celery学习笔记

celery使用在django下，官方4.2文档 http://docs.celeryproject.org/en/latest/django/index.html， github文档：https://github.com/celery/celery/tree/master/examples/django/

首先生成celery的app

from __future__ import absolute_import, unicode_literals
import os
from celery import Celery

# set the default Django settings module for the 'celery' program.
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'proj.settings')  #  导入django环境

app = Celery('proj')  # 生成app

# 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()  #  自动到每个app下边寻找tasks文件，并导入


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

使用@shared_task装饰器，为了使用它，首先在项目的__init__.py文件导入app

from __future__ import absolute_import, unicode_literals

# 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',)

创建tasks模块：

# Create your tasks here
from __future__ import absolute_import, unicode_literals
from celery import shared_task


@shared_task
def add(x, y):
    return x + y


@shared_task
def mul(x, y):
    return x * y

运行celery

celery -A proj worker -l info

window 10下运行报错，弄了好久，最后看别人的博客解决了：https://blog.csdn.net/qq_30242609/article/details/79047660，解决办法：

celery -A proj worker -l info -P eventlet

把celery的并行执行方式改为 eventlet, 而不是默认的prefork，需要安装

pip install eventlet

把保存结果后端设为django的结果后端，需要使用django-celery-results

$ pip install django-celery-results
INSTALLED_APPS{
　　django_celery_results,
}

 python manage.py migrate django_celery_results

数据库

 
  CELERY_RESULT_BACKEND = 'django-db'

缓存

 
  CELERY_RESULT_BACKEND = 'django-cache' 
 

帮助：

 celery help

序列化配置，由于4.0默认是json序列化，序列化有时候会不成功，需要进行配置

CELERY_ACCEPT_CONTENT = ['json', 'pickle'] 
CELERY_TASK_SERIALIZER = 'pickle'  #  'json'默认， 改为pickle

CELERY_RESULT_SERIALIZER= 'json' # 结果序列化，默认json可以改为pickle

使用redis作为中间人

CELERY_BROKER_URL = 'redis://:password@host:port/db'

'redis://localhost/0'

简写：'redis://'

RabbitMQ: 'amqp://guest:guest@localhost//'

其他后端

　　　　sqlite (filename) CELERY_RESULT_BACKEND = ‘db+sqlite:///results.sqlite’

# mysql CELERY_RESULT_BACKEND = ‘db+mysql://scott:tiger@localhost/foo’

# postgresql CELERY_RESULT_BACKEND = ‘db+postgresql://scott:tiger@localhost/mydatabase’

# oracle CELERY_RESULT_BACKEND = ‘db+oracle://scott:[email protected]:1521/sidname’

配置时区app.conf.timezone = 'Asia/Shanghai'

运行周期性任务：

进行配置

from celery import Celery
from celery.schedules import crontab

app = Celery()

@app.on_after_configure.connect
def setup_periodic_tasks(sender, **kwargs):
    # 调用 test('hello') 每10秒运行
    sender.add_periodic_task(10.0, test.s('hello'), name='add every 10')

    # test('world') 每30秒
    sender.add_periodic_task(30.0, test.s('world'), expires=10)

    # 每个星期一早上 7:30 a.m.
    sender.add_periodic_task(
        crontab(hour=7, minute=30, day_of_week=1),
        test.s('Happy Mondays!'),
    )

@app.task
def test(arg):
    print(arg)

动态配置

app.conf.beat_schedule = {
    'add-every-30-seconds': {
        'task': 'tasks.add',
        'schedule': 30.0,
        'args': (16, 16)
    },
}
app.conf.timezone = 'UTC'

args位置参数元组，列表

kwargs关键字参数, 字典类型

定时任务示例

from celery.schedules import solar

app.conf.beat_schedule = {
    # Executes at sunset in Melbourne
    'add-at-melbourne-sunset': {
        'task': 'tasks.add',
        'schedule': solar('sunset', -37.81753, 144.96715),
        'args': (16, 16),
    },
}

文档链接：http://docs.celeryproject.org/en/latest/userguide/periodic-tasks.html#crontab-schedules

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