Celery介绍和基本使用
Celery 是一个分布式异步消息队列，通过它可以轻松的实现任务的异步处理
举几个实例场景中可用的例子:
-
你想对100台机器执行一条批量命令，可能会花很长时间 ，但你不想让你的程序等着结果返回，而是给你返回 一个任务ID,你过一段时间只需要拿着这个任务id就可以拿到任务执行结果， 在任务执行ing进行时，你可以继续做其它的事情。
-
你想做一个定时任务，比如每天检测一下你们所有客户的资料，如果发现今天 是客户的生日，就给他发个短信祝福
Celery 在执行任务时需要通过一个消息中间件来接收和发送任务消息，以及存储任务结果， 一般使用rabbitMQ or Redis
Celery有以下优点：
-
简单：一单熟悉了celery的工作流程后，配置和使用还是比较简单的
-
高可用：当任务执行失败或执行过程中发生连接中断，celery 会自动尝试重新执行任务
-
快速：一个单进程的celery每分钟可处理上百万个任务
-
灵活： 几乎celery的各个组件都可以被扩展及自定制
Celery基本工作流程图：
Celery安装使用
1、Celery的默认broker是RabbitMQ, 仅需配置一行就可以
broker_url = 'amqp://my_user:my_password@localhost:5672//'
2、Redis做broker
broker_url = 'redis://localhost:6379' broker_url = 'redis://:my_password@localhost:port'
如果想获取每个任务的执行结果，还需要配置一下把任务结果存在哪
result_backend = 'redis://localhost:6379'
一、创建一个celery application 用来定义你的任务列表
①.创建一个任务 tasks.py
from celery import Celery
app = Celery('celery_test',
broker='redis://localhost',
backend='redis://localhost')
@app.task
def add(x,y):
print("running...",x,y)
return x+y
②.启动Celery Worker来开始监听并执行任务
$ celery -A tasks worker --loglevel=info [debug] # tasks 为 tasks文件路径! $ celery -A tasks worker -l info
③.调用任务
>>> from tasks import add >>> add.delay(4, 4)
worker终端会显示收到 一个任务，此时你想看任务结果的话，需要在调用 任务时 赋值个变量
>>> result = add.delay(4, 4) >>> result.ready() # 返回执行状态 >>> result.get(timeout=1) # 超时报错 >>> result.get(propagate=False) # 程序执行过程出错报异常 >>> result.traceback # 获取异常信息
注:任务结果需要是可以json转化的，celery代码修改后，worker需要重启
二、在项目中使用celery
可以把celery配置成一个应用
目录格式如下
proj/__init__.py
/celery.py
/tasks.py
proj/celery.py内容
from __future__ import absolute_import, unicode_literals
from celery import Celery
app = Celery('proj',
broker='redis://192.168.18.147',
backend = 'redis://192.168.18.147',
include=['my_proj.tasks'])
# Optional configuration, see the application user guide.
app.conf.update(
result_expires=3600,
)
if __name__ == '__main__':
app.start()
proj/tasks.py中的内容
from __future__ import absolute_import, unicode_literals from .celery import app @app.task def add(x, y): return x + y @app.task def mul(x, y): return x * y @app.task def xsum(numbers): return sum(numbers)
启动worker 方式一
$ celery -A proj worker -l info
启动worker 方式二 后台启动
celery multi start w1 -A proj -l info # w1 自定义名字 celery multi restart w1 -A proj -l info celery multi stop w1 -A proj -l info
三、Celery 定时任务
celery支持定时任务，设定好任务的执行时间，celery就会定时自动帮你执行， 这个定时任务模块叫celery beat
periodic_task.py
from celery import Celery
from celery.schedules import crontab
app = Celery()
@app.on_after_configure.connect
def setup_periodic_tasks(sender, **kwargs):
# Calls test('hello') every 10 seconds.
sender.add_periodic_task(10.0, test.s('hello'), name='add every 10')
# Calls test('world') every 30 seconds
sender.add_periodic_task(30.0, test.s('world'), expires=10)
# Executes every Monday morning at 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)
add_periodic_task 会添加一条定时任务
上面是通过调用函数添加定时任务，也可以像写配置文件 一样的形式添加， 下面是每30s执行的任务
app.conf.beat_schedule = {
'add-every-30-seconds': {
'task': 'tasks.add',
'schedule': 30.0,
'args': (16, 16)
},
}
app.conf.timezone = 'UTC'
任务添加好了，需要让celery单独启动一个进程来定时发起这些任务，
注意， 这里是发起任务，不是执行，这个进程只会不断的去检查你的任务计划， 每发现有任务需要执行了，就发起一个任务调用消息，交给celery worker去执行
启动任务调度器 celery beat
$ celery -A periodic_task beat
启动celery worker来执行任务
$ celery -A periodic_task worker
更复杂的定时配置
from celery.schedules import crontab
app.conf.beat_schedule = {
# Executes every Monday morning at 7:30 a.m.
'add-every-monday-morning': {
'task': 'tasks.add',
'schedule': crontab(hour=7, minute=30, day_of_week=1),
'args': (16, 16),
},
}
上面的这条意思是每周1的早上7.30执行tasks.add任务
还有更多定时配置方式如下：
| Example | Meaning |
| crontab() | Execute every minute. |
| crontab(minute=0, hour=0) | Execute daily at midnight. |
| crontab(minute=0, hour='*/3') | Execute every three hours: midnight, 3am, 6am, 9am, noon, 3pm, 6pm, 9pm. |
|
Same as previous. |
| crontab(minute='*/15') | Execute every 15 minutes. |
| crontab(day_of_week='sunday') | Execute every minute (!) at Sundays. |
|
Same as previous. |
|
Execute every ten minutes, but only between 3-4 am, 5-6 pm, and 10-11 pm on Thursdays or Fridays. |
| crontab(minute=0,hour='*/2,*/3') | Execute every even hour, and every hour divisible by three. This means: at every hour except: 1am, 5am, 7am, 11am, 1pm, 5pm, 7pm, 11pm |
| crontab(minute=0, hour='*/5') | Execute hour divisible by 5. This means that it is triggered at 3pm, not 5pm (since 3pm equals the 24-hour clock value of “15”, which is divisible by 5). |
| crontab(minute=0, hour='*/3,8-17') | Execute every hour divisible by 3, and every hour during office hours (8am-5pm). |
| crontab(0, 0,day_of_month='2') | Execute on the second day of every month. |
|
Execute on every even numbered day. |
|
Execute on the first and third weeks of the month. |
|
Execute on the eleventh of May every year. |
| crontab(0, 0,month_of_year='*/3') | Execute on the first month of every quarter. |
上面能满足你绝大多数定时任务需求了，甚至还能根据潮起潮落来配置定时任务，
具体看 http://docs.celeryproject.org/en/latest/userguide/periodic-tasks.html#solar-schedules
四、Django项目中使用celery
目录格式:
CeleryTest/
CeleryTest/__init__.py
/celery.py
/setting.py
app/task.py
....
/views.py
celery.py内容
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', 'CeleryTest.settings')
app = Celery('CeleryTest')
# Using a string here means the worker don'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('Request: {0!r}'.format(self.request))
__init__.py内容
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']
setting.py内容
CELERY_BROKER_URL = 'redis://192.168.18.147' CELERY_RESULT_BACKEND = 'redis://192.168.18.147'
tasks.py内容 (必须在各app根目录下,不能随意命名)
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
@shared_task
def xsum(numbers):
return sum(numbers)
views.py调用celery tasks
from app01 import tasks
from celery.result import AsyncResult
def index(request):
res = tasks.add.delay(9,8)
print("start running task")
return HttpResponse(res.task_id)
def get_data(request,task_id):
result = AsyncResult(task_id)
return HttpResponse(result.status)
AsyncResult 根据返回的id获取结果
调用worker
$:~/..../CeleryTest$ celery -A CeleryTest worker -l info
五、django中使用计划任务功能
1.安装package
$ pip install django-celery-beat
2.setting中注册app
INSTALLED_APPS = (
...,
'django_celery_beat',
)
3.生成数据库表
$ python manage.py migrate
4. Django-Admin 创建任务
5.开启任务调度器
$ celery -A proj beat -l info -S django
在admin页面里，有3张表
配置完长这样
此时启动你的celery beat 和worker，会发现每隔2分钟，beat会发起一个任务消息让worker执行scp_task任务
注意，经测试，每添加或修改一个任务，celery beat都需要重启一次，要不然新的配置不会被celery beat进程读到