Python 3.x 为什么芹菜工人将任务置于挂起状态这么长时间？

我有一个芹菜工人运行tasks.py，如下所示：

from celery import Celery
from kombu import Connection, Exchange, Queue, Consumer
import socket


app = Celery('tasks', backend='redis://', broker='pyamqp://guest:guest@localhost/')
app.conf.task_default_queue = 'default'
app.conf.task_queues = (
    Queue('queue1',    routing_key='tasks.add'),
    Queue('queueA',    routing_key='tasks.task_1'),
    Queue('queueB',    routing_key='tasks.task_2'),
    Queue('queueC',    routing_key='tasks.task_3'),
    Queue('queueD',    routing_key='tasks.task_4')
)


@app.task
def add(x, y):
    print ("add("+ str(x) + "+" + str(y) + ")")
    return x + y

from celery import signature

from celery import chain
from tasks import *

signature('tasks.add', args=(2,2))

result = chain(add.s(2,2), add.s(4), add.s(8)).apply_async(queue='queue1')

print (result.status)
print (result.get())

以及一个tasks_canvas.py，它创建了一个任务链，如下所示：

from celery import Celery
from kombu import Connection, Exchange, Queue, Consumer
import socket


app = Celery('tasks', backend='redis://', broker='pyamqp://guest:guest@localhost/')
app.conf.task_default_queue = 'default'
app.conf.task_queues = (
    Queue('queue1',    routing_key='tasks.add'),
    Queue('queueA',    routing_key='tasks.task_1'),
    Queue('queueB',    routing_key='tasks.task_2'),
    Queue('queueC',    routing_key='tasks.task_3'),
    Queue('queueD',    routing_key='tasks.task_4')
)


@app.task
def add(x, y):
    print ("add("+ str(x) + "+" + str(y) + ")")
    return x + y

from celery import signature

from celery import chain
from tasks import *

signature('tasks.add', args=(2,2))

result = chain(add.s(2,2), add.s(4), add.s(8)).apply_async(queue='queue1')

print (result.status)
print (result.get())

但是，当运行tasks_canvas.py时，result.status始终处于挂起状态，并且worker从不运行整个链。以下是正在运行的tasks_canvas.py的输出：

C:\Users\user_\Desktop\Aida>tasks_canvas.py
PENDING

下面是工人的输出：

C:\Users\user_\Desktop\Aida>celery -A tasks worker -l info -P eventlet

 -------------- celery@User-RazerBlade v4.2.0 (windowlicker)
---- **** -----
--- * ***  * -- Windows-10-10.0.17134-SP0 2018-07-16 12:04:20
-- * - **** ---
- ** ---------- [config]
- ** ---------- .> app:         tasks:0x41d5390
- ** ---------- .> transport:   amqp://guest:**@localhost:5672//
- ** ---------- .> results:     redis://
- *** --- * --- .> concurrency: 4 (eventlet)
-- ******* ---- .> task events: OFF (enable -E to monitor tasks in this worker)
--- ***** -----
 -------------- [queues]
                .> queue1           exchange=(direct) key=tasks.add
                .> queueA           exchange=(direct) key=tasks.task_1
                .> queueB           exchange=(direct) key=tasks.task_2
                .> queueC           exchange=(direct) key=tasks.task_3
                .> queueD           exchange=(direct) key=tasks.task_4

[tasks]
  . tasks.add
  . tasks.task_1
  . tasks.task_2
  . tasks.task_3
  . tasks.task_4
  . tasks.task_5

[2018-07-16 12:04:20,334: INFO/MainProcess] Connected to amqp://guest:**@127.0.0.1:5672//
[2018-07-16 12:04:20,351: INFO/MainProcess] mingle: searching for neighbors
[2018-07-16 12:04:21,394: INFO/MainProcess] mingle: all alone
[2018-07-16 12:04:21,443: INFO/MainProcess] celery@User-RazerBlade ready.
[2018-07-16 12:04:21,448: INFO/MainProcess] pidbox: Connected to amqp://guest:**@127.0.0.1:5672//.
[2018-07-16 12:04:23,101: INFO/MainProcess] Received task: tasks.add[e6306b5b-211f-4015-b57e-05e2d0ac2df2]
[2018-07-16 12:04:23,102: WARNING/MainProcess] add(2+2)
[2018-07-16 12:04:23,128: INFO/MainProcess] Task tasks.add[e6306b5b-211f-4015-b57e-05e2d0ac2df2] succeeded in 0.031000000000858563s: 4

---

我想知道为什么会发生这种情况，因为我对芹菜不熟悉，我如何让工人来管理整个链条？

我解决了这个问题。关于任务为什么总是处于挂起状态，有一个指南。但是，它并不涵盖所有情况。在我的例子中，有一个任务路由问题。当我使用默认队列时，链中的所有任务都会立即运行