rmflight,
@rmflight@mastodon.social avatar

Kind of thankful that is not a system dependency that is pretty much embedded in the OS, and that I can upgrade it even on older software (like running R 4.3.0 on Ubuntu 20 LTS) without worrying about other things depending on it.

In contrast to 3.6, that I'm not keen to try and force an upgrade to 3.8 so I can get access to a newer version of SciPy that exposes some underlying functionality that one of our python packages depends on.

rmflight,
@rmflight@mastodon.social avatar

Before anyone suggests Docker or VM, this is already a VM running on top of a cluster of machines, and it has another big project for a manuscript that is currently under review inside of it, so I'm very hesitant to break it in any way before the manuscript is completely done.

So I guess I'm just leaving it be for now.

brodriguesco,
@brodriguesco@fosstodon.org avatar

@rmflight you could use python virtual environments for this. No VM or Docker needed, and you'll have per-project development environments.

rmflight,
@rmflight@mastodon.social avatar

@brodriguesco I've done that for packages, but not generally python versions.

Someone else suggested pyenv to give a custom version of python and packages, I will probably end up trying that.

brodriguesco,
@brodriguesco@fosstodon.org avatar

@rmflight yes exactly pyenv also allows you to choose python version afaik

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