python-day37(正式学习)

前景回顾

抢票系统的代码优化，使用了Lock类

from multiprocessing import Process,Lock
import os,time,json

with open('user', 'w', encoding='utf-8')as f:
    dic={'count':2}
    json.dump(dic,f)

def search():
    with open('user','r',encoding='utf-8')as f:
        data=json.load(f)
        print(data.get('count'))

def get():
    with open('user','r',encoding='utf-8')as f:
        data = json.load(f)
    if data['count'] > 0:
        data['count'] -= 1
        with open('user','w',encoding='utf-8')as f:
                json.dump(data,f)
                print('success')
                time.sleep(1)
    else:
        print('票已售空')
def piao(lock):
    search()
    lock.acquire()
    get()
    lock.release()

if __name__ == '__main__':
    lock=Lock()
    for i in range(5):
        p=Process(target=piao,args=(lock,))
        p.start()

队列

1

from multiprocessing import Queue,Process

q=Queue()
q.put(1)
print(q)
data=q.get()
print(data)
data=q.get()
print(data) #默认会一直等待拿值
q.put(5)

2

from multiprocessing import Queue,Process

q=Queue(4)
q.put(1)
q.put(5)
q.put(5)
q.put(5)
q.put(5)    #此处队列满了，就会成阻塞状态
q.get()
q.get()

3

from multiprocessing import Queue,Process

q=Queue(4)
q.put(1)
q.put(5)
q.put(5)
q.put(5)
q.put(5,block=True,timeout=3)    #此处队列满了，就会成阻塞状态,block为等待状态，timeout为等待时间，等不到就报错
q.get()
q.get()

4

from multiprocessing import Queue,Process

q=Queue(4)
q.put(1)
q.get()
q.get(block=True,timeout=3) #队列已被取空，此时再取就会阻塞，block为阻塞状态，timeout为阻塞时间

5

from multiprocessing import Queue,Process

q=Queue(1)
q.put(1)
q.put_nowait(5) #队列已满，此时再存就会阻塞，相当于put的默认block为False

生产者消费者模型

版本一

from multiprocessing import Queue,Process
import time

def produce(q,name,msg):
    for i in range(3):
        q.put(msg+str(i))
        print(f'{name}生产了{msg+str(i)}')
        time.sleep(1)
    q.put(None)				#用None来终止消费者

def cost(q,name):
    while True:
        msg=q.get()
        if msg==None:
            break
        print(f'{name}吃了{msg}')
        time.sleep(1)

if __name__ == '__main__':
    q=Queue()
    p1=Process(target=produce,args=(q,'wind','card'))
    p2=Process(target=produce,args=(q,'nick','niunai'))
    # p1=Process(target=Process,args=(q,'wind','card'))
    c1=Process(target=cost,args=(q,'chanyuli'))
    c2=Process(target=cost,args=(q,'zhongshifu'))
    p1.start()
    p2.start()
    c1.start()
    c2.start()

版本二

from multiprocessing import Queue,Process,JoinableQueue
import time

def produce(q,name,msg):
    for i in range(3):
        q.put(msg+str(i))
        print(f'{name}生产了{msg+str(i)}')
        time.sleep(1)


def cost(q,name):
    while True:
        msg=q.get()
        q.task_done()
        if msg==None:
            break
        print(f'{name}吃了{msg}')
        time.sleep(1)

if __name__ == '__main__':
    q=JoinableQueue()
    p1=Process(target=produce,args=(q,'wind','card'))
    p2=Process(target=produce,args=(q,'nick','niunai'))
    # p1=Process(target=Process,args=(q,'wind','card'))
    c1=Process(target=cost,args=(q,'chanyuli'))
    c2=Process(target=cost,args=(q,'zhongshifu'))
    c1.daemon=True
    c2.daemon=True
    p1.start()
    p2.start()
    c1.start()
    c2.start()
    p1.join()
    p2.join()
    q.join()