Python多进程操作Coding

最新推荐文章于 2022-07-08 22:27:45 发布

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本文通过Python代码示例介绍如何使用多进程池进行任务并行处理。具体包括创建进程池、分配任务、获取结果等步骤，并展示了如何通过回调函数收集各进程的执行结果。

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import time
import multiprocessing

ls = [i for i in range(10000)]

print(ls)

ls1 = ls[0: 100]

ls2 = ls[100:200]
ls3 = ls[200: 300]
l = []

test2调用test1函数

def test2():
test1()
print(‘test2’)

def func1(x):
for i in ls1:
l.append(i)
# print(‘func1’)
# print(l)
return l

def func2(x):
for i in ls2:
l.append(i)
# print(‘func2’)
# print(l)
return l

def func3(x):
for i in ls3:
l.append(i)
print(‘func3’)
# print(l)
return l

if name == “main“:

def test1():
    print('test1')
    start_time = time.clock()
    pool = multiprocessing.Pool(processes=3)
    res1 = pool.apply_async(func1, (1, ), callback=func1)
    res2 = pool.apply_async(func2, (2, ), callback=func2)
    res3 = pool.apply_async(func3, (3, ), callback=func3)
    pool.close()
    pool.join()
    print('-------------------------')
    # l = res3.get()
    # print(l)
    l1 = res1.get()
    l2 = res2.get()
    l3 = res3.get()
    # print(l1)
    # print(l2)
    print(l3)
    print("Sub-process(es) done.")
    end_time = time.clock()
    run_time = end_time - start_time
    print(run_time)

test2()
# print('-------------l1-------------------')
# print(l1)
# print('-------------l2-------------------')
# print(l2)
# print('-------------l3-------------------')
# print(l3)
#
# print('-------------l-------------------')
# l = l1 + l2 + l3
# print(l)