python celery任务分发

Celery是由Python开发的一个简单、灵活、可靠的处理大量任务的分发系统，它不仅支持实时处理也支持任务调度。

• user：用户程序，用于告知celery去执行一个任务。
• broker: 存放任务（依赖RabbitMQ或Redis，进行存储）
• worker：执行任务

celery需要rabbitMQ、Redis、Amazon SQS、Zookeeper（测试中） 充当broker来进行消息的接收，并且也支持多个broker和worker来实现高可用和分布式。http://docs.celeryproject.org/en/latest/getting-started/brokers/index.html

    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 </span>2.6: Celery series 3.1 <span style="color: #0000ff;">or</span><span style="color: #000000;"> earlier.
    Python </span>2.5: Celery series 3.0 <span style="color: #0000ff;">or</span><span style="color: #000000;"> earlier.
    Python </span>2.4 was Celery series 2.2 <span style="color: #0000ff;">or</span><span style="color: #000000;"> earlier.

Celery </span><span style="color: #0000ff;">is</span> a project with minimal funding, so we don&rsquo;t support Microsoft Windows. Please don&rsquo;t open any issues related to that platform.</pre>

环境准备：

• 安装rabbitMQ或Redis
      见：http://www.cnblogs.com/wupeiqi/articles/5132791.html
• 安装celery
       pip3 install celery

快速上手

import time
from celery import Celery
app = Celery('tasks', broker='redis://192.168.10.48:6379', backend='redis://192.168.10.48:6379')
@app.task

def xxxxxx(x, y):

time.sleep(10)

return x + y

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from s1 import xxxxxx
# 立即告知celery去执行xxxxxx任务，并传入两个参数

result = xxxxxx.delay(4, 4)

print(result.id)

from celery.result import AsyncResult
from s1 import app
async = AsyncResult(id="f0b41e83-99cf-469f-9eff-74c8dd600002", app=app)
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 s1.py 创建worker（终端执行命令）：

celery worker -A s1 -l info

执行 s2.py ，创建一个任务并获取任务ID：

python3 s2.py 

执行 s3.py ,检查任务状态并获取结果：

python3 s3.py

多任务结构

pro_cel
    ├── celery_tasks# celery相关文件夹
    │   ├── celery.py   # celery连接和配置相关文件
    │   └── tasks.py    #  所有任务函数
    ├── check_result.py # 检查结果
    └── send_task.py    # 触发任务

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from celery import Celery
celery = Celery('xxxxxx',

broker='redis://192.168.0.111:6379',

backend='redis://192.168.0.111:6379',

include=['celery_tasks.tasks'])
# 时区

celery.conf.timezone = 'Asia/Shanghai'

# 是否使用UTC

celery.conf.enable_utc = False

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import time

from .celery import celery
@celery.task

def xxxxx(*args, **kwargs):

time.sleep(5)

return "任务结果"
@celery.task

def hhhhhh(*args, **kwargs):

time.sleep(5)

return "任务结果"

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from celery.result import AsyncResult

from celery_tasks.celery import celery
async = AsyncResult(id="ed88fa52-11ea-4873-b883-b6e0f00f3ef3", app=celery)
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')

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import celery_tasks.tasks
# 立即告知celery去执行xxxxxx任务，并传入两个参数

result = celery_tasks.tasks.xxxxx.delay(4, 4)
print(result.id)

更多配置：http://docs.celeryproject.org/en/latest/userguide/configuration.html

定时任务

1. 设定时间让celery执行一个任务

import datetime
from celery_tasks.tasks import xxxxx
"""
from datetime import datetime
v1 = datetime(2017, 4, 11, 3, 0, 0)

print(v1)
v2 = datetime.utcfromtimestamp(v1.timestamp())

print(v2)
"""

ctime = datetime.datetime.now()

utc_ctime = datetime.datetime.utcfromtimestamp(ctime.timestamp())
s10 = datetime.timedelta(seconds=10)

ctime_x = utc_ctime + s10
使用apply_async并设定时间
result = xxxxx.apply_async(args=[1, 3], eta=ctime_x)

print(result.id)

2. 类似于contab的定时任务

"""
celery beat -A proj
celery worker -A proj -l info
"""

from celery import Celery

from celery.schedules import crontab
app = Celery('tasks', broker='amqp://47.98.134.86:5672', backend='amqp://47.98.134.86:5672', include=['proj.s1', ])

app.conf.timezone = 'Asia/Shanghai'

app.conf.enable_utc = False
app.conf.beat_schedule = {

# 'add-every-10-seconds': {

#     'task': 'proj.s1.add1',

#     'schedule': 10.0,

#     'args': (16, 16)

# },

'add-every-12-seconds': {

'task': 'proj.s1.add1',

'schedule': crontab(minute=42, hour=8, day_of_month=11, month_of_year=4),

'args': (16, 16)

},

}

注：如果想要定时执行类似于crontab的任务，需要定制 Scheduler来完成。

Flask中应用Celery

pro_flask_celery/
├── app.py
├── celery_tasks
    ├── celery.py
    └── tasks.py

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from flask import Flask

from celery.result import AsyncResult
from celery_tasks import tasks

from celery_tasks.celery import celery
app = Flask(name)
TASK_ID = None
@app.route('/')

def index():

global TASK_ID

result = tasks.xxxxx.delay()

# result = tasks.task.apply_async(args=[1, 3], eta=datetime(2018, 5, 19, 1, 24, 0))

TASK_ID = result.id
</span><span style="color: #0000ff;">return</span> <span style="color: #800000;">"</span><span style="color: #800000;">任务已经提交</span><span style="color: #800000;">"</span><span style="color: #000000;">

@app.route('/result')

def result():

global TASK_ID

result = AsyncResult(id=TASK_ID, app=celery)

if result.ready():

return result.get()

return "xxxx"
if name == 'main':

app.run()

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from celery import Celery
from celery.schedules import crontab
celery = Celery('xxxxxx',

broker='redis://192.168.10.48:6379',

backend='redis://192.168.10.48:6379',

include=['celery_tasks.tasks'])
# 时区

celery.conf.timezone = 'Asia/Shanghai'

# 是否使用UTC

celery.conf.enable_utc = False

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import time

from .celery import celery
@celery.task

def hello(*args, **kwargs):

print('执行hello')

return "hello"
@celery.task

def xxxxx(*args, **kwargs):

print('执行xxxxx')

return "xxxxx"
@celery.task

def hhhhhh(*args, **kwargs):

time.sleep(5)

return "任务结果"

Django中应用Celery

一、基本使用

django_celery_demo
├── app01
│   ├── __init__.py
│   ├── admin.py
│   ├── apps.py
│   ├── migrations
│   ├── models.py
│   ├── tasks.py
│   ├── tests.py
│   └── views.py
├── db.sqlite3
├── django_celery_demo
│   ├── __init__.py
│   ├── celery.py
│   ├── settings.py
│   ├── urls.py
│   └── wsgi.py
├── manage.py
├── red.py
└── templates

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import os

from celery import Celery
# set the default Django settings module for the 'celery' program.

os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'django_celery_demo.settings')
app = Celery('django_celery_demo')
# 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()

from .celery import app as celery_app
all = ('celery_app',)

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)

...
....
.....
# ######################## Celery配置 ########################
CELERY_BROKER_URL = 'redis://10.211.55.20:6379'
CELERY_ACCEPT_CONTENT = ['json']
CELERY_RESULT_BACKEND = 'redis://10.211.55.20:6379'
CELERY_TASK_SERIALIZER = 'json'

from django.shortcuts import render, HttpResponse
from app01 import tasks
from django_celery_demo import celery_app
from celery.result import AsyncResult
def index(request):

result = tasks.add.delay(1, 8)

print(result)

return HttpResponse('...')
def check(request):

task_id = request.GET.get('task')

async = AsyncResult(id=task_id, app=celery_app)

if async.successful():

data = async.get()

print('成功', data)

else:

print('任务等待中被执行')
</span><span style="color: #0000ff;">return</span> HttpResponse(<span style="color: #800000;">'</span><span style="color: #800000;">...</span><span style="color: #800000;">'</span>)</pre>

"""django_celery_demo URL Configuration
The urlpatterns list routes URLs to views. For more information please see:

https://docs.djangoproject.com/en/1.11/topics/http/urls/

Examples:

Function views

1. Add an import:  from my_app import views

2. Add a URL to urlpatterns:  url(r'^(', views.home, name='home')
Class-based views
    1. Add an import:  from other_app.views import Home
    2. Add a URL to urlpatterns:  url(r'^)', Home.as_view(), name='home')

Including another URLconf

1. Import the include() function: from django.conf.urls import url, include

2. Add a URL to urlpatterns:  url(r'^blog/', include('blog.urls'))

"""

from django.conf.urls import url

from django.contrib import admin

from app01 import views
urlpatterns = [

url(r'^admin/', admin.site.urls),

url(r'^index/', views.index),

url(r'^check/', views.check),

]

二、定时任务

1. 安装

install django-celery-beat

2. 注册app

INSTALLED_APPS = (
    ...,
    'django_celery_beat',
)

3. 数据库去迁移生成定时任务相关表

python manage.py migrate

4. 设置定时任务

• 方式一：代码中配置
  

  #!/usr/bin/env python
  # -*- coding:utf-8 -*-
  import os
  
  from celery import Celery
  # set the default Django settings module for the 'celery' program.
  
  os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'django_celery_demo.settings')
  app = Celery('django_celery_demo')
  # 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')
  app.conf.beat_schedule = {
  
  'add-every-5-seconds': {
  
  'task': 'app01.tasks.add',
  
  'schedule': 5.0,
  
  'args': (16, 16)
  
  },
  
  }
  # Load task modules from all registered Django app configs.
  
  app.autodiscover_tasks()

• 方式二：数据表录入
  

5. 后台进程创建任务

celery -A django_celery_demo beat -l info --scheduler django_celery_beat.schedulers:DatabaseScheduler

6. 启动worker执行任务

celery -A django_celery_demo worker -l INFO　　

官方参考：http://docs.celeryproject.org/en/latest/django/first-steps-with-django.html#using-celery-with-django

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