Python3之网络编程总结

重中之重

进程池、线程池

from concurrent.futures import ProcessPoolExecutor, ThreadPoolExecutorimport timedef task(n):    time.sleep(2)    return n ** 2def deal_result(ret):    # print(ret)    ret = ret.result()    print(ret)if __name__ == '__main__':    # p = ProcessPoolExecutor()    p = ThreadPoolExecutor()  # 默认20线程    p_list = []    # obj = p.map(task, range(10))    # print(list(obj))    for i in range(10):        obj = p.submit(task, i).add_done_callback(deal_result)        p_list.append(obj)    p.shutdown()    print([i.result() for i in p_list])

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生产者消费者模型

进程实现消费者生产者模型

from multiprocessing import Process, JoinableQueueimport timeimport multiprocessingq = JoinableQueue()def consumer(q):    while 1:        res = q.get()        time.sleep(2)        print('消费者消费了%s' % res)        q.task_done()def producer0(q):    for i in range(5):        q.put(i)        print('生产者生产了%s' % i)    q.join()def producer1(q):    for i in range(5):        q.put(i)        print('生产者生产了%s' % i)    q.join()if __name__ == '__main__':    p1 = Process(target=producer0, args=(q,))    p2 = Process(target=producer1, args=(q,))    p3 = Process(target=consumer, args=(q,))    p3.daemon = True    p1.start()    p2.start()    p3.start()    p1.join()    p2.join()

线程实现生产者消费者模型

from threading import Threadimport queueimport timeq = queue.Queue()def consumer():    while 1:        res = q.get()        time.sleep(2)        print('消费者消费了%s' % res)        q.task_done()def producer0():    for i in range(5):        q.put(i)        print('生产者0000生产了%s' % i)    q.join()def producer1():    for i in range(5):        q.put(i)        print('生产者1111生产了%s' % i)    q.join()if __name__ == '__main__':    t1 = Thread(target=consumer,)    t2 = Thread(target=producer0,)    t3 = Thread(target=producer1,)    t1.daemon = True    t1.start()    t2.start()    t3.start()    t2.join()    t3.join()

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回调函数

任务必须要有返回值以供回调函数调用，在add_done_callback中处理数据要先在任务中调用ret.result()将数据获取到~

from concurrent.futures import ProcessPoolExecutor, ThreadPoolExecutorimport timedef task(n):    time.sleep(2)    return n ** 2def deal_result(ret):    # print(ret)    ret = ret.result()    print(ret)if __name__ == '__main__':    # p = ProcessPoolExecutor()    p = ThreadPoolExecutor()  # 默认20线程    p_list = []    # obj = p.map(task, range(10))    # print(list(obj))    for i in range(10):        obj = p.submit(task, i).add_done_callback(deal_result)        p_list.append(obj)    p.shutdown()    print([i.result() for i in p_list])

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Queue

from multiprocessing import Process, JoinableQueueimport timeimport multiprocessingq = JoinableQueue()def consumer(q):    while 1:        res = q.get()        time.sleep(2)        print('消费者消费了%s' % res)        q.task_done()def producer0(q):    for i in range(5):        q.put(i)        print('生产者生产了%s' % i)    q.join()def producer1(q):    for i in range(5):        q.put(i)        print('生产者生产了%s' % i)    q.join()if __name__ == '__main__':    p1 = Process(target=producer0, args=(q,))    p2 = Process(target=producer1, args=(q,))    p3 = Process(target=consumer, args=(q,))    p3.daemon = True    p1.start()    p2.start()    p3.start()    p1.join()    p2.join()

进程池线程池不能用Queue，如果想用，请参考下面的博客：
Python3之无法在进程池中使用队列Queue的解决方案

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