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stock_reptile.py
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import re
import time
import random
import requests
import pandas
# 请求头信息
headers = {'Accept': '*/*', 'Accept-Encoding': 'gzip, deflate, br', 'Accept-Language': 'zh-CN,zh;q=0.9',
'Connection': 'keep-alive',
'Cookie': 'qgqp_b_id=19f66ef1368d6e2506b33a57d7d42102; websitepoptg_api_time=1693827592377; '
'st_si=15311446147433; websitepoptg_show_time=1693827592660; st_asi=delete; '
'st_pvi=64611557087756; st_sp=2023-09-04%2019%3A39%3A52; '
'st_inirUrl=https%3A%2F%2Fwww.baidu.com%2Flink; st_sn=3; '
'st_psi=20230904194014849-113200301321-2315029714',
'Host': '48.push2.eastmoney.com', 'Referer': 'https://quote.eastmoney.com/center/gridlist.html',
'Sec-Ch-Ua': '"Chromium";v="116", "Not)A;Brand";v="24", "Google Chrome";v="116"', 'Sec-Ch-Ua-Mobile': '?0',
'Sec-Ch-Ua-Platform': '"Windows"', 'Sec-Fetch-Dest': 'script', 'Sec-Fetch-Mode': 'no-cors',
'Sec-Fetch-Site': 'same-site',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) '
'Chrome/116.0.0.0 Safari/537.36'}
# 定义一个函数，用来获取股票数据
def get_stock_data(_url):
# 发送GET请求获取网页内容
res = requests.get(_url, headers=headers)
# 返回网页内容
return res.text
# 定义一个函数，用来解析股票数据
def parse_stock_data(data):
# 使用正则表达式提取股票数据
stock_code = re.findall('"f12":"(.*?)","f13"', data)
company_name = re.findall('"f14":"(.*?)","f15"', data)
latest_price = re.findall('f2":(.*?),"f3', data)
change_percent = re.findall('f3":(.*?),"f4', data)
change_amount = re.findall('"f4":(.*?),"f5"', data)
volume = re.findall('f5":(.*?),"f6', data)
turnover = re.findall('f6":(.*?),"f7', data)
amplitude = re.findall('f7":(.*?),"f8', data)
highest = re.findall('f15":(.*?),"f16', data)
lowest = re.findall('f16":(.*?),"f17', data)
open_price = re.findall('f17":(.*?),"f18', data)
previous_close = re.findall('f18":(.*?),"f20', data)
volume_ratio = re.findall('f10":(.*?),"f11', data)
turnover_rate = re.findall('f8":(.*?),"f9', data)
pe_ratio = re.findall('f9":(.*?),"f10', data)
pb_ratio = re.findall('f23":(.*?),"f24', data)
return stock_code, company_name, latest_price, change_percent, change_amount, volume, turnover, amplitude, \
highest, lowest, open_price, previous_close, volume_ratio, turnover_rate, pe_ratio, pb_ratio
# 定义一个函数，用来获取股票数据
def scrape_stock_info():
# 定义一个列表，用来存放所有股票数据
_all_list = []
# 定义一个初始化页码的变量
page = 1
# 定义一个循环，用来爬取所有股票数据
while page <= 2:
url = f'https://48.push2.eastmoney.com/api/qt/clist/get?cb=jQuery112408633284394296752_1693827639686&pn={page}&pz' \
f'=20&po=1&np=1&ut=bd1d9ddb04089700cf9c27f6f7426281&fltt=2&invt=2&wbp2u=|0|0|0|web&fid=f3&fs=m:0+t:6,' \
f'm:0+t:80,m:1+t:2,m:1+t:23,m:0+t:81+s:2048&fields=f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f12,f13,f14,f15,f16,f17,' \
f'f18,f20,f21,f23,f24,f25,f22,f11,f62,f128,f136,f115,f152&_=1693827639687 '
# 调用函数获取股票数据
data = get_stock_data(url)
# 调用函数解析股票数据
stock_code, company_name, latest_price, change_percent, change_amount, volume, turnover, amplitude, \
highest, lowest, open_price, previous_close, volume_ratio, turnover_rate, pe_ratio, pb_ratio = parse_stock_data(
data)
# 将股票数据添加到列表中
for i in range(len(stock_code)):
# 定义一个列表，用来存放每一条股票数据
mylist = [stock_code[i], company_name[i], latest_price[i], change_percent[i], change_amount[i], volume[i],
turnover[i], amplitude[i], highest[i], lowest[i], open_price[i], previous_close[i],
volume_ratio[i],
turnover_rate[i], pe_ratio[i], pb_ratio[i]]
# 将每一条股票数据添加到列表中
_all_list.append(mylist)
print('正在获取数据。。。')
page += 1
# 设置一个随机的休眠时间，防止被服务器拒绝访问
time.sleep(random.randint(1, 5))
# 返回所有股票数据
return _all_list
# 定义一个函数，用来将数据保存到excel表格中
def excel_data(_all_list):
# 创建一个表格对象
table_data = pandas.DataFrame(_all_list)
# 将表格数据保存到excel表格中
table_data.to_excel('股票信息.xlsx',
header=['股票代码', '企业名称', '最新价', '涨跌幅', '涨跌额', '成交量', '成交额', '振幅',
'最高',
'最低', '今开', '昨收', '量比', '换手率', '市盈率', '市净率'])
# 定义一个主函数
if __name__ == '__main__':
# 调用函数获取股票数据
all_list = scrape_stock_info()
# 调用函数将数据保存到excel表格中
excel_data(all_list)
print('数据获取完成！')