Django 1.9 + celery + django-celry 实现定时任务

celery可以进行任务异步处理，celery还有一种Celery的常用模式便是执行定期任务. 执行定期任务时, Celery会通过celerybeat进程来完成. Celerybeat会保持运行, 一旦到了某一定期任务需要执行时, Celerybeat便将其加入到queue中. 
配置

那么我们如何让他和django搭配着使用呢

其实很简单拿一个项目来说吧

项目介绍

celery==3.1.23

Django==1.9

django-celery==3.1.17

flower==0.9.2

请严格按照版本安装，否则出现故障请自行解决，版本坑不是你很容易发现的

创建一个虚拟环境

virtualenv my-celery_v1 -p python2.
pip install django==1.9 django-celery==3.1. celery==3.1. flower==0.9. redis
cd my-celery_v1/
source bin/active
django-admin startproject proj
cd  proj
python manage.py startapp demoapp

修改配置文件settings.py

INSTALLED_APPS = [
    'django.contrib.admin',
    'django.contrib.auth',
    'django.contrib.contenttypes',
    'django.contrib.sessions',
    'django.contrib.messages',
    'django.contrib.staticfiles',
    'djcelery',
    'demoapp',

]

 1 import djcelery
 djcelery.setup_loader()
 BROKER_URL = 'redis://localhost:6379'
 CELERYBEAT_SCHEDULER = 'djcelery.schedulers.DatabaseScheduler' # 定时任务
 CELERY_RESULT_BACKEND = 'djcelery.backends.database:DatabaseBackend'
 # CELERY_RESULT_BACKEND = 'redis://localhost:6379'
 CELERY_ACCEPT_CONTENT = ['application/json']
 CELERY_TASK_SERIALIZER = 'json'
 CELERY_RESULT_SERIALIZER = 'json'
 CELERY_TIMEZONE = 'Asia/Shanghai'
 CELERY_LOG_FILE = os.path.join(os.path.join(os.path.join(BASE_DIR, 'logs'), 'celery'), 'celery.log')
 CELERYBEAT_LOG_FILE = os.path.join(os.path.join(os.path.join(BASE_DIR, 'logs'), 'celery'), 'beat.log')

创建celery.py文件

#!/bin/python
#-*- coding:utf-8 -*-

from __future__ import absolute_import

import os

from celery import Celery,platforms

os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'proj.settings')
# Specifying the settings here means the celery command line program will know where your Django project is.
# This statement must always appear before the app instance is created, which is what we do next:
from django.conf import settings

app = Celery('proj')

app.config_from_object('django.conf:settings')
platforms.C_FORCE_ROOT = True
# This means that you don’t have to use multiple configuration files, and instead configure Celery directly from the Django settings.
# You can pass the object directly here, but using a string is better since then the worker doesn’t have to serialize the object.

app.autodiscover_tasks(lambda: settings.INSTALLED_APPS)

# With the line above Celery will automatically discover tasks in reusable apps if you define all tasks in a separate tasks.py module.
# The tasks.py should be in dir which is added to INSTALLED_APP in settings.py.
# So you do not have to manually add the individual modules to the CELERY_IMPORT in settings.py.

@app.task(bind=True)
def debug_task(self):
    print('Request: {0!r}'.format(self.request))  # dumps its own request information

在proj/__init__.py

#!/bin/python
from __future__ import absolute_import

# 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']

在项目demoapp/tasks.py

from __future__ import absolute_import

import time
from celery import task

from celery import shared_task

# from celery.task import tasks
# from celery.task import Task

# @task()
@shared_task
def add(x, y):
    print "%d + %d = %d" % (x, y, x + y)
    return x + y

# class AddClass(Task):
#    def run(x,y):
#        print "%d + %d = %d"%(x,y,x+y)
#        return x+y
# tasks.register(AddClass)

@shared_task
def mul(x, y):
    print "%d * %d = %d" % (x, y, x * y)
    return x * y

@shared_task
def sub(x, y):
    print "%d - %d = %d" % (x, y, x - y)
    return x - y

@task
def sendmail(mail):
    print('sending mail to %s...' % mail)
    time.sleep(2.0)
    print('mail sent.')
    print "------------------------------------"
    return mail

运行之前创建logs/celery 日志文件夹同步数据库和创建超级用户

python manage.py migrate
python manage.py createsuperuser

首先启动worker没报错正常

python manage.py celery worker --loglevel=info --settings=proj.settings  --autoreload

启动计划任务

python manage.py celery beat

另外为更好的展示任务执行情况我们还是用了flower作为页面展示，使用5555端口访问

python manage.py celery flower -l info --settings=proj.settings

启动django

django manage.py runserver

执行结果：

更直观的执行结果127.0.0.1:5555