename, _ = tuple(basename.split("_")) lineName = basename if a.RIGHT_TO_LEFT: basename += "_rtl" # Read data _, stations = readCsv(a.DATA_FILE) _, instruments = readCsv(a.INSTRUMENTS_FILE) lstations = [] if len(a.DATA_LOCAL_FILE): _, lstations = readCsv(a.DATA_LOCAL_FILE) # Parse instruments instruments = prependAll(instruments, ("file", a.MEDIA_DIRECTORY)) instruments = [i for i in instruments if i["active"] > 0] instruments = addIndices(instruments, "index") for i, instrument in enumerate(instruments): instruments[i]["from_beat_ms"] = roundInt(1.0 * BEAT_MS / instrument["from_tempo"]) instruments[i]["to_beat_ms"] = roundInt(1.0 * BEAT_MS / instrument["to_tempo"]) instruments[i]["interval_ms"] = roundInt(instrument["interval_phase"] * BEAT_MS) instruments[i]["price"] = instrument["price"] * a.PRICE_MULTIPLIER # Buy instruments based on a specified budget # Add local stations in-between express ones if len(lstations) > 0: lbasename = getBasename(a.DATA_LOCAL_FILE) estations = {} addStations = [] for i, s in enumerate(stations): lines = str(s["Daytime Routes"]).split(" ") if lbasename in lines: estations[s["Station ID"]] = s.copy() sortByStart = None currentLStations = [] for i, s in enumerate(lstations): if s["Station ID"] in estations: if sortByStart is not None and len(currentLStations) > 0: step = 1.0 / (len(currentLStations) + 1) for j, ls in enumerate(currentLStations): currentLStations[j]["sortBy"] = sortByStart + (j+1) * step currentLStations[j]["isLocal"] = 1 addStations += currentLStations currentLStations = [] sortByStart = estations[s["Station ID"]]["sortBy"] elif sortByStart is not None: currentLStations.append(s) stations += addStations # stations = sorted(stations, key=lambda d: d["sortBy"]) # for s in stations: # if "isLocal" in s: # print(" --"+s["Stop Name"]) # else: # print(s["Stop Name"]) # sys.exit() # Parse stations stations = sorted(stations, key=lambda d: d["income"]) stations = addNormalizedValues(stations, "income", "nIncome") stations = addIndices(stations, "incomeIndex") isReverse = a.REVERSE if a.RIGHT_TO_LEFT: isReverse = (not isReverse) stations = sorted(stations, key=lambda d: d["sortBy"], reverse=isReverse) stations = addIndices(stations, "index") stationCount = len(stations) ms = a.PAD_START for i, station in enumerate(stations): stations[i]["percentile"] = 1.0 * station["incomeIndex"] / stationCount * 100 # stations[i]["percentile"] = min(99.999, 1.0 * station["nIncome"] * 100) stations[i]["instruments"] = buyInstruments(stations[i], instruments) # print(len(stations[i]["instruments"])) distance = beats = duration = 0 if i < stationCount-1: distance = earthDistance(stations[i+1]['GTFS Latitude'], stations[i+1]['GTFS Longitude'], station['GTFS Latitude'], station['GTFS Longitude']) beats = roundInt(1.0 * distance / a.METERS_PER_BEAT) duration = beats * BEAT_MS boroughNext = stations[i+1]["Borough"] stations[i]["distance"] = distance stations[i]["beats"] = beats stations[i]["duration"] = duration stations[i]["vduration"] = duration stations[i]["BoroughNext"] = boroughNext stations[i]["ms"] = ms stations[i]["lineName"] = lineName ms += duration if a.PROBE: print("===========================") for s in stations: if "isLocal" in s: print(formatSeconds(roundInt(s["ms"]/1000.0)) + " --- " + s["Stop Name"] + " (LOCAL) - $" + formatNumber(s["income"])) else: print(formatSeconds(roundInt(s["ms"]/1000.0)) + " - " + s["Stop Name"] + " - $" + formatNumber(s["income"])) print("===========================") else: dataFilename = a.DATA_OUTPUT_FILE % basename makeDirectories([dataFilename]) writeCsv(dataFilename, stations, headings=["ms", "Stop Name", "isLocal", "income", "Borough", "lineName"]) textFilename = replaceFileExtension(dataFilename, ".txt") text = f'Subway Inequality: {basename} train ({stations[-1]["Stop Name"]} Bound)\n\n' text += f'This song above mimics a ride along a subway line (the {basename} train), where the quantity and power of the instruments at any given moment in the song corresponds to the median household income of the neighborhood that you are passing through. The goal is to have the dramatic contrasts of the song echo the dramatic contrast of income in the city.\n\n' for s in stations: if "isLocal" not in s: text += f'{formatSeconds(roundInt(s["ms"]/1000.0))} - {s["Stop Name"]} - ${formatNumber(s["income"])} household income\n' writeTextFile(textFilename, text) if a.DATA_ONLY: sys.exit() # Calculate ranges distances = [s["distance"] for s in stations if s["distance"] > 0] totalDistance = sum(distances) minDistance, maxDistance = (min(distances), max(distances)) durations = [s["duration"] for s in stations if s["duration"] > 0] totalMs = sum(durations) minDuration, maxDuration = (min(durations), max(durations)) totalBeats = sum([s["beats"] for s in stations]) totalSeconds = roundInt(totalMs / 1000.0) secondsPerStation = roundInt(1.0*totalSeconds/stationCount) print('Total distance in meters: %s' % roundInt(totalDistance)) print('Distance range in meters: [%s, %s]' % (roundInt(minDistance), roundInt(maxDistance))) print('Average beats per station: %s' % roundInt(1.0*totalBeats/stationCount)) print('Average time per station: %s' % formatSeconds(secondsPerStation)) print('Main sequence beats: %s' % totalBeats) # Retrieve gain based on current beat # Get beat duration in ms based on current point in time # Return if the instrument should be played in the given interval # Add beats to sequence # Build main sequence sequence = [] for i, instrument in enumerate(instruments): ms = 0 stationQueueDur = 0 # Each station in stations for station in stations: # Check if instrument is in this station instrumentIndex = findInList(station['instruments'], 'index', instrument['index']) # Instrument not here, just add the station duration and continue if instrumentIndex < 0 and stationQueueDur > 0: sequence = addBeatsToSequence(sequence, instrument, stationQueueDur, ms, BEAT_MS, ROUND_TO_NEAREST, a.PAD_START) ms += stationQueueDur + station['duration'] stationQueueDur = 0 elif instrumentIndex < 0: ms += station['duration'] else: stationQueueDur += station['duration'] if stationQueueDur > 0: sequence = addBeatsToSequence(sequence, instrument, stationQueueDur, ms, BEAT_MS, ROUND_TO_NEAREST, a.PAD_START) sequenceDuration = max([s["ms"] for s in sequence]) + a.PAD_END # Now start the video frame logic # Calculations aa = vars(a) aa["STATION_WIDTH"] = roundInt(1.0 * a.WIDTH * a.STATION_WIDTH) aa["TEXT_WIDTH"] = roundInt(1.0 * a.WIDTH * a.TEXT_WIDTH) aa["CENTER_Y"] = roundInt(1.0 * a.HEIGHT * a.CENTER_Y) aa["BOROUGH_TEXT_Y"] = roundInt(1.0 * a.HEIGHT * a.BOROUGH_TEXT_Y) aa["STATION_TEXT_Y"] = roundInt(1.0 * a.HEIGHT * a.STATION_TEXT_Y) RESOLUTION = a.WIDTH / 1920.0 aa["CIRCLE_WIDTH"] = roundInt(a.CIRCLE_WIDTH * RESOLUTION) aa["LINE_HEIGHT"] = roundInt(a.LINE_HEIGHT * RESOLUTION) aa["BOUNDARY_MARGIN"] = roundInt(a.BOUNDARY_MARGIN * RESOLUTION) aa["BOUNDARY_HEIGHT"] = roundInt(a.BOUNDARY_HEIGHT * RESOLUTION) aa["BOUNDARY_WIDTH"] = roundInt(a.BOUNDARY_WIDTH * RESOLUTION) aa["BOROUGH_THRESHOLD"] = roundInt(1.0 * a.WIDTH * a.BOROUGH_THRESHOLD) aa["MARKER_WIDTH"] = roundInt(a.MARKER_WIDTH * RESOLUTION) aa["STATION_TEXT_SIZE"] = roundInt(a.STATION_TEXT_SIZE * RESOLUTION) aa["STATION_TEXT_MARGIN"] = roundInt(a.STATION_TEXT_MARGIN * RESOLUTION) aa["STATION_LETTER_MARGIN"] = roundInt(a.STATION_LETTER_MARGIN * RESOLUTION) aa["BOROUGH_TEXT_SIZE"] = roundInt(a.BOROUGH_TEXT_SIZE * RESOLUTION) aa["BOROUGH_LETTER_MARGIN"] = roundInt(a.BOROUGH_LETTER_MARGIN * RESOLUTION) aa["MAP_COORDS"] = tuple([float(c) for c in a.MAP_COORDS.strip().split(",")]) aa["MAP_MARGIN"] = roundInt(a.MAP_MARGIN * RESOLUTION) aa["MAP_W"] = roundInt(a.MAP_W * RESOLUTION) aa["MAP_LINE_WIDTH"] = roundInt(a.MAP_LINE_WIDTH * RESOLUTION) aa["DIVIDER_WIDTH"] = roundInt(a.DIVIDER_WIDTH * RESOLUTION) aa["DIVIDER_DISTANCE"] = roundInt(1.0 * a.WIDTH * a.DIVIDER_DISTANCE) # Add borough names boroughNames = { "Q": "Queens", "M": "Manhattan", "Bk": "Brooklyn", "Bx": "Bronx", "SI": "Staten Island" } for i, station in enumerate(stations): stations[i]["borough"] = boroughNames[station["Borough"]] x = 0 mlon0, mlat0, mlon1, mlat1 = a.MAP_COORDS vstations = stations[:] # If going right to left, reverse the stations visually if a.RIGHT_TO_LEFT: vstations = list(reversed(vstations)) for i, station in enumerate(vstations): if i < stationCount-1: vstations[i]["vduration"] = vstations[i+1]["duration"] else: vstations[i]["vduration"] = 0 for i, station in enumerate(vstations): boroughNext = station["borough"] if i < stationCount-1: boroughNext = vstations[i+1]["borough"] vstations[i]["boroughNext"] = boroughNext vstations[i]["width"] = roundInt(1.0 * station["vduration"] / minDuration * a.STATION_WIDTH) vstations[i]["x"] = x vstations[i]["x0"] = x - a.TEXT_WIDTH / 2 vstations[i]["x1"] = x + a.TEXT_WIDTH / 2 vstations[i]["mapNx"] = norm(station["GTFS Longitude"], (mlon0, mlon1)) vstations[i]["mapNy"] = norm(station["GTFS Latitude"], (mlat0, mlat1)) x += vstations[i]["width"] totalW = x pxPerMs = 1.0 * totalW / totalMs pxPerS = pxPerMs * 1000.0 pxPerFrame = pxPerS / a.FPS print("Total width: %s px" % totalW) print("Pixels per second: %s" % pxPerS) print("Pixels per frame: %s" % pxPerFrame) totalFrames = msToFrame(sequenceDuration, a.FPS) totalFrames = int(ceilToNearest(totalFrames, a.FPS)) print("Total frames: %s" % totalFrames) sequenceDuration = frameToMs(totalFrames, a.FPS) audioFilename = a.AUDIO_OUTPUT_FILE % basename print("%s steps in sequence" % len(sequence)) print('Total sequence time: %s' % formatSeconds(sequenceDuration/1000.0)) if a.VISUALIZE_SEQUENCE: instrumentsCount = len(instruments) labelW = 200 unitH = 10 unitW = 10 marginH = 2 imgH = (unitH+marginH) * instrumentsCount imgW = totalSeconds * unitW + labelW dfont = ImageFont.truetype(font="fonts/OpenSans-Regular.ttf", size=10) print("Making viz %s x %s" % (imgW, imgH)) im = Image.new('RGB', (imgW, imgH), "#000000") draw = ImageDraw.Draw(im, 'RGB') for i, ins in enumerate(instruments): y = i * (unitH + marginH) draw.text((2, y), ins["name"], fill="#FFFFFF", font=dfont) steps = [step for step in sequence if step["instrumentIndex"]==ins["index"]] for step in steps: sx = roundInt((step["ms"] - a.PAD_START) / 1000.0 / totalSeconds * (imgW-labelW) + labelW) draw.rectangle([(sx, y), (sx+3, y+unitH)], fill=(roundInt(255*step["volume"]),0,0)) if i > 0: draw.line([(0, y-1), (imgW, y-1)], fill="#cccccc", width=1) printProgress(i+1, instrumentsCount) im.save("output/viz.png") sys.exit() if a.PLOT_SEQUENCE: import matplotlib.pyplot as plt xs = [s['ms']/1000.0 for s in stations] ys = [s['income'] for s in stations] plt.plot(xs, ys) plt.show() sys.exit() if a.PROBE: sys.exit() makeDirectories([a.AUDIO_OUTPUT_FILE, a.OUTPUT_FILE]) if not a.AUDIO_ONLY: bulletImg = Image.open(a.IMAGE_FILE) bulletImg = bulletImg.resize((a.CIRCLE_WIDTH, a.CIRCLE_WIDTH), resample=Image.LANCZOS) mapImg = Image.open(a.MAP_IMAGE) mapH = roundInt((1.0 * mapImg.size[1] / mapImg.size[0]) * a.MAP_W) mapImg = mapImg.resize((a.MAP_W, mapH), resample=Image.LANCZOS) fontStation = ImageFont.truetype(font=a.STATION_FONT, size=a.STATION_TEXT_SIZE, layout_engine=ImageFont.LAYOUT_RAQM) fontBorough = ImageFont.truetype(font=a.BOROUGH_FONT, size=a.BOROUGH_TEXT_SIZE, layout_engine=ImageFont.LAYOUT_RAQM) makeDirectories([a.OUTPUT_FRAME % (basename, "*")]) if a.OVERWRITE and a.SINGLE_FRAME < 1: removeFiles(a.OUTPUT_FRAME % (basename, "*")) # calculations for easing in/out padFrameInCount = msToFrame(a.PAD_START, a.FPS) station0FrameCount = msToFrame(stations[0]["duration"], a.FPS) easeInFrames = getEasedFrames(padFrameInCount, station0FrameCount, pxPerFrame) easeInFrameCount = len(easeInFrames) padFrameOutCount = msToFrame(a.PAD_END, a.FPS) station1FrameCount = msToFrame(stations[-2]["duration"], a.FPS) easeOutFrames = getEasedFrames(padFrameOutCount, station1FrameCount, pxPerFrame) # easeOutFrames = list(reversed(easeOutFrames)) easeOutFrameCount = len(easeOutFrames) easeOutPixels = roundInt(sum(easeOutFrames)) print("Making video frame sequence...") videoFrames = [] centerX = roundInt(a.WIDTH * 0.5) xOffset = centerX direction = -1 if a.RIGHT_TO_LEFT: direction = 1 xOffset -= totalW xOffsetF = 1.0 * xOffset target = centerX-totalW if direction < 0 else centerX for f in range(totalFrames): frame = f + 1 ms = frameToMs(frame, a.FPS) frameFilename = a.OUTPUT_FRAME % (basename, zeroPad(frame, totalFrames)) if a.SINGLE_FRAME < 1 or a.SINGLE_FRAME == frame: if a.SINGLE_FRAME > 0: frameFilename = "output/frame.png" drawFrame(frameFilename, ms, xOffset, vstations, totalW, bulletImg, mapImg, fontStation, fontBorough, a) if a.SINGLE_FRAME > 0: sys.exit() pixelsLeft = abs(target - xOffset) # ease in start if frame < easeInFrameCount: xOffsetF += (direction * easeInFrames[frame-1]) xOffset = roundInt(xOffsetF) # print(abs(xOffset-centerX)) # # correct any discrepancy after ease in # elif frame <= easeInFrameCount: # xOffset = (frame - padFrameInCount) * pxPerFrame # xOffsetF = 1.0 * xOffset # ease out end elif pixelsLeft <= easeOutPixels: pxStep = easeOutFrames.pop() if len(easeOutFrames) > 0 else 1 xOffsetF += (direction * pxStep) xOffset = roundInt(xOffsetF) # print("%s > %s" % (xOffset, centerX-totalW)) else: xOffset += (direction * pxPerFrame) xOffsetF = 1.0 * xOffset xOffset = lim(xOffset, (centerX-totalW, centerX)) printProgress(frame, totalFrames) # break stepTime = logTime(startTime, "Finished frames") padZeros = len(str(totalFrames)) outfile = a.OUTPUT_FILE % basename frameInfile = a.OUTPUT_FRAME % (basename, '%s') if a.VIDEO_ONLY: compileFrames(frameInfile, a.FPS, outfile, padZeros) sys.exit() if a.OVERWRITE or not os.path.isfile(audioFilename): mixAudio(sequence, sequenceDuration, audioFilename, masterDb=a.MASTER_DB) else: print("%s already exists" % audioFilename) stepTime = logTime(stepTime, "Finished Audio") if not a.AUDIO_ONLY: if a.VIDEO_ONLY: audioFilename = None if a.OVERWRITE or not os.path.isfile(outfile): compileFrames(frameInfile, a.FPS, outfile, padZeros, audioFile=audioFilename) else: print("%s already exists" % outfile) logTime(startTime, "Total execution time")

48.559572

371

0.668688

bee4367acb7e986f0d0dbc48437bdbc33f87cdab

15,487

py

Python

release/scripts/startup/bl_ui/space_text.py

vic3t3chn0/Bforartists

7c54a60dd7aa568e20ae7e3778dfef993b61b7b5

[ "Naumen", "Condor-1.1", "MS-PL" ]

1

2020-01-18T22:13:24.000Z

release/scripts/startup/bl_ui/space_text.py

vic3t3chn0/Bforartists

7c54a60dd7aa568e20ae7e3778dfef993b61b7b5

[ "Naumen", "Condor-1.1", "MS-PL" ]

null

release/scripts/startup/bl_ui/space_text.py

vic3t3chn0/Bforartists

7c54a60dd7aa568e20ae7e3778dfef993b61b7b5

[ "Naumen", "Condor-1.1", "MS-PL" ]

null

# ##### BEGIN GPL LICENSE BLOCK ##### # # This program is free software; you can redistribute it and/or # modify it under the terms of the GNU General Public License # as published by the Free Software Foundation; either version 2 # of the License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software Foundation, # Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. # # ##### END GPL LICENSE BLOCK ##### # <pep8-80 compliant> import bpy from bpy.types import Header, Menu, Panel from bpy.app.translations import pgettext_iface as iface_ # bfa - show hide the editormenu #Redraw timer sub menu - Debug stuff # move_select submenu classes = ( ALL_MT_editormenu, TEXT_HT_header, TEXT_HT_footer, TEXT_MT_editor_menus, TEXT_PT_properties, TEXT_PT_find, TEXT_MT_view, TEXT_MT_redraw_timer, TEXT_MT_text, TEXT_MT_templates, TEXT_MT_templates_py, TEXT_MT_templates_osl, TEXT_MT_format, TEXT_MT_edit_to3d, TEXT_MT_context_menu, TEXT_MT_edit, TEXT_MT_edit_move_select, TEXT_MT_edit_delete, ) if __name__ == "__main__": # only for live edit. from bpy.utils import register_class for cls in classes: register_class(cls)

31.735656

125

0.612966

bee4d2aa2b67b36999556e3fe3dbdddbb08d368e

6,151

py

Python

wb/main/jobs/create_setup_bundle/create_setup_bundle_job.py

apaniukov/workbench

2f2653ecfd0143d2d53e33ad84379f13443fdfaa

[ "Apache-2.0" ]

23

2022-03-17T12:24:09.000Z

2022-03-31T09:13:30.000Z

wb/main/jobs/create_setup_bundle/create_setup_bundle_job.py

apaniukov/workbench

2f2653ecfd0143d2d53e33ad84379f13443fdfaa

[ "Apache-2.0" ]

18

2022-03-21T08:17:44.000Z

2022-03-30T12:42:30.000Z

wb/main/jobs/create_setup_bundle/create_setup_bundle_job.py

apaniukov/workbench

2f2653ecfd0143d2d53e33ad84379f13443fdfaa

[ "Apache-2.0" ]

16

2022-03-17T12:24:14.000Z

2022-03-31T12:15:12.000Z

""" OpenVINO DL Workbench Class for create setup bundle job Copyright (c) 2020 Intel Corporation Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ import os import shutil import tempfile from contextlib import closing from wb.extensions_factories.database import get_db_session_for_celery from wb.main.enumerates import JobTypesEnum, StatusEnum from wb.main.jobs.interfaces.ijob import IJob from wb.main.jobs.utils.database_functions import set_status_in_db from wb.main.models import CreateSetupBundleJobModel, SharedArtifactModel from wb.main.scripts.job_scripts_generators.setup_script_generator import SetupScriptGenerator from wb.main.utils.bundle_creator.setup_bundle_creator import SetupBundleCreator, SetupComponentsParams from wb.main.utils.utils import find_by_ext

55.918182

115

0.676313

bee53cb77bca7c1ce3a8035bc7f1d877d50fc52d

2,365

py

Python

ros_awsiot_agent/src/ros_awsiot_agent/mqtt2ros.py

whill-labs/ros_awsiot

4c15be53c0643fb81fd5a261a1af5be2652c4166

[ "MIT" ]

4

2021-10-06T10:19:07.000Z

2022-03-02T02:13:09.000Z

ros_awsiot_agent/src/ros_awsiot_agent/mqtt2ros.py

whill-labs/ros_awsiot

4c15be53c0643fb81fd5a261a1af5be2652c4166

[ "MIT" ]

1

2021-10-02T15:13:48.000Z

ros_awsiot_agent/src/ros_awsiot_agent/mqtt2ros.py

whill-labs/ros_awsiot

4c15be53c0643fb81fd5a261a1af5be2652c4166

[ "MIT" ]

1

2021-10-07T02:11:27.000Z

#!/usr/bin/env python3 import logging from os.path import expanduser from typing import Any, Dict from uuid import uuid4 import rospy from awsiotclient import mqtt, pubsub from ros_awsiot_agent import set_module_logger from rosbridge_library.internal.message_conversion import populate_instance from rosbridge_library.internal.ros_loader import get_message_class set_module_logger(modname="awsiotclient", level=logging.WARN) if __name__ == "__main__": main()

30.320513

80

0.689641

bee627678ed010aec77f469faec38fc6e41f1465

5,031

py

Python

poly/app.py

thdb-theo/Polynomial

9943ee5eb175ef01720954c6a95c685bd7fd5f6c

[ "MIT" ]

null

poly/app.py

thdb-theo/Polynomial

9943ee5eb175ef01720954c6a95c685bd7fd5f6c

[ "MIT" ]

null

poly/app.py

thdb-theo/Polynomial

9943ee5eb175ef01720954c6a95c685bd7fd5f6c

[ "MIT" ]

null

import sys import re from PyQt4 import QtGui, QtCore from polynomial import Polynomial from rational import Rational if __name__ == '__main__': main()

33.098684

93

0.603459

bee68e7de68c03f76e1ccae51e5aa678663d50fa

493

py

Python

ariadne_server/tests/fixtures/fake_context.py

seanaye/FeatherLight-API

4d42a424762311ee35b3fd4f689883aa4197eb2e

[ "MIT" ]

3

2020-06-28T17:30:57.000Z

2022-01-25T18:03:38.000Z

ariadne_server/tests/fixtures/fake_context.py

seanaye/FeatherLight-API

4d42a424762311ee35b3fd4f689883aa4197eb2e

[ "MIT" ]

null

ariadne_server/tests/fixtures/fake_context.py

seanaye/FeatherLight-API

4d42a424762311ee35b3fd4f689883aa4197eb2e

[ "MIT" ]

1

2021-02-04T07:14:08.000Z

from secrets import token_hex import pytest

18.259259

47

0.584178

bee850ee36621b995a6de029e878f2bcfff1b23e

4,552

py

Python

libs/evaluation/training_benchmark_database.py

eeshakumar/hythe

52ca795c8370ddfb2aa6fb87ff3f63a85c55f913

[ "MIT" ]

null

libs/evaluation/training_benchmark_database.py

eeshakumar/hythe

52ca795c8370ddfb2aa6fb87ff3f63a85c55f913

[ "MIT" ]

null

libs/evaluation/training_benchmark_database.py

eeshakumar/hythe

52ca795c8370ddfb2aa6fb87ff3f63a85c55f913

[ "MIT" ]

null

# Copyright (c) 2020 Julian Bernhard, # Klemens Esterle, Patrick Hart, Tobias Kessler # # This software is released under the MIT License. # https://opensource.org/licenses/MIT from bark.benchmark.benchmark_result import BenchmarkConfig from bark_ml.library_wrappers.lib_fqf_iqn_qrdqn.agent import TrainingBenchmark from bark.benchmark.benchmark_runner import BenchmarkRunner, BehaviorConfig

47.915789

133

0.65312

bee859bef7a37ff661836407bce80f2d3470ddd9

27,023

py

Python

goldstone/tenants/tests_cloud.py

Solinea/goldstone-server

91b078ca9fed1b33f48dc79f4af5c9d1817a1bc5

[ "Apache-2.0" ]

14

2015-05-18T22:11:11.000Z

2020-08-14T06:50:09.000Z

goldstone/tenants/tests_cloud.py

lexjacobs/goldstone-server

91b078ca9fed1b33f48dc79f4af5c9d1817a1bc5

[ "Apache-2.0" ]

568

2015-05-17T01:26:36.000Z

2021-06-10T20:36:47.000Z

goldstone/tenants/tests_cloud.py

lexjacobs/goldstone-server

91b078ca9fed1b33f48dc79f4af5c9d1817a1bc5

[ "Apache-2.0" ]

22

2015-05-25T20:16:06.000Z

2021-08-08T20:25:24.000Z

"""Unit tests for /tenants/<id>/cloud endpoints.""" # Copyright 2015 Solinea, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import json from django.contrib.auth import get_user_model from rest_framework.status import HTTP_200_OK, HTTP_401_UNAUTHORIZED, \ HTTP_400_BAD_REQUEST, HTTP_201_CREATED, HTTP_403_FORBIDDEN, \ HTTP_204_NO_CONTENT from goldstone.test_utils import Setup, create_and_login, \ AUTHORIZATION_PAYLOAD, CONTENT_BAD_TOKEN, CONTENT_NO_CREDENTIALS, \ check_response_without_uuid, TEST_USER_1, CONTENT_PERMISSION_DENIED, \ BAD_TOKEN, BAD_UUID from .models import Tenant, Cloud from .tests_tenants import TENANTS_ID_URL # HTTP response content. CONTENT_MISSING_OS_USERNAME = '"username":["This field is required."]' CONTENT_MISSING_OS_NAME = '"tenant_name":["This field is required."]' CONTENT_MISSING_OS_PASSWORD = '"password":["This field is required."]' CONTENT_MISSING_OS_URL = '"auth_url":["This field is required."]' # URLs used by this module. TENANTS_ID_CLOUD_URL = TENANTS_ID_URL + "cloud/" TENANTS_ID_CLOUD_ID_URL = TENANTS_ID_CLOUD_URL + "%s/"

41.130898

79

0.531029

bee920effbd17d10746b345bbf080e1ea4ae7a4f

4,750

py

Python

onnxruntime/test/server/integration_tests/model_zoo_data_prep.py

PhaniShekhar/onnxruntime

2663b9c44381b30525ae6234e13ed25c69206d07

[ "MIT" ]

null

onnxruntime/test/server/integration_tests/model_zoo_data_prep.py

PhaniShekhar/onnxruntime

2663b9c44381b30525ae6234e13ed25c69206d07

[ "MIT" ]

null

onnxruntime/test/server/integration_tests/model_zoo_data_prep.py

PhaniShekhar/onnxruntime

2663b9c44381b30525ae6234e13ed25c69206d07

[ "MIT" ]

null

# Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. import os import sys import shutil import onnx import onnxruntime import json from google.protobuf.json_format import MessageToJson import predict_pb2 import onnx_ml_pb2 # Current models only have one input and one output if __name__ == '__main__': model_zoo = os.path.realpath(sys.argv[1]) test_data = os.path.realpath(sys.argv[2]) os.makedirs(test_data, exist_ok=True) gen_req_resp(model_zoo, test_data)

32.758621

123

0.708842

beea57272100654c7600d64caab6b4c5cdc2179e

2,484

py

Python

articlequality/feature_lists/tests/test_enwiki.py

mariushoch/articlequality

57edf786636548bed466aa4e9d9e213fe8d1093b

[ "MIT" ]

null

articlequality/feature_lists/tests/test_enwiki.py

mariushoch/articlequality

57edf786636548bed466aa4e9d9e213fe8d1093b

[ "MIT" ]

null

articlequality/feature_lists/tests/test_enwiki.py

mariushoch/articlequality

57edf786636548bed466aa4e9d9e213fe8d1093b

[ "MIT" ]

null

from revscoring.datasources.revision_oriented import revision from revscoring.dependencies import solve from .. import enwiki revision_text = revision.text

27

76

0.654589

beead51f0acfbaced2396459fa3fc222015aa766

6,984

py

Python

GPU_compare_CPU.py

kvmu/SFU-workterm

91c976b094097912e71dd7e0d6207ad8ce7a7e93

[ "MIT" ]

null

GPU_compare_CPU.py

kvmu/SFU-workterm

91c976b094097912e71dd7e0d6207ad8ce7a7e93

[ "MIT" ]

null

GPU_compare_CPU.py

kvmu/SFU-workterm

91c976b094097912e71dd7e0d6207ad8ce7a7e93

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Mon Aug 10 14:31:17 2015 @author: Kevin M. Description: This script does CPU and GPU matrix element time complexity profiling. It has a function which applies the matrix element analysis for a given set of parameters, profiles the code and plots the time complexity results (with fit) and plots the matrix elements from each case. """ import numpy as np import scipy as sp import matplotlib matplotlib.use('Agg') from matplotlib import pyplot as plt from my_timer import timer from math import log from scipy.optimize import curve_fit def flinear(N, mode): """ O(n) function """ y = np.asarray([i for i in range(N)]) np.asarray([i for i in range(N)]) np.asarray([i for i in range(N)]) return y ,1 def fsquare(N, mode): """ O(n^2) function """ for i in range(N): for j in range(N): y = i*j return y,1 def algoAnalysis(fn, nMin, nMax, mode): """ Run timer and plot time complexity """ n = [] time_result = [] y_result = [] y_err = [] for i in [j*32 for j in range(nMin,nMax+1)]: with timer() as t: temp_result, temp_err = fn(i, mode) time_result.append(t.msecs) y_result.append(temp_result) y_err.append(temp_err) n.append(i) return n, time_result, y_result, y_err # main() function # call main if __name__ == '__main__': # matplotlib.rcParams.update({'font.family': 'Zapf Chancery'}) main()

29.719149

88

0.583477

beeae2374b9c6c4f75bcbbf6e4da5b6372460220

7,714

py

Python

applications/plugins/Flexible/Flexible_test/scenes/python/reInitMapping.py

sofa-framework/issofa

94855f488465bc3ed41223cbde987581dfca5389

[ "OML" ]

null

applications/plugins/Flexible/Flexible_test/scenes/python/reInitMapping.py

sofa-framework/issofa

94855f488465bc3ed41223cbde987581dfca5389

[ "OML" ]

null

applications/plugins/Flexible/Flexible_test/scenes/python/reInitMapping.py

sofa-framework/issofa

94855f488465bc3ed41223cbde987581dfca5389

[ "OML" ]

null

import Sofa import SofaTest import SofaPython.Tools OBJ = SofaPython.Tools.localPath( __file__, "beam.obj" ) RAW = SofaPython.Tools.localPath( __file__, "beam.raw" ) ##Check if calling Mapping::init() change anything # #The trick is to know that if the option evaluateShapeFunction is activated #in the ImageGaussPointSampler then a sampler::bwdInit() must be called #to update weights using gauss points.

47.913043

298

0.704693

beeda21a5090a064572591c96a86d43fd6daf247

1,688

py

Python

mindspore/ops/_register_for_op.py

Vincent34/mindspore

a39a60878a46e7e9cb02db788c0bca478f2fa6e5

[ "Apache-2.0" ]

1

2021-07-16T12:05:53.000Z

mindspore/ops/_register_for_op.py

Vincent34/mindspore

a39a60878a46e7e9cb02db788c0bca478f2fa6e5

[ "Apache-2.0" ]

null

mindspore/ops/_register_for_op.py

Vincent34/mindspore

a39a60878a46e7e9cb02db788c0bca478f2fa6e5

[ "Apache-2.0" ]

null

# Copyright 2020 Huawei Technologies Co., Ltd # # 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. # ============================================================================ """Registry the relation.""" from collections import UserDict from .primitive import Primitive

33.76

82

0.593009

beee49868a956aa3196803cdf539676b921996ae

11,496

py

Python

senlin-7.0.0/senlin/tests/unit/api/middleware/test_version_negotiation.py

scottwedge/OpenStack-Stein

7077d1f602031dace92916f14e36b124f474de15

[ "Apache-2.0" ]

null

senlin-7.0.0/senlin/tests/unit/api/middleware/test_version_negotiation.py

scottwedge/OpenStack-Stein

7077d1f602031dace92916f14e36b124f474de15

[ "Apache-2.0" ]

5

2019-08-14T06:46:03.000Z

2021-12-13T20:01:25.000Z

senlin-7.0.0/senlin/tests/unit/api/middleware/test_version_negotiation.py

scottwedge/OpenStack-Stein

7077d1f602031dace92916f14e36b124f474de15

[ "Apache-2.0" ]

2

2020-03-15T01:24:15.000Z

2020-07-22T20:34:26.000Z

# 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. import mock import six import webob from senlin.api.common import version_request as vr from senlin.api.common import wsgi from senlin.api.middleware import version_negotiation as vn from senlin.common import exception from senlin.tests.unit.common import base

40.336842

79

0.673626

bef071b99c5638f1355cc9be272ba0f93a6cb31f

493

py

Python

iot/models.py

kkishans/IOT_DJANGO

12a19858f002a8c684e4dbb93868a8859d57615f

[ "MIT" ]

null

iot/models.py

kkishans/IOT_DJANGO

12a19858f002a8c684e4dbb93868a8859d57615f

[ "MIT" ]

null

iot/models.py

kkishans/IOT_DJANGO

12a19858f002a8c684e4dbb93868a8859d57615f

[ "MIT" ]

null

from django.db import models from django import forms # Create your models here.

25.947368

60

0.699797

bef0b40fe98f05288d080226293e4d439b57a362

2,970

py

Python

Homework files/Think_Python_Book_Homework_1.py

SillyHatsOnly/Python-Education-Experiments

22244defc47b4e3ba41af07957a782013afe12b0

[ "MIT" ]

null

Homework files/Think_Python_Book_Homework_1.py

SillyHatsOnly/Python-Education-Experiments

22244defc47b4e3ba41af07957a782013afe12b0

[ "MIT" ]

null

Homework files/Think_Python_Book_Homework_1.py

SillyHatsOnly/Python-Education-Experiments

22244defc47b4e3ba41af07957a782013afe12b0

[ "MIT" ]

null

do_twice(print_spam) do_twice(print_spam, 'spamm') do_four(print_spam, "SPAM") hor_line hor_line() hor_line() hor_line() square_print() square_print() square_print() double_square double_square() double_square() square_print() square_print()

18.679245

47

0.476431

bef16a350cb321f3059e524b8af8bbcaac507956

123

py

Python

email_log/apps.py

bernd-wechner/django-email-log

dbbe0ef6cee8b8067d6420dccc7a8f2061662a68

[ "MIT" ]

26

2015-04-14T18:24:54.000Z

2022-03-07T13:01:34.000Z

email_log/apps.py

bernd-wechner/django-email-log

dbbe0ef6cee8b8067d6420dccc7a8f2061662a68

[ "MIT" ]

23

2015-06-23T02:40:39.000Z

2022-02-08T05:07:42.000Z

email_log/apps.py

bernd-wechner/django-email-log

dbbe0ef6cee8b8067d6420dccc7a8f2061662a68

[ "MIT" ]

25

2015-02-04T16:16:05.000Z

2021-09-28T10:53:00.000Z

from django.apps import AppConfig

17.571429

33

0.731707

bef17e7d48e784a47058c04dd63db533f851c334

83

py

Python

gawain/tests/test_numerics.py

henrywatkins/gawain

c556be20242249504fc0e04a5d3b7168a8369043

[ "MIT" ]

1

2021-11-20T06:16:13.000Z

gawain/tests/test_numerics.py

henrywatkins/gawain

c556be20242249504fc0e04a5d3b7168a8369043

[ "MIT" ]

null

gawain/tests/test_numerics.py

henrywatkins/gawain

c556be20242249504fc0e04a5d3b7168a8369043

[ "MIT" ]

null

import pytest from gawain.numerics import Clock, SolutionVector, MHDSolutionVector

27.666667

68

0.86747

bef2574ded37985d33b872832104339ea2dcbc78

384

py

Python

project_9/util.py

sople1/project_9

7d91d786533d508572feae1ffbd1b4a6a80208ab

[ "CC0-1.0" ]

null

project_9/util.py

sople1/project_9

7d91d786533d508572feae1ffbd1b4a6a80208ab

[ "CC0-1.0" ]

null

project_9/util.py

sople1/project_9

7d91d786533d508572feae1ffbd1b4a6a80208ab

[ "CC0-1.0" ]

null

""" utility for project 9 :author: Seongsu Yoon <sople1@snooey.net> :license: CC0 """ def clear(): """ clear cmd/term :return: void """ import os import sys if sys.platform == 'win32': os.system('cls') # on windows else: os.system('clear') # on linux / os x if __name__ == '__main__': raise Exception("please run main py")

14.769231

45

0.570313

bef2add5e5d23f2bc354f97f806087052f88a9fd

2,383

py

Python

api/views.py

HigoOliveira/DesafioFinalServer

284d3cea59f28f6da229345496896106e3d2048a

[ "MIT" ]

null

api/views.py

HigoOliveira/DesafioFinalServer

284d3cea59f28f6da229345496896106e3d2048a

[ "MIT" ]

null

api/views.py

HigoOliveira/DesafioFinalServer

284d3cea59f28f6da229345496896106e3d2048a

[ "MIT" ]

null

from rest_framework.views import APIView from .models import User, Event from .serializer import UserSerializer, EventSerializer from rest_framework.permissions import AllowAny, IsAuthenticated from rest_framework.authentication import TokenAuthentication from rest_framework import status, mixins, generics from rest_framework.response import Response

36.661538

85

0.768779

bef317cba640175d733bcaa55e5644bbab2602a1

1,582

py

Python

Searching_Sorting/MinimumMovesToEqualAllArrayElements2.py

PK-100/Competitive_Programming

d0863feaaa99462b2999e85dcf115f7a6c08bb8d

[ "MIT" ]

70

2018-06-25T21:20:15.000Z

2022-03-24T03:55:17.000Z

Searching_Sorting/MinimumMovesToEqualAllArrayElements2.py

An3sha/Competitive_Programming

ee7eadf51939a360d0b004d787ebabda583e92f0

[ "MIT" ]

4

2018-09-04T13:12:20.000Z

2021-06-20T08:29:12.000Z

Searching_Sorting/MinimumMovesToEqualAllArrayElements2.py

An3sha/Competitive_Programming

ee7eadf51939a360d0b004d787ebabda583e92f0

[ "MIT" ]

24

2018-12-26T05:15:32.000Z

2022-01-23T23:04:54.000Z

# LC 462 #from statistics import median from random import randrange from math import floor

28.763636

76

0.474083

bef32dc0efa2656e8a84216ea747c7b952e1b452

43

py

Python

moban/_version.py

CLiu13/moban

5deada1af7ff24a6adf698de6a8b589a258d4dc2

[ "MIT" ]

1

2018-12-16T01:16:22.000Z

moban/_version.py

CLiu13/moban

5deada1af7ff24a6adf698de6a8b589a258d4dc2

[ "MIT" ]

null

moban/_version.py

CLiu13/moban

5deada1af7ff24a6adf698de6a8b589a258d4dc2

[ "MIT" ]

null

__version__ = "0.3.9" __author__ = "C. W."

14.333333

21

0.604651

bef3d9edefde231b494e39df17d4acf13c5e8797

666

py

Python

Gif_Rick/rick_random_gif.py

BiceCold/Citadel_of_Ricks

72f1a447accc2c11d1fa1cbf3c3342913913e50e

[ "Apache-2.0" ]

2

2018-04-13T17:41:08.000Z

2018-09-20T22:19:52.000Z

Gif_Rick/rick_random_gif.py

BiceCold/Citadel_of_Ricks

72f1a447accc2c11d1fa1cbf3c3342913913e50e

[ "Apache-2.0" ]

null

Gif_Rick/rick_random_gif.py

BiceCold/Citadel_of_Ricks

72f1a447accc2c11d1fa1cbf3c3342913913e50e

[ "Apache-2.0" ]

null

import imgurpython from Environment_Handlers.configs import get_config import random client_id = get_config("client_id") client_secret = get_config("client_secret") client_refresh_token = get_config("client_refresh") client_access_token = get_config("client_access_token") username = 'antipoliticsrick' client = imgurpython.ImgurClient(client_id, client_secret, client_access_token, client_refresh_token) # album_ids = client.get_account_album_ids(username, page=0) img_lst = client.get_album_images('GebVe10') giflink = []

26.64

101

0.792793

bef57e6edf7a67698588bda9e271df4b1e689682

131

py

Python

catalyst/dl/experiment/__init__.py

andrey-avdeev/catalyst

fd17aaba7775c99b7e2b1ce86e60aa8f2379acc3

[ "Apache-2.0" ]

3

2019-11-02T05:37:06.000Z

2020-01-13T02:26:07.000Z

catalyst/dl/experiment/__init__.py

andrey-avdeev/catalyst

fd17aaba7775c99b7e2b1ce86e60aa8f2379acc3

[ "Apache-2.0" ]

null

catalyst/dl/experiment/__init__.py

andrey-avdeev/catalyst

fd17aaba7775c99b7e2b1ce86e60aa8f2379acc3

[ "Apache-2.0" ]

1

2021-12-20T07:32:25.000Z

# flake8: noqa from .base import BaseExperiment from .config import ConfigExperiment from .supervised import SupervisedExperiment

21.833333

44

0.839695

bef59cacc937701b313af0467ffa47a4f4a7a929

3,217

py

Python

home_directories/Library/Application Support/Alfred 3/Alfred.alfredpreferences/workflows/user.workflow.BC9837BA-F60E-475C-B524-E761FBD0E1EB/common.py

joekallen/dotfiles

9318c168fdb9ce0b1066b032e93a7e465d0ffcee

[ "Apache-2.0" ]

null

home_directories/Library/Application Support/Alfred 3/Alfred.alfredpreferences/workflows/user.workflow.BC9837BA-F60E-475C-B524-E761FBD0E1EB/common.py

joekallen/dotfiles

9318c168fdb9ce0b1066b032e93a7e465d0ffcee

[ "Apache-2.0" ]

null

home_directories/Library/Application Support/Alfred 3/Alfred.alfredpreferences/workflows/user.workflow.BC9837BA-F60E-475C-B524-E761FBD0E1EB/common.py

joekallen/dotfiles

9318c168fdb9ce0b1066b032e93a7e465d0ffcee

[ "Apache-2.0" ]

null

import os import argparse import subprocess from workflow import Workflow

27.732759

126

0.608952

bef59fb3dbc590e868cbbe9ba87904ee2be92c5d

528

py

Python

dependencies/generate maps/pythongis/app/tk2/__init__.py

karimbahgat/AutoMap

eae52f16b7ce71cb2b4b7ae67cf6e4680ea2194f

[ "MIT" ]

4

2015-12-05T14:31:55.000Z

2018-02-09T05:54:36.000Z

dependencies/generate maps/pythongis/app/tk2/__init__.py

karimbahgat/AutoMap

eae52f16b7ce71cb2b4b7ae67cf6e4680ea2194f

[ "MIT" ]

1

2022-01-13T02:52:09.000Z

dependencies/generate maps/pythongis/app/tk2/__init__.py

karimbahgat/AutoMap

eae52f16b7ce71cb2b4b7ae67cf6e4680ea2194f

[ "MIT" ]

1

2018-10-24T01:08:11.000Z

""" Tk2 Tk2 is a convenience library for extending the functionality of Tkinter, to make it easier and more flexible to create GUI applications. """ from .basics import * from .scrollwidgets import * from .texteditor import Text, MultiTextSearch from .variables import * # Later from .multiwidgets import * from .progbar import * from .ribbon import * #from orderedlist import * #from calendar import * from web import * from . import filedialog from . import messagebox from . import colorchooser from . import dispatch

20.307692

73

0.767045

bef5e1efda3dd7f954a3c06d34cbd2bd9106ec13

803

py

Python

tools/deepke/relation_extraction/standard/models/BasicModule.py

dfface/DoctorKG

6bd6ebec8244a9ce0a2c8c278a704f02b9afaaf8

[ "MIT" ]

1

2022-03-26T16:08:08.000Z

tools/deepke/relation_extraction/standard/models/BasicModule.py

dfface/DoctorKG

6bd6ebec8244a9ce0a2c8c278a704f02b9afaaf8

[ "MIT" ]

null

tools/deepke/relation_extraction/standard/models/BasicModule.py

dfface/DoctorKG

6bd6ebec8244a9ce0a2c8c278a704f02b9afaaf8

[ "MIT" ]

null

import os import time import torch import torch.nn as nn

22.942857

85

0.555417

bef786a72fbb29131b60f5c806a5c2a1d2c1e463

3,135

py

Python

software/nuke/init.py

kei-iketani/plex

cf09c8ef93984e5a69b23bf56248b87e4cfd98b0

[ "MIT" ]

153

2018-03-22T18:29:17.000Z

2022-03-07T03:43:09.000Z

software/nuke/init.py

kei-iketani/plex

cf09c8ef93984e5a69b23bf56248b87e4cfd98b0

[ "MIT" ]

30

2018-08-16T16:27:42.000Z

2021-02-24T05:37:25.000Z

software/nuke/init.py

alexanderrichter/arPipeline

3466f70a79e4d32c0647ba21d9689157a0f7772e

[ "MIT" ]

34

2018-03-24T03:54:05.000Z

2022-03-10T11:36:52.000Z

#********************************************************************* # content = init Nuke # version = 0.1.0 # date = 2019-12-01 # # license = MIT <https://github.com/alexanderrichtertd> # author = Alexander Richter <alexanderrichtertd.com> #********************************************************************* import os import errno import nuke import pipefunc from tank import Tank #********************************************************************* # VARIABLE TITLE = os.path.splitext(os.path.basename(__file__))[0] LOG = Tank().log.init(script=TITLE) PROJECT_DATA = Tank().data_project RESOLUTION = (' ').join([str(PROJECT_DATA['resolution'][0]), str(PROJECT_DATA['resolution'][1]), PROJECT_DATA['name'].replace(' ', '')]) #********************************************************************* # FOLDER CREATION #********************************************************************* # PIPELINE Tank().init_software() add_plugin_paths() try: from scripts import write_node except: LOG.warning('FAILED loading write_node') # LOAD paths try: for paths in os.getenv('SOFTWARE_SUB_PATH').split(';'): nuke.pluginAddPath(paths) except: LOG.warning('FAILED loading SOFTWARE_SUB_PATH') print('SETTINGS') # RESOLUTION ********************************************************************* try: nuke.addFormat(RESOLUTION) nuke.knobDefault('Root.format', PROJECT_DATA['name'].replace(' ', '')) print(' {} ON - {}'.format(chr(254), RESOLUTION)) except: LOG.error(' OFF - {}'.format(RESOLUTION), exc_info=True) print(' {} OFF - {}'.format(chr(254), RESOLUTION)) # FPS ********************************************************************* try: nuke.knobDefault("Root.fps", str(PROJECT_DATA['fps'])) print(' {} ON - {} fps'.format(chr(254), PROJECT_DATA['fps'])) except: LOG.error(' OFF - {} fps'.format(PROJECT_DATA['fps']), exc_info=True) print(' {} OFF - {} fps'.format(chr(254), PROJECT_DATA['fps'])) # createFolder ********************************************************************* try: nuke.addBeforeRender(create_write_dir) print(' {} ON - create_write_dir (before render)'.format(chr(254))) except: LOG.error(' OFF - create_write_dir (before render)'.format(chr(254)), exc_info=True) print(' {} OFF - create_write_dir (before render)'.format(chr(254))) print('')

30.436893

89

0.536204

bef8b3cc0e57e7d1cb77a57410c13eec81de3df9

589

py

Python

main.py

gaoshanyu/web_ui_test_sample

8a6cc9b54b5f728af7ef0725dea42d759bd115d0

[ "MIT" ]

null

main.py

gaoshanyu/web_ui_test_sample

8a6cc9b54b5f728af7ef0725dea42d759bd115d0

[ "MIT" ]

null

main.py

gaoshanyu/web_ui_test_sample

8a6cc9b54b5f728af7ef0725dea42d759bd115d0

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Created at 03/10/2020 __author__ = 'raniys' import pytest if __name__ == '__main__': # -v: verbose; -s: shortcut for --capture=no; # -m: only run tests matching given mark expression. example: -m 'mark1 and not mark2'; # --html=path: create html report file at given path. # pytest.main(["-v", "-s", "-m", "smoke", "--html=./reports/smoke_tests_report.html"]) # pytest.main(["-v", "-s", "-m", "sample", "--html=./reports/sample_tests_report.html"]) pytest.main(["-v", "-s", "-m", "search", "--html=./reports/search_tests_report.html"])

39.266667

92

0.614601

bef9a72ceb82bbb48832da89c306ea29b20a4752

863

py

Python

rnd/HaskellRSLCompiler/test/parse/test.py

syoyo/lucille

ff81b332ae78181dbbdc1ec3c3b0f59992e7c0fa

[ "BSD-3-Clause" ]

77

2015-01-29T21:02:10.000Z

2022-03-04T11:23:12.000Z

rnd/HaskellRSLCompiler/test/parse/test.py

syoyo/lucille

ff81b332ae78181dbbdc1ec3c3b0f59992e7c0fa

[ "BSD-3-Clause" ]

1

2018-11-08T02:11:24.000Z

2018-11-08T04:31:17.000Z

rnd/HaskellRSLCompiler/test/parse/test.py

syoyo/lucille

ff81b332ae78181dbbdc1ec3c3b0f59992e7c0fa

[ "BSD-3-Clause" ]

13

2015-04-20T08:17:29.000Z

2020-06-17T18:35:06.000Z

#!/usr/bin/env python import os, sys import subprocess import re import glob errlog = [] if __name__ == '__main__': main()

17.979167

98

0.499421

befb15db729fb7dcc8145ec21e9b327a9461b95c

657

py

Python

glasses/models/classification/base/__init__.py

rentainhe/glasses

34300a76985c7fc643094fa8d617114926a0ee75

[ "MIT" ]

271

2020-10-20T12:30:23.000Z

2022-03-17T03:02:38.000Z

glasses/models/classification/base/__init__.py

rentainhe/glasses

34300a76985c7fc643094fa8d617114926a0ee75

[ "MIT" ]

212

2020-07-25T13:02:23.000Z

2022-02-20T10:33:32.000Z

glasses/models/classification/base/__init__.py

rentainhe/glasses

34300a76985c7fc643094fa8d617114926a0ee75

[ "MIT" ]

23

2021-01-03T13:53:36.000Z

2022-03-17T05:40:34.000Z

from torch import Tensor, nn from ...base import VisionModule

21.9

65

0.584475

befc1052790c2cb39af3f31238e68ac4213b7a50

3,202

py

Python

lib/data.py

PEDIA-Charite/classifier

13e9d6108f9691b089aac59c7392f7940033b8af

[ "MIT" ]

2

2019-04-04T03:44:25.000Z

2019-12-23T17:08:51.000Z

lib/data.py

PEDIA-Charite/classifier

13e9d6108f9691b089aac59c7392f7940033b8af

[ "MIT" ]

9

2017-05-23T09:55:15.000Z

2019-11-22T11:24:20.000Z

lib/data.py

PEDIA-Charite/classifier

13e9d6108f9691b089aac59c7392f7940033b8af

[ "MIT" ]

2

2017-05-24T12:23:13.000Z

2019-09-03T08:36:18.000Z

# -*- coding: utf-8 -*- import os import numpy as np import sys import logging import csv # Setup logging logger = logging.getLogger(__name__) console_handle = logging.StreamHandler() console_handle.setLevel(logging.INFO) formatter = logging.Formatter('%(asctime)s: %(message)s', datefmt='%m-%d %H:%M') console_handle.setFormatter(formatter) logger.addHandler(console_handle)

37.232558

135

0.553716