[amakelov]

Thanks Rachit! Great running into you after all these years!

Being aware of types is certainly a must in a more performance-critical implementation; this project is not at this stage though, opting for simplicity and genericity instead. I've found this best for maintenance until the core stabilizes; plus, it's not a major pain point in my ML projects yet.

Regarding incremental computation: the main idea is simple - if you call a function on some inputs, and this function was called on the same (modulo hashing) inputs in the past and used some set of dependencies that currently have the same code as before (or compatible code, if manually marked by the user), the past call's outputs are reused (key question here: will there be at most one such past call? yes, if functions invoke their dependencies deterministically).

You can probably add some tools to automatically delete old versions and everything that depends on them, but this is definitely a decision the user must make (e.g., you might want to be able to time-travel back to look at old results). I'm happy to answer more nuanced questions about the incremental computation implementation in `mandala` if you have any!