code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
import os
import numpy as np
from keras.models import Sequential, Model
from keras.layers import Dense, Dropout, Flatten, concatenate
from keras.layers import Conv2D, MaxPooling2D, GlobalAveragePooling2D, Activation
from keras.layers.normalization import BatchNormalization
from keras.optimizers import SGD
from keras.... | normal | {
"blob_id": "ebc050544da69837cc2b8977f347380b94474bab",
"index": 576,
"step-1": "<mask token>\n\n\ndef _build(_input, *nodes):\n x = _input\n for node in nodes:\n if callable(node):\n x = node(x)\n elif isinstance(node, list):\n x = [_build(x, branch) for branch in node]... | [
1,
2,
3,
4,
5
] |
# -*- encoding: utf-8 -*-
import requests
import time
import random
STATS = True
INFINITE = True
VOTING_ENDPOINT = 'http://www.adressa.no/poll/vote.do'
# These are the required fields from the voting form
payload = {
"vote": "svar4",
"mentometerId": "10790638",
"publicationId": "167",
"redirectTo": "... | normal | {
"blob_id": "1e344330b88b336598295e2a7be6a6dc57cb3d59",
"index": 8207,
"step-1": "# -*- encoding: utf-8 -*-\n\nimport requests\nimport time\nimport random\n\nSTATS = True\nINFINITE = True\nVOTING_ENDPOINT = 'http://www.adressa.no/poll/vote.do'\n\n# These are the required fields from the voting form\npayload = {\... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
forbidden = ['Key.esc', 'Key.cmd', 'Key.cmd_r', 'Key.menu', 'Key.pause',
'Key.scroll_lock', 'Key.print_screen', 'Key.enter', 'Key.space',
'Key.backspace', 'Key.ctrl_l', 'Key.ctrl_r', 'Key.alt_l', 'Key.alt_gr',
'Key.caps_lock', 'Key.num_lock', 'Key... | flexible | {
"blob_id": "995dc34ea32de4566e2804b6797d9b551b733ff3",
"index": 3406,
"step-1": "<mask token>\n",
"step-2": "forbidden = ['Key.esc', 'Key.cmd', 'Key.cmd_r', 'Key.menu', 'Key.pause',\n 'Key.scroll_lock', 'Key.print_screen', 'Key.enter', 'Key.space',\n 'Key.backspace', 'Key.ctrl_l', 'Key.ctrl_r', 'Key.alt... | [
0,
1
] |
import os
os.environ.setdefault('DJANGO_SETTINGS_MODULE','mkrandom.settings')
import django
django.setup()
from main.models import Character, Vehicle, Tire, Glider
char_names = [
'Mario',
'Luigi',
'Peach',
'Daisy',
'Rosalina',
'Mario Tanooki',
'Peach cat',
'Yoshi',
'Yoshi (LBlue)',
... | normal | {
"blob_id": "dbda5df7dff3f8acc320ffe7b9c7c279ebed2cc2",
"index": 7108,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nos.environ.setdefault('DJANGO_SETTINGS_MODULE', 'mkrandom.settings')\n<mask token>\ndjango.setup()\n<mask token>\nfor char in char_names:\n index = x - y + 1\n name = char_names[x]\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def watch():
print('시청하다')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def watch():
print('시청하다')
watch()
print('tv.py의 module 이름은', __name__)
<|reserved_special_token_1|>
def watch():
print("시청하다")
watch()
print("tv.py의 m... | flexible | {
"blob_id": "b9622bede471c76ae36d3f59130d2be113310d4c",
"index": 7045,
"step-1": "<mask token>\n",
"step-2": "def watch():\n print('시청하다')\n\n\n<mask token>\n",
"step-3": "def watch():\n print('시청하다')\n\n\nwatch()\nprint('tv.py의 module 이름은', __name__)\n",
"step-4": "def watch():\n print(\"시청하다\")\... | [
0,
1,
2,
3
] |
#!/usr/bin/python
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
occl_frac = 0.445188
result = [1-occl_frac, occl_frac, 0]
#Reading res_data.txt
mnfa = [0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9] #min NN factor array
nna = [2,3,4,5,6,7,8,9,10,11,12,1... | normal | {
"blob_id": "1c8b843174521f1056e2bac472c87d0b5ec9603e",
"index": 3370,
"step-1": "#!/usr/bin/python\nimport matplotlib.pyplot as plt\nfrom matplotlib import cm\nfrom mpl_toolkits.mplot3d import Axes3D\nimport numpy as np\n\noccl_frac = 0.445188\nresult = [1-occl_frac, occl_frac, 0]\n\n#Reading res_data.txt\nmnfa... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
parser.add_argument('-u', '--user')
parser.add_argument('-c', '--color')
<|reserved_special_token_0|>
print(combined['color'])
print(combined['user'])
<|reserved_special_token_1|>
<|reserved_special_token_0|>
defaults = {'color... | flexible | {
"blob_id": "3c31e3f2a6f320bc5ae33f0ba1d234a089371899",
"index": 9199,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nparser.add_argument('-u', '--user')\nparser.add_argument('-c', '--color')\n<mask token>\nprint(combined['color'])\nprint(combined['user'])\n",
"step-3": "<mask token>\ndefaults = {'colo... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Solution:
def sortElemsByFrequency(self, arr):
if arr:
x = []
res = []
mydict = {}
for k, v in enumerate(arr):
mydict[v] = mydict.get(v, 0) + 1
for k, v in mydict.items():
heapq.... | flexible | {
"blob_id": "dcb12e282962c63f8e7de5d29c4c81ad177a387e",
"index": 7775,
"step-1": "<mask token>\n\n\nclass Solution:\n\n def sortElemsByFrequency(self, arr):\n if arr:\n x = []\n res = []\n mydict = {}\n for k, v in enumerate(arr):\n mydict[v] =... | [
2,
3,
4,
5,
6
] |
#from tinyTensor.Node import Node
import tinyTensor
import plotly.plotly as py
from graphviz import render
#from tinyTensor.Operation import Operation
def init():
global _default_graph
_default_graph = None
def postOrder(node):
nodes_postorder = []
def recurse(node):
if isinstan... | normal | {
"blob_id": "7bd2a29bff1e435cf813dd54109d7f4e17612425",
"index": 474,
"step-1": "<mask token>\n\n\nclass Graph:\n <mask token>\n\n def appendNode(self, node):\n if node.name in self.placeholderNames and node.isPlaceholder:\n raise Exception(\n 'Placeholder name \"{}\" is al... | [
5,
7,
8,
9,
10
] |
from ttkwidgets import CheckboxTreeview
from tkinter import *
from tkinter.ttk import *
from tkinter import messagebox
import json
import os
from DbDataloader import *
class DataLoader():
def __init__(self,master):
self.anne={}
self.master=Toplevel(master)
master.wait_visibility(self.master)... | normal | {
"blob_id": "a70dae504a4dfa3997a11e4c605accfab0024318",
"index": 8796,
"step-1": "<mask token>\n\n\nclass DataLoader:\n <mask token>\n\n def main(self):\n choice = messagebox.askyesno('askquestion',\n 'Cliquer sur Oui pour charger les données en mode Trasactionnel')\n if choice:\n ... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
def multi_set_symmetric_difference(sets):
return list(functools.reduce(lambda a, b: a ^ b, [set(s) for s in sets]))
def flood_iteration_plaquettes(l, plaquettes):
return set(plaquettes) | set(it.chain.from_iterable(l.plaquettes[p].
adjacent_plaquettes for p in plaquettes... | flexible | {
"blob_id": "d429f03c0f0c241166d6c0a5a45dc1101bcaec16",
"index": 5878,
"step-1": "<mask token>\n\n\ndef multi_set_symmetric_difference(sets):\n return list(functools.reduce(lambda a, b: a ^ b, [set(s) for s in sets]))\n\n\ndef flood_iteration_plaquettes(l, plaquettes):\n return set(plaquettes) | set(it.cha... | [
3,
4,
5,
6,
7
] |
import os
from flask import request, jsonify
from flask_api import FlaskAPI
from flask_api.exceptions import NotAcceptable
from dotenv import load_dotenv
load_dotenv(dotenv_path='./.env')
from src.service.jira import jira
from src.service.helper import helper
application = FlaskAPI(__name__)
jiraservice = jira()
help... | normal | {
"blob_id": "72e03e7199044f3ed1d562db622a7b884fa186b0",
"index": 2206,
"step-1": "<mask token>\n\n\n@application.route('/')\ndef hello_world():\n return jsonify({'Hello': 'World'})\n\n\n<mask token>\n",
"step-2": "<mask token>\nload_dotenv(dotenv_path='./.env')\n<mask token>\n\n\n@application.route('/')\nde... | [
1,
3,
4,
5,
6
] |
import os
import sys
import random
import string
trainingData = open('./Data.txt').readlines()
# Used for storing the Markov states
table = {}
# Stores all the words
words = []
# The size of the tuple that represents the Markov State
ChainLength = 2
# Length of hte output chain
Size = int(sys.argv[1])
if(len(sys.... | normal | {
"blob_id": "379ab72f5cc74cf6ed4319fff76437ce84aaca23",
"index": 4185,
"step-1": "import os\nimport sys\nimport random\nimport string\n\n\ntrainingData = open('./Data.txt').readlines()\n\n# Used for storing the Markov states\ntable = {} \n\n# Stores all the words\nwords = []\n\n# The size of the tuple that repre... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
cv2.putText(image, 'Hello World!', (75, 290), cv2.FONT_HERSHEY_COMPLEX, 2,
(100, 170, 0), 3)
cv2.imshow('Hello World!', image)
cv2.imwrite('Text.jpg', image)
cv2.waitKey(0)
cv2.destroyAllWindows()
<|reserved_special_token_1|... | flexible | {
"blob_id": "693f2a56578dfb1e4f9c73a0d33c5585070e9f9e",
"index": 5371,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncv2.putText(image, 'Hello World!', (75, 290), cv2.FONT_HERSHEY_COMPLEX, 2,\n (100, 170, 0), 3)\ncv2.imshow('Hello World!', image)\ncv2.imwrite('Text.jpg', image)\ncv2.waitKey(0)\ncv2.d... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class HandView:
<|reserved_special_token_0|>
def __init__(self, controller, display, ruleset):
self.controller = controller
self.display = display
self.ruleset = ruleset
self.Meld_Threshold = controller._state.rules.Meld_Threshold
self.deal... | flexible | {
"blob_id": "1cdd315eec6792a8588dc2e6a221bc024be47078",
"index": 7885,
"step-1": "<mask token>\n\n\nclass HandView:\n <mask token>\n\n def __init__(self, controller, display, ruleset):\n self.controller = controller\n self.display = display\n self.ruleset = ruleset\n self.Meld_T... | [
7,
9,
11,
12,
13
] |
#! /usr/bin/env python
"""
Normalizes a vidoe by dividing against it's background.
See: BackgroundExtractor.py to get the background of a video.
USING:
As a command line utility:
$ Normalizer.py input_video input_image output_video
As a module:
from Normalizer import Normalizer
... | normal | {
"blob_id": "141e0f20ce912ecf21940f78e9f40cb86b91dc2b",
"index": 6121,
"step-1": "<mask token>\n\n\nclass Normalizer:\n <mask token>\n\n def imageFromArg(self, image):\n if isinstance(image, (str, unicode)):\n return cv2.imread(image, 0)\n else:\n return image\n\n def... | [
5,
7,
10,
11,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
import enter
import loginout
import roleinfo
import zhanyi
import package
<|reserved_special_token_1|>
import enter
import loginout
import roleinfo
import zhanyi
import package
#import matrix | flexible | {
"blob_id": "de665735f02c7569ab382fdc3e910d5d3ac05bb5",
"index": 9088,
"step-1": "<mask token>\n",
"step-2": "import enter\nimport loginout\nimport roleinfo\nimport zhanyi\nimport package\n",
"step-3": "import enter\nimport loginout\nimport roleinfo\nimport zhanyi\nimport package\n#import matrix",
"step-4"... | [
0,
1,
2
] |
import librosa
import soundfile
import os, glob
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.neural_network import MLPClassifier
from sklearn.metrics import accuracy_score
emotionsRavdessData = {
'01': 'neutral',
'02': 'calm',
'03': 'happy',
'04': 'sad',
'05'... | normal | {
"blob_id": "8cd54362680aa3a96babe100b9231f6f16b3f577",
"index": 6670,
"step-1": "<mask token>\n\n\ndef extract_feature(file_name, mfcc, chroma, mel):\n with soundfile.SoundFile(file_name) as file:\n X = file.read(dtype='float32')\n sample_rate = file.samplerate\n if chroma:\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [url('^$', CommentListAPIView.as_view(), name='list'), url(
'^(?P<pk>\\d+)/$', CommentDetailAPIView, name='detail')]
<|reserved_special_token_1|>
from django.conf.urls import url
from django.contrib import adm... | flexible | {
"blob_id": "e08820ff4fb35a3770fcb110ef7181aad1abbae5",
"index": 8778,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^$', CommentListAPIView.as_view(), name='list'), url(\n '^(?P<pk>\\\\d+)/$', CommentDetailAPIView, name='detail')]\n",
"step-3": "from django.conf.urls import url... | [
0,
1,
2,
3
] |
import os
import config as cfg
import numpy as np
class lfwdata():
def __init__(self):
self._pairs = []
pairs = open(os.path.join(cfg.LFW_IMAGEPATH, '../pairs.txt'))
pairs.readline()
for pair in pairs:
pair = pair.split()
if len(pair) == 3:
... | normal | {
"blob_id": "ccdd7a5e0a1de75762530a7cadd919a2ee753d18",
"index": 1758,
"step-1": "<mask token>\n\n\nclass lfwdata:\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass lfwdata:\n\n def __init__(self):\n self._pairs = []\n pairs = open(os.path.join(cfg.LFW_IMAGEPATH, '../p... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = 'Brice Chou'
import os
import lib
import sys
import time
import getopt
import training
try:
import cv2
import h5py
except Exception as e:
error_info = 'Please install h5py/cv2 tools first. Error: {}.\n'.format(e)
print('\033[0;31m%s\033[0m' ... | normal | {
"blob_id": "398263b65fd98003f27020e46ae38e913dc5dd45",
"index": 323,
"step-1": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n__author__ = 'Brice Chou'\n\nimport os\nimport lib\nimport sys\nimport time\nimport getopt\nimport training\n\ntry:\n import cv2\n import h5py\nexcept Exception as e:\n err... | [
0
] |
import csv
import os
from collections import namedtuple
from typing import List, Dict
from config import *
HEADER = ['File', 'LKHContigs', 'LKHValue', 'LKHTime', 'APContigs', 'APValue', 'APTime', 'ActualObjectiveValue']
Assembly_Stats = namedtuple('Assembly_Stats', HEADER)
dir = '/home/andreas/GDrive/workspace/spars... | normal | {
"blob_id": "edd98e3996b0fce46d33dd33340018ab5b029637",
"index": 2333,
"step-1": "<mask token>\n\n\ndef read_assembly_file(file: str) ->List:\n if not os.path.isfile(file):\n return [-1, -1, -1, -1, -1, -1]\n with open(file, 'r') as f:\n file_content_string = f.read()\n if 'LKH_Contigs... | [
5,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
class UtilTestCase(TestCase):
<|reserved_special_token_0|>
def test_get_tree_queryset(self):
qs = get_tree_queryset(Country)
self.assertEqual(len(qs), 257)
self.assertEqual(qs[0].name, 'root')
qs = get_tree_queryset(Country, node_id=Country.objects... | flexible | {
"blob_id": "ac5c4edda8a5df7abc030fd637866fa4c8fc4bfc",
"index": 1493,
"step-1": "<mask token>\n\n\nclass UtilTestCase(TestCase):\n <mask token>\n\n def test_get_tree_queryset(self):\n qs = get_tree_queryset(Country)\n self.assertEqual(len(qs), 257)\n self.assertEqual(qs[0].name, 'root... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def program_skeleton(dictionary: dict):
if dictionary['tasks']['environmental_vars']['run'] == True:
dictionary['tasks']['environmental_vars']['log'][
'environmental_vars_set'] = lv.set_environmental_vars... | flexible | {
"blob_id": "6a8007e44d2c4b56426cd49772cbc23df2eca49c",
"index": 6917,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef program_skeleton(dictionary: dict):\n if dictionary['tasks']['environmental_vars']['run'] == True:\n dictionary['tasks']['environmental_vars']['log'][\n 'envi... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def decode_page(page_bytes, charsets=('utf-8',)):
"""通过指定的字符集对页面进行解码(不是每个网站都将字符集设置为utf-8)"""
page_html = None
for charset in charsets:
try:
page_html = page_bytes.decode(charset)
break
except UnicodeDecodeError:
pass
retu... | flexible | {
"blob_id": "53fae0103168f4074ba0645c33e4640fcefdfc96",
"index": 731,
"step-1": "<mask token>\n\n\ndef decode_page(page_bytes, charsets=('utf-8',)):\n \"\"\"通过指定的字符集对页面进行解码(不是每个网站都将字符集设置为utf-8)\"\"\"\n page_html = None\n for charset in charsets:\n try:\n page_html = page_bytes.decode(c... | [
5,
6,
7,
8,
9
] |
import socket
from threading import Thread
from ast import literal_eval
clients = {}
addresses = {}
host = '127.0.0.1'
port = 5678
active = []
addr = (host, port)
server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
server.bind(addr)
groups = []
def broadcast(msg, prefix=""): # prefix is for name identificatio... | normal | {
"blob_id": "9f02313b6f91f83e3a8b4af8d9447b1d8f3558f6",
"index": 4430,
"step-1": "<mask token>\n\n\ndef broadcast(msg, prefix=''):\n \"\"\"Broadcasts a message to all the clients.\"\"\"\n for sock in clients:\n sock.send(bytes(prefix, 'utf8') + msg)\n\n\ndef broadcast_file(msg):\n for sock in cli... | [
5,
6,
7,
8,
9
] |
import os
bind = '0.0.0.0:8000'
workers = os.environ['GET_KEYS_ACCOUNTS_WORKERS']
| normal | {
"blob_id": "d84a7e16471c604283c81412653e037ecdb19102",
"index": 3530,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nbind = '0.0.0.0:8000'\nworkers = os.environ['GET_KEYS_ACCOUNTS_WORKERS']\n",
"step-3": "import os\nbind = '0.0.0.0:8000'\nworkers = os.environ['GET_KEYS_ACCOUNTS_WORKERS']\n",
"step-4... | [
0,
1,
2
] |
"""
Django settings for geobombay project.
For more information on this file, see
https://docs.djangoproject.com/en/1.7/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.7/ref/settings/
"""
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
... | normal | {
"blob_id": "32ca107fde4c98b61d85f6648f30c7601b31c7f3",
"index": 3182,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n SECRET_KEY\nexcept NameError:\n SECRET_FILE = os.path.join(BASE_DIR, 'secret.txt')\n try:\n SECRET_KEY = open(SECRET_FILE).read().strip()\n except IOError:\n ... | [
0,
1,
2,
3,
4
] |
from flask_restful import Resource
from flask import jsonify, make_response, request
from ..models.Users import UsersModel
from ..models.Incidents import IncidentsModel
from app.api.validations.validations import Validations
class UsersView(Resource):
def __init__(self):
self.db = UsersModel()
def... | normal | {
"blob_id": "0188355f84054143bd4ff9da63f1128e9eb5b23b",
"index": 2244,
"step-1": "<mask token>\n\n\nclass LoginView(Resource):\n\n def __init__(self):\n self.db = UsersModel()\n self.user_db = IncidentsModel()\n\n def post(self):\n data = request.get_json()\n username = data['us... | [
8,
10,
11,
12,
14
] |
import os.path as path
from googleapiclient.discovery import build
from google.oauth2 import service_account
# If modifying these scopes, delete the file token.pickle.
SCOPES = ['https://www.googleapis.com/auth/spreadsheets.readonly']
# The ID and range of a sample spreadsheet.
SAMPLE_SPREADSHEET_ID = '1FSMATLJUNCbV8... | normal | {
"blob_id": "f9261c1844cc629c91043d1221d0b76f6e22fef6",
"index": 6157,
"step-1": "<mask token>\n\n\ndef main():\n service_account_json = path.join(path.dirname(path.abspath(__file__)),\n 'service_account.json')\n credentials = service_account.Credentials.from_service_account_file(\n service_a... | [
3,
5,
6,
7,
8
] |
import numpy as np
import random
import argparse
import networkx as nx
from gensim.models import Word2Vec
from utils import read_node_label, plot_embeddings
class node2vec_walk():
def __init__(self, nx_G, is_directed, p, q):
self.G = nx_G
self.is_directed = is_directed
self.p = p
... | normal | {
"blob_id": "fc2748d766ebce8c9577f1eebc8435e2aa58ae25",
"index": 8605,
"step-1": "<mask token>\n\n\nclass node2vec_walk:\n\n def __init__(self, nx_G, is_directed, p, q):\n self.G = nx_G\n self.is_directed = is_directed\n self.p = p\n self.q = q\n\n def node2vec_walk(self, walk_l... | [
7,
8,
12,
13,
15
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('IncomeHome/', views.IncomeHome, name='IncomeHome'),
path('IncomeCreate/', views.IncomeCreate.as_view(), name='IncomeCreate'
), path('IncomeUpdate/<int:pk>', views.IncomeUpdate.as_view(), name=
'Inc... | flexible | {
"blob_id": "ad3a7221883a847fc9d26097c3801973cbbda38e",
"index": 355,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('IncomeHome/', views.IncomeHome, name='IncomeHome'),\n path('IncomeCreate/', views.IncomeCreate.as_view(), name='IncomeCreate'\n ), path('IncomeUpdate/<int:pk>', ... | [
0,
1,
2,
3
] |
providers = {
'provider-1': {
'name': 'provider-1',
'roles': ['licensor', 'producer'],
'description': 'This is a full description of the provider',
'url': 'https://www.provider.com'
},
'provider-2': {
'name': 'provider-2',
'roles': ['licensor'],
'descr... | normal | {
"blob_id": "7801676df91a7ded6f123113acc62f3955dfe6cb",
"index": 7113,
"step-1": "<mask token>\n",
"step-2": "providers = {'provider-1': {'name': 'provider-1', 'roles': ['licensor',\n 'producer'], 'description':\n 'This is a full description of the provider', 'url':\n 'https://www.provider.com'}, 'pro... | [
0,
1,
2
] |
# encoding=utf-8
######
# 遗传算法应用于旅行商问题(TSP)
# Python 3.6
# https://morvanzhou.github.io/tutorials/machine-learning/evolutionary-algorithm/2-03-genetic-algorithm-travel-sales-problem/
######
| normal | {
"blob_id": "e79e4eb1640d5ad6e360dfb18430fbf261cf9d3b",
"index": 6675,
"step-1": "# encoding=utf-8\n\n######\n# 遗传算法应用于旅行商问题(TSP)\n# Python 3.6\n# https://morvanzhou.github.io/tutorials/machine-learning/evolutionary-algorithm/2-03-genetic-algorithm-travel-sales-problem/\n######\n\n",
"step-2": null,
"step-3"... | [
1
] |
#!/usr/bin/env python3
import sys
class Parse:
data = []
def __parseLine(line):
"""Parse the given line"""
# extract name
name_len = line.index(" ")
name = line[:name_len]
line = line[name_len + 3:]
# array-ize 'electron' val
elec_pos = line.index("e... | normal | {
"blob_id": "cb77696a90716acdee83a1cf6162a8f42c524e11",
"index": 7612,
"step-1": "<mask token>\n\n\nclass Write:\n\n def __writeHeader(fd):\n \"\"\"Write html header\"\"\"\n print('<!DOCTYPE html>', '<html>', ' <head>',\n ' <title>Super Tableau 3000</title>',\n \" <meta c... | [
8,
11,
12,
13,
16
] |
from database import db
from database import ma
from datetime import datetime
from sqlalchemy import ForeignKeyConstraint
from models.admin import Admin, admin_limited_schema
from models.event_status import EventStatus, event_status_schema
from models.org_unit import org_unit_schema
class Event(db.Model):
# class ... | normal | {
"blob_id": "f3167d8f1a806c38fb10672605d8e94265d2fc9c",
"index": 723,
"step-1": "<mask token>\n\n\nclass Event(db.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask ... | [
4,
6,
7,
8,
9
] |
#------------------------------------------------------------------------
#
# @Author : EV2 CHEVALLIER
#
# @Date : 16.09.20
# @Location : École Navale / Chaire de Cyberdéfense des systèmes navals
# @Project : Projet de Fin d'Études
# @Subject : # Real time detection of cyber anomalies upon a NMEA network by using mach... | normal | {
"blob_id": "6726c8f1b3ef9a0df74c25c1921203af3aaacb12",
"index": 8758,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef training(dict):\n model = {}\n model['µ'] = {}\n model['sigma'] = {}\n for x in dict:\n model['µ'][x] = {}\n model['sigma'][x] = {}\n for y in dic... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
import json
import os
import io
import shutil
import pytest
from chi_annotator.algo_factory.common import TrainingData
from chi_annotator.task_center.config import AnnotatorConfig
from chi_annotator.task_center.data_loader import load_local_data
from chi_annotator.task_center.model import Inte... | normal | {
"blob_id": "192c44540018b9e1ab857bdbfba6fdb39bb74431",
"index": 8769,
"step-1": "<mask token>\n\n\nclass TestTrainer(object):\n <mask token>\n\n @classmethod\n def teardown_class(cls):\n \"\"\" teardown any state that was previously setup with a call to\n setup_class.\n \"\"\"\n ... | [
10,
12,
13,
14,
16
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def euclidean(p, q):
sumSq = 0.0
for i in range(len(p)):
sumSq += (p[i] - q[i]) ** 2
return sumSq ** 0.5
<|reserved_special_token_1|>
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# ユークリッド距離
# http://en.wikipedia.org/wiki/Euclidean_spa... | flexible | {
"blob_id": "11a7ebac3dad1f91a6d46b62f557b51ded8e3d7a",
"index": 1271,
"step-1": "<mask token>\n",
"step-2": "def euclidean(p, q):\n sumSq = 0.0\n for i in range(len(p)):\n sumSq += (p[i] - q[i]) ** 2\n return sumSq ** 0.5\n",
"step-3": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n# ユーク... | [
0,
1,
2
] |
# coding: utf-8
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
driver = webdriver.Chrome()
driver.get("https://www.baidu.com")
elem = driver.find_element_by_xpath('//*[@id="kw"]')
elem.send_keys("python selenium", Keys.ENTER)
print(driver.page_source)
| normal | {
"blob_id": "3c8352ff2fc92ada1b58603df2a1a402e57842be",
"index": 8606,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndriver.get('https://www.baidu.com')\n<mask token>\nelem.send_keys('python selenium', Keys.ENTER)\nprint(driver.page_source)\n",
"step-3": "<mask token>\ndriver = webdriver.Chrome()\ndri... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
config = {'numIndividuals': 50, 'maxNumGen': 20, 'eliteProp': 0.1,
'mutantProp': 0.2, 'inheritanceProb': 0.7}
| flexible | {
"blob_id": "85d1069d85e285bc5c36811f569dabd793b5064b",
"index": 4460,
"step-1": "<mask token>\n",
"step-2": "config = {'numIndividuals': 50, 'maxNumGen': 20, 'eliteProp': 0.1,\n 'mutantProp': 0.2, 'inheritanceProb': 0.7}\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1... | [
0,
1
] |
<|reserved_special_token_0|>
class Book:
def __init__(self, url):
self.url = url
self.title = ''
self.category = ''
self.upc = ''
self.price_including_tax = ''
self.price_excluding_tax = ''
self.number_available = ''
self.description = ''
se... | flexible | {
"blob_id": "3dc83168264fbb4f9b0ab2980b845dffdc4417bb",
"index": 7588,
"step-1": "<mask token>\n\n\nclass Book:\n\n def __init__(self, url):\n self.url = url\n self.title = ''\n self.category = ''\n self.upc = ''\n self.price_including_tax = ''\n self.price_excluding_... | [
11,
12,
13,
15,
16
] |
import numpy as np
a = np.ones((3,4))
b = np.ones((4,1))
# a.shape = (3,4)
# b.shape = (4,1)
c = np.zeros_like(a)
for i in range(3):
for j in range(4):
c[i][j] = a[i][j] + b[j]
print(c)
d = a+b.T
print(d)
| normal | {
"blob_id": "d6213698423902771011caf6b5206dd4e3b27450",
"index": 5753,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(3):\n for j in range(4):\n c[i][j] = a[i][j] + b[j]\nprint(c)\n<mask token>\nprint(d)\n",
"step-3": "<mask token>\na = np.ones((3, 4))\nb = np.ones((4, 1))\nc =... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class IndexSetter(BaseEstimator, TransformerMixin):
""" Set index """
def __init__(self, index_cols, drop_existing):
self.index_cols = index_cols
self.drop_existing = drop_existing
def fit(self, X, y=None):
return self
def transform(self, X):
... | flexible | {
"blob_id": "9f7b1cfcc3c20910201fc67b5a641a5a89908bd1",
"index": 8980,
"step-1": "<mask token>\n\n\nclass IndexSetter(BaseEstimator, TransformerMixin):\n \"\"\" Set index \"\"\"\n\n def __init__(self, index_cols, drop_existing):\n self.index_cols = index_cols\n self.drop_existing = drop_exist... | [
41,
44,
52,
56,
62
] |
from django.apps import AppConfig
class AttendaceConfig(AppConfig):
name = 'attendace'
| normal | {
"blob_id": "d5d61b23dc14ffdfe7fe6f983164916863928eaf",
"index": 3685,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass AttendaceConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass AttendaceConfig(AppConfig):\n name = 'attendace'\n",
"step-4": "from django.apps impo... | [
0,
1,
2,
3
] |
from celery_app import celery_app
@celery_app.task
def demo_celery_run():
return 'result is ok'
| normal | {
"blob_id": "4bb973b598a9c35394a0cd78ed9ba807f3a595d7",
"index": 2323,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@celery_app.task\ndef demo_celery_run():\n return 'result is ok'\n",
"step-3": "from celery_app import celery_app\n\n\n@celery_app.task\ndef demo_celery_run():\n return 'resul... | [
0,
1,
2
] |
import glob
import xarray as xr
from model_diagnostics import *
data_root = '../data/synthetic/standard/'
var_list = ['hs', 'dp', 'spr', 'fp', 'dir', 't0m1']
eke = 0.01
##########################
output = []
diagnostic_functions = [basic_stats]
for var in var_list:
grid_files = glob.glob(data_root+'gridded/*%s*%s... | normal | {
"blob_id": "6b727cdfc684db4ba919cd5390fe45de43a806fe",
"index": 309,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor var in var_list:\n grid_files = glob.glob(data_root + 'gridded/*%s*%s.nc' % (eke, var))\n for f in grid_files:\n output.append(analize_member(f, var, diagnostic_functions)... | [
0,
1,
2,
3,
4
] |
""" Interfaces to Juju API ModelManager """
from conjureup import juju
@juju.requires_login
def list_models(user='user-admin'):
""" Lists Juju Models
Arguments:
user: Name of user to list models for.
Returns:
Dictionary of known Juju Models (default: user-admin)
"""
models = juju.CLIENT... | normal | {
"blob_id": "11045cffc6d47902be7236e1d684422317f2c5f9",
"index": 1444,
"step-1": "<mask token>\n\n\n@juju.requires_login\ndef list_models(user='user-admin'):\n \"\"\" Lists Juju Models\n\n Arguments:\n user: Name of user to list models for.\n\n Returns:\n Dictionary of known Juju Models (default: ... | [
1,
2,
3,
4,
5
] |
# Imports
from __future__ import print_function
import numpy
from numpy.random import randint
from enum import Enum
__all__ = ["common", "plot"]
class result(Enum):
CRIT = 16
HIT = 8
EVADE = 4
FOCUS = 2
BLANK = 1
def result_str(res):
str = ""
if res & result.BLANK:
str += "BLANK"
i... | normal | {
"blob_id": "5261346f96e7520b6ef75a292b3d44a6f00d868c",
"index": 5566,
"step-1": "<mask token>\n\n\nclass result(Enum):\n CRIT = 16\n HIT = 8\n EVADE = 4\n FOCUS = 2\n BLANK = 1\n\n\n<mask token>\n\n\nclass die:\n\n def __init__(self):\n self.rerolled = False\n\n def __str__(self):\n ... | [
24,
26,
29,
33,
38
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('\n'.join(re.findall(
'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+'
, sys.stdin.read())))
<|reserved_special_token_1|>
import sys, re
print('\n'.join(re.findall(
'http[s]?:... | flexible | {
"blob_id": "4cefaa964251e77a05066af1f61f9fd2a4350d38",
"index": 7622,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('\\n'.join(re.findall(\n 'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\\\(\\\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+'\n , sys.stdin.read())))\n",
"step-3": "import sys, re\nprint(... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ConcatZeroPadding(OptimizeRule):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ConcatZeroPadding(OptimizeRule):
def optimize(self, graph: Graph) ->Tuple[Graph, b... | flexible | {
"blob_id": "687f7f4908e8a5448335f636edf74a627f03c306",
"index": 9110,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ConcatZeroPadding(OptimizeRule):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass ConcatZeroPadding(OptimizeRule):\n\n def optimize(self, graph: Graph) ->Tuple[Grap... | [
0,
1,
2,
3,
4
] |
from . import *
from module import *
from transfer import *
from dataset import *
| normal | {
"blob_id": "94d992ef4b9015aa8f42071bb1409703d509c313",
"index": 9810,
"step-1": "<mask token>\n",
"step-2": "from . import *\nfrom module import *\nfrom transfer import *\nfrom dataset import *\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
import pydgm
import numpy as np
import sys
class XS():
# Hold the cross section values with routines for outputting to txt file
def __init__(self, sig_t, sig_f, chi, sig_s, mu=None):
self.sig_t = sig_t
self.sig_f = sig_f
self.chi = chi
self.sig_s = sig_s
self.mu = mu i... | normal | {
"blob_id": "1358adc3b2b3ffe72c0ed87fb0024f1079ca7d04",
"index": 1710,
"step-1": "<mask token>\n\n\nclass DGMSOLVER:\n\n def __init__(self, G, fname, fm, cm, mm, nPin, norm=None, mapping=None,\n vacuum=False, k=None, phi=None, psi=None):\n \"\"\"\n Inputs:\n G - Number of e... | [
6,
8,
9,
11,
13
] |
# -*- coding: utf-8 -*-
import sys
#from Constants import *
# start
import CrudMatrixDao
class CrudAccessValue:
def __init__(self):
self.crudAccessValue = {}
self.__run()
def __run(self):
aCrudMatrixDao = CrudMatrixDao.CrudMatrixDao()
# print aCrudMatrixDao.selectCrudAccessValueAction()
... | normal | {
"blob_id": "38e616e35f165d458d774dd0b6837a733b8402d7",
"index": 1555,
"step-1": "# -*- coding: utf-8 -*-\r\nimport sys\r\n#from Constants import *\r\n# start\r\nimport CrudMatrixDao\r\n\r\nclass CrudAccessValue:\r\n\tdef __init__(self):\r\n\t\tself.crudAccessValue = {}\r\n\t\tself.__run()\r\n\t\t\r\n\tdef __ru... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with onto:
class Pizza(Thing):
pass
class MeatPizza(Pizza):
pass
class Topping(Thing):
pass
class has_Topping((Pizza >> Topping)):
pass
print(Pizza)
<|reserved_special_token_... | flexible | {
"blob_id": "cc7f1f38efcd4d757c1d11e2bd53695fca44e15a",
"index": 212,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith onto:\n\n\n class Pizza(Thing):\n pass\n\n\n class MeatPizza(Pizza):\n pass\n\n\n class Topping(Thing):\n pass\n\n\n class has_Topping((Pizza >> Toppi... | [
0,
1,
2,
3,
4
] |
import logging as log
from time import monotonic
import re
from jmap.account import ImapAccount
import jmap.core as core
import jmap.mail as mail
import jmap.submission as submission
import jmap.vacationresponse as vacationresponse
import jmap.contacts as contacts
import jmap.calendars as calendars
from jmap import er... | normal | {
"blob_id": "aac3b2478980d3a5453451cb848afcfd6aca1743",
"index": 1680,
"step-1": "<mask token>\n\n\ndef handle_request(user, data):\n results = []\n resultsByTag = {}\n api = Api(user, data.get('createdIds', None))\n for capability in data['using']:\n CAPABILITIES[capability].register_methods(... | [
6,
7,
8,
9,
10
] |
#!/bin/python3
import socket
HOST = '127.0.0.1'
PORT= 4444
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.connect((HOST,PORT)) | normal | {
"blob_id": "14a39b9aa56777c8198794fe2f51c9a068500743",
"index": 4075,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ns.connect((HOST, PORT))\n",
"step-3": "<mask token>\nHOST = '127.0.0.1'\nPORT = 4444\ns = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\ns.connect((HOST, PORT))\n",
"step-4": "imp... | [
0,
1,
2,
3,
4
] |
#@@range_begin(list1) # ←この行は無視してください。本文に引用するためのものです。
#ファイル名 Chapter07/0703person.py
# __metaclass__ = type #← python 2を使っている場合は行頭の「#」を取る
class Person:
def set_name(self, name):
self.name = name
def get_name(self):
return self.name
def greet(self): # あいさつをする
print(f"こんにちは。私は{self... | normal | {
"blob_id": "321dc411b003949a6744216a13c59c70d919a675",
"index": 8402,
"step-1": "class Person:\n <mask token>\n\n def get_name(self):\n return self.name\n\n def greet(self):\n print(f'こんにちは。私は{self.name}です。')\n\n\n<mask token>\n",
"step-2": "class Person:\n\n def set_name(self, name)... | [
3,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
# упражнение выполнено на Python 3
manual_calc = 53 + 1.0/3
def trapezoidal(f, a, b, n):
h = float(b - a)/n
result = 0.5*(f(a) + f(b))
for i in range(1, n):
result += f(a + i*h)
result *= h
return result
def rectangular(f, a, b, n):
h = float(b - a)/n
result = f(a+0.5*h)
for ... | normal | {
"blob_id": "4fbf5b4520aa4dca4c7cc80d56ba00f634d184bf",
"index": 3405,
"step-1": "<mask token>\n\n\ndef rectangular(f, a, b, n):\n h = float(b - a) / n\n result = f(a + 0.5 * h)\n for i in range(1, n):\n result += f(a + 0.5 * h + i * h)\n result *= h\n return result\n\n\n<mask token>\n",
... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
janela.title('Teste de frame')
janela.geometry('800x600')
<|reserved_special_token_0|>
Label(frame, text='lsdakçasd').grid(row=0, column=0)
janela.mainloop()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
janela = Tk... | flexible | {
"blob_id": "4ae24d1e39bdcde3313a8a0c8029a331864ba40e",
"index": 6985,
"step-1": "<mask token>\n",
"step-2": "<mask token>\njanela.title('Teste de frame')\njanela.geometry('800x600')\n<mask token>\nLabel(frame, text='lsdakçasd').grid(row=0, column=0)\njanela.mainloop()\n",
"step-3": "<mask token>\njanela = T... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def load_data(data):
temp = []
for i in range(len(data)):
im = cv2.imread(data[i])
im = misc.imresize(im, size=DOWNSAMPLE_RATIO)
im = crop(im)
temp.append(im)
return temp
def normalize(data):
a = -0.5
b = 0.5
greyscale_min = 0
... | flexible | {
"blob_id": "b109568c4dba05b16cbed1759a2b9e0a99babc67",
"index": 2982,
"step-1": "<mask token>\n\n\ndef load_data(data):\n temp = []\n for i in range(len(data)):\n im = cv2.imread(data[i])\n im = misc.imresize(im, size=DOWNSAMPLE_RATIO)\n im = crop(im)\n temp.append(im)\n ret... | [
8,
10,
12,
16,
19
] |
<|reserved_special_token_0|>
class TestListDiff(TestCase):
<|reserved_special_token_0|>
def test_two(self):
assert list_diff([1, 2, 2, 2, 3], [2]) == [1, 3]
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class TestDiffLR(TestCase):
def test_one(self):
assert list_diff_... | flexible | {
"blob_id": "76526bdff7418997ac90f761936abccbb3468499",
"index": 6513,
"step-1": "<mask token>\n\n\nclass TestListDiff(TestCase):\n <mask token>\n\n def test_two(self):\n assert list_diff([1, 2, 2, 2, 3], [2]) == [1, 3]\n <mask token>\n\n\n<mask token>\n\n\nclass TestDiffLR(TestCase):\n\n def ... | [
6,
8,
9,
10,
12
] |
<|reserved_special_token_0|>
class floatlayoutApp(App):
def build(self):
return LayoutWindow()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class LayoutWindow(FloatLayout):
pass
class floatlayoutApp(App):
def build(self):
return LayoutWi... | flexible | {
"blob_id": "2af8677e76b77b9bfa579012a85ea331c0c7f390",
"index": 136,
"step-1": "<mask token>\n\n\nclass floatlayoutApp(App):\n\n def build(self):\n return LayoutWindow()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass LayoutWindow(FloatLayout):\n pass\n\n\nclass floatlayoutApp(App):\n\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(stevila)
print(stevila[1])
<|reserved_special_token_1|>
stevila = [5, 2, 8, 3]
print(stevila)
print(stevila[1])
<|reserved_special_token_1|>
stevila = [5, 2, 8, 3]
#Izpis vseh števil
print(stevila)
#Izpis števila na ... | flexible | {
"blob_id": "6e845f2543b548fb936cc3719eb150e530281945",
"index": 9505,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(stevila)\nprint(stevila[1])\n",
"step-3": "stevila = [5, 2, 8, 3]\nprint(stevila)\nprint(stevila[1])\n",
"step-4": "stevila = [5, 2, 8, 3]\n\n#Izpis vseh števil\nprint(stevila)\... | [
0,
1,
2,
3
] |
from django import forms
class LoginForm(forms.Form):
usuario=forms.CharField(label="Usuario",max_length=20, required=True, widget=forms.TextInput(
attrs={'class':'form-control'}
))
contraseña=forms.CharField(label="Contraseña",max_length=20, widget=forms.PasswordInput(
attrs={'class':'for... | normal | {
"blob_id": "7da5a7476c807619bed805cb892774c23c04c6f7",
"index": 4917,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass LoginForm(forms.Form):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass LoginForm(forms.Form):\n usuario = forms.CharField(label='Usuario', max_le... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(volume, surface_area)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
pi = 3.14159
r = 3.14
h = 5
volume = pi * r ** 2 * h
surface_area = 2 * pi * r ** 2 + r * h
print(volume, surface_area)
<|reserved_special_... | flexible | {
"blob_id": "d04e69c234f2887f5301e4348b4c4ec2ad3af7a2",
"index": 2623,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(volume, surface_area)\n",
"step-3": "<mask token>\npi = 3.14159\nr = 3.14\nh = 5\nvolume = pi * r ** 2 * h\nsurface_area = 2 * pi * r ** 2 + r * h\nprint(volume, surface_area)\n",... | [
0,
1,
2,
3
] |
import collections
import inspect
import struct
from pygments.token import *
import decompil.builder
import decompil.disassemblers
import decompil.ir
class Context(decompil.ir.Context):
def __init__(self):
super(Context, self).__init__(16)
self.pointer_type = self.create_pointer_type(self.half_... | normal | {
"blob_id": "865d7c606b287dbce158f721c6cf768cd078eb48",
"index": 9231,
"step-1": "<mask token>\n\n\nclass Register(decompil.ir.Register):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass BaseDecoder:\n name = None\n opcode = None\n op... | [
18,
24,
25,
29,
33
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def reverse(string):
if len(string) == 0:
return
temp = string[0]
reverse(string[1:])
print(temp, end='')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def ... | flexible | {
"blob_id": "d1ee33ce6fb071aae800b0597a09e7039a209ec8",
"index": 2574,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef reverse(string):\n if len(string) == 0:\n return\n temp = string[0]\n reverse(string[1:])\n print(temp, end='')\n\n\n<mask token>\n",
"step-3": "<mask token>\... | [
0,
1,
2,
3,
4
] |
# data={
# "name":"Alby",
# "age":23
# }
# print (data['age'])
# def foo():
# print("Hellow world")
# return 1
# print (foo())
a="aa"
def add():
print(a)
add() | normal | {
"blob_id": "97857c1c5468a96187d44abc23ffaaf2a7ead1a6",
"index": 1869,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef add():\n print(a)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef add():\n print(a)\n\n\nadd()\n",
"step-4": "a = 'aa'\n\n\ndef add():\n print(a)\n\n\nadd()\n"... | [
0,
1,
2,
3,
4
] |
import random
def main():
#print('You rolled a die')
return random.randint(1,6)
if __name__== "__main__":
main()
| normal | {
"blob_id": "6d92b944ab8503d3635626c0c23021fc2b40dce3",
"index": 5732,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n return random.randint(1, 6)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef main():\n return random.randint(1, 6)\n\n\nif __name__ == '__main__':\n mai... | [
0,
1,
2,
3,
4
] |
from django import forms
from django.contrib.auth.forms import UserCreationForm
from .models import AuthUser
class SignUpForm(forms.Form):
username = forms.CharField(widget=forms.TextInput(attrs={'class':
'form-control'}))
email = forms.EmailField(widget=forms.EmailInput(attrs={'class':
'form-... | normal | {
"blob_id": "7644dcd956e1ad179f42e44870864386744c6cdf",
"index": 2553,
"step-1": "<mask token>\n\n\nclass LoginForm(forms.Form):\n username = forms.CharField(widget=forms.TextInput(attrs={'class':\n 'form-control'}))\n password = forms.CharField(widget=forms.PasswordInput(attrs={'class':\n 'f... | [
2,
3,
4,
5
] |
a = [1, 1, 2, 3, 4, 4, 5, 7, 12, 30, 49]
for i in range(0, len(a)):
if a[i] < 5:
print(str(a[i]) + " ")
i += 1
else:
i += 1
| normal | {
"blob_id": "24635989ccdb0f35f1e618dd8dc07f2cf84faddb",
"index": 6621,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, len(a)):\n if a[i] < 5:\n print(str(a[i]) + ' ')\n i += 1\n else:\n i += 1\n",
"step-3": "a = [1, 1, 2, 3, 4, 4, 5, 7, 12, 30, 49]\nfor i in... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def pre_proc(INP_DIR):
INP_DIR = INP_DIR + '/'
NONE_DIR = os.path.dirname(INP_DIR) + '_none'
SQUARE_DIR = os.path.dirname(INP_DIR) + '_square'
CROP_DIR = os.path.dirname(INP_DIR) + '_cropped'
os.makedirs(NONE_DIR, exist_ok=True)
os.makedirs(SQUARE_DIR, exist_ok=Tru... | flexible | {
"blob_id": "4ad4cf46be735c6ac26b5b0953d4c2458f37496a",
"index": 9372,
"step-1": "<mask token>\n\n\ndef pre_proc(INP_DIR):\n INP_DIR = INP_DIR + '/'\n NONE_DIR = os.path.dirname(INP_DIR) + '_none'\n SQUARE_DIR = os.path.dirname(INP_DIR) + '_square'\n CROP_DIR = os.path.dirname(INP_DIR) + '_cropped'\n... | [
1,
2,
3,
4,
5
] |
# Python 2.7 Doritobot Vision System
# EECS 498 Purple Team, 2014
# Written by Cody Hyman (hymanc@umich.edu)
# Written against OpenCV 3.0.0-alpha
import sys
import os
import cv2
import numpy as np
from uvcinterface import UVCInterface as uvc
from visionUtil import VisionUtil as vu
from collections import deque
from ... | normal | {
"blob_id": "324030a976af29dc93fdb637583bfaab93671cc2",
"index": 8515,
"step-1": "# Python 2.7 Doritobot Vision System\n# EECS 498 Purple Team, 2014\n# Written by Cody Hyman (hymanc@umich.edu)\n# Written against OpenCV 3.0.0-alpha\n\nimport sys\nimport os\n\nimport cv2\nimport numpy as np\n\nfrom uvcinterface im... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@es_bot.event
async def on_ready():
print('es started')
@nas_bot.event
async def on_ready():
print('nas started')
@dow_bot.event
async def on_ready():
print('dow started')
@silver_bot.event
async def on_ready()... | flexible | {
"blob_id": "e57109f1c5c2e1468ef1cf9f10fba743633ca150",
"index": 8094,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@es_bot.event\nasync def on_ready():\n print('es started')\n\n\n@nas_bot.event\nasync def on_ready():\n print('nas started')\n\n\n@dow_bot.event\nasync def on_ready():\n prin... | [
0,
1,
2,
3,
4
] |
import re
text = 'Macademia nuts, Honey tuile, Cocoa powder, Pistachio nuts'
search_pattern = re.compile('nuts')
search_match_object = search_pattern.search(text)
if search_match_object:
print(search_match_object.span())
print(search_match_object.start())
print(search_match_object.end())
print(search_... | normal | {
"blob_id": "ef5d235f09eea827b240290218c397f880f1046d",
"index": 4433,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif search_match_object:\n print(search_match_object.span())\n print(search_match_object.start())\n print(search_match_object.end())\n print(search_match_object.group())\nprint... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(getsizeof(a))
<|reserved_special_token_0|>
print(getsizeof(c))
for b in a:
print(b)
print(sum(a))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
a = (b for b in range(10))
print(getsizeof(a))
c = [b for b i... | flexible | {
"blob_id": "2ee4b31f880441e87c437d7cc4601f260f34ae24",
"index": 6574,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(getsizeof(a))\n<mask token>\nprint(getsizeof(c))\nfor b in a:\n print(b)\nprint(sum(a))\n",
"step-3": "<mask token>\na = (b for b in range(10))\nprint(getsizeof(a))\nc = [b for... | [
0,
1,
2,
3,
4
] |
import json
import yaml
import argparse
import sys
def json2yaml(json_input, yaml_input):
json_data = json.load(open(json_input, 'r'))
yaml_file = open(yaml_input, 'w')
yaml.safe_dump(json_data, yaml_file, allow_unicode=True, default_flow_style=False)
yaml_data = yaml.load_all(open(yaml_input, 'r'), L... | normal | {
"blob_id": "5c15252611bee9cd9fbb5d91a19850c242bb51f1",
"index": 4940,
"step-1": "<mask token>\n\n\ndef json2yaml(json_input, yaml_input):\n json_data = json.load(open(json_input, 'r'))\n yaml_file = open(yaml_input, 'w')\n yaml.safe_dump(json_data, yaml_file, allow_unicode=True,\n default_flow_s... | [
2,
3,
4,
5,
6
] |
import datetime
import os
# os.getcwd()
class LMS: # This class is used to keep records of the books in the Library
def __init__(self, list_of_books, library_name):
self.list_of_books = "List_of_books.txt"
self.library_name = library_name
self.books_dict = {}
Id = 101
w... | normal | {
"blob_id": "1a2616472c8d432c91e2b48260cbae61d3ecfd90",
"index": 1746,
"step-1": "<mask token>\n\n\nclass LMS:\n <mask token>\n <mask token>\n\n def issue_books(self):\n books_id = input(\"Enter book's ID: \")\n current_date = datetime.datetime.now().strftime('%d-%m-%Y %H:%M:%S')\n ... | [
4,
5,
6,
7,
9
] |
<|reserved_special_token_0|>
class BinarySearchTree:
<|reserved_special_token_0|>
def __init__(self):
self._root = None
def __str__(self):
""" yield 迭代器 """
tree2list = [x.data for x in self._generate_node()]
return 'the BinarySearchTree is %s' % tree2list
def __bool... | flexible | {
"blob_id": "fa46bd784dcfeee4f9012ffb6ab6731d2764c9fa",
"index": 8484,
"step-1": "<mask token>\n\n\nclass BinarySearchTree:\n <mask token>\n\n def __init__(self):\n self._root = None\n\n def __str__(self):\n \"\"\" yield 迭代器 \"\"\"\n tree2list = [x.data for x in self._generate_node(... | [
15,
19,
26,
31,
34
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def home_admin(request):
"""
:view home_admin: Menu principale des Administrateurs
:template home_admin.html:
"""
if not request.user.is_authenticated():
return redirect('login')
title = 'Accueil'... | flexible | {
"blob_id": "b453c8e9cc50066d1b5811493a89de384a000f37",
"index": 4929,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef home_admin(request):\n \"\"\"\n :view home_admin: Menu principale des Administrateurs\n :template home_admin.html:\n \"\"\"\n if not request.user.is_authenticated()... | [
0,
1,
2,
3
] |
#
# cuneiform_python.py
#
# Example showing how to create a custom Unicode set for parsing
#
# Copyright Paul McGuire, 2021
#
from typing import List, Tuple
import pyparsing as pp
class Cuneiform(pp.unicode_set):
"""Unicode set for Cuneiform Character Range"""
_ranges: List[Tuple[int, ...]] = [
(0x10... | normal | {
"blob_id": "bc1aefd0b0a87b80a10cecf00407b4608a6902b5",
"index": 3897,
"step-1": "<mask token>\n\n\nclass Cuneiform(pp.unicode_set):\n <mask token>\n _ranges: List[Tuple[int, ...]] = [(66432, 66517), (73728, 74751), (\n 74752, 74879)]\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Cuneif... | [
1,
3,
4,
5,
6
] |
import numpy as np
import cv2
from camera import load_K, load_camera_dist, load_camera_ret
def undistort_img(img):
'''
Return an undistorted image given previous calibrated parameters
References from OpenCV docs
'''
ret = load_camera_ret()
K = load_K()
dist = load_camera_dist()
h,w = img.sha... | normal | {
"blob_id": "844c630d3fe2dda833064556228b524608cfece9",
"index": 4671,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef undistort_img(img):\n \"\"\"\n Return an undistorted image given previous calibrated parameters \n References from OpenCV docs\n \"\"\"\n ret = load_camera_ret()\n K =... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def main():
num = int(input('dia: '))
dia(num)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def main():
num = int(input('dia: '))
dia(num)
def dia(a):
if a == 1:
print('Domingo !')
elif a == 2:
print... | flexible | {
"blob_id": "07332e2da5458fda2112de2507037a759d3c62db",
"index": 3382,
"step-1": "<mask token>\n",
"step-2": "def main():\n num = int(input('dia: '))\n dia(num)\n\n\n<mask token>\n",
"step-3": "def main():\n num = int(input('dia: '))\n dia(num)\n\n\ndef dia(a):\n if a == 1:\n print('Dom... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def asymmetric_extend(q1, q2, extend_fn, backward=False):
if backward and ASYMETRIC:
return reversed(list(extend_fn(q2, q1)))
return extend_fn(q1, q2)
<|reserved_special_token_0|>
def calculate_radius(d=2):
interval = 1 - 0
vol_free = interval ** d
radius =... | flexible | {
"blob_id": "84febcc599aa97858ded3b6f803b6b76960878d4",
"index": 7188,
"step-1": "<mask token>\n\n\ndef asymmetric_extend(q1, q2, extend_fn, backward=False):\n if backward and ASYMETRIC:\n return reversed(list(extend_fn(q2, q1)))\n return extend_fn(q1, q2)\n\n\n<mask token>\n\n\ndef calculate_radius... | [
7,
8,
10,
12,
13
] |
#!/usr/bin/env python
"""Server that accepts and executes control-type commands on the bot."""
import sys
import os
from inspect import getmembers, ismethod
from simplejson.decoder import JSONDecodeError
import zmq
import signal
# This is required to make imports work
sys.path = [os.getcwd()] + sys.path
import bot.l... | normal | {
"blob_id": "ddb81e3ce0df44ee503c558b68b41c35935358a0",
"index": 8663,
"step-1": "<mask token>\n\n\nclass CtrlServer(object):\n <mask token>\n <mask token>\n <mask token>\n\n def assign_subsystems(self):\n \"\"\"Instantiates and stores references to bot subsystems.\n\n :returns: Dict of... | [
10,
13,
16,
18,
19
] |
from dataclasses import dataclass, field
from typing import List
@dataclass
class Root:
a: List[object] = field(
default_factory=list,
metadata={
"type": "Element",
"namespace": "",
"min_occurs": 2,
"max_occurs": 4,
"sequence": 1,
... | normal | {
"blob_id": "7e318ae7317eac90d6ce9a6b1d0dcc8ff65abef0",
"index": 9430,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@dataclass\nclass Root:\n a: List[object] = field(default_factory=list, metadata={'type':\n 'Element', 'namespace': '', 'min_occurs': 2, 'max_occurs': 4,\n 'sequence'... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
torch.manual_seed(1)
if use_cuda:
torch.cuda.manual_seed(1)
np.random.seed(1)
<|reserved_special_token_0|>
print('DCCNet training script')
<|reserved_special_token_0|>
parser.add_argument('--checkpoint', type=str, default='')
... | flexible | {
"blob_id": "0c97569c77fb3598d83eba607960328bb2134dd2",
"index": 333,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntorch.manual_seed(1)\nif use_cuda:\n torch.cuda.manual_seed(1)\nnp.random.seed(1)\n<mask token>\nprint('DCCNet training script')\n<mask token>\nparser.add_argument('--checkpoint', type=... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class ScannerTests(unittest.TestCase):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def testPricingSingleItems(self):
scanner = Scanner(self.singleItemListOneDiscount)
groceryList = ['Apple', 'Orange', 'Tomato', 'A... | flexible | {
"blob_id": "fc2a123f8a86d149af9fc73baa360a029fcde574",
"index": 6316,
"step-1": "<mask token>\n\n\nclass ScannerTests(unittest.TestCase):\n <mask token>\n <mask token>\n <mask token>\n\n def testPricingSingleItems(self):\n scanner = Scanner(self.singleItemListOneDiscount)\n groceryList... | [
5,
7,
8,
11,
14
] |
from rest_framework import serializers
from .models import Backend
class BackendSerializer(serializers.ModelSerializer):
class Meta:
model = Backend
fields = '__all__'
| normal | {
"blob_id": "b4787d65fb8adf5dc6a99c1a13922c8f9acc2087",
"index": 1971,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass BackendSerializer(serializers.ModelSerializer):\n\n\n class Meta:\n model = Backend\n fields = '__all__'\n",
"step-3": "from rest_framework import serializers... | [
0,
1,
2
] |
f = open("resources/yesterday.txt", 'r')
yesterday_lyric = ""
while 1 :
line = f.readline()
if not line :
break
yesterday_lyric = yesterday_lyric + line.strip() + "\n"
f.close()
# 대소문자 구분없이 yesterday 단어의 개수 세기 : 대문자로 또는 소문자로 만들고 카운드 세기
num_of_yesterday = yesterday_lyric.upper().count("YESTERDAY")
... | normal | {
"blob_id": "8559448822b3d3989a9795e7b497a2791588c327",
"index": 9539,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile 1:\n line = f.readline()\n if not line:\n break\n yesterday_lyric = yesterday_lyric + line.strip() + '\\n'\nf.close()\n<mask token>\nprint(\"Number of a Word 'YESTER... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def get_Userid(path):
path_Divided = path.split('\\')
get_id = path_Divided[6].split('.')
get_id = get_id[0]
return get_id
def compose_Json_Path_ToRead(path_json_source, get_id):
json_path_to_read = path_json_source + '\\' + str(get_id) + '.json'
return json_path... | flexible | {
"blob_id": "2e5dbd84eb1f9cc09602df8ef8d7bdd30e1b2f26",
"index": 7119,
"step-1": "<mask token>\n\n\ndef get_Userid(path):\n path_Divided = path.split('\\\\')\n get_id = path_Divided[6].split('.')\n get_id = get_id[0]\n return get_id\n\n\ndef compose_Json_Path_ToRead(path_json_source, get_id):\n js... | [
5,
6,
7,
8,
9
] |
# coding: UTF-8 -*-
import os.path
PROJECT_ROOT = os.path.dirname(os.path.abspath(__file__))
EMOTICONS = {
"O:)": "angel",
"o:)": "angel",
"O:-)": "angel",
"o:-)": "angel",
"o:-3": "angel",
"o:3": "angel",
"O;^)": "angel",
">:[": "annoyed/disappointed",
":-(": "annoyed/disappointed... | normal | {
"blob_id": "3f3ed0165120dc135a4ce1f282dbdf9dad57adf8",
"index": 980,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nPROJECT_ROOT = os.path.dirname(os.path.abspath(__file__))\nEMOTICONS = {'O:)': 'angel', 'o:)': 'angel', 'O:-)': 'angel', 'o:-)':\n 'angel', 'o:-3': 'angel', 'o:3': 'angel', 'O;^)': 'ang... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class GraphWalkAgent(nn.Module):
def __init__(self, args):
super(GraphWalkAgent, self).__init__()
self.model = args.model
self.relation_only = args.relation_only
self.history_dim = args.history_dim
self.history_num_layers = args.history_num_lay... | flexible | {
"blob_id": "4a892c3532a3e3ddcd54705336dce820ff49b91b",
"index": 6289,
"step-1": "<mask token>\n\n\nclass GraphWalkAgent(nn.Module):\n\n def __init__(self, args):\n super(GraphWalkAgent, self).__init__()\n self.model = args.model\n self.relation_only = args.relation_only\n self.his... | [
10,
13,
16,
18,
20
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_data_dir_register():
register = register_path.DataDirRegister(namespace_to_data_dirs={'ns1':
[epath.Path('/path/ns1')]})
assert {'ns1'} == register.namespaces
<|reserved_special_token_1|>
<|reserved_s... | flexible | {
"blob_id": "ed65d7e0de3fc792753e34b77254bccc8cee6d66",
"index": 3657,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_data_dir_register():\n register = register_path.DataDirRegister(namespace_to_data_dirs={'ns1':\n [epath.Path('/path/ns1')]})\n assert {'ns1'} == register.namespa... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(TSA, V)
<|reserved_special_token_1|>
l, w, h = map(int, input().split())
TSA = 2 * (l * w + w * h + h * l)
V = l * w * h
print(TSA, V)
| flexible | {
"blob_id": "d3382ead1d98ba2fb15fe3ea277430f1bb07131c",
"index": 2544,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(TSA, V)\n",
"step-3": "l, w, h = map(int, input().split())\nTSA = 2 * (l * w + w * h + h * l)\nV = l * w * h\nprint(TSA, V)\n",
"step-4": null,
"step-5": null,
"step-ids": [... | [
0,
1,
2
] |
'''
Created on 4 Oct 2016
@author: MetalInvest
'''
def isHammerHangman(high, low, open, close):
body = abs(open - close)
leg = min(open, close) - low
return leg / body >= 2.0 and high/max(open, close) <= 1.08
def isEngulfing(df, bottom = True):
open_0 = df['open'][-1]
close_0 = d... | normal | {
"blob_id": "6e739c30b3e7c15bd90b74cfd5a1d6827e863a44",
"index": 4413,
"step-1": "<mask token>\n\n\ndef isHammerHangman(high, low, open, close):\n body = abs(open - close)\n leg = min(open, close) - low\n return leg / body >= 2.0 and high / max(open, close) <= 1.08\n\n\ndef isEngulfing(df, bottom=True):... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2017/7/14 下午6:06
# @Author : Huang HUi
# @Site :
# @File : Longest Common Prefix.py
# @Software: PyCharm
class Solution(object):
def longestCommonPrefix(self, strs):
"""
:type strs: List[str]
:rtype: str
"""
... | normal | {
"blob_id": "1aed8e92a31ee42a3a609123af927f7074598ec1",
"index": 1820,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n\n\n<mask token>\n",
"step-3": "class Solution(object):\n\n def longestCommonPrefix(self, strs):\n \"\"\"\n :type strs: List[str]\n ... | [
0,
1,
2,
3,
4
] |
# Generated by Django 2.1.5 on 2019-01-21 22:51
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
ope... | normal | {
"blob_id": "a6cb7a134fb8480d344743bcb7bc8766146d256f",
"index": 8238,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n initial = T... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def test_read_from_file():
"""
Test of function of reading data from file.
:return:
"""
reading_file = d.read_code_from_file()
assert type(reading_file) == list
assert len(reading_file) == 7
assert '\n' not in d.read_code_from_file()
def test_decode_from... | flexible | {
"blob_id": "8cfab525ab3a86dd6964475d5621fdc7c6413e38",
"index": 8019,
"step-1": "<mask token>\n\n\ndef test_read_from_file():\n \"\"\"\n Test of function of reading data from file.\n\n :return:\n \"\"\"\n reading_file = d.read_code_from_file()\n assert type(reading_file) == list\n assert le... | [
5,
6,
7,
8,
9
] |
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