[python基础] celery beat/task/flower解析

一.Celery 介绍

Celery 是一个强大的分布式任务队列,它可以让任务的执行完全脱离主程序,甚至可以被分配到其他主机上运行。我们通常使用它来实现异步任务( async task )和定时任务( crontab )。 异步任务比如是发送邮件、或者文件上传, 图像处理等等一些比较耗时的操作 ,定时任务是需要在特定时间执行的任务。它的架构组成如下图:

celery架构图

[以上转自]作者:Shyllin 来源:CSDN 原文:https://blog.csdn.net/Shyllin/article/details/80940643?utm_source=copy 版权声明:本文为博主原创文章,转载请附上博文链接!

划重点~

(1). 任务模块:包含异步任务和定时任务。异步任务在业务逻辑中触发被发送到任务队列,定时任务由celery beat周期性的发往任务队列。

(2).celery beat:任务调度器。beat进程会读取配置文件里的内容(celerybeat_schedule里设置),周期性的将配置中到期需要执行的任务发送到任务队列。

(3).消息中间件broker:任务调度队列。接收任务生产者发来的消息任务,存储到队列中。因为celery本身并不提供队列服务,官方推荐rabbitMQ和redis,在这里我们使用redis。

(4).任务执行单元worker:实行任务的处理单元。实时监控消息队列,获取队列调度中的任务,并执行它。

(5).任务结果存储backend:用于任务执行结果的存储,同中间件一样可以用rabbitMQ和redis。

二.代码实🌰:

(1).目录结构

celery_learning

     |----celery_config.py

     |----celery_app.py

     |----tasks.py

   |----test.py
(2)代码:

celery_config.py

#-*-coding=utf-8-*-
from __future__ import absolute_import

from celery.schedules import crontab
# 中间件
BROKER_URL = 'redis://localhost:6379/6'
# 结果存储
CELERY_RESULT_BACKEND = 'redis://:127.0.0.1:6379/5'
# 默认worker队列
CELERY_DEFAULT_QUEUE = 'default'
# 异步任务
CELERY_IMPORTS = (
    "tasks"
)

from datetime import timedelta
# celery beat
CELERYBEAT_SCHEDULE = {
    'add':{
        'task':'tasks.add',
        'schedule':timedelta(seconds=10),
        'args':(1,12)
    }
}

[注] backend一定要在broker之后设置,不然会报错:

ValueError: invalid literal for int() with base 10: '127.0.0.1'

celery_app.py

from __future__ import absolute_import
from celery import Celery

app = Celery('celery_app')
app.config_from_object('celery_config')

tasks.py

from celery_app import app

@app.task(queue='default')
def add(x, y):
    return x + y

@app.task(queue='default')
def sub(x, y):
    return x - y

test.py

import sys, os

# sys.path.append(os.path.abspath('.'))
sys.path.append(os.path.abspath('..'))
from tasks import add

def add_loop():
    ret = add.apply_async((1, 2), queue='default')
    print(type(ret))
    return ret

if __name__ == '__main__':
    ret = add_loop()
    print(ret.get())
    print(ret.status)

三.执行步骤:

(1).异步任务:

终端输入 celery -A celery_app worker -Q default --loglevel=info

执行test.py 

[结果如下]:

python test.py

<class 'celery.result.AsyncResult'>
3
SUCCESS

worker队列

[2018-10-16 15:17:15,173: INFO/MainProcess] Received task: tasks.add[79bfdfc8-d6eb-44b4-b094-4355961d18b3]  
[2018-10-16 15:17:15,193: INFO/ForkPoolWorker-2] Task tasks.add[79bfdfc8-d6eb-44b4-b094-4355961d18b3] succeeded in 0.0133806611411s: 3

(2)定时任务:

终端1输入 celery -A celery_app worker -Q default --loglevel=info

终端2输入 celery -A celery_app beat 

celery beat v4.2.0 (windowlicker) is starting.
__    -    ... __   -        _
LocalTime -> 2018-10-16 15:30:57
Configuration ->
    . broker -> redis://localhost:6379/6
    . loader -> celery.loaders.app.AppLoader
    . scheduler -> celery.beat.PersistentScheduler
    . db -> celerybeat-schedule
    . logfile -> [stderr]@%WARNING
    . maxinterval -> 5.00 minutes (300s)

[结果如下]:

[2018-10-16 15:31:27,078: INFO/MainProcess] Received task: tasks.add[80e5b7a9-f610-47b2-91ae-2de731ee58f2]  
[2018-10-16 15:31:27,089: INFO/ForkPoolWorker-2] Task tasks.add[80e5b7a9-f610-47b2-91ae-2de731ee58f2] succeeded in 0.00957242585719s: 13
[2018-10-16 15:31:37,078: INFO/MainProcess] Received task: tasks.add[3b03d215-139b-4072-856e-b4941c332215]  
[2018-10-16 15:31:37,080: INFO/ForkPoolWorker-3] Task tasks.add[3b03d215-139b-4072-856e-b4941c332215] succeeded in 0.000707183033228s: 13
[2018-10-16 15:31:47,077: INFO/MainProcess] Received task: tasks.add[2ecb1645-5dff-4647-8035-fd1fdf8a4249]  
[2018-10-16 15:31:47,079: INFO/ForkPoolWorker-2] Task tasks.add[2ecb1645-5dff-4647-8035-fd1fdf8a4249] succeeded in 0.000692856963724s: 13
[2018-10-16 15:31:57,079: INFO/MainProcess] Received task: tasks.add[3abac1ce-df1d-4c2f-b08f-3248c054f893]  
[2018-10-16 15:31:57,082: INFO/ForkPoolWorker-3] Task tasks.add[3abac1ce-df1d-4c2f-b08f-3248c054f893] succeeded in 0.00103094079532s: 13

四.celery flower

(1).查看任务历史,任务具体参数,开始时间等信息。

(2).提供图表和统计数据。

(3).实现全面的远程控制功能, 包括但不限于 撤销/终止任务, 关闭重启 worker, 查看正在运行任务。

(4).提供一个 HTTP API , 方便集成。
终端执行:
celery flower --broker=redis://localhost:6379/6

[I 181016 15:41:13 command:139] Visit me at http://localhost:5555
[I 181016 15:41:13 command:144] Broker: redis://localhost:6379/6
[I 181016 15:41:13 command:147] Registered tasks: 
    [u'celery.accumulate',
     u'celery.backend_cleanup',
     u'celery.chain',
     u'celery.chord',
     u'celery.chord_unlock',
     u'celery.chunks',
     u'celery.group',
     u'celery.map',
     u'celery.starmap']

posted @ 2018-10-16 15:46  赞美上帝  阅读(6953)  评论(1编辑  收藏  举报