Django中使用Celery的方法步骤
(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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