That is why I created
https://codeberg.org/ZelphirKaltstahl/guile-examples. I like GNU Guile and many things exist, even in the batteries that are included, but are not easy to find or one needs to figure out how to effectively use them. Also got an awesome list somewhere, but I need to migrate that to codeberg later.
Compared to some other languages, the ecosystem is small though. While in Python often you have 3 or 4 libraries solving the same or similar problem, in GNU Guile you often only have 1 or need to write your own. Knowledgeable people are able to quickly throw something together, or call out to C libraries using FFI, but I have not done FFI yet. Some day I really should look into that ... And into Hoot by Spritely Institute [1]
If one wants to check out more algorithmic stuff, I also have some stuff on that: AoC 2024[2] (and previous years too), and guile-algorithms[3] (not that much yet, but useful things, and trying to keep it fully functional). Some time ago I also wrote a toy implementation of a decision tree in Guile[4]. It is even parallelized and achieves linear speedup in my tests. I call it a toy, because you will have to do all the data preparation yourself, because it only deals with numbers, and there are probably smarter ways of storing the data for each node, maybe even avoiding duplication. There is also no library like numpy or dataframes like in Python, so I am using possibly not so optimal data structures. But it is probably worth checking out and adapting, if anyone wants to make a proper decision tree library. It is a start.
[1]: https://spritely.institute/
[2]: https://codeberg.org/ZelphirKaltstahl/advent-of-code-2024
[3]: https://codeberg.org/ZelphirKaltstahl/guile-algorithms
[4]: https://codeberg.org/ZelphirKaltstahl/guile-ml