一、摘要

在人工智能时代，法律文书只是海量数据的一个产生源，但它所提供的数据具有数据量大、涉及面广、影响力大、时效性强等重要特点。因此，本文将爬取裁判文书网的若干法律文书，希望可以为喜欢网络爬虫的同学提供一点灵感。

二、运行环境

1.Pycharm
2.python 3.6
3.selenium
4.lxml

三、思路

（1）主页链接为http://wenshu.court.gov.cn/，一共有五种类型的法律文书，因此我们需要将五种类型事件对应的URL作为爬虫的种子URL
（2）由于裁判文书网不允许爬虫，因此我们需要使用一些反爬虫策略（建立代理IP池、改变user-agent）
（3）我们需要利用selenium模拟浏览器登陆，否则将无法获取数据，这点很重要！！！

四、实现代码

import requests
from lxml import etree
from selenium import webdriver
import time
import lxml.html
import random

#head = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.99 Safari/537.36"}
UA_LIST = [
   "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
   "Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
   "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
   "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",
   "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",
   "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
   "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
   "Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
   "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3",
   "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24",
   "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24"
]

headers = {
   'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',
   'Accept-Encoding': 'gzip, deflate',
   'Accept-Language': 'zh-CN,zh;q=0.9',
   'Connection': 'keep-alive',
   'Host': 'wenshu.court.gov.cn',
   'User-Agent': random.choice(UA_LIST)
}
def downloadHtml(url):
   try:
       r = requests.get(url, headers=headers)
       r.raise_for_status()
       r.encoding = r.apparent_encoding
       return r.text
   except:
       return ""

def parse():
   list = []
   url = "http://wenshu.court.gov.cn"
   response = downloadHtml(url)
   html = etree.HTML(response)
   urls = html.xpath("//*[@id='nav']/ul/li/a[@target='_blank']/@href")
   for ul0 in range(len(urls)):
       fullurl = url + urls[ul0]
       # 模拟谷歌浏览器
       driver = webdriver.Chrome('C:\chromedriver_win32\chromedriver.exe')
       driver.get(fullurl)
       time.sleep(20)
       html = driver.page_source
       doc = lxml.html.fromstring(html)
       url1 = doc.xpath("//*[@id='resultList']/div/table/tbody/tr[1]/td/div/a[2]/@href")
       list = list + url1
       driver.close()
   return list

def URL():
   urlList = []
   url = "http://wenshu.court.gov.cn"
   base = parse()
   for i in range(len(base)):
       new_url = url + base[i]
       urlList.append(new_url)
   return urlList

def download(url):
   driver = webdriver.Chrome('C:\chromedriver_win32\chromedriver.exe')
   driver.get(url)
   time.sleep(10)
   html = driver.page_source
   doc = lxml.html.fromstring(html)
   try:
       title = doc.xpath("//*[@id='contentTitle']/text()")
       content = doc.xpath("//*[@id='DivContent']/div/text()")
       for title_i, content_i in zip(title, content):
           content = {
               'title': title,
               'app_title': content
           }
           print(content)
   except:
       print("")

if __name__ == '__main__':
   urlss = URL()
   for i in range(len(urlss)):
       download(urlss[i])

五、运行结果

六、总结

这次学习的东西还是很多，selenium用的模块很多。爬取数据的时候使用了不同的方式，受益匪浅。