Python爬虫：一些常用的爬虫技巧总结(IP,cookie,header,多线程)

野性酷女 2022-07-24 07:15 196阅读 0赞

http://python.jobbole.com/84622/

用python也差不多一年多了，python应用最多的场景还是web快速开发、爬虫、自动化运维：写过简单网站、写过自动发帖脚本、写过收发邮件脚本、写过简单验证码识别脚本。

爬虫在开发过程中也有很多复用的过程，这里总结一下，以后也能省些事情。

# 1、基本抓取网页 #

## get方法 ##

Python

import urllib2 url "http://www.baidu.com" respons = urllib2.urlopen(url) print response.read()

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    <div style=""> 
     <div> 
      <span>import</span> 
      <span> </span> 
      <span>urllib2</span> 
     </div> 
     <div> 
      <span>url</span> 
      <span>&nbsp;&nbsp;</span> 
      <span>"http://www.baidu.com"</span> 
     </div> 
     <div> 
      <span>respons</span> 
      <span> </span> 
      <span>=</span> 
      <span> </span> 
      <span>urllib2</span> 
      <span>.</span> 
      <span>urlopen</span> 
      <span>(</span> 
      <span>url</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>print</span> 
      <span> </span> 
      <span>response</span> 
      <span>.</span> 
      <span>read</span> 
      <span>(</span> 
      <span>)</span> 
     </div> 
    </div> </td> 
  </tr> 
 </tbody> 
</table>

## post方法 ##

import urllib import urllib2 url = "http://abcde.com" form = \{'name':'abc','password':'1234'\} form\_data = urllib.urlencode(form) request = urllib2.Request(url,form\_data) response = urllib2.urlopen(request) print response.read()

# 2、使用代理IP #

在开发爬虫过程中经常会遇到IP被封掉的情况，这时就需要用到代理IP；

在urllib2包中有ProxyHandler类，通过此类可以设置代理访问网页，如下代码片段：

import urllib2 proxy = urllib2.ProxyHandler(\{'http': '127.0.0.1:8087'\}) opener = urllib2.build\_opener(proxy) urllib2.install\_opener(opener) response = urllib2.urlopen('http://www.baidu.com') print response.read()

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    <div style=""> 
     <div> 
      <span>import</span>&nbsp; 
      <span>urllib2</span> 
     </div> 
     <div>
       &nbsp; 
     </div> 
     <div> 
      <span>proxy</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>urllib2</span> 
      <span>.</span> 
      <span>ProxyHandler</span> 
      <span>(</span> 
      <span>{ </span> 
      <span>'http'</span> 
      <span>:</span>&nbsp; 
      <span>'127.0.0.1:8087'</span> 
      <span>}</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>opener</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>urllib2</span> 
      <span>.</span> 
      <span>build_opener</span> 
      <span>(</span> 
      <span>proxy</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>urllib2</span> 
      <span>.</span> 
      <span>install_opener</span> 
      <span>(</span> 
      <span>opener</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>response</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>urllib2</span> 
      <span>.</span> 
      <span>urlopen</span> 
      <span>(</span> 
      <span>'http://www.baidu.com'</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>print</span>&nbsp; 
      <span>response</span> 
      <span>.</span> 
      <span>read</span> 
      <span>(</span> 
      <span>)</span> 
     </div> 
    </div> </td> 
  </tr> 
 </tbody> 
</table>

# 3、Cookies处理 #

cookies是某些网站为了辨别用户身份、进行session跟踪而储存在用户本地终端上的数据(通常经过加密)，python提供了cookielib模块用于处理cookies，cookielib模块的主要作用是提供可存储cookie的对象，以便于与urllib2模块配合使用来访问Internet资源.

代码片段：

import urllib2, cookielib cookie\_support= urllib2.HTTPCookieProcessor(cookielib.CookieJar()) opener = urllib2.build\_opener(cookie\_support) urllib2.install\_opener(opener) content = urllib2.urlopen('http://XXXX').read()

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      <span>import</span>&nbsp; 
      <span>urllib2</span> 
      <span>,</span>&nbsp; 
      <span>cookielib</span> 
     </div> 
     <div>
       &nbsp; 
     </div> 
     <div> 
      <span>cookie_support</span> 
      <span>=</span>&nbsp; 
      <span>urllib2</span> 
      <span>.</span> 
      <span>HTTPCookieProcessor</span> 
      <span>(</span> 
      <span>cookielib</span> 
      <span>.</span> 
      <span>CookieJar</span> 
      <span>(</span> 
      <span>)</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>opener</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>urllib2</span> 
      <span>.</span> 
      <span>build_opener</span> 
      <span>(</span> 
      <span>cookie_support</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>urllib2</span> 
      <span>.</span> 
      <span>install_opener</span> 
      <span>(</span> 
      <span>opener</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>content</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>urllib2</span> 
      <span>.</span> 
      <span>urlopen</span> 
      <span>(</span> 
      <span>'http://XXXX'</span> 
      <span>)</span> 
      <span>.</span> 
      <span>read</span> 
      <span>(</span> 
      <span>)</span> 
     </div> 
    </div> </td> 
  </tr> 
 </tbody> 
</table>

关键在于CookieJar()，它用于管理HTTP cookie值、存储HTTP请求生成的cookie、向传出的HTTP请求添加cookie的对象。整个cookie都存储在内存中，对CookieJar实例进行垃圾回收后cookie也将丢失，所有过程都不需要单独去操作。

手动添加cookie

cookie = "PHPSESSID=91rurfqm2329bopnosfu4fvmu7; kmsign=55d2c12c9b1e3; KMUID=b6Ejc1XSwPq9o756AxnBAg=" request.add\_header("Cookie", cookie)

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      <span>cookie</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>"PHPSESSID=91rurfqm2329bopnosfu4fvmu7;&nbsp;kmsign=55d2c12c9b1e3;&nbsp;KMUID=b6Ejc1XSwPq9o756AxnBAg="</span> 
     </div> 
     <div> 
      <span>request</span> 
      <span>.</span> 
      <span>add_header</span> 
      <span>(</span> 
      <span>"Cookie"</span> 
      <span>,</span>&nbsp; 
      <span>cookie</span> 
      <span>)</span> 
     </div> 
    </div> </td> 
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# 4、伪装成浏览器 #

某些网站反感爬虫的到访，于是对爬虫一律拒绝请求。所以用urllib2直接访问网站经常会出现HTTP Error 403: Forbidden的情况

对有些 header 要特别留意，Server 端会针对这些 header 做检查

1.User-Agent 有些 Server 或 Proxy 会检查该值，用来判断是否是浏览器发起的 Request

2.Content-Type 在使用 REST 接口时，Server 会检查该值，用来确定 HTTP Body 中的内容该怎样解析。

这时可以通过修改http包中的header来实现，代码片段如下：

import urllib2 headers = \{ 'User-Agent':'Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US; rv:1.9.1.6) Gecko/20091201 Firefox/3.5.6' \} request = urllib2.Request( url = 'http://my.oschina.net/jhao104/blog?catalog=3463517', headers = headers ) print urllib2.urlopen(request).read()

# 5、页面解析 #

对于页面解析最强大的当然是正则表达式，这个对于不同网站不同的使用者都不一样，就不用过多的说明，附两个比较好的网址：

正则表达式入门：[http://www.cnblogs.com/huxi/archive/2010/07/04/1771073.html][http_www.cnblogs.com_huxi_archive_2010_07_04_1771073.html]

正则表达式在线测试：[http://tool.oschina.net/regex/][http_tool.oschina.net_regex]

其次就是解析库了，常用的有两个lxml和BeautifulSoup，对于这两个的使用介绍两个比较好的网站：

lxml：[http://my.oschina.net/jhao104/blog/639448][http_my.oschina.net_jhao104_blog_639448]

BeautifulSoup：[http://cuiqingcai.com/1319.html][http_cuiqingcai.com_1319.html]

对于这两个库，我的评价是，都是HTML/XML的处理库，Beautifulsoup纯python实现，效率低，但是功能实用，比如能用通过结果搜索获得某个HTML节点的源码；lxmlC语言编码，高效，支持Xpath

# 6、验证码的处理 #

对于一些简单的验证码，可以进行简单的识别。本人也只进行过一些简单的验证码识别。但是有些反人类的验证码，比如12306，可以通过打码平台进行人工打码，当然这是要付费的。

# 7、gzip压缩 #

有没有遇到过某些网页，不论怎么转码都是一团乱码。哈哈，那说明你还不知道许多web服务具有发送压缩数据的能力，这可以将网络线路上传输的大量数据消减 60% 以上。这尤其适用于 XML web 服务，因为 XML 数据 的压缩率可以很高。

但是一般服务器不会为你发送压缩数据，除非你告诉服务器你可以处理压缩数据。

于是需要这样修改代码：

import urllib2, httplib request = urllib2.Request('http://xxxx.com') request.add\_header('Accept-encoding', 'gzip') 1 opener = urllib2.build\_opener() f = opener.open(request)

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      <span>import</span>&nbsp; 
      <span>urllib2</span> 
      <span>,</span>&nbsp; 
      <span>httplib</span> 
     </div> 
     <div> 
      <span>request</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>urllib2</span> 
      <span>.</span> 
      <span>Request</span> 
      <span>(</span> 
      <span>'http://xxxx.com'</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>request</span> 
      <span>.</span> 
      <span>add_header</span> 
      <span>(</span> 
      <span>'Accept-encoding'</span> 
      <span>,</span>&nbsp; 
      <span>'gzip'</span> 
      <span>)</span>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 
      <span>1</span> 
     </div> 
     <div> 
      <span>opener</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>urllib2</span> 
      <span>.</span> 
      <span>build_opener</span> 
      <span>(</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>f</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>opener</span> 
      <span>.</span> 
      <span>open</span> 
      <span>(</span> 
      <span>request</span> 
      <span>)</span> 
     </div> 
    </div> </td> 
  </tr> 
 </tbody> 
</table>

这是关键:创建Request对象，添加一个 Accept-encoding 头信息告诉服务器你能接受 gzip 压缩数据

然后就是解压缩数据：

import StringIO import gzip compresseddata = f.read() compressedstream = StringIO.StringIO(compresseddata) gzipper = gzip.GzipFile(fileobj=compressedstream) print gzipper.read()

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      <span>import</span>&nbsp; 
      <span>StringIO</span> 
     </div> 
     <div> 
      <span>import</span>&nbsp; 
      <span>gzip</span> 
     </div> 
     <div>
       &nbsp; 
     </div> 
     <div> 
      <span>compresseddata</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>f</span> 
      <span>.</span> 
      <span>read</span> 
      <span>(</span> 
      <span>)</span>&nbsp; 
     </div> 
     <div> 
      <span>compressedstream</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>StringIO</span> 
      <span>.</span> 
      <span>StringIO</span> 
      <span>(</span> 
      <span>compresseddata</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>gzipper</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>gzip</span> 
      <span>.</span> 
      <span>GzipFile</span> 
      <span>(</span> 
      <span>fileobj</span> 
      <span>=</span> 
      <span>compressedstream</span> 
      <span>)</span>&nbsp; 
     </div> 
     <div> 
      <span>print</span>&nbsp; 
      <span>gzipper</span> 
      <span>.</span> 
      <span>read</span> 
      <span>(</span> 
      <span>)</span> 
     </div> 
    </div> </td> 
  </tr> 
 </tbody> 
</table>

# 8、多线程并发抓取 #

单线程太慢的话，就需要多线程了，这里给个简单的线程池模板 这个程序只是简单地打印了1-10，但是可以看出是并发的。

虽然说python的多线程很鸡肋，但是对于爬虫这种网络频繁型，还是能一定程度提高效率的。

from threading import Thread from Queue import Queue from time import sleep \# q是任务队列 \#NUM是并发线程总数 \#JOBS是有多少任务 q = Queue() NUM = 2 JOBS = 10 \#具体的处理函数，负责处理单个任务 def do\_somthing\_using(arguments): print arguments \#这个是工作进程，负责不断从队列取数据并处理 def working(): while True: arguments = q.get() do\_somthing\_using(arguments) sleep(1) q.task\_done() \#fork NUM个线程等待队列 for i in range(NUM): t = Thread(target=working) t.setDaemon(True) t.start() \#把JOBS排入队列 for i in range(JOBS): q.put(i) \#等待所有JOBS完成 q.join()

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    </div> </td> 
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    <div style=""> 
     <div> 
      <span>from</span>&nbsp; 
      <span>threading</span>&nbsp; 
      <span>import</span>&nbsp; 
      <span>Thread</span> 
     </div> 
     <div> 
      <span>from</span>&nbsp; 
      <span>Queue</span>&nbsp; 
      <span>import</span>&nbsp; 
      <span>Queue</span> 
     </div> 
     <div> 
      <span>from</span>&nbsp; 
      <span>time</span>&nbsp; 
      <span>import</span>&nbsp; 
      <span>sleep</span> 
     </div> 
     <div> 
      <span>#&nbsp;q是任务队列</span> 
     </div> 
     <div> 
      <span>#NUM是并发线程总数</span> 
     </div> 
     <div> 
      <span>#JOBS是有多少任务</span> 
     </div> 
     <div> 
      <span>q</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>Queue</span> 
      <span>(</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>NUM</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>2</span> 
     </div> 
     <div> 
      <span>JOBS</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>10</span> 
     </div> 
     <div> 
      <span>#具体的处理函数，负责处理单个任务</span> 
     </div> 
     <div> 
      <span>def</span>&nbsp; 
      <span>do_somthing_using</span> 
      <span>(</span> 
      <span>arguments</span> 
      <span>)</span> 
      <span>:</span> 
     </div> 
     <div>
       &nbsp;&nbsp;&nbsp;&nbsp; 
      <span>print</span>&nbsp; 
      <span>arguments</span> 
     </div> 
     <div> 
      <span>#这个是工作进程，负责不断从队列取数据并处理</span> 
     </div> 
     <div> 
      <span>def</span>&nbsp; 
      <span>working</span> 
      <span>(</span> 
      <span>)</span> 
      <span>:</span> 
     </div> 
     <div>
       &nbsp;&nbsp;&nbsp;&nbsp; 
      <span>while</span>&nbsp; 
      <span>True</span> 
      <span>:</span> 
     </div> 
     <div>
       &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 
      <span>arguments</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>q</span> 
      <span>.</span> 
      <span>get</span> 
      <span>(</span> 
      <span>)</span> 
     </div> 
     <div>
       &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 
      <span>do_somthing_using</span> 
      <span>(</span> 
      <span>arguments</span> 
      <span>)</span> 
     </div> 
     <div>
       &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 
      <span>sleep</span> 
      <span>(</span> 
      <span>1</span> 
      <span>)</span> 
     </div> 
     <div>
       &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 
      <span>q</span> 
      <span>.</span> 
      <span>task_done</span> 
      <span>(</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>#fork&nbsp;NUM个线程等待队列</span> 
     </div> 
     <div> 
      <span>for</span>&nbsp; 
      <span>i</span>&nbsp; 
      <span>in</span>&nbsp; 
      <span>range</span> 
      <span>(</span> 
      <span>NUM</span> 
      <span>)</span> 
      <span>:</span> 
     </div> 
     <div>
       &nbsp;&nbsp;&nbsp;&nbsp; 
      <span>t</span>&nbsp; 
      <span>=</span>&nbsp; 
      <span>Thread</span> 
      <span>(</span> 
      <span>target</span> 
      <span>=</span> 
      <span>working</span> 
      <span>)</span> 
     </div> 
     <div>
       &nbsp;&nbsp;&nbsp;&nbsp; 
      <span>t</span> 
      <span>.</span> 
      <span>setDaemon</span> 
      <span>(</span> 
      <span>True</span> 
      <span>)</span> 
     </div> 
     <div>
       &nbsp;&nbsp;&nbsp;&nbsp; 
      <span>t</span> 
      <span>.</span> 
      <span>start</span> 
      <span>(</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>#把JOBS排入队列</span> 
     </div> 
     <div> 
      <span>for</span>&nbsp; 
      <span>i</span>&nbsp; 
      <span>in</span>&nbsp; 
      <span>range</span> 
      <span>(</span> 
      <span>JOBS</span> 
      <span>)</span> 
      <span>:</span> 
     </div> 
     <div>
       &nbsp;&nbsp;&nbsp;&nbsp; 
      <span>q</span> 
      <span>.</span> 
      <span>put</span> 
      <span>(</span> 
      <span>i</span> 
      <span>)</span> 
     </div> 
     <div> 
      <span>#等待所有JOBS完成</span> 
     </div> 
     <div> 
      <span>q</span> 
      <span>.</span> 
      <span>join</span> 
      <span>(</span> 
      <span>)</span> 
     </div> 
    </div> </td> 
  </tr> 
 </tbody> 
</table>

[http_www.cnblogs.com_huxi_archive_2010_07_04_1771073.html]: http://www.cnblogs.com/huxi/archive/2010/07/04/1771073.html
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