为什么jupyter笔记本电脑的子过程结果不同？

发布于 2025-02-04 21:21:43 字数 646 浏览 1 评论 0原文

我正在尝试了解subprocess模块在Linux上的Jupyter笔记本上运行时的行为。我正在使用subprocess来捕获Linux上的开放文件限制的数量。在终端上如下：

ulimit -n

这给了我1024的限制。

如果我使用subprocess从命令行上的python调用此，则我仍然可以预期的是1024：

from subprocess import call
call("ulimit -n", shell = True)

但是，如果我运行此操作从jupyter笔记本电脑中，我得到4096。

如果我使用Resource模块来找出软限制，也可以合作。以下内容从命令行提供了1024，但是jupyter笔记本中的4096。

import resource
soft, hard = resource.getrlimit(resource.RLIMIT_NOFILE)
soft

我（可能是幼稚的）假设是subprocess.call应该给我相同的结果，而不管我从哪里调用。谁能解释什么原因导致差异？

原文

I am trying to understand the behaviour of the subprocess module when it is running on a Jupyter notebook on linux. I am using subprocess to capture the number of open files limit on Linux. On the terminal this is as follows:

ulimit -n

This gives me a limit of 1024.

If I call this using subprocess from Python on the command line, I still get 1024, as expected:

from subprocess import call
call("ulimit -n", shell = True)

However, if I run this from a Jupyter notebook, I get 4096.

The same also holds if I use the resource module to find out the soft limit. The following gives me 1024 from the command line, but 4096 from a Jupyter notebook.

import resource
soft, hard = resource.getrlimit(resource.RLIMIT_NOFILE)
soft

My (possibly naive) assumption is that subprocess.call should give me the same results regardless of where I am calling it from. Can anyone explain what causes the difference?

分享到QQ

分享到微博