进程---管道、数据共享Manager、进程池和回调函数（重要）（六）

#   管道

from multiprocessing import Pipe,Process

def func(conn1,conn2):    conn2.close()   #子进程只关闭conn2时会抛出一个EOFError（没数据可取时recv)，根据EOFError结束循环    while True:        try :            msg = conn1.recv()#不判断话会阻塞            print(msg)        except EOFError:            conn1.close()            break

if __name__ == ‘__main__‘:    conn1, conn2 = Pipe()    Process(target=func,args = (conn1,conn2)).start()    conn1.close()    for i in range(20):        conn2.send(‘吃了么‘)    conn2.close()  #主进程Conn1和Conn2全部关闭，不会影响子进程的Conn1和Conn2

管道实现生产者消费者模型

# from multiprocessing import Lock,Pipe,Process# def producer(con,pro,name,food):#     con.close()#     for i in range(100):#         f = ‘%s生产%s%s‘%(name,food,i)#         print(f)#         pro.send(f)#     pro.send(None)#     pro.send(None)#     pro.send(None)#     pro.close()## def consumer(con,pro,name,lock):#     pro.close()#     while True:#             lock.acquire()#             food = con.recv()#             lock.release()#             if food is None:#                 con.close()#                 break#             print(‘%s吃了%s‘ % (name, food))# if __name__ == ‘__main__‘:#     con,pro = Pipe()#     lock= Lock()#     p = Process(target=producer,args=(con,pro,‘egon‘,‘泔水‘))#     c1 = Process(target=consumer, args=(con, pro, ‘alex‘,lock))#     c2 = Process(target=consumer, args=(con, pro, ‘bossjin‘,lock))#     c3 = Process(target=consumer, args=(con, pro, ‘wusir‘,lock))#     c1.start()#     c2.start()#     c3.start()#     p.start()#     con.close()#     pro.close()

# from multiprocessing import Process,Pipe,Lock## def consumer(produce, consume,name,lock):#     produce.close()#     while True:#         lock.acquire()#         baozi=consume.recv()#         lock.release()#         if baozi:#             print(‘%s 收到包子:%s‘ %(name,baozi))#         else:#             consume.close()#             break## def producer(produce, consume,n):#     consume.close()#     for i in range(n):#         produce.send(i)#     produce.send(None)#     produce.send(None)#     produce.close()## if __name__ == ‘__main__‘:#     produce,consume=Pipe()#     lock = Lock()#     c1=Process(target=consumer,args=(produce,consume,‘c1‘,lock))#     c2=Process(target=consumer,args=(produce,consume,‘c2‘,lock))#     p1=Process(target=producer,args=(produce,consume,30))#     c1.start()#     c2.start()#     p1.start()#     produce.close()#     consume.close()

# pipe 数据不安全性# IPC# 加锁来控制操作管道的行为 来避免（多人消费同时取一个数据）进程之间争抢数据造成的数据不安全现象

# 队列 进程之间数据安全的# 管道 + 锁

#  进程之间的数据共享

普通正常的进程之间数据是不共享的# from multiprocessing import Manager,Process

# def main(dic):#     dic[‘count‘] -= 1#     print(dic)## if __name__ == ‘__main__‘:#     m = Manager()#     dic=m.dict({‘count‘:100})#     p_lst = []#     p = Process(target=main, args=(dic,))#     p.start()#     p.join()

from multiprocessing import Manager,Process,Lockdef main(dic,lock):    lock.acquire()    dic[‘count‘] -= 1  #这里会出现两个进程同时修改一个数据情况，最后会发现每次次执行count的值不一样，就是因为多进程同时操作一个数据导致的   lock.release()     #，正常理想count值应该是50，为了达到这效果就加锁。虽然加锁在效率会降低，但安全

if __name__ == ‘__main__‘:    m = Manager()    l = Lock()    dic=m.dict({‘count‘:100})    p_lst = []    for i in range(50):        p = Process(target=main,args=(dic,l))        p.start()        p_lst.append(p)    for i in p_lst: i.join()    print(‘主进程‘,dic)

#  进程池1

原文地址：https://www.cnblogs.com/mys6/p/10850226.html