from multiprocessing import Process, Queue, Pool, Manager, Pipe
# 注意线程间的通信,使用的queue.Queue
# from queue import Queue
import time


# 1. 使用multiprocessing.Queue可以在进程间通信

# 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)
#   p = Process(target=producer, args=(queue,))
#   c = Process(target=consumer, args=(queue,))
#   p.start()
#   c.start()
#   p.join()
#   c.join()


# 2. 使用共享全局变量,在多进程间通信(结论: 不行)
# def producer(a):
#   a += 1
#   time.sleep(2)
#
#
# def consumer(a):
#   time.sleep(2)
#   print(a)
#
# if __name__ == '__main__':
#   a = 1
#   p = Process(target=producer, args=(a,))
#   c = Process(target=consumer, args=(a,))
#   p.start()
#   c.start()
#   p.join()
#   c.join()


# 3. multiprocessing.Queue不能用于multiprocessing.Pool进程池创建的进程间进行通信
# def producer(queue):
#   queue.put('A')
#   time.sleep(2)
#
#
# def consumer(queue):
#   time.sleep(2)
#   data = queue.get()
#   print("consumer:%s" % data)
#
#
# if __name__ == '__main__':
#   # queue = Queue(10) # 这个是使用multiprocessing.Queue,无效
#   queue = Manager().Queue(10) # 这个是使用multiprocessing.Manager.Queue, 可以
#   pool = Pool(2)
#   pool.apply_async(producer, args=(queue,))
#   pool.apply_async(consumer, args=(queue,))
#   pool.close()
#   pool.join()


# 4.通过Pipe进行线程间的通信, pipe进程间通信的性能高于Queue
# def producer(pipe):
#   pipe.send('admin')
#
#
# def consumer(pipe):
#   data = pipe.recv()
#   print("consumer:%s" % data)
#
#
# if __name__ == '__main__':
#   receive_pipe, send_pipe = Pipe()
#   """Pipe只能适应于两个进程间的通信"""
#   p = Process(target=producer, args=(send_pipe,))
#   c = Process(target=consumer, args=(receive_pipe,))
#   p.start()
#   c.start()
#   p.join()
#   c.join()


# 5. 进程间通信的其它方式

def add_data(p_dict, key, value):
  p_dict[key] = value

if __name__ == '__main__':
  progress_dict = Manager().dict() #Manager()类中提供的数据结构都能够做到进程的通信
  first_progress = Process(target=add_data, args=(progress_dict, 'name', 'admin',))
  second_progress = Process(target=add_data, args=(progress_dict, 'age', 45,))
  first_progress.start()
  second_progress.start()
  first_progress.join()
  second_progress.join()
  print(progress_dict) #{'age': 45, 'name': 'admin'}