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(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.

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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