Python多线程爬虫简单示例

# -*-coding:utf-8 -*-
import urllib2, time
import threading
 
 
class MyThread(threading.Thread):
  def __init__(self, func, args):
    threading.Thread.__init__(self)
    self.args = args
    self.func = func
 
  def run(self):
    apply(self.func, self.args)
 
 
def open_url(url):
  request = urllib2.Request(url)
  html = urllib2.urlopen(request).read()
  print len(html)
  return html
 
if __name__ == '__main__':
  # 构造url列表
  urlList = []
  for p in range(1, 10):
    urlList.append('http://s.wanfangdata.com.cn/Paper.aspx?q=%E5%8C%BB%E5%AD%A6&p=' + str(p))
   
  # 一般方式
  n_start = time.time()
  for each in urlList:
    open_url(each)
  n_end = time.time()
  print 'the normal way take %s s' % (n_end-n_start)
   
  # 多线程
  t_start = time.time()
  threadList = [MyThread(open_url, (url,)) for url in urlList]
  for t in threadList:
    t.setDaemon(True)
    t.start()
  for i in threadList:
    i.join()
  t_end = time.time()
  print 'the thread way take %s s' % (t_end-t_start)

分别用两种方式获取10个访问速度比较慢的网页，一般方式耗时50s，多线程耗时10s。

多线程代码解读:

# 创建线程类，继承Thread类
class MyThread(threading.Thread):
  def __init__(self, func, args):
    threading.Thread.__init__(self) # 调用父类的构造函数
    self.args = args
    self.func = func
 
  def run(self): # 线程活动方法
    apply(self.func, self.args)
  

threadList = [MyThread(open_url, (url,)) for url in urlList] # 调用线程类创建新线程，返回线程列表
  for t in threadList:
    t.setDaemon(True) # 设置守护线程，父线程会等待子线程执行完后再退出
    t.start() # 线程开启
  for i in threadList:
    i.join() # 等待线程终止，等子线程执行完后再执行父线程