celery使用

1、定义一个celery 应用  和  其他的任务函数, 放在文件celery_app_task.py中

 

#celery_app_task.py
import celery
import time
# broker='redis://127.0.0.1:6379/2' 不加密码
backend='redis://121.36.209.194:6379/1'  #结果存储在1中 打开reids可视化即可明白
broker='redis://121.36.209.194:6379/2'   #消息中间件,消息中间件放在2中

cel=celery.Celery('test',backend=backend,broker=broker)
#定义要让celery执行的任务,其实就是一个函数,用@cel.task装饰一下
@cel.task
def add(x,y):
    return x+y

2、定义一个add_task.py文件, 通过celery将任务发送到broker消息队列

#add_task.py

import  celery_app_task

rs = celery_app_task.add.delay(1,9)
print(rs)

运行add_task.py共两次, 某一次的执行结果如下:

"D:\Program Files (x86)\python36\python.exe" D:/test0429/add_task.py
032f289b-5a3b-40de-b5de-f58e39f75771

Process finished with exit code 0

 

查看redis中第2个数据库中,是否存放了两个消息队列

root@ecs-s6-medium-2-linux-20191230105810:~# ps aux|grep celery
root      3799  0.1  1.7  98688 34832 pts/3    S+   19:10   0:01 /usr/bin/python3 /usr/local/bin/celery -A celery_app_task worker -l info
root      3803  0.0  1.4  97972 29760 pts/3    S+   19:10   0:00 /usr/bin/python3 /usr/local/bin/celery -A celery_app_task worker -l info
root      4155  0.0  0.0  14428  1000 pts/5    S+   19:24   0:00 grep --color=auto celery
root@ecs-s6-medium-2-linux-20191230105810:~#
root@ecs-s6-medium-2-linux-20191230105810:~#
root@ecs-s6-medium-2-linux-20191230105810:~# kill -9 3799 3803
root@ecs-s6-medium-2-linux-20191230105810:~# ps aux|grep celery
root      4157  0.0  0.0  14428  1036 pts/5    S+   19:24   0:00 grep --color=auto celery
root@ecs-s6-medium-2-linux-20191230105810:~#
root@ecs-s6-medium-2-linux-20191230105810:~#
root@ecs-s6-medium-2-linux-20191230105810:~# docker ps
CONTAINER ID        IMAGE               COMMAND                  CREATED             STATUS              PORTS                    NAMES
da8316ec988d        redis               "docker-entrypoint.s…"   17 minutes ago      Up 17 minutes       0.0.0.0:6379->6379/tcp   cool_galois
root@ecs-s6-medium-2-linux-20191230105810:~# docker exec -it da8316ec988d  /bin/bash
root@da8316ec988d:/data# redis-cli
127.0.0.1:6379> keys *
(empty list or set)
127.0.0.1:6379> select 2
OK
127.0.0.1:6379[2]> keys *
1) "_kombu.binding.celeryev"
2) "_kombu.binding.celery"
3) "_kombu.binding.celery.pidbox"
4) "celery"
127.0.0.1:6379[2]> type celery
list
127.0.0.1:6379[2]> lrange celery 0 -1
1) "{\"body\": \"W1sxLCA5XSwge30sIHsiY2FsbGJhY2tzIjogbnVsbCwgImVycmJhY2tzIjogbnVsbCwgImNoYWluIjogbnVsbCwgImNob3JkIjogbnVsbH1d\", \"content-encoding\": \"utf-8\", \"content-type\": \"application/json\", \"headers\": {\"lang\": \"py\", \"task\": \"celery_app_task.add\", \"id\": \"9ecfa5ac-09e3-4a8b-9b57-2182e05e141d\", \"shadow\": null, \"eta\": null, \"expires\": null, \"group\": null, \"retries\": 0, \"timelimit\": [null, null], \"root_id\": \"9ecfa5ac-09e3-4a8b-9b57-2182e05e141d\", \"parent_id\": null, \"argsrepr\": \"(1, 9)\", \"kwargsrepr\": \"{}\", \"origin\": \"gen7748@wzg\"}, \"properties\": {\"correlation_id\": \"9ecfa5ac-09e3-4a8b-9b57-2182e05e141d\", \"reply_to\": \"7c55c123-b8e2-3010-af48-13bac103e22c\", \"delivery_mode\": 2, \"delivery_info\": {\"exchange\": \"\", \"routing_key\": \"celery\"}, \"priority\": 0, \"body_encoding\": \"base64\", \"delivery_tag\": \"82573b1d-5e6f-40c5-a48e-79efaf117b7d\"}}"
127.0.0.1:6379[2]>
127.0.0.1:6379[2]>
127.0.0.1:6379[2]> lrange celery 0 -1
1) "{\"body\": \"W1sxLCA5XSwge30sIHsiY2FsbGJhY2tzIjogbnVsbCwgImVycmJhY2tzIjogbnVsbCwgImNoYWluIjogbnVsbCwgImNob3JkIjogbnVsbH1d\", \"content-encoding\": \"utf-8\", \"content-type\": \"application/json\", \"headers\": {\"lang\": \"py\", \"task\": \"celery_app_task.add\", \"id\": \"032f289b-5a3b-40de-b5de-f58e39f75771\", \"shadow\": null, \"eta\": null, \"expires\": null, \"group\": null, \"retries\": 0, \"timelimit\": [null, null], \"root_id\": \"032f289b-5a3b-40de-b5de-f58e39f75771\", \"parent_id\": null, \"argsrepr\": \"(1, 9)\", \"kwargsrepr\": \"{}\", \"origin\": \"gen5980@wzg\"}, \"properties\": {\"correlation_id\": \"032f289b-5a3b-40de-b5de-f58e39f75771\", \"reply_to\": \"65d63650-97c5-39b2-ade5-f4554772ca6b\", \"delivery_mode\": 2, \"delivery_info\": {\"exchange\": \"\", \"routing_key\": \"celery\"}, \"priority\": 0, \"body_encoding\": \"base64\", \"delivery_tag\": \"72429ecb-2e01-4531-997e-534d67892829\"}}"
2) "{\"body\": \"W1sxLCA5XSwge30sIHsiY2FsbGJhY2tzIjogbnVsbCwgImVycmJhY2tzIjogbnVsbCwgImNoYWluIjogbnVsbCwgImNob3JkIjogbnVsbH1d\", \"content-encoding\": \"utf-8\", \"content-type\": \"application/json\", \"headers\": {\"lang\": \"py\", \"task\": \"celery_app_task.add\", \"id\": \"9ecfa5ac-09e3-4a8b-9b57-2182e05e141d\", \"shadow\": null, \"eta\": null, \"expires\": null, \"group\": null, \"retries\": 0, \"timelimit\": [null, null], \"root_id\": \"9ecfa5ac-09e3-4a8b-9b57-2182e05e141d\", \"parent_id\": null, \"argsrepr\": \"(1, 9)\", \"kwargsrepr\": \"{}\", \"origin\": \"gen7748@wzg\"}, \"properties\": {\"correlation_id\": \"9ecfa5ac-09e3-4a8b-9b57-2182e05e141d\", \"reply_to\": \"7c55c123-b8e2-3010-af48-13bac103e22c\", \"delivery_mode\": 2, \"delivery_info\": {\"exchange\": \"\", \"routing_key\": \"celery\"}, \"priority\": 0, \"body_encoding\": \"base64\", \"delivery_tag\": \"82573b1d-5e6f-40c5-a48e-79efaf117b7d\"}}"
127.0.0.1:6379[2]>

 

3、在任意一个linux服务器上也存放一个celery_app_task.py脚本, 名字必须跟celery添加任务到消息队列时倒入的文件名称一致

即,跟下面import的文件名一致

import  celery_app_task

rs = celery_app_task.add.delay(1,9)
print(rs)

然后执行celery 启动worker的命令:

root@ecs-s6-medium-2-linux-20191230105810:/home# celery -A celery_app_task worker -l info
/usr/local/lib/python3.6/dist-packages/celery/platforms.py:801: RuntimeWarning: You're running the worker with superuser privileges: this is
absolutely not recommended!

Please specify a different user using the --uid option.

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

  uid=uid, euid=euid, gid=gid, egid=egid,

 -------------- celery@ecs-s6-medium-2-linux-20191230105810 v4.4.2 (cliffs)
--- ***** -----
-- ******* ---- Linux-4.15.0-65-generic-x86_64-with-Ubuntu-18.04-bionic 2020-04-30 19:27:11
- *** --- * ---
- ** ---------- [config]
- ** ---------- .> app:         test:0x7fd1c4f49780
- ** ---------- .> transport:   redis://121.36.209.194:6379/2
- ** ---------- .> results:     redis://121.36.209.194:6379/1
- *** --- * --- .> concurrency: 1 (prefork)
-- ******* ---- .> task events: OFF (enable -E to monitor tasks in this worker)
--- ***** -----
 -------------- [queues]
                .> celery           exchange=celery(direct) key=celery


[tasks]
  . celery_app_task.add

[2020-04-30 19:27:11,613: INFO/MainProcess] Connected to redis://121.36.209.194:6379/2
[2020-04-30 19:27:11,640: INFO/MainProcess] mingle: searching for neighbors
[2020-04-30 19:27:12,692: INFO/MainProcess] mingle: all alone
[2020-04-30 19:27:12,749: INFO/MainProcess] celery@ecs-s6-medium-2-linux-20191230105810 ready.
[2020-04-30 19:27:12,828: INFO/MainProcess] Received task: celery_app_task.add[9ecfa5ac-09e3-4a8b-9b57-2182e05e141d]
[2020-04-30 19:27:12,837: INFO/MainProcess] Received task: celery_app_task.add[032f289b-5a3b-40de-b5de-f58e39f75771]
[2020-04-30 19:27:12,842: INFO/ForkPoolWorker-1] Task celery_app_task.add[9ecfa5ac-09e3-4a8b-9b57-2182e05e141d] succeeded in 0.011989665000328387s: 10
[2020-04-30 19:27:12,846: INFO/ForkPoolWorker-1] Task celery_app_task.add[032f289b-5a3b-40de-b5de-f58e39f75771] succeeded in 0.0030052060001253267s: 10

woker启动后,两个任务被执行了; redis中的两个任务也变成空了;

 

4、在python脚本中查看执行的结果

#result.py
from celery.result import AsyncResult
from celery_app_task import cel

async = AsyncResult(id="2f0207eb-b6aa-42cc-84d2-2450ececbb18", app=cel)

if async.successful(): #如果执行成功,获取到结果
    result = async.get()
    print(result)
    # result.forget() # 将结果删除
elif async.failed():
    print('执行失败')
elif async.status == 'PENDING':
    print('任务等待中被执行')
elif async.status == 'RETRY':
    print('任务异常后正在重试')
elif async.status == 'STARTED':
    print('任务已经开始被执行')

运行结果如下:

"D:\Program Files (x86)\python36\python.exe" D:/test0429/result.py
10

Process finished with exit code 0

 

posted on 2020-04-30 19:33  芦苇草鱼  阅读(232)  评论(2编辑  收藏  举报