(一)、概述
Celery是一个简单、灵活和可靠的基于多任务的分布式系统,为运营提供用于维护此系统的工具。专注于实时处理的任务队列,同时也支持任务的调度。执行单元为任务(task),利用多线程这些任务可以被并发的在单个或多个职程(worker)上运行。
Celery通过消息机制通信,通常通过中间人(broker)来分配和调节客户端与职程服务器(worker)之间的通信。客户端发送一条消息,中间人把消息分配给一个职程,最后由职程来负责执行此任务。
Celery可以有多个职程和中间人,这样提高了高可用性和横向的扩展能力
Celery由python语言开发,但是该协议可以用任何语言拉力实现,例如:Django中的Celery、node中的node-celery和php中的celery-php
(二)、Django中使用Celery的流程与配置
导入Celery:pip3 install Celery
在 与项目同名的目录下 创建celery.py文件,特别注意:项目同名的目录下
复制内容到该文件
修改两处内容
- os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'proj.settings')中的proj改为项目名
- app = Celery('pro')中的pro改为项目名
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import os from celery import Celery # set the default Django settings module for the 'celery' program. os.environ.setdefault( 'DJANGO_SETTINGS_MODULE' , 'proj.settings' ) app = Celery( 'pro' ) # 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.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 (f 'Request: {self.request!r}' ) |
在 与项目同名的目录下 的__init__.py文件中添加内容
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# 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' ,) |
在settings.py文件中添加配置
- CELERY_BROKER_URL:中间人url,可以配置redis或者RabbitMQ
- CELERY_RESULT_BACKEND:返回结果的存储地址
- CELERY_ACCEPT_CONTENT:接收内容的格式,分为两种:json和msgpack。msgpack比json格式的数据体积更小,传输速度更快。
- CELERY_TASK_SERIALIZER:任务载荷的序列化方式-->json
- CELERY_TIMEZONE
- CELERY_TASK_TRACK_STARTED:是否开启任务跟踪
- CELERY_TASK_TIME_LIMIT:任务超时限制
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# Celery配置 CELERY_BROKER_URL = env( "CELERY_BROKER_URL" ) CELERY_RESULT_BACKEND = env( "CELERY_RESULT_BACKEND" ) CELERY_ACCEPT_CONTENT = [ "json" , "msgpack" ] CELERY_TASK_SERIALIZER = "json" CELERY_TIMEZONE = "Asia/Shanghai" CELERY_TASK_TRACK_STARTED = True CELERY_TASK_TIME_LIMIT = 30 * 60 |
在app下创建tasks.py文件,创建发送消息功能,任务方法必须添加装饰器:@shared_task
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from rest_framework.response import Response from rest_framework.generics import GenericAPIView from time import sleep from celery import shared_task class TestView3(GenericAPIView): @classmethod @shared_task def sleep( self , duration): sleep(duration) return Response( "成功" , status = 200 ) |
创建视图和路由
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### views.py from .tasks import TestView3 class TestView1(GenericAPIView): def get( self , request): TestView3.sleep( 10 ) return Response( "celery实验成功" ) test_view_1 = TestView1.as_view() ### urls.py from django.urls import path from .views import ( test_view_1 ) urlpatterns = [ path( 'celery/' , test_view_1, name = "test1" ) ] |
安装redis并启动
启动django项目
使用Celery命令启动Celery服务,命令:celery -A 项目名 worker -l info,如果如下所示则为启动成功.
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celery@AppledeMacBook-Air.local v5.0.3 (singularity) Darwin-20.1.0-x86_64-i386-64bit 2020-12-05 20:52:17 [config] .> app: drf_email_project:0x7f84a0c4ad68 .> transport: redis://127.0.0.1:6379/1%20 .> results: redis://127.0.0.1:6379/2 .> concurrency: 4 (prefork) .> task events: OFF (enable -E to monitor tasks in this worker) [queues] .> celery exchange=celery(direct) key=celery [tasks] . drf_email_project.celery.debug_task . users.tasks.sleep [2020-12-05 20:52:18,166: INFO/MainProcess] Connected to redis://127.0.0.1:6379/1%20 [2020-12-05 20:52:18,179: INFO/MainProcess] mingle: searching for neighbors [2020-12-05 20:52:19,212: INFO/MainProcess] mingle: all alone [2020-12-05 20:52:19,248: WARNING/MainProcess] /Users/apple/drf-email/lib/python3.7/site-packages/celery/fixups/django.py:204: UserWarning: Using settings.DEBUG leads to a memory leak, never use this setting in production environments! leak, never use this setting in production environments!''') [2020-12-05 20:52:19,249: INFO/MainProces |
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原文链接:https://segmentfault.com/a/1190000038390568