211 lines
7.2 KiB
Python
211 lines
7.2 KiB
Python
# -*- coding:utf-8 -*-
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"""
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电影票房
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Created on 2015/12/24
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@author: Jimmy Liu
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@group : waditu
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@contact: jimmysoa@sina.cn
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"""
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import pandas as pd
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from tushare.stock import cons as ct
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from tushare.util import dateu as du
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try:
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from urllib.request import urlopen, Request
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except ImportError:
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from urllib2 import urlopen, Request
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import time
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import json
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def realtime_boxoffice(retry_count=3,pause=0.001):
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"""
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获取实时电影票房数据
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数据来源：EBOT艺恩票房智库
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Parameters
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------
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retry_count : int, 默认 3
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如遇网络等问题重复执行的次数
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pause : int, 默认 0
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重复请求数据过程中暂停的秒数，防止请求间隔时间太短出现的问题
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return
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-------
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DataFrame
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BoxOffice 实时票房（万）
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Irank 排名
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MovieName 影片名
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boxPer 票房占比 （%）
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movieDay 上映天数
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sumBoxOffice 累计票房（万）
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time 数据获取时间
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"""
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for _ in range(retry_count):
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time.sleep(pause)
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try:
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request = Request(ct.MOVIE_BOX%(ct.P_TYPE['http'], ct.DOMAINS['mbox'],
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ct.BOX, _random()))
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lines = urlopen(request, timeout = 10).read()
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if len(lines) < 15: #no data
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return None
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except Exception as e:
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print(e)
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else:
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js = json.loads(lines.decode('utf-8') if ct.PY3 else lines)
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df = pd.DataFrame(js['data2'])
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df = df.drop(['MovieImg','mId'], axis=1)
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df['time'] = du.get_now()
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return df
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def day_boxoffice(date=None, retry_count=3, pause=0.001):
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"""
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获取单日电影票房数据
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数据来源：EBOT艺恩票房智库
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Parameters
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------
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date:日期，默认为上一日
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retry_count : int, 默认 3
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如遇网络等问题重复执行的次数
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pause : int, 默认 0
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重复请求数据过程中暂停的秒数，防止请求间隔时间太短出现的问题
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return
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-------
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DataFrame
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AvgPrice 平均票价
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AvpPeoPle 场均人次
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BoxOffice 单日票房（万）
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BoxOffice_Up 环比变化 （%）
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IRank 排名
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MovieDay 上映天数
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MovieName 影片名
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SumBoxOffice 累计票房（万）
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WomIndex 口碑指数
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"""
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for _ in range(retry_count):
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time.sleep(pause)
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try:
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if date is None:
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date = 0
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else:
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date = int(du.diff_day(du.today(), date)) + 1
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request = Request(ct.BOXOFFICE_DAY%(ct.P_TYPE['http'], ct.DOMAINS['mbox'],
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ct.BOX, date, _random()))
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lines = urlopen(request, timeout = 10).read()
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if len(lines) < 15: #no data
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return None
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except Exception as e:
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print(e)
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else:
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js = json.loads(lines.decode('utf-8') if ct.PY3 else lines)
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df = pd.DataFrame(js['data1'])
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df = df.drop(['MovieImg', 'BoxOffice1', 'MovieID', 'Director', 'IRank_pro'], axis=1)
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return df
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def month_boxoffice(date=None, retry_count=3, pause=0.001):
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"""
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获取单月电影票房数据
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数据来源：EBOT艺恩票房智库
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Parameters
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------
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date:日期，默认为上一月，格式YYYY-MM
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retry_count : int, 默认 3
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如遇网络等问题重复执行的次数
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pause : int, 默认 0
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重复请求数据过程中暂停的秒数，防止请求间隔时间太短出现的问题
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return
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-------
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DataFrame
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Irank 排名
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MovieName 电影名称
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WomIndex 口碑指数
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avgboxoffice 平均票价
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avgshowcount 场均人次
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box_pro 月度占比
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boxoffice 单月票房(万)
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days 月内天数
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releaseTime 上映日期
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"""
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if date is None:
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date = du.day_last_week(-30)[0:7]
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elif len(date)>8:
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print(ct.BOX_INPUT_ERR_MSG)
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return
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date += '-01'
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for _ in range(retry_count):
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time.sleep(pause)
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try:
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request = Request(ct.BOXOFFICE_MONTH%(ct.P_TYPE['http'], ct.DOMAINS['mbox'],
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ct.BOX, date))
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lines = urlopen(request, timeout = 10).read()
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if len(lines) < 15: #no data
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return None
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except Exception as e:
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print(e)
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else:
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js = json.loads(lines.decode('utf-8') if ct.PY3 else lines)
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df = pd.DataFrame(js['data1'])
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df = df.drop(['defaultImage', 'EnMovieID'], axis=1)
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return df
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def day_cinema(date=None, retry_count=3, pause=0.001):
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"""
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获取影院单日票房排行数据
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数据来源：EBOT艺恩票房智库
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Parameters
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------
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date:日期，默认为上一日
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retry_count : int, 默认 3
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如遇网络等问题重复执行的次数
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pause : int, 默认 0
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重复请求数据过程中暂停的秒数，防止请求间隔时间太短出现的问题
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return
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-------
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DataFrame
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Attendance 上座率
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AvgPeople 场均人次
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CinemaName 影院名称
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RowNum 排名
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TodayAudienceCount 当日观众人数
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TodayBox 当日票房
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TodayShowCount 当日场次
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price 场均票价（元）
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"""
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if date is None:
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date = du.day_last_week(-1)
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data = pd.DataFrame()
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ct._write_head()
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for x in range(1, 11):
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df = _day_cinema(date, x, retry_count,
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pause)
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if df is not None:
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data = pd.concat([data, df])
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data = data.drop_duplicates()
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return data.reset_index(drop=True)
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def _day_cinema(date=None, pNo=1, retry_count=3, pause=0.001):
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ct._write_console()
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for _ in range(retry_count):
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time.sleep(pause)
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try:
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request = Request(ct.BOXOFFICE_CBD%(ct.P_TYPE['http'], ct.DOMAINS['mbox'],
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ct.BOX, pNo, date))
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lines = urlopen(request, timeout = 10).read()
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if len(lines) < 15: #no data
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return None
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except Exception as e:
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print(e)
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else:
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js = json.loads(lines.decode('utf-8') if ct.PY3 else lines)
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df = pd.DataFrame(js['data1'])
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df = df.drop(['CinemaID'], axis=1)
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return df
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def _random(n=13):
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from random import randint
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start = 10**(n-1)
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end = (10**n)-1
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return str(randint(start, end))
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