Python网络爬虫与信息提取-Day14-（实例）股票数据定向爬虫

功能描述

目标：获取上交所和深交所所有股票的名称和交易信息

股票数据是进行量化交易的基础型数据，此爬虫也能为量化交易提供获得基础数据的方法

输出：保存到文件中

技术路线：requests‐bs4‐re

候选数据网站的选择

新浪股票：http://finance.sina.com.cn/stock/

百度股票：https://gupiao.baidu.com/stock/

选取原则：股票信息静态存在于HTML页面中，非js代码生成

没有Robots协议限制

选取方法：浏览器 F12，源代码查看等

选取心态：不要纠结于某个网站，多找信息源尝试

数据网站的确定

新浪股票在页面上看到的股票代码在源代码中并没有，说明很可能是由JavaScript脚本生成的；而百度股票的每一支个股的信息都写在HTML代码中

所以对于这两个网站来讲，百度股票更适合作为定向爬虫的数据来源

获取股票列表：

东方财富网：http://quote.eastmoney.com/stocklist.html

获取个股信息：

百度股票：https://gupiao.baidu.com/stock/

单个股票：https://gupiao.baidu.com/stock/sz002439.html

程序的结构设计

步骤1：从东方财富网获取股票列表

步骤2：根据股票列表逐个到百度股票获取个股信息

步骤3：将结果存储到文件

 


百度股票源代码中个股信息的组织形式

所以键值对，用字典类型

实例编写

为了调试方便，使用traceback库

import requests
from bs4 import BeautifulSoup
import traceback
import re

def getHTMLText(url):
try:
r = requests.get(url)
r.raise_for_status()
r.encoding = r.apparent_encoding
return r.text
except:
return ""

def getStockList(lst, stockURL):
html = getHTMLText(stockURL)
soup = BeautifulSoup(html, 'html.parser')
a = soup.find_all('a')
for i in a:
try:
href = i.attrs['href']
lst.append(re.findall(r"[s][hz]\d{6}", href)[0])
except:
continue

def getStockInfo(lst, stockURL, fpath):
for stock in lst:
url = stockURL + stock + ".html"
html = getHTMLText(url)
try:
if html=="":
continue
infoDict = {}
soup = BeautifulSoup(html, 'html.parser')
stockInfo = soup.find('div',attrs={'class':'stock-bets'})

name = stockInfo.find_all(attrs={'class':'bets-name'})[0]
infoDict.update({'股票名称': name.text.split()[0]})

keyList = stockInfo.find_all('dt')
valueList = stockInfo.find_all('dd')
for i in range(len(keyList)):
key = keyList[i].text
val = valueList[i].text
infoDict[key] = val

with open(fpath, 'a', encoding='utf-8') as f:
f.write( str(infoDict) + '\n' )
except:
traceback.print_exc()
continue

def main():
stock_list_url = 'http://quote.eastmoney.com/stocklist.html'
stock_info_url = 'https://gupiao.baidu.com/stock/'
output_file = 'D:/BaiduStockInfo.txt'
slist=[]
getStockList(slist, stock_list_url)
getStockInfo(slist, stock_info_url, output_file)

main()


实例优化

如何提高用户体验?

速度提高：编码识别的优化

r.apparent_encoding需要分析文本，运行较慢，可辅助人工分析

体验提高：增加动态进度显示

 

import requests
from bs4 import BeautifulSoup
import traceback
import re

def getHTMLText(url, code="utf-8"):
try:
r = requests.get(url)
r.raise_for_status()
r.encoding = code
return r.text
except:
return ""

def getStockList(lst, stockURL):
html = getHTMLText(stockURL, "GB2312")
soup = BeautifulSoup(html, 'html.parser')
a = soup.find_all('a')
for i in a:
try:
href = i.attrs['href']
lst.append(re.findall(r"[s][hz]\d{6}", href)[0])
except:
continue

def getStockInfo(lst, stockURL, fpath):
count = 0
for stock in lst:
url = stockURL + stock + ".html"
html = getHTMLText(url)
try:
if html=="":
continue
infoDict = {}
soup = BeautifulSoup(html, 'html.parser')
stockInfo = soup.find('div',attrs={'class':'stock-bets'})

name = stockInfo.find_all(attrs={'class':'bets-name'})[0]
infoDict.update({'股票名称': name.text.split()[0]})

keyList = stockInfo.find_all('dt')
valueList = stockInfo.find_all('dd')
for i in range(len(keyList)):
4000

key = keyList[i].text
val = valueList[i].text
infoDict[key] = val

with open(fpath, 'a', encoding='utf-8') as f:
f.write( str(infoDict) + '\n' )
count = count + 1
print("\r当前进度: {:.2f}%".format(count*100/len(lst)),end="")
except:
count = count + 1
print("\r当前进度: {:.2f}%".format(count*100/len(lst)),end="")
continue

def main():
stock_list_url = 'http://quote.eastmoney.com/stocklist.html'
stock_info_url = 'https://gupiao.baidu.com/stock/'
output_file = 'D:/BaiduStockInfo.txt'
slist=[]
getStockList(slist, stock_list_url)
getStockInfo(slist, stock_info_url, output_file)

main()

总结

采用requests‐bs4‐re路线实现了股票信息爬取和存储

实现了展示爬取进程的动态滚动条