import time from multiprocessing import Process, Queue, Pool, Manager, Pipe # def producer(queue): # queue.put("a") # time.sleep(2) # # def consumer(queue): # time.sleep(2) # data = queue.get() # print(data) # # if __name__ == "__main__": # queue = Queue(10) # my_producer = Process(target=producer, args=(queue,)) # my_consumer = Process(target=consumer, args=(queue,)) # my_producer.start() # my_consumer.start() # my_producer.join() # my_consumer.join() #共享全局变量通信 #共享全局变量不能适用于多进程编程,可以适用于多线程 # def producer(a): # a += 100 # time.sleep(2) # # def consumer(a): # time.sleep(2) # print(a) # # if __name__ == "__main__": # a = 1 # my_producer = Process(target=producer, args=(a,)) # my_consumer = Process(target=consumer, args=(a,)) # my_producer.start() # my_consumer.start() # my_producer.join() # my_consumer.join() #multiprocessing中的queue不能用于pool进程池 #pool中的进程间通信需要使用manager中的queue # def producer(queue): # queue.put("a") # time.sleep(2) # # def consumer(queue): # time.sleep(2) # data = queue.get() # print(data) # # if __name__ == "__main__": # queue = Manager().Queue(10) # pool = Pool(2) # # pool.apply_async(producer, args=(queue,)) # pool.apply_async(consumer, args=(queue,)) # # pool.close() # pool.join() #通过pipe实现进程间通信 #pipe的性能高于queue # def producer(pipe): # pipe.send("bobby") # # def consumer(pipe): # print(pipe.recv()) # # if __name__ == "__main__": # recevie_pipe, send_pipe = Pipe() # #pipe只能适用于两个进程 # my_producer= Process(target=producer, args=(send_pipe, )) # my_consumer = Process(target=consumer, args=(recevie_pipe,)) # # my_producer.start() # my_consumer.start() # my_producer.join() # my_consumer.join() def add_data(p_dict, key, value): p_dict[key] = value if __name__ == "__main__": progress_dict = Manager().dict() from queue import PriorityQueue first_progress = Process(target=add_data, args=(progress_dict, "bobby1", 22)) second_progress = Process(target=add_data, args=(progress_dict, "bobby2", 23)) first_progress.start() second_progress.start() first_progress.join() second_progress.join() print(progress_dict)