Python之多進程（multiprocessing）學習【3】：平常狀態，多線程，多進程比較

一. 代碼

import multiprocessing as mp
import threading as td
import time

def job(q):
    res = 0
    for i in range(1000000):
        res += i+i**2+i**3
    q.put(res) # queue

def multicore():
    q = mp.Queue()
    p1 = mp.Process(target=job, args=(q,))
    p2 = mp.Process(target=job, args=(q,))
    p1.start()
    p2.start()
    p1.join()
    p2.join()
    res1 = q.get()
    res2 = q.get()
    print('multicore:' , res1+res2)

def normal():
    res = 0
    for _ in range(2):
        for i in range(1000000):
            res += i+i**2+i**3
    print('normal:', res)

def multithread():
    q = mp.Queue()
    t1 = td.Thread(target=job, args=(q,))
    t2 = td.Thread(target=job, args=(q,))
    t1.start()
    t2.start()
    t1.join()
    t2.join()
    res1 = q.get()
    res2 = q.get()
    print('multithread:', res1+res2)

if __name__ == '__main__':
    st = time.time()
    normal()
    st1= time.time()
    print('normal time:', st1 - st)
    multithread()
    st2 = time.time()
    print('multithread time:', st2 - st1)
    multicore()
    print('multicore time:', time.time()-st2)

二. 運行結果

三. 分析

      由上圖可知，在IO不是特別多的時候，多線程不一定節約時間，而多進程是可以節約時間的。