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  • celery--处理多任务的分发系统

    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 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.
    版本和要求

    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
    s1.py
    #!/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)
    s2.py
    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')
    s3.py

    执行 s1.py 创建worker(终端执行命令):

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    celery worker -A s1 -l info

    执行 s2.py ,创建一个任务并获取任务ID:

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    python3 s2.py

    执行 s3.py ,检查任务状态并获取结果:

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    python3 s3.py

    多任务结构

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    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
    pro_cel/celery_tasks/celery
    #!/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"
    pro_cel/celery_tasks/tasks.py
    #!/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')
    pro_cel/check_result.py
    #!/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)
    pro_cel/send_task.py

    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

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    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=[13], eta=ctime_x)
    print(result.id)

    2. 类似于contab的定时任务

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    """
    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': (1616)
        },
    }

    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

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    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
    
        return "任务已经提交"
    
    
    @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()
    app.py
    #!/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
    celery_tasks/celery.py
    #!/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"
    celery_task/tasks.py

    Django中应用Celery

    一、基本使用

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    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()
    django_celery_demo/celery.py
    from .celery import app as celery_app
    
    __all__ = ('celery_app',)
    django_celery_demo/__init__.py
    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)
    app01/tasks.py
    # ######################## 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'
    django_celery_demo/settings.py
    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')
    
        return HttpResponse('...')
    app01/views.py
    """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),
    ]
    django_celery_demo/urls.py

    二、定时任务

    1. 安装

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    install django-celery-beat

    2. 注册app

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

    3. 数据库去迁移生成定时任务相关表

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    python manage.py migrate

    4. 设置定时任务

    • 方式一:代码中配置
      复制代码
      #!/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()
      复制代码
    • 方式二:数据表录入

    5. 后台进程创建任务

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

    6. 启动worker执行任务

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    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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  • 原文地址:https://www.cnblogs.com/shangping/p/12910418.html
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