Python 如何保持多个独立的芹菜队列？
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How to keep multiple independent celery queues?
提问by jwoww
I'm trying to keep multiple celery queues with different tasks and workers in the same redis database. Really just a convenience issue of only wanting one redis server rather than two on my machine.
我试图在同一个 redis 数据库中保留多个具有不同任务和工作人员的 celery 队列。真的只是一个方便的问题，我的机器上只需要一个 redis 服务器而不是两个。
I followed the celery tutorial docs verbatim, as it as the only way to get it to work for me. Now when I try to duplicate everything with slightly tweaked names/queues, it keeps erroring out.
我逐字跟踪芹菜教程文档，因为这是让它为我工作的唯一方法。现在，当我尝试使用稍微调整的名称/队列复制所有内容时，它不断出错。
Note - I'm a newish to Python and Celery, which is obviously part of the problem. I'm not sure which parts are named "task/tasks" as a name vs special words.
注意 - 我是 Python 和 Celery 的新手，这显然是问题的一部分。我不确定哪些部分被命名为“任务/任务”作为名称与特殊词。
My condensed version of docs:
Run celery -A tasks workerto spawn the workers.
tasks.py contains task code with celery = Celery('tasks', broker='redis://localhost')to connect to Celery and @task()above my functions that I want to delay.
我的文档精简版：运行celery -A tasks worker以生成工人。tasks.py 包含celery = Celery('tasks', broker='redis://localhost')用于连接到 Celery 的任务代码以及@task()我想要延迟的函数。
Within my program for queueing tasks...
在我的排队任务程序中......
from tasks import do_work
do_work.delay()
So given all of the above, what are the steps I need to take to turn this into two types of tasks that run independently on separate queues and workers? For example, blue_tasks and red_tasks?
因此，鉴于上述所有内容，我需要采取哪些步骤才能将其转变为两种类型的任务，这些任务在单独的队列和工作人员上独立运行？例如，blue_tasks 和 red_tasks？
I've tried changing all instances of tasks to blue_tasks or red_tasks. However, when I queue blue_tasks, the red_tasks workers I've started up start trying to work on them.
我尝试将所有任务实例更改为 blue_tasks 或 red_tasks。但是，当我排队 blue_tasks 时，我启动的 red_tasks 工作人员开始尝试处理它们。
I read about default queues and such, so I tried this code, which didn't work:
我阅读了默认队列等内容，所以我尝试了这段代码，但没有用：
CELERY_DEFAULT_QUEUE = 'red'
CELERY_QUEUES = (
Queue('red', Exchange('red'), routing_key='red'),
)
As a side note, I don't understand why celery workererrors out with celery attempting to connect to a default amqp instance, while celery -A tasks workertells celery to connect to Redis. What task code is celery workerattempting to run on the worker if nothing has been specified?
作为旁注，我不明白为什么celery workercelery 尝试连接到默认 amqp 实例时出错，而celery -A tasks worker告诉 celery 连接到 Redis。celery worker如果没有指定什么任务代码试图在工作器上运行？
采纳答案by dbr
By default everything goes into a default queue named celery(and this is what celery workerwill process if no queue is specified)
默认情况下，所有内容都进入一个名为的默认队列celery（celery worker如果未指定队列，这将处理）
So say you have your do_worktask function in django_project_root/myapp/tasks.py.
因此，假设您do_work在django_project_root/myapp/tasks.py.
You could configure the do_worktask to live in it's own queue like so:
您可以将do_work任务配置为存在于它自己的队列中，如下所示：
CELERY_ROUTES = {
'myproject.tasks.do_work': {'queue': 'red'},
}
Then run a worker using celery worker -Q redand it will only process things in that queue (another worker invoked with celery workerwill only pickup things in the default queue)
然后运行一个工作程序celery worker -Q red，它只会处理该队列中的内容（另一个被调用的工作程序celery worker只会在默认队列中提取内容）
The task routingsection in the documentation should explain all.
文档中的任务路由部分应该解释所有。
回答by josepainumkal
To link to different queue dynamically, follow the below steps:
要动态链接到不同的队列，请按照以下步骤操作：
1) Specify the name of the queue with the 'queue' attribute
1) 使用'queue'属性指定队列的名称
celery.send_task('job1', args=[], kwargs={}, queue='queue_name_1')
celery.send_task('job1', args=[], kwargs={}, queue='queue_name_2')
(Here a particular job uses two queues)
（此处特定作业使用两个队列）
2) Add the following entry in the configuration file
2）在配置文件中添加如下条目
CELERY_CREATE_MISSING_QUEUES = True
3) While starting the worker, use -Q to specify the queue name' from which the jobs to be consumed
3）在启动worker时，使用-Q指定要消耗的作业的队列名称
celery -A proj worker -l info -Q queue1
celery -A proj worker -l info -Q queue2
