多线程操作

对Python线程池进行详细说明

2010-02-26 09:42 佚名 CSDN博客 我要评论() 字号：T | T

本文对Python线程池进行详细说明介绍，IDE选择及编码的解决方案进行了一番详细的描述，实为Python初学者必读的Python学习经验心得。

AD：

下面给大家总结一下自己总结的对Python线程池经验之谈，对于那些没有接触学习过编程语言或者多开发语言略懂的用户而言，Python语言绝对是最好的选择之一，并建议初学的程序员先从Python开始学习编程。

import Queue, threading, sys
from threading import Thread
import time,urllib
# working thread
class Worker(Thread):
   worker_count = 0
   def __init__( self, workQueue, resultQueue, timeout = 0, **kwds):
       Thread.__init__( self, **kwds )
       self.id = Worker.worker_count
       Worker.worker_count += 1
       self.setDaemon( True )
       self.workQueue = workQueue
       self.resultQueue = resultQueue
       self.timeout = timeout
       self.start( )
   def run( self ):
       ''' the get-some-work, do-some-work main loop of worker threads '''
       while True:
           try:
               callable, args, kwds = self.workQueue.get(timeout=self.timeout)
               res = callable(*args, **kwds)
               print "worker[%2d]: %s" % (self.id, str(res) )
               self.resultQueue.put( res )
           except Queue.Empty:
               break
           except :
               print 'worker[%2d]' % self.id, sys.exc_info()[:2]

class WorkerManager:
   def __init__( self, num_of_workers=10, timeout = 1):
       self.workQueue = Queue.Queue()
       self.resultQueue = Queue.Queue()
       self.workers = []
       self.timeout = timeout
       self._recruitThreads( num_of_workers )
   def _recruitThreads( self, num_of_workers ):
       for i in range( num_of_workers ):
           worker = Worker( self.workQueue, self.resultQueue, self.timeout )
           self.workers.append(worker)
   def wait_for_complete( self):
       # ...then, wait for each of them to terminate:
       while len(self.workers):
           worker = self.workers.pop()
           worker.join( )
           if worker.isAlive() and not self.workQueue.empty():
               self.workers.append( worker )
       print "All jobs are are completed."
   def add_job( self, callable, *args, **kwds ):
       self.workQueue.put( (callable, args, kwds) )
   def get_result( self, *args, **kwds ):
       return self.resultQueue.get( *args, **kwds )

Worker类是一个Python线程池，不断地从workQueue队列中获取需要执行的任务，执行之，并将结果写入到resultQueue中。这里的workQueue和resultQueue都是现成安全的，其内部对各个线程的操作做了互斥。当从workQueue中获取任务超时，则线程结束。

WorkerManager负责初始化Python线程池，提供将任务加入队列和获取结果的接口，并能等待所有任务完成。一个典型的测试例子如下，它用10个线程去下载一个固定页面的内容，实际应用时应该是执行不同的任务。

def test_job(id, sleep = 0.001 ):
   try:
       urllib.urlopen('https://www.gmail.com/').read()
   except:
       print '[%4d]' % id, sys.exc_info()[:2]
   return id
def test():
   import socket
   socket.setdefaulttimeout(10)
   print 'start testing'
   wm = WorkerManager(10)
   for i in range(500):
       wm.add_job( test_job, i, i*0.001 )
   wm.wait_for_complete()
   print 'end testing'