【Python】Python-pool的

#coding: utf-8
import multiprocessing
import time


def func(msg):
    print("msg:", msg)
    time.sleep(3)
    print("end")


if __name__ == "__main__":
    cores = multiprocessing.cpu_count()
    pool = multiprocessing.Pool(processes=cores)
    print("Adding tasks...")
    for i in range(cores):
        msg = "hello %d" %(i)
        pool.apply_async(func, (msg, ))   #维持执行的进程总数为processes，当一个进程执行完毕后会添加新的进程进去
    print("Starting tasks...")
    pool.close()
    pool.join()   #调用join之前，先调用close函数，否则会出错。执行完close后不会有新的进程加入到pool,join函数等待所有子进程结束
    print("Sub-process(es) done.")

#coding: utf-8
import multiprocessing
import time

def func(msg):
    print("msg:", msg)
    time.sleep(3)
    print("end")
    return msg

if __name__ == "__main__":
    cores = multiprocessing.cpu_count()
    pool = multiprocessing.Pool(processes=cores)
    print("Adding tasks...")
    results = []
    for i in range(cores):
        msg = "hello %d" %(i)
        results.append(pool.apply_async(func, (msg, )))   #维持执行的进程总数为processes，当一个进程执行完毕后会添加新的进程进去
    print("Starting tasks...")
    pool.close()
    pool.join()   #调用join之前，先调用close函数，否则会出错。执行完close后不会有新的进程加入到pool,join函数等待所有子进程结束
    print([r.get() for r in results])
    print("Sub-process(es) done.")

This is an issue with IDLE, which you're using to run your code. IDLE does a fairly basic emulation of a terminal for handling the output of a program you run in it. It cannot handle subprocesses though, so while they'll run just fine in the background, you'll never see their output.

The simplest fix is to simply run your code from the command line.

An alternative might be to use a more sophisticated IDE. There are a bunch of them listed on the Python wiki, though I'm not sure which ones have better terminal emulation for multiprocessing output.

#coding=utf-8
import multiprocessing

def do(n) :
  #获取当前线程的名字
  name = multiprocessing.current_process().name
  print(name,'starting')
  print("worker ", n)
  return 

if __name__ == '__main__' :
  numList = []
  for i in range(4) :
    p = multiprocessing.Process(target=do, args=(i,))
    numList.append(p)
    p.start()
    p.join()
    print("Process end.")