线程池

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线程池：线程池主要用来解决线程生命周期开销问题和资源不足问题。通过对多个任务重用线程，线程创建的开销就被分摊到了多个任务上了，线程池中的所有线程主动从工作队列中寻找执行的工作。

import sys, Queue, threading
import time

class _Thread(threading.Thread):
	def __init__(self, workQueue, resultQueue,timeout=1, **kwargs):
		threading.Thread.__init__(self, kwargs=kwargs)
		self.timeout = timeout
		self.setDaemon(True)
		self.workQueue = workQueue
		self.resultQueue = resultQueue
#		self.start()

	def run(self):
		while True:
			try:
				callable, args, kwargs = self.workQueue.get(timeout=self.timeout)
				res = callable(args, kwargs)
				print res," | "+self.getName()
				self.resultQueue.put(res+" | "+self.getName())    
			except Queue.Empty:
				break
			except :
				print sys.exc_info()
				raise

class ThreadPool:
	def __init__( self, num_of_threads=2):
		self.workQueue = Queue.Queue()		#work queue func args
		self.resultQueue = Queue.Queue()	#resulst queue 
		self.threads = []			#threadlist
		self.__createThreadPool(num_of_threads)

	def __createThreadPool( self, num_of_threads ):
		for i in range( num_of_threads ):
			thread = _Thread( self.workQueue, self.resultQueue )
			self.threads.append(thread)

	def wait_for_complete(self):
		while len(self.threads):
			thread = self.threads.pop()
			if thread.isAlive():
				thread.join()
	def start(self):
		for th in self.threads:
			th.start()

	def add_job( self, callable, *args, **kwargs ):
		self.workQueue.put( (callable,args,kwargs) ) #put msg


def test_job(id, sleep = 0.001 ):
	time.sleep(0.1)
	return str(id)

def test():
	print ‘start testing‘
	tp = ThreadPool(5)
	for i in range(50):
		tp.add_job( test_job, i, i )
	tp.start()
	tp.wait_for_complete()

	print ‘result Queue\‘s length == %d ‘% tp.resultQueue.qsize()

	while tp.resultQueue.qsize():
		print tp.resultQueue.get()
	print ‘end testing‘

if __name__ == ‘__main__‘:
	test()

线程池

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原文地址：http://www.cnblogs.com/pylab/p/4575290.html