自己改写的代码，用进程池，线程，协程及不用实现的

最新推荐文章于 2022-07-30 14:53:57 发布

hellenlee22

最新推荐文章于 2022-07-30 14:53:57 发布

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CC 4.0 BY-SA版权

本文链接：https://blog.youkuaiyun.com/hellenlee22/article/details/90707041

博客提及了进程池写、线程写和协程写三种写入方式，但未展开具体内容。这些写入方式在信息技术领域常用于处理并发任务，不同方式有不同特点和适用场景。

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进程池写：


from multiprocessing import Process, Array,Pool
import time
def f(x):
    time.sleep(0.5)
    print(x)
    return x*x

if __name__ == '__main__':
    pool = Pool(processes=2) #最多可以跑11个进程
    res_list = []
    start=time.time()
    for i in range(100):
        res = pool.apply_async(f,[i,]) #apply同步 apply_async异步
        res_list.append(res)
    for l in res_list:
        #print(l)
        #l.get(timeout=9)  #超时apply_async
        l.get()  #超时apply_async
    end=time.time()
    print('the final',end-start)

线程写：

'''
#线程实现
import threading
import time
def f(x):
    time.sleep(0.5)
    print(x)
    return x*x


if __name__ == '__main__':
    start = time.time()
    for i in range(100):
        t1=threading.Thread(target=f,args=(i,))
        t2 = threading.Thread(target=f, args=(i,))
        t1.start()
        t2.start()
        #f(i)
    end=time.time()
    print('the final', end - start)
'''

协程写：

#协程

import time
def f(x):
    time.sleep(0.5)
    yield(x)
    return x*x


# if __name__ == '__main__':
#     start = time.time()
#     for i in range(100):
#         t1=threading.Thread(target=f,args=(i,))
#         t2 = threading.Thread(target=f, args=(i,))
#         t1.start()
#         t2.start()
#         #f(i)
#     end=time.time()
#     print('the final', end - start)

if __name__ == '__main__':
    start = time.time()
    for i in range(100):
        x1=f(i)
        next(x1)

    end=time.time()
    print('the final', end - start)

不用的


#from multiprocessing import Process, Array,Pool
import time
def f(x):
    time.sleep(0.5)
    print(x)
    return x*x


if __name__ == '__main__':
    start = time.time()
    for i in range(100):

        f(i)
    end=time.time()
    print('the final', end - start)