celery 'Worker-n' pid:xxxx 在我导入 hmmlearn 时以 'exitcode 1' 退出 [英] celery 'Worker-n' pid:xxxx exited with 'exitcode 1' when I import hmmlearn

问题描述

在我的 tasks.py 文件中，当我导入 hmmlearn 时，

In my tasks.py file, when I import hmmlearn,

from hmmlearn import hmm

并启动我的芹菜工人，我收到以下错误

and start my celery workers, I get the following error

[2017-06-14 09:18:27,638: INFO/MainProcess] Received task: 
sm.tasks.mytask[4e46806e-6f0f-420f-baac-c727c2a382d4]
[2017-06-14 09:18:27,716: ERROR/MainProcess] Process 'Worker-4' pid:5264 
exited with 'exitcode 1'
[2017-06-14 09:18:29,857: ERROR/MainProcess] Process 'Worker-7' pid:3172 
exited with 'exitcode 1'
[2017-06-14 09:18:29,857: ERROR/MainProcess] Process 'Worker-6' pid:5768 
exited with 'exitcode 1'
[2017-06-14 09:18:29,857: ERROR/MainProcess] Process 'Worker-5' pid:5236 
exited with 'exitcode 1'
[2017-06-14 09:18:31,450: ERROR/MainProcess] Process 'Worker-8' pid:5876 
exited with 'exitcode 1'

在我关闭工人之后，

[2017-06-14 09:19:28,545: WARNING/MainProcess] c:anaconda3libsite-
packagesceleryappsworker.py:161: CDeprecationWarning:
Starting from version 3.2 Celery will refuse to accept pickle by default.

如果我只是注释掉该导入并使用该导入进行编码，则一切正常.但是，我可以在 ipython 上将所有任务(包括 hmm 代码)作为独立的 python 代码执行，没有任何问题.

If I just comment out that import and code using that import, everything works fine. But, I'm able to execute all the tasks(including the hmm code) as standalone python code on ipython without any issues.

我正在使用带有以下详细信息的 conda 分发版

I'm using the conda distribution with following details

Current conda install:

           platform : win-64
      conda version : 4.3.21
   conda is private : False
  conda-env version : 4.3.21
conda-build version : 1.21.3
     python version : 3.5.2.final.0
   requests version : 2.14.2

λ conda list | grep celery
celery                    3.1.18                    <pip>

λ conda list | grep kombu
kombu                     3.0.37                    <pip>

λ conda list | grep hmmlearn
hmmlearn                  0.1.1               np111py35_0    omnia

我该怎么办?

推荐答案

这可能是因为 celery 3.1.xx 捆绑了台球 3.3.

This might be because celery 3.1.xx comes bundled with billiard 3.3.

如果您升级该软件包(在撰写本文时升级到 3.5)，该服务可能会再次运行.

If you upgrade that package (to 3.5 at time of writing), the service might work again.

pip install --upgrade billiard

这篇关于celery 'Worker-n' pid:xxxx 在我导入 hmmlearn 时以 'exitcode 1' 退出的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！