I recently started using https://github.com/prefix-dev/pixi for Python projects. I really love it so far, but this tool looks a bit more mature, which makes sense considering pixi is relatively new.
For as much improvement as there has been with what can be distributed via PyPI, there are still some domains that have gnarlier dependencies than wheels happily handle alone, and you either need to reach for the system package manager (and loose the ability to really control the dependency environment from that mismatch), or take advantage of the Conda ecosystem.
My org does a lot of work combining machine learning with oceanographic and climate modeling, which are both domains that have deep dependency chains that don't always mesh well, especially as our researchers mix in R and other languages as the same time, and the Conda ecosystem helps us a ton with that, but there are issues that `conda` and `mamba` don't help us out with.
Pixi takes a swing at some of what the Conda ecosystem hasn't been great at (at least without a lot of manual custom ceremony) that Cargo, Poetry, Pipenv, PDM, and other dependency and workflow management tools have demonstrated can be done such as lock files, cross platform dependency management, task running, and defining multiple related environments.
I know this is over a week old, just coming back to say I moved off Poetry in favor of PDM. The main reason is because of PDM's built in scripting/tasks management. I have to install a plugin to get this with Poetry, and it's clumsy even then.
The other 2 reasons are more subjective. The first being I've had less issues installing packages with PDM. It's been a while and I don't remember which specific packages Poetry struggled to install, but my takeaway was just that I don't run into those problems with PDM the way I did with Poetry.
The other larger/more consequential reason is the maintainers of Poetry. There have been a number of GitHub issues replies laying out plans for things they will/won't do with Poetry, and it didn't inspire confidence in me. I want to do things the "Python way," not the "Poetry way," and PDM adheres more closely to the direction the Python project is moving. I don't want surprises later down the road when a tool (Poetry) is doing a bunch of custom stuff that eventually may not be compatible with the ecosystem at large.
All that being said, I had a lot of good things to say about Poetry while I was using it, and I do understand why people make it their package/project manager. Just wasn't the right fit for me.
My experience with Poetry has been mixed the last couple of times I've tried it, it attempts to do way to many things but often failed to do them properly. Determining dependencies and proper packaging and upload to PyPI are the ones which come to mind.
asdf.vm together with pipenv is my go-to for Python environment management.
As for Poetry, it is constantly improving and has gotten very popular. It should not be dismissed, especially for larger projects since its dependency management is so much better than pipenv. This is a good primer: https://diegoquintanav.github.io/poetry-primer.html
pyenv + pip tools is all one needs. Supposedly uv is gunning to be a drop in for both. I think there’s a good chance uv pulls it off and becomes defacto for this use case.
I think it’s fair to see appeal in poetry, but ultimately the maintainers have created a culture that feels a bit too non-collaborative to outside ideas or use cases beyond what they more narrowly envisage. That said, my perspective may just be tainted by multiple poor experiences interacting with the maintainers.
I can’t speak to rbenv or npm, but IMO it’s better of use well known and canonical tools for each rather than a more unknown mega tool that wraps or replaces these.
pyenv isn’t perfect, and isn’t what I’d use for prod images, but for dev setup it’s relatively bulletproof and less issue-prone than any alternative I’ve seen.
