python celery任务分发

Celery是由Python开发的一个简单、灵活、可靠的处理大量任务的分发系统，它不仅支持实时处理也支持任务调度。

python celery任务分发

user：用户程序，用于告知celery去执行一个任务。
broker: 存放任务（依赖RabbitMQ或Redis，进行存储）
worker：执行任务

celery需要rabbitMQ、Redis、Amazon SQS、Zookeeper（测试中）充当broker来进行消息的接收，并且也支持多个broker和worker来实现高可用和分布式。http://docs.celeryproject.org/en/latest/getting-started/brokers/index.html

    Celery version 4.0 runs on
        Python ❨2.7, 3.4, 3.5❩
        PyPy ❨5.4, 5.5❩
    This is the last version to support Python 2.7, and from the next version (Celery 5.x) Python 3.5 or newer is required.
If you&rsquo;re running an older version of Python, you need to be running an older version of Celery:

    Python </span>2.6: Celery series 3.1 <span style="color: #0000ff;">or</span><span style="color: #000000;"> earlier.
    Python </span>2.5: Celery series 3.0 <span style="color: #0000ff;">or</span><span style="color: #000000;"> earlier.
    Python </span>2.4 was Celery series 2.2 <span style="color: #0000ff;">or</span><span style="color: #000000;"> earlier.

Celery </span><span style="color: #0000ff;">is</span> a project with minimal funding, so we don&rsquo;t support Microsoft Windows. Please don&rsquo;t open any issues related to that platform.</pre>

版本和要求

环境准备：

安装rabbitMQ或Redis
见：http://www.cnblogs.com/wupeiqi/articles/5132791.html
安装celery
pip3 install celery

快速上手

import time
from celery import Celery
app = Celery('tasks', broker='redis://192.168.10.48:6379', backend='redis://192.168.10.48:6379')
@app.task
def xxxxxx(x, y):

time.sleep(10)
return x + y

s1.py

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from s1 import xxxxxx
# 立即告知celery去执行xxxxxx任务，并传入两个参数

result = xxxxxx.delay(4, 4)
print(result.id)

s2.py