python3.7 中使用django-celery 完成异步任务

本文是在学习了慕课网中 “Python 异步任务队列 Celery 使用”课程后记录下来的笔记。由于笔者使用的python版本是python 3.7，所以直接需要在老师的代码基础上进行一定的修改，才能适配当前的环境。

环境：
python: python3.7
django: 2.1.5
celery: 4.2.0
django-celery: 3.2.2
flower: 0.9.2
kombu: 4.3.0
tornado: 5.1.1

什么是 Celery ?

• 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。

使用场景

• 异步任务

  将耗时的操作任务提交给 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

  类似于 crontab ，比如每日数据统计

安装配置

python 虚拟环境管理工具

1. virtualenv & virtualenvwrapper

2. pyenv

3. pipenv

4. venv

• 安装 Celery

  pip install celery[redis]
  

• Celery 的消息中间件

  • RabbitMQ
  • Redis

• 创建 Celery App

  app = Celery('xxx', backend='xxxxx', broker='xxxxx')
  

使用 Celery

1. 配置 Celery

   broker = 'redis://localhost:6379/1'
   backend = 'redis://localhost:6379/2'
   app = Celery('my_task', broker=broker, backend=backend)
   

2. 注册任务

   @app.task   # 将 `add` 方法变成异步
   def add(x, y):
       print('enter call function ...')
       time.sleep(5)
       return x + y
   

3. 向 Celery 提交任务

   • windows 64bit用户：在任务脚本下添加以下代码

     import os
     
     os.environ.setdefault('FORKED_BY_MULTIPROCESSING', '1')
     

   • 提交任务

     result = add.delay(2, 15)
     s
     # 或者使用 apply_async(由参数组成的元组)
     # result = add.apply_async((2, 15))
     

合理分配文件夹管理 celery 任务

1. 在当前项目下新建一个 celery_app 的包，用来存放 celery 的 task 和 config， 并在 __init__.py 中配置 celery 实例

   from celery import Celery
   import os
   
   os.environ.setdefault('FORKED_BY_MULTIPROCESSING', '1')
   
   app = Celery('demo')
   
   # 通过 `Celery` 实例加载配置模块
   app.config_from_object('celery_app.celery_config')
   

2. 在 celery_config.py 中添加 celery 的配置

   # celery_config.py
   from datetime import timedelta
   from celery.schedules import crontab
   
   
   BROKER_URL = 'redis://localhost:6379/1'
   CELERY_RESULT_BACKEND = 'redis://localhost:6379/2'
   
   
   CELERY_TIMEZONE = 'Asia/Shanghai'  # 默认为 UTC
   
   # 导入指定的任务模块
   CELERY_IMPORTS = {
       'celery_app.task1',
       'celery_app.task2',
   }
   
   
   # 指定 `celery` 要执行的任务
   CELERYBEAT_SCHEDULE = {
       'task1': {
           'task': 'celery_app.task1.add',
           'schedule': timedelta(seconds=500),
           'args': (2, 8)
       },
       'task2': {
           'task': 'celery_app.task2.multiply',
           'schedule': crontab(hour=16, minute=32),
           'args': (4,6)
       }
   }
   

3. 编写 celery 的 task

   import time
   
   from celery_app import app
   
   @app.task
   def add(x, y):
       time.sleep(3)
       return x + y
   

4. 在外部脚本中向 celery 提交任务

   # app.py
   from celery_app import task1, task2
   
   task1.add.delay(2 ,5)
   task2.multiply.apply_async(args=(2, 5))  # 可以添加额外参数，比如：指定使用的队列  
   

启动 Celery

• 运行 Celery worker

  celery worker -A [celery_project_name] -l INFO
  

  参数说明：

  • -A : 指定celery实例的位置
  • -l : 指定日志的级别

  注意：在windows 64bit 环境中运行上述命令会报错

  (venv) c:\Users\jzw\Desktop\dj_celery>celery worker -A tasks -l INFO
  
  -------------- celery@DESKTOP-5DO1L05 v4.2.1 (windowlicker)
  ---- **** -----
  --- * ***  * -- Windows-10-10.0.17134-SP0 2019-02-10 15:17:01
  -- * - **** ---
  - ** ---------- [config]
  - ** ---------- .> app:         my_task:0x1a932e708d0
  - ** ---------- .> transport:   redis://localhost:6379/1
  - ** ---------- .> results:     redis://localhost:6379/2
  - *** --- * --- .> concurrency: 8 (prefork)
  -- ******* ---- .> task events: OFF (enable -E to monitor tasks in this worker)
  --- ***** -----
  -------------- [queues]
                  .> celery           exchange=celery(direct) key=celery
  
  
  [tasks]
  . app.add
  
  [2019-02-10 15:17:01,905: INFO/SpawnPoolWorker-1] child process 11932 calling self.run()
  [2019-02-10 15:17:01,913: INFO/SpawnPoolWorker-2] child process 10864 calling self.run()
  [2019-02-10 15:17:01,924: INFO/SpawnPoolWorker-3] child process 5544 calling self.run()
  [2019-02-10 15:17:01,937: INFO/SpawnPoolWorker-4] child process 5236 calling self.run()
  [2019-02-10 15:17:01,953: INFO/SpawnPoolWorker-6] child process 8684 calling self.run()
  [2019-02-10 15:17:01,963: INFO/SpawnPoolWorker-5] child process 2660 calling self.run()
  [2019-02-10 15:17:01,964: INFO/SpawnPoolWorker-7] child process 15968 calling self.run()
  [2019-02-10 15:17:01,979: INFO/SpawnPoolWorker-8] child process 15808 calling self.run()
  [2019-02-10 15:17:02,606: INFO/MainProcess] Connected to redis://localhost:6379/1
  [2019-02-10 15:17:03,614: INFO/MainProcess] mingle: searching for neighbors
  [2019-02-10 15:17:07,641: INFO/MainProcess] mingle: all alone
  [2019-02-10 15:17:12,664: INFO/MainProcess] celery@DESKTOP-5DO1L05 ready.
  [2019-02-10 15:18:13,158: INFO/MainProcess] Received task: app.add[b7c0cbcc-c9a3-40e5-a7f8-e629bdc6d7e8]
  [2019-02-10 15:18:14,174: ERROR/MainProcess] Task handler raised error: ValueError('not enough values to unpack (expected 3, got 0)')
  Traceback (most recent call last):
  File "c:\users\jzw\desktop\dj_celery\venv\lib\site-packages\billiard\pool.py", line 358, in workloop
      result = (True, prepare_result(fun(*args, **kwargs)))
  File "c:\users\jzw\desktop\dj_celery\venv\lib\site-packages\celery\app\trace.py", line 537, in _fast_trace_task
      tasks, accept, hostname = _loc
  ValueError: not enough values to unpack (expected 3, got 0)
  

  解决方案参考：

  https://github.com/celery/celery/issues/4081

  解决方案：添加celery运行时的环境变量，在脚本中添加如下代码

  # task.py
  import os
  
  os.environ.setdefault('FORKED_BY_MULTIPROCESSING', '1')
  

在Python3.7中运行celery worker时出现报错以及解决办法

from . import async, base
                ^
SyntaxError: invalid syntax

错误提出及讨论：

https://github.com/celery/celery/issues/4500

解决方案：

https://github.com/celery/celery/pull/4852/commits/d737dec3c943632f21f73a2235409c29e3fe63e3

• 运行 celery beat

  celery beat -A [celery_project_name] -l INFO
  

  参数说明：

  • -A : 指定celery实例的位置
  • -l : 指定日志的级别

• 同时运行 celery worker 和 celery beat (不支持Windows)

  celery -B -A celery_app worker -l[--loglevel] INFO
  

• 查看 celery 帮助

  celery worker --help
  

在django中使用 celery

• 当前环境
  • Windows 64bit
  • python 3.7
  • Python 包环境

    Package       Version
    ------------- -------
    amqp          2.4.1
    anyjson       0.3.3
    billiard      3.5.0.5
    celery        4.2.0
    Django        2.1.5
    django-celery 3.2.2
    kombu         4.3.0
    

运行 python manage.py celery worker -l INFO 时报错：

Traceback (most recent call last):
  File "manage.py", line 15, in 
    execute_from_command_line(sys.argv)
  File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\django\core\management\__init__.py", line 381, in execute_from_command_line
    utility.execute()
  File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\django\core\management\__init__.py", line 375, in execute
    self.fetch_command(subcommand).run_from_argv(self.argv)
  File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\django\core\management\__init__.py", line 224, in fetch_command
    klass = load_command_class(app_name, subcommand)
  File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\django\core\management\__init__.py", line 36, in load_command_class
    module = import_module('%s.management.commands.%s' % (app_name, name))
  File "D:\Programs\Python\Python37\lib\importlib\__init__.py", line 127, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "", line 1006, in _gcd_import
  File "", line 983, in _find_and_load
  File "", line 967, in _find_and_load_unlocked
  File "", line 677, in _load_unlocked
  File "", line 728, in exec_module
  File "", line 219, in _call_with_frames_removed
  File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\djcelery\management\co
mmands\celery.py", line 11, in 
    class Command(CeleryCommand):
  File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\djcelery\management\co
mmands\celery.py", line 15, in Command
    base.get_options() +
TypeError: can only concatenate tuple (not "NoneType") to tuple

参考：

https://stackoverflow.com/questions/49085230/django-celery-typeerror-can-only-concatenate-tuple-not-nonetype-to-tuple
http://docs.celeryproject.org/en/latest/django/first-steps-with-django.html

解决方案：

1. 将 djcelery\management\commands\celery.py 中的 options 部分注释掉

   # celery.py
   from __future__ import absolute_import, unicode_literals
   
   from celery.bin import celery
   
   from djcelery.app import app
   from djcelery.management.base import CeleryCommand
   
   base = celery.CeleryCommand(app=app)
   
   
   class Command(CeleryCommand):
       """The celery command."""
       help = 'celery commands, see celery help'
       # options = (CeleryCommand.options +
       #            base.get_options() +
       #            base.preload_options)
   
       def run_from_argv(self, argv):
           argv = self.handle_default_options(argv)
           base.execute_from_commandline(
               ['{0[0]} {0[1]}'.format(argv)] + argv[2:],
           )
   

2. 修改后运行 python manage.py celery worker -l INFO 时报错，报错信息如下：

   [2019-02-11 01:11:40,836: CRITICAL/MainProcess] Unrecoverable error: SyntaxError('invalid syntax', ('C:\\Users\\jzw\\Desktop\\celery_learn\\dj_celery\\venv\\lib\\site-packages\\cel
   ery\\backends\\redis.py', 22, 19, 'from . import async, base\n'))
   Traceback (most recent call last):
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\kombu\utils\objects.py", line 42, in __get__
       return obj.__dict__[self.__name__]
   KeyError: 'backend'
   
   During handling of the above exception, another exception occurred:
   
   Traceback (most recent call last):
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\celery\worker\worker.py", line 205, in start
       self.blueprint.start(self)
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\celery\bootsteps.py", line 115, in start
       self.on_start()
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\celery\apps\worker.py", line 139, in on_start
       self.emit_banner()
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\celery\apps\worker.py", line 154, in emit_banner
       ' \n', self.startup_info(artlines=not use_image))),
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\celery\apps\worker.py", line 217, in startup_info
       results=self.app.backend.as_uri(),
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\kombu\utils\objects.py", line 44, in __get__
       value = obj.__dict__[self.__name__] = self.__get(obj)
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\celery\app\base.py", line 1196, in backend
       return self._get_backend()
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\celery\app\base.py", line 914, in _get_backend
       self.loader)
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\celery\app\backends.py", line 70, in by_url
       return by_name(backend, loader), url
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\celery\app\backends.py", line 50, in by_name
       cls = symbol_by_name(backend, aliases)
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\kombu\utils\imports.py", line 56, in symbol_by_name
       module = imp(module_name, package=package, **kwargs)
     File "D:\Programs\Python\Python37\lib\importlib\__init__.py", line 127, in import_module
       return _bootstrap._gcd_import(name[level:], package, level)
     File "", line 1006, in _gcd_import
     File "", line 983, in _find_and_load
     File "", line 967, in _find_and_load_unlocked
     File "", line 677, in _load_unlocked
     File "", line 724, in exec_module
     File "", line 860, in get_code
     File "", line 791, in source_to_code
     File "", line 219, in _call_with_frames_removed
     File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\celery\backends\redis.py", line 22
       from . import async, base
                         ^
   SyntaxError: invalid syntax
   

说明：这是因为在 python 3.7 中将 async 作为了关键字，所以当 py 文件中出现类似 from . import async, base 这类不符合python语法的语句时，Python会报错。

解决：

在 celery 官方的提议下，建议将 async.py 文件的文件名改成 asynchronous。所以我们只需要将 celery\backends\async.py 改成 celery\backends\asynchronous.py，并且把 celery\backends\redis.py 中的所有 async 改成 asynchronous 就可以了。

1. 重新运行 python manage.py celery worker 命令，celery 的 worker 运行成功！

• 安装

  pip install django-celery
  

• 通过 manage.py 脚本来启动 worker

  python manage.py celery worker -l INFO -Q [queue_name]
  

Celery 的监控工具: flower

• 安装

  pip install flower
  

• 启动

  • 正常启动

    celery flower --address=0.0.0.0 --port=5555 --broker=xxx --basic_auth=finlu:finlu
    

  参数说明：

  • adderss: flower 服务的地址
  • port: flower 服务的端口
  • broker:
  • basic_auth: flower 的基本认证
  • 通过 manage.py 脚本启动（可以读取到 settings.py 中的配置信息）

  python manage.py celery flower
  

  在 windows 上 worker 执行任务时崩溃

  • 报错信息

    Traceback (most recent call last):
    File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\billiard\pool.py", line 358, in workloop
      result = (True, prepare_result(fun(*args, **kwargs)))
    File "C:\Users\jzw\Desktop\celery_learn\dj_celery\venv\lib\site-packages\celery\app\trace.py", line 537, in _fast_trace_task
      tasks, accept, hostname = _loc
    ValueError: not enough values to unpack (expected 3, got 0)
    

  参考：

  https://github.com/celery/celery/pull/4078

  解决方案：

  • 在执行 worker 是设置 FORKED_BY_MULTIPROCESSING 环境变量的值为'1'（可以通过在 settings.py 中添加以下代码实现

    # settings.py
    import os
    
    os.environ.setdefault('FORKED_BY_MULTIPROCESSING', '1')
    

使用 supervisor 来部署管理 celery

• 安装 supervisor

  • 由于 pip 上的 supeervisor 只支持 python2.x， 所以选择在github上进行源码安装。
  • supervisor 项目地址：https://github.com/Supervisor/supervisor

• 配置

  • 修改 supervisor 基本配置

    # 将 `supervisor` 的配置存储在 `conf` 目录中
    mkdir conf
    echo_supervisord_conf > conf/supervisord.conf  # 将 `supervisor` 的默认配置重定向到 `supervisord.conf`
    

    在 supervisord.conf 中增加下列配置

    [unix_http_server]
    file=/tmp/supervisor.sock   ; the path to the socket file
    
    [inet_http_server]         ; inet (TCP) server disabled by default
    port=127.0.0.1:9001        ; ip_address:port specifier, *:port for all iface
    
    [supervisorctl]
    serverurl=unix:///tmp/supervisor.sock ; use a unix:// URL  for a unix socket
    
    [include]
    files = *.ini
    

  • 在 conf 文件夹下增加进程的配置

    • supervisor_celery_worker.ini 配置 celery worker

      [program:celery-worker]
      command=python manage.py celery worker -l INFO  # 运行的命令
      directory=/home/finlu/celery_learn/dj_celery   # 命令运行的目录
      enviroment=PATH="/home/finlu/celery_learn/dj_celery/venv/bin"  # Python虚拟环境
      stdout_logfile=/home/finlu/celery_learn/dj_celery/logs/celery.worker.log  # 输出日志
      stderr_logfile=/home/finlu/celery_learn/dj_celery/logs/celery.worker.log  # 错误日志
      autostart=True  # 自动启动
      autorestart=True  # 自动重启
      startsecs=10  # 启动延时
      stopwatisecs=60  # 停止延迟
      priority=998  # 进程优先级
      

    • supervisor_celery_flower.ini 配置 celery flower

      [program:celery-flower]
      command=python manage.py celery flower
      directory=/home/finlu/celery_learn/dj_celery
      enviroment=PATH="/home/finlu/celery_learn/dj_celery/venv/bin"
      stdout_logfile=/home/finlu/celery_learn/dj_celery/logs/celery.flower.log
      stderr_logfile=/home/finlu/celery_learn/dj_celery/logs/celery.flower.log
      autostart=True
      autorestart=True
      startsecs=10
      stopwatisecs=60
      priority=1000
      

    • supervisor_celery_beat.ini # 配置 celery beat

      [program:celery-beat]
      command=python manage.py celery beat -l INFO
      directory=/home/finlu/celery_learn/dj_celery
      enviroment=PATH="/home/finlu/celery_learn/dj_celery/venv/bin"
      stdout_logfile=/home/finlu/celery_learn/dj_celery/logs/celery.beat.log
      stderr_logfile=/home/finlu/celery_learn/dj_celery/logs/celery.beat.log
      autostart=True
      autorestart=True
      startsecs=10
      stopwatisecs=60
      priority=997
      

• 运行 supervisor

  • 指定配置文件并运行 supervisor

    supervisord -c conf/supervisord.conf
    

  • 使用 supervisorctl 命令进行管理
    • update: 更新配置信息（相当于restart）

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