教你用python3根据关键词爬取百度百科的内容

站长资源 2024/11/25 佚名

2 0 1

前言

关于python版本，我一开始看很多资料说python2比较好，因为很多库还不支持3，但是使用到现在为止觉得还是pythin3比较好用，因为编码什么的问题，觉得2还是没有3方便。而且在网上找到的2中的一些资料稍微改一下也还是可以用。

好了，开始说爬百度百科的事。

这里设定的需求是爬取北京地区n个景点的全部信息，n个景点的名称是在文件中给出的。没有用到api，只是单纯的爬网页信息。

1、根据关键字获取url

由于只需要爬取信息，而且不涉及交互，可以使用简单的方法而不需要模拟浏览器。

可以直接

<strong>http://baike.baidu.com/search/word"guanjianci"</strong>

<strong>for </strong>l <strong>in </strong>view_names:
 <strong>'''http://baike.baidu.com/search/word"color: #ff0000">2、下载url
用urllib库轻松实现，见下面的代码中def download(self,url) 
3、利用Beautifulsoup获取html 
4、数据分析
百科中的内容是并列的段，所以在爬的时候不能自然的按段逻辑存储（因为全都是并列的）。所以必须用正则的方法。
基本的想法就是把整个html文件看做是str,然后用正则的方法截取想要的内容，在重新把这段内容转换成beautifulsoup对象，然后在进一步处理。
可能要花些时间看一下正则。
代码中还有很多细节，忘了再查吧只能，下次绝对应该边做编写文档，或者做完马上写。。。
贴代码！


# coding:utf-8
'''
 function：爬取百度百科所有北京景点，
 author:yi
'''
import urllib.request
from urllib.request import urlopen
from urllib.error import HTTPError
import urllib.parse
from bs4 import BeautifulSoup
import re
import codecs
import json
 
class BaikeCraw(object):
 def __init__(self):
  self.urls =set()
  self.view_datas= {}
 
 def craw(self,filename):
  urls = self.getUrls(filename)
  if urls == None:
   print("not found")
  else:
   for urll in urls:
    print(urll)
    try:
     html_count=self.download(urll)
     self.passer(urll, html_count)
    except:
     print("view do not exist")
    '''file=self.view_datas["view_name"]
    self.craw_pic(urll,file,html_count)
     print(file)'''
 
 
 def getUrls (self, filename):
  new_urls = set()
  file_object = codecs.open(filename, encoding='utf-16', )
  try:
   all_text = file_object.read()
  except:
   print("文件打开异常！")
   file_object.close()
  file_object.close()
  view_names=all_text.split(" ")
  for l in view_names:
   if '"main-content").find('h1') is not None:
   self.view_datas["view_name"]=soup.find('div',class_="main-content").find('h1').get_text()#景点名
   print(self.view_datas["view_name"])
  else:
   self.view_datas["view_name"] = soup.find("div", class_="feature_poster").find("h1").get_text()
  self.view_datas["view_message"] = soup.find('div', class_="lemma-summary").get_text()#简介
  self.view_datas["basic_message"]=soup.find('div', class_="basic-info cmn-clearfix").get_text() #基本信息
  self.view_datas["basic_message"]=self.view_datas["basic_message"].split("\n")
  get=[]
  for line in self.view_datas["basic_message"]:
   if line != "":
   get.append(line)
  self.view_datas["basic_message"]=get
  i=1
  get2=[]
  tmp="%%"
  for line in self.view_datas["basic_message"]:
 
   if i % 2 == 1:
    tmp=line
   else:
    a=tmp+":"+line
    get2.append(a)
   i=i+1
  self.view_datas["basic_message"] = get2
  self.view_datas["catalog"] = soup.find('div', class_="lemma-catalog").get_text().split("\n")#目录整体
  get = []
  for line in self.view_datas["catalog"]:
   if line != "":
    get.append(line)
  self.view_datas["catalog"] = get
  #########################百科内容
  view_name=self.view_datas["view_name"]
  html = urllib.request.urlopen(url)
  soup2 = BeautifulSoup(html.read(), 'html.parser').decode('utf-8')
  p = re.compile(r'', re.DOTALL) # 尾
  r = p.search(content_data_node)
  content_data = content_data_node[0:r.span(0)[0]]
  lists = content_data.split('')
  i = 1
  for list in lists:#每一大块
   final_soup = BeautifulSoup(list, "html.parser")
   name_list = None
   try:
    part_name = final_soup.find('h2', class_="title-text").get_text().replace(view_name, '').strip()
    part_data = final_soup.get_text().replace(view_name, '').replace(part_name, '').replace('编辑', '') # 历史沿革
    name_list = final_soup.findAll('h3', class_="title-text")
    all_name_list = {}
    na="part_name"+str(i)
    all_name_list[na] = part_name
    final_name_list = []###########
    for nlist in name_list:
     nlist = nlist.get_text().replace(view_name, '').strip()
     final_name_list.append(nlist)
    fin="final_name_list"+str(i)
    all_name_list[fin] = final_name_list
    print(all_name_list)
    i=i+1
    #正文
    try:
     p = re.compile(r'', re.DOTALL)
     final_soup = final_soup.decode('utf-8')
     r = p.search(final_soup)
     final_part_data = final_soup[r.span(0)[0]:]
     part_lists = final_part_data.split('')
     for part_list in part_lists:
      final_part_soup = BeautifulSoup(part_list, "html.parser")
      content_lists = final_part_soup.findAll("div", class_="para")
      for content_list in content_lists: # 每个最小段
       try:
        pic_word = content_list.find("div",
                class_="lemma-picture text-pic layout-right").get_text() # 去掉文字中的图片描述
        try:
         pic_word2 = content_list.find("div", class_="description").get_text() # 去掉文字中的图片描述
         content_list = content_list.get_text().replace(pic_word, '').replace(pic_word2, '')
        except:
         content_list = content_list.get_text().replace(pic_word, '')
 
       except:
        try:
         pic_word2 = content_list.find("div", class_="description").get_text() # 去掉文字中的图片描述
         content_list = content_list.get_text().replace(pic_word2, '')
        except:
         content_list = content_list.get_text()
       r_part = re.compile(r'\[\d.\]|\[\d\]')
       part_result, number = re.subn(r_part, "", content_list)
       part_result = "".join(part_result.split())
       #print(part_result)
    except:
     final_part_soup = BeautifulSoup(list, "html.parser")
     content_lists = final_part_soup.findAll("div", class_="para")
     for content_list in content_lists:
      try:
       pic_word = content_list.find("div", class_="lemma-picture text-pic layout-right").get_text() # 去掉文字中的图片描述
       try:
        pic_word2 = content_list.find("div", class_="description").get_text() # 去掉文字中的图片描述
        content_list = content_list.get_text().replace(pic_word, '').replace(pic_word2, '')
       except:
        content_list = content_list.get_text().replace(pic_word, '')
 
      except:
       try:
        pic_word2 = content_list.find("div", class_="description").get_text() # 去掉文字中的图片描述
        content_list = content_list.get_text().replace(pic_word2, '')
       except:
        content_list = content_list.get_text()
      r_part = re.compile(r'\[\d.\]|\[\d\]')
      part_result, number = re.subn(r_part, "", content_list)
      part_result = "".join(part_result.split())
      #print(part_result)
 
   except:
    print("error")
  return
 
 def output(self,filename):
  json_data = json.dumps(self.view_datas, ensure_ascii=False, indent=2)
  fout = codecs.open(filename+'.json', 'a', encoding='utf-16', )
  fout.write( json_data)
  # print(json_data)
  return
 
 def craw_pic(self,url,filename,html_count):
  soup = BeautifulSoup(html_count, 'html.parser', from_encoding='utf_8')
  node_pic=soup.find('div',class_='banner').find("a", href=re.compile("/photo/poi/....\."))
  if node_pic is None:
   return None
  else:
   part_url_pic=node_pic['href']
   full_url_pic=urllib.parse.urljoin(url,part_url_pic)
   #print(full_url_pic)
  try:
   html_pic = urlopen(full_url_pic)
  except HTTPError as e:
   return None
  soup_pic=BeautifulSoup(html_pic.read())
  pic_node=soup_pic.find('div',class_="album-list")
  print(pic_node)
  return
 
if __name__ =="__main__" :
 spider=BaikeCraw()
 filename="D:\PyCharm\\view_spider\\view_points_part.txt"
 spider.craw(filename)


总结
用python3根据关键词爬取百度百科的内容到这就基本结束了，希望这篇文章能对大家学习python有所帮助。