Home  >  Article  >  Backend Development  >  Python crawler multi-threading detailed explanation and example code

Python crawler multi-threading detailed explanation and example code

WBOY
WBOYOriginal
2016-12-05 13:27:201576browse

Python supports multi-threading, mainly through the two modules thread and threading. The thread module is a relatively low-level module, and the threading module provides some packaging for thread, making it more convenient to use.

Although python's multi-threading is limited by GIL and is not true multi-threading, it can still significantly improve efficiency for I/O-intensive calculations, such as crawlers.
An example is used below to verify the efficiency of multi-threading. The code only involves page acquisition and does not parse it.

# -*-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)

Use two methods to obtain 10 web pages with relatively slow access speed. The general method takes 50 seconds, and multi-threading takes 10 seconds.
Interpretation of multi-threaded code:

# 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

The above is the entire content of this article, I hope it will be helpful to everyone’s study.

Statement:
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn