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。

subprocess.run:

import subprocess
import re
active_process_txt = subprocess.run(['celery', '-A', 'my_proj', 'inspect', 'active'],
                                        stdout=subprocess.PIPE).stdout.decode('utf-8')
return len(re.findall(r'worker_pid', active_process_txt))

注意使用your_proj更改my_proj

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']

如果你正在使用芹菜+Django，最简单的方法是在虚拟环境中直接从终端使用命令检查任务，或者使用芹菜的完整路径:

道格:http://docs.celeryproject.org/en/latest/userguide/workers.html?highlight=revoke inspecting-workers

$ celery inspect reserved
$ celery inspect active
$ celery inspect registered
$ celery inspect scheduled

另外，如果你正在使用芹菜+RabbitMQ，你可以使用下面的命令检查队列列表:

更多信息:https://linux.die.net/man/1/rabbitmqctl

$ sudo rabbitmqctl list_queues

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