芹菜有效，但用花不起作用

Question

我安装了芹菜、RabitMQ和flower。我可以浏览到花端口。我有以下简单的工人，我可以连接到芹菜上，并从python程序调用：

# -*- coding: utf-8 -*-
"""
Created on Sat Dec 12 16:37:33 2015
@author: idf
"""
from celery import Celery
app = Celery('tasks', broker='amqp://guest@localhost//')
@app.task
def add(x, y):
    return x + y 

这个程序称之为

# -*- coding: utf-8 -*-
"""
Created on Sat Dec 12 16:40:16 2015
@author: idf
"""
from tasks import add
add.delay(36, 5)   

我这样开始吃芹菜：

idf@DellInsp:~/Documents/Projects/python3$ celery -A tasks worker --loglevel=info
    [2015-12-12 19:22:46,223: WARNING/MainProcess] /home/idf/anaconda3/lib/python3.5/site-packages/celery/apps/worker.py:161: CDeprecationWarning: 
    Starting from version 3.2 Celery will refuse to accept pickle by default.
    The pickle serializer is a security concern as it may give attackers
    the ability to execute any command.  It's important to secure
    your broker from unauthorized access when using pickle, so we think
    that enabling pickle should require a deliberate action and not be
    the default choice.
    If you depend on pickle then you should set a setting to disable this
    warning and to be sure that everything will continue working
    when you upgrade to Celery 3.2::
        CELERY_ACCEPT_CONTENT = ['pickle', 'json', 'msgpack', 'yaml']
    You must only enable the serializers that you will actually use.

      warnings.warn(CDeprecationWarning(W_PICKLE_DEPRECATED))
     -------------- celery@DellInsp v3.1.19 (Cipater)
    ---- **** ----- 
    --- * ***  * -- Linux-3.19.0-39-lowlatency-x86_64-with-debian-jessie-sid
    -- * - **** --- 
    - ** ---------- [config]
    - ** ---------- .> app:         tasks:0x7f61485e61d0
    - ** ---------- .> transport:   amqp://guest:**@localhost:5672//
    - ** ---------- .> results:     disabled
    - *** --- * --- .> concurrency: 4 (prefork)
    -- ******* ---- 
    --- ***** ----- [queues]
     -------------- .> celery           exchange=celery(direct) key=celery

    [tasks]
      . tasks.add
    [2015-12-12 19:22:46,250: INFO/MainProcess] Connected to amqp://guest:**@127.0.0.1:5672//
    [2015-12-12 19:22:46,267: INFO/MainProcess] mingle: searching for neighbors
    [2015-12-12 19:22:47,275: INFO/MainProcess] mingle: all alone
    [2015-12-12 19:22:47,286: WARNING/MainProcess] celery@DellInsp ready.
    [2015-12-12 19:22:47,288: INFO/MainProcess] Received task: tasks.add[3c0e5317-ac53-465e-a8fd-3e2861e31db6]
    [2015-12-12 19:22:47,289: INFO/MainProcess] Task tasks.add[3c0e5317-ac53-465e-a8fd-3e2861e31db6] succeeded in 0.00045899399992777035s: 41
^C
worker: Hitting Ctrl+C again will terminate all running tasks!
worker: Warm shutdown (MainProcess)

注意41 的正确输出

但是，如果传入flower参数，则在执行调用时不会发生任何事情。我在flower网站上也没有看到任何任务。

idf@DellInsp:~/Documents/Projects/python3$ celery flower -A tasks worker --loglevel=info
[I 151212 19:23:59 command:113] Visit me at http://localhost:5555
[I 151212 19:23:59 command:115] Broker: amqp://guest:**@localhost:5672//
[I 151212 19:23:59 command:118] Registered tasks: 
    ['celery.backend_cleanup',
     'celery.chain',
     'celery.chord',
     'celery.chord_unlock',
     'celery.chunks',
     'celery.group',
     'celery.map',
     'celery.starmap',
     'tasks.add']
[I 151212 19:23:59 mixins:231] Connected to amqp://guest:**@127.0.0.1:5672//
[W 151212 19:24:01 control:44] 'stats' inspect method failed
[W 151212 19:24:01 control:44] 'active_queues' inspect method failed
[W 151212 19:24:01 control:44] 'registered' inspect method failed
[W 151212 19:24:01 control:44] 'scheduled' inspect method failed
[W 151212 19:24:01 control:44] 'active' inspect method failed
[W 151212 19:24:01 control:44] 'reserved' inspect method failed
[W 151212 19:24:01 control:44] 'revoked' inspect method failed
[W 151212 19:24:01 control:44] 'conf' inspect method failed
^Cidf@DellInsp:~/Documents/Projects/python3$ 

最后，不确定这是一个错误，但我的花网站没有工人选项卡。

Answer 1

我不确定我是否理解，但你是在一起管理花和工人吗？Flower不处理任务。您必须同时运行两者，然后Flower才能用作监控工具。

运行芹菜：

celery -A tasks worker --loglevel=info

打开另一个外壳并运行花朵：

celery -A tasks flower --loglevel=info

然后转到http://localhost:5555看看你的工人。当然，如果你想看到一些东西，你必须运行一些任务。

Answer 2

面临同样的问题。以下是它的工作原理：

  rabbitmq:
    image: rabbitmq:3-management
  flower:
    image: mher/flower
    ports:
      - 5555:5555
    command:
      - "celery"
      - "--broker=amqp://guest@rabbitmq:5672//"
      - "flower"
      - "--broker_api=http://guest:guest@rabbitmq:15672/api//"
    depends_on:
      - rabbitmq