• itadakimasu@programming.dev
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    1 year ago

    No issue setting up Nim itself (and I realize my complaint is not fault to Nim itself) but it would be great if this complimentary jupyter kernel for Nim would work on MacOS… Hasn’t been maintained in a while: https://github.com/stisa/jupyternim/issues/38

    Would be very useful for my workflow as someone who wants to explore Nim for data science-y type tasks.

    Anyone know of an alternative Nim jupyter kernel?

    • sotolf@programming.dev
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      1 year ago

      I don’t think the jupyter kernel is made by the core developers of nim, it’s kind of weird to call the language pain in the ass because of one weird niche usecase being hard to set up :)

    • insomniac_lemon@kbin.social
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      1 year ago

      Not sure about MacOS plus it’s not REPL (sorry if that is key), but have you tried faster compilers for prototyping? Such as TCC (Bellard’s Tiny C Compiler) as long as performance isn’t critical and if you don’t need multi-threading.

      Clang is also pretty good (for a simple benchmark, the result I got was that Clang with opt:size gives similar performance to plain GCC but with half the compile time). (nlvm is also a thing but I have no idea how that’d compare even to Nim compiling code via Clang)

      With some setup, maybe some form of hot code reloading?

    • janAkali@lemmy.one
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      1 year ago

      Try inim.

      It’s not perfect, but closest thing to repl.
      I use it all the time for very small experiments.
      Installation should be as easy as:

      nimble install inim