Since you've posted in HN about the state of Julia in 2024, I think you have the knowledge, and perhaps the desire, to provide information about what the improvement are in Julia with respect to problems expressed in the 2022 long discussion by Yuri Vishnevsky (1).
replyAnyway the problem I see is that other languages and tools are also improving, for example the author of this post (2) "I am reluctant to shift to Symbolics, as the calculus specifics (limits and integrals) aren't as competitive".
(1) https://discourse.julialang.org/t/discussion-on-why-i-no-lon...
(2) https://github.com/jverzani/CalculusWithJulia.jl/issues/50
Edited for grammar and spelling.
As to (1), all the bugs Yuri filed seem to be fixed, save https://github.com/JuliaLang/julia/issues/39385, for which there is a largish PR that's still wending it's way to being merged.
replyAll the bugs he listed as "filed by others" also seem to have been fixed, again save for one: https://github.com/JuliaLang/julia/issues/36069.
I'm not sure I understand what you're getting at with (2).
My question from (2) would be: is Symbolics still not on par with SymPy?
replyHave you ever looked into APL or BQN?
replyBQN is not intended for this!
replyToo dissimilar to the blackboard although I really do like them
replyI have, compared to Julia they’re both just overall too slow. Same with K and Uiua and Matlab.
replyDo you seriously need performance to teach integrals or derivatives?
replyI understand TFA is scoped to calculus, but the parent post scoped their usage of Julia to "anything with linear algebra involved", so I would say in that case you should teach languages that are practical for linear algebra. I threw Matlab under the bus because it's generally slow (although there are ways to optimize it a bit more) and expensive, but I would teach matlab or julia before apl or bqn. Also bqn is a very new language, it's not ready to be used for classroom teaching purposes.
replyI must’ve meant best* instead of kind oop
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