Guix

I recently installed Guix in hopes of learning to use it. I wanted to update the system and gathered from the reference card that the proper command was "guix pull". My issue is that while no error message is given this didn't seem to update anything after. One thing that makes me think this is that I'm still on the 6.0.10 kernel as I was before. Am I doing this wrong ?

Hello. I am new to the Guix GNU+Linux distro. And I'm trying to get the latest version of Anki (2.1.65). However, the newest version is not in the Guix channel. I'm reading here that a simple edit to the education.scm file (the version var) would fix it. Unfortunately, the education.scm file in a Guix system is readonly. Unless they update the code, my only option is to make a custom module and package to supply a newer version. Though, I don't know how to do that (I'm a noobie). I just need help on figuring that out. Any help is appreciated.

just decided to share this information on a cool recently released command that i have been eager to see for a while and hopefully jumpstart things on the guix community here!

How can I prevent Doom Emacs from pointlessly downloading emacs packages whenever I update it and instead load the ones provided by Guix?

I have this in my Doom configuration but I have no idea about how to test if it's working, and anyway Doom still dowloads i.e. undo-tree which I installed in my Guix profile

There is no shortage of package managers. Each tool makes its own set of tradeoffs regarding speed, ease of use, customizability, and reproducibility. Guix occupies a sweet spot, providing reproducibility by design as pioneered by Nix, package customization à la Spack from the command line, the ability to create container images without hassle, and more.

Beyond the “feature matrix” of the tools themselves, a topic that is often overlooked is packages—or rather, what’s inside of them. Chances are that a given package may be installed using any of the many tools at your disposal. But are you really getting the same thing regardless of the tool you are using? The answer is “no”, contrary to what one might think. The author realized this very acutely while fearlessly attempting to package the PyTorch machine learning framework for Guix.

This post is about the journey packaging PyTorch the Guix way, the rationale, a glimpse at what other PyTorch packages out there look like, and conclusions we can draw for high-performance computing and scientific workflows.