Celery是一个简单、灵活且可靠的，处理大量消息的分布式系统
专注于实时处理的异步任务队列
同时也支持任务调度
Celery的架构由三部分组成，消息中间件（message broker），任务执行单元（worker）和任务执行结果存储（task result store）组成。
Celery version 4.0 runs on Python ❨2.7, 3.4, 3.5❩ PyPy ❨5.4, 5.5❩ This is the last version to support Python 2.7, and from the next version (Celery 5.x) Python 3.5 or newer is required. If you’re running an older version of Python, you need to be running an older version of Celery: Python 2.6: Celery series 3.1 or earlier. Python 2.5: Celery series 3.0 or earlier. Python 2.4 was Celery series 2.2 or earlier. Celery is a project with minimal funding, so we don’t support Microsoft Windows. Please don’t open any issues related to that platform.
异步任务：将耗时操作任务提交给Celery去异步执行，比如发送短信/邮件、消息推送、音视频处理等等
定时任务：定时执行某件事情，比如每天数据统计
pip install celery
消息中间件：RabbitMQ/Redis
app=Celery('任务名'，backend='xxx',broker='xxx')
基本使用
创建项目celerytest
创建py文件：celery_app_task.py
import celery import time # broker='redis://127.0.0.1:6379/2' 不加密码 backend='redis://:123456@127.0.0.1:6379/1' broker='redis://:123456@127.0.0.1:6379/2' cel=celery.Celery('test',backend=backend,broker=broker) @cel.task def add(x,y): return x+y
from celery_app_task import add result = add.delay(4,5) print(result.id)
创建py文件：run.py，执行任务，或者使用命令执行：celery worker -A celery_app_task -l info
注：windows下：celery worker -A celery_app_task -l info -P eventlet
eventlet此模块需要另外安装
from celery_app_task import cel if __name__ == '__main__': cel.worker_main() # cel.worker_main(argv=['--loglevel=info')
创建py文件：result.py，查看任务执行结果
from celery.result import AsyncResult from celery_app_task import cel async = AsyncResult(id="e919d97d-2938-4d0f-9265-fd8237dc2aa3", app=cel) if async.successful(): result = async.get() print(result) # result.forget() # 将结果删除 elif async.failed(): print('执行失败') elif async.status == 'PENDING': print('任务等待中被执行') elif async.status == 'RETRY': print('任务异常后正在重试') elif async.status == 'STARTED': print('任务已经开始被执行')
执行 add_task.py，添加任务，并获取任务ID
执行 run.py ，或者执行命令：celery worker -A celery_app_task -l info
执行 result.py,检查任务状态并获取结果
pro_cel ├── celery_task# celery相关文件夹 │ ├── celery.py # celery连接和配置相关文件,必须叫这个名字 │ └── tasks1.py # 所有任务函数 │ └── tasks2.py # 所有任务函数 ├── check_result.py # 检查结果 └── send_task.py # 触发任务
celery.py
from celery import Celery cel = Celery('celery_demo', broker='redis://127.0.0.1:6379/1', backend='redis://127.0.0.1:6379/2', # 包含以下两个任务文件，去相应的py文件中找任务，对多个任务做分类 include=['celery_task.tasks1', 'celery_task.tasks2' ]) # 时区 cel.conf.timezone = 'Asia/Shanghai' # 是否使用UTC cel.conf.enable_utc = False
tasks1.py
import time from celery_task.celery import cel @cel.task def test_celery(res): time.sleep(5) return "test_celery任务结果:%s"%res
tasks2.py
import time from celery_task.celery import cel @cel.task def test_celery2(res): time.sleep(5) return "test_celery2任务结果:%s"%res
check_result.py
from celery.result import AsyncResult from celery_task.celery import cel async = AsyncResult(id="08eb2778-24e1-44e4-a54b-56990b3519ef", app=cel) if async.successful(): result = async.get() print(result) # result.forget() # 将结果删除,执行完成，结果不会自动删除 # async.revoke(terminate=True) # 无论现在是什么时候，都要终止 # async.revoke(terminate=False) # 如果任务还没有开始执行呢，那么就可以终止。 elif async.failed(): print('执行失败') elif async.status == 'PENDING': print('任务等待中被执行') elif async.status == 'RETRY': print('任务异常后正在重试') elif async.status == 'STARTED': print('任务已经开始被执行')
send_task.py
from celery_task.tasks1 import test_celery from celery_task.tasks2 import test_celery2 # 立即告知celery去执行test_celery任务，并传入一个参数 result = test_celery.delay('第一个的执行') print(result.id) result = test_celery2.delay('第二个的执行') print(result.id)
添加任务（执行send_task.py），开启work：celery worker -A celery_task -l info -P eventlet，检查任务执行结果（执行check_result.py）
设定时间让celery执行一个任务
add_task.py
from celery_app_task import add from datetime import datetime # 方式一 # v1 = datetime(2019, 2, 13, 18, 19, 56) # print(v1) # v2 = datetime.utcfromtimestamp(v1.timestamp())将当前时间转成utc格式 # print(v2) # result = add.apply_async(args=[1, 3], eta=v2) # print(result.id) # 方式二 ctime = datetime.now() # 默认用utc时间,需要转成utc时间格式 utc_ctime = datetime.utcfromtimestamp(ctime.timestamp()) from datetime import timedelta time_delay = timedelta(seconds=10) task_time = utc_ctime + time_delay # 使用apply_async并设定时间 result = add.apply_async(args=[4, 3], eta=task_time) print(result.id)
类似于contab的定时任务
多任务结构中celery.py修改如下
from datetime import timedelta from celery import Celery from celery.schedules import crontab cel = Celery('tasks', broker='redis://127.0.0.1:6379/1', backend='redis://127.0.0.1:6379/2', include=[ 'celery_task.tasks1', 'celery_task.tasks2', ]) cel.conf.timezone = 'Asia/Shanghai' cel.conf.enable_utc = False cel.conf.beat_schedule = { # 名字随意命名 'add-every-10-seconds': { # 执行tasks1下的test_celery函数 'task': 'celery_task.tasks1.test_celery', # 每隔2秒执行一次 # 'schedule': 1.0, # 'schedule': crontab(minute="*/1"), 'schedule': timedelta(seconds=2), # 传递参数 'args': ('test',) }, # 'add-every-12-seconds': { # 'task': 'celery_task.tasks1.test_celery', # 每年4月11号，8点42分执行 # 'schedule': crontab(minute=42, hour=8, day_of_month=11, month_of_year=4), # 'schedule': crontab(minute=42, hour=8, day_of_month=11, month_of_year=4), # 'args': (16, 16) # }, }
启动一个beat：celery beat -A celery_task -l info
注意：同一个目录下只能开启一个beat
启动work执行：celery worker -A celery_task -l info -P eventlet
django-celery模块兼容不太友好建议不使用,可以直接用多任务结构,在任何python框架中都能使用
celery==3.1.25
django-celery==3.1.20
在项目目录下创建celeryconfig.py
import djcelery djcelery.setup_loader() CELERY_IMPORTS=( 'app01.tasks', ) #有些情况可以防止死锁 CELERYD_FORCE_EXECV=True # 设置并发worker数量 CELERYD_CONCURRENCY=4 #允许重试 CELERY_ACKS_LATE=True # 每个worker最多执行100个任务被销毁，可以防止内存泄漏 CELERYD_MAX_TASKS_PER_CHILD=100 # 超时时间 CELERYD_TASK_TIME_LIMIT=12*30
在app01目录下创建tasks.py
from celery import task @task def add(a,b): with open('a.text', 'a', encoding='utf-8') as f: f.write('a') print(a+b)
视图函数views.py
from django.shortcuts import render,HttpResponse from app01.tasks import add from datetime import datetime def test(request): # result=add.delay(2,3) ctime = datetime.now() # 默认用utc时间 utc_ctime = datetime.utcfromtimestamp(ctime.timestamp()) from datetime import timedelta time_delay = timedelta(seconds=5) task_time = utc_ctime + time_delay result = add.apply_async(args=[4, 3], eta=task_time) print(result.id) return HttpResponse('ok')
settings.py
INSTALLED_APPS = [ ... 'djcelery', 'app01' ] ... from djagocele import celeryconfig BROKER_BACKEND='redis' BOOKER_URL='redis://127.0.0.1:6379/1' CELERY_RESULT_BACKEND='redis://127.0.0.1:6379/2'