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Python自定義進程池實例分析【生產(chǎn)者、消費者模型問題】

更新時間：2016年09月19日 10:34:04 作者：RQSLT

這篇文章主要介紹了Python自定義進程池,結(jié)合實例分析了Python使用自定義進程池實現(xiàn)的生產(chǎn)者、消費者模型問題,需要的朋友可以參考下

本文實例分析了Python自定義進程池。分享給大家供大家參考，具體如下：

代碼說明一切：

#encoding=utf-8
#author: walker
#date: 2014-05-21
#function: 自定義進程池遍歷目錄下文件
from multiprocessing import Process, Queue, Lock
import time, os
#消費者
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()  #隊列中無任務(wù)時，會阻塞進程
      if isinstance(task, str) and task == 'quit':
        break;
      time.sleep(1)  #假定任務(wù)處理需要1秒鐘
      self.ioLock.acquire()
      print( str(os.getpid()) + ' ' + task)
      self.ioLock.release()
    self.ioLock.acquire()
    print 'Bye-bye'
    self.ioLock.release()
#生產(chǎn)者
def Producer():
  queue = Queue()  #這個隊列是進程/線程安全的
  ioLock = Lock()
  subNum = 4  #子進程數(shù)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: #控制隊列中任務(wù)數(shù)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()
#創(chuàng)建進程池
def build_worker_pool(queue, ioLock, size):
  workers = []
  for _ in range(size):
    worker = Consumer(queue, ioLock)
    worker.start()
    workers.append(worker)
  return workers
if __name__ == '__main__':
  Producer()

ps：

self.ioLock.acquire()
...
self.ioLock.release()

可用：

with self.ioLock:
  ...

替代。

再來一個好玩的例子：

#encoding=utf-8
#author: walker
#date: 2016-01-06
#function: 一個多進程的好玩例子
import os, sys, time
from multiprocessing import Pool
cur_dir_fullpath = os.path.dirname(os.path.abspath(__file__))
g_List = ['a']
#修改全局變量g_List
def ModifyDict_1():
  global g_List
  g_List.append('b')
#修改全局變量g_List
def ModifyDict_2():
  global g_List
  g_List.append('c')
#處理一個
def ProcOne(num):
  print('ProcOne ' + str(num) + ', g_List:' + repr(g_List))
#處理所有
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() #修改全局變量g_List
if __name__ == '__main__':
  ModifyDict_2() #修改全局變量g_List
  print('In main g_List :' + repr(g_List))
  ProcAll()

Windows7 下運行的結(jié)果：

λ python3 demo.py
In 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下運行的結(jié)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']

可以看見Windows7下第二次修改沒有成功，而Ubuntu下修改成功了。據(jù)uliweb作者limodou講，原因是Windows下是充重啟實現(xiàn)的子進程；Linux下是fork實現(xiàn)的。

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