code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
config.read('dwh.cfg')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
config = configparser.ConfigParser()
config.read('dwh.cfg')
drop_schema = 'DROP SCHEMA IF EXISTS sparkifydb;'
set_sea... | flexible | {
"blob_id": "652918e09a3506869c939be39b71a06467459f8a",
"index": 5992,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nconfig.read('dwh.cfg')\n<mask token>\n",
"step-3": "<mask token>\nconfig = configparser.ConfigParser()\nconfig.read('dwh.cfg')\ndrop_schema = 'DROP SCHEMA IF EXISTS sparkifydb;'\nset_se... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
def addBinary(self, a, b):
"""
:type a: str
:type b: str
:rtype: str
"""
max_len = max(len(a)... | flexible | {
"blob_id": "9655cba5b459ae8b6812bcebc31cc46e19e52386",
"index": 2741,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n",
"step-3": "class Solution(object):\n\n def addBinary(self, a, b):\n \"\"\"\n :type a: str\n :type b: str\n :rtype: str\n ... | [
0,
1,
2,
3
] |
#!/bin/python3
import sys
# import numpy as np
def _get_change_making_matrix(set_of_coins, r):
matrix = [[0 for _ in range(r + 1)] for _ in range(len(set_of_coins) + 1)]
# matrix = np.array(matrix)
for i in range(1,len(set_of_coins) + 1):
matrix[i][0] = i
return matrix
def change_making(co... | normal | {
"blob_id": "f15bc62fad2c47fed2e9e5d269284ebe7487b789",
"index": 2297,
"step-1": "<mask token>\n\n\ndef _get_change_making_matrix(set_of_coins, r):\n matrix = [[(0) for _ in range(r + 1)] for _ in range(len(set_of_coins) + 1)\n ]\n for i in range(1, len(set_of_coins) + 1):\n matrix[i][0] = i\... | [
2,
3,
4,
5,
6
] |
#Embedded file name: c:/depot/games/branches/release/EVE-TRANQUILITY/eve/client/script/paperDoll/SkinRaytracing.py
import trinity
import blue
import telemetry
import ctypes
import math
import time
import geo2
import struct
import itertools
import weakref
import uthread
import paperDoll as PD
import log
import random
my... | normal | {
"blob_id": "3c01ca27a5eef877b606b93b04ffe6f73168cd6b",
"index": 9090,
"step-1": "#Embedded file name: c:/depot/games/branches/release/EVE-TRANQUILITY/eve/client/script/paperDoll/SkinRaytracing.py\nimport trinity\nimport blue\nimport telemetry\nimport ctypes\nimport math\nimport time\nimport geo2\nimport struct\... | [
0
] |
from django.db import models
from datetime import datetime
class Message(models.Model):
text = models.CharField(max_length=200)
votes = models.IntegerField()
date_added = models.DateTimeField(default=datetime.now)
score = models.BigIntegerField()
next_vote = models.IntegerField(default=3600) # 8640... | normal | {
"blob_id": "7159b447ed6fcb2005f63c7b7359970defbc9d43",
"index": 1496,
"step-1": "<mask token>\n\n\nclass Message(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Message(models.Model):\n <mask t... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
CORS(app)
app.config.from_object(Config)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
app = Flask(__name__)
CORS(app)
app.config.from_object(Config)
app.config['SQLALCHEMY_DATABASE_URI'... | flexible | {
"blob_id": "f494d8aeee8c72cce8fc14e44ca896bcf30c100a",
"index": 5627,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nCORS(app)\napp.config.from_object(Config)\n<mask token>\n",
"step-3": "<mask token>\napp = Flask(__name__)\nCORS(app)\napp.config.from_object(Config)\napp.config['SQLALCHEMY_DATABASE_UR... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python3
# -*- coding: UTF-8 -*-
import RPi.GPIO as gpio # 导入Rpi.GPIO库函数命名为GPIO
import time
gpio.setmode(gpio.BOARD) #将GPIO编程方式设置为BOARD模式
pin = 40
gpio.setup(pin, gpio.OUT) #控制pin号引脚
gpio.output(pin, gpio.HIGH) #11号引脚输出高电平
time.sleep(5) #计时0.5秒
gpio.output(pin, gpio.LOW) #11号引脚输出低电平
time.sleep(1) #计时1秒
... | normal | {
"blob_id": "cfdfc490396546b7af732417b506100357cd9a1f",
"index": 6762,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ngpio.setmode(gpio.BOARD)\n<mask token>\ngpio.setup(pin, gpio.OUT)\ngpio.output(pin, gpio.HIGH)\ntime.sleep(5)\ngpio.output(pin, gpio.LOW)\ntime.sleep(1)\ngpio.cleanup()\n",
"step-3": "<... | [
0,
1,
2,
3,
4
] |
import matplotlib.pyplot as plt
from partisan_symmetry_noplot import partisan_symmetry
for k in range(1,100):
a=[]
for i in range(1,100):
a.append([])
for j in range(1,100):
a[i-1].append(partisan_symmetry([5*i/100,.20,5*j/100],1000,False))
plt.imshow(a)
plt.colorbar()
p... | normal | {
"blob_id": "cfa0937f1c49b52283c562d9ab1cb0542e71b990",
"index": 5970,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor k in range(1, 100):\n a = []\n for i in range(1, 100):\n a.append([])\n for j in range(1, 100):\n a[i - 1].append(partisan_symmetry([5 * i / 100, 0.2, 5... | [
0,
1,
2,
3
] |
#!/usr/bin/env python
import fileinput
#open the file with the matched DNA short reads
#create a file with the modified version
f1 = open('CompleteDNAsequence.txt', 'r')
f2 = open('CompleteDNAsequence.txt.tmp', 'w')
for line in f1:
f2.write(line.replace('_', '\n')) #replaces _ with tab
f1.close()
f2.close()
#ope... | normal | {
"blob_id": "d02ef5fc27cde353e90dda4090905b89b5be5c49",
"index": 2897,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in f1:\n f2.write(line.replace('_', '\\n'))\nf1.close()\nf2.close()\n<mask token>\nopen('ANSWER.txt', 'w').writelines(lines[:+1])\n",
"step-3": "<mask token>\nf1 = open('Com... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class HelloApiHandler(Resource):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class HelloApiHandler(Resource):
def get(self):
return {'resultStatus': 'SUCCESS', 'message': 'Hello Api Handler'}... | flexible | {
"blob_id": "80c3d9165c1b592122fabf6382e265465604989c",
"index": 1450,
"step-1": "<mask token>\n\n\nclass HelloApiHandler(Resource):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass HelloApiHandler(Resource):\n\n def get(self):\n return {'resultStatus': 'SUCCESS', 'message':... | [
1,
2,
3,
4,
5
] |
# !/usr/bin/env python3
# -*- coding:utf-8 -*-
# @Time : 2021/05/08 20:06
# @Author : Yi
# @FileName: show_slices.py
import os
import pydicom
import glob
import shutil
import random
import numpy as np
import cv2
import skimage.io as io
from data_Parameter import parse_args
import matplotlib.pyplot as plt
def d... | normal | {
"blob_id": "4905b820f33619a80a9915d0603bc39e0d0368d9",
"index": 6175,
"step-1": "<mask token>\n\n\ndef dir_create(path):\n \"\"\"创造新的文件夹。\n\n :param path: 文件夹路径\n :return:\n \"\"\"\n if os.path.exists(path) and os.listdir(path) != []:\n shutil.rmtree(path)\n os.makedirs(path)\n i... | [
7,
8,
9,
10,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(type(list1))
print(list1[0])
print(list1[len(list1) - 1])
<|reserved_special_token_0|>
print(list1)
<|reserved_special_token_0|>
list4
<|reserved_special_token_0|>
list4
<|reserved_special_token_0|>
list4
<|reserved_special_... | flexible | {
"blob_id": "32b22cccac75c87b8638c76c0c6d27db0de4d750",
"index": 8480,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(type(list1))\nprint(list1[0])\nprint(list1[len(list1) - 1])\n<mask token>\nprint(list1)\n<mask token>\nlist4\n<mask token>\nlist4\n<mask token>\nlist4\n<mask token>\nlist4\n<mask to... | [
0,
1,
2,
3
] |
from .cli import cli
if __name__ == "__main__":
exit(cli.main(prog_name="htmap"))
| normal | {
"blob_id": "069338b188f3cf16357b2502cbb3130b69918bd9",
"index": 286,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n exit(cli.main(prog_name='htmap'))\n",
"step-3": "from .cli import cli\nif __name__ == '__main__':\n exit(cli.main(prog_name='htmap'))\n",
"step-4": "... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Solution:
<|reserved_special_token_0|>
class Solution:
def countArrangement(self, n: int) ->int:
@cache
def dfs(bm, i):
if i == 0:
return 1
cnt = 0
for num in range(n):
if not bm & 1 << n... | flexible | {
"blob_id": "e6acc7b022001d8419095ad6364a6ae9504ec7aa",
"index": 508,
"step-1": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n\nclass Solution:\n\n def countArrangement(self, n: int) ->int:\n\n @cache\n def dfs(bm, i):\n if i == 0:\n return 1\n cnt ... | [
5,
6,
7,
8,
10
] |
#!/usr/bin/env python
import os, time, sys
fifoname = '/dev/pi-blaster' # must open same name
def child( ):
pipeout = os.open(fifoname, os.O_WRONLY) # open fifo pipe file as fd
zzz = 0
while 1:
time.sleep(zzz)
os.write(pipeout, 'Spam %03d\n' % zzz)
zzz = (z... | normal | {
"blob_id": "7502e28197cb40044303a0a2163546f42375aeb6",
"index": 6119,
"step-1": "#!/usr/bin/env python\nimport os, time, sys\nfifoname = '/dev/pi-blaster' # must open same name\n\ndef child( ):\n pipeout = os.open(fifoname, os.O_WRONLY) # open fifo pipe file as fd\n zzz = 0\n ... | [
0
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Module that defines a controller for database's operations over business rules
"""
# built-in dependencies
import functools
import typing
# external dependencies
import sqlalchemy
from sqlalchemy.orm import sessionmaker
# project dependencies
from database.table im... | normal | {
"blob_id": "c024e12fe06e47187c25a9f384ceed566bf94645",
"index": 6909,
"step-1": "<mask token>\n\n\nclass _DatabaseResourceTableController:\n <mask token>\n <mask token>\n\n def register_peer(self, peer_id: str, peer_ip: str, peer_port: int,\n resource_name: str, resource_path: str, resource_hash... | [
5,
6,
7,
9,
11
] |
import requests
if __name__ == "__main__":
# individual datacake webhook url
# Change this to the webhook url of your datacake device/product
datacake_url = "https://api.datacake.co/integrations/api/ae6dd531-4cf6-4966-b5c9-6c43939aae90/"
# Serial number
# Include Serial Number in Payload so Datac... | normal | {
"blob_id": "00af9627242648a5a16a34a18bfc117945f1bc08",
"index": 4936,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n datacake_url = (\n 'https://api.datacake.co/integrations/api/ae6dd531-4cf6-4966-b5c9-6c43939aae90/'\n )\n serial = 'python0001'\n numbe... | [
0,
1,
2,
3
] |
##########################################################################################
## Scene Classification ##
## Authors : Chris Andrew, Santhoshini Reddy, Nikath Yasmeen, Sai Hima, Sriya Ragini ##
###############################################... | normal | {
"blob_id": "b8b20d6c977a6c1df6a592188c6e799f12da6a23",
"index": 9734,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in f:\n l = line.strip()\n l = l.split(',')\n l = map(float, l)\n data.append(l)\nf.close()\nfor i in range(100):\n shuffle(data)\nfor l in data:\n train_data.a... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
import argparse
import keyring
import papercut
import ConfigParser
import getpass
import time
import os
config = ConfigParser.ConfigParser()
config.read([os.path.expanduser('~/.papercut')])
try:
username = config.get('papercut','username')
except ConfigParser.NoSectionError:
username = No... | normal | {
"blob_id": "33cc8814d9397bcb0041728407efef80a136f151",
"index": 505,
"step-1": "#!/usr/bin/env python\nimport argparse\nimport keyring\nimport papercut\nimport ConfigParser\nimport getpass\nimport time\nimport os\n\nconfig = ConfigParser.ConfigParser()\nconfig.read([os.path.expanduser('~/.papercut')])\ntry:\n ... | [
0
] |
#!/usr/bin/env python
import rospy
from mark1.srv import WordCount, WordCountResponse
s= set('',)
def count_words(request):
s.update(set( request.words.split() ))
print s
return WordCountResponse( len( request.words.split()))
rospy.init_node('mark_service_server')
service = rospy.Service('Word_count', W... | normal | {
"blob_id": "e90e4d2c777554999ab72d725d7e57bdfd508d3a",
"index": 3966,
"step-1": "#!/usr/bin/env python\nimport rospy\nfrom mark1.srv import WordCount, WordCountResponse\n\ns= set('',)\n\ndef count_words(request):\n s.update(set( request.words.split() ))\n print s\n return WordCountResponse( len( reques... | [
0
] |
from flask_wtf import FlaskForm
from wtforms import StringField, SelectField,SubmitField, PasswordField, RadioField, MultipleFileField, SubmitField, TextAreaField
from wtforms.fields.html5 import EmailField, TelField, DateField
from wtforms.validators import DataRequired, Email, Length, InputRequired
class SignUpForm(... | normal | {
"blob_id": "32ed07a89a6f929a6c4b78fd79e687b85e01015b",
"index": 535,
"step-1": "<mask token>\n\n\nclass ForgotForm(FlaskForm):\n email = EmailField('Email Id*', validators=[DataRequired(), Email()])\n design = SelectField(u'Designation*', choices=[('admin', 'Admin'), (\n 'stud', 'Student')], valida... | [
8,
10,
11,
12,
14
] |
#!/usr/bin/env python3
import json
import sqlite3
import sys
from scorelib import *
#from .scorelib import *
from collections import defaultdict
def __map2list(mp):
if len(mp.keys()) == 0:
return []
lst = [None] * max(mp.keys())
for idx in mp.keys():
lst[idx-1] = mp[idx]
return lst
d... | normal | {
"blob_id": "9f6e5c219f7b668720b5379dde912ff22ef434d1",
"index": 9072,
"step-1": "<mask token>\n\n\ndef __map2list(mp):\n if len(mp.keys()) == 0:\n return []\n lst = [None] * max(mp.keys())\n for idx in mp.keys():\n lst[idx - 1] = mp[idx]\n return lst\n\n\ndef __translate_keys(translati... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class GetDefaultUsers(APIView):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class GetSpecificUser(APIView):
permission_classes = [permissions.IsAuthenticated]
def post(self, request, id=None, *args, **kwargs):
try:
queryset = users.obje... | flexible | {
"blob_id": "c5a7f269f579bd1960afa4f700b5c3436ac6d91a",
"index": 2733,
"step-1": "<mask token>\n\n\nclass GetDefaultUsers(APIView):\n <mask token>\n <mask token>\n\n\nclass GetSpecificUser(APIView):\n permission_classes = [permissions.IsAuthenticated]\n\n def post(self, request, id=None, *args, **kwa... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
admin.site.register(username)
<|reserved_special_token_1|>
from django.contrib import admin
from get_my_tweets.models import username
admin.site.register(username)
| flexible | {
"blob_id": "84ece5d1a9e38b83a5b60052fc3ab089c498d2fc",
"index": 9147,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.site.register(username)\n",
"step-3": "from django.contrib import admin\nfrom get_my_tweets.models import username\nadmin.site.register(username)\n",
"step-4": null,
"step-5":... | [
0,
1,
2
] |
#!/bin/python3
# TODO: implement the stack O(N) version
'''
Naive: O(N^3) or sum_{k=1...N}( O(N^2 (N-K)) )
for each size N
for each window of size N in the array
traverse the window to find the max
Naive with heap: O(N^2 log N)
for each size N O(N)
traverse array and accumulate window of size N O(N... | normal | {
"blob_id": "dce7fd0c9ed8e1d433f9131a8d137c8dcca4ac56",
"index": 8307,
"step-1": "<mask token>\n\n\ndef riddle(lst):\n \"\"\"\n Holy fuck.\n\n Better summary than above of what's happening:\n\n Define an value `v` in the list to dominate a range of size `n`, including `v`\n itself, if `v` is smaller than ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class TestCommand(ExternalNotificationsPatchTestCase):
<|reserved_special_token_0|>
@patch('intake.management.commands.send_followups.is_the_weekend')
@patch('intake.management.commands.send_followups.FollowupsService')
def test_doesnt_do_anything_on_the_weekend(self, Fol... | flexible | {
"blob_id": "5cb67e5fcedafca4ce124e4094cbd8e1e9d95bb4",
"index": 3740,
"step-1": "<mask token>\n\n\nclass TestCommand(ExternalNotificationsPatchTestCase):\n <mask token>\n\n @patch('intake.management.commands.send_followups.is_the_weekend')\n @patch('intake.management.commands.send_followups.FollowupsSe... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
T = List[int]
C = Callable[[int], None]
<|reserved_special_token_1|>
from typing import List, Callable
T = List[int]
C = Callable[[int], None]
<|reserved_special_token_1|>
from typing import List, Callable
#: A list of int
... | flexible | {
"blob_id": "aaee69d339cf1c14e54366633155ee57026e6487",
"index": 2071,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nT = List[int]\nC = Callable[[int], None]\n",
"step-3": "from typing import List, Callable\nT = List[int]\nC = Callable[[int], None]\n",
"step-4": "from typing import List, Callable\n\... | [
0,
1,
2,
3
] |
from __future__ import absolute_import
import sys
from apscheduler.executors.base import BaseExecutor, run_job
try:
import gevent
except ImportError: # pragma: nocover
raise ImportError('GeventExecutor requires gevent installed')
class GeventExecutor(BaseExecutor):
"""
Runs jobs as greenlets.
... | normal | {
"blob_id": "afcadc11d23fb921eb6f8038a908de02ee763ca4",
"index": 693,
"step-1": "<mask token>\n\n\nclass GeventExecutor(BaseExecutor):\n <mask token>\n\n def _do_submit_job(self, job, run_times):\n\n def callback(greenlet):\n try:\n events = greenlet.get()\n exce... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def boundarytester(playerinput):
if playerinput[1][0] > 14 or playerinput[1][0] < 0 or playerinput[1][1
] > 14 or playerinput[1][1] < 0:
return False
if playerinput[2] == 'h':
if playerinput[1][1] + len(list(playerinput[0])) - 1 > 14:
return Fal... | flexible | {
"blob_id": "2cb0f2fbf3ceddb2f1ee65614506dbfb3b5c8089",
"index": 4736,
"step-1": "<mask token>\n\n\ndef boundarytester(playerinput):\n if playerinput[1][0] > 14 or playerinput[1][0] < 0 or playerinput[1][1\n ] > 14 or playerinput[1][1] < 0:\n return False\n if playerinput[2] == 'h':\n ... | [
6,
7,
8,
9,
10
] |
from sys import stdin
read = lambda: stdin.readline().strip()
class Trie:
def __init__(self, me, parent=None):
self.me = me
self.parent = parent
self.children = {}
def get_answer(trie, count):
print(("--" * count) + trie.me)
trie.children = dict(sorted(trie.children.items(), key... | normal | {
"blob_id": "c5605f4770d61d435cc1817bad4d5cbe0aaf1d18",
"index": 8824,
"step-1": "<mask token>\n\n\nclass Trie:\n\n def __init__(self, me, parent=None):\n self.me = me\n self.parent = parent\n self.children = {}\n\n\n<mask token>\n\n\ndef main():\n trie_dict = {}\n for i in range(in... | [
3,
5,
6,
7,
8
] |
from tkinter import *
import mathcalc as c
root= Tk()
root.title("CALCULATOR")
ent=Entry(root,width=35)
ent.grid(row=0,column=0,columnspan=3,padx=10,pady=10)
#ent.grid(row=0,column=0)
ch=''
num=ent.get()
def clicked(num):
current=ent.get()
ent.delete(0,END)
ent.insert(0,str(current)+str(num))
def click... | normal | {
"blob_id": "bdd9ebfa9a2f14d57efd527ca88032bfb0160a5e",
"index": 7504,
"step-1": "<mask token>\n\n\ndef clicked(num):\n current = ent.get()\n ent.delete(0, END)\n ent.insert(0, str(current) + str(num))\n\n\ndef click_clear():\n ent.delete(0, END)\n\n\ndef add():\n global ch\n ch = '+'\n clic... | [
7,
8,
9,
10,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
try:
fh = open('testfile', 'w')
fh.write('test')
except IOError:
print('Error:没有找到文件')
else:
print('sucess')
fh.close()
<|reserved_special_token_1|>
try:
fh = open("testfile","w")
fh.write("test")
except IOError:
print("Error:没有找... | flexible | {
"blob_id": "15e0b396a4726f98ce5ae2620338d7d48985707e",
"index": 9533,
"step-1": "<mask token>\n",
"step-2": "try:\n fh = open('testfile', 'w')\n fh.write('test')\nexcept IOError:\n print('Error:没有找到文件')\nelse:\n print('sucess')\n fh.close()\n",
"step-3": "try:\r\n\tfh = open(\"testfile\",\"w\... | [
0,
1,
2
] |
name = input("Enter your name: ")
print("Hi buddy! Today we will play a game " + name + "!")
print("Are you ready?")
question = input("Are you ready ? Yes or no: ")
print(name + " we are starting!")
liste1 = ['My neighbor ', 'My girlfriend ', 'My boyfriend ', 'My dog ']
num = input("Enter a number: ")
... | normal | {
"blob_id": "4ef6002480fcaa514f41227978bae76f6e02c22d",
"index": 6401,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Hi buddy! Today we will play a game ' + name + '!')\nprint('Are you ready?')\n<mask token>\nprint(name + ' we are starting!')\n<mask token>\nprint(liste1 + liste2 + liste3 + liste4... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
import random
import gym
import numpy as np
from collections import deque
from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import Adam
from simulation_utils import box, simulation
from kinematics import pose3D
a = np.log(2)/25
apdataX = np.random.random(... | normal | {
"blob_id": "7e7e96fb9377e4dc59a46a46951f5057ecae419a",
"index": 201,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(np.linalg.norm(mat))\n",
"step-3": "<mask token>\na = np.log(2) / 25\napdataX = np.random.random((5, 35))\nquarter_way_arr = [False, False, False]\nquarter_way_arr[0] = True\nquart... | [
0,
1,
2,
3,
4
] |
from django.urls import path
from jobscrapper.views import *
urlpatterns = [
path('', home_vacancies_view, name="vacancy-home"),
path('list/', vacancies_view, name="vacancy"),
] | normal | {
"blob_id": "3ee20391d56d8c429ab1bd2f6b0e5b261721e401",
"index": 7965,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', home_vacancies_view, name='vacancy-home'), path(\n 'list/', vacancies_view, name='vacancy')]\n",
"step-3": "from django.urls import path\nfrom jobscrapper.vie... | [
0,
1,
2,
3
] |
"""
k-element subsets of the set [n]
3-element subsets of the set [6]
123
"""
result = []
def get_subset(A, k, n):
a_list = [i for i in A]
if len(a_list) == k:
result.append(a_list)
return
s_num = max(a_list)+1 if a_list else 1
for i in range(s_num, n+1):
a_list.append(i)
... | normal | {
"blob_id": "d48353caa07d3bfa003ea9354b411fe0c79591db",
"index": 2725,
"step-1": "<mask token>\n\n\ndef get_subset(A, k, n):\n a_list = [i for i in A]\n if len(a_list) == k:\n result.append(a_list)\n return\n s_num = max(a_list) + 1 if a_list else 1\n for i in range(s_num, n + 1):\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class NewScrape:
def scrape_main(self):
"""
Top-level function.
Use links from below, scrape a page, sleep for 5s, and restart on the next link.
"""
for i in self.gen_links():
index = str(self.gen_links().index(i))
link ... | flexible | {
"blob_id": "ed3fbae19c88100690dd5c558c0dc6d36a4849c8",
"index": 1451,
"step-1": "<mask token>\n\n\nclass NewScrape:\n\n def scrape_main(self):\n \"\"\"\n Top-level function.\n Use links from below, scrape a page, sleep for 5s, and restart on the next link.\n \"\"\"\n for i ... | [
9,
12,
13,
14,
15
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def index(request):
baseball = League.objects.filter(name__contains='Baseball')
women_league = League.objects.filter(name__contains='women')
hockey_league = League.objects.filter(sport__contains='hockey')
not_foo... | flexible | {
"blob_id": "49703775da87e8cbbe78a69c91a68128c3fd78e1",
"index": 3363,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef index(request):\n baseball = League.objects.filter(name__contains='Baseball')\n women_league = League.objects.filter(name__contains='women')\n hockey_league = League.obje... | [
0,
1,
2,
3,
4
] |
from app_auth.recaptcha.services.recaptcha_service import validate_recaptcha
from django.shortcuts import render, redirect
from django.contrib import auth
from django.views import View
from rest_framework.permissions import IsAuthenticated
from rest_framework.views import APIView
from rest_framework.response import Res... | normal | {
"blob_id": "b2eb2d006d6285947cc5392e290af50f25a9f566",
"index": 4724,
"step-1": "<mask token>\n\n\nclass Signup(Auth):\n <mask token>\n <mask token>\n\n\nclass UserViewSet(APIView):\n authentication_classes = [CustomBearerAuthentication]\n permission_classes = [IsAuthenticated]\n\n def get(self, ... | [
12,
14,
16,
18,
22
] |
#!/usr/bin/python3
# encoding: utf-8
import sys
import argparse
import logging
from pathlib import Path
module = sys.modules['__main__'].__file__
__author__ = 'FFX'
__version__ = '1.0'
log = logging.getLogger(module)
def parse_command_line(argv):
"""Parse command line argument. See -h option
:param argv: ... | normal | {
"blob_id": "46adb1834f6013ca0f13a64f280182a805d76278",
"index": 215,
"step-1": "<mask token>\n\n\ndef parse_command_line(argv):\n \"\"\"Parse command line argument. See -h option\n :param argv: arguments on the command line must include caller file name.\n \"\"\"\n formatter_class = argparse.RawDesc... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class Estoque(object):
<|reserved_special_token_0|>
def save_categoria(self, categoria):
pass
<|reserved_special_token_0|>
def save_produtos(self, produto):
pass
<|reserved_special_token_0|>
def create_subcategoria(self):
""""
Cri... | flexible | {
"blob_id": "9f3ca0d5a10a27d926a0f306665889418f8d6a0c",
"index": 5884,
"step-1": "<mask token>\n\n\nclass Estoque(object):\n <mask token>\n\n def save_categoria(self, categoria):\n pass\n <mask token>\n\n def save_produtos(self, produto):\n pass\n <mask token>\n\n def create_subca... | [
7,
11,
12,
17,
18
] |
#
# linter.py
# Linter for SublimeLinter version 4.
#
# Written by Brian Schott (Hackerpilot)
# Copyright © 2014-2019 Economic Modeling Specialists, Intl.
#
# License: MIT
#
"""This module exports the D-Scanner plugin class."""
from SublimeLinter.lint import Linter, STREAM_STDOUT
class Dscanner(Linter):
"""Pro... | normal | {
"blob_id": "fda73b5dac038f077da460d6ebfb432b756909d9",
"index": 3125,
"step-1": "<mask token>\n\n\nclass Dscanner(Linter):\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",
"step-2": "<mask token>\n\n\nclass Dsca... | [
1,
2,
3,
4,
5
] |
# Copyright (c) 2011-2020 Eric Froemling
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish,... | normal | {
"blob_id": "7c63abacce07ee9d4c2b3941d05f951b75c8d0ff",
"index": 1157,
"step-1": "<mask token>\n\n\nclass PlayerRecord:\n <mask token>\n character: str\n <mask token>\n\n @property\n def team(self) ->ba.SessionTeam:\n \"\"\"The ba.SessionTeam the last associated player was last on.\n\n ... | [
17,
23,
28,
29,
30
] |
'''
IplNorm.py
Description:
Normalizing 0 - 255 initial fingerprint to a normalized image.
Using energy normalization.
Input:
-image
Output:
-norm_im
@author: Edoardo Foco
'''
import cv2
import numpy as np
def normalise(image):
dbl_image = image.astype(float)
#... | normal | {
"blob_id": "f51d85ff352d9c84a8ded29ad94b24ca6dda46ad",
"index": 7593,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef normalise(image):\n dbl_image = image.astype(float)\n mean = np.mean(dbl_image)\n iplImage = cv2.cv.CreateImageHeader((image.shape[1], image.shape[0]),\n cv2.cv.IP... | [
0,
1,
2,
3
] |
import sys
import psyco
sys.stdin = open("/home/shiva/Learning/1.txt", "r")
sys.stdout = open("/home/shiva/Learning/2.txt", "w")
def compute(plus,minus,total,inp):
if plus == 1 and minus == 0:
print(total); return
elif (plus == 1 and minus == 1):
print("Impossible"); return
elif (abs(plus-minus) > total):
pl... | normal | {
"blob_id": "d29c8ec737b8e962d381c8fdd0999e7e01847836",
"index": 5274,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef compute(plus, minus, total, inp):\n if plus == 1 and minus == 0:\n print(total)\n return\n elif plus == 1 and minus == 1:\n print('Impossible')\n ... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def compute_integrated_acquisition(acquisition, x):
"""
Used to compute the acquisition function when samples of the hyper-parameters have been generated (used in GP_MCMC model).
:param acquisition: acquisition function with GpyOpt model type GP_MCMC.
:param x: location w... | flexible | {
"blob_id": "4e7cfbf51ec9bad691d8dd9f103f22728cf5e952",
"index": 1229,
"step-1": "<mask token>\n\n\ndef compute_integrated_acquisition(acquisition, x):\n \"\"\"\n Used to compute the acquisition function when samples of the hyper-parameters have been generated (used in GP_MCMC model).\n\n :param acquisi... | [
7,
9,
12,
15,
16
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(c)
<|reserved_special_token_1|>
i = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
f = [10.5, 12.2, 13.7, 14.9, 14.9, 18.8, 19.7, 23.6, 90.9, 25.7]
s = ['Arpi', 'world', 'Hello', 'Python', 'Consultadd', 'job', 'c++',
'Concepts', 'in... | flexible | {
"blob_id": "87d1c28819d187944a3cf99b35b1d41eab11b139",
"index": 6652,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(c)\n",
"step-3": "i = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\nf = [10.5, 12.2, 13.7, 14.9, 14.9, 18.8, 19.7, 23.6, 90.9, 25.7]\ns = ['Arpi', 'world', 'Hello', 'Python', 'Consultadd', 'jo... | [
0,
1,
2,
3
] |
"""
Tests based on: https://github.com/pydata/xarray/blob/071da2a900702d65c47d265192bc7e424bb57932/xarray/tests/test_backends_file_manager.py
"""
import concurrent.futures
import gc
import pickle
from unittest import mock
import pytest
from rioxarray._io import URIManager
def test_uri_manager_mock_write():
mock... | normal | {
"blob_id": "8fe71e87512dfd2ccfcd21c9c175cb50274d9661",
"index": 1867,
"step-1": "<mask token>\n\n\ndef test_uri_manager_mock_write():\n mock_file = mock.Mock()\n opener = mock.Mock(spec=open, return_value=mock_file)\n manager = URIManager(opener, 'filename')\n f = manager.acquire()\n f.write('con... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
@app.route('/')
def home_page():
"""Offer user choice of Madlib Games"""
return render_template('index.html', stories=stories.values())
<|reserved_special_token_0|>
@app.route('/story')
def show_story():
"""Display Madlib Story"""
answers = request.args
story_title... | flexible | {
"blob_id": "08ed57ffb7a83973059d62f686f77b1bea136fbd",
"index": 3828,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef home_page():\n \"\"\"Offer user choice of Madlib Games\"\"\"\n return render_template('index.html', stories=stories.values())\n\n\n<mask token>\n\n\n@app.route('/story')\ndef show_story(... | [
2,
4,
5,
6,
7
] |
import xlsxwriter
workbook = xlsxwriter.Workbook('商品编码.xlsx')
worksheet = workbook.add_worksheet()
with open('商品编码.txt', 'rt') as f:
data = f.read()
data = data.splitlines(True)
count = 1
row = 0
for x in data:
if count < 3:
count += 1
continue
x = x.split(',')
column = 0
for e in x:... | normal | {
"blob_id": "59a8a4cf4b04a191bfb70fd07668141dbfeda790",
"index": 6822,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('商品编码.txt', 'rt') as f:\n data = f.read()\n<mask token>\nfor x in data:\n if count < 3:\n count += 1\n continue\n x = x.split(',')\n column = 0\n fo... | [
0,
1,
2,
3
] |
class IndividualStack:
def __init__(self):
self.stack=[None]*5
class StackwithStacks:
def __init__(self):
self.stacks = []
self.stackcount=-1
self.count=0
self.st = None
def push(self, element):
if self.count%5==0:
self.stackcount = self.stackco... | normal | {
"blob_id": "a8f52772522d1efc097c3d17d9c08199816f1168",
"index": 3785,
"step-1": "class IndividualStack:\n def __init__(self):\n self.stack=[None]*5\n\n\nclass StackwithStacks:\n def __init__(self):\n self.stacks = []\n self.stackcount=-1\n self.count=0\n self.st = None\n... | [
0
] |
import cv2,os
import sqlite3
cam = cv2.VideoCapture(0)
detector = cv2.CascadeClassifier('Classifiers/face.xml')
i = 0
offset = 50
def create_or_open_db(db_file):
db_is_new = not os.path.exists(db_file)
conn = sqlite3.connect(db_file)
if db_is_new:
print 'Creating schema'
sql = '''create ta... | normal | {
"blob_id": "3beaea1f2b1b085a60bdc5e53f4e6d9aff7e8b6f",
"index": 5538,
"step-1": "import cv2,os\nimport sqlite3\ncam = cv2.VideoCapture(0)\ndetector = cv2.CascadeClassifier('Classifiers/face.xml')\ni = 0\noffset = 50\n\n\ndef create_or_open_db(db_file):\n db_is_new = not os.path.exists(db_file)\n conn = sq... | [
0
] |
def lcs(X, Y, m, n):
dp = [[0]*(n+1) for i in range(m+1)]
for i in range(1,m+1):
for j in range(1,n+1):
if X[i-1] == Y[j-1]:
dp[i][j] = 1 + dp[i-1][j-1]
else:
dp[i][j] = max(dp[i-1][j], dp[i][j-1])
index = dp[m][n]
s = ""
... | normal | {
"blob_id": "247e352b7772a1da74a26f007228355f5af8d3b3",
"index": 191,
"step-1": "<mask token>\n",
"step-2": "def lcs(X, Y, m, n):\n dp = [([0] * (n + 1)) for i in range(m + 1)]\n for i in range(1, m + 1):\n for j in range(1, n + 1):\n if X[i - 1] == Y[j - 1]:\n dp[i][j] =... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def update(a, b):
global counter
if b == 'x':
b = 0
a = week
counter = 0
else:
counter += b
a += counter
train_set = get_train_set(a)
txtLbl1.configure(text=train_set[0])
txtLbl2.configure(text=train_set[2])
txtLbl3.confi... | flexible | {
"blob_id": "62fe29b0ac4dee8fec4908cf803dba9bd7e92fa5",
"index": 4602,
"step-1": "<mask token>\n\n\ndef update(a, b):\n global counter\n if b == 'x':\n b = 0\n a = week\n counter = 0\n else:\n counter += b\n a += counter\n train_set = get_train_set(a)\n txtLbl1.c... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(name * 1000)
<|reserved_special_token_1|>
name = 'valentina '
print(name * 1000)
| flexible | {
"blob_id": "aff1a9263e183610f403a4d6a7f27b45eacb7ff2",
"index": 0,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(name * 1000)\n",
"step-3": "name = 'valentina '\nprint(name * 1000)\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
A = []
ans = 0
def merge(left, mid, right):
global A
global ans
n1 = mid - left
n2 = right - mid
l = []
r = []
for i in range(n1):
l += [A[left + i]]
for i in range(n2):
r += [A[mid + i]]
l += [10**18]
r += [10**18]
i = 0
j = 0
ans += right - left
for k in range(left, right):
if l[i] <= r[j]:
A[... | normal | {
"blob_id": "dc81ab808720c3a2c76174264c9be9bcdd99c292",
"index": 1265,
"step-1": "<mask token>\n\n\ndef Msort(left, right):\n if left + 1 < right:\n mid = int((left + right) / 2)\n Msort(left, mid)\n Msort(mid, right)\n merge(left, mid, right)\n\n\ndef main():\n global ans\n ... | [
2,
3,
4,
5,
6
] |
from cobra.model.fabric import HIfPol
from createMo import *
DEFAULT_AUTO_NEGOTIATION = 'on'
DEFAULT_SPEED = '10G'
DEFAULT_LINK_DEBOUNCE_INTERVAL = 100
AUTO_NEGOTIATION_CHOICES = ['on', 'off']
SPEED_CHOICES = ['100M', '1G', '10G', '40G']
def input_key_args(msg='\nPlease Specify Link Level Policy:'):
print msg
... | normal | {
"blob_id": "36ab827b889adcd4d54296e7da432d3b39d5a2e6",
"index": 2246,
"step-1": "from cobra.model.fabric import HIfPol\n\nfrom createMo import *\n\nDEFAULT_AUTO_NEGOTIATION = 'on'\nDEFAULT_SPEED = '10G'\nDEFAULT_LINK_DEBOUNCE_INTERVAL = 100\n\nAUTO_NEGOTIATION_CHOICES = ['on', 'off']\nSPEED_CHOICES = ['100M', '... | [
0
] |
list = input().split()
n = int(list[0])
k = int(list[1])
list.clear()
for i in range(0, n):
list.append("")
tmp = input().split()
list[i] = tmp[0] + list[int(tmp[1])-1]
for i in range(0, k):
start = input()
print(len([word for word in list if word.startswith(start)])) | normal | {
"blob_id": "1808be09c2730af5829bb0c7c0c7cfe9f80fe84c",
"index": 7546,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nlist.clear()\nfor i in range(0, n):\n list.append('')\n tmp = input().split()\n list[i] = tmp[0] + list[int(tmp[1]) - 1]\nfor i in range(0, k):\n start = input()\n print(le... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Player(object):
def __init__(self, player_num, px, py, sx, sy, start_direction):
self.player_num = player_num
self.rect = pygame.Rect(px, py, sx, sy)
self.direction = start_direction
self.moto = Moto(player_num, start_direction)
self.moto... | flexible | {
"blob_id": "1d1f1c9b70ca487b48593c85c3e0b5afc10f0b07",
"index": 6642,
"step-1": "<mask token>\n\n\nclass Player(object):\n\n def __init__(self, player_num, px, py, sx, sy, start_direction):\n self.player_num = player_num\n self.rect = pygame.Rect(px, py, sx, sy)\n self.direction = start_... | [
13,
15,
19,
22,
24
] |
<|reserved_special_token_0|>
def remove_zero_bars(dgm):
"""
remove zero bars from diagram
"""
inds = dgm[:, 0] != dgm[:, 1]
return dgm[inds, :]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def remove_filler(dgm, val=np.inf):
"""
remove fille... | flexible | {
"blob_id": "ac459bff6d4281ce07b70dbccde3243412ddb414",
"index": 3155,
"step-1": "<mask token>\n\n\ndef remove_zero_bars(dgm):\n \"\"\"\n remove zero bars from diagram\n \"\"\"\n inds = dgm[:, 0] != dgm[:, 1]\n return dgm[inds, :]\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef remove_fil... | [
1,
2,
3,
4,
5
] |
# __author__ = 'Vasudev Gupta'
import tf_lightning as tl
import tensorflow as tf
class TestModel(tl.LightningModule):
# just a random model with random dataset
def __init__(self):
# simple test model
super().__init__()
self.model = tf.keras.Sequential([
tf.keras.layers.D... | normal | {
"blob_id": "f2397ba3fe1452238f251111f35b06b4a93e0359",
"index": 2441,
"step-1": "<mask token>\n\n\nclass TestModel(tl.LightningModule):\n <mask token>\n <mask token>\n <mask token>\n\n def training_step(self, batch, batch_idx, optimizer_idx):\n pred = self(batch)\n loss = tf.reduce_mea... | [
7,
11,
12,
14,
15
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def merge(L1, L2):
if L1 == []:
return L2
if L2 == []:
return L1
x1, R1 = L1[0], L1[1:]
x2, R2 = L2[0], L2[1:]
if x1 <= x2:
return [x1] + merge(R1, L2)
else:
return [x2] + ... | flexible | {
"blob_id": "056636e2220e529d3f66872a4a48c0984cda1ce4",
"index": 6617,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef merge(L1, L2):\n if L1 == []:\n return L2\n if L2 == []:\n return L1\n x1, R1 = L1[0], L1[1:]\n x2, R2 = L2[0], L2[1:]\n if x1 <= x2:\n return ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Player(pygame.sprite.Sprite):
def __init__(self, group):
super().__init__(group)
self.weapon = Weapon(self, 'Green laser gun')
self.image = load_image('player.jpg', -1)
self.rect = self.image.get_rect()
self.coords = self.rect.x, self.rec... | flexible | {
"blob_id": "244191087fcab2a6f03bf024708484b9838731ed",
"index": 9301,
"step-1": "<mask token>\n\n\nclass Player(pygame.sprite.Sprite):\n\n def __init__(self, group):\n super().__init__(group)\n self.weapon = Weapon(self, 'Green laser gun')\n self.image = load_image('player.jpg', -1)\n ... | [
7,
13,
16,
22,
30
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print(' whats your name boi ?')
<|reserved_special_token_0|>
if name == 'arrya':
print('u are a boi')
elif name == 'jon':
print('basterd')
elif name == 'ned':
print('you are dead man')
elif name == 'rob':
print('the king in the north')
else:
... | flexible | {
"blob_id": "483a5e95a7bfca2cc6b1e7e81740620468fb5623",
"index": 9646,
"step-1": "<mask token>\n",
"step-2": "print(' whats your name boi ?')\n<mask token>\nif name == 'arrya':\n print('u are a boi')\nelif name == 'jon':\n print('basterd')\nelif name == 'ned':\n print('you are dead man')\nelif name ==... | [
0,
1,
2,
3
] |
#!/usr/bin/python
# -*- coding: UTF-8 -*-
from connect import Connect
class Resource:
def __init__(self, row: tuple):
self.video_path = row[0]
self.pic_path = row[1]
| normal | {
"blob_id": "65aa27addaec6014fe5fd66df2c0d3632231a314",
"index": 3124,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Resource:\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Resource:\n\n def __init__(self, row: tuple):\n self.video_path = row[0]\n self.pic_path = ... | [
0,
1,
2,
3,
4
] |
import cv2
import numpy as np
from matplotlib import pyplot as plt
#cargar la imagen a analizar
imagen= cv2.imread("tomate22.jpg")
#cv2.imshow("Original", imagen)
#cv2.waitKey(0)
# Convertimos en escala de grise
gris = cv2.cvtColor(imagen, cv2.COLOR_BGR2GRAY)
#cv2.imshow("En gris", gris)
#cv2.waitKey(0)
# Aplicar s... | normal | {
"blob_id": "9f42a9d0ca622d6c4e2cf20bc2e494262c16055b",
"index": 7744,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nplt.subplot(121), plt.imshow(canny, cmap='gray')\nplt.title('Canny'), plt.xticks([]), plt.yticks([])\n<mask token>\ncv2.drawContours(imagen, contornos, -1, (255, 0, 0), 2)\ncv2.imshow('co... | [
0,
1,
2,
3,
4
] |
# list audio files
import glob
def listFiles(path):
return glob.glob(path + '*.wav')
import random
def getNextFile(files):
return random.choice(files)
import pyaudio
import wave
CHUNK = 1024
def getRandomFile(folder = 'test/'):
files = listFiles(folder)
filename = getNextFile(files)
return filename
def pl... | normal | {
"blob_id": "a3bcd383656284a2236e79b5d5d7acdfe433a13b",
"index": 8409,
"step-1": "<mask token>\n\n\ndef getNextFile(files):\n return random.choice(files)\n\n\n<mask token>\n\n\ndef getRandomFile(folder='test/'):\n files = listFiles(folder)\n filename = getNextFile(files)\n return filename\n\n\ndef pl... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class Timer(object):
<|reserved_special_token_0|>
def reset(self):
self.time_ = 0.0
self.start_ = 0.0
def start(self):
self.start_ = time.clock()
def end(self):
self.time_ += time.clock() - self.start_
<|reserved_special_token_0|>
<|r... | flexible | {
"blob_id": "0cf5b009f384d2ca7162b5a88699afb3702ae1f6",
"index": 1147,
"step-1": "<mask token>\n\n\nclass Timer(object):\n <mask token>\n\n def reset(self):\n self.time_ = 0.0\n self.start_ = 0.0\n\n def start(self):\n self.start_ = time.clock()\n\n def end(self):\n self.t... | [
4,
5,
6,
7,
8
] |
from elements import Node, Bar, Material, Group, Load
from pprint import pprint
# query
# next((e for e in result['coordinates']['nodes'] if e.n == int(el[0])), None)
class Reader():
def read(self, filePath):
"""
Reads text file with nodes and returns the result dict with all objects
and their nested p... | normal | {
"blob_id": "c796123fbbf3adcde59779a104dcafb30a673a79",
"index": 6422,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Reader:\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Reader:\n\n def read(self, filePath):\n \"\"\"\n Reads text file with nodes and returns the resul... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print(auto.head())
sns.pairplot(auto, kind='reg', hue='origin')
plt.show()
<|reserved_special_token_1|>
# EXERCISE:
# Plotting distributions pairwise (2)
# In this exercise, you will generate pairwise joint distributions again. This time, you will make t... | flexible | {
"blob_id": "0eaaa81d3c8bc61368701e1916b42ede88b90d04",
"index": 412,
"step-1": "<mask token>\n",
"step-2": "print(auto.head())\nsns.pairplot(auto, kind='reg', hue='origin')\nplt.show()\n",
"step-3": "# EXERCISE:\n\n# Plotting distributions pairwise (2)\n\n# In this exercise, you will generate pairwise joint... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
import django.core.validators
class Migration(migrations.Migration):
dependencies = [
('Registration', '0015_auto_20150525_1815'),
]
operations = [
migrations.AlterField(
... | normal | {
"blob_id": "7a1be5c9c48413ba1969631e99ecb45cf15ef613",
"index": 559,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('Registration... | [
0,
1,
2,
3,
4
] |
# coding: utf8
from __future__ import unicode_literals
from nltk.tag import stanford
from .SequenceTagger import SequenceTagger
class POSTagger(SequenceTagger):
"""
>>> tagger = POSTagger(model='resources/postagger.model')
>>> tagger.tag(['من', 'به', 'مدرسه', 'رفته_بودم', '.'])
[('من', 'PRO'), ('به', 'P'), ('مدر... | normal | {
"blob_id": "1ac3630e6433a2d11c716b558640cab7c559f6ba",
"index": 4483,
"step-1": "<mask token>\n\n\nclass StanfordPOSTagger(stanford.StanfordPOSTagger):\n <mask token>\n\n def __init__(self, model_filename, path_to_jar, *args, **kwargs):\n self._SEPARATOR = '/'\n super(stanford.StanfordPOSTag... | [
3,
5,
7,
8,
9
] |
/Users/apple/anaconda/lib/python3.5/operator.py | normal | {
"blob_id": "b4a267873c5823ecfa62a5e90b67c37f9cca3cd2",
"index": 8181,
"step-1": "/Users/apple/anaconda/lib/python3.5/operator.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while n > 0:
r = n % 10
sum = sum + r
n = n // 10
print('The total sum of digits is:', sum)
<|reserved_special_token_1|>
n = int(input('Enter a number:\n'))
sum = 0
while n > 0:
r = n % 10
sum = sum + r
... | flexible | {
"blob_id": "78e3750a1bbe9f2f6680937729c1a810bd29fd4d",
"index": 4232,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile n > 0:\n r = n % 10\n sum = sum + r\n n = n // 10\nprint('The total sum of digits is:', sum)\n",
"step-3": "n = int(input('Enter a number:\\n'))\nsum = 0\nwhile n > 0:\n ... | [
0,
1,
2,
3
] |
from django.urls import path
from . import views
urlpatterns = [
path('', views.home, name ='park-home'),
path('login/', views.login, name ='park-login'),
] | normal | {
"blob_id": "2fd490ca54f5d038997cec59a3e07c3f2c2d2538",
"index": 6757,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', views.home, name='park-home'), path('login/', views\n .login, name='park-login')]\n",
"step-3": "from django.urls import path\nfrom . import views\nurlpattern... | [
0,
1,
2,
3
] |
def swap(a,b):
print(a,b)
a=input("enter a value 1 : ")
b=input("enter b value 2 : ")
a,b=b,a
print("the vaalues after swaping the variables are below:")
print("the value of a is : ",a)
print("the value of b is : ",b)
| normal | {
"blob_id": "4fbe4d474e10e08eafee3bcc6173f8cd6b797dde",
"index": 3203,
"step-1": "<mask token>\n",
"step-2": "def swap(a, b):\n print(a, b)\n\n\n<mask token>\n",
"step-3": "def swap(a, b):\n print(a, b)\n\n\n<mask token>\nprint('the vaalues after swaping the variables are below:')\nprint('the value of ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class AmplitudeLogger:
<|reserved_special_token_0|>
async def log_event(self, event):
event = {'api_key': self.api_key, 'events': [event]}
try:
validate(instance=event, schema=self.api_schema)
except ValidationError:
log.error('Inva... | flexible | {
"blob_id": "d32f009f373249b7b602ac36f29982273a2ed192",
"index": 2289,
"step-1": "<mask token>\n\n\nclass AmplitudeLogger:\n <mask token>\n\n async def log_event(self, event):\n event = {'api_key': self.api_key, 'events': [event]}\n try:\n validate(instance=event, schema=self.api_s... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def zero_pad(values, max_m):
m = len(values)
values += [0] * (max_m - m)
def solve_with_solver(values_copy, n):
return xpress_solver(values_copy, n)
def solve_with_net(values_copy, n):
start = time.time()
sum_vals = sum(values_copy)
new_values = [(val / sum_val... | flexible | {
"blob_id": "1f63f9234596787e4859b740d3a7fbfaacc9c0c8",
"index": 9930,
"step-1": "<mask token>\n\n\ndef zero_pad(values, max_m):\n m = len(values)\n values += [0] * (max_m - m)\n\n\ndef solve_with_solver(values_copy, n):\n return xpress_solver(values_copy, n)\n\n\ndef solve_with_net(values_copy, n):\n ... | [
3,
5,
7,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open(tree_csv, 'rU') as csvinput:
with open('../harbordvillage/outfile.csv', 'w+') as csvoutput:
writer = csv.writer(csvoutput, quoting=csv.QUOTE_NONNUMERIC)
reader = csv.reader(csvinput)
all = []
... | flexible | {
"blob_id": "40b9114e4348bab5d76d68a937b3abe95a90c230",
"index": 4130,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(tree_csv, 'rU') as csvinput:\n with open('../harbordvillage/outfile.csv', 'w+') as csvoutput:\n writer = csv.writer(csvoutput, quoting=csv.QUOTE_NONNUMERIC)\n r... | [
0,
1,
2,
3,
4
] |
# Copyright The Cloud Custodian Authors.
# SPDX-License-Identifier: Apache-2.0
from c7n_azure.provider import resources
from c7n_azure.resources.arm import ArmResourceManager
from c7n.utils import type_schema
from c7n.filters.core import ValueFilter
@resources.register('mysql-flexibleserver')
class MySQLFlexibleServ... | normal | {
"blob_id": "b9bc6a9dbb3dbe51fbae45078bd499fb97fa003f",
"index": 3950,
"step-1": "<mask token>\n\n\n@MySQLFlexibleServer.filter_registry.register('server-parameter')\nclass ServerParametersFilter(ValueFilter):\n <mask token>\n schema = type_schema('server-parameter', required=['type', 'name'],\n rin... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(data)
<|reserved_special_token_0|>
print(mx, my)
<|reserved_special_token_0|>
for i in range(len(x)):
num += (x[i] - mx) * (y[i] - my)
den += (x[i] - mx) ** 2
<|reserved_special_token_0|>
print(beta1, beta0)
<|reserv... | flexible | {
"blob_id": "ca6b064dbd8200c49665eaa944fdf1fc80c25726",
"index": 1047,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(data)\n<mask token>\nprint(mx, my)\n<mask token>\nfor i in range(len(x)):\n num += (x[i] - mx) * (y[i] - my)\n den += (x[i] - mx) ** 2\n<mask token>\nprint(beta1, beta0)\n<mas... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
from setuptools import setup
import NagAconda
setup(name=NagAconda.__name__,
version=NagAconda.__version__,
description="NagAconda is a Python Nagios wrapper.",
long_description=open('README').read(),
author='Steven Schlegel',
author_email='steven@schlegel.tech',
... | normal | {
"blob_id": "c3719f30bcf13061134b34b0925dfa2af4535f14",
"index": 7854,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name=NagAconda.__name__, version=NagAconda.__version__, description=\n 'NagAconda is a Python Nagios wrapper.', long_description=open('README'\n ).read(), author='Steven Schle... | [
0,
1,
2,
3
] |
# 0=RED, 1=GREEN, 2=BLUE, 3=ALPHA
#import tkinter as tk
#import tkinter.ttk as ttk
#from tkcolorpicker import askcolor
import time
c1 = [0,0,0,0] #this color
c2 = [0,0,0] #over this color
c3 = [0,0,0] #result
cont='y'
#--------------------------------
while cont=='y':
print('--enter underlay co... | normal | {
"blob_id": "5fa8ae36c4b4a5bffa64f4c65b74b74b29ba246f",
"index": 4578,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile cont == 'y':\n print('--enter underlay color in r,g,b--')\n c2[0] = int(input('red: '))\n c2[1] = int(input('green: '))\n c2[2] = int(input('blue: '))\n print('')\n ... | [
0,
1,
2,
3,
4
] |
# coding: utf-8
from pyquery import PyQuery as pq
html = '''
<div id="container">
<ul class="list">
<li class="item-0">first item</li>
<li class="item-1"><a href="link2.html">second item</a></li>
<li class="item-0 active"><a href="link3.html">third item</a></li>
... | normal | {
"blob_id": "02ab822dacb26d623a474fa45ebb034f9c1291b8",
"index": 1604,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(a, type(a))\nprint(a.attr('href'))\nprint(a.attr.href)\n",
"step-3": "<mask token>\nhtml = \"\"\"\n <div id=\"container\">\n <ul class=\"list\">\n <li class=\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
@app.route('/')
def index():
result_plot = compute_model_output()
return render_template('index.html', graphJSON=result_plot)
def compute_model_output():
num_steps = 500
init_inf = 5
t_inc = 5
t_inf = 9
r_t = 2.5
rho = 1.0
kappa_0 = 0.0
kappa = 0.... | flexible | {
"blob_id": "7d099012584b84e9767bf0ce9d9df1596ca3bbab",
"index": 542,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef index():\n result_plot = compute_model_output()\n return render_template('index.html', graphJSON=result_plot)\n\n\ndef compute_model_output():\n num_steps = 500\n init_inf = 5\n ... | [
2,
3,
4,
5,
6
] |
import datetime
import operator
import geopy
from django.db import models
from django.db.models import Q
from django.db.models.query import QuerySet
from django.db.models import permalink
from django.contrib.auth.models import User
geocoder = geopy.geocoders.Google()
class City(models.Model):
name = models.C... | normal | {
"blob_id": "89ba805e47a9727573e1e25371a70fb887ee170d",
"index": 9141,
"step-1": "<mask token>\n\n\nclass Area(models.Model):\n <mask token>\n <mask token>\n\n\n class Meta:\n unique_together = 'name', 'city'\n ordering = 'name',\n <mask token>\n\n\nclass ApartmentQuerySet(QuerySet):\n\... | [
15,
19,
20,
21,
23
] |
#!/usr/bin/python
# Copyright (c) 2020 Maryushi3
import emoji_data_python as edp
import sys
import pyautogui
from Xlib import display
from PyQt5.QtWidgets import QApplication, QGridLayout, QLabel, QLineEdit, QScrollArea, QSizePolicy, QStackedLayout, QVBoxLayout, QWidget
from PyQt5.QtCore import QEvent, QSettings, Qt, ... | normal | {
"blob_id": "c860c1fa6e7610c60077f0eab1572895a23393fd",
"index": 3725,
"step-1": "<mask token>\n\n\ndef fill_grid_with_char_list(charList):\n global emojiToShowCount\n global fullRowsCount\n global lastRowEmojiCount\n emojiToShowCount = min(len(charList), emojiGridColumnCount *\n emojiGridRowC... | [
17,
19,
21,
24,
29
] |
# Create your models here.
from django.db import models
from django.utils import timezone
from django.db import models
# Create your models here.
#필드 개수가 다르다.
class Post(models.Model):
#이 Post의 저자이다라는 의미, CASCADE : 종속이라는 의미
author = models.ForeignKey('auth.User', on_delete=models.CASCADE)
title = models.C... | normal | {
"blob_id": "fe5398b03d2f0cfc7c972677faa0ea3ec701469e",
"index": 7858,
"step-1": "<mask token>\n\n\nclass Post(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def publish(self):\n self.published_date = timezone.now()\n self.save()\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def DFS(idx, cost, cur_loc):
global min_cost
if min_cost < cost:
return
if idx == N and arr[cur_loc][0]:
if min_cost > cost + arr[cur_loc][0]:
min_cost = cost + arr[cur_loc][0]
return
for i in range(1, N):
... | flexible | {
"blob_id": "4ff7e83c6e85a041578a8b3471cbbb7e0c2543e6",
"index": 2663,
"step-1": "<mask token>\n",
"step-2": "def DFS(idx, cost, cur_loc):\n global min_cost\n if min_cost < cost:\n return\n if idx == N and arr[cur_loc][0]:\n if min_cost > cost + arr[cur_loc][0]:\n min_cost = c... | [
0,
1,
2,
3,
4
] |
import os
import json
import librosa
# Constants
# Dataset used for training
DATASET_PATH = "dataset"
# Where the data is stored
JSON_PATH = "data.json"
# Number of samples considered to preprocess data
SAMPLES_TO_CONSIDER = 22050 # 1 sec worth of sound
# Main function to preprocess the data
def prepare_dataset(dat... | normal | {
"blob_id": "ba808d23f6a8226f40e1c214012a1535ee1e9e98",
"index": 2947,
"step-1": "<mask token>\n\n\ndef prepare_dataset(dataset_path, json_path, n_mfcc=13, hop_length=512,\n n_fft=2048):\n data = {'mappings': [], 'labels': [], 'MFCCs': [], 'files': []}\n for i, (dir_path, dir_names, filenames) in enumer... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class _PULPIER:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class _PULPIER:
def __init__(self):
self.name = 'PULPIER'
self.definitions = pulpy
self.parents = []
self.childen = []
self.propertie... | flexible | {
"blob_id": "a1d1056f302cf7bc050537dd8cc53cdb2da7e989",
"index": 5507,
"step-1": "<mask token>\n",
"step-2": "class _PULPIER:\n <mask token>\n",
"step-3": "class _PULPIER:\n\n def __init__(self):\n self.name = 'PULPIER'\n self.definitions = pulpy\n self.parents = []\n self.c... | [
0,
1,
2,
3
] |
#!/usr/bin/env python
"""
This code is fot testing the region growing.
"""
import os
import sys
import time
import nibabel as nib
import region_growing as rg
import matplotlib.pyplot as plt
import numpy as np
img = nib.load("zstat1.nii.gz")
data = img.get_data()
#test coor [36,60,28] [21,39,30] [23,38,30]
coor = [23,... | normal | {
"blob_id": "6bcddd1b2ec8653400f710e5cab552d4bec75b6b",
"index": 1162,
"step-1": "#!/usr/bin/env python\n\"\"\"\nThis code is fot testing the region growing.\n\"\"\"\nimport os\nimport sys\nimport time\nimport nibabel as nib\nimport region_growing as rg\nimport matplotlib.pyplot as plt \nimport numpy as np\n\nim... | [
0
] |
#https://docs.python.org/3.4/library/itertools.html#module-itertools
l = [(1, 2, 9), (1, 3, 12), (2, 3, 8), (2, 4, 4), (2, 5, 7), (3, 5, 5), (3, 6, 2), (4, 5, 2), (4, 7, 10),
(5, 6, 11), (5, 7, 2), (6, 8, 4), (7, 8, 4), (7, 9, 3), (8, 9, 13)]
b = ['America', 'Sudan', 'Srilanka', 'Pakistan', 'Nepal', 'India'... | normal | {
"blob_id": "629353392e3a4f346f734543ae3f2b8dc616a6c3",
"index": 5816,
"step-1": "<mask token>\n\n\ndef itertools_groupby_example(list_of_nodes):\n graph = defaultdict(list)\n for key, group in groupby(l, lambda x: x[0]):\n graph[key].append(list(group))\n print(dict(graph))\n\n\ndef itertools_fa... | [
7,
10,
11,
12,
14
] |
#!/bin/python
from flask import Flask, jsonify, request
import subprocess
import os
app = Flask(__name__)
text = ""
greetings = "'/play' and '/replay'\n"
@app.route('/')
def index():
return greetings
@app.route('/play', methods=['POST'])
def play():
global text
text = request.data.decode('utf-8')
o... | normal | {
"blob_id": "956e63bf06255df4a36b5fa97aa62c0ed805c3f3",
"index": 9452,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef index():\n return greetings\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\n@app.route('/')\ndef index():\n return greetings\n\n\n@app.route('/play', methods=['POST'])\ndef play():\... | [
1,
4,
5,
6,
7
] |
import random
import tqdm
from keras.models import load_model
from ModelUtil import precision, recall, f1
from tqdm import tqdm
import cv2 as cv
import numpy as np
import os
import pandas as pd
from PIL import Image
os.environ['CUDA_VISIBLE_DEVICES']='1'
model_path = '/home/bo/Project/densenet.hdf5'
train_img_path... | normal | {
"blob_id": "c2b3594d25e2d1670d9b99e0d3484c680f59421f",
"index": 9465,
"step-1": "<mask token>\n\n\ndef preprocess_image(image_path, desired_size=SIZE):\n \"\"\"\n Resize the picture to the desired size\n :param image_path: the path of image folder\n :param desired_size: the size that image will be c... | [
9,
10,
12,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main():
graphics = BreakoutGraphics()
lives = NUM_LIVES
graphics.window.add(graphics.scoreboard, 0, graphics.window_height)
while True:
pause(FRAME_RATE)
if graphics.ball_fall_down():
... | flexible | {
"blob_id": "b218f5e401510f844006cb6079737b54aa86827b",
"index": 2194,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n graphics = BreakoutGraphics()\n lives = NUM_LIVES\n graphics.window.add(graphics.scoreboard, 0, graphics.window_height)\n while True:\n pause(FRAME_RA... | [
0,
2,
3,
4,
5
] |
from django import template
from apps.account.models import User, Follow, RequestFollow
from apps.post.models import Post
register = template.Library()
@register.inclusion_tag('user/user_list.html')
def user_list():
"""show user name list"""
users = User.objects.all()
return {"users": users}
# @regist... | normal | {
"blob_id": "999c19fd760ffc482a15f5a14e188d416fcc5f21",
"index": 7218,
"step-1": "<mask token>\n\n\n@register.inclusion_tag('user/user_list.html')\ndef user_list():\n \"\"\"show user name list\"\"\"\n users = User.objects.all()\n return {'users': users}\n\n\n@register.simple_tag()\ndef accept_request(pk... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class TestTaniHub:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TestTaniHub:
<|reserved_special_token_0|>
<|reserved_special_to... | flexible | {
"blob_id": "777dc2056443f0404ccb75d570f2ddc3a3aa747b",
"index": 6669,
"step-1": "<mask token>\n\n\nclass TestTaniHub:\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass TestTaniHub:\n <mask token>\n <mask token>\n\n def test_tanihub_number_2... | [
1,
2,
4,
6,
8
] |
from django.db.models import Q
from django.contrib.auth.mixins import LoginRequiredMixin
from django.http import HttpResponseRedirect
from django.shortcuts import render, redirect
from django.views.generic import ListView, DetailView, CreateView, UpdateView, DeleteView
from carga_horaria.models import Profesor, Asignat... | normal | {
"blob_id": "d0d86d8b5b276218add6dd11a44d5c3951cc4e14",
"index": 3846,
"step-1": "<mask token>\n\n\nclass AsistenteDetailView(LoginRequiredMixin, DetailView):\n \"\"\"\n Detalle de Asistente\n \"\"\"\n model = Asistente\n template_name = 'carga_horaria/asistente/detalle_asistente.html'\n\n\ncl... | [
52,
53,
56,
73,
85
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
router.register('users', views.CategoryView)
<|reserved_special_token_0|>
if settings.DEBUG:
urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT
)
<|reserved_special_token_1|>
<|reserved_spec... | flexible | {
"blob_id": "4a8fa195a573f8001e55b099a8882fe71bcca233",
"index": 8335,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrouter.register('users', views.CategoryView)\n<mask token>\nif settings.DEBUG:\n urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT\n )\n",
"step-3": ... | [
0,
1,
2,
3,
4
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.