Django中使用Celery

(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

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

# 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

# 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

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

### 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.

[email protected] 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/MainProcess] [email protected] ready.