NonlinearSolve.jl VS Unitful.jl

I would highly suggest using NonlinearSolve.jl instead as it's more maintained. For this, the solution object is documented here: https://docs.sciml.ai/NonlinearSolve/stable/basics/NonlinearSolution/

Julia's Unitful package is one of my favorites. https://github.com/PainterQubits/Unitful.jl

Tangentially related, LaTeX's siunitx package makes typesetting units a joy. https://ctan.org/pkg/siunitx

Laughs in https://github.com/PainterQubits/Unitful.jl

Not sure why you think more units is more powerful. Defining specific units is seldom the difficult part of dealing with units in code. I'd say that just looking at the tests for Unitful (excluding the separate tests for dates) to the tests of Similitude that there seems to be a lot more functionality in Unitful. What are the advantages of these alternate packages? And I do not think focusing on "more powerful" is too useful unless qualified appropriately.

It's really two separate problems but they kinda interact.

Unitful quantities with heterogeneous units don't have a `zero` function that works correctly, which gets in the way inside numerical routines. [0] There are other places where 0 or 1 is added, which is an error for quantities but not for plain real numbers. [1]

Zygote doesn't handle mutating arrays. [2]

[0]: https://github.com/PainterQubits/Unitful.jl/pull/472

Julia has the Unitful package [1], which does a decent job. It's quite ergonomic, and Julia's design helps with making existing code/libraries play nicely with Unitful-encoded units/values.

[1] https://github.com/PainterQubits/Unitful.jl

I've seen a few before, and a quick search yielded a bunch for me, right off the bat. By no means exhaustive:

Julia: https://github.com/PainterQubits/Unitful.jl

Python: https://pint.readthedocs.io/en/0.6/

C++: https://github.com/nholthaus/units

etc.

And yes, it has always struck me as strange that date/time/calendar libraries are standard as canonical libraries shipped with language distributions, but units are not.