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
http://baike.baidu.com/search/word?word=\"guanjianci\"
for l in view_names: \'\'\'http://baike.baidu.com/search/word?word=\'\'\' # 得到url的方法 name=urllib.parse.quote(l) name.encode(\'utf-8\') url=\'http://baike.baidu.com/search/word?word=\'+name
这里要注意关键词是中午所以要注意编码问题,由于url中不能出现空格,所以需要用quote函数处理一下。
关于quote():
在 Python2.x 中的用法是:urllib.quote(text) 。Python3.x 中是urllib.parse.quote(text) 。按照标准,URL只允许一部分ASCII 字符(数字字母和部分符号),其他的字符(如汉字)是不符合URL标准的。所以URL中使用其他字符就需要进行URL编码。URL中传参数的部分(query String),格式是:name1=value1&name2=value2&name3=value3。假如你的name或者value值中的『&』或者『=』等符号,就当然会有问题。所以URL中的参数字符串也需要把『&=』等符号进行编码。URL编码的方式是把需要编码的字符转化为%xx的形式。通常URL编码是基于UTF-8的(当然这和浏览器平台有关)
例子:
比如『我,unicode 为 0x6211,UTF-8编码为0xE60x880x91,URL编码就是 %E6%88%91。
Python的urllib库中提供了quote和quote_plus两种方法。这两种方法的编码范围不同。不过不用深究,这里用quote就够了。
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 \'?\' in l:
view_names.remove(l)
for l in view_names:
\'\'\'http://baike.baidu.com/search/word?word=\'\'\' # 得到url的方法
name=urllib.parse.quote(l)
name.encode(\'utf-8\')
url=\'http://baike.baidu.com/search/word?word=\'+name
new_urls.add(url)
print(new_urls)
return new_urls
def manger(self):
pass
def passer(self,urll,html_count):
soup = BeautifulSoup(html_count, \'html.parser\', from_encoding=\'utf_8\')
self._get_new_data(urll, soup)
return
def download(self,url):
if url is None:
return None
response = urllib.request.urlopen(url)
if response.getcode() != 200:
return None
return response.read()
def _get_new_data(self, url, soup): ##得到数据
if soup.find(\'div\',class_=\"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。