Python多进程库multiprocessing中进程池Pool类的使用详解

from multiprocessing import Process

def f(name):
  print 'hello', name

if __name__ == '__main__':
  p = Process(target=f, args=('bob',)) # 新建一个子进程p，目标函数是f，args是函数f的参数列表
  p.start() # 开始执行进程
  p.join() # 等待子进程结束

import multiprocessing
import time

def func(msg):
  print multiprocessing.current_process().name + '-' + msg

if __name__ == "__main__":
  pool = multiprocessing.Pool(processes=4) # 创建4个进程
  for i in xrange(10):
    msg = "hello %d" %(i)
    pool.apply_async(func, (msg, ))
  pool.close() # 关闭进程池，表示不能在往进程池中添加进程
  pool.join() # 等待进程池中的所有进程执行完毕，必须在close()之后调用
  print "Sub-process(es) done."

Sub-process(es) done.
PoolWorker-34-hello 1
PoolWorker-33-hello 0
PoolWorker-35-hello 2
PoolWorker-36-hello 3
PoolWorker-34-hello 7
PoolWorker-33-hello 4
PoolWorker-35-hello 5
PoolWorker-36-hello 6
PoolWorker-33-hello 8
PoolWorker-36-hello 9

import multiprocessing
import time

def func(msg):
  return multiprocessing.current_process().name + '-' + msg

if __name__ == "__main__":
  pool = multiprocessing.Pool(processes=4) # 创建4个进程
  results = []
  for i in xrange(10):
    msg = "hello %d" %(i)
    results.append(pool.apply_async(func, (msg, )))
  pool.close() # 关闭进程池，表示不能再往进程池中添加进程，需要在join之前调用
  pool.join() # 等待进程池中的所有进程执行完毕
  print ("Sub-process(es) done.")

  for res in results:
    print (res.get())

Sub-process(es) done.
PoolWorker-37-hello 0
PoolWorker-38-hello 1
PoolWorker-39-hello 2
PoolWorker-40-hello 3
PoolWorker-37-hello 4
PoolWorker-38-hello 5
PoolWorker-39-hello 6
PoolWorker-37-hello 7
PoolWorker-40-hello 8
PoolWorker-38-hello 9