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JuliaLang: The Ingredients for a Composable Programming Language

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Re: JuliaLang: The Ingredients for a Composable Programming Language

#2

Post by xvilka »

I hope Julia will be more popular in bioinformatics. Personally, I have a high hopes for BioJulia[1][2][3] and the amazing AI framework FluxML[4][5] + Turing.jl[6][7]. Apart from the speed, they offer some interesting concepts too - I recommend to check them out.

[1] https://biojulia.net/

[2] https://github.com/BioJulia

[3] https://github.com/BioJulia

[4] https://fluxml.ai/

[5] https://github.com/FluxML/

[6] https://turing.ml/dev/

[7] https://github.com/TuringLang

Re: JuliaLang: The Ingredients for a Composable Programming Language

#4

Post by newen »

classified wrote: post #3

Is it possible yet to compile ahead-of-time to a stand-alone binary executable?

Look under Static Julia Compiler here [1]. I've successfully done it in Linux, don't know about Windows. It doesn't work when you have binary dependencies like GTK, etc.

[1] https://github.com/JuliaLang/PackageCompiler.jl

Re: JuliaLang: The Ingredients for a Composable Programming Language

#5

Post by cultus »

classified wrote: post #3

Is it possible yet to compile ahead-of-time to a stand-alone binary executable?

Yes, with PackageCompiler.jl. There are some restrictions IIRC since it is a dynamically typed language.

https://github.com/JuliaLang/PackageCompiler.jl

Re: JuliaLang: The Ingredients for a Composable Programming Language

#8

Post by cmcaine »

classified wrote: post #3

Is it possible yet to compile ahead-of-time to a stand-alone binary executable?

The other replies are slightly out of date and imprecise.

PackageCompilerX replaced PackageCompiler (and there's a PR open that will pull all the X work in soon).

The binaries produced bundle the whole Julia sysimage by default and they're quite big, but they are quite fast!

A more traditional static compilation approach is being tried with StaticCompiler.jl by tshort, but it's in early development.

Re: JuliaLang: The Ingredients for a Composable Programming Language

#9

Post by fishmaster »

I've been using Julia along with python and Pytorch, not yet for machine learning until flux is more mature but for NLP scripts, and I have to say that I'm starting to like it. Multiple dispatch, linear algebra and numpy built in, dynamic language but with optional types, user defined types, etc.

Re: JuliaLang: The Ingredients for a Composable Programming Language

#10

Post by smabie »

Julia is great. It’s significantly simpler than Python while also being much more expressive. It’s too bad the typing is only for dispatch, but hopefully someone will write a typechecker someday. I’ve found it surprisingly refreshing to not have to think about classes and just add functions on objects wherever I want. Some languages solve this with monkey patching (which is bad), others like Scala with an extension class (reasonable, but you still don’t get access to private properties), but the Julia approach is cleaner.

I wouldn’t use Julia for a non-scientific computing app as I don’t think it’s suitable, but for anything data science related, it’s great! And with the Python interop, I don’t really think there’s any reason not to use Julia for your next data science project. I suspect that over the next 5 years Python will no longer be used for these applications at all.

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