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Conda: A package management disaster?

pyherald.com

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Re: Conda: A package management disaster?

#3

Post by anakaine »

orf wrote: post #2

Impossible to read on mobile, least of all because of the lack of any word breaking.

Seconded. How about we don't write a blog trashing an implementation of something when our own design is missing some very basic accessibility and ux features.

Though I agree with the premise, Conda is an absolute pest when you start customising an environment with a number of packages. Dependency resolution hell.

Re: Conda: A package management disaster?

#4

Post by alsodumb »

As someone with admittedly no formal CS education, I've been using conda for all of my grad school and never managed to break it.

I create a virtual environment for every project. I install almost all packages with pip, except for any binaries or CUDA related things from conda. I always exported the conda yaml file and managed to reproduce the code/environment including the Python version. I've seen a lot of posts over time praising poetry and other tools and complaining about conda but I could never relate to any of them.

Am i doing something wrong? Or something right?

Re: Conda: A package management disaster?

#5

Post by thangngoc89 »

alsodumb wrote: post #4

As someone with admittedly no formal CS education, I've been using conda for all of my grad school and never managed to break it. I create a virtual environment for every project. I install almost all packages with pip, except for any binaries or CUDA related things from conda. I always exported the conda yaml file and managed to reproduce the code/environment including the Python version. I've seen a lot of posts ov…

1. You need to run export manual while other tools you mentioned would create it automatically (the lock file) 2. Distinguishes between direct dependencies (packages you added yourself) and indirect dependencies (packages of the packages)

Re: Conda: A package management disaster?

#7

Post by theamk »

alsodumb wrote: post #4

As someone with admittedly no formal CS education, I've been using conda for all of my grad school and never managed to break it. I create a virtual environment for every project. I install almost all packages with pip, except for any binaries or CUDA related things from conda. I always exported the conda yaml file and managed to reproduce the code/environment including the Python version. I've seen a lot of posts ov…

You are doing something right, author does some pretty unusual things:

- Setup custom kernels in Jupyter Notebook

- Hardlink the environments, then install same packages via pip in one and conda in others

- install conda inside conda (!!!) and enter nested environment

- Use tox within conda

I believe as long as you treat the environments as "cattle" (if it goes bad, remove it and re-create from yaml file), you should not have any problems. It's clearly not the case of for the post's author though.

Re: Conda: A package management disaster?

#9

Post by throwawaymaths »

alsodumb wrote: post #4

As someone with admittedly no formal CS education, I've been using conda for all of my grad school and never managed to break it. I create a virtual environment for every project. I install almost all packages with pip, except for any binaries or CUDA related things from conda. I always exported the conda yaml file and managed to reproduce the code/environment including the Python version. I've seen a lot of posts ov…

i think you got lucky and fell into best practices on your first go

> except for any binaries or CUDA related things from conda

doing the default thing with cuda related python packages used to often result in "fuck it, reinstall linux". admittedly, i dont know how it is now. i have one machine that runs python with a gpu and it runs only one python program.

Re: Conda: A package management disaster?

#10

Post by duped »

alsodumb wrote: post #4

As someone with admittedly no formal CS education, I've been using conda for all of my grad school and never managed to break it. I create a virtual environment for every project. I install almost all packages with pip, except for any binaries or CUDA related things from conda. I always exported the conda yaml file and managed to reproduce the code/environment including the Python version. I've seen a lot of posts ov…

My experience with conda is that its fine if you're the original author of whatever you're using it for and never share it with anyone else. But as a professional I usually have to pull in someone else's work and make it function on a completely different machine/environment. I've only had negative experiences with conda for that reason. IME the hard job of package management is not getting software to work in one location, but allowing that software to be moved somewhere else and used in the same way. Poetry solves that problem, conda doesn't.

Poetry isn't perfect, but it's working in an imperfect universe and at least gets the basics (lockfiles) correct to where packages can be semi-reproducible.

There's another rant to be had at the very existence of venvs as part of the solution, but that's neither poetry or anaconda's fault.

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