code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
import numpy as np
from random import randint
def combinacaoDeEmbralhamento(qtdeLinhas):
while True:
a = randint(0,qtdeLinhas)
b = randint(0,qtdeLinhas)
if a == b :
continue
else:
break
resp = [[a,b]]
return resp
def embaralhaMatriz(x):
for i in range(qtdeLinhas):
print(i)
combinacaoDeEmbralha... | normal | {
"blob_id": "28ed494939d0928bf3ad4f07f58186374e925426",
"index": 7024,
"step-1": "<mask token>\n\n\ndef combinacaoDeEmbralhamento(qtdeLinhas):\n while True:\n a = randint(0, qtdeLinhas)\n b = randint(0, qtdeLinhas)\n if a == b:\n continue\n else:\n break\n ... | [
2,
3,
4,
5,
6
] |
def pin():
print('wqeqwwqe')
from tkinter import *
from tkinter import messagebox
from PIL import Image
from PIL import ImageTk
window = Tk() #创建一个窗口
window.title('爱你吆') #定义窗口标题
window.geometry('400x400+800+200') #定义窗口大小 窗口显示位置
# window.protocol('WM_DELETE_WINDOW', pin) #摧毁窗口，引到另一个函数命令
window.protocol(... | normal | {
"blob_id": "55c9fe8caf1983f22d5a752574f590fa129e8017",
"index": 1443,
"step-1": "def pin():\n print('wqeqwwqe')\n\n\n<mask token>\n",
"step-2": "def pin():\n print('wqeqwwqe')\n\n\n<mask token>\nwindow.title('爱你吆')\nwindow.geometry('400x400+800+200')\nwindow.protocol('WM_DELETE_WINDOW')\n<mask token>\nl... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
renWin.SetMultiSamples(0)
renWin.AddRenderer(ren1)
renWin.AddRenderer(ren2)
<|reserved_special_token_0|>
iren.SetRenderWindow(renWin)
<|reserved_special_token_0|>
pl3d.SetXYZFileName('' + str(VTK_DATA_ROOT) + '/Data/combxyz.bin')
... | flexible | {
"blob_id": "7399612f64eb8e500bc676e6d507be5fe375f40f",
"index": 3746,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrenWin.SetMultiSamples(0)\nrenWin.AddRenderer(ren1)\nrenWin.AddRenderer(ren2)\n<mask token>\niren.SetRenderWindow(renWin)\n<mask token>\npl3d.SetXYZFileName('' + str(VTK_DATA_ROOT) + '/Da... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.2 on 2017-07-20 08:05
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
depe... | normal | {
"blob_id": "e68d872232b3eab4c33cbbe4376be7dd788888e2",
"index": 1242,
"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
] |
"""
Create all figures and Excel files that combine data from all embryos in a given genetic background
Copyright (C) 2017 Ahmet Ay, Dong Mai, Soo Bin Kwon, Ha Vu
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software ... | normal | {
"blob_id": "86928f4358e4999a5cec8bfad1fe055c9a2778d1",
"index": 6230,
"step-1": "<mask token>\n\n\ndef main():\n args = sys.argv[1:]\n num_args = len(args)\n req_args = [False] * 3\n num_bins = DEFAULT_NUM_BIN\n if num_args >= 6:\n i = 0\n while i < num_args - 1:\n option... | [
2,
3,
4,
5,
6
] |
import pickle
from sklearn import linear_model
from sklearn.model_selection import train_test_split
import random
from sklearn.manifold import TSNE
import matplotlib
def loadXY():
zippedXY = pickle.load(open("../Vectorizer/zippedXY_wff_2k.p","rb"))
#random.shuffle(zippedXY)
X,Y = zip(*zippedXY)
return X,Y
def out... | normal | {
"blob_id": "cb13011def8fc7ed6a2e98a794343857e3e34562",
"index": 3142,
"step-1": "import pickle\nfrom sklearn import linear_model\nfrom sklearn.model_selection import train_test_split\nimport random\nfrom sklearn.manifold import TSNE\nimport matplotlib\n\ndef loadXY():\n\tzippedXY = pickle.load(open(\"../Vectori... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for line in hand:
line = line.rstrip()
x = re.findall('([0-9]+)', line)
if len(x) > 0:
for i in x:
total += float(i)
print('sum is', int(total))
<|reserved_special_token_1|>
<|reserved_special_to... | flexible | {
"blob_id": "860908126d473e6c4ed070992a1b518683fd4c27",
"index": 3275,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in hand:\n line = line.rstrip()\n x = re.findall('([0-9]+)', line)\n if len(x) > 0:\n for i in x:\n total += float(i)\nprint('sum is', int(total))\n",
... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
import argparse
import subprocess
def module_exists(module_name):
try:
__import__(module_name)
except ImportError:
return False
else:
return True
def quote(items):
return ["'" + item + "'" for item in items]
if module_exists('urllib.parse'):
from url... | normal | {
"blob_id": "68371acc58da6d986d94d746abb4fea541d65fdd",
"index": 3384,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef module_exists(module_name):\n try:\n __import__(module_name)\n except ImportError:\n return False\n else:\n return True\n\n\ndef quote(items):\n r... | [
0,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class LaunchMovieLottery(object):
<|reserved_special_token_0|>
def movie_list(self):
movie_list = MovieList(file_name, function)
self.return_movie_list = movie_list.return_movie_list()
self.full_list = movie_list.return_full_list()
return [self.ret... | flexible | {
"blob_id": "e35a106a3852a7a004fdae6819d4075e1fe929d6",
"index": 4373,
"step-1": "<mask token>\n\n\nclass LaunchMovieLottery(object):\n <mask token>\n\n def movie_list(self):\n movie_list = MovieList(file_name, function)\n self.return_movie_list = movie_list.return_movie_list()\n self.... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
@app.route('/direct')
def direct():
"""
A RemoteFlowSource is used directly as DN and search filter using a oneline call to .search
"""
unsafe_dc = request.args['dc']
unsafe_filter = request.args['username']
dn = 'dc={}'.format(unsafe_dc)
search_filter = '(user... | flexible | {
"blob_id": "b51591de921f6e153c1dd478cec7fad42ff4251a",
"index": 749,
"step-1": "<mask token>\n\n\n@app.route('/direct')\ndef direct():\n \"\"\"\n A RemoteFlowSource is used directly as DN and search filter using a oneline call to .search\n \"\"\"\n unsafe_dc = request.args['dc']\n unsafe_filter =... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if n % 10 == 1 and (n < 11 or n > 20):
print(n, 'korova')
elif n % 10 > 1 and n % 10 < 5 and (n < 11 or n > 20):
print(n, 'korovy')
else:
print(n, 'korov')
<|reserved_special_token_1|>
n = int(input())
if n % 10 == ... | flexible | {
"blob_id": "78037d936ee5f9b31bf00263885fbec225a4f8f2",
"index": 2191,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif n % 10 == 1 and (n < 11 or n > 20):\n print(n, 'korova')\nelif n % 10 > 1 and n % 10 < 5 and (n < 11 or n > 20):\n print(n, 'korovy')\nelse:\n print(n, 'korov')\n",
"step-3"... | [
0,
1,
2,
3
] |
# This file is Copyright (c) 2020 LambdaConcept <contact@lambdaconcept.com>
# License: BSD
from math import log2
from nmigen import *
from nmigen.utils import log2_int
from nmigen_soc import wishbone
from nmigen_soc.memory import MemoryMap
from lambdasoc.periph import Peripheral
class gramWishbone(Peripheral, Elab... | normal | {
"blob_id": "3775ba538d6fab13e35e2f0761a1cacbe087f339",
"index": 4723,
"step-1": "<mask token>\n\n\nclass gramWishbone(Peripheral, Elaboratable):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass gramWishbone(Peripheral, Elaboratable):\n\n def __init__(self, core, data_width=32, gra... | [
1,
2,
3,
4,
5
] |
from django.urls import path
from .views import *
urlpatterns = [
path('', ListUser.as_view() , name = 'list'),
path('register/', UserRegister.as_view() , name = 'register'),
path('login/', UserLogin.as_view() , name = 'login'),
path('delete/' , UserDelete.as_view() , name ='delete'),
path('update/... | normal | {
"blob_id": "5fe4f2738285d2f4b8bbfee2c4c6d15665737ea4",
"index": 8627,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', ListUser.as_view(), name='list'), path('register/',\n UserRegister.as_view(), name='register'), path('login/', UserLogin.\n as_view(), name='login'), path('d... | [
0,
1,
2,
3
] |
# Copyright 2017 The LUCI Authors. All rights reserved.
# Use of this source code is governed under the Apache License, Version 2.0
# that can be found in the LICENSE file.
DEPS = [
'step',
]
def RunSteps(api):
try:
api.step('test step', [{}])
except AssertionError as e:
assert str(e) == 'Type <type \'... | normal | {
"blob_id": "25d210144ef209fd5e4ff7e4e4c2e77fd7eb79ac",
"index": 3480,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef GenTests(api):\n yield api.test('basic')\n",
"step-3": "<mask token>\n\n\ndef RunSteps(api):\n try:\n api.step('test step', [{}])\n except AssertionError as e:\n... | [
0,
1,
2,
3,
4
] |
#
# -*- coding: utf-8 -*-
# Copyright 2019 Fortinet, Inc.
# GNU General Public License v3.0+
# (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
"""
The fortios firewall monitor class
It is in this file the runtime information is collected from the device
for a given resource, parsed, and the facts tree is popu... | normal | {
"blob_id": "62bc8fec6833c5e8bc1598941eaad141ab6c9d5a",
"index": 3758,
"step-1": "<mask token>\n\n\nclass FirewallFacts(object):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass FirewallFacts(object):\n <mask token>\n <mask token>\n\n def populate_facts(self... | [
1,
2,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def modCount(n, m):
if m <= n:
inBetween = n - m
dividible = []
for x in range(m + 1, n):
if x % m == 0:
dividible.append(x)
return (
"""There are {} numbers between {} and {}
and ... | flexible | {
"blob_id": "0699c9f70f1c16b4cb9837edf7a4ef27f021faec",
"index": 8318,
"step-1": "<mask token>\n",
"step-2": "def modCount(n, m):\n if m <= n:\n inBetween = n - m\n dividible = []\n for x in range(m + 1, n):\n if x % m == 0:\n dividible.append(x)\n retur... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution:
def canDivideIntoSubsequences(self, nums: List[int], K: int) ->bool:
return len(nums) >... | flexible | {
"blob_id": "6b55a9061bb118558e9077c77e18cfc81f3fa034",
"index": 1092,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution:\n\n def canDivideIntoSubsequences(self, nums: List[int], K: int) ->bool:\n return len(nu... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def convertEnEntier(nombre):
result = ''
if nombre == 4:
result = 'IV'
if nombre == 3:
result = 'III'
if nombre == 2:
result = 'II'
if nombre == 1:
result = 'I'
return result
<|reserved_special_token_0... | flexible | {
"blob_id": "ef7fad5019e79950e8fad56404e9ba5d302cfe1c",
"index": 7596,
"step-1": "<mask token>\n",
"step-2": "def convertEnEntier(nombre):\n result = ''\n if nombre == 4:\n result = 'IV'\n if nombre == 3:\n result = 'III'\n if nombre == 2:\n result = 'II'\n if nombre == 1:\n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class AirflowPlugin(AirflowPlugin):
name = 'airflow-plugin'
operators = []
hooks = []
executors = []
macros = []
admin_views = []
flask_blueprints = []
menu_links = []
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0... | flexible | {
"blob_id": "39f1fc04911f8d22d07532add24cd1671a569e72",
"index": 9414,
"step-1": "<mask token>\n\n\nclass AirflowPlugin(AirflowPlugin):\n name = 'airflow-plugin'\n operators = []\n hooks = []\n executors = []\n macros = []\n admin_views = []\n flask_blueprints = []\n menu_links = []\n\n\n... | [
2,
3,
4,
5,
6
] |
# -*- coding: utf-8 -*-
# @Time : 2019/3/21 20:12
# @Author : for
# @File : test01.py
# @Software: PyCharm
import socket
s=socket.socket()
host=socket.gethostname()
port=3456
s.connect((host,port))
cmd=input(">>>")
s.sendall(cmd.encode())
data=s.recv(1024)
print(data.decode())
s.close()
| normal | {
"blob_id": "596814032218c3db746f67e54e4f1863753aea06",
"index": 6299,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ns.connect((host, port))\n<mask token>\ns.sendall(cmd.encode())\n<mask token>\nprint(data.decode())\ns.close()\n",
"step-3": "<mask token>\ns = socket.socket()\nhost = socket.gethostname... | [
0,
1,
2,
3,
4
] |
import cv2
import numpy as np
"""
# Create a black image
image = np.zeros((512,512,3), np.uint8)
# Can we make this in black and white?
image_bw = np.zeros((512,512), np.uint8)
cv2.imshow("Black Rectangle (Color)", image)
cv2.imshow("Black Rectangle (B&W)", image_bw)
cv2.waitKey(0)
cv2.destroyAllWindows()
image = ... | normal | {
"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|>
def on_release(key):
if key == keyboard.Key.esc:
write_in_file()
return False
def write_in_file():
file = open('strokes.txt', 'a')
for k in list:
file.writelines('{}\n'.format(str(k)))
file.close()
<|reserved_special_token_0|>
<|reserved_speci... | flexible | {
"blob_id": "e60fcf19560b4826577797c8ae8b626ff984dcfd",
"index": 6923,
"step-1": "<mask token>\n\n\ndef on_release(key):\n if key == keyboard.Key.esc:\n write_in_file()\n return False\n\n\ndef write_in_file():\n file = open('strokes.txt', 'a')\n for k in list:\n file.writelines('{}\... | [
2,
3,
4,
5,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def register_handlers_for_other(dp: Dispatcher):
dp.register_message_handler(new_member, content_types=['new_chat_members'])
dp.register_message_handler(left_member, content_types=['left_chat_member']
)
<|reser... | flexible | {
"blob_id": "dfcfa4fa036fe8c058d66fc0b9ea73ddb9d4446e",
"index": 7524,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef register_handlers_for_other(dp: Dispatcher):\n dp.register_message_handler(new_member, content_types=['new_chat_members'])\n dp.register_message_handler(left_member, content... | [
0,
1,
2,
3,
4
] |
from flask import Flask, render_template, request
import random, requests
app = Flask(__name__)
@app.route('/')
def hello():
# return 'Hello World'
return render_template('index.html')
# root 디렉토리에 있는 templates라는 폴더를 탐색하여 파일을 찾음
@app.route('/ace')
def ace():
return '불기둥!'
@app.route('/html')
def html... | normal | {
"blob_id": "9fa3a7c57b311a47e67de73bf6083f1f151d73f4",
"index": 8554,
"step-1": "<mask token>\n\n\n@app.route('/html')\ndef html():\n return '<h1> 태그 사용할 수 있어요! <h1>'\n\n\n<mask token>\n\n\n@app.route('/ping')\ndef ping():\n return render_template('ping.html')\n\n\n@app.route('/pong')\ndef pong():\n us... | [
7,
10,
14,
16,
17
] |
<|reserved_special_token_0|>
class Company(models.Model):
<|reserved_special_token_0|>
@classmethod
def create(cls, name):
company = cls(name=name)
return company
def __str__(self):
return self.name
class Entry(models.Model):
fetched_date = models.DateTimeField()
me... | flexible | {
"blob_id": "47f6c4b3c279a065b8f21dab2faa71271db8d6ab",
"index": 6680,
"step-1": "<mask token>\n\n\nclass Company(models.Model):\n <mask token>\n\n @classmethod\n def create(cls, name):\n company = cls(name=name)\n return company\n\n def __str__(self):\n return self.name\n\n\ncla... | [
7,
8,
11,
12,
13
] |
<|reserved_special_token_0|>
def array_to_stack(stack, source):
"""
-------------------------------------------------------
Pushes contents of source onto stack. At finish, source is empty.
Last value in source is at bottom of stack,
first value in source is on top of stack.
Use: array_to_sta... | flexible | {
"blob_id": "dab9b58b08b562d902ee0ae1104198cb1ebbffe5",
"index": 1928,
"step-1": "<mask token>\n\n\ndef array_to_stack(stack, source):\n \"\"\"\n -------------------------------------------------------\n Pushes contents of source onto stack. At finish, source is empty.\n Last value in source is at bo... | [
4,
9,
12,
13,
14
] |
<|reserved_special_token_0|>
class PingWindow:
<|reserved_special_token_0|>
def __init__(self, last_parent):
self.last_parent = last_parent
self.main_widget = QWidget()
self.main_widget.setMaximumHeight(400)
self.parent_layout = QVBoxLayout()
self.ping_log_layout = QHB... | flexible | {
"blob_id": "75b1d2fb927063669a962f72deb57323001c0b7a",
"index": 5657,
"step-1": "<mask token>\n\n\nclass PingWindow:\n <mask token>\n\n def __init__(self, last_parent):\n self.last_parent = last_parent\n self.main_widget = QWidget()\n self.main_widget.setMaximumHeight(400)\n se... | [
3,
4,
5,
6,
7
] |
import boto3
import pprint
import yaml
#initialize empty dictionary to store values
new_dict = {}
count = 0
new_dict2 = {}
# dev = boto3.session.Session(profile_name='shipt')
mybatch = boto3.client('batch')
#load config properties
with open('config.yml') as f:
content = yaml.load(f)
# pprint.pprint(content) #to... | normal | {
"blob_id": "3ba9ff00b0d6a2006c714a9818c8b561d884e252",
"index": 2302,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('config.yml') as f:\n content = yaml.load(f)\n<mask token>\nfor k, v in response.items():\n if k == 'jobDefinitions':\n new_dict = v[0]['containerProperties']\nprin... | [
0,
1,
2,
3,
4
] |
import sys
sys.path.append("../circos_report/cnv_anno2conf")
from cnv_anno2conf import main_cnv
tarfile = {"yaml": "data/test_app.yaml"}
def test_main_cnv():
main_cnv(tarfile)
if __name__ == "__main__":
test_main_cnv()
| normal | {
"blob_id": "3c0beb7be29953ca2d7b390627305f4541b56efa",
"index": 69,
"step-1": "<mask token>\n\n\ndef test_main_cnv():\n main_cnv(tarfile)\n\n\n<mask token>\n",
"step-2": "<mask token>\nsys.path.append('../circos_report/cnv_anno2conf')\n<mask token>\n\n\ndef test_main_cnv():\n main_cnv(tarfile)\n\n\nif _... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class CardRarityParam(CardTextParameter):
<|reserved_special_token_0|>
@classmethod
def get_parameter_name(cls) ->str:
return 'rarity'
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "c7d9bbdff9148c5d928de66f4406ee8b4e1bcdac",
"index": 2672,
"step-1": "<mask token>\n\n\nclass CardRarityParam(CardTextParameter):\n <mask token>\n\n @classmethod\n def get_parameter_name(cls) ->str:\n return 'rarity'\n <mask token>\n <mask token>\n <mask token>\n <mask tok... | [
4,
5,
6,
8,
12
] |
# -*- encoding:utf-8 -*-
import os
import unittest
from HTMLTestRunner_cn import HTMLTestRunner
from time import sleep
from framework.SunFlower import SunFlower
from testcase.TestCRM import TestCRM
class TestCRMcreateCustomer(TestCRM):
# 创建客户
def createCustomer(self):
# 点击客户图标
self.driver.... | normal | {
"blob_id": "74bc530d53cd86c52c44ba8e98d4d8f502032340",
"index": 2423,
"step-1": "<mask token>\n\n\nclass TestCRMcreateCustomer(TestCRM):\n <mask token>\n\n def test_weiChat(self):\n self.login()\n self.createCustomer()\n self.logout()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('/Users/ste/Desktop/Ste/Python/AlgorithmsCourse/KargerMinCut.txt'
) as v_list_file:
for line in v_list_file:
node = map(int, line.split())
for adjacent in node[1:]:
edges.append([node[... | flexible | {
"blob_id": "1b7b94a0331e2462f83f4f77bcfaefbeefdf24f4",
"index": 3754,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('/Users/ste/Desktop/Ste/Python/AlgorithmsCourse/KargerMinCut.txt'\n ) as v_list_file:\n for line in v_list_file:\n node = map(int, line.split())\n for adjace... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def encrypt(message, passphrase):
passphrase = trans(passphrase)
IV = Random.new().read(BLOCK_SIZE)
aes = AES.new(passphrase, AES.MODE_CFB, IV)
return base64.b32encode(IV + aes.encrypt(message)).decode('utf-8')
def decrypt(encrypted, passphrase):
passphrase = trans(p... | flexible | {
"blob_id": "e55115a65ebee5d41dcd01a5cbabc328acf152da",
"index": 6079,
"step-1": "<mask token>\n\n\ndef encrypt(message, passphrase):\n passphrase = trans(passphrase)\n IV = Random.new().read(BLOCK_SIZE)\n aes = AES.new(passphrase, AES.MODE_CFB, IV)\n return base64.b32encode(IV + aes.encrypt(message)... | [
7,
9,
10,
12,
13
] |
<|reserved_special_token_0|>
def emit_all_users(channel):
"""emits all users"""
all_users = [user.name for user in db.session.query(models.User1).all()]
socketio.emit(channel, {'allUsers': all_users})
return channel
<|reserved_special_token_0|>
@socketio.on('new google user')
def on_new_google_use... | flexible | {
"blob_id": "8d48b5b831edb62b2d9624bc23cae45d390fd224",
"index": 8035,
"step-1": "<mask token>\n\n\ndef emit_all_users(channel):\n \"\"\"emits all users\"\"\"\n all_users = [user.name for user in db.session.query(models.User1).all()]\n socketio.emit(channel, {'allUsers': all_users})\n return channel\... | [
12,
13,
14,
18,
19
] |
class BaseService:
def __init__(self, context):
self._context = context
def post(self, path, body):
result = self._context.http.post(path, body)
return result.json()["Data"]
| normal | {
"blob_id": "5000663e3cde9c1a1100c9022707ccae13db0034",
"index": 1426,
"step-1": "<mask token>\n",
"step-2": "class BaseService:\n <mask token>\n <mask token>\n",
"step-3": "class BaseService:\n <mask token>\n\n def post(self, path, body):\n result = self._context.http.post(path, body)\n ... | [
0,
1,
2,
3,
4
] |
# THIS FILE WAS CREATED IN THIS DIRECTORY EARLIER, NOW MOIVED TO ROOT OF THE REPO
print "Hello buddy"
print "Let's get started"
spy_name = raw_input ("What is your spy name? ")
if len(spy_name) >3:
print "Welcome " + spy_name + ". Glad to have you with us."
spy_salutation= raw_input("What's your titl... | normal | {
"blob_id": "79f03af05fb40f5f5247b582eabae2dc125e6b52",
"index": 4522,
"step-1": "# THIS FILE WAS CREATED IN THIS DIRECTORY EARLIER, NOW MOIVED TO ROOT OF THE REPO\r\n\r\n\r\nprint \"Hello buddy\"\r\nprint \"Let's get started\"\r\nspy_name = raw_input (\"What is your spy name? \")\r\nif len(spy_name) >3:\r\n ... | [
0
] |
<|reserved_special_token_0|>
@pytest.fixture
def runner() ->CliRunner:
"""Fixture for invoking command-line interfaces."""
return CliRunner()
def test_main_succeeds(runner: CliRunner) ->None:
"""It exits with a status code of zero."""
with runner.isolated_filesystem():
df = generate_test_dat... | flexible | {
"blob_id": "97a51d959ad642467c508cedc8786f636e4050bb",
"index": 1333,
"step-1": "<mask token>\n\n\n@pytest.fixture\ndef runner() ->CliRunner:\n \"\"\"Fixture for invoking command-line interfaces.\"\"\"\n return CliRunner()\n\n\ndef test_main_succeeds(runner: CliRunner) ->None:\n \"\"\"It exits with a s... | [
3,
6,
7,
8,
9
] |
import argparse
import cv2
import numpy as np
refPt = []
cropping = False
def click_and_crop(event, x, y, flags, param):
global refPt, cropping
if event == cv2.EVENT_LBUTTONDOWN:
refPt = [(x, y)]
cropping = True
elif event == cv2.EVENT_LBUTTONUP:
refPt.append((x, y))
cropping = False
cv2.rect... | normal | {
"blob_id": "986df5a41bc87ecb390dfbd1db9e1f5cd6c5b8fb",
"index": 9702,
"step-1": "\nimport argparse\nimport cv2\nimport numpy as np\n \n\nrefPt = []\ncropping = False\n \ndef click_and_crop(event, x, y, flags, param):\n\tglobal refPt, cropping\n \n\tif event == cv2.EVENT_LBUTTONDOWN:\n\t\trefPt = [(x, y)]\n\t\tc... | [
0
] |
import os
import closet
import unittest
import tempfile
def in_response(response, value):
return value.encode() in response.data
def is_404(response):
response.status_code == 404
class ClosetTestBase(unittest.TestCase):
def setUp(self):
"""Set up test environment befor each test"""
se... | normal | {
"blob_id": "a5856e12c281ed6a252f499a380f9c51082ea740",
"index": 3711,
"step-1": "<mask token>\n\n\nclass ModelBase(unittest.TestCase):\n <mask token>\n <mask token>\n\n def get(self, url):\n \"\"\"Process a GET request to the app\"\"\"\n return self.app.get(get_url(url), follow_redirects=... | [
31,
43,
44,
49,
56
] |
import subprocess
import logging
import time
import argparse
import threading
import os
import matplotlib.pyplot as plt
import numpy as np
import argparse
def runWeka(wekapath, modelpath, datapath):
os.chdir(wekapath)
proc = subprocess.Popen(['/usr/bin/java', '-classpath', 'weka.jar', 'weka.classifiers.functio... | normal | {
"blob_id": "a1f0eced5d122fe8557ebc4d707c87b4194513e3",
"index": 4976,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef runWeka(wekapath, modelpath, datapath):\n os.chdir(wekapath)\n proc = subprocess.Popen(['/usr/bin/java', '-classpath', 'weka.jar',\n 'weka.classifiers.functions.Multi... | [
0,
1,
2,
3,
4
] |
"""
爱丽丝和鲍勃有不同大小的糖果棒：A[i] 是爱丽丝拥有的第 i 根糖果棒的大小，B[j] 是鲍勃拥有的第 j 根糖果棒的大小。
因为他们是朋友，所以他们想交换一根糖果棒，这样交换后，他们都有相同的糖果总量。（一个人拥有的糖果总量是他们拥有的糖果棒大小的总和。）
返回一个整数数组 ans，其中 ans[0] 是爱丽丝必须交换的糖果棒的大小，ans[1] 是 Bob 必须交换的糖果棒的大小。
如果有多个答案，你可以返回其中任何一个。保证答案存在。
"""
def fairCandySwap(A, B):
sumA, sumB = sum(A), sum(B)
setA, setB = set(A), se... | normal | {
"blob_id": "9abc5f18e2eb07afe6bc31d6bd27298350707d1d",
"index": 962,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef fairCandySwap(A, B):\n sumA, sumB = sum(A), sum(B)\n setA, setB = set(A), set(B)\n delta = (sumA - sumB) // 2\n for j in setB:\n if j + delta in setA:\n ... | [
0,
1,
2,
3
] |
"""
Registers $v0 and $v1 are used to return values from functions.
Registers $t0 – $t9 are caller-saved registers that are used to
hold temporary quantities that need not be preserved across calls
Registers $s0 – $s7 (16–23) are callee-saved registers that hold long-lived
values that should be preserved across calls.... | normal | {
"blob_id": "63bc191a81a200d3c257de429c082cc8d13c98f4",
"index": 9952,
"step-1": "<mask token>\n\n\nclass MipsVisitor:\n <mask token>\n\n def __init__(self, inherit_graph, output_file='mips_code.mips'):\n self.inherit_graph, _ = inherit_graph\n self.offset = dict()\n self.type_index = ... | [
25,
31,
32,
48,
50
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
array = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
solution = Solution.Find(6, array)
<|reserved_special_token_1|>
from find import Solution
array = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
solution = Solution.Find(6, array)
| flexible | {
"blob_id": "d4361b169bf75d3af82eca3d26609961ccc2f27e",
"index": 2405,
"step-1": "<mask token>\n",
"step-2": "<mask token>\narray = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]\nsolution = Solution.Find(6, array)\n",
"step-3": "from find import Solution\narray = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]\nsolution = Solution.Fi... | [
0,
1,
2
] |
# coding:utf-8
from flask_sqlalchemy import SQLAlchemy
from config.manager import app
from config.db import db
class Category(db.Model):
__tablename__ = 'category'
id = db.Column(db.Integer, primary_key=True) # 编号
name = db.Column(db.String(20), nullable=False) # 账号
addtime = db.Column(db.DateTime, ... | normal | {
"blob_id": "743aa4ccbb9a131b5ef3d04475789d3d1da1a2fa",
"index": 2407,
"step-1": "<mask token>\n\n\nclass Category(db.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Category(db.Model):\n __tablename__... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for _ in range(5):
sum_value += int(input())
print(sum_value)
<|reserved_special_token_1|>
sum_value = 0
for _ in range(5):
sum_value += int(input())
print(sum_value)
| flexible | {
"blob_id": "4add80894036e0395a6e6eb13e8a2db0d963de8c",
"index": 9654,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(5):\n sum_value += int(input())\nprint(sum_value)\n",
"step-3": "sum_value = 0\nfor _ in range(5):\n sum_value += int(input())\nprint(sum_value)\n",
"step-4": nul... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def pdfToFolder(projectName):
os.chdir('/home/gmclaughlin/Downloads')
if projectName.find('DEM') != -1:
shutil.move('/home/gmclaughlin/Downloads/Detail Report - Basic.pdf',
'/home/gmclaughlin/Python/Safety Project/Demo/%s/%s-Detail Report.pdf'
... | flexible | {
"blob_id": "6e9fd8ee2a187888df07c9dd1c32fe59a111c869",
"index": 8823,
"step-1": "<mask token>\n\n\ndef pdfToFolder(projectName):\n os.chdir('/home/gmclaughlin/Downloads')\n if projectName.find('DEM') != -1:\n shutil.move('/home/gmclaughlin/Downloads/Detail Report - Basic.pdf',\n \n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(best_fit1)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
objective_func = F1
problem_size = 30
domain_range = [-15, 15]
log = True
epoch = 100
pop_size = 50
p = 0.8
md1 = BaseFPA(objective_func, problem_size, ... | flexible | {
"blob_id": "93b12d1e936331c81522790f3f45faa3383d249e",
"index": 3515,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(best_fit1)\n",
"step-3": "<mask token>\nobjective_func = F1\nproblem_size = 30\ndomain_range = [-15, 15]\nlog = True\nepoch = 100\npop_size = 50\np = 0.8\nmd1 = BaseFPA(objective_... | [
0,
1,
2,
3,
4
] |
# # -*- coding:utf-8 -*-
import sys
reload(sys)
sys.setdefaultencoding( "utf-8" )
import urllib
import urllib2
import cookielib
from excel import *
from user import *
List=[]
cookie = cookielib.CookieJar()
opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cookie))
postdata = urllib.urlencode({'zjh':user(0),'mm... | normal | {
"blob_id": "3c7280bbd23bd3472915da0760efbfd03bfe995d",
"index": 9314,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nreload(sys)\nsys.setdefaultencoding('utf-8')\n<mask token>\nwrite_schedule(cut(get_son(schedule[0], List)))\n",
"step-3": "<mask token>\nreload(sys)\nsys.setdefaultencoding('utf-8')\n<m... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "de347b41cd88947690cb42e043880a80d81e2c5c",
"index": 436,
"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 = [('cryptocurren... | [
0,
1,
2,
3,
4
] |
"""This module provides constants for locale-dependent providers."""
import typing as t
from mimesis.enums import Locale
from mimesis.exceptions import LocaleError
__all__ = ["Locale", "validate_locale"]
def validate_locale(locale: t.Union[Locale, str]) -> Locale:
if isinstance(locale, str):
try:
... | normal | {
"blob_id": "779445aa22145d5076940ea5b214c25ad233dd0e",
"index": 3087,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef validate_locale(locale: t.Union[Locale, str]) ->Locale:\n if isinstance(locale, str):\n try:\n return Locale(locale)\n except ValueError:\n ... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
# ------------------------------------------------------------------------------------------------------%
# Created by "Thieu Nguyen" at 19:47, 08/04/2020 %
# ... | normal | {
"blob_id": "93b12d1e936331c81522790f3f45faa3383d249e",
"index": 3515,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(best_fit1)\n",
"step-3": "<mask token>\nobjective_func = F1\nproblem_size = 30\ndomain_range = [-15, 15]\nlog = True\nepoch = 100\npop_size = 50\np = 0.8\nmd1 = BaseFPA(objective_... | [
0,
1,
2,
3,
4
] |
class MedianFinder:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class MedianFinder:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def findMedian(self) ->float:
if len(self.maxheap) == len(self.minheap... | flexible | {
"blob_id": "e7699bb3f6080c78517f11445e2c48a0e40f3332",
"index": 3209,
"step-1": "class MedianFinder:\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "class MedianFinder:\n <mask token>\n <mask token>\n\n def findMedian(self) ->float:\n if len(self.maxheap) == len(self.minhe... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class ZabbixItem:
def __init__(self, user, password, ext_group, ext_template, zabbix_host):
self.user = user
self.password = password
self.zabbix_host = zabbix_host
self.zabbix_api = f'http://{zabbix_host}'
self.connection = self.connection_ini... | flexible | {
"blob_id": "14826b5b121ba2939519492c1e1d8700c32396d2",
"index": 8963,
"step-1": "<mask token>\n\n\nclass ZabbixItem:\n\n def __init__(self, user, password, ext_group, ext_template, zabbix_host):\n self.user = user\n self.password = password\n self.zabbix_host = zabbix_host\n self.... | [
6,
8,
9,
11,
12
] |
<|reserved_special_token_0|>
def calc_auc(subm):
preds = subm['target'].values
labels = subm['labels'].values
if len(set(labels)) == 1:
print('warning calc_auc with single label dataset, return 0')
return 0
return metrics.roc_auc_score(labels, preds)
def save_submission(df, name, do_... | flexible | {
"blob_id": "fe0b21deb2e48ad74449b264265729cb328090ea",
"index": 6380,
"step-1": "<mask token>\n\n\ndef calc_auc(subm):\n preds = subm['target'].values\n labels = subm['labels'].values\n if len(set(labels)) == 1:\n print('warning calc_auc with single label dataset, return 0')\n return 0\n ... | [
3,
4,
5,
6,
7
] |
#!/usr/bin/env python
# coding: utf-8
# In[2]:
from __future__ import absolute_import, division, print_function, unicode_literals
import tensorflow as tf
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
# In[1]:
import numpy as np
import pandas as pd
import matplotlib.pypl... | normal | {
"blob_id": "aea92827753e12d2dc95d63ddd0fe4eb8ced5d14",
"index": 3815,
"step-1": "<mask token>\n\n\ndef convolve(image, fltr):\n r_p = 0\n c_p = 0\n conv_list = []\n while r_p + 1 <= image.shape[0] - 1:\n while c_p + 1 <= image.shape[1] - 1:\n x = np.sum(np.multiply(image[r_p:r_p + ... | [
1,
2,
3,
4,
5
] |
import openpyxl # 适用于xlsx文件
'''
纯文本文件 student.txt为学生信息, 里面的内容（包括花括号）如下所示：
{
"1":["张三",150,120,100],
"2":["李四",90,99,95],
"3":["王五",60,66,68]
}
请将上述内容写到 student.xls 文件中
'''
def read_file():
words = []
with open('15.txt', 'r') as file:
content = file.read()
# print(content)
# print(... | normal | {
"blob_id": "f75e0ddf42cc9797cdf1c4a4477e3d16441af740",
"index": 5478,
"step-1": "<mask token>\n\n\ndef write_list(list):\n wb = openpyxl.Workbook()\n sheet = wb.active\n sheet.title = 'test'\n value = list\n for i in range(0, len(value)):\n for j in range(0, len(value[i])):\n sh... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class Base_dfCleaner(LoggerMixIn, null_clean_methodMixIn, df_plotterMixIn):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self, df: DF, df_Xs_keys, df_Ys_key, silent=False, verbose=0):
LoggerMixIn.__init__(self, verbose)
null_clean_met... | flexible | {
"blob_id": "198beb5a17575d781f7bce1ab36a6213ad7331b3",
"index": 5853,
"step-1": "<mask token>\n\n\nclass Base_dfCleaner(LoggerMixIn, null_clean_methodMixIn, df_plotterMixIn):\n <mask token>\n <mask token>\n\n def __init__(self, df: DF, df_Xs_keys, df_Ys_key, silent=False, verbose=0):\n LoggerMix... | [
8,
15,
16,
17,
19
] |
import pandas as pd
triples = pd.read_csv("SollTripel.csv", sep=",", skip_blank_lines=True, skipinitialspace=True)
triples.columns = ["triple", "found"]
triples = triples["#" not in triples.triple]
print(triples) | normal | {
"blob_id": "97afa67cbe20900e2388994481abebe772e22818",
"index": 5301,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(triples)\n",
"step-3": "<mask token>\ntriples = pd.read_csv('SollTripel.csv', sep=',', skip_blank_lines=True,\n skipinitialspace=True)\ntriples.columns = ['triple', 'found']\nt... | [
0,
1,
2,
3,
4
] |
from __future__ import unicode_literals
import frappe, json
def execute():
for ps in frappe.get_all('Property Setter', filters={'property': '_idx'},
fields = ['doc_type', 'value']):
custom_fields = frappe.get_all('Custom Field',
filters = {'dt': ps.doc_type}, fields=['name', 'fieldname'])
if custom_fields:
... | normal | {
"blob_id": "6f951815d0edafb08e7734d0e95e6564ab1be1f7",
"index": 2375,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef execute():\n for ps in frappe.get_all('Property Setter', filters={'property': '_idx'\n }, fields=['doc_type', 'value']):\n custom_fields = frappe.get_all('Custom ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class SolutionBest(object):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class SolutionBest(object):
def nextGreatestLetter(self, letters, target):
"""
:type letters: List[str]
:type target: str
:rtype... | flexible | {
"blob_id": "9cb3d8bc7af0061047136d57abfe68cbb5ae0cd7",
"index": 3344,
"step-1": "<mask token>\n\n\nclass SolutionBest(object):\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass SolutionBest(object):\n\n def nextGreatestLetter(self, letters, target):\n \"\"\"\n :type letters: List[str]\... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def user_defined_shoot():
global variable_flag
global variable_i
global list_angle_list
variable_i = 1
for count in range(3):
gimbal_ctrl.angle_ctrl(list_angle_list[1], list_angle_list[2])
gun_ctrl.fire_once()
variable_i = variable_i + 2
... | flexible | {
"blob_id": "012e4112970a07559f27fa2127cdffcc557a1566",
"index": 4638,
"step-1": "<mask token>\n\n\ndef user_defined_shoot():\n global variable_flag\n global variable_i\n global list_angle_list\n variable_i = 1\n for count in range(3):\n gimbal_ctrl.angle_ctrl(list_angle_list[1], list_angle... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Agent:
def __init__(self):
self.model = torch.load(__file__[:-8] + '/agent.pkl')
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Agent:
def __init__(self):
self.model = t... | flexible | {
"blob_id": "50a4084dd3028acc2e6788e77794c100efcb3fac",
"index": 132,
"step-1": "<mask token>\n\n\nclass Agent:\n\n def __init__(self):\n self.model = torch.load(__file__[:-8] + '/agent.pkl')\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Agent:\n\n def __init__(self):\... | [
2,
3,
4,
5,
6
] |
#!/bin/env python
from boincvm_common.stomp.StompProtocol import StompProtocolFactory
from stomp.HostStompEngine import HostStompEngine
from boincvm_host.xmlrpc.HostXMLRPCService import HostXMLRPCService
from twisted.internet import reactor
from ConfigParser import SafeConfigParser
import coilmq.start
import loggi... | normal | {
"blob_id": "e533b7aadd1cd7137301af8862dd2987622e499e",
"index": 3357,
"step-1": "#!/bin/env python\n\nfrom boincvm_common.stomp.StompProtocol import StompProtocolFactory\nfrom stomp.HostStompEngine import HostStompEngine\n\nfrom boincvm_host.xmlrpc.HostXMLRPCService import HostXMLRPCService\n\nfrom twisted.inte... | [
0
] |
<|reserved_special_token_0|>
class SEMGaussianMixture(MyGMM):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def _draw_conditionnal_Z(self, Y):
"""
Tire un échantillon de loi Z sachant Y
:param Y: Observations (n_samples, n_features)
:return: Z (n_samples,n_com... | flexible | {
"blob_id": "39475626b7e3e0f4c8143b300c002a2eb50cc23a",
"index": 9341,
"step-1": "<mask token>\n\n\nclass SEMGaussianMixture(MyGMM):\n <mask token>\n <mask token>\n\n def _draw_conditionnal_Z(self, Y):\n \"\"\"\n Tire un échantillon de loi Z sachant Y\n\n :param Y: Observations (n_s... | [
8,
9,
10,
11,
12
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
start_operator >> stage_events_to_redshift >> load_songplays_table
start_operator >> stage_songs_to_redshift >> load_songplays_table
load_songplays_table >> load_song_dimension_table >> run_quality_checks
load_songplays_table >> l... | flexible | {
"blob_id": "7994d9605c8654053c9a85f8d37983da04f8003a",
"index": 2674,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nstart_operator >> stage_events_to_redshift >> load_songplays_table\nstart_operator >> stage_songs_to_redshift >> load_songplays_table\nload_songplays_table >> load_song_dimension_table >>... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Statistics(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_tok... | flexible | {
"blob_id": "728f9402b3ce4b297be82b3ba1a17c4180ac7c0d",
"index": 8839,
"step-1": "<mask token>\n\n\nclass Statistics(models.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... | [
4,
5,
6,
7,
8
] |
#!/usr/bin/env python
#coding=utf-8
from datetime import *
import unittest
def getSnapshot(historyData, id):
data = historyData.split('\n')
lines = len(data)
if lines < 2 :
return 'Input is too short!'
index = 0
curid = ''
idlist = dict()
recordtime = ''
animal_pos = dict()
f... | normal | {
"blob_id": "ddbcc8e768f93a0b4f8776b19e752c57feb5bbf9",
"index": 6362,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef getSnapshot(historyData, id):\n data = historyData.split('\\n')\n lines = len(data)\n if lines < 2:\n return 'Input is too short!'\n index = 0\n curid = ''\n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def v_measure(cluster_labels, true_labels):
h_score = homogeneity_score(true_labels, cluster_labels)
c_score = completeness_score(true_labels, cluster_labels)
v_score = v_measure_score(true_labels, cluster_labels)
print('Homogeneity Score: %.6f' % h_score)
print('Compl... | flexible | {
"blob_id": "fe63d9b0939bc91d2da14e4d966b33575eab5394",
"index": 2531,
"step-1": "<mask token>\n\n\ndef v_measure(cluster_labels, true_labels):\n h_score = homogeneity_score(true_labels, cluster_labels)\n c_score = completeness_score(true_labels, cluster_labels)\n v_score = v_measure_score(true_labels, ... | [
8,
10,
12,
13,
14
] |
from genericentity import GenericEntity as GEntity
import random as ran
class GenericBreeder(object):
"""description of class: its a classy class"""
def __init__(self,nlifesize,nparentsize,nlowestscore):
self.Reset(nlifesize,nparentsize,nlowestscore)
def Reset(self,nlifesize,nparentsize,nlowe... | normal | {
"blob_id": "753617c189a88adee8430e994aa597c9db9410fe",
"index": 6143,
"step-1": "<mask token>\n\n\nclass GenericBreeder(object):\n <mask token>\n\n def __init__(self, nlifesize, nparentsize, nlowestscore):\n self.Reset(nlifesize, nparentsize, nlowestscore)\n\n def Reset(self, nlifesize, nparents... | [
8,
10,
13,
14,
15
] |
<|reserved_special_token_0|>
def get_server_ip(device_ip):
import socket
s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
s.connect((device_ip, 80))
return s.getsockname()[0]
def transfer_file(from_ip, to_ip, remote_file_path, cmd='ftpput'):
"""
Transfer file from from_ip to to_ip via te... | flexible | {
"blob_id": "3d1e6be71f92910cdc9eb2bf60ea7f8f1187f706",
"index": 3698,
"step-1": "<mask token>\n\n\ndef get_server_ip(device_ip):\n import socket\n s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\n s.connect((device_ip, 80))\n return s.getsockname()[0]\n\n\ndef transfer_file(from_ip, to_ip, remo... | [
6,
12,
13,
14,
16
] |
def correctLineup1(athletes: list) ->list:
return [(athletes[i + 1] if i % 2 == 0 else athletes[i - 1]) for i in
range(len(athletes))]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def correctLineup1(athletes: list) ->list:
return [(athletes[i + 1] if i % 2 == 0 else athletes[i - 1]) fo... | flexible | {
"blob_id": "6c5f60e7a122e3da5e6705bfacf73a361f6c1362",
"index": 1120,
"step-1": "def correctLineup1(athletes: list) ->list:\n return [(athletes[i + 1] if i % 2 == 0 else athletes[i - 1]) for i in\n range(len(athletes))]\n\n\n<mask token>\n",
"step-2": "def correctLineup1(athletes: list) ->list:\n ... | [
1,
2,
3,
4,
5
] |
DEFAULT_LL_URL = "https://ll.thespacedevs.com"
DEFAULT_VERSION = "2.0.0"
DEFAULT_API_URL = "/".join([DEFAULT_LL_URL, DEFAULT_VERSION])
| normal | {
"blob_id": "1a72da7f436e6c5e73e396b771f8ce1a3affba1a",
"index": 3010,
"step-1": "<mask token>\n",
"step-2": "DEFAULT_LL_URL = 'https://ll.thespacedevs.com'\nDEFAULT_VERSION = '2.0.0'\nDEFAULT_API_URL = '/'.join([DEFAULT_LL_URL, DEFAULT_VERSION])\n",
"step-3": "DEFAULT_LL_URL = \"https://ll.thespacedevs.com\... | [
0,
1,
2
] |
class Node:
def __init__(self, dataVal=None):
self.dataVal = dataVal
self.nextVal = None
class LinkedList:
def __init__(self):
self.headVal = None
def atBeginning(self, data):
NewNode = Node(data)
NewNode.nextVal = self.headVal
self.headVal = NewNode
... | normal | {
"blob_id": "00260e23614a7b0a11ff3649e71392e4892de423",
"index": 4511,
"step-1": "<mask token>\n\n\nclass LinkedList:\n <mask token>\n <mask token>\n\n def atEnd(self, data):\n NewNode = Node(data)\n NewNode.nextVal = None\n if self.headVal is None:\n self.headVal = NewNo... | [
6,
9,
12,
15,
17
] |
import os
import sys
import glob
import shutil
import json
import codecs
from collections import OrderedDict
def getRegionClass(image_path, data_id, imgName):
region_class = ['nosmoke_background', 'nosmoke_face', 'nosmoke_suspect', 'nosmoke_cover', 'smoke_hand', 'smoke_nohand', 'smoke_hard']
label_class = ['nosmok... | normal | {
"blob_id": "75833617996549167fa157ff78cc1a11f870784f",
"index": 8639,
"step-1": "<mask token>\n\n\ndef getRegionClass(image_path, data_id, imgName):\n region_class = ['nosmoke_background', 'nosmoke_face', 'nosmoke_suspect',\n 'nosmoke_cover', 'smoke_hand', 'smoke_nohand', 'smoke_hard']\n label_clas... | [
1,
2,
3,
4,
5
] |
import datetime
from datetime import datetime, timedelta
import time
import json
import base64
import requests
from bson.objectid import ObjectId
import urllib
isinpackage = not __name__ in ['google_api', '__main__']
if isinpackage:
from .settings import settings
from . import util
from .util import Just
... | normal | {
"blob_id": "c75c69b006734e476352de1913fd4a58021bffd6",
"index": 2704,
"step-1": "<mask token>\n\n\ndef get_certs_keys(kid):\n url = 'https://www.googleapis.com/oauth2/v3/certs'\n data = requests.get(url).json()['keys']\n return next(filter(lambda e: kid == e['kid']), None)\n\n\ndef get_redirect_link(re... | [
11,
12,
14,
15,
16
] |
class Solution:
def countLetters(self, S: str) ->int:
ans = 0
for _, g in itertools.groupby(S):
cnt = len(list(g))
ans += (1 + cnt) * cnt // 2
return ans
| normal | {
"blob_id": "f9cee552dde5ecf229fda559122b4b0e780c3b88",
"index": 7350,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def countLetters(self, S: str) ->int:\n ans = 0\n for _, g in itertools.groupby(S):\n cnt = len(list(g... | [
0,
1,
2
] |
#!/usr/bin/python3
"Places module"
from flask import jsonify, request, Response, abort
from api.v1.views import app_views
from models import storage
from models.place import Place
@app_views.route('cities/<city_id>/places', strict_slashes=False,
methods=['GET'])
def get_all_places(city_id):
''' g... | normal | {
"blob_id": "d67a2eca4e2fde443b99f5133c2657cdf4ac00de",
"index": 4173,
"step-1": "<mask token>\n\n\n@app_views.route('cities/<city_id>/places', strict_slashes=False, methods=[\n 'GET'])\ndef get_all_places(city_id):\n \"\"\" gets all places in a city \"\"\"\n city = storage.get('City', city_id)\n if ... | [
3,
4,
5,
6,
7
] |
from operator import itemgetter
import math
def get_tf_idf_map(document, max_freq, n_docs, index):
tf_idf_map = {}
for term in document:
tf = 0
idf = math.log(n_docs)
if term in index and term not in tf_idf_map:
posting_list = index[term]
freq_term = sum([p... | normal | {
"blob_id": "39197b3f9f85d94457584d7e488ca376e52207f1",
"index": 5832,
"step-1": "<mask token>\n\n\ndef get_cosinus_simularity(tf_idf_map, key_words):\n sum_common_terms = 0\n sum_tf_idf_terms = 0\n for term in tf_idf_map:\n if term in key_words:\n sum_common_terms += tf_idf_map[term]\... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
import pywikibot
from pywikibot import pagegenerators
import re
from pywikibot import xmlreader
import datetime
import collections
from klasa import *
def fraz(data):
data_slownie = data[6:8] + '.' + data[4:6] + '.' + data[0:4]
lista_stron = getListFromXML(data)
... | normal | {
"blob_id": "2b928dad60bfb0ba863e9039a5462faa885644f3",
"index": 4643,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef fraz(data):\n data_slownie = data[6:8] + '.' + data[4:6] + '.' + data[0:4]\n lista_stron = getListFromXML(data)\n site = pywikibot.Site('pl', 'wiktionary')\n outputPag... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class BubbleTypes(Enum):
USER = auto()
SYSTEM = auto()
STATUS = auto()
INFO = auto()
def __str__(self):
return str(self.value)
class Relations(Enum):
UNDERMINE = 'undermine'
UNDERCUT = 'undercut'
REBUT = 'rebut'
SUPPORT = 'support'
def _... | flexible | {
"blob_id": "10a9437453371bd7472e93af1026c778b7983cf8",
"index": 1137,
"step-1": "<mask token>\n\n\nclass BubbleTypes(Enum):\n USER = auto()\n SYSTEM = auto()\n STATUS = auto()\n INFO = auto()\n\n def __str__(self):\n return str(self.value)\n\n\nclass Relations(Enum):\n UNDERMINE = 'unde... | [
29,
31,
47,
55,
60
] |
import surname_common as sc
from sklearn.utils import shuffle
import glob
import os
import re
import pprint
import pandas as pd
import unicodedata
import string
def unicode_to_ascii(s):
return ''.join(
c for c in unicodedata.normalize('NFD', s)
if unicodedata.category(c) != 'Mn' and c in sc.ALL_LE... | normal | {
"blob_id": "db46fbfb1acd855eebb5c9f557d70038b84e812d",
"index": 8573,
"step-1": "<mask token>\n\n\ndef save_df_surnames_as_pickle():\n df_surnames, df_categories = load_surnames()\n df = shuffle(df_surnames, random_state=sc.RANDOM_STATE)\n train_cnt = int(df['surname'].count() * sc.TRAIN_TEST_RATIO)\n ... | [
1,
2,
3,
4,
5
] |
from django.db import models
# Create your models here.
class GeneralInformation(models.Model):
name = models.CharField(max_length=100)
address = models.TextField()
city = models.CharField(max_length=20)
class Meta:
ordering = ['name']
def __str__(self):
return "{} {} {}".format... | normal | {
"blob_id": "d0f83e3b7eb5e1bc81a56e46043f394757437af8",
"index": 5504,
"step-1": "<mask token>\n\n\nclass GeneralInformation(models.Model):\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n ordering = ['name']\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass GeneralInf... | [
1,
2,
3,
4,
5
] |
import datetime
import matplotlib.pyplot as plt
import numpy as np
import statsmodels.api as sm
import xlrd
from pandas import *
from xlrd import xldate
#since I messed up when first scraping the data, I have the dates and viewcounts in separate files
#need to create a dictionary of 'author-title':[viewcount, date]
... | normal | {
"blob_id": "6ece524c82521b175cc7791e22c8249dd24dc714",
"index": 2281,
"step-1": "import datetime\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport statsmodels.api as sm\nimport xlrd\nfrom pandas import *\nfrom xlrd import xldate\n\n\n#since I messed up when first scraping the data, I have the dates a... | [
0
] |
from .ros_publisher import *
| normal | {
"blob_id": "6e7cca4f766ca89d2e2f82a73f22742b0e8f92a8",
"index": 5870,
"step-1": "<mask token>\n",
"step-2": "from .ros_publisher import *\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from django.shortcuts import render
from rest_framework.response import Response
from rest_framework import status
from rest_framework.decorators import api_view
from rest_framework.permissions import IsAuthenticated
from .models import Flight, Passenger, Reservation
from .serializers import FlightSerializer, Passenger... | normal | {
"blob_id": "d437d77d5a57a6f2f4a2d530be05c3845dce93bc",
"index": 1459,
"step-1": "<mask token>\n\n\nclass Detailedreservation(RetrieveUpdateDestroyAPIView):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ListReservation(ListCreateAPIView):\n <mask token>\n <mask token>\n\n\ncl... | [
1,
7,
13,
14,
16
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
panel.pack()
root.mainloop()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
root = Tk()
photo = PhotoImage(file='flag.png')
panel = Label(root, image=photo)
panel.pack()
root.mainloop()
<|reserved_special_token_1|>... | flexible | {
"blob_id": "2d192963bfe046bce1a0c82e0179380693f5c541",
"index": 9518,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npanel.pack()\nroot.mainloop()\n",
"step-3": "<mask token>\nroot = Tk()\nphoto = PhotoImage(file='flag.png')\npanel = Label(root, image=photo)\npanel.pack()\nroot.mainloop()\n",
"step-... | [
0,
1,
2,
3
] |
import numpy as np
import string
import networkx as nx
import matplotlib.pyplot as plt
def PlotUndirectedGraph(A,color):
NodesNames = list(string.ascii_uppercase);
NNodes = A.shape[0]
G = nx.DiGraph()
for i in range(NNodes):
G.add_node(NodesNames[i])
for i in range(NNodes):
for ... | normal | {
"blob_id": "61388b2edb35055cccbdc98ed52caedcd0b02983",
"index": 5624,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef PlotUndirectedGraph(A, color):\n NodesNames = list(string.ascii_uppercase)\n NNodes = A.shape[0]\n G = nx.DiGraph()\n for i in range(NNodes):\n G.add_node(Nodes... | [
0,
1,
2,
3
] |
import random
import re
from datetime import datetime, timedelta
from threading import Lock
from telegram.ext import run_async
from src.models.user import UserDB
from src.models.user_stat import UserStat
from src.utils.cache import cache, USER_CACHE_EXPIRE
from src.utils.logger_helpers import get_logger
logger = get... | normal | {
"blob_id": "109ca06685eece74034f77a98b1d7172a17aca21",
"index": 7469,
"step-1": "<mask token>\n\n\nclass PidorWeekly:\n <mask token>\n <mask token>\n <mask token>\n\n @classmethod\n def get_top_pidor(cls, cid, date=None):\n monday = cls.__get_current_monday(\n ) if date is None ... | [
9,
12,
13,
14,
15
] |
a = int(input('점수를 입력하세요'))
if a >= 70 :
print:('통과입니다.')
print:('축하합니다.')
else :
print:('불합격입니다.')
print("안녕")
| normal | {
"blob_id": "f8d0cc9cb0e5f8adf9077ffb39dd6abedfedaa12",
"index": 5427,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif a >= 70:\n print: '통과입니다.'\n print: '축하합니다.'\nelse:\n print: '불합격입니다.'\nprint('안녕')\n",
"step-3": "a = int(input('점수를 입력하세요'))\nif a >= 70:\n print: '통과입니다.'\n print: ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Remove_ItemView(generic.ListView):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class Update_ItemView(generic.ListView):
model = GPS
template_name = 'inv_templates/update_item.html'
context_object_name = 'unit'
cl... | flexible | {
"blob_id": "67db3a66e5525d41de13df665167a0db2d81056e",
"index": 2721,
"step-1": "<mask token>\n\n\nclass Remove_ItemView(generic.ListView):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass Update_ItemView(generic.ListView):\n model = GPS\n template_name = 'inv_templates/update_item.html'\n... | [
7,
11,
12,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "fed94e0affa1fe6c705577a63fabee839aa9f05c",
"index": 5096,
"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 = [('rover', '00... | [
0,
1,
2,
3,
4
] |
# Definition for singly-linked list.
# class ListNode:
# def __init__(self, val=0, next=None):
# self.val = val
# self.next = next
class Solution:
def swapPairs(self, head: ListNode) -> ListNode:
dummy_head=ListNode(0)
dummy_head.next=head
pre=dummy_head
cur=head
... | normal | {
"blob_id": "4afc2ceed860c20af071e1d9ccaca17973cb9a8e",
"index": 7553,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def swapPairs(self, head: ListNode) ->ListNode:\n dummy_head = ListNode(0)\n dummy_head.next = head\n pre ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class AuthenticatorTest(absltest.TestCase):
<|reserved_special_token_0|>
def testGetGoogleSheetsServiceByCred_badFilePath_raisesFileNotFoundError(
self):
bad_file_path = './credential.json'
with self.assertRaises(FileNotFoundError):
authenticat... | flexible | {
"blob_id": "86b24ddaae0d3477a3f82295224b7e84805eed91",
"index": 1413,
"step-1": "<mask token>\n\n\nclass AuthenticatorTest(absltest.TestCase):\n <mask token>\n\n def testGetGoogleSheetsServiceByCred_badFilePath_raisesFileNotFoundError(\n self):\n bad_file_path = './credential.json'\n ... | [
2,
3,
4,
5,
6
] |
"""
This module is an intermediate layer between flopy version 3.2
and the inowas-modflow-configuration format.
Author: Ralf Junghanns
EMail: ralf.junghanns@gmail.com
"""
from .BasAdapter import BasAdapter
from .ChdAdapter import ChdAdapter
from .DisAdapter import DisAdapter
from .GhbAdapter import GhbAdapter
from .L... | normal | {
"blob_id": "fb64003c1acbddcbe952a17edcbf293a54ef28ae",
"index": 2185,
"step-1": "<mask token>\n\n\nclass InowasFlopyCalculationAdapter:\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\n def __init__(self, versio... | [
7,
11,
12,
13,
14
] |
from collections.abc import Iterator
import json
import click
def print_json(obj, err=False):
if isinstance(obj, Iterator):
obj = list(obj)
click.echo(json.dumps(obj, sort_keys=True, indent=4, ensure_ascii=False),
err=err)
def show_fields(*fields):
def show(obj, verbose=False):
... | normal | {
"blob_id": "d340ac979f57cf4650131665e4fa5b9923f22a3e",
"index": 6691,
"step-1": "<mask token>\n\n\ndef print_json(obj, err=False):\n if isinstance(obj, Iterator):\n obj = list(obj)\n click.echo(json.dumps(obj, sort_keys=True, indent=4, ensure_ascii=False\n ), err=err)\n\n\n<mask token>\n",
... | [
1,
2,
3,
4,
5
] |
# Let's look at the lowercase letters.
import string
alphabet = " " + string.ascii_lowercase
| normal | {
"blob_id": "da3be0d3b815e11d292a7c7e8f5ce32b35580f98",
"index": 1016,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nalphabet = ' ' + string.ascii_lowercase\n",
"step-3": "import string\nalphabet = ' ' + string.ascii_lowercase\n",
"step-4": "# Let's look at the lowercase letters.\nimport string\nalp... | [
0,
1,
2,
3
] |
import praw
import config
from imgurpython import ImgurClient
import datetime
from time import sleep
def respond_to_comment(comment, album_user, album_url, num_images, num_gifs):
body = "Here is an album of all unique image/gif posts made by " \
"[{user}]({album_url}). ({num_images} images" \
... | normal | {
"blob_id": "ca009022832963934230e356f9ea9eaedac7378b",
"index": 1745,
"step-1": "<mask token>\n\n\ndef update_album(user, imgur_client, reddit_client):\n return\n\n\n<mask token>\n\n\ndef is_gif(url):\n return True\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef respond_to_comment(comment, album_... | [
2,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
def lab1(x):
list1 = []
for i in range(4):
sum = x * i
list1.append(sum)
return list1
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def lab1(x):
list1 = []
for i in range(4):
sum = x * i
li... | flexible | {
"blob_id": "807e19f09f4a46b6c39457b8916714e2c54c3e8d",
"index": 5802,
"step-1": "<mask token>\n\n\ndef lab1(x):\n list1 = []\n for i in range(4):\n sum = x * i\n list1.append(sum)\n return list1\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef lab1(x):\n list1 = []\n for i i... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class QRCodeConfig(PluginConfig):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_t... | flexible | {
"blob_id": "6306acd1508698687842ba6b55a839743af420cc",
"index": 5840,
"step-1": "<mask token>\n\n\nclass QRCodeConfig(PluginConfig):\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\n\n<mask token>\n",
"step-2": "... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class PrimaryCategoryAdmin(admin.ModelAdmin):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class PlaceCategoryAdmin(admin.ModelAdmin):
list_display = ('category_name', 'is_paid', 'description', 'is_active',
'image', 'prim... | flexible | {
"blob_id": "606abf8501d85c29051df4bf0276ed5b098ee6c5",
"index": 8679,
"step-1": "<mask token>\n\n\nclass PrimaryCategoryAdmin(admin.ModelAdmin):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass PlaceCategoryAdmin(admin.ModelAdmin):\n list_display = ('category_name', 'is_paid', 'description', ... | [
5,
6,
7,
8,
10
] |
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