Re:Cthulhu.jl – show type-inferred Julia code
by npalli on Friday September 08, 2023 @02:08AM
(#37430012)
Using Julia as non-numerics/non-scientific systems language is not a good fit. So, not surprising you are not finding it as useful as Rust. JIT performance notwithstanding. As for Python, it is getting defaulted to any and every programming niche with predictably bad results.
Re:Cthulhu.jl – show type-inferred Julia code
by cmrdporcupine on Friday September 08, 2023 @06:43AM
(#37431951)
The problem is that the language is in part pitched this way, as a "best of both worlds" language where you can get "C-like" performance while still living in a dynamic world, at least in part. But it's not true.
It's certainly faster than Python, and a more elegant language. So I'd be in a much happier world if people were using it for some of the places where they're using Python. But its slow startup time makes it unsuitable for many scripting type tasks. And its module system and deployment thereof is... complicated.
And yes, like any late-bound language, it's going to be prone to crashing at runtime in unexpected ways. Julia has some okayish tools for doing some static analysis, but it's never going to be at the level of what you can get out of an actual modern static type system. I was fortune to work with some very smart people who had written some very high quality code in Julia, and some aspects of the language I found very nice and expressive (and even sometimes miss), but I was happy to go back to writing Rust after I switched jobs.
And yeah, not being a VSCode user (JetBrains addict), I found tooling lacking as well. The emacs mode was okayish. Also found I kept having to use the Repl in ways I found non-intuitive.