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安装celery

sudo pip install celery

实例化 celery

from celery import Celery
app = Celery("testapp")
# 导入配置
app.config_from_object('celery_tasks.config')
 
# 自动添加任务
app.autodiscover_tasks(["celery_tasks.test","celery_tasks.test2"])

简单配置

# 任务队列的地址
broker_url = "redis://127.0.0.1/14"
# 任务处理结果的保存地址[如果不需要接收任务处理结果,那么,可以不设置下面]
result_backend = "redis://127.0.0.1/15"

文件目录如下

.
├── config.py
├── main.py
├── test
│  └── tasks.py
└── test2
  ├── __init__.py
  └── tasks.py

一个应用一个文件夹

异步任务的文件名必须是tasks.py

在需要执行该任务的地方导入该任务

from celery_tasks.test.tasks import test
from celery_tasks.test2.tasks import test as test2
 
test_id = test.delay()
test2_id = test2.delay()
 
print(test_id)
print(test2_id)

调用该异步任务会马上放回一个id,执行结果可以在result_backend中通过id找到

/home/python/.virtualenvs/kol_site_py3/bin/python /home/python/projects/supervisor/supervisor/celery_tasks/test.py
a6e13745-c05b-496d-bbbe-2b636f84009c
d92d50b4-0ba1-4b05-9e96-eeb92a854929
 
Process finished with exit code 0
127.0.0.1:6379[15]> keys *
 1) "celery-task-meta-2a9c0a4b-5b40-4121-9986-a8430fc6b235"
 2) "celery-task-meta-0f16e227-393f-48ea-b41b-3419df84528e"
 3) "celery-task-meta-fbf31a20-6eee-4298-8a91-214d2e5c9399"
 4) "celery-task-meta-61f012c0-bde1-4344-9e1c-b5e8a7b93902"
 5) "celery-task-meta-074a659f-d76f-4818-8516-f098d1b900ed"
 6) "celery-task-meta-8a89c4db-f2e2-484b-94ee-e1af9911c69f"
 7) "celery-task-meta-0012966d-e8fd-483b-b8ac-d160d65c8221"
 8) "celery-task-meta-f97a452d-3812-4950-bfd9-02ff9e69a4b2"
 9) "celery-task-meta-4bebe710-7725-43f5-b0f7-9a35b57ba3b1"
10) "celery-task-meta-4b1cca23-31c3-4c82-a99f-bbe306846191"
11) "celery-task-meta-4cdf3a68-7df4-4bdf-8f54-abe6be83df3a"
12) "celery-task-meta-d92d50b4-0ba1-4b05-9e96-eeb92a854929"
13) "celery-task-meta-17265693-ba36-4f6c-80c8-d89a52f549f7"
14) "celery-task-meta-d62bbf16-6469-40a7-bc25-61b553014d76"
15) "celery-task-meta-4cca0f47-2f2d-45e6-8341-52264e50d969"
16) "celery-task-meta-1fd1e52a-00e1-486a-a224-36bd0fbb5d4a"
17) "celery-task-meta-af3b9536-91a6-4ae3-ab9b-59755bfb4883"
18) "celery-task-meta-b5710e2a-1905-44fd-8b11-4d7057113291"
19) "celery-task-meta-bebeb902-cce1-4edb-bdac-734ed6dc16ae"
20) "celery-task-meta-2771b961-694f-4727-9b19-07928834475e"
21) "celery-task-meta-8c683476-5cec-4933-8370-73793d656e23"
22) "celery-task-meta-6c8e6763-a416-4c02-9689-a0bb38bf26a6"
23) "celery-task-meta-7a4edb71-b13b-4f0f-b882-408716bb3ba9"
24) "celery-task-meta-4e368ca3-f686-4215-aed7-f0c6463cfac9"
25) "celery-task-meta-757f196d-c377-4f38-982d-700fa4f45c6b"
26) "celery-task-meta-094ea32e-5cf8-41c5-bf63-fb629e0e1e67"
27) "celery-task-meta-2e1f2188-0806-41f1-8eb8-4a0f73ec2aca"
28) "celery-task-meta-fd7e8fea-c738-4d49-b13d-c5d782eeaa96"
29) "celery-task-meta-e476f036-7192-4687-b9b7-c6a06556b4c3"
30) "celery-task-meta-2463c15f-5903-4381-8646-1b2aa6418ca0"
31) "celery-task-meta-a6e13745-c05b-496d-bbbe-2b636f84009c"
32) "celery-task-meta-f4f2d940-3e16-4d78-a0c4-3766eb91c908"
33) "celery-task-meta-5a1eaba8-0675-4e82-aedc-fee801ff31ef"
127.0.0.1:6379[15]> 

启动celery的方法

# 最终在终端运行这个main文件
celery -A 应用包名 worker -l info
 
# 我们当前项目,在后端项目根目录下运行
celery -A celery_tasks.main worker -l info
# 守护进程
celery multi start w1 -A celery_tasks.main -l info --logfile=./celerylog.log
# 停止和重启 分别将 start 改为 stop / restart

守护进程的另一种方式,使用supervisor,这是一个管理进程的工具,这种启动方式就是用supervisor接管celery。

标签:
python3,celery异步使用

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