案例一、
from celery import Celery
broker = "redis://192.168.48.136:6379/5"
backend = "redis://192.168.48.136:6379/6"
app = Celery("ajing", broker=broker, backend=backend)
@app.task
def add(x, y):
time.sleep(5)
return x+y
案例二、
'''
一个是生产者
一个是消费者
创建一个队列 q = Queue()
发消息： q.put()
收消息： data = q.get()
'''
from multiprocessing import Queue, Pipe
from threading import Thread
import time
def produce(q):
print("start produce")
for i in range(10):
q.put(i)
print("produce has produced value {0}".format(i))
time.sleep(0.3)
print("end produce")
def custome(q):
print("start custorme")
while 1:
data = q.get()
print("custormer has get value {0}".format(data))
if __name__ == '__main__':
q = Queue()
p = Thread(target=produce, args=(q,))
c = Thread(target=custome, args=(q, ))
p.start()
c.start()
# Pipe
案例三、
'''
Pipe的方法返回一个tuple (conn1, conn2)
Pipe方法还有一个参数duplex参数，如果deplex=True,叫双工模式
如果deplex=False conn1只负责接受， conn2只负责发消息
发消息： send
收消息： recv
关闭管道： close
'''
import time
import multiprocessing
from multiprocessing import Process
def proc1(pipe):
for i in range(10):
print("send {0}".format(i))
pipe.send(i)
time.sleep(0.1)
def proc2(pipe):
n = 10
while n:
print("proc2 recv: {0}".format(pipe.recv()))
n -= 1
if __name__ == '__main__':
(p1, p2) = multiprocessing.Pipe(duplex=False)
pr = Process(target=proc1, args=(p2,))
cu = Process(target=proc2, args=(p1,))
pr.start()
cu.start()
案例四、
'''
Queue(maxsize=0) 指定队列大小，0表示无限
q.qsize()
'''
from Queue import Queue
q = Queue()
q.qsize() #返回当前队列的空间
q.empty() #判断当前队列是否为空
q.full() #判断当前队列是否满
q.put() #放消息
q.get() #获取消息
q.task_done() #接受消息的线程调用该函数来说明消息对应的任务是否已经完成
q.join() #等待队列为空，在执行别的操作
案例五、
'''
pip install celery
pip install redis
安装redis，并启动redis
'''
import time
from ajing import add
re = add.delay(10, 20)
print(re.task_id)
print(re)
print(re.status)
time.sleep(2)
print(re.status)
print(re.get(timeout=1))
print(re.result)