如果你不使用优先级任务，这其实很简单，如果你使用的是Redis。获取任务计数:

redis-cli -h HOST -p PORT -n DATABASE_NUMBER llen QUEUE_NAME

但是，优先级任务在redis中使用不同的键，所以整体情况稍微复杂一些。总的来说，您需要为任务的每个优先级查询redis。在python中(以及在Flower项目中)，它看起来像:

PRIORITY_SEP = '\x06\x16'
DEFAULT_PRIORITY_STEPS = [0, 3, 6, 9]


def make_queue_name_for_pri(queue, pri):
    """Make a queue name for redis

    Celery uses PRIORITY_SEP to separate different priorities of tasks into
    different queues in Redis. Each queue-priority combination becomes a key in
    redis with names like:

     - batch1\x06\x163 <-- P3 queue named batch1

    There's more information about this in Github, but it doesn't look like it 
    will change any time soon:

      - https://github.com/celery/kombu/issues/422

    In that ticket the code below, from the Flower project, is referenced:

      - https://github.com/mher/flower/blob/master/flower/utils/broker.py#L135

    :param queue: The name of the queue to make a name for.
    :param pri: The priority to make a name with.
    :return: A name for the queue-priority pair.
    """
    if pri not in DEFAULT_PRIORITY_STEPS:
        raise ValueError('Priority not in priority steps')
    return '{0}{1}{2}'.format(*((queue, PRIORITY_SEP, pri) if pri else
                                (queue, '', '')))


def get_queue_length(queue_name='celery'):
    """Get the number of tasks in a celery queue.

    :param queue_name: The name of the queue you want to inspect.
    :return: the number of items in the queue.
    """
    priority_names = [make_queue_name_for_pri(queue_name, pri) for pri in
                      DEFAULT_PRIORITY_STEPS]
    r = redis.StrictRedis(
        host=settings.REDIS_HOST,
        port=settings.REDIS_PORT,
        db=settings.REDIS_DATABASES['CELERY'],
    )
    return sum([r.llen(x) for x in priority_names])

如果你想要获得一个实际的任务，你可以使用以下方法:

redis-cli -h HOST -p PORT -n DATABASE_NUMBER lrange QUEUE_NAME 0 -1

从那里，您必须反序列化返回的列表。以我为例，我可以通过以下方法来实现:

r = redis.StrictRedis(
    host=settings.REDIS_HOST,
    port=settings.REDIS_PORT,
    db=settings.REDIS_DATABASES['CELERY'],
)
l = r.lrange('celery', 0, -1)
pickle.loads(base64.decodestring(json.loads(l[0])['body']))

请注意，反序列化可能需要一些时间，您需要调整上面的命令以处理不同的优先级。

如果你正在使用rabbitMQ，在终端中使用这个:

sudo rabbitmqctl list_queues

它将打印带有挂起任务数量的队列列表。例如:

Listing queues ...
0b27d8c59fba4974893ec22d478a7093    0
0e0a2da9828a48bc86fe993b210d984f    0
10@torob2.celery.pidbox 0
11926b79e30a4f0a9d95df61b6f402f7    0
15c036ad25884b82839495fb29bd6395    1
celerey_mail_worker@torob2.celery.pidbox    0
celery  166
celeryev.795ec5bb-a919-46a8-80c6-5d91d2fcf2aa   0
celeryev.faa4da32-a225-4f6c-be3b-d8814856d1b6   0

右边列的数字是队列中的任务数。在上面，芹菜队列有166个待处理的任务。

这在我的申请中很奏效:

def get_celery_queue_active_jobs(queue_name):
    connection = <CELERY_APP_INSTANCE>.connection()

    try:
        channel = connection.channel()
        name, jobs, consumers = channel.queue_declare(queue=queue_name, passive=True)
        active_jobs = []

        def dump_message(message):
            active_jobs.append(message.properties['application_headers']['task'])

        channel.basic_consume(queue=queue_name, callback=dump_message)

        for job in range(jobs):
            connection.drain_events()

        return active_jobs
    finally:
        connection.close()

Active_jobs将是一个字符串列表，对应于队列中的任务。

不要忘记将CELERY_APP_INSTANCE替换为您自己的。

感谢@ashish在这里为我指出了正确的方向:https://stackoverflow.com/a/19465670/9843399

EDIT:查看获取队列中任务列表的其他答案。

你应该看这里: 芹菜指南-检查工人

基本上是这样的:

my_app = Celery(...)

# Inspect all nodes.
i = my_app.control.inspect()

# Show the items that have an ETA or are scheduled for later processing
i.scheduled()

# Show tasks that are currently active.
i.active()

# Show tasks that have been claimed by workers
i.reserved()

这取决于你想要什么

Redis json序列化的复制粘贴解决方案:

def get_celery_queue_items(queue_name):
    import base64
    import json  

    # Get a configured instance of a celery app:
    from yourproject.celery import app as celery_app

    with celery_app.pool.acquire(block=True) as conn:
        tasks = conn.default_channel.client.lrange(queue_name, 0, -1)
        decoded_tasks = []

    for task in tasks:
        j = json.loads(task)
        body = json.loads(base64.b64decode(j['body']))
        decoded_tasks.append(body)

    return decoded_tasks

它与Django一起工作。只是别忘了改变你的项目。

要获得队列上的任务数，你可以使用flower库，下面是一个简化的例子:

from flower.utils.broker import Broker
from django.conf import settings

def get_queue_length(queue):
    broker = Broker(settings.CELERY_BROKER_URL)
    queues_result = broker.queues([queue])
    return queues_result.result()[0]['messages']