Assume mainstream adoption as used by around 7% of all github projects

Personally, I’d like to see Nim get that growth.

  • @tatterdemalion@programming.dev
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    1 year ago

    If we’re saying 7% is the bar for mainstream, then Rust is my vote.

    C# is not even mainstream by that standard.

    I’d also like to see Julia used more.

    • @Hawk@lemmynsfw.com
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      41 year ago

      I personally find multiple dispatch far more challenging to use than OOP. I’d reach for Torch over Flux any day.

      Although, I really like that the majority of the Flux stack is Julia rather than a collection of Cpp.

      • What do you find challenging about multiple dispatch? I don’t use Julia for my job, so I can’t say I’ve had enough experience to have a strong opinion. MD seems like a valuable tool though.

        • @Hawk@lemmynsfw.com
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          21 year ago

          Simply, the lsp is far less useful. An object might have a dozen methods that act like verbs or some attributes that act as adjectives.

          In Julia there is a huge number of functions, that work differently for different types and different combinations of types. So finding the documentation involves finding the right name for a function that does different things for different types, then scrolling down the docs for the the behaviour that corresponds to the specific combination of inputs.

          I moved from R/Py to Julia for a while before moving back to Py (and a little bit of Rust).

          I love how fast Julia is and the 1-index is fine for me, but I still prefer py for the oop.

          • So there’s no LSP function to just show all of the multi-methods that accept a specific type? That’s a pretty serious tooling limitation.

            Maybe Julia sounds better in theory than in practice, if the tooling still isn’t ready for production use.

            • @Hawk@lemmynsfw.com
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              21 year ago

              Well it’s there, in one loooong print out. It’s not as bad as I’m making it out to be, however, I went back to python unfortunately.

              The crucial issue with Julia, no error messages.

              So I use Julia for things that need to be fast (e.g. moving hdf5 to SQL and ffts) but I use python for everything else (except ggplot).