本文实例分析了Python自定义进程池。分享给大家供大家参考，具体如下：代码说明一切：
#encoding=utf-8#author: walker#date: 2014-05-21#function: 自定义进程池遍历目录下文件from multiprocessing import Process, Queue, Lockimport time, os#消费者class Consumer(Process): def __init__(self, queue, ioLock): super(Consumer, self).__init__() self.queue = queue self.ioLock = ioLock def run(self): while True: task = self.queue.get() #队列中无任务时，会阻塞进程 if isinstance(task, str) and task == 'quit': break; time.sleep(1) #假定任务处理需要1秒钟 self.ioLock.acquire() print( str(os.getpid()) + ' ' + task) self.ioLock.release() self.ioLock.acquire() print 'Bye-bye' self.ioLock.release()#生产者def Producer(): queue = Queue() #这个队列是进程/线程安全的 ioLock = Lock() subNum = 4 #子进程数量 workers = build_worker_pool(queue, ioLock, subNum) start_time = time.time() for parent, dirnames, filenames in os.walk(r'D:\test'): for filename in filenames: queue.put(filename) ioLock.acquire() print('qsize:' + str(queue.qsize())) ioLock.release() while queue.qsize() > subNum * 10: #控制队列中任务数量 time.sleep(1) for worker in workers: queue.put('quit') for worker in workers: worker.join() ioLock.acquire() print('Done! Time taken: {}'.format(time.time() - start_time)) ioLock.release()#创建进程池def build_worker_pool(queue, ioLock, size): workers = [] for _ in range(size): worker = Consumer(queue, ioLock) worker.start() workers.append(worker) return workersif __name__ == '__main__': Producer()
ps：
self.ioLock.acquire()...self.ioLock.release()
可用：
with self.ioLock: ...
替代。再来一个好玩的例子：
#encoding=utf-8#author: walker#date: 2016-01-06#function: 一个多进程的好玩例子import os, sys, timefrom multiprocessing import Poolcur_dir_fullpath = os.path.dirname(os.path.abspath(__file__))g_List = ['a']#修改全局变量g_Listdef ModifyDict_1(): global g_List g_List.append('b')#修改全局变量g_Listdef ModifyDict_2(): global g_List g_List.append('c')#处理一个def ProcOne(num): print('ProcOne ' + str(num) + ', g_List:' + repr(g_List))#处理所有def ProcAll(): pool = Pool(processes = 4) for i in range(1, 20): #ProcOne(i) #pool.apply(ProcOne, (i,)) pool.apply_async(ProcOne, (i,)) pool.close() pool.join()ModifyDict_1() #修改全局变量g_Listif __name__ == '__main__': ModifyDict_2() #修改全局变量g_List print('In main g_List :' + repr(g_List)) ProcAll()
Windows7 下运行的结果：
λ python3 demo.pyIn main g_List :['a', 'b', 'c']ProcOne 1, g_List:['a', 'b']ProcOne 2, g_List:['a', 'b']ProcOne 3, g_List:['a', 'b']ProcOne 4, g_List:['a', 'b']ProcOne 5, g_List:['a', 'b']ProcOne 6, g_List:['a', 'b']ProcOne 7, g_List:['a', 'b']ProcOne 8, g_List:['a', 'b']ProcOne 9, g_List:['a', 'b']ProcOne 10, g_List:['a', 'b']ProcOne 11, g_List:['a', 'b']ProcOne 12, g_List:['a', 'b']ProcOne 13, g_List:['a', 'b']ProcOne 14, g_List:['a', 'b']ProcOne 15, g_List:['a', 'b']ProcOne 16, g_List:['a', 'b']ProcOne 17, g_List:['a', 'b']ProcOne 18, g_List:['a', 'b']ProcOne 19, g_List:['a', 'b']
Ubuntu 14.04下运行的结果：
In main g_List :['a', 'b', 'c']ProcOne 1, g_List:['a', 'b', 'c']ProcOne 2, g_List:['a', 'b', 'c']ProcOne 3, g_List:['a', 'b', 'c']ProcOne 5, g_List:['a', 'b', 'c']ProcOne 4, g_List:['a', 'b', 'c']ProcOne 8, g_List:['a', 'b', 'c']ProcOne 9, g_List:['a', 'b', 'c']ProcOne 7, g_List:['a', 'b', 'c']ProcOne 11, g_List:['a', 'b', 'c']ProcOne 6, g_List:['a', 'b', 'c']ProcOne 12, g_List:['a', 'b', 'c']ProcOne 13, g_List:['a', 'b', 'c']ProcOne 10, g_List:['a', 'b', 'c']ProcOne 14, g_List:['a', 'b', 'c']ProcOne 15, g_List:['a', 'b', 'c']ProcOne 16, g_List:['a', 'b', 'c']ProcOne 17, g_List:['a', 'b', 'c']ProcOne 18, g_List:['a', 'b', 'c']ProcOne 19, g_List:['a', 'b', 'c']
可以看见Windows7下第二次修改没有成功，而Ubuntu下修改成功了。据uliweb作者limodou讲，原因是Windows下是充重启实现的子进程；Linux下是fork实现的。更多关于Python相关内容感兴趣的读者可查看本站专题：《Python URL操作技巧总结》、《Python图片操作技巧总结》、《Python数据结构与算法教程》、《Python Socket编程技巧总结》、《Python函数使用技巧总结》、《Python字符串操作技巧汇总》、《Python入门与进阶经典教程》及《Python文件与目录操作技巧汇总》希望本文所述对大家Python程序设计有所帮助。命运如同手中的掌纹，无论多曲折，终掌握在自己手中。
