Celery分布式任务队列基本使用

langy1990

2024-07-03 帮助1人

Celery基本概念

Broker

broker是一个消息传输的中间件每当程序调用celery的异步任务的时候会向broker传递消息而后celery的worker将会取到消息

broker的实现方案有 redis rabbitmq 数据库

Backend

backend是用来存储celery执行任务的当前状态和最终结果

worker

具体执行代码的基础单元负责从rabbitmq或者redis中拉取任务执行可以在不同的主机上启动worker 实现分布式执行

beat

负责定时或者循环的向redis等broker中写入任务以便让worker从broker中获取任务执行两者配合实现celery定时任务

Celery基础操作

pip install celery

[root@node3 jade]# yum install redis
[root@node3 jade]# systemctl start redis

[root@node3 jade]# vi tasks.py

from celery import Celery
app=Celery('tasks',broker='redis://localhost',backend='redis://localhost')


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

本机启动worker  tasks代表的当前目录下的tasks.py文件
[root@node3 jade]# celery -A tasks worker --loglevel=info


调用
>>> from tasks import add
>>> add.delay(4,5)
<AsyncResult: f1d84db4-91dc-4603-99af-c3047aaa32c4>
>>> 

t=add.delay(4,5)
t.get()             同步获取结果
t.ready()           检查任务是否完成
t.get(timeout=1)    设置获取结果的超时时间
t.get(propagate=False) 如果执行方法出错 不触发异常 只显示异常结果
t.traceback            输出错误详细信息

View Code

1.在项目的根目录下创建一个目录celery_pro目录
[root@node3 jade]# ls
appconf     comlib      docs           jadehare.log  media         tools
audit       cron        elk            jobs          monitor  requirements.txt
celery_pro  db.sqlite3  jadehare       logcenter     navi     static
cmdb        deploy      jadehare.conf  manage.py     portals  templates
[root@node3 jade]# cd celery_pro/
  2.在celery_pro目录下创建两个py文件
[root@node3 celery_pro]# ls
celery.py  tasks.py

vi celery.py

from __future__ import absolute_import, unicode_literals
from celery import Celery

app = Celery('proj',
             broker='redis://localhost',
             backend='redis://localhost',
             include=['celery_pro.tasks'])

# Optional configuration, see the application user guide.
app.conf.update(
    result_expires=3600,
)

if __name__ == '__main__':
    app.start()

vi tasks.py

from __future__ import absolute_import, unicode_literals
from .celery import app

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

@app.task
def mul(x,y):
        print("running jianfa.....",x,y)
        return x-y

@app.task
def jihe(x,y):
        import time
        time.sleep(6)
        print("0099990000000")

启动celery 在项目的根目录下执行  celery_pro表示刚才上面创建的目录
[root@node3 jade]# celery -A celery_pro worker -l info
/root/.pyenv/versions/3.5.3/envs/jade/lib/python3.5/site-packages/celery/platforms.py:795: RuntimeWarning: You're running the worker with superuser privileges: this is
absolutely not recommended!

[tasks]
  . celery_pro.tasks.add
  . celery_pro.tasks.jihe
  . celery_pro.tasks.mul

后台启动celery worker
[root@node3 jade]# celery multi start w1 -A celery_pro -l info
 celery multi v4.1.0 (latentcall)
  > Starting nodes...
  > w1@node3: OK

重启worker
  celery multi restart w1 w2 -A celery_pro

可以在不同主机上启动celery的worker 只需要这些主机都能连接到redis broker和redis backend  这样就实现了celery的分布式执行


调用celery 在项目的根目录下
 [root@node3 ~]# cd /mnt/hgfs/jade
 [root@node3 jade]# python
Python 3.5.3 (default, Sep  2 2018, 15:29:35) 
[GCC 4.8.5 20150623 (Red Hat 4.8.5-28)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from celery_pro import tasks
>>> t = tasks.add.delay(2,5)
>>> t.get()
7

celery配置和任务分离

[root@node3 celery_pro]# vi celery.py 
from __future__ import absolute_import, unicode_literals
from celery import Celery

app = Celery('proj',
             broker='redis://localhost',
             backend='redis://localhost',
             include=['celery_pro.tasks','celery_pro.periodic_task'])

# Optional configuration, see the application user guide.
app.conf.update(
    result_expires=3600,
)

if __name__ == '__main__':
    app.start()


[root@node3 celery_pro]# vi periodic_task.py

from __future__ import absolute_import, unicode_literals
from .celery import app

@app.on_after_configure.connect
def setup_periodic_tasks(sender, **kwargs):
    # Calls test('hello') every 10 seconds.
    #test表示下面定义的函数
    #s('hello') 表示给test函数传递的参数
    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=7, minute=30, day_of_week=1),
        test.s('Happy Mondays!'),
    )

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


启动beat
[root@node3 jade]# celery -A celery_pro.periodic_task beat -l debug

启动worker
 [root@node3 jade]# celery -A celery_pro worker -l info

 [2018-10-09 19:51:45,939: WARNING/ForkPoolWorker-4] hello
[2018-10-09 19:51:45,951: INFO/MainProcess] Received task: celery_pro.periodic_task.test[f8d493df-a167-40d6-962e-2c74814443d4]   expires:[2018-10-09 11:51:51.135272 00:00]
[2018-10-09 19:51:45,951: INFO/ForkPoolWorker-4] Task celery_pro.periodic_task.test[aa34fad3-7b03-4524-9075-5b3caaf0ae4e] succeeded in 0.0125010800002201s: None

celery定时任务

vi celery.py

app.conf.beat_schedule = {
    'add-every-5-seconds': {
        'task': 'celery_pro.tasks.add',
        'schedule': 5.0,
        'args': (16, 16)
    },
}



vi celery.py
from celery.schedules import crontab
 
app.conf.beat_schedule = {
    # Executes every Monday morning at 7:30 a.m.
    'add-every-monday-morning': {
        'task': 'celery_pro.tasks.add',
        'schedule': crontab(hour=7, minute=30, day_of_week=1),
        'args': (16, 16),
    },
}


重启beat
  celery -A celery_pro.periodic_task beat -l debug

不需要重启worker便可直接生效

复杂定时任务配置

Celery普通task集成到django

[root@node3 jadehare]# vi settings.py
#Celery 设置
CELERY_ENABLE_UTC = False
CELERY_BROKER_URL = 'redis://127.0.0.1:6379/0'
CELERY_ACCEPT_CONTENT = ['json']
CELERY_TASK_SERIALIZER = 'json'
CELERY_RESULT_BACKEND = 'django-db'
#CELERY_RESULT_BACKEND='redis://127.0.0.1:6379/1'
CELERY_TIMEZONE = 'Asia/Shanghai'
#防止内存溢出
CELERYD_MAX_TASKS_PER_CHILD = 3


INSTALLED_APPS = [
        'django_celery_results',
        'django_celery_beat',
]

settings.py

[root@node3 jadehare]# ls
celery.py  __init__.py   settings.py   urls.py  views.py  wsgi.py
[root@node3 jadehare]# vi celery.py 
#! /usr/bin/env python
# -*- coding: utf-8 -*-

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

# set the default Django settings module for the 'celery' program.
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'jadehare.settings')
app = Celery('jadehare')

# redis connect code
#BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
#config = ConfigParser.ConfigParser()
#config.read(os.path.join(BASE_DIR, 'adminset.conf'))
#redis_host = config.get('redis', "redis_host")
#redis_port = config.get("redis", "redis_port")
#redis_db = config.get('redis', "redis_db")
#redis_password = config.get('redis', "redis_password")
#redis_port = config.get("redis", "redis_port")
#redis_db = config.get('redis', "redis_db")
#redis_password = config.get('redis', "redis_password")
from celery import Celery
#import configparser

# set the default Django settings module for the 'celery' program.
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'jadehare.settings')
app = Celery('jadehare')

# redis connect code
#BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
#config = ConfigParser.ConfigParser()
#config.read(os.path.join(BASE_DIR, 'adminset.conf'))
#redis_host = config.get('redis', "redis_host")
#redis_port = config.get("redis", "redis_port")
#redis_db = config.get('redis', "redis_db")
#redis_password = config.get('redis', "redis_password")
#if redis_password:
#    app.conf.broker_url = 'redis://:{0}@{1}:{2}/{3}'.format(redis_password, redis_host, redis_port, redis_db)
#else:
#    app.conf.broker_url = 'redis://{0}:{1}/{2}'.format(redis_host, redis_port, redis_db)

# Using a string here means the worker doesn't have to serialize
# the configuration object to child processes.
# - namespace='CELERY' means all celery-related configuration keys
#   should have a `CELERY_` prefix.
#app.conf.broker_transport_options = {'visibility_timeout': 3600}
#app.conf.result_backend = 'redis://127.0.0.1:6379/0'
app.config_from_object('django.conf:settings', namespace='CELERY')


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

celery.py

[root@node3 jadehare]# vi __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

在任何一个app下添加tasks.py文件 这个文件名称必须叫tasks.py
[root@node3 jade]# pwd
/mnt/hgfs/jade
[root@node3 jade]# cd navi/
[root@node3 navi]# vi tasks.py 

from __future__ import absolute_import, unicode_literals
from celery import shared_task


@shared_task
def add_navi(x, y):
    return x   y

tasks.py

[root@node3 jade]# pwd
/mnt/hgfs/jade
[root@node3 jade]# celery -A jadehare worker -l info
/root/.pyenv/versions/3.5.3/envs/jade/lib/python3.5/site-packages/celery/platforms.py:795: RuntimeWarning: You're running the worker with superuser privileges: this is
absolutely not recommended!

Please specify a different user using the -u option.

User information: uid=0 euid=0 gid=0 egid=0

  uid=uid, euid=euid, gid=gid, egid=egid,
 
 -------------- celery@node3 v4.1.0 (latentcall)
---- **** ----- 
--- * ***  * -- Linux-3.10.0-862.11.6.el7.x86_64-x86_64-with-centos-7.5.1804-Core 2018-10-10 08:49:14
-- * - **** --- 
- ** ---------- [config]
- ** ---------- .> app:         jadehare:0x7f575ac00710
- ** ---------- .> transport:   redis://127.0.0.1:6379/0
- ** ---------- .> results:     
- *** --- * --- .> concurrency: 4 (prefork)
-- ******* ---- .> task events: OFF (enable -E to monitor tasks in this worker)
--- ***** ----- 
 -------------- [queues]
                .> celery           exchange=celery(direct) key=celery
                

[tasks]
  . appconf.tasks.deploy
  . appconf.tasks.getadminstatus
  . appconf.tasks.getserverstatus
  . appconf.tasks.geturlstatus
  . appconf.tasks.rollback
  . appconf.tasks.task_appconf_updata
  . appconf.tasks.task_nginxconf_updata
  . appconf.tasks.task_restartapp
  . appconf.tasks.task_stopapp
  . cmdb.tasks.add
  . cmdb.tasks.mul
  . cmdb.tasks.xsum
  . jadehare.celery.debug_task
  . navi.tasks.add_navi

启动worker

[root@node3 jadehare]# pwd
/mnt/hgfs/jade/jadehare

[root@node3 jadehare]# vi urls.py 

urlpatterns = [
    url(r'celery_call/',views.celery_call),
    url(r'celery_back/',views.celery_back),

django的urls.py

[root@node3 jadehare]# vi views.py 

from django.shortcuts import redirect,HttpResponse
from navi import tasks  导入某个app下面的tasks模块文件
from celery.result import AsyncResult


def celery_call(request):
        t=tasks.add.delay(10,20)
        return HttpResponse(t.id)

def celery_back(request):
        task_id = request.GET.get("id")
        res = AsyncResult(id=task_id)
        if res.ready():
                return HttpResponse(res.get())
        else:
                return HttpResponse(res.ready())



http://192.168.11.136:8000/celery_call/
http://192.168.11.136:8000/celery_back/?id=07bd41b6-432b-497d-9dd1-bda8df775e34

django的views.py

Celery定时任务集成到django

[root@node3 jadehare]# pip install django-celery-beat

INSTALLED_APPS = [
        'django.contrib.admin',
        'django.contrib.auth',
        'django.contrib.contenttypes',
        'django.contrib.sessions',
        'django.contrib.messages',
        'django.contrib.staticfiles',
        'django_celery_results',
        'django_celery_beat'
]

settings.py

配置django

学新通

启动beat

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

[root@node3 jade]# celery -A jadehare beat -l info -S django

启动worker

[root@node3 jade]# celery -A jadehare worker -l info

这篇好文章是转载于：学新通技术网

Celery分布式任务队列基本使用

Celery基本概念

Celery基础操作

Celery普通task集成到django

Celery定时任务集成到django

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