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一. 代码
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. 运行结果
三. 分析
由上图可知,在IO不是特别多的时候,多线程不一定节约时间,而多进程是可以节约时间的。