maxima-jupyter VS reduce-algebra

An alternative is to run maxima from jupyter: https://github.com/robert-dodier/maxima-jupyter.

Usually the arguments are a) it provides runtime access to the source (which for example is useful in R), b) runtime introspection is easier to understand (for the proponents) and c) macros are too static (they want more flexibility at runtime). For example authors of the REDUCE computer algebra system disliked Common Lisp for the lack of FEXPRs and that's why they stayed away from it: https://reduce-algebra.sourceforge.io/ .

> The languages you mention probably

No, see above.

Reduce is another lisp based computer algebra system from the prehistoric times, now open sourced.

https://en.wikipedia.org/wiki/Reduce_(computer_algebra_syste...

https://reduce-algebra.sourceforge.io/

I paid money for a Reduce release for RISCOS back in the last ice age. I recollect having to register my licence with the Rand Corporation for some reason.

I idly wonder how these compare to the arbitrary-precision implementations in REDUCE (https://github.com/reduce-algebra/reduce-algebra/blob/master...) - written mostly by me, 30 years ago in the unusual, Lisp-based but largely procedural, language of REDUCE. Can't remember much about the subject now.

The citations in the Julia source file are certainly newer - Abramowitz and Stegun was basically all I had.

I think the REDUCE functions were considered quite fast (for higher precision) at the time, but it was certainly true that they weren't tested as thoroughly as would be the norm now.