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Comment by freedomben | Hacker News Reader

What is deficient about Julia? I've been heavily tempted to try it out but if there are problems I may invest my previous time elsewhere.

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For what it's worth, I think learning Julia would be a fantastic investment. I think it made me a much better programmer because it substantially lowers the barrier between 'developers' and 'users'.

I also don't think I could ever go back to using a langue that doesn't have multiple dispatch, and I don't think any language out there has a comparable out-of-the-box REPL experience.

Common Lisp.

Julia is really nice the only problems are 1) its focus is it being used from the REPL. While you can use a .jl script from the cli it feels wrong because of 2) its lack of a good AOT compilation/runtime/static binary option. Its JIT compiler is really good but you pay a price on startup and first runs hence Julians usually just have long running REPLs they don't close. 3) the ecosystem is still immature there are some amazing parts but also a lot of empty or poor parts still.

Community and libraries.

If I'm a person who wants to do some data science or whatever and I have very little software background I want there to be libraries that do basically everything I ever want to do and those libraries need to be very easy to support. I want to be able to Google every single error message I ever see, no matter how trivial or language specific, and find a reasonable explanation. I also want the environment to work more or less out of the box (admittedly, python has botched this one since so many machines now have a python2 and a python3 install).

Julia punches well above it's weight in libraries, especially for datascience and has the best online community I've ever been a part of. Googling an error in julia definitely won't give you nearly as many StackOverflow hits, but the community Discourse, Slack and Zulip channels are amazingly responsive and helpful.

I think a big advantage of Julia is that it has a unusually high ratio of domain experts to newbies, and those domain experts are very helpful caring people. It's quite easy to get tailored, detailed personalized help from someone.

This advantage will probably fade as the community grows, but at least for now, it's fantastic.

Eh wrote it for a couple years my tldr; multiple dispatch is odd, types are too shallow, jit is really slow to boot, the tooling is poor.

I've a lot more experience with Julia than any other language (and am a huge fan/am heavily invested). My #2 is R, which has a much more basic type system than Julia.

So -- as I don't have experience with languages with much richer type systems like Rust or Haskell -- it's hard to imagine what's missing, or conceive of tools other than a hammer. Mind elaborating (or pointing me to a post or article explaining the point)?

I found multiple dispatch to be odd at first, but after adapting my mindset a bit I really like it. It makes it really easy to just drop your functions specialized for your types into existing libraries, for example. It's a win for code reuse.

What do you mean by "types are too shallow"?

Yes, jit can be slow to boot, but I think this is an area they're going to be focusing on.

"the tooling is poor" Not sure I agree here. I think it's great that I can easily see various stages from LLVM IR to x86 asm of a function if I want to.

What version did you last use?

Boot times still aren't ideal, but I find it takes about .1 seconds to launch a julia repl now. First time to plot is still a bit painful due to JIT overhead, but that's coming down very aggressively (there will be a big improvement in 1.5, the next release with differential compilation levels for different modules), and we now have PackageCompiler.jl for bundling packages into your Sysimage so they don't need to be recompiled every time to you reboot julia.

I also think the tooling is quite strong, we have ana amazingly powerful type system and I would classify discovering multiple dispatch as a religious experience.

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