code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
from datetime import datetime
import xarray
import matplotlib.pyplot as plt
import pandas as pd
from matplotlib.dates import date2num
import numpy as np
from matplotlib.gridspec import GridSpec
def test_plot_area_avg(target_nc_folder="", source_nc_path=""):
# target_nc_folder = "/HOME/huziy/skynet3_rech1/Netbea... | normal | {
"blob_id": "2d5e147b081283047cd044746d73d91ee2e59052",
"index": 4139,
"step-1": "<mask token>\n\n\ndef __print_field_stats(tfield, field, label):\n good_mask = ~field.mask\n if not np.any(good_mask):\n print(f'{label}: no meaningful data')\n return\n good_data = field[good_mask]\n prin... | [
3,
4,
5,
6,
7
] |
# coding: utf-8
import sys
from flask.ext.script import Manager
from flask.ext.migrate import Migrate, MigrateCommand
from flask_assets import ManageAssets
from app import app
from assets import assets
from db import db
from .changepassword import ChangePassword
from .create_superuser import SuperUserCommand
from .... | normal | {
"blob_id": "c331802cf5a09bc8db8ddbfa37636a01cf73684e",
"index": 2626,
"step-1": "<mask token>\n\n\nclass MyMan(Manager):\n\n def run(self, commands=None, default_command=None):\n \"\"\"\n Prepares manager to receive command line input. Usually run\n inside \"if __name__ == \"__main__\" b... | [
2,
3,
4,
5,
6
] |
import os, sys, datetime, pytz, tzlocal, urllib.request, requests, csv, hashlib, json, boto3
uri = 'ftp://ftpcimis.water.ca.gov/pub2/daily/daily107.csv' #Station 107 is Santa Barbara
base_et = 0.15
def main():
try:
tempfile = tempfile_name()
get_datafile(tempfile)
except:
print("Could not retrieve da... | normal | {
"blob_id": "4d82e68faa3102fc2949fd805588504b7d874589",
"index": 5457,
"step-1": "<mask token>\n\n\ndef main():\n try:\n tempfile = tempfile_name()\n get_datafile(tempfile)\n except:\n print('Could not retrieve datafile ' + tempfile)\n exit(-1)\n et = get_yesterdays_et(tempfi... | [
8,
9,
10,
11,
12
] |
# 数组的每个索引作为一个阶梯，第 i个阶梯对应着一个非负数的体力花费值 cost[i](索引从0开始)。
#
# 每当你爬上一个阶梯你都要花费对应的体力花费值，然后你可以选择继续爬一个阶梯或者爬两个阶梯。
#
# 您需要找到达到楼层顶部的最低花费。在开始时，你可以选择从索引为 0 或 1 的元素作为初始阶梯。
#
# 示例 1:
#
# 输入: cost = [10, 15, 20]
# 输出: 15
# 解释: 最低花费是从cost[1]开始，然后走两步即可到阶梯顶，一共花费15。
#
#
# 示例 2:
#
# 输入: cost = [1, 100, 1, 1, 1, 100, 1, 1, 100, 1]
# 输出... | normal | {
"blob_id": "38363316cc9a8419a528bb78b9ad03682e24172d",
"index": 9823,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n\n\n<mask token>\n",
"step-3": "class Solution(object):\n\n def minCostClimbingStairs(self, cost):\n \"\"\"\n :type cost: List[int]\n ... | [
0,
1,
2,
3,
4
] |
#https://codeforces.com/problemset/problem/1321/A
n=int(input())
r=list(map(int,input().split()))
b=list(map(int,input().split()))
l=[0]*n
x=0
y=0
for i in range(n):
if r[i]-b[i]==1:
x+=1
elif r[i]-b[i]==-1:
y+=1
if x==0:
print(-1)
else:
print(y//x+min(y%x+1,1))
| normal | {
"blob_id": "7aa6bba8483082354a94ed5c465e59a0fc97fe23",
"index": 1248,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(n):\n if r[i] - b[i] == 1:\n x += 1\n elif r[i] - b[i] == -1:\n y += 1\nif x == 0:\n print(-1)\nelse:\n print(y // x + min(y % x + 1, 1))\n",
"s... | [
0,
1,
2,
3
] |
from django import forms
from django.forms import ModelForm
from .models import Noticia
class NoticiaForm(ModelForm):
class Meta:
model = Noticia
fields = ['idNoticia', 'resumen', 'titulo', 'categoria']
| normal | {
"blob_id": "e7a283e0e0e16e9adb415b26d724b2ee84c4f4f8",
"index": 1547,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass NoticiaForm(ModelForm):\n\n\n class Meta:\n model = Noticia\n fields = ['idNoticia', 'resumen', 'titulo', 'categoria']\n",
"step-3": "from django import forms... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
from __future__ import print_function, absolute_import, unicode_literals, division
__all__ = ['getLevelName', 'getLevel'] #, 'getLevelOrName', '_checkLevel']
import logging
# private re-implementations till Python Core fixes Lib/logging
# XXX bug numbers here
def getLevelName(level, format='... | normal | {
"blob_id": "ba8b46f830abaaaedf1730cba2f04fd677f11da4",
"index": 182,
"step-1": "<mask token>\n\n\ndef getLevel(levelName, no_match=logging.NOTSET):\n \"\"\"Return the numeric representation of levelName.\n\n see getLevelName() for background\n \"\"\"\n try:\n result = logging._nameToLevel.get... | [
2,
3,
5,
6,
7
] |
# -*- encoding: utf-8 -*-
##############################################################################
#
# ServerPLM, Open Source Product Lifcycle Management System
# Copyright (C) 2020-2020 Didotech srl (<http://www.didotech.com>). All Rights Reserved
#
# Created on : 2018-03-01
# Author : Fabio ... | normal | {
"blob_id": "06643bf4b1bded757078b0974c21ddec814f5889",
"index": 1762,
"step-1": "<mask token>\n\n\nclass plm_component(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def _insertlog(self, ids, changes={}, note={}):\n ret = False\n op_... | [
20,
34,
38,
44,
49
] |
import socket
from Server.MachineClient.Identification import Identification
from Server.SQL import DataBase
import threading
import time
from Server.Connection.AcceptClients import Accept
from Server.Connection.ConnectionCheck import ConnectionCheck
from Server.Clients_Data import Clients
class MachineClient:
de... | normal | {
"blob_id": "ff1bb2634ffec6181a42c80a4b2a19c2c27a8f9f",
"index": 3136,
"step-1": "<mask token>\n\n\nclass MachineClient:\n\n def __init__(self, host, port):\n self.host = host\n self.port = port\n self.s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n self.db = DataBase(\n ... | [
5,
6,
7,
8,
9
] |
import sys
def tackle_mandragora(health):
health.sort()
# for all tipping points, where we change over from eating to defeating
defeating = defeating_cost_precompute(health)
opt = 0
for i in range(0, len(health) + 1):
opt = max(opt, defeating_cost(i, defeating))
return opt
def defe... | normal | {
"blob_id": "24ad62342fb9e7759be8561eaf0292736c7dcb6d",
"index": 6756,
"step-1": "<mask token>\n\n\ndef defeating_cost(i, defeating):\n return (i + 1) * defeating[i]\n\n\ndef defeating_cost_precompute(health):\n n = len(health) + 1\n defeating = [(0) for x in range(n)]\n defeating[len(health)] = 0\n ... | [
2,
4,
5,
6,
7
] |
"""This module contains an algorithm to find the different
components in a graph represented as an adjacency matrix.
"""
def find_components(adjacency_matrix):
visited = set()
components = []
for node in range(len(adjacency_matrix)):
if node not in visited:
component = []
b... | normal | {
"blob_id": "e71a23ef7a065bc4210e55552e19c83c428bc194",
"index": 3187,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef find_components(adjacency_matrix):\n visited = set()\n components = []\n for node in range(len(adjacency_matrix)):\n if node not in visited:\n component... | [
0,
1,
2,
3
] |
import server_pb2
import atexit
from grpc.beta import implementations
from random import randint
from grpc._adapter._types import ConnectivityState
global _pool
_pool = dict()
class ChannelPool(object):
def __init__(self, host, port, pool_size):
self.host = host
self.port = port
self.p... | normal | {
"blob_id": "aec45936bb07277360ea1a66b062edc4c282b45a",
"index": 4097,
"step-1": "import server_pb2\n\nimport atexit\n\nfrom grpc.beta import implementations\nfrom random import randint\nfrom grpc._adapter._types import ConnectivityState\n\nglobal _pool\n_pool = dict()\n\n\nclass ChannelPool(object):\n\n def ... | [
0
] |
import itertools
import unittest
from pylev3 import Levenshtein
TEST_DATA = [
('classic', "kitten", "sitting", 3),
('same', "kitten", "kitten", 0),
('empty', "", "", 0),
('a', "meilenstein", "levenshtein", 4),
('b', "levenshtein", "frankenstein", 6),
('c', "confide", "deceit", 6),
('d', "... | normal | {
"blob_id": "892d6662e4276f96797c9654d15c96a608d0835a",
"index": 8927,
"step-1": "<mask token>\n\n\nclass Tests(unittest.TestCase):\n\n def test_singleton(self):\n lev1, lev2 = Levenshtein(), Levenshtein()\n self.assertIs(lev1, lev2)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Tes... | [
2,
3,
4,
5,
7
] |
#! /usr/bin/env python
import ldac
from numpy import *
import shearprofile as sp
import sys
import os, subprocess
import pylab
if len(sys.argv) != 6:
sys.stderr.write("wrong number of arguments!\n")
sys.exit(1)
catfile= sys.argv[1]
clusterz=float(sys.argv[2])
center= map(float,sys.argv[3].split(','))
pixsc... | normal | {
"blob_id": "f19d8aa2104240cc93a0146f1b14c635e7cd3a41",
"index": 268,
"step-1": "#! /usr/bin/env python\n\nimport ldac\nfrom numpy import *\nimport shearprofile as sp\nimport sys\nimport os, subprocess\n\nimport pylab\n\n\nif len(sys.argv) != 6:\n sys.stderr.write(\"wrong number of arguments!\\n\")\n sys.e... | [
0
] |
#!/usr/bin/env python
import crawl
import logging
from elasticsearch import Elasticsearch
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO)
logging.getLogger("crawl").setLevel(logging.INFO)
logging.getLogger("elasticsearch").setLevel(logging.ERROR)
es = Elasticsearch()
crawl... | normal | {
"blob_id": "21d07c2b80aa00d0c75da342d37195b6829593b6",
"index": 1110,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n logging.basicConfig(level=logging.INFO)\n logging.getLogger('crawl').setLevel(logging.INFO)\n logging.getLogger('elasticsearch').setLevel(logging.ERR... | [
0,
1,
2,
3
] |
#
# @lc app=leetcode id=67 lang=python3
#
# [67] Add Binary
#
# https://leetcode.com/problems/add-binary/description/
#
# algorithms
# Easy (46.70%)
# Likes: 2566
# Dislikes: 331
# Total Accepted: 572.1K
# Total Submissions: 1.2M
# Testcase Example: '"11"\n"1"'
#
# Given two binary strings a and b, return their ... | normal | {
"blob_id": "227a56c970a74d515ab694d2c0924885e2209cfe",
"index": 7089,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def addBinary(self, a: str, b: str) ->str:\n if len(a) < len(b):\n a = '0' * (len(b) - len(a)) + a\n e... | [
0,
1,
2,
3
] |
class Patient(object):
def __init__(self, id_number, name, bed_number, *allergies):
self.id_number = id_number
self.name = name
self.allergies = allergies
self.bed_number = bed_number
class Hospital(object):
def __init__(self, name, capacity):
self.patients = []
... | normal | {
"blob_id": "259a4bb39496bdfc71d60edb4994d26351c6961d",
"index": 3621,
"step-1": "class Patient(object):\r\n def __init__(self, id_number, name, bed_number, *allergies):\r\n self.id_number = id_number\r\n self.name = name\r\n self.allergies = allergies\r\n self.bed_number = bed_num... | [
0
] |
from pathlib import Path
from build_midi.appenders import *
from build_midi.converters import Converter
from build_midi.melody_builder import MelodyBuilder
from build_midi.sequences import *
from build_midi.tracks import *
from music_rules.instruments import Instruments
from music_rules.music_scale import MusicScale
f... | normal | {
"blob_id": "c846c33ef13795d51c6d23ffa5a6b564b66e6a3c",
"index": 3438,
"step-1": "<mask token>\n\n\nclass WeatherToMusicConverter:\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 WeatherToMusicConverter:\n <ma... | [
1,
4,
5,
6,
7
] |
# Copyright (c) 2015 OpenStack Foundation.
#
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unle... | normal | {
"blob_id": "89a3c34b3145b93a4cfa78eeb055c8136ab2bfe6",
"index": 2084,
"step-1": "<mask token>\n\n\nclass OvsApi(object):\n <mask token>\n\n def __init__(self, ip, protocol='tcp', port='6640', timeout=10):\n super(OvsApi, self).__init__()\n self.ip = ip\n self.protocol = protocol\n ... | [
18,
23,
25,
27,
35
] |
from flask import Flask, request, jsonify
import sqlite3
from database import Database
app = Flask(__name__)
db = Database()
@app.route('/')
def homepage():
argslist = request.args
faciltype = argslist.get('facil')
facils = []
try:
facils = db.getFacilitiesFromFacilityType(facilty... | normal | {
"blob_id": "2424d667e1bb4ee75b5053eb6f9b002787a5317f",
"index": 6391,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef homepage():\n argslist = request.args\n faciltype = argslist.get('facil')\n facils = []\n try:\n facils = db.getFacilitiesFromFacilityType(faciltype)\n facils = map(l... | [
2,
6,
7,
8,
9
] |
from flask import Flask, render_template, request
app = Flask(__name__)
def convert(decimal_num):
roman = {1000:'M', 900:'CM', 500:'D', 400:'CD', 100:'C', 90:'XC', 50:'L', 40:'XL', 10:'X', 9:'IX', 5:'V', 4:'IV', 1:'I'}
num_to_roman = ''
for i in roman.keys():
num_to_roman += roman[i]*(decimal_num/... | normal | {
"blob_id": "7025cc896035c59e0bbb7943493b6ca24fd9e6ca",
"index": 9429,
"step-1": "<mask token>\n\n\ndef convert(decimal_num):\n roman = {(1000): 'M', (900): 'CM', (500): 'D', (400): 'CD', (100): 'C',\n (90): 'XC', (50): 'L', (40): 'XL', (10): 'X', (9): 'IX', (5): 'V',\n (4): 'IV', (1): 'I'}\n ... | [
2,
3,
4,
5,
6
] |
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: MIT-0
#
# This code is sample only. Not for use in production.
#
# Author: Babu Srinivasan
# Contact: babusri@amazon.com, babu.b.srinivasan@gmail.com
#
# Spark Streaming ETL script
# Input:
# 1/ Kinesis Data Strea... | normal | {
"blob_id": "fcccbc8d582b709aa27500ef28d86103e98eee4c",
"index": 7980,
"step-1": "<mask token>\n\n\ndef populateTimeInterval(rec):\n out_ts = (rec['event_time'] - TEMP_TS) // DELTA_MINS * DELTA_MINS + TEMP_TS\n rec['intvl_date'] = datetime.datetime.strftime(out_ts, '%Y-%m-%d')\n rec['intvl_hhmm'] = date... | [
2,
3,
4,
5,
6
] |
#import cvxopt
from cvxopt import matrix, spmatrix, solvers
#import scipy
from scipy.special import expit
import numpy as np
import sys
import pandas as pd
import time
class KernelNC():
"""
distance based classifier for spectrum kernels
"""
def __init__(self, classes):
self.classes = class... | normal | {
"blob_id": "6f35c29f6f2dcc6c1dae3e9c1ddf595225748041",
"index": 3018,
"step-1": "<mask token>\n\n\nclass KernelNC:\n <mask token>\n\n def __init__(self, classes):\n self.classes = classes\n\n def compute_dist(self, X, Y):\n K_x = np.dot(X, X.T).toarray()\n K_y = np.dot(Y, Y.T).toar... | [
16,
17,
19,
20,
21
] |
# Copyright (c) "Neo4j"
# Neo4j Sweden AB [https://neo4j.com]
#
# This file is part of Neo4j.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2... | normal | {
"blob_id": "5b33615e1890631bac68801310e4b606ac41cb13",
"index": 1340,
"step-1": "<mask token>\n\n\nclass TestTimeDehydration(_TestTemporalDehydrationV1):\n\n @pytest.fixture\n def hydration_handler(self):\n return HydrationHandler()\n <mask token>\n <mask token>\n\n def test_pandas_date_ti... | [
6,
7,
8,
11,
13
] |
def check_bit4(input):
mas=0b1000
desired=input & mas
if desired>0:
return "om"
else :
return "off"
| normal | {
"blob_id": "29dc940292a6805aabfa5bed22bb75d31140c83f",
"index": 3257,
"step-1": "<mask token>\n",
"step-2": "def check_bit4(input):\n mas = 8\n desired = input & mas\n if desired > 0:\n return 'om'\n else:\n return 'off'\n",
"step-3": "def check_bit4(input):\n\tmas=0b1000\n\tdesire... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
"""
项目：爬取思否网站首页推荐文章
作者：cho
时间：2019.9.23
"""
import json
import parsel
import scrapy
from scrapy import Request
from SF.items import SfItem
class SfCrawlSpider(scrapy.Spider):
name = 'sf_crawl'
allowed_domains = ['segmentfault.com']
header = {
'user-agent': 'Mozilla/5.0 (W... | normal | {
"blob_id": "7ed6d475bfe36fdd0b6cd2f0902a0bccb22f7f60",
"index": 6082,
"step-1": "<mask token>\n\n\nclass SfCrawlSpider(scrapy.Spider):\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 SfCrawlSpider(scrapy.Spider)... | [
1,
4,
5,
6,
7
] |
import re
from typing import Any, Dict, List
import aiosqlite
from migri.elements import Query
from migri.interfaces import ConnectionBackend, TransactionBackend
class SQLiteConnection(ConnectionBackend):
_dialect = "sqlite"
@staticmethod
def _compile(query: Query) -> dict:
q = query.statement
... | normal | {
"blob_id": "191a57d3f13fcbe217ff6d0bd92dea163d5fb3cf",
"index": 4822,
"step-1": "<mask token>\n\n\nclass SQLiteConnection(ConnectionBackend):\n <mask token>\n <mask token>\n\n async def connect(self):\n self.db = await aiosqlite.connect(self.db_name)\n self.db.row_factory = aiosqlite.Row\... | [
3,
4,
5,
6,
7
] |
import pygame
import random
from lb_juego import*
#Dimensiones de la pantalla
ALTO=400
ANCHO=600
#lista de colores basicos
ROJO=(255,0,0)
SALMON=(240,99,99)
BLANCO=(255,255,255)
NEGRO=(0,0,0)
AZUL=(59,131,189)
VERDE=(0,255,0)
if __name__=='__main__':
#Inicializacion de la aplicacion en pygame
pygame.init()
... | normal | {
"blob_id": "85fc2fc0a404c20b1f0806412424192ea4a50a9b",
"index": 7085,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n pygame.init()\n fuente = pygame.font.Font(None, 36)\n pantalla = pygame.display.set_mode([ANCHO, ALTO])\n pantalla.fill(BLANCO)\n General = pyg... | [
0,
1,
2,
3,
4
] |
def readint(): return int(raw_input())
T = readint()
for t in xrange(T):
N = int(raw_input())
res = 0
sum = 0
min = 1000000
for i in raw_input().split():
r = int(i)
res ^= r
sum += r
if min > r: min = r
if res == 0:
sum -= min
print "Case #%d: %s" % (t + 1, sum)
else:
print "Case ... | normal | {
"blob_id": "81a1fbd13b06e4470bfbaa0d1716d5301e1a4b36",
"index": 1035,
"step-1": "def readint(): return int(raw_input())\r\n\r\nT = readint()\r\nfor t in xrange(T):\r\n\tN = int(raw_input())\r\n\tres = 0\r\n\tsum = 0\r\n\tmin = 1000000\r\n\tfor i in raw_input().split():\r\n\t\tr = int(i)\r\n\t\tres ^= r\r\n\t\ts... | [
0
] |
#manual forward propagation
#based on a course I got from Datacamp.com 'Deep Learning in Python'
#python3 ~/Documents/pyfiles/dl/forward.py
#imports
import numpy as np
#we are going to simulate a neural network forward propagation algorithm
#see the picture forwardPropagation.png for more info
#the basics are it mov... | normal | {
"blob_id": "6a09311b5b3b876fd94ed0a9cce30e070528f22c",
"index": 2993,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(weights)\n<mask token>\nprint(hidden_layer_vals)\n<mask token>\nprint(output_val)\n<mask token>\n",
"step-3": "<mask token>\ninput_data = np.array([2, 3])\nweights = {'node_0': np... | [
0,
1,
2,
3,
4
] |
# -*- coding:utf-8 -*-
# Author: 李泽军
# Date: 2020/1/27 3:31 PM
# Project: flask-demo
from flask import abort
from flask_login import current_user
from functools import wraps
from simpledu.modes import User
def role_required(role):
'''
带参数的装饰器，可以用它来保护一个路由处理函数智能被特定的用户访问
:param role:
:return:
'''... | normal | {
"blob_id": "b3f6d255830bdb2b0afc99aab6e3715616ac4dec",
"index": 4298,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef role_required(role):\n \"\"\"\n 带参数的装饰器，可以用它来保护一个路由处理函数智能被特定的用户访问\n :param role:\n :return:\n \"\"\"\n\n def decorator(func):\n\n @wraps(func)\n de... | [
0,
1,
2,
3,
4
] |
# 1.Create a list of 10 elements of four different data types like int, string, complex and float.
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','interesting']
c=[1+2j,2+3j,4+5j,5+6j,56+7j,8+9j,7+8j,3+6j,7+9j]
print... | normal | {
"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
] |
'''
Trolls are attacking your comment section!
A common way to deal with this situation is to remove all of the vowels from the trolls' comments, neutralizing the threat.
Your task is to write a function that takes a string and return a new string with all vowels removed.
For example, the string "This website is for... | normal | {
"blob_id": "4dea0967a0ee3e9eb3b46145739dfeb233f3a120",
"index": 5307,
"step-1": "<mask token>\n\n\ndef disemvowel(s):\n return s.translate(None, 'aeiouAEIOU')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef disemvowel(string):\n returnString = ''\n vowels = ['a', 'e', 'i', 'o', 'u']\n upper... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/python
import os
import sys
import csv
import json
from time import sleep
from datetime import datetime
ShowProgress = False
ConvertTime = False
def print_welcome():
print("""
[*******************************************************************************************************]
... | normal | {
"blob_id": "dace25428f48da633ee571b51565d15650782649",
"index": 1237,
"step-1": "#!/usr/bin/python\nimport os\nimport sys\nimport csv\nimport json\nfrom time import sleep\nfrom datetime import datetime\n\nShowProgress = False\nConvertTime = False\n\n\ndef print_welcome():\n print(\"\"\"\n[*******************... | [
0
] |
"""
Python wrapper that connects CPython interpreter to the numba dictobject.
"""
from collections import MutableMapping
from numba.types import DictType, TypeRef
from numba import njit, dictobject, types, cgutils
from numba.extending import (
overload_method,
box,
unbox,
NativeValue
)
@njit
def _mak... | normal | {
"blob_id": "ad44e9411ba6a07c54bb55b0d8af9d0c16c6b71b",
"index": 5173,
"step-1": "<mask token>\n\n\ndef _from_meminfo_ptr(ptr, dicttype):\n d = TypedDict(meminfo=ptr, dcttype=dicttype)\n return d\n\n\nclass TypedDict(MutableMapping):\n \"\"\"A typed-dictionary usable in Numba compiled functions.\n\n ... | [
19,
24,
28,
29,
33
] |
#!/bin/env python3
"""
A tool for painting and saving Game Boy tiles.
Usage: `python3 gb-tile-painter.py`
Please see: README.md.
"""
from sys import argv, exit
# If we got an argument and it is --help or -h
if len(argv) == 2 and (argv[1] == "--help" or argv[1] == "-h"):
print(__doc__) # Print the docstring
... | normal | {
"blob_id": "c153c7a3a11a09ed645540632daec42e8905432a",
"index": 4165,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif len(argv) == 2 and (argv[1] == '--help' or argv[1] == '-h'):\n print(__doc__)\n exit(0)\n<mask token>\nif __name__ == '__main__':\n window = MainWindow()\n window.mainloop(... | [
0,
1,
2,
3
] |
import numpy as np
import faiss
from util import vecs_io, vecs_util
from time import time
import os
'''
提取vecs, 输出numpy文件
'''
def vecs2numpy(fname, new_file_name, file_type, file_len=None):
if file_type == 'bvecs':
vectors, dim = vecs_io.bvecs_read_mmap(fname)
elif file_type == 'ivecs':... | normal | {
"blob_id": "5f84c8654c976bca2fa33e8f9ba5e28e3249253d",
"index": 7312,
"step-1": "<mask token>\n\n\ndef vecs2numpy(fname, new_file_name, file_type, file_len=None):\n if file_type == 'bvecs':\n vectors, dim = vecs_io.bvecs_read_mmap(fname)\n elif file_type == 'ivecs':\n vectors, dim = vecs_io.... | [
1,
2,
3,
4,
5
] |
import sqlite3
if __name__ == '__main__':
conn = sqlite3.connect('donations.sqlite')
c = conn.cursor()
query = """DROP TABLE IF EXISTS factions;"""
c.execute(query)
query = """DROP TABLE IF EXISTS members;"""
c.execute(query)
query = """DROP TABLE IF EXISTS bank;"""
c.execute(query)
... | normal | {
"blob_id": "b6b8dfaa9644fa4f4c250358b89f4a30c26c317f",
"index": 4788,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n conn = sqlite3.connect('donations.sqlite')\n c = conn.cursor()\n query = 'DROP TABLE IF EXISTS factions;'\n c.execute(query)\n query = 'DROP TA... | [
0,
1,
2,
3
] |
import numpy as np
import pandas as pd
import time
from sklearn.metrics import log_loss
from keras.models import Sequential, Model
from keras.layers import Dense, Input
from keras.layers import Dropout
from keras.layers import Flatten
from keras.layers import LSTM
from keras.layers.convolutional import Convolution3D
f... | normal | {
"blob_id": "e3d886dedaf5b120392d0dc81c4c71398f08f8d6",
"index": 8234,
"step-1": "<mask token>\n\n\ndef base_model():\n input_shape = 1, HM_SLICES, IMG_PX_SIZE, IMG_PX_SIZE\n inputs = Input(shape=input_shape)\n conv1 = Convolution3D(32, 5, 5, 5, activation='relu')(inputs)\n drop1 = Dropout(0.2)(conv1... | [
1,
2,
3,
4,
5
] |
import time
import os, os.path
import random
import cv2
import glob
import keras
import matplotlib
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.cluster import KMeans
from sklearn.mixture import GaussianMixture
from sklearn.decomposition import PCA
import pandas as ... | normal | {
"blob_id": "9c8a213fc8a7397662eebb74d6ee1ad34cb884d9",
"index": 1420,
"step-1": "<mask token>\n\n\ndef create_train_kmeans(data, number_of_clusters):\n k = KMeans(n_clusters=number_of_clusters, n_jobs=-1, random_state=728)\n start = time.time()\n k.fit(data)\n end = time.time()\n print('Training ... | [
1,
3,
4,
6,
7
] |
import cv2
import numpy as np
from pycocotools.coco import maskUtils
# from dataset.augmentors import FlipTransform, joints_to_point8, point8_to_joints, AugImgMetadata
# from dataset.base_dataflow import Meta
from dataset.augmentors import FlipTransform, joints_to_point8, point8_to_joints, AugImgMetadata
from data... | normal | {
"blob_id": "e47223622a2718830d830dbb779800659d659ae3",
"index": 8472,
"step-1": "<mask token>\n\n\ndef augment(components, augmentors, use_o=False):\n \"\"\"\n Augmenting of images.\n\n :param components: components\n :return: updated components.\n \"\"\"\n img_path = components[0]\n height... | [
2,
4,
5,
6,
7
] |
import sys
from pprint import pprint
sys.stdin = open("sample_input.txt", "r")
test_case = int(input())
"""
for test in range(test_case):
nxn_array, palin_len = map(int, input().split())
## 2차 배열 만들기 => 행스트링 리스트
order_2nd_array = []
for i in range(nxn_array):
order_2nd_array.append(input())
... | normal | {
"blob_id": "15fea8a84accdfc2dac87c111cbe8bfca61fe801",
"index": 3482,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.stdin = open('sample_input.txt', 'r')\ntest_case = int(input())\n<mask token>\n",
"step-3": "import sys\nfrom pprint import pprint\nsys.stdin = open('sample_input.txt', 'r')\ntest_c... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
import math
#COMECE SEU CÓDIGO AQUI
f = float(input('Digite o valor de f: '))
L = float(input('Digite o valor de L: '))
Q = float(input('Digite o valor de Q: '))
DeltaH = float(input('Digite o valor de DeltaH: '))
v = float(input('Digite o valor de v: '))
g = 9.81
e = 0.000002
#PROCESSAMENTO
D =... | normal | {
"blob_id": "b6183daa943cc63fd2959e3e54fc1e6af5d761de",
"index": 202,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('valor de D: %.4f' % D)\nprint('valor de Rey: %.4f' % Rey)\nprint('valor de k: %.4f' % k)\n",
"step-3": "<mask token>\nf = float(input('Digite o valor de f: '))\nL = float(input('D... | [
0,
1,
2,
3,
4
] |
#coding=utf-8
from selenium import webdriver
from selenium.webdriver import ActionChains
# 常用鼠标操作
driver = webdriver.Chrome()
driver.get('https://www.baidu.com')
driver.maximize_window()
element = driver.find_element_by_link_text(u"新闻")
#˫ 双击 ‘新闻’ 这个超链接
ActionChains(driver).double_click(element).perform()
import time
... | normal | {
"blob_id": "e3f180d4309ade39ac42a895f7f73469fd20724f",
"index": 4538,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndriver.get('https://www.baidu.com')\ndriver.maximize_window()\n<mask token>\nActionChains(driver).double_click(element).perform()\n<mask token>\ntime.sleep(2)\ndriver.quit()\n<mask token>... | [
0,
1,
2,
3,
4
] |
import os, time
def counter(count): # run in new process
for i in range(count):
time.sleep(1) # simulate real work
print('[%s] => %s' % (os.getpid(), i))
import pdb;pdb.set_trace()
for i in range(5):
pid= os.fork()
if pid !... | normal | {
"blob_id": "fd564d09d7320fd444ed6eec7e51afa4d065ec4d",
"index": 6945,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef counter(count):\n for i in range(count):\n time.sleep(1)\n print('[%s] => %s' % (os.getpid(), i))\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef counter... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
##############################################################################
#
# OpenERP, Open Source Management Solution
# Copyright (c) 2010-2014 Elico Corp. All Rights Reserved.
# Alex Duan <alex.duan@elico-corp.com>
#
# This program is free software: you can redistribute it and... | normal | {
"blob_id": "19d86c64876575ed9b3f5e33dd44e7633c96e696",
"index": 2401,
"step-1": "<mask token>\n\n\nclass product_product(orm.Model):\n <mask token>\n <mask token>\n <mask token>\n\n def _get_sale_quotation_qty(self, cr, uid, product_id, context=None):\n \"\"\"get all qty of the product in all... | [
2,
6,
8,
9,
10
] |
'Attempts to use <http://countergram.com/software/pytidylib>.'
try:
import tidylib
def tidy(html):
html, errors = tidylib.tidy_document(html, options={'force-output': True,
'output-xhtml': True, 'tidy-mark': False})
return html
except ImportError:
def tidy(html):
return html
| normal | {
"blob_id": "33ec822f6149a57244edf6d8d99a5b3726600c2e",
"index": 3236,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n import tidylib\n\n def tidy(html):\n html, errors = tidylib.tidy_document(html, options={'force-output':\n True, 'output-xhtml': True, 'tidy-mark': False})\... | [
0,
1,
2
] |
from tkinter import *
import tkinter.messagebox
import apikey
import tinify
class Setting_GUI(Toplevel):
def __init__(self,parent):
super().__init__()
self.parent = parent
key = "Input your key here"
self.keystringvar = StringVar()
self.wm_title("Settings - TingImage")
... | normal | {
"blob_id": "9340c9055a7e0d74d232d878b43d91a3e6cd32e5",
"index": 5785,
"step-1": "<mask token>\n\n\nclass Setting_GUI(Toplevel):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Setting_GUI(Toplevel):\n\n def __init__(self, parent):\n super().__init__()\n self.parent ... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
#
# ConVirt - Copyright (c) 2008 Convirture Corp.
# ======
#
# ConVirt is a Virtualization management tool with a graphical user
# interface that allows for performing the standard set of VM operations
# (start, stop, pause, kill, shutdown, reboot, snapshot, etc...). It
# also attempts to s... | normal | {
"blob_id": "3078a0c7e2c711da88846ca3401c7924b1790dbc",
"index": 1251,
"step-1": "#!/usr/bin/env python\n#\n# ConVirt - Copyright (c) 2008 Convirture Corp.\n# ======\n#\n# ConVirt is a Virtualization management tool with a graphical user\n# interface that allows for performing the standard set of VM opera... | [
0
] |
"""
Python 3.3 introduces the new "yield from" statement to provide straightforward way for
a generator to call out to other generators
"""
def gen1():
yield 'foo'
yield 'bar'
def gen2():
yield 'spam'
yield 'eggs'
"""
For python versions < 3.3
"""
def full_gen():
for word in gen1():
yiel... | normal | {
"blob_id": "c1e649b73c207ea08235d295c28daad8c91398a7",
"index": 1440,
"step-1": "\"\"\"\nPython 3.3 introduces the new \"yield from\" statement to provide straightforward way for\na generator to call out to other generators\n\"\"\"\n\ndef gen1():\n yield 'foo'\n yield 'bar'\n\ndef gen2():\n yield 'spam... | [
0
] |
import numpy as np
# UM TRABALHO FEITO PELA GRANDE DUPLA PEQUENA Mag e Rud
def main():
a = int(input("Informe a sua opção (Aleatório = 0, Você escolhe = outro numero): "))
if(a != 0):
linhas = int(input("Informe o número de linhas da matriz: "))
colunas = int(input("Informe o número de colunas... | normal | {
"blob_id": "c80ecb97c8863b724169715b766024ce824b9225",
"index": 5572,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n a = int(input(\n 'Informe a sua opção (Aleatório = 0, Você escolhe = outro numero): '))\n if a != 0:\n linhas = int(input('Informe o número de linhas... | [
0,
1,
2,
3,
4
] |
import sys
from PyQt4 import QtGui,QtCore
class Button(QtGui.QPushButton):
def __init__(self,*__args):
super().__init__(*__args)
self.setAcceptDrops(True) # 设置可以接受拖入事件
def dragEnterEvent(self, e):
"设置接受的类型"
#判断拖动的数据类型是否是：text/plain # 这两个一组表示一个类型
#查询方法是：e.mimeData().form... | normal | {
"blob_id": "e4b0dc2e3d9310bbe462e746e21080d309dfed84",
"index": 9640,
"step-1": "<mask token>\n\n\nclass Button(QtGui.QPushButton):\n\n def __init__(self, *__args):\n super().__init__(*__args)\n self.setAcceptDrops(True)\n\n def dragEnterEvent(self, e):\n \"\"\"设置接受的类型\"\"\"\n ... | [
5,
6,
7,
8,
9
] |
from scrapy import Spider, Request
from urllib.parse import quote
from Product.items import ProductItem
class TaobaoSpider(Spider):
name = 'taobao'
allowed_domains = ['www.taobao.com']
start_urls = ['http://www.taobao.com/']
def parse(self, response, **kwargs):
pass
| normal | {
"blob_id": "8f709af924820c77290f97731d9f96258c3db095",
"index": 2533,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TaobaoSpider(Spider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TaobaoSpider(Spider):\n <mask token>\n ... | [
0,
1,
2,
3,
4
] |
# -*- encoding: utf-8 -*-
import requests
import time
import random
STATS = True
INFINITE = True
VOTING_ENDPOINT = 'http://www.adressa.no/poll/vote.do'
# These are the required fields from the voting form
payload = {
"vote": "svar4",
"mentometerId": "10790638",
"publicationId": "167",
"redirectTo": "... | normal | {
"blob_id": "1e344330b88b336598295e2a7be6a6dc57cb3d59",
"index": 8207,
"step-1": "# -*- encoding: utf-8 -*-\n\nimport requests\nimport time\nimport random\n\nSTATS = True\nINFINITE = True\nVOTING_ENDPOINT = 'http://www.adressa.no/poll/vote.do'\n\n# These are the required fields from the voting form\npayload = {\... | [
0
] |
N=int(input("N="))
K=int()
K=0
while N>=2:
N=N/2
K=K+1
print("K=",K) | normal | {
"blob_id": "7f4c6e4a5627b44b9a700d2de4f9caca0ae8b17c",
"index": 2808,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile N >= 2:\n N = N / 2\n K = K + 1\nprint('K=', K)\n",
"step-3": "N = int(input('N='))\nK = int()\nK = 0\nwhile N >= 2:\n N = N / 2\n K = K + 1\nprint('K=', K)\n",
"ste... | [
0,
1,
2,
3
] |
n = int(input())
b = 0
p = [0,0]
flg = True
for i in range(n):
t,x,y = map(int,input().split())
diff = abs(x - p[0]) + abs(y - p[1])
time = t - b
if(diff > time or time%2 != diff %2):
flg = False
break
else:
b = t
p[0] = x
p[1] = y
if flg:
print("Yes")
else:
print("No")
| normal | {
"blob_id": "8bc465a1b546907d8a9e5eee2cae672befb1ea13",
"index": 7808,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(n):\n t, x, y = map(int, input().split())\n diff = abs(x - p[0]) + abs(y - p[1])\n time = t - b\n if diff > time or time % 2 != diff % 2:\n flg = False\n... | [
0,
1,
2,
3
] |
# https://leetcode.com/problems/how-many-numbers-are-smaller-than-the-current-number/
# BruteForce
class BruteForceSolution:
def smallerNumbersThanCurrent(self, nums):
answer = []
for num in nums:
counter = 0
for i in range(len(nums)):
if n... | normal | {
"blob_id": "58e023c3c453d1e190fdb5bc457358f42d1bd93f",
"index": 397,
"step-1": "class BruteForceSolution:\n <mask token>\n\n\nclass Solution:\n\n def smallerNumbersThanCurrent(self, nums):\n answer = []\n sortedNums = sorted(nums)\n for num in nums:\n answer.append(sortedNu... | [
3,
4,
5,
6,
7
] |
import os
import numpy as np
import nibabel as nib
def loop_access(n,m,data,tpl):
if n >m:
return loop_access(n,m+1,data[tpl[m]],tpl)
else:
return data[tpl[m]]
def loop_rec(n,m,mapCoords,dims,data,tple):
if n >= m:
for x in range(dims[m]):
loop_rec(n,m+1,mapCoords,dims,... | normal | {
"blob_id": "55b4448caa73bcb50a15eb46d07328934fce72c8",
"index": 7029,
"step-1": "<mask token>\n\n\ndef loop_rec(n, m, mapCoords, dims, data, tple):\n if n >= m:\n for x in range(dims[m]):\n loop_rec(n, m + 1, mapCoords, dims, data, tple + (x,))\n else:\n temp = loop_access(len(dim... | [
1,
2,
3,
4,
5
] |
import sqlparse
f = open("parse.sql")
go = open("struct.go", "w+")
dictiony = {
"uuid": "string",
"varchar": "string",
"timestamp": "time.Time",
"int": "int",
"text": "string",
"dbname": "IndividualContrAgent",
"interface": "IndividualContrAgentI",
"ica":"ica"
}
#package
go.write("packa... | normal | {
"blob_id": "e99e558ebf5938a90f00df6593c9f75a18affcb8",
"index": 9127,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ngo.write('package main\\n\\n')\ngo.write('import (\\n ')\ngo.write(\"\"\"\"github.com/jmoiron/sqlx\"\n)\n\n\"\"\")\ngo.write('type {0} struct {1}\\n'.format(dictiony['dbname'], '{'))\n... | [
0,
1,
2,
3,
4
] |
import httplib
import sys
http_server = "localhost:8000"
connection = httplib.HTTPConnection(http_server)
# Open test input.
test_file_path = "test_input"
test_f = open(test_file_path)
inputs = test_f.readlines()
inputs = [x.strip() for x in inputs]
test_f.close()
# Open expected input.
expected_file_path = "expect... | normal | {
"blob_id": "cd9b04a93d85ba0ee2a38b534386f9aec0ef6895",
"index": 5165,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntest_f.close()\n<mask token>\nexpected_f.close()\nassert len(inputs) == len(expecteds)\nfor i in range(len(inputs)):\n connection.request('GET', '<start>%s<end>' % inputs[i])\n resp... | [
0,
1,
2,
3,
4
] |
# Generated by Django 3.2.4 on 2021-07-18 02:05
from django.db import migrations, models
import django.db.models.deletion
import uuid
class Migration(migrations.Migration):
initial = True
dependencies = [
('tracker', '0003_auto_20210626_0735'),
]
operations = [
migrations.CreateMod... | normal | {
"blob_id": "ead843f1edcfe798613effb049e3ca79dcd03b71",
"index": 7919,
"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
] |
"""Unit test for int install
"""
import math
import pytest
ROUND_OFF_ERROR = 0.001
def int_installs(x):
try:
return int(x.replace(',', '').replace('+', ''))
except:
raise ValueError("Cannot transform to int.")
def test_int_install_1():
"""Unit test to showcase functionality of int... | normal | {
"blob_id": "b874bfe9590a3eaff4298d6f9cc72be92000dc30",
"index": 1108,
"step-1": "<mask token>\n\n\ndef int_installs(x):\n try:\n return int(x.replace(',', '').replace('+', ''))\n except:\n raise ValueError('Cannot transform to int.')\n\n\ndef test_int_install_1():\n \"\"\"Unit test to sho... | [
2,
4,
5,
6,
7
] |
from django.contrib import admin
from employees.models import Leave,EmployeeProfile
admin.site.register(Leave)
admin.site.register(EmployeeProfile)
# Register your models here.
| normal | {
"blob_id": "77ea670b537e9ff7082aeb9ed54b011fa8e3a035",
"index": 6328,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.site.register(Leave)\nadmin.site.register(EmployeeProfile)\n",
"step-3": "from django.contrib import admin\nfrom employees.models import Leave, EmployeeProfile\nadmin.site.registe... | [
0,
1,
2,
3
] |
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init as init
import numpy as np
import time
import os
import csv
import matplotlib.pyplot as plt
from GELu import GELu
from My_Dataset import MyDataset
from pytorchtools import EarlyStopping
from LSTM import LSTM
'''
Wr... | normal | {
"blob_id": "80531ac3cc247d48ee36bff581925b8f29f9e235",
"index": 8590,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef train_model(model, DEVICE, patience, n_epochs, csv_record=False):\n train_losses = []\n valid_losses = []\n avg_train_losses = []\n avg_valid_losses = []\n early_st... | [
0,
1,
2,
3,
4
] |
import basevcstest
class TestVCSBoxfill(basevcstest.VCSBaseTest):
def testRobinsonBoxfill(self):
# This tests if extending the longitude to more than 360 decrees is handled correctly by
# proj4. See https://github.com/UV-CDAT/uvcdat/issues/1728 for more
# information.
clt3 = self.c... | normal | {
"blob_id": "c1475209d9c9a98d72d7f703e0516aceaeb13163",
"index": 6820,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TestVCSBoxfill(basevcstest.VCSBaseTest):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TestVCSBoxfill(basevcstest.VCSBaseTest):\n\n def testRobinsonBoxfill(self)... | [
0,
1,
2,
3,
4
] |
import os
import random
import cv2
import tensorflow as tf
import tensorflow.contrib.slim as slim
import tensorflow.contrib.slim.nets as nets
from skimage.transform import resize
import PIL
import numpy as np
import json
# os.environ["CUDA_VISIBLE_DEVICES"] = "1"
import matplotlib.pyplot as plt
# plt.switch_backend('... | normal | {
"blob_id": "31d87b11f6a1f6304a2fef6dd1cd1c0ca292dfe8",
"index": 3491,
"step-1": "<mask token>\n\n\ndef inception(image, reuse):\n preprocessed = tf.multiply(tf.subtract(tf.expand_dims(image, 0), 0.5), 2.0)\n arg_scope = nets.inception.inception_v3_arg_scope(weight_decay=0.0)\n with slim.arg_scope(arg_s... | [
5,
6,
7,
9,
10
] |
import sys
sys.stdin = open("sample_input_17.txt","r")
T = int(input())
def code(N): # 암호코드가 있는 열의 위치를 찾음
code = []
for i in range(N-4):
for j in range(49,53):
if S[i][j] == "1" :
code = S[i]
return code
def code_s(code): # 암호코드의 행 위치를 찾아 슬라이싱
for x in ... | normal | {
"blob_id": "b739c1de6c008158ee3806bed9fa2865eb484b4f",
"index": 5596,
"step-1": "<mask token>\n\n\ndef code(N):\n code = []\n for i in range(N - 4):\n for j in range(49, 53):\n if S[i][j] == '1':\n code = S[i]\n return code\n\n\ndef code_s(code):\n for x ... | [
3,
4,
5,
6,
7
] |
from flask import Flask,render_template, redirect, url_for,request, jsonify, abort,request
from flask_sqlalchemy import SQLAlchemy
from src.flaskbasic import *
from src.flaskbasic.form import StudentForm
from src.flaskbasic.models import Student
import sys
import logging
# logging.basicConfig(filename='app.log... | normal | {
"blob_id": "18f9e55b62b30ce8c9d4a57cd9c159543a738770",
"index": 4709,
"step-1": "<mask token>\n\n\n@application.route('/results', methods=['GET', 'POST'])\ndef get_results():\n _logger_getting.warning('retrieving all student results')\n data = Student.query.all()\n _logger_getting.warning('the students... | [
4,
6,
7,
8,
9
] |
def spam(divide_by):
return 42 / divide_by
try:
print(spam(2))
print(spam(12))
print(spam(0))
print(spam(1))
print(spam("dog"))
except Exception:
print("Error: Invalid argument.")
| normal | {
"blob_id": "357ee02060cbfa391920b3d45dfbe16e679a6c8d",
"index": 7346,
"step-1": "<mask token>\n",
"step-2": "def spam(divide_by):\n return 42 / divide_by\n\n\n<mask token>\n",
"step-3": "def spam(divide_by):\n return 42 / divide_by\n\n\ntry:\n print(spam(2))\n print(spam(12))\n print(spam(0))... | [
0,
1,
2,
3
] |
from common.get_keyword import GetKeyword
from common.operation_Excel import OperationExcel
from common.op_database import OpDatabase
from interface.login import Login
from interface.address import Address
import unittest
import ddt
# 测试数据
op_excel = OperationExcel()
add_file = r'D:\pyCharm\Demo\pycode\Requests\201911... | normal | {
"blob_id": "0f0b3eea9dc397d32e81749304041abaf6651e94",
"index": 1873,
"step-1": "<mask token>\n\n\n@ddt.ddt\nclass TestAddress(unittest.TestCase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def test_02_check_address(self):\n url = 'http://ecshop.itsoso.cn/ECMobile/?url... | [
2,
8,
9,
10,
12
] |
from django.apps import AppConfig
class FitnerappConfig(AppConfig):
name = 'fitnerapp'
| normal | {
"blob_id": "6546d04d3755d62d1a8756bdec1a10f6f018dcea",
"index": 5638,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass FitnerappConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass FitnerappConfig(AppConfig):\n name = 'fitnerapp'\n",
"step-4": "from django.apps impo... | [
0,
1,
2,
3
] |
from share_settings import Settings
import urllib.request,json
import pprint as p
s = Settings()
prefix = "http://finance.google.com/finance?client=ig&output=json&q="
def get(symbol,exchange):
url = prefix+"%s:%s"%(exchange,symbol)
u = urllib.request.urlopen(url)
#translates url to string
c = u.re... | normal | {
"blob_id": "7247ef463998f6738c21ad8efa988a32f7fb99c0",
"index": 4760,
"step-1": "<mask token>\n\n\ndef get_lp(s):\n \"\"\"gets latest prices from google\"\"\"\n sl = []\n for stock in s.symbols:\n quote = get(stock, 'LON')\n x = quote.replace(',', '')\n x = float(x)\n sl.app... | [
1,
2,
3,
4,
5
] |
# data={
# "name":"Alby",
# "age":23
# }
# print (data['age'])
# def foo():
# print("Hellow world")
# return 1
# print (foo())
a="aa"
def add():
print(a)
add() | normal | {
"blob_id": "97857c1c5468a96187d44abc23ffaaf2a7ead1a6",
"index": 1869,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef add():\n print(a)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef add():\n print(a)\n\n\nadd()\n",
"step-4": "a = 'aa'\n\n\ndef add():\n print(a)\n\n\nadd()\n"... | [
0,
1,
2,
3,
4
] |
import io
import os
from setuptools import setup
setup(name='testcov-plugin',
version='1.0',
packages=['testcov'],
namespace_packages=['testcov'],
entry_points={
'plugins': ['testp = testcov.plugin:testp'],
},
description="Test for coverage bug")
| normal | {
"blob_id": "88f5aa56eca6b61ba2b428bff0efdf4ec7f5f5d9",
"index": 1913,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name='testcov-plugin', version='1.0', packages=['testcov'],\n namespace_packages=['testcov'], entry_points={'plugins': [\n 'testp = testcov.plugin:testp']}, description='Test ... | [
0,
1,
2,
3
] |
#for declaring the variables used in program
img_rows=200
img_cols=200
img_channels=1
nb_classes=3
nb_test_images=1
| normal | {
"blob_id": "c41388043295280f9354e661a8d38ae46cae2d65",
"index": 9590,
"step-1": "<mask token>\n",
"step-2": "img_rows = 200\nimg_cols = 200\nimg_channels = 1\nnb_classes = 3\nnb_test_images = 1\n",
"step-3": "#for declaring the variables used in program\nimg_rows=200\nimg_cols=200\nimg_channels=1\nnb_classe... | [
0,
1,
2
] |
# Generated by Django 4.1.9 on 2023-06-29 16:11
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("search", "0003_auto_20230209_1441"),
]
operations = [
migrations.CreateModel(
name="SearchSettings",
fields=[
... | normal | {
"blob_id": "45969b346d6d5cbdef2f5d2f74270cf12024072d",
"index": 3,
"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 = [('search', '0003... | [
0,
1,
2,
3,
4
] |
# -*- coding:utf-8 -*-
__author__ = 'leandro'
from datetime import *
from PyQt4 import QtGui, QtCore
from baseDatos.ventas.venta import NotaCredito
from gui import CRUDWidget,MdiWidget
from ventanas import Ui_vtnDevolucionDeCliente, Ui_vtnReintegroCliente, Ui_vtnVentaContado
from baseDatos.obraSocial import ObraSoc... | normal | {
"blob_id": "59233cd45000cd6d6ad0876eb3812599392d7c05",
"index": 9357,
"step-1": "# -*- coding:utf-8 -*-\n__author__ = 'leandro'\n\n\nfrom datetime import *\n\nfrom PyQt4 import QtGui, QtCore\n\nfrom baseDatos.ventas.venta import NotaCredito\nfrom gui import CRUDWidget,MdiWidget\nfrom ventanas import Ui_vtnDevol... | [
0
] |
import pickle
import time
start = time.time()
f = open('my_classifier.pickle', 'rb')
cl = pickle.load(f)
f.close()
print(cl.classify("Where to travel in bangalore ?"))
print(cl.classify("Name a golf course in Myrtle beach ."))
print(cl.classify("What body of water does the Danube River flow into ?"))
#print("Accuracy... | normal | {
"blob_id": "82a3fca0261b4bde43f7bf258bb22e5b2ea8c28d",
"index": 5370,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nf.close()\nprint(cl.classify('Where to travel in bangalore ?'))\nprint(cl.classify('Name a golf course in Myrtle beach .'))\nprint(cl.classify('What body of water does the Danube River fl... | [
0,
1,
2,
3,
4
] |
import os
import re
import sys
import traceback
import readline
from typing import NamedTuple, List
from PyInquirer import prompt
from pygments import highlight
from pygments.formatters.terminal import TerminalFormatter
from pygments.lexers.python import PythonLexer
import argparse
parser = argparse.ArgumentParser(d... | normal | {
"blob_id": "bec3d8546cd7d27f7da48f5658480cf17c36a255",
"index": 9462,
"step-1": "<mask token>\n\n\nclass Grade(NamedTuple):\n score: int\n message: str\n comments: List[Comment]\n\n\ndef clear():\n os.system('cls' if os.name == 'nt' else 'clear')\n\n\n<mask token>\n\n\ndef complete(comment):\n if... | [
9,
12,
13,
14,
17
] |
import hashlib
md5 = hashlib.md5(b'Najmul')
print(md5.hexdigest())
sha1 = hashlib.sha1(b'Najmul')
print(sha1.hexdigest())
sha224 = hashlib.sha224(b'Najmul')
print(sha224.hexdigest())
sha256 = hashlib.sha256(b'Najmul')
print(sha256.hexdigest())
sha384 = hashlib.sha384(b'Najmul')
print(sha384.hexdigest())
sha512 = hashli... | normal | {
"blob_id": "ab4c668c8a167f8c387199b7aa49aa742d563250",
"index": 1698,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(md5.hexdigest())\n<mask token>\nprint(sha1.hexdigest())\n<mask token>\nprint(sha224.hexdigest())\n<mask token>\nprint(sha256.hexdigest())\n<mask token>\nprint(sha384.hexdigest())\n<... | [
0,
1,
2,
3
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
@author: Allen(Zifeng) An
@course:
@contact: anz8@mcmaster.ca
@file: 17. Letter Combinations of a Phone Number.py
@time: 2020/2/2 21:18
'''
from typing import List
class Solution:
def letterCombinations(self, digits: str) -> List[str]:
d={2:'abc',
... | normal | {
"blob_id": "de925b8f6bd31bfdfd1f04628659847b0761899d",
"index": 340,
"step-1": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n\n def letterCombinations(self, digits: str) ->List[str]:\n d = {(2): 'abc', (3): 'def', (4): 'ghi',... | [
1,
2,
3,
4,
5
] |
import graphene
from django.core.exceptions import ValidationError
from ....app import models
from ....app.error_codes import AppErrorCode
from ....permission.enums import AppPermission, get_permissions
from ....webhook.event_types import WebhookEventAsyncType
from ...account.utils import can_manage_app
from ...core.m... | normal | {
"blob_id": "972a063bab35926472be592e6a17d450034fbf37",
"index": 4745,
"step-1": "<mask token>\n\n\nclass AppUpdate(ModelMutation):\n\n\n class Arguments:\n id = graphene.ID(description='ID of an app to update.', required=True)\n input = AppInput(required=True, description=\n 'Fields ... | [
1,
2,
3,
4,
5
] |
"""empty message
Revision ID: 0bb5933fe69f
Revises: 09c6fdb3cf81
Create Date: 2021-03-11 16:48:06.771046
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '0bb5933fe69f'
down_revision = '09c6fdb3cf81'
branch_labels = None
depends_on = None
def upgrade():
# ... | normal | {
"blob_id": "f727c0551f20fb0dc72b4d81b7b3ed8ce9b1b6f4",
"index": 2072,
"step-1": "<mask token>\n\n\ndef downgrade():\n op.drop_constraint(None, 'user', type_='unique')\n op.drop_constraint(None, 'user', type_='unique')\n op.drop_column('user', 'money')\n",
"step-2": "<mask token>\n\n\ndef upgrade():\n... | [
1,
2,
3,
4,
5
] |
import os
from flask import Flask,render_template,request,redirect,url_for
from sqlalchemy import create_engine
from sqlalchemy.orm import scoped_session,sessionmaker
app = Flask(__name__)
engine = create_engine("postgres://lkghylsqhggivp:d827f6dc5637928e95e060761de590b7d9514e9463c5241ed3d652d777a4a3a9@ec2-5... | normal | {
"blob_id": "af9430caff843242381d7c99d76ff3c964915700",
"index": 6753,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef index():\n return render_template('a.html')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\n@app.route('/')\ndef index():\n return render_template('a.html')\n\n\n@app.route('/insert... | [
1,
2,
3,
4,
5
] |
from __future__ import absolute_import
import unittest
import yaml
import os
from bok_choy.web_app_test import WebAppTest
from .pages.job_config_history_subpage import JobConfigHistorySubPage
class TestJobConfigHistory(WebAppTest):
def setUp(self):
super(TestJobConfigHistory, self).setUp()
config_... | normal | {
"blob_id": "51bdbec732bebd73a84b52c6d1d39eead047d29e",
"index": 5349,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TestJobConfigHistory(WebAppTest):\n\n def setUp(self):\n super(TestJobConfigHistory, self).setUp()\n config_path = os.getenv('CONFIG_PATH')\n try:\n ... | [
0,
2,
3,
4,
5
] |
# pyOCD debugger
# Copyright (c) 2006-2013,2018 Arm Limited
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | normal | {
"blob_id": "58aa72588357b18ab42391dfffbf2a1b66589edd",
"index": 552,
"step-1": "<mask token>\n\n\nclass KV11Z7(Kinetis):\n <mask token>\n\n def __init__(self, session):\n super(KV11Z7, self).__init__(session, self.MEMORY_MAP)\n self._svd_location = SVDFile.from_builtin('MKV11Z7.svd')\n",
"... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/python
# -*- coding: UTF-8 -*-
def parse(node, array):
string = ''
string += "\t%s = ScrollView:create();\n" % node
if (array.get('IsBounceEnabled') != None and array['IsBounceEnabled']):
string += "\t%s:setBounceEnabled(true);\n" % node
if (array.get('InnerNodeSize') != None):
... | normal | {
"blob_id": "97b94f3388a6e2473d43e3c4c4e281a86a031dbb",
"index": 9288,
"step-1": "<mask token>\n",
"step-2": "def parse(node, array):\n string = ''\n string += '\\t%s = ScrollView:create();\\n' % node\n if array.get('IsBounceEnabled') != None and array['IsBounceEnabled']:\n string += '\\t%s:set... | [
0,
1,
2
] |
from flask import Blueprint, render_template, flash, redirect, url_for, request, current_app, g, session
from flask_login import current_user
from app import decorators
from app.models import User, Post, Comment, Tag
from slugify import slugify
from app.main.forms import CommentForm, TagForm, ProfileForm, ContactForm
f... | normal | {
"blob_id": "4e66fe0485d987da590d11c848009b2e1665b3dc",
"index": 5445,
"step-1": "<mask token>\n\n\ndef manage_prev_page():\n global session, request\n if ('profile' not in request.referrer and 'change_password' not in\n request.referrer and 'forgot_password' not in request.referrer and \n 'r... | [
5,
6,
7,
8,
9
] |
from collections import deque
def solution(people, limit):
people.sort()
cnt = 0
left_idx = 0
right_idx = len(people) - 1
while left_idx <= right_idx:
if people[left_idx] + people[right_idx] <= limit:
cnt += 1
left_idx += 1
right_idx -= 1
else:
... | normal | {
"blob_id": "b0dbc4e8a2ce41dc9d2040890e3df4d078680fa1",
"index": 5444,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef solution(people, limit):\n people.sort()\n cnt = 0\n left_idx = 0\n right_idx = len(people) - 1\n while left_idx <= right_idx:\n if people[left_idx] + people... | [
0,
1,
2
] |
#!/bin/env python3
import os
##print(os.environ)
##print("**********************************************************************")
##print("**********************************************************************")
##print("**********************************************************************")
##print(str(os.environ.ge... | normal | {
"blob_id": "b49696d6cac5fbf97172aa7cf16903d002262b5c",
"index": 1940,
"step-1": "<mask token>\n\n\ndef AddOverflow(h):\n nxbins = h.GetXaxis().GetNbins()\n nybins = h.GetYaxis().GetNbins()\n idxx = 0.0\n idxy = nybins + 1\n for ix in range(nxbins):\n idxx = ix + 1\n ovf_bincont = h.... | [
1,
2,
3,
4,
5
] |
# MINISTを読み込んでレイヤーAPIでCNNを構築するファイル
import tensorflow as tf
import numpy as np
import os
import tensorflow as tf
import glob
import numpy as np
import config as cf
from data_loader import DataLoader
from PIL import Image
from matplotlib import pylab as plt
dl = DataLoader(phase='Train', shuffle=True)
X... | normal | {
"blob_id": "a5559ff22776dee133f5398bae573f515efb8484",
"index": 3820,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndl = DataLoader(phase='Train', shuffle=True)\nX_data, y_data = dl.shuffle_and_get()\nX_data = np.reshape(X_data, [-1, cf.Height, cf.Width])\nconfig = tf.ConfigProto()\nconfig.gpu_options.... | [
0,
1,
2,
3
] |
num=int(input("enter no"))
def factorial(no):
fact=1
if no <0:
print("-ve no factorial not exist")
else:
for i in range(1,no+1):
fact=fact*i
return fact
print(factorial(num)) | normal | {
"blob_id": "2d3ab575b18144f714f06167f54cd069af4e5895",
"index": 7506,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef factorial(no):\n fact = 1\n if no < 0:\n print('-ve no factorial not exist')\n else:\n for i in range(1, no + 1):\n fact = fact * i\n retu... | [
0,
1,
2,
3,
4
] |
#! /usr/bin/env python
#
# Copyright (c) 2015 Jason Ish
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copyright
# notice, this li... | normal | {
"blob_id": "41889456fbb56d263e0039716519e8959316b67e",
"index": 3473,
"step-1": "<mask token>\n\n\ndef render_timestamp(sec, usec):\n tt = time.localtime(sec)\n return '%04d-%02d-%02dT%02d:%02d:%02d.%06d%s' % (tt.tm_year, tt.tm_mon,\n tt.tm_mday, tt.tm_hour, tt.tm_min, tt.tm_sec, usec, get_tzoffset... | [
12,
15,
16,
17,
19
] |
# -*- coding: utf-8 -*-
"""
Created on Fri Apr 10 01:03:35 2020
@author: Jordan
"""
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from datetime import date
## from COVID19_Simple import *
from COVID19_Diff import calc_diff_country
### Dash Stuff ###
import dash
import dash_core... | normal | {
"blob_id": "1e02d584cde0cdf251aa36abd27b683219ef87ed",
"index": 7539,
"step-1": "<mask token>\n\n\n@app.callback(Output(component_id='global-box-1', component_property=\n 'figure'), [Input(component_id='global-dropdown', component_property=\n 'value')])\ndef global_update(select_global):\n if select_gl... | [
3,
4,
5,
6,
7
] |
from django.db import models
# Create your models here.
class Covid(models.Model):
states= models.CharField(max_length=100, null=True, blank=True)
affected = models.IntegerField(null=True)
cured = models.IntegerField(null=True)
death = models.IntegerField(null=True)
| normal | {
"blob_id": "284955a555ce1a727ba5041008cd0bac3c3bed49",
"index": 1283,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Covid(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Covid(models.Model):\n states = models.C... | [
0,
1,
2,
3,
4
] |
import unittest.mock
import assist
import pytest
def test_simple_query():
q = assist.build_query(select='time, value', from_='system_load',
where='L2=\'cpuload\' and time > \'2021-06-16 00:00:00\' and time < \'2021-06-17 00:00:00\' and "name" != \'Idle\'',
gr... | normal | {
"blob_id": "8aa9ba145b6c7347a7a926d50dca35383ddd52a3",
"index": 9217,
"step-1": "<mask token>\n\n\ndef test_nested_query_with_datetime():\n inner_q = assist.build_query(select='time, value', from_='system_load',\n where='L2=\\'cpuload\\' and \"name\" != \\'Idle\\'', groupby=('host', 'L3'))\n outer_... | [
6,
8,
9,
11,
12
] |
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from sklearn import linear_model
from features import calculateTargets
currency = 'EURUSD'
interval = '1440'
df = pd.read_csv(
r'../data/' + currency.upper() + interval + '.csv',
names=['date', 'time', 'open', 'high', 'low', 'close', 'volu... | normal | {
"blob_id": "8c0bae9e49c5ea9fbdee7c5c864afff16cc9f8b8",
"index": 3757,
"step-1": "import matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nfrom sklearn import linear_model\nfrom features import calculateTargets\n\ncurrency = 'EURUSD'\ninterval = '1440'\n\ndf = pd.read_csv(\n r'../data/' + cur... | [
0
] |
# Default imports
from sklearn.feature_selection import SelectFromModel
from sklearn.ensemble import RandomForestClassifier
import pandas as pd
import numpy as np
data = pd.read_csv('data/house_prices_multivariate.csv')
# Your solution code here
def select_from_model(dataframe):
X = dataframe.iloc[:, :-1]
y... | normal | {
"blob_id": "d6791c8122129a46631582e7d9339ea08bd2e92b",
"index": 3183,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef select_from_model(dataframe):\n X = dataframe.iloc[:, :-1]\n y = dataframe.iloc[:, -1]\n np.random.seed(9)\n model = RandomForestClassifier()\n sfm = SelectFromMode... | [
0,
1,
2,
3,
4
] |
class Solution:
def commonFactors(self, a: int, b: int) ->int:
gcd = math.gcd(a, b)
return sum(a % i == 0 and b % i == 0 for i in range(1, gcd + 1))
| normal | {
"blob_id": "ea696329a0cfd558fb592ffaf6339a35e8950a3c",
"index": 6721,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def commonFactors(self, a: int, b: int) ->int:\n gcd = math.gcd(a, b)\n return sum(a % i == 0 and b % i == 0 for ... | [
0,
1,
2
] |
from django.contrib.auth.decorators import permission_required
from django.db import models
from students.models import Student
# Create your models here.
class Fine(models.Model):
amount = models.DecimalField(max_digits=8, decimal_places=2, null=True, default=0)
student = models.OneToOneField(Student, on_de... | normal | {
"blob_id": "22b697790516e1160ac501a58ad93ef5b579414a",
"index": 7109,
"step-1": "<mask token>\n\n\nclass Fine(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n db_table = 'fines'\n verbose_name_plural = 'Fines'\n verbose_name = 'Fi... | [
1,
2,
3,
4,
5
] |
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