code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
"""Command 'run' module."""
import click
from loguru import logger
from megalus.main import Megalus
@click.command()
@click.argument("command", nargs=1, required=True)
@click.pass_obj
def run(meg: Megalus, command: str) -> None:
"""Run selected script.
:param meg: Megalus instance
:param command: comma... | normal | {
"blob_id": "23a4ca8eec50e6ab72be3f1b1077c61f676b3cce",
"index": 5777,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@click.command()\n@click.argument('command', nargs=1, required=True)\n@click.pass_obj\ndef run(meg: Megalus, command: str) ->None:\n \"\"\"Run selected script.\n\n :param meg: M... | [
0,
1,
2,
3
] |
'''
PROBLEM N. 5:
2520 is the smallest number that can be divided by each of the numbers from 1 to 10 without any remainder.
What is the smallest positive number that is evenly divisible by all of the numbers from 1 to 20?
'''
'''
Greatest common divisior using the Euclidean Algorithm, vide http://en.wikipedia.org/wi... | normal | {
"blob_id": "0f0ded26e115b954a5ef698b03271ddf2b947334",
"index": 9998,
"step-1": "'''\nPROBLEM N. 5:\n2520 is the smallest number that can be divided by each of the numbers from 1 to 10 without any remainder.\n\nWhat is the smallest positive number that is evenly divisible by all of the numbers from 1 to 20?\n''... | [
0
] |
#给你一个字符串 croakOfFrogs，它表示不同青蛙发出的蛙鸣声（字符串 "croak" ）的组合。由于同一时间可以有多只青蛙呱呱作响，所以 croakOfFrogs 中会混合多个 “croak” 。请你返回模拟字符串中所有蛙鸣所需不同青蛙的最少数目。
#注意：要想发出蛙鸣 "croak"，青蛙必须 依序 输出 ‘c’, ’r’, ’o’, ’a’, ’k’ 这 5 个字母。如果没有输出全部五个字母，那么它就不会发出声音。
#如果字符串 croakOfFrogs 不是由若干有效的 "croak" 字符混合而成，请返回 -1 。
#来源：力扣（LeetCode）
#链接：https://leetcode-cn.com/pr... | normal | {
"blob_id": "b4491b5522e85fec64164b602045b9bd3e58c5b8",
"index": 4666,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def minNumberOfFrogs(self, croakOfFrogs: str) ->int:\n c, r, o, a, k = 0, 0, 0, 0, 0\n ans = 0\n for i in ... | [
0,
1,
2,
3
] |
import random
def generatePassword ():
numLowerCase = numUpperCase = numSpecialCase = numNumber = 0
password = ""
randomChars = "-|@.,?/!~#%^&*(){}[]\=*"
length = random.randint(10, 25)
while(numSpecialCase < 1 or numNumber < 1 or numLowerCase < 1 or numUpperCase < 1):
password = ""
... | normal | {
"blob_id": "3956d4cdb0a8654b6f107975ac003ce59ddd3de1",
"index": 4485,
"step-1": "<mask token>\n\n\ndef main():\n print(generatePassword())\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef generatePassword():\n numLowerCase = numUpperCase = numSpecialCase = numNumber = 0\n password = ''\n ran... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
def quick_sort(a):
_quick_sort(a, 0, len(a)-1)
return a
def _quick_sort(a, lo, hi):
if lo < hi:
j = partition2(a, lo, hi)
_quick_sort(a, lo, j-1)
_quick_sort(a, j+1, hi)
def partition(a, lo, hi):
# simply select first element as... | normal | {
"blob_id": "52513bf3f50726587bee800f118e2ac0fa00d98b",
"index": 4354,
"step-1": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\ndef quick_sort(a):\n _quick_sort(a, 0, len(a)-1)\n return a\n\n\ndef _quick_sort(a, lo, hi):\n\n if lo < hi:\n j = partition2(a, lo, hi)\n _quick_sort(a, lo, ... | [
0
] |
from django.shortcuts import render,redirect
from django.contrib.auth.decorators import login_required
from .form import UserForm, ProfileForm, PostForm
from django.contrib import messages
from .models import Profile, Projects
from django.contrib.auth.models import User
from django.http import HttpResponseRedirect
# ... | normal | {
"blob_id": "67de51e2a176907fd89793bd3ec52f898130e104",
"index": 3713,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@login_required(login_url='/accounts/login/')\ndef postpoject(request):\n if request.method == 'POST':\n postform = PostForm(request.POST, request.FILES)\n if postfor... | [
0,
3,
4,
5,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
def projectionArea(self, grid):
"""
:type grid: List[List[int]]
:rtype: int
"""
res = 0
for i in grid:
... | flexible | {
"blob_id": "62fc71e26ba3788513e5e52efc5f20453080837d",
"index": 8514,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def projectionArea(self, grid):\n \"\"\"\n :type grid: List[List[int]]\n :rtype: int\n \"\"\"\n ... | [
0,
1,
2
] |
def pattern4(n):
"""
n: length of the base of the triangle ie. the max number
of starts it will contain.
"""
for row in range(1, n+1):
for col in range(1, row+1):
print("*", end="")
print("")
if __name__ == '__main__':
n = int(input(("Enter height of the triangle: ")))
pattern4(n)
| normal | {
"blob_id": "d77036ed07231719358658a42dc14d20453bd792",
"index": 7563,
"step-1": "<mask token>\n",
"step-2": "def pattern4(n):\n \"\"\"\n\tn: length of the base of the triangle ie. the max number\n\t\tof starts it will contain.\n\t\"\"\"\n for row in range(1, n + 1):\n for col in range(1, row + 1)... | [
0,
1,
2,
3
] |
<|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 = [m... | flexible | {
"blob_id": "7040db119f8fd6da78499fc732e291280228ca10",
"index": 1852,
"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 = [migrations.sw... | [
0,
1,
2,
3,
4
] |
class Process:
def __init__(self, id, at, bt):
self.id = id
self.at = at
self.bt = bt
self.wt = 0
self.ct = 0
self.st = 0
self.tat = 0
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_toke... | flexible | {
"blob_id": "be58a2e0dcdbcb3a3df0da87be29ce7ebcee7fe9",
"index": 6185,
"step-1": "class Process:\n\n def __init__(self, id, at, bt):\n self.id = id\n self.at = at\n self.bt = bt\n self.wt = 0\n self.ct = 0\n self.st = 0\n self.tat = 0\n <mask token>\n <ma... | [
2,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print('Hello')
<|reserved_special_token_1|>
# ---------------------MODULE 1 notes--------------------
# .
# .
# .
# .
# .
# .
# .
# .
# .
# .
# save as (file).py first if not it will not work
print("Hello")
# control s to save
| flexible | {
"blob_id": "bb64da929ff2e1e04267518ec93a28bedb5a4de5",
"index": 7306,
"step-1": "<mask token>\n",
"step-2": "print('Hello')\n",
"step-3": "# ---------------------MODULE 1 notes--------------------\r\n# .\r\n# .\r\n# .\r\n# .\r\n# .\r\n# .\r\n# .\r\n# .\r\n# .\r\n# .\r\n\r\n# save as (file).py first if not i... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
"""
@File : densenet_block.py
@Time : 12/11/20 9:59 PM
@Author : Mingqiang Ning
@Email : ningmq_cv@foxmail.com
@Modify Time @Version @Description
------------ -------- -----------
12/11/20 9:59 PM 1.0 None
# @Software: PyCharm
"""
import torch
from torch... | normal | {
"blob_id": "c2ba18062b8555c77b329718ec1f2ae7f326c78e",
"index": 1988,
"step-1": "<mask token>\n\n\nclass DenseBlock(nn.Module):\n <mask token>\n\n def forward(self, x):\n out = self.denseblock(x)\n return out\n",
"step-2": "<mask token>\n\n\nclass BottleNeck(nn.Module):\n <mask token>\n... | [
2,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class ListNode:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class ListNode:
def __init__(self, listt, node, g, h):
self.node_list = []
for element in listt:
self.node_list.... | flexible | {
"blob_id": "2b796fb99e4607d310a533e8d9897100c4df087d",
"index": 2665,
"step-1": "<mask token>\n",
"step-2": "class ListNode:\n <mask token>\n <mask token>\n",
"step-3": "class ListNode:\n\n def __init__(self, listt, node, g, h):\n self.node_list = []\n for element in listt:\n ... | [
0,
1,
2,
3,
4
] |
# -*- coding:utf-8 -*-
'''
Created on 2018/2/23
@author : xxfore
'''
import time
import sys
import re
sys.dont_write_bytecode = True
class TimeUtils(object):
@staticmethod
def convert_timestamp_to_date(timestamp):
time_local = time.localtime(timestamp)
dt = time.strftime("%Y-%m-%d %H:%M:%S",t... | normal | {
"blob_id": "933f74e4fda0b30bdf70ff3f3dbde2383b10c694",
"index": 8773,
"step-1": "<mask token>\n\n\nclass TimeUtils(object):\n <mask token>\n\n\nclass StringUtils(object):\n\n @staticmethod\n def remove_emoji_from_string(text):\n co = re.compile(u'[𐀀-\\U0010ffff]')\n return co.sub(u'', te... | [
3,
4,
5,
6,
7
] |
for i in range(-10,0):
print(i,end=" ") | normal | {
"blob_id": "8d0fcf0bf5effec9aa04e7cd56b4b7098c6713cb",
"index": 70,
"step-1": "<mask token>\n",
"step-2": "for i in range(-10, 0):\n print(i, end=' ')\n",
"step-3": "for i in range(-10,0):\n print(i,end=\" \")",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
import sys
import json
import eventlet
import datetime
import flask
from flask import Flask
from flask import render_template
__version__ = 0.1
PORT = 8000
HOST = '0.0.0.0'
DEBUG = False
RELDR = False
app = Flask(__name__)
app.config['SECRET_KEY'] = 'secretkey'
@app.route('/login/')
def login():
return render_tem... | normal | {
"blob_id": "a945d7f673d009a59e597cd3c99a886094ea9e57",
"index": 2639,
"step-1": "<mask token>\n\n\n@app.route('/login/')\ndef login():\n return render_template('login.html', name=None)\n\n\n@app.route('/chat/')\ndef chat():\n return render_template('chat.html', name=None)\n\n\n@app.route('/messages/')\nde... | [
3,
4,
5,
6
] |
# -*- coding: utf-8 -*-
from __future__ import absolute_import, unicode_literals
import swapper
from haystack.constants import Indexable
from haystack.fields import CharField, DateTimeField
from haystack.indexes import SearchIndex
class BasePageIndex(SearchIndex):
text = CharField(document=True, use_template=True... | normal | {
"blob_id": "8e1eef3c5a9ca3ea504bbc269b48446527637626",
"index": 1323,
"step-1": "<mask token>\n\n\nclass PageIndex(BasePageIndex, Indexable):\n template = CharField(model_attr='template')\n template_title = CharField(model_attr='get_template_display')\n get_template_display = CharField(model_attr='get_... | [
2,
4,
5,
6,
7
] |
from sqlalchemy import create_engine, Column, Integer, Float, \
String, Text, DateTime, Boolean, ForeignKey
from sqlalchemy.orm import sessionmaker, relationship
from sqlalchemy.ext.declarative import declarative_base
from flask_sqlalchemy import SQLAlchemy
engine = create_engine('sqlite:///app/databases/fays-web-... | normal | {
"blob_id": "3d2b8730953e9c2801eebc23b6fb56a1b5a55e3c",
"index": 6156,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nengine = create_engine('sqlite:///app/databases/fays-web-dev.db',\n connect_args={'check_same_thread': False})\nSession = sessionmaker(bind=engine)\nsession = Session()\nBase = declara... | [
0,
1,
2,
3
] |
# Напишите программу, которая вводит с клавиатуры последовательность чисел и выводит её
# отсортированной в порядке возрастания.
def is_numb_val(val):
try:
x = float(val)
except ValueError:
return False
else:
return True
def main():
num_seq = input("Введите последовательность ... | normal | {
"blob_id": "4c8a873c816678532b029af409be13258757eae1",
"index": 7577,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n num_seq = input('Введите последовательность чисел через пробел: ').split()\n num_lst = [float(s) for s in num_seq if is_numb_val(s)]\n print(sorted(num_lst))\n\... | [
0,
1,
2,
3,
4
] |
# -*- coding: UTF-8 -*-
'''=================================================
@Project -> File ：AutoMailApp -> handle_yaml
@IDE ：PyCharm
@Author ：Mr. wang
@Date ：2019/11/15 0015 19:53
@Desc ：
=================================================='''
import yaml
from Common.dir_path import YAML_FILE_PATH
class Han... | normal | {
"blob_id": "08c309645a4ee59716bdd00556096be1c784331a",
"index": 2469,
"step-1": "<mask token>\n\n\nclass HandleYaml:\n \"\"\"\n 处理并封装yaml文件\n \"\"\"\n\n def __init__(self):\n with open(YAML_FILE_PATH, 'r') as fs:\n content = fs.read()\n self.ya = yaml.load(content, yaml.... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
mpl_logger.setLevel(logging.WARNING)
<|reserved_special_token_0|>
if __name__ == '__main__':
if 'experiments' in os.getcwd():
os.chdir('../..')
this_dir = dirname(abspath(__file__))
for dir_name in ('.cache', '... | flexible | {
"blob_id": "88d8d04dd7117daed0e976f3abc52c5d7bf18434",
"index": 9334,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmpl_logger.setLevel(logging.WARNING)\n<mask token>\nif __name__ == '__main__':\n if 'experiments' in os.getcwd():\n os.chdir('../..')\n this_dir = dirname(abspath(__file__))\... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
# BSD 3-Clause License
#
# Copyright (c) 2017
# All rights reserved.
# Copyright 2022 Huawei Technologies Co., Ltd
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source ... | normal | {
"blob_id": "ee489c2e313a96671db79398218f8604f7ae1bf3",
"index": 3569,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef collect_env():\n \"\"\"Collect the information of the running environments.\n\n Returns:\n dict: The environment information. The following fields are contained.\n\n ... | [
0,
1,
2,
3
] |
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 11 13:25:03 2020
@author: Dr. Michael Sigmond, Canadian Centre for Climate Modelling and Analysis
"""
import matplotlib.colors as col
import matplotlib.cm as cm
import numpy as np
def register_cccmacms(cmap='all'):
"""create my ... | normal | {
"blob_id": "31a5bf0b275238e651dcb93ce80446a49a4edcf4",
"index": 6561,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef register_cccmacms(cmap='all'):\n \"\"\"create my personal colormaps with discrete colors and register them.\n \n \n default is to register all of them. can also specif... | [
0,
1,
2,
3,
4
] |
#exceptions.py
#-*- coding:utf-8 -*-
#exceptions
try:
print u'try。。。'
r = 10/0
print 'result:',r
except ZeroDivisionError,e:
print 'except:',e
finally:
print 'finally...'
print 'END'
try:
print u'try。。。'
r = 10/int('1')
print 'result:',r
except ValueError,e:
print 'ValueError:',e
... | normal | {
"blob_id": "1568cf544a4fe7aec082ef1d7506b8484d19f198",
"index": 3776,
"step-1": "#exceptions.py \n#-*- coding:utf-8 -*-\n\n#exceptions\ntry:\n print u'try。。。'\n r = 10/0\n print 'result:',r\nexcept ZeroDivisionError,e:\n print 'except:',e\nfinally:\n print 'finally...'\nprint 'END'\n\ntry:\n p... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def testeum():
a = 10
print(id(a))
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def testeum():
a = 10
print(id(a))
def testedois():
a = 10
print(id(a))
<|reserved_special_token_1|>
# -*- coding: utf-8 -*-
def tes... | flexible | {
"blob_id": "a2e2528f560f6117d4ceeb9cd20d3f6f6b2a30a7",
"index": 213,
"step-1": "<mask token>\n",
"step-2": "def testeum():\n a = 10\n print(id(a))\n\n\n<mask token>\n",
"step-3": "def testeum():\n a = 10\n print(id(a))\n\n\ndef testedois():\n a = 10\n print(id(a))\n",
"step-4": "# -*- co... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def add_info(report):
if os.path.exists('/var/log/oem-config.log'):
report['OemConfigLog'] = '/var/log/oem-config.log',
<|reserved_special_token_1|>
import os.path
def add_info(report):
if os.path.exists('/v... | flexible | {
"blob_id": "74b1cdcb1aaf6cde7e8ce3eeb73cd82689719b00",
"index": 6404,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef add_info(report):\n if os.path.exists('/var/log/oem-config.log'):\n report['OemConfigLog'] = '/var/log/oem-config.log',\n",
"step-3": "import os.path\n\n\ndef add_info... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
df.head()
<|reserved_special_token_0|>
df.drop(labels=columns_to_remove, axis=1, inplace=True)
df.head()
df['bat_team'].unique()
<|reserved_special_token_0|>
df.head()
<|reserved_special_token_0|>
df.head()
<|reserved_special_toke... | flexible | {
"blob_id": "3b1b3cab1fa197f75812ca5b1f044909914212c0",
"index": 9050,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndf.head()\n<mask token>\ndf.drop(labels=columns_to_remove, axis=1, inplace=True)\ndf.head()\ndf['bat_team'].unique()\n<mask token>\ndf.head()\n<mask token>\ndf.head()\n<mask token>\ndf.he... | [
0,
1,
2,
3,
4
] |
import control.matlab as ctrl
import matplotlib.pylab as plt
def process_data(num11, den11, num21, den21):
w11 = ctrl.tf(num11, den11)
w21 = ctrl.tf(num21, den21)
print('результат w11={} w21={}'.format(w11, w21))
TimeLine = []
for i in range (1, 3000):
TimeLine.append(i/1000)
plt.figur... | normal | {
"blob_id": "c08e6cee61e9f32a9f067a9554c74bb2ddbd7cf3",
"index": 2288,
"step-1": "<mask token>\n\n\ndef process_data(num11, den11, num21, den21):\n w11 = ctrl.tf(num11, den11)\n w21 = ctrl.tf(num21, den21)\n print('результат w11={} w21={}'.format(w11, w21))\n TimeLine = []\n for i in range(1, 3000... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class StepName(Enum):
<|reserved_special_token_0|>
null = 'null'
unitTest = 'unitTest'
integrationTest = 'integrationTest'
changeLog = 'changeLog'
requirements = 'requirements'
docs = 'docs'
build = 'build'
githubRelease = 'githubRelease'
artifactPu... | flexible | {
"blob_id": "21e86e4719cda5c40f780aca6e56eb13c8c9b8e5",
"index": 988,
"step-1": "<mask token>\n\n\nclass StepName(Enum):\n <mask token>\n null = 'null'\n unitTest = 'unitTest'\n integrationTest = 'integrationTest'\n changeLog = 'changeLog'\n requirements = 'requirements'\n docs = 'docs'\n ... | [
15,
20,
21,
25,
27
] |
# Generated by Django 3.0.4 on 2020-07-20 00:05
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('users', '0004_auto_20200720_0154'),
]
operations = [
migrations.DeleteModel(
name='Report',
),
migrations.AlterF... | normal | {
"blob_id": "98bc6e0552991d7de1cc29a02242b25e7919ef82",
"index": 3764,
"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 = [('users', '00... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
env.Execute('cd vjunit && make -f makevjunit')
env.Execute('cd VJQA/src && make -f makexmlcheck')
Execute('rm -rf ovj_qa')
<|reserved_special_token_0|>
if not os.path.exists(path):
os.makedirs(path)
Execute('cp -r VJQA ovj_qa/... | flexible | {
"blob_id": "549d7368d49cf2f4d2c6e83e300f31db981b62bd",
"index": 6285,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nenv.Execute('cd vjunit && make -f makevjunit')\nenv.Execute('cd VJQA/src && make -f makexmlcheck')\nExecute('rm -rf ovj_qa')\n<mask token>\nif not os.path.exists(path):\n os.makedirs(p... | [
0,
1,
2,
3,
4
] |
# coding=utf-8
# Copyright 2016 Mystopia.
from __future__ import (absolute_import, division, generators, nested_scopes,
print_function, unicode_literals, with_statement)
from django.db.models.signals import m2m_changed, post_save
from django.dispatch import receiver
from dicpick.models import... | normal | {
"blob_id": "065a566b3e520c14f20d0d7d668ec58404d6e11b",
"index": 494,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@receiver(post_save, sender=TaskType)\ndef create_task_instances(sender, instance, **kwargs):\n \"\"\"Ensure that there is a task instance for each date in the range specified by th... | [
0,
1,
2,
3,
4
] |
def part_1() -> int:
start = 382345
end = 843167
total = 0
for number in range(start, end + 1):
if check_number(str(number)):
total += 1
return total
def check_number(problem_input: str) -> bool:
previous = 0
double = False
for current in range(1, len(problem_inpu... | normal | {
"blob_id": "c46495eebbe796253f56b7472d5548b41c5d0bc4",
"index": 2411,
"step-1": "def part_1() ->int:\n start = 382345\n end = 843167\n total = 0\n for number in range(start, end + 1):\n if check_number(str(number)):\n total += 1\n return total\n\n\n<mask token>\n\n\ndef check_nu... | [
3,
4,
5,
6,
7
] |
import numpy as n, pylab as p
from scipy import stats as st
a=st.norm(0,1)
b=st.norm(0.1,1)
domain=n.linspace(-4,4,10000)
avals=a.cdf(domain)
bvals=b.cdf(domain)
diffN=n.abs(avals-bvals).max()
a=st.norm(0,1)
b=st.norm(0,1.2)
domain=n.linspace(-4,4,10000)
avals=a.cdf(domain)
bvals=b.cdf(domain)
diffN2=n.abs(avals-bvals... | normal | {
"blob_id": "647258ee5f2f6f1cb8118bcf146b8959c65b70cd",
"index": 8045,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef weib(x, nn, a):\n return a / nn * (x / nn) ** (a - 1) * n.exp(-(x / nn) ** a)\n\n\n<mask token>\nprint('distancias de KS para os modelos matematicos:', diffN, diffN2, diffU,\n ... | [
0,
2,
3,
4,
5
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import sqlite3
# 连接到db文件
conn = sqlite3.connect('app.db')
# 创建一个Cursor:
cursor = conn.cursor()
# 查询所有表名：
cursor.execute("select name from sqlite_master where type = 'table' order by name")
print("Tables name:", cursor.fetchall())
# 查询表user的结构：
cursor.ex... | normal | {
"blob_id": "dd8f4b08b88d487b68e916e9f92c08c9c0bc39da",
"index": 2681,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncursor.execute(\n \"select name from sqlite_master where type = 'table' order by name\")\nprint('Tables name:', cursor.fetchall())\ncursor.execute('PRAGMA table_info(user)')\nprint('Ta... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def isCourseCode(corseCode):
try:
matchObj = re.match('[A-Z]?[A-Z]?[A-Z]?[A-Z]?\\d?\\d?\\d?\\d?([A-Z]?)',
str(corseCode))
if matchObj != None:
return True
except ValueError as err:
print('Your courseCode is not correct: ', err)
r... | flexible | {
"blob_id": "b3a07107ef64bb50f4768954cbb579d8e66bd003",
"index": 6612,
"step-1": "<mask token>\n\n\ndef isCourseCode(corseCode):\n try:\n matchObj = re.match('[A-Z]?[A-Z]?[A-Z]?[A-Z]?\\\\d?\\\\d?\\\\d?\\\\d?([A-Z]?)',\n str(corseCode))\n if matchObj != None:\n return True\n... | [
6,
13,
14,
18,
19
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.7 on 2018-01-26 05:04
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Discou... | normal | {
"blob_id": "957db647500433fd73723fdeb3933037ba0641b1",
"index": 1527,
"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
] |
from app import db, session, Node_Base, Column, relationship
from datetime import datetime
import models
import os
import json
| normal | {
"blob_id": "1711f74fae36ba761a7c0d84b95271b4e5043d27",
"index": 6312,
"step-1": "<mask token>\n",
"step-2": "from app import db, session, Node_Base, Column, relationship\nfrom datetime import datetime\nimport models\nimport os\nimport json\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids"... | [
0,
1
] |
<|reserved_special_token_0|>
class TestCOEClusters(base.TestCase):
<|reserved_special_token_0|>
def get_mock_url(self, service_type=
'container-infrastructure-management', base_url_append=None, append
=None, resource=None):
return super(TestCOEClusters, self).get_mock_url(service_type... | flexible | {
"blob_id": "2bf057621df3b860c8f677baf54673d2da8c2bd1",
"index": 5804,
"step-1": "<mask token>\n\n\nclass TestCOEClusters(base.TestCase):\n <mask token>\n\n def get_mock_url(self, service_type=\n 'container-infrastructure-management', base_url_append=None, append\n =None, resource=None):\n ... | [
3,
5,
6,
7,
8
] |
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. 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... | normal | {
"blob_id": "a491772258a52bdfc93083343d2a2e48a240340d",
"index": 490,
"step-1": "<mask token>\n\n\n@ClassFactory.register(ClassType.METRIC, alias='accuracy')\nclass Accuracy(MetricBase):\n <mask token>\n __metric_name__ = 'accuracy'\n\n def __init__(self, topk=(1, 5)):\n \"\"\"Init Accuracy metri... | [
12,
13,
14,
15,
16
] |
n=7
a=[]
for i in range(1,n+1):
print(i)
if(i<n):
print("+")
a.append(i)
print("= {}".format(sum(a)))
| normal | {
"blob_id": "de9b85c250dea15ff9201054957ebc38017a8c35",
"index": 5435,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(1, n + 1):\n print(i)\n if i < n:\n print('+')\n a.append(i)\nprint('= {}'.format(sum(a)))\n",
"step-3": "n = 7\na = []\nfor i in range(1, n + 1):\n pr... | [
0,
1,
2,
3
] |
#!/usr/bin/python3
# The uploader service listens for connections from localhost on port 3961.
# It expects a JSON object on a line by itself as the request. It responds
# with another JSON object on a line by itself, then closes the connection.
# Atropine CGI scripts can send requests to this service to tell it to:
#... | normal | {
"blob_id": "bd202e18cb98efc2b62ce4670fadcf70c35a33cb",
"index": 2529,
"step-1": "<mask token>\n\n\nclass UploaderThread(object):\n <mask token>\n\n def is_uploading_tourney(self, tourney):\n return tourney in self.uploading_tourneys\n <mask token>\n <mask token>\n\n def get_last_successful... | [
19,
21,
26,
31,
34
] |
# stopwatch.py - A simple stopwatch program.
import time
# Display the porgram's instructions
print(
""" \n\nInstructions\n
press Enter to begin.\n
Afterwards press Enter to "click" the stopwatch.\n
Press Ctrl-C to quit"""
)
input() # press Enter to begin
print("Started")
startTime = time.time()
lastTime = star... | normal | {
"blob_id": "cc87682d4ebb283e2d0ef7c09ad28ba708c904bd",
"index": 4407,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(\n \"\"\" \n\nInstructions\n\npress Enter to begin.\n\nAfterwards press Enter to \"click\" the stopwatch.\n\nPress Ctrl-C to quit\"\"\"\n )\ninput()\nprint('Started')\n<mask t... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def hurdleRace(k, height):
if k < max(height):
return max(height) - k
return 0
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def hurdleRace(k, height):
if k < max(height):
return max(height) - k
return 0
prin... | flexible | {
"blob_id": "c139cbc3e693d75ad196e10257ff3028aa835709",
"index": 428,
"step-1": "<mask token>\n",
"step-2": "def hurdleRace(k, height):\n if k < max(height):\n return max(height) - k\n return 0\n\n\n<mask token>\n",
"step-3": "def hurdleRace(k, height):\n if k < max(height):\n return m... | [
0,
1,
2,
3
] |
#!/usr/bin/env python3
from typing import ClassVar, List
print(1, 2)
# Annotated function (Issue #29)
def foo(x: int) -> int:
return x + 1
# Annotated variables #575
CONST: int = 42
class Class:
cls_var: ClassVar[str]
def m(self):
xs: List[int] = []
# True and False are keywords in Python ... | normal | {
"blob_id": "689c6c646311eba1faa93cc72bbe1ee4592e45bc",
"index": 8392,
"step-1": "<mask token>\n\n\ndef foo(x: int) ->int:\n return x + 1\n\n\n<mask token>\n\n\nclass Class:\n cls_var: ClassVar[str]\n\n def m(self):\n xs: List[int] = []\n\n\n<mask token>\n\n\ndef a():\n pass\n\n\n<mask token>\... | [
5,
7,
8,
10,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
matplotlib.use('Agg')
<|reserved_special_token_0|>
f.close()
<|reserved_special_token_0|>
train_model.load_weights(weights_file)
<|reserved_special_token_0|>
if data_format == 'channels_first':
X_test = np.transpose(X_test, (0... | flexible | {
"blob_id": "a3507019ca3310d7ad7eb2a0168dcdfe558643f6",
"index": 1615,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmatplotlib.use('Agg')\n<mask token>\nf.close()\n<mask token>\ntrain_model.load_weights(weights_file)\n<mask token>\nif data_format == 'channels_first':\n X_test = np.transpose(X_test, ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
loadPly('head.ply', mesh)
<|reserved_special_token_0|>
for v in mesh.getVertices():
verts.append((v.x, v.y, v.z))
for t in mesh.getTrianglesIndices():
faces.append((t.x, t.y, t.z))
for e in mesh.getLinesIndices():
edge... | flexible | {
"blob_id": "c02af2ecd980da4ceff133c13072ad7c6b724041",
"index": 5329,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nloadPly('head.ply', mesh)\n<mask token>\nfor v in mesh.getVertices():\n verts.append((v.x, v.y, v.z))\nfor t in mesh.getTrianglesIndices():\n faces.append((t.x, t.y, t.z))\nfor e in... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def get_trajectories(args, global_min, path='regularized_evolution',
methods=['RE', 'RS']):
all_trajectories = {}
for m in methods:
dfs = []
for seed in range(500):
filename = os.path.join(path, m, 'algo_{}_0_ssp_{}_seed_{}.obj'
.for... | flexible | {
"blob_id": "a757bbb9ad2f6f5bf04cdf4091b97841b8e40432",
"index": 6601,
"step-1": "<mask token>\n\n\ndef get_trajectories(args, global_min, path='regularized_evolution',\n methods=['RE', 'RS']):\n all_trajectories = {}\n for m in methods:\n dfs = []\n for seed in range(500):\n fi... | [
3,
4,
5,
6,
7
] |
<|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": "0cba18ca7126dda548a09f34dc26b83d6471bf68",
"index": 1652,
"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 = [('courses', '... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python2.7
# Google APIs
from oauth2client import client, crypt
CLIENT_ID = '788221055258-j59svg86sv121jdr7utnhc2rs9tkb9s4.apps.googleusercontent.com'
def fetchIdToken():
url = 'https://www.googleapis.com/oauth2/v3/tokeninfo?id_token='
f = urllib.urlopen(url + urllib.urlencode(CLIENT_ID))
i... | normal | {
"blob_id": "2251a6064998f25cca41b018a383053d73bd09eb",
"index": 2321,
"step-1": "<mask token>\n\n\ndef getIdInfo(token):\n try:\n idinfo = client.verify_id_token(token, CLIENT_ID)\n if idinfo['aud'] not in [CLIENT_ID]:\n return None\n if idinfo['iss'] not in ['accounts.google.... | [
1,
2,
3,
4,
5
] |
from flask import Flask
app = Flask(__name__)
@app.route('/')
def root():
return "Test!"
@app.route('/federal/geographic')
def federal_geographic():
pass
@app.route('/federal/issue')
def federal_issue():
pass
@app.route('/state/geographic')
def state_geographic():
pass
@app.route('/local/temporal'... | normal | {
"blob_id": "cc094f8aeff3b52bd9184f7b815320529ecb4550",
"index": 9928,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef root():\n return 'Test!'\n\n\n@app.route('/federal/geographic')\ndef federal_geographic():\n pass\n\n\n<mask token>\n\n\n@app.route('/state/geographic')\ndef state_geographic():\n pas... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main(input, output):
vocab = OrderedDict({'</s>': 0, '<unk>': 1})
for line in io.open(input, 'r', encoding='utf-8'):
word, count = line.strip().split()
vocab[word] = len(vocab)
with io.open(output... | flexible | {
"blob_id": "e3665141397d52877242463d548c059272d13536",
"index": 863,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main(input, output):\n vocab = OrderedDict({'</s>': 0, '<unk>': 1})\n for line in io.open(input, 'r', encoding='utf-8'):\n word, count = line.strip().split()\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class ToolBar(QWidget):
<|reserved_special_token_0|>
def __init__(self, parent):
super().__init__(parent)
self._main_wnd = parent
self.setAttribute(Qt.WA_StyledBackground, True)
self.setObjectName('options')
self.setStyleSheet(
... | flexible | {
"blob_id": "772e2e0a442c1b63330e9b526b76d767646b0c7c",
"index": 7819,
"step-1": "<mask token>\n\n\nclass ToolBar(QWidget):\n <mask token>\n\n def __init__(self, parent):\n super().__init__(parent)\n self._main_wnd = parent\n self.setAttribute(Qt.WA_StyledBackground, True)\n sel... | [
3,
5,
6,
9,
10
] |
# Copyright 2018 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import datetime
import json
import logging
import mock
from parameterized import parameterized
from buildbucket_proto import common_pb2
from buildbucket_pr... | normal | {
"blob_id": "325efe65030ad3488a7fc45c0d4a289eb0b17196",
"index": 1311,
"step-1": "<mask token>\n\n\nclass StepUtilTest(wf_testcase.WaterfallTestCase):\n\n def testGetLowerBoundBuildNumber(self):\n self.assertEqual(5, step_util._GetLowerBoundBuildNumber(5, 100))\n self.assertEqual(50, step_util._... | [
26,
32,
43,
49,
55
] |
import os
path = r'D:\python\风变编程\python基础-山顶班\fb_16'
path1 = 'test_01'
path2 = 'fb_csv-01-获取网页内容.py'
print(os.getcwd()) # 返回当前工作目录
print(os.listdir(path)) # 返回path指定的文件夹包含的文件或文件夹的名字的列表
#print(os.mkdir(path1)) # 创建文件夹
print(os.path.abspath(path)) # 返回绝对路径
print(os.path.basename(path)) # 返回文件名
print(os.path.isfi... | normal | {
"blob_id": "c01ea897cd64b3910531babe9fce8c61b750185d",
"index": 7912,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(os.getcwd())\nprint(os.listdir(path))\nprint(os.path.abspath(path))\nprint(os.path.basename(path))\nprint(os.path.isfile(path2))\nprint(os.path.isdir(path1))\n",
"step-3": "<mask ... | [
0,
1,
2,
3,
4
] |
import json
parsed = {}
with open('/Users/danluu/dev/dump/terra/filtered_events.json','r') as f:
# with open('/Users/danluu/dev/dump/terra/game-data/2017-05.json','r') as f:
# with open('/Users/danluu/dev/dump/terra/ratings.json','r') as f:
parsed = json.load(f)
# print(json.dumps(parsed, indent=2))
print(js... | normal | {
"blob_id": "886024a528112520948f1fb976aa7cb187a1da46",
"index": 6767,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('/Users/danluu/dev/dump/terra/filtered_events.json', 'r') as f:\n parsed = json.load(f)\nprint(json.dumps(parsed['4pLeague_S1_D1L1_G4']['events']['faction'], indent=2))\n",
... | [
0,
1,
2,
3,
4
] |
####
#Some more on variables
####
#Variables are easily redefined.
#Let's start simple.
x=2 #x is going to start at 2
print (x)
x=54 #we are redefining x to equal 54
print (x)
x= "Cheese" #x is now the string 'cheese'
print (x)
#Try running this program to see x
#printed at each point
#Clearly variables can be... | normal | {
"blob_id": "dae8529aa58f1451d5acdd6607543c202c3c0c66",
"index": 3810,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(x)\n<mask token>\nprint(x)\n<mask token>\nprint(x)\n",
"step-3": "x = 2\nprint(x)\nx = 54\nprint(x)\nx = 'Cheese'\nprint(x)\n",
"step-4": "####\n#Some more on variables\n####\n\... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('The ave_age of survivors is {}'.format(ave_survived_age))
print('The ave_age of victims is {}'.format(ave_non_survived_age))
<|reserved_special_token_1|>
survived_age = [48.0, 15.0, 40.0, 36.0, 47.0, 32.0, 60.0, 31.0, 17... | flexible | {
"blob_id": "85c51f155439ff0cb570faafc48ac8da094515bf",
"index": 3362,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('The ave_age of survivors is {}'.format(ave_survived_age))\nprint('The ave_age of victims is {}'.format(ave_non_survived_age))\n",
"step-3": "survived_age = [48.0, 15.0, 40.0, 36.... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
numpy.random.seed(1)
<|reserved_special_token_0|>
Y.observe(y)
<|reserved_special_token_0|>
C.initialize_from_random()
<|reserved_special_token_0|>
Q.set_callback(R.rotate)
Q.update(repeat=1000)
<|reserved_special_token_0|>
bpplt.... | flexible | {
"blob_id": "9af2b94c6eef47dad0348a5437593cc8561a7deb",
"index": 3593,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnumpy.random.seed(1)\n<mask token>\nY.observe(y)\n<mask token>\nC.initialize_from_random()\n<mask token>\nQ.set_callback(R.rotate)\nQ.update(repeat=1000)\n<mask token>\nbpplt.hinton(C)\n"... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
mydata.rename(columns=lambda x: x.strip(' '), inplace=True)
<|reserved_special_token_0|>
print(my_need_data.iloc[:, 0:3])
my_need_data.to_csv('result_csv.csv', index=0)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "ab760ec4cbb9f616f38b0f0f2221987460c6f618",
"index": 6492,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmydata.rename(columns=lambda x: x.strip(' '), inplace=True)\n<mask token>\nprint(my_need_data.iloc[:, 0:3])\nmy_need_data.to_csv('result_csv.csv', index=0)\n",
"step-3": "<mask token>\n... | [
0,
1,
2,
3,
4
] |
from ._sinAction import *
from ._sinActionFeedback import *
from ._sinActionGoal import *
from ._sinActionResult import *
from ._sinFeedback import *
from ._sinGoal import *
from ._sinResult import *
| normal | {
"blob_id": "c6b261a09b2982e17704f847586bbf38d27cb786",
"index": 353,
"step-1": "<mask token>\n",
"step-2": "from ._sinAction import *\nfrom ._sinActionFeedback import *\nfrom ._sinActionGoal import *\nfrom ._sinActionResult import *\nfrom ._sinFeedback import *\nfrom ._sinGoal import *\nfrom ._sinResult impor... | [
0,
1
] |
import os
from sklearn import metrics
import pandas as pd
import numpy as np
from submission import submission
import argparse
import glob
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... | normal | {
"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 python3
import sys
import collections as cl
def II(): return int(sys.stdin.readline())
def MI(): return map(int, sys.stdin.readline().split())
def LI(): return list(map(int, sys.stdin.readline().split()))
MOD = 998244353
def main():
N, K = MI()
kukan = []
for _ in range(K):
... | normal | {
"blob_id": "60b70171dededd758e00d6446842355a47b54cc0",
"index": 9700,
"step-1": "<mask token>\n\n\ndef II():\n return int(sys.stdin.readline())\n\n\ndef MI():\n return map(int, sys.stdin.readline().split())\n\n\ndef LI():\n return list(map(int, sys.stdin.readline().split()))\n\n\n<mask token>\n",
"st... | [
3,
5,
6,
7,
8
] |
#!/usr/bin/env python
# encoding: utf8
#from __future__ import unicode_literals
class RefObject(object):
def __init__(self,):
self.pose = []
self.name = []
self.time = None
self.id = None
def set_data(self,pose, name, time, Id):
self.pose = pose
self.... | normal | {
"blob_id": "7611a57705939ce456e34d5ae379d6ca748b13c3",
"index": 1884,
"step-1": "<mask token>\n\n\nclass Datafunction(object):\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\n ... | [
3,
11,
12,
16,
18
] |
<|reserved_special_token_0|>
class Visit(object):
<|reserved_special_token_0|>
def __init__(self, id_visit, id_stay_point, pivot_arrival_fix: GpsFix,
pivot_departure_fix: GpsFix, detection_arrival_fix: GpsFix,
detection_departure_fix: GpsFix):
"""
Builds a Visit object
... | flexible | {
"blob_id": "703ed320e7c06856a0798d9c0de9aafe24458767",
"index": 7937,
"step-1": "<mask token>\n\n\nclass Visit(object):\n <mask token>\n\n def __init__(self, id_visit, id_stay_point, pivot_arrival_fix: GpsFix,\n pivot_departure_fix: GpsFix, detection_arrival_fix: GpsFix,\n detection_departur... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Article(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_1|>
<|... | flexible | {
"blob_id": "28233cb4a56ee805e66f34e6abd49137503d5f7b",
"index": 1405,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Article(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Article(models.Model):\... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
from access.ssh.session import Client
from access.ssh.datachannel import DataChannel
| flexible | {
"blob_id": "967c8348352c805b926643617b88b03a62df2d16",
"index": 2271,
"step-1": "<mask token>\n",
"step-2": "from access.ssh.session import Client\nfrom access.ssh.datachannel import DataChannel\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
import sys
from pcaspy import SimpleServer, Driver
import time
from datetime import datetime
import thread
import subprocess
import argparse
#import socket
#import json
import pdb
class myDriver(Driver):
def __init__(self):
super(myDriver, self).__init__()
def printDb(prefix):
global pvdb
print... | normal | {
"blob_id": "03943e146c0d64cfe888073e3a7534b6615b023f",
"index": 6410,
"step-1": "import sys\n\nfrom pcaspy import SimpleServer, Driver\nimport time\nfrom datetime import datetime\nimport thread\nimport subprocess\nimport argparse\n#import socket\n#import json\nimport pdb\n\nclass myDriver(Driver):\n def __in... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for _ in range(u + v):
s, e = map(int, input().split())
warp[s] = e
<|reserved_special_token_0|>
q.append(1)
<|reserved_special_token_0|>
while q:
now = q.popleft()
for k in range(1, 7):
if now + k <= 100 a... | flexible | {
"blob_id": "dd792c502317288644d4bf5d247999bb08d5f401",
"index": 5369,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(u + v):\n s, e = map(int, input().split())\n warp[s] = e\n<mask token>\nq.append(1)\n<mask token>\nwhile q:\n now = q.popleft()\n for k in range(1, 7):\n ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class InheritUser(models.Model):
_inherit = 'res.users'
pos_sessions = fields.Many2many('pos.config', string=
'Point of Sale Accessible')
@api.multi
def write(self, vals):
if 'pos_sessions' in vals:
if vals['pos_sessions'][0][2]:
... | flexible | {
"blob_id": "2cff5fdfc86793592dd97de90ba9c3a11870b356",
"index": 8987,
"step-1": "<mask token>\n\n\nclass InheritUser(models.Model):\n _inherit = 'res.users'\n pos_sessions = fields.Many2many('pos.config', string=\n 'Point of Sale Accessible')\n\n @api.multi\n def write(self, vals):\n i... | [
4,
6,
7,
8,
10
] |
<|reserved_special_token_0|>
class GANSynthWrapper(GenerativeModel):
def __init__(self, ckpt_path, data_size, use_approx=True):
super(GANSynthWrapper, self).__init__(use_approx=use_approx)
self.latent_size = 256
self.data_size = data_size
self.data_dim = 1
self.expected_di... | flexible | {
"blob_id": "f13a2820fe1766354109d1163c7e6fe887cd6f34",
"index": 7051,
"step-1": "<mask token>\n\n\nclass GANSynthWrapper(GenerativeModel):\n\n def __init__(self, ckpt_path, data_size, use_approx=True):\n super(GANSynthWrapper, self).__init__(use_approx=use_approx)\n self.latent_size = 256\n ... | [
7,
8,
9,
10,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('loveMusic.csv', 'w', newline='') as csvFile:
fieldsName = ['nameFile', 'tittle', 'artist', 'gender', 'path']
writer = csv.DictWriter(csvFile, fieldnames=fieldsName)
writer.writeheader()
tittle = audiofil... | flexible | {
"blob_id": "629649abe9d855122a5db6d61a20735ceb89c5cf",
"index": 6426,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('loveMusic.csv', 'w', newline='') as csvFile:\n fieldsName = ['nameFile', 'tittle', 'artist', 'gender', 'path']\n writer = csv.DictWriter(csvFile, fieldnames=fieldsName)\n... | [
0,
1,
2,
3
] |
friends = ["Rolf", "Bob", "Anne"]
print(friends[0])
print(friends[1])
print(len(friends))
new_friends = [
["Rolf", 24],
["Bob", 30],
["Anne", 27],
["Charlie", 25],
["Jen", 25],
["Adam", 29]
]
print(friends[0][0])
friends.append("Jen")
print(friends)
new_friends.remove(["Anne", 27])
print(new... | normal | {
"blob_id": "355d60300cbbed817b4512e9b02cc4dd53d1293e",
"index": 2692,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(friends[0])\nprint(friends[1])\nprint(len(friends))\n<mask token>\nprint(friends[0][0])\nfriends.append('Jen')\nprint(friends)\nnew_friends.remove(['Anne', 27])\nprint(new_friends)\... | [
0,
1,
2,
3
] |
button6 = Button(tk,text=" ",font=('Times 26 bold'), heigh = 4, width = 8, command=lambda:checker(button6))
button6.grid(row=2, column=2,sticky = S+N+E+W)
button7 = Button(tk,text=" ",font=('Times 26 bold'), heigh = 4, width = 8, command=lambda:checker(button7))
button7.grid(row=3, column=0,sticky = S+N+E+W)
button8 = ... | normal | {
"blob_id": "e543c7f7f1b249e53b8ebf82641ec398abf557af",
"index": 477,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nbutton6.grid(row=2, column=2, sticky=S + N + E + W)\n<mask token>\nbutton7.grid(row=3, column=0, sticky=S + N + E + W)\n<mask token>\nbutton8.grid(row=3, column=1, sticky=S + N + E + W)\n<... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if len(argv) == 2 and (argv[1] == '--help' or argv[1] == '-h'):
print(__doc__)
exit(0)
<|reserved_special_token_0|>
if __name__ == '__main__':
window = MainWindow()
window.mainloop()
<|reserved_special_token_1|>
... | flexible | {
"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 logging
import ibmsecurity.utilities.tools
import os.path
logger = logging.getLogger(__name__)
def get(isamAppliance, check_mode=False, force=False):
"""
Get information on existing snapshots
"""
return isamAppliance.invoke_get("Retrieving snapshots", "/snapshots")
def get_latest(isamApplian... | normal | {
"blob_id": "23066cd644826bcfef1ef41f154924ac89e12069",
"index": 2081,
"step-1": "<mask token>\n\n\ndef get(isamAppliance, check_mode=False, force=False):\n \"\"\"\n Get information on existing snapshots\n \"\"\"\n return isamAppliance.invoke_get('Retrieving snapshots', '/snapshots')\n\n\n<mask token... | [
9,
12,
13,
14,
17
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def solution(prices):
answer = [0] * len(prices)
for i in range(len(prices) - 1):
for j in range(i + 1, len(prices)):
answer[i] += 1
if prices[i] > prices[j]:
break
return answer
<|reserved_special... | flexible | {
"blob_id": "23b6d754adf1616bc6ea1f8c74984fbd8dade6dd",
"index": 4238,
"step-1": "<mask token>\n",
"step-2": "def solution(prices):\n answer = [0] * len(prices)\n for i in range(len(prices) - 1):\n for j in range(i + 1, len(prices)):\n answer[i] += 1\n if prices[i] > prices[j... | [
0,
1,
2
] |
import xarray as xr
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import pickle
import seaborn as sns
%load_ext autoreload
%autoreload 2
%matplotlib
data_dir = Path('/Volumes/Lees_Extend/data/ecmwf_sowc/data/')
# READ in model (maybe want to do more predictions on historical data)
from src.m... | normal | {
"blob_id": "d265781c6b618752a1afcf65ac137052c26388a6",
"index": 985,
"step-1": "import xarray as xr\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pickle\nimport seaborn as sns\n\n%load_ext autoreload\n%autoreload 2\n%matplotlib\n\ndata_dir = Path('/Volumes/Lees_Extend/data/ec... | [
0
] |
# -*- coding: utf-8 -*-
import time
import re
from config import allowed_users, master_users, chat_groups
from bs4 import BeautifulSoup
import requests
import urllib.request, urllib.error, urllib.parse
import http.cookiejar
import json
import os
import sys
#from random import randint, choice
from random import uniform,... | normal | {
"blob_id": "98dd7446045f09e6d709f8e5e63b0a94341a796e",
"index": 3158,
"step-1": "<mask token>\n\n\ndef fetch_images_from_db(chat_id, keyword_id, keyword_n, db, shared_dict):\n search = False\n if str(chat_id) + str(keyword_id) + 'db' in shared_dict:\n print('%s for group %s already in progress, sle... | [
4,
5,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(list(myquery))
<|reserved_special_token_0|>
print(list(myquery))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
myclient = pymongo.MongoClient('mongodb://localhost:27017/')
mydb = myclient['divya_db']
mycol = m... | flexible | {
"blob_id": "d91bacfd4b45832a79189c0f1ec4f4cb3ef14851",
"index": 2210,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(list(myquery))\n<mask token>\nprint(list(myquery))\n",
"step-3": "<mask token>\nmyclient = pymongo.MongoClient('mongodb://localhost:27017/')\nmydb = myclient['divya_db']\nmycol = ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Product:
<|reserved_special_token_0|>
def __init__(self, cost: int) ->None:
self.__cost = cost
def get_yen(self) ->int:
return self.__cost
class ProductAdapter(ProductPrice):
"""Adapter"""
DOLL_RATE: int = 110
def __init__(self, product: ... | flexible | {
"blob_id": "829e23ce2388260467ed159aa7e1480d1a3d6045",
"index": 6546,
"step-1": "<mask token>\n\n\nclass Product:\n <mask token>\n\n def __init__(self, cost: int) ->None:\n self.__cost = cost\n\n def get_yen(self) ->int:\n return self.__cost\n\n\nclass ProductAdapter(ProductPrice):\n \... | [
7,
9,
12,
13,
14
] |
<|reserved_special_token_0|>
def base(request):
return render(request, 'VICHealth_app/base.html')
<|reserved_special_token_0|>
def check_activity_level(request):
return render(request, 'VICHealth_app/check_activity_level.html')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_spec... | flexible | {
"blob_id": "b0818b545ab47c27c705f2ccfa3b9edb741602f7",
"index": 4757,
"step-1": "<mask token>\n\n\ndef base(request):\n return render(request, 'VICHealth_app/base.html')\n\n\n<mask token>\n\n\ndef check_activity_level(request):\n return render(request, 'VICHealth_app/check_activity_level.html')\n\n\n<mask... | [
2,
3,
5,
6,
7
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Date : 2016-03-15 16:39:32
# @Author : Your Name (you@example.org)
# @Link : http://example.org
# @Version : $Id$
from PyQt5.QtWidgets import *
from PyQt5.QtCore import *
from PyQt5.QtGui import *
from widgets.favorits.favorit_win import Ui_DialogFavorit
import j... | normal | {
"blob_id": "14023785983f493af57189b3d96254efef2e33ae",
"index": 8180,
"step-1": "<mask token>\n\n\nclass Favorits(QDialog, Ui_DialogFavorit):\n <mask token>\n\n def __init__(self):\n super(Favorits, self).__init__()\n self.setupUi(self)\n self.buttonBox.button(QDialogButtonBox.Save).s... | [
4,
5,
7,
8,
9
] |
<|reserved_special_token_0|>
class ZhouyiSpider(scrapy.Spider):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def parse_detail(self, response):
item = response.meta['item']
item['hexagram1'] = response.xpath(
... | flexible | {
"blob_id": "cd9f25a2810b02f5588e4e9e8445e7aaec056bf8",
"index": 7704,
"step-1": "<mask token>\n\n\nclass ZhouyiSpider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def parse_detail(self, response):\n item = response.meta['item']\n item['hexagram1'] ... | [
2,
3,
4,
5,
6
] |
from sklearn.preprocessing import RobustScaler
from statsmodels.tsa.arima.model import ARIMA
from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_error
from math import sqrt
import tensorflow as tf
import pandas as pd
import numpy as np
import os
import random
# set random seed
random.seed(1)
np.ra... | normal | {
"blob_id": "d78ac5188cad104ee1b3e214898c41f843b6d8c0",
"index": 5185,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrandom.seed(1)\nnp.random.seed(1)\ntf.random.set_random_seed(1)\n<mask token>\nfor i in range(1, 6):\n df = pd.read_csv(random_sample_save_folder_path + \n 'power_demand_sample%... | [
0,
1,
2,
3,
4
] |
from face_recognition.model import Backbone
import torch
import numpy
class face_verifier():
def __init__(self, net_depth=50, drop_ratio=0.6, net_mode="ir_se", device="cuda"):
# create model
self.model = Backbone(net_depth, drop_ratio, net_mode).to(device)
save_path = "face_recognit... | normal | {
"blob_id": "0659df48bb150582917e333a7a25d2d25395dfda",
"index": 1381,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass face_verifier:\n <mask token>\n\n def verify_person(self, f1, f2):\n batch_tensor = torch.cat([f1, f2], 0)\n output_feat = self.model(batch_tensor.cuda())\n ... | [
0,
2,
3,
4,
5
] |
from const import BORN_KEY, PRESIDENT_KEY, CAPITAL_KEY, PRIME_KEY, MINISTER_KEY, POPULATION_KEY, \
GOVERNMENT_KEY,AREA_KEY, WHO_KEY, IS_KEY, THE_KEY, OF_KEY, WHAT_KEY, WHEN_KEY, WAS_KEY
from geq_queries import capital_of_country_query, area_of_country_query, government_of_country_query, \
population_of_country... | normal | {
"blob_id": "18dce1ce683b15201dbb5436cbd4288a0df99c28",
"index": 938,
"step-1": "<mask token>\n\n\ndef get_last_argument(words):\n return ' '.join(words)[:-1]\n\n\n<mask token>\n\n\ndef parse_what_is_the(words):\n question_number = None\n arg = None\n if words[3] == POPULATION_KEY:\n question_... | [
5,
6,
7,
8,
9
] |
#! /usr/bin/env python
import smtpsend
S = smtpsend.Smtpsent(SUBJECT='Test')
S.sendemail('''
this is a test!
''')
| normal | {
"blob_id": "7754974e79202b2df4ab9a7f69948483042a67cc",
"index": 855,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nS.sendemail(\"\"\"\nthis is a test!\n\"\"\")\n",
"step-3": "<mask token>\nS = smtpsend.Smtpsent(SUBJECT='Test')\nS.sendemail(\"\"\"\nthis is a test!\n\"\"\")\n",
"step-4": "import smtp... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
sys.stdin = open('sample_input.txt', 'r')
test_case = int(input())
<|reserved_special_token_0|>
<|reserved_special_token_1|>
import sys
from pprint import pprint
sys.stdin = open('sample_input.txt', 'r')
test_case = int(input()... | flexible | {
"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
] |
import os
from flask import (
Flask,
render_template,
request
)
# from flask_jwt_extended import JWTManager
from flask_login import LoginManager
from flask_migrate import Migrate
from flask_sqlalchemy import SQLAlchemy
from flask_wtf.csrf import CSRFError, CSRFProtect
from config import Config
from log_con... | normal | {
"blob_id": "9d142e8de5235d55cd99371c9884e8dc7a10c947",
"index": 8111,
"step-1": "<mask token>\n\n\n@app.errorhandler(404)\ndef not_found(error):\n logger.warning(f'page not found {error} - {request.url}')\n return render_template('error_pages/404.html'), 404\n\n\n@app.errorhandler(500)\ndef server_error(e... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
"""
Created on Fri Apr 12 16:38:15 2013
@author: a92549
Fixes lack of / between tzvp and tzvpfit
"""
import sys
def main(argv):
for com in argv:
with open(com, 'rb') as f:
txt = f.read()
if 'tzvp tzvpfit' in txt:
parts = txt.spl... | normal | {
"blob_id": "85974e48c7eafdf39379559820ed7f0bdc07fb7a",
"index": 3680,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main(argv):\n for com in argv:\n with open(com, 'rb') as f:\n txt = f.read()\n if 'tzvp tzvpfit' in txt:\n parts = txt.split('tzvp tzvpfit',... | [
0,
1,
2,
3,
4
] |
"""
Module for generic standard analysis plots.
"""
import numpy as np
import matplotlib.pyplot as plt
import cartopy as cart
import xarray as xr
import ecco_v4_py as ecco
def global_and_stereo_map(lat, lon, fld,
plot_type='pcolormesh',
cmap='YlOrRd',
... | normal | {
"blob_id": "b039ed74e62f3a74e8506d4e14a3422499046c06",
"index": 860,
"step-1": "<mask token>\n\n\ndef plot_depth_slice(x, depth, fld, stretch_depth=-500, plot_type=\n 'pcolormesh', cmap='YlOrRd', title=None, cmin=None, cmax=None, dpi=100,\n show_colorbar=True):\n \"\"\"2D plot of depth vs some other va... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
@torch.no_grad()
def validate(data, model):
model.evaluate()
out = model(data.x, data.train_index)
return model.loss(out[data.val_mask == 1], data.y[data.val_mask == 1])
@torch.no_grad()
def validate_fb(data, model, lsym):
model.evaluate()
out = model(data.x, data.tr... | flexible | {
"blob_id": "83c109bc5aab6739a3a32116fae4f0c011d6118e",
"index": 4136,
"step-1": "<mask token>\n\n\n@torch.no_grad()\ndef validate(data, model):\n model.evaluate()\n out = model(data.x, data.train_index)\n return model.loss(out[data.val_mask == 1], data.y[data.val_mask == 1])\n\n\n@torch.no_grad()\ndef ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if not webcam.isOpened():
print('Could not open webcam')
exit()
<|reserved_special_token_0|>
while webcam.isOpened():
status, frame = webcam.read()
sample_num = sample_num + 1
if not status:
break
c... | flexible | {
"blob_id": "856a27e953a6b4e1f81d02e00717a8f95a7dea5f",
"index": 7790,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif not webcam.isOpened():\n print('Could not open webcam')\n exit()\n<mask token>\nwhile webcam.isOpened():\n status, frame = webcam.read()\n sample_num = sample_num + 1\n ... | [
0,
1,
2,
3,
4
] |
import logging
import random
from pyage.core.address import Addressable
from pyage.core.agent.agent import AbstractAgent
from pyage.core.inject import Inject, InjectOptional
logger = logging.getLogger(__name__)
class AggregateAgent(Addressable, AbstractAgent):
@Inject("aggregated_agents:_AggregateAgent__agents")... | normal | {
"blob_id": "85903f0c6bd4c896379c1357a08ae3bfa19d5415",
"index": 7065,
"step-1": "<mask token>\n\n\nclass AggregateAgent(Addressable, AbstractAgent):\n\n @Inject('aggregated_agents:_AggregateAgent__agents')\n @InjectOptional('locator')\n def __init__(self, name=None):\n self.name = name\n ... | [
7,
10,
11,
13,
15
] |
from random import shuffle
"""all sorting algorithm implementation"""
class Sorts:
def quick_sort(self, elements):
"""quick sort implementation"""
if len(elements) < 2:
return elements
else:
shuffle(elements)
pivot = elements[0]
print("pivot ... | normal | {
"blob_id": "2044140fb2678f9507946007fdfb7edbaf11798e",
"index": 5683,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Sorts:\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Sorts:\n\n def quick_sort(self, elements):\n \"\"\"quick sort implementation\"\"\"\n if len(el... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class KayakHandler(webapp.RequestHandler):
<|reserved_special_token_0|>
class ClearTripHandler(webapp.RequestHandler):
def get(self):
file = open('result.xml', 'r')
content = file.read()
content = replace(content, '&', '&')
xml = XML2Dict()
... | flexible | {
"blob_id": "08568c31e5a404957c11eca9cbc9472c71cf088b",
"index": 9546,
"step-1": "<mask token>\n\n\nclass KayakHandler(webapp.RequestHandler):\n <mask token>\n\n\nclass ClearTripHandler(webapp.RequestHandler):\n\n def get(self):\n file = open('result.xml', 'r')\n content = file.read()\n ... | [
5,
8,
9,
11,
17
] |
'''
Created on Dec 23, 2011
@author: boatkrap
'''
import kombu
from kombu.common import maybe_declare
from . import queues
import logging
logger = logging.getLogger(__name__)
import threading
cc = threading.Condition()
class Publisher:
def __init__(self, exchange_name, channel, routing_key=None):
s... | normal | {
"blob_id": "8205541dcdd4627a535b14c6775f04b80e7c0d15",
"index": 3354,
"step-1": "<mask token>\n\n\nclass Publisher:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass TopicPublisher(Publisher):\n\n def __init__(self, exchange_name, channel, routing_key=None):... | [
7,
9,
12,
13,
15
] |
from django.urls import path
from .views import PollsList, SinglePollsView, PollsCreate, PollsAnswer
app_name = "authors"
# app_name will help us do a reverse look-up latter.
urlpatterns = [
path('polls/', PollsList.as_view()),
path('polls/create', PollsCreate.as_view()),
path('polls/<int:pk>', SinglePollsV... | normal | {
"blob_id": "64ac007faeebe0e71ba0060e74fa07154e6291e2",
"index": 6053,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_name = 'authors'\nurlpatterns = [path('polls/', PollsList.as_view()), path('polls/create',\n PollsCreate.as_view()), path('polls/<int:pk>', SinglePollsView.as_view(\n )), path('... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
@numba.jit(nopython=True)
def backtrack_steps():
"""
Compute the number of steps it takes a 1d random walker starting
at zero to get to +1.
"""
x = 0
n_steps = 0
while x < 1:
x += 2 * np.random.randint(0, 2) - 1
n_steps += 1
return n_steps
... | flexible | {
"blob_id": "00a2992af78f9edadd3f4cbc7d073c1f74fcd9a2",
"index": 2810,
"step-1": "<mask token>\n\n\n@numba.jit(nopython=True)\ndef backtrack_steps():\n \"\"\"\n Compute the number of steps it takes a 1d random walker starting\n at zero to get to +1.\n \"\"\"\n x = 0\n n_steps = 0\n while x <... | [
2,
3,
4,
5,
6
] |
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