python3 process pool

IO process pool without clogging case

# Coding: UTF. 8- 
Import Time
 from multiprocessing Import Process, Pool 


DEF FUNC (n-):
     Pass 


IF  the __name__ == ' __main__ ' : 
    NUM = 10 
    start_pool_time = the time.time () 
    the pool = Pool (. 5 ) 
    pool.map (FUNC , the Range (NUM))   # the Map is asynchronous, and comes close and the Join 
    Print ( " time to perform the process by the pool: " , time.time () - start_pool_time) 

    std_start_time = time.time ()
     forI in : (NUM) Range
         Pass 
    Print ( " execution time normally performed: " , the time.time () - std_start_time) 

    pro_start_time = the time.time () 
    p_lst = []
     for I in (NUM) Range: 
        P = Process ( FUNC = target, args = (i,)) 
        p.start () 
        p_lst.append (the p-) 

    [pp.join () for PP in p_lst]
     Print ( " execution time multi-process: " , time.time () - pro_start_time) 

#By the time of the execution process pool: 0.46875 
# normal execution execution time: 0.0 
# execution time multi-process: 0.828125 

# general convention of the process is the number of process pool for the number of CPU's work depends on the specific circumstances to consider.

 

There are circumstances IO blocked

# coding:utf-8
import time
from multiprocessing import Process, Pool


def func(n):
    time.sleep(1)


if __name__ == '__main__':
    num = 10
    start_pool_time = time.time()
    pool = Pool(5)
    pool.map(func, range(num))
    print("通过进程池执行的时间:", time.time() - start_pool_time)

    std_start_time = time.time()
    for i in range(num):
        time.sleep(1)
    print("正常执行的执行时间:", time.time() - std_start_time)

    pro_start_time = time.time()
    p_lst = []
    for i in range(num):
        p = Process(target=func, args=(i,))
        p.start()
        p_lst.append(p)

    [pp.join() for pp in p_lst]
    print("多进程的执行时间:", time.time() - pro_start_time)


# 通过进程池执行的时间: 2.578125
# 正常执行的执行时间: 10.0
# 多进程的执行时间: 1.75