[droelf]

Thanks for bringing up conda. We're definitely trying to paint this vision as well with `pixi` (https://pixi.sh) - which is a modern package manager, written in Rust, but using the Conda ecosystem under the hood.

It follows more of a project based approach, comes with lockfiles and a lightweight task system. But we're building it up for much bigger tasks as well (`pixi build` will be a bit like Bazel for cross-platform, cross-language software building tasks).

While I agree that conda has many short-comings, the fundamental packages are alright and there is a huge community keeping the fully open source (conda-forge) distribution running nicely.

[bitvoid]

I just want to give a hearty thank you for pixi. It's been an absolute godsend for us. I can't express how much of a headache it was to deal with conda environments with student coursework and research projects in ML, especially when they leave and another student builds upon their work. There was no telling if the environment.yml in a student's repo was actually up to date or not, and most often didn't include actual version constraints for dependencies. We also provide an HPC cluster for students, which brings along its own set of headaches.

Now, I just give students a pixi.toml and pixi.lock, and a few commands in the README to get them started. It'll even prevent students from running their projects, adding packages, or installing environments when working on our cluster unless they're on a node with GPUs. My inbox used to be flooded with questions from students asking why packages weren't installing or why their code was failing with errors about CUDA, and more often than not, it was because they didn't allocate any GPUs to their HPC job.

And, as an added bonus, it lets me install tools that I use often with the global install command without needing to inundate our HPC IT group with requests.

So, once again, thank you