celery异步消息队列的使用

1、准备工作

1.1 流程图

2、环境安装

2.1、在Ubuntu中需要安装redis

安装redis
$sudo apt-get update
$sudo apt-get install redis-server
启动redis
$redis-server
连接redis
$redis-cli
$redis-cli -h ip -a
安装Python操作redis的包
pip install redis
重启redis
sudo service reids restart 

安装redis

redis默认绑定的ip为127.0.0.1其他电脑无法访问Ubuntu的redis

重启redis服务 service redis restart

查看绑定端口

在wind上telnet ip  6379 成功说明成功

2.2、安装celery

pip install celery

2、开始使用celery

2、1基本应用

在/home/zbwu103/celery 文件中创建一个tasks.py的任务文件

#task.py 

from celery import Celery

app = Celery('tasks',
             broker='redis://192.168.1.111',
             backend='redis://192.168.1.111'
             #redis://密码@ip
)

@app.task
def add(x,y):
    print("running...",x,y)
    return x+y        

在home/zbwu103/celery的目录启动监听任务

#打印日志的模式运行
celery -A tasks worker --loglevel=info

在开一个终端，到/home/zbwu103/celery用Python进入命令行运行

from tasks import add
t = add.delay(4,5)

#t.result.ready() 查看任务是否完成，完成返回True，未完成返回False
#t.get()  返回完成之后的结果
#t.task_id  返回任务的唯一ID号，可以通过ID查询到任务

上面任务都是在终端上运行，如果终端关闭tasks也会终止。

所以需要任务在后台运行

celery multi stop w1 停止 w1

2.2 、在项目中如何使用celery

from __future__ import absolute_import, unicode_literals
from celery import Celery

app = Celery('my_proj',
             broker='redis://192.168.1.111',
             backend='redis://192.168.1.111',
             include=['myp_roj.tasks'])

app.conf.update(
    result_expires=3600,
)
if __name__ == '__main__':
    app.start()

celery

from __future__ import absolute_import, unicode_literals
import subprocess
from .celery import app

@app.task
def add(x,y):
    return x+y

@app.task
def run_cmd(cmd):
    obj = subprocess.Popen(cmd,shell=True,stdout=subprocess.PIPE,stderr=subprocess.PIPE)
    return obj.stdout.read().decode('utf-8')

tasks.py

在my_proj同级目录启动

查看任务启动情况

ps -ef |grep celery

2.3 、celery 定时任务

celery使用beat来执行celert beat 来实现定时任务

worker定时任务

from celery import Celery
from celery.schedules import crontab

app = Celery('task',
             broker='redis://192.168.1.111',
             backend='redis://192.168.1.111')

@app.on_after_configure.connect
def setup_periodic_tasks(sender, **kwargs):
    # Calls test('hello') every 10 seconds.
    sender.add_periodic_task(10.0, test.s('hello'), name='add every 10')

    # Calls test('world') every 30 seconds
    sender.add_periodic_task(30.0, test.s('world'), expires=10)

    # Executes every Monday morning at 7:30 a.m.
    sender.add_periodic_task(
        crontab(hour=21, minute=26, day_of_week='Sum'),
        test.s('Happy Mondays!'),
    )

@app.task
def test(arg):
    print('runing test.....')
    print(arg)

periodic_task.py

启动定时任务

celery -A periodic_task worker

另外开一个任务调度区不断的检测你的任务计划

celery -A periodic_task beat

2.4、celery和django配置一起使用

在setting同级的目录中新建一个celery.py的文件配置celery基本的配置

from __future__ import absolute_import, unicode_literals
import os
from celery import Celery

# set the default Django settings module for the 'celery' program.
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'CeleryTest.settings')

app = Celery('CeleryTest')

# Using a string here means the worker don't have to serialize
# the configuration object to child processes.
# - namespace='CELERY' means all celery-related configuration keys
#   should have a `CELERY_` prefix.
app.config_from_object('django.conf:settings', namespace='CELERY')

# Load task modules from all registered Django app configs.
app.autodiscover_tasks()

@app.task(bind=True)
def debug_task(self):
    print('Request: {0!r}'.format(self.request))

celery.py

在setting.py同级的目录配置__init__.py

from __future__ import absolute_import, unicode_literals

# This will make sure the app is always imported when
# Django starts so that shared_task will use this app.
from .celery import app as celery_app

__all__ = ['celery_app']

__init__.py

在APP的目录里面新建一个tasks.py的任务来填写任务

#app01/tasks.py
# Create your tasks here
from __future__ import absolute_import, unicode_literals
from celery import shared_task
import time

@shared_task
def add(x, y):
    print("running task add,我是windows ")
    time.sleep(1)
    return x + y

@shared_task
def mul(x, y):
    return x * y

@shared_task
def xsum(numbers):
    return sum(numbers)

tasks.py

从views中调用任务

/app01/view.py
from django.shortcuts import render,HttpResponse
from  app01 import tasks
from celery.result import AsyncResult

def index(request):

    res = tasks.add.delay(5,999)

    print("res:",res)
    print(res.status)
    # import pdb
    # pdb.set_trace()
    return HttpResponse(res.task_id)

def task_res(request):
    #通过ID获取结果
    result = AsyncResult(id="be4933c0-ed9b-4a04-ade8-79f4c57cfc74")

    #return HttpResponse(result.get())
    return HttpResponse(result.status)

views.py

2.5、在django中使用定时的任务

在Ubuntu中安装django-celery-beat插件

pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple django-celery-beat

在setting中增加APP

’‘django_celery_beat",

使用Python manage.py migrate 生成表结构

直接可以在django的admin配置任务

之后在Ubuntu中启动celery worker

celery -A CeleryTest worker -l info 

启动调度器来监控定时任务

celery -A CeleryTest beat -l info -S django

注意，经测试，每添加或修改一个任务，celery beat都需要重启一次，要不然新的配置不会被celery beat进程读到