conda-libmamba-solver VS mamba

Lol, bro, use https://github.com/conda/conda-libmamba-solver

Link to relevant GitHub. (no affiliation)

I didn't know conda could use the same solver, thanks for that reference. Is this through this libmamba package? https://github.com/conda-incubator/conda-libmamba-solver

Completely - I assumed it was an implementation of https://github.com/mamba-org/mamba

I also assumed that "a pure NumPy implementation" meant that it was built purely numpy, which it isn't smh

>"everyone" seems to know Mamba. I never heard of Mamba

Only the "everybody who knows what mamba is" are the ones upvoting and commenting. Think of all the people who ignore it. For me, Mamba is the faster version of Conda [1], and that's why I clicked on the article.

https://github.com/mamba-org/mamba

Yes, this is a big disadvantage. But have you tried Mamba that aims at implementing Anaconda more efficiently? It works really well in most cases.

https://mamba.readthedocs.io/

Because conda is very slow at resolving dependencies. Mamba (https://github.com/mamba-org/mamba) is faster if that is your goal

use mamba instead

We started using tl::expected in https://github.com/mamba-org/mamba/ since the beginning of this year and some other related projects like https://github.com/mamba-org/powerloader . I don't know much other big open-source codebases that use that specific lib.

Great writeup. Minor comment about the portion of the post mentioning Conda being glacially slow: Mamba [1] is a much better drop-in replacement written in C++. Not only is it significantly faster, but error messages are much more sane and helpful.

That being said, I do agree that Pkg.jl is much more sleek and modern than Conda/Mamba.

[1]: https://github.com/mamba-org/mamba

I thought that python could live a little longer when I learned about mamba. But then I found out it is written in C++? Why write a package manager for a dying language in a language that is almost dead???