Task handler raised error: ValueError(‘not enough values to unp…

Python version 3.7.2

Celery – Distributed task queues

Celery is a simple, flexible and reliable distributed system that processes large amounts of messages and provides the necessary tools to maintain such a system. It is a task queue that focuses on real-time processing and also supports task scheduling.

Usage scenario: A user initiates a request and waits for a response to return. In some views, users may have to wait for a long time to execute a time-consuming program, resulting in poor user experience, such as sending emails and mobile verification codes. With celery, the situation is different. Solution: Put time-consuming procedures into celery to execute.

  • Please click on the celery official website
  • Click to view celery Chinese file

Celery nouns:

  • Task: is a Python function.
  • Queue: Adds tasks to be executed to a queue.
  • Worker: Performs tasks in a queue in a new process.
  • Broker: Responsible for scheduling, redis needs to be deployed in advance.

The installation package:

Pip3 install -celery pip3 install django- Celery == Celery"celery[librabbitmq,redis,auth,msgpack]"
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Version celery 4.3.0

The sample

1) Create view sayHello in assetinfo/views.py.

import time
...
def sayhello(request):
    print('hello ... ')
    time.sleep(2)
    print('world ... ')
    return HttpResponse("hello world")
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2) Configure it in assetinfo/urls.py.

urlpatterns = [
    # ex:/assetinfo/sayhello
    path('sayhello', views.sayhello, name='sayhello'),]Copy the code

3) Start the server and enter the following url in the browser:

http://127.0.0.1:8000/assetinfo/sayhello

4) The browser took 2 seconds to complete the access because the view was set to sleep 2 seconds.

5) Install in project /settings.py.

INSTALLED_APPS = (
  ...
  'djcelery',}Copy the code

6) Create a celery_tasks package file to store the tasks.py task scripts

7) Create the tasks.py file in the celery_tasks directory.

from celery import Celery
import time

Create an instance object of Celery class
app = Celery('celery_tasks.tasks', broker='redis: / / 127.0.0.1:6379/8')

@app.task
def async_sayhello():
    print('hello ... ')
    time.sleep(2)
    print('world ... ')
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8) Open the assetinfo/views.py file and modify the sayHello view as follows:

from celery_tasks.tasks import async_sayhello

def sayhello(request):
    # print('hello ... ')
    # time.sleep(2)
    # print('world ... ')
    async_sayhello.delay()
    return HttpResponse("hello world")
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Data table needed to perform celery generation.

python3 manage.py migrate
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The following table is generated:

10) Start Redis, if already started, do not need to start.

[root@server01 ~]# ps -ef | grep redisroot 3694 3462 0 00:41 pts/4 00:00:00 grep --color=auto redis root 31054 1 0 Jun27 ? 01:12:52./redis-server 127.0.0.1:6379 [root@server01 ~]# redis-cli 127.0.0.1:6379 >Copy the code

11) Start the worker. celery -A celery_tasks.tasks worker –loglevel=info

Celery = ‘celery’

http://127.0.0.1:8000/assetinfo/sayhello

Check error as follows:

[2019-08-01 00:16:03,062: ERROR/MainProcess] Task handler raised error: ValueError('not enough values to unpack (expected 3, got 0)')
Traceback (most recent call last):
  File "g:\python3\python371\lib\site-packages\billiard\pool.py", line 358, in workloop
    result = (True, prepare_result(fun(*args, **kwargs)))
  File "g:\python3\python371\lib\site-packages\celery\app\trace.py", line 544, in _fast_trace_task
    tasks, accept, hostname = _loc
ValueError: not enough values to unpack (expected 3, got 0)
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After looking up the information it was found that there was an issue with the high version of celery running in Win10.

13) Resolve the error

Solution:

Unable to Run Tasks under Windows

Win10: celery4. X: celery4. X: celery4.

Start by installing an Eventlet

pip3 install eventlet
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Then add a parameter to start the worker as follows:

celery -A <mymodule> worker -l info -P eventlet
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Officially implemented as follows:

(venv) F:\pythonProject\django-pratice>celery -A celery_tasks.tasks worker -lInfo - P eventlet -- -- -- -- -- -- -- -- -- -- -- -- -- -- celery @ USC2VG2F9NPB650 v4.3.0 (rhubarb) - * * * * -- -- -- -- -- -- -- -- - * * * * * Windows 2019-08-01-10-10.0.17763 - SP0 00:22:21 - * - * * * * * * -- -- -- -- -- -- -- -- -- -- -- -- -- -- (config) * * -- -- -- -- -- -- -- -- -- -. > app: Celery_tasks. Tasks: 0 x1e4a24170f0 - * * -- -- -- -- -- -- -- -- -- - > transport: redis: / / 127.0.0.1:6379/8 - * * -- -- -- -- -- -- -- -- -- - > the results: disabled:// - *** --- * --- .> concurrency: 12 (eventlet) -- ******* ---- .> task events: OFF (enable -E to monitor tasks inthis worker) --- ***** ----- -------------- [queues] .> celery exchange=celery(direct) key=celery [tasks] . Celery_tasks. Tasks. Async_sayhello [00:22:21 2019-08-01, 629: INFO/MainProcess] Connected to Redis ://127.0.0.1:6379/8 [2019-08-01 00:22:21,700: INFO/MainProcess] Mingle: searchingforNeighbors [2019-08-01 00:22:22,913: INFO/MainProcess] Mingle: All alone with Neighbors [2019-08-01 00:22:22, 012] INFO/MainProcess] celery@USC2VG2F9NPB650 ready. [2019-08-01 00:22:23,045: INFO/MainProcess] Connected to redis: / / 127.0.0.1:6379/8.Copy the code

Once again, visit http://127.0.0.1:8000/assetinfo/sayhello

The following information is displayed: