Did #julialang end up kinda stalling or at least plateau-ing lower than hoped?

I know it’s got its community and dedicated users and has continued development.

But without being in that space, and speculating now at a distance, it seems it might be an interesting case study in a tech/lang that just didn’t have landing spot it could arrive at in time as the tech-world & “data science” reshuffled while julia tried to grow … ?

Can a language ever solve a “two language” problem?

@programming

  • tschenkel@mathstodon.xyz
    4·
    4 months ago

    @maegul @astrojuanlu @programming

    You put your finger right on it. If I tell people that they can replace Matlab or Python with Julia, then there is often not the pressure justifying learning another language.

    But when I show them, that (a) the fundamental syntax is nearly the same as Matlab or (b) that the same thing in Python is much more clunky (Numpy and Scipy are not exactly elegant in my eyes), and they can get 40 and 600 times speedup respectively, then there is much more interest.

    I needed the performance and DifferentialEquations.jl gave it, and my students stay for the easier language. But then they don’t have a long time with Matlab or Python under their belts, so the perceived pain of learning a new language to the same level is less, of course.

    At the moment we still teach Matlab mostly, because that’s what employers expect, but some of my students choose Julia in addition to it. And they do like it.

    More and more universities move their scientific “computational thinking” type of classes to Julia (from either Matlab or Python), which may move the trend when their will be more STEM graduates knowing the language.