I really want to like Julia. It has a nice type system, a good ecosystem, reasonable syntax, and it’s far faster than Python. But there are several issues with its DX that prevent me from using it: the most severe of which being the complete lack of a cache for the JIT (or JIT like system), inducing multi second compile times for scripts that run in <100ms. There are some external packages that try to solve this issue, but they are far from first-party quality, and, in my experience, are quite buggy.
(I last tried Julia a few years ago; perhaps this has been improved since?)
adgjlsfhk1 40 minutes ago [-]
a between session cache had been merged for 1.14 (release expected within 6-12 months).
bandrami 21 minutes ago [-]
[dead]
24 minutes ago [-]
muragekibicho 35 minutes ago [-]
Julia uses 1-based indexing. It's competes with R and Matlab for the same set of users. Both R and Julia have their core functions written in C++. Absolutely nothing new.
From my experience, grad students use Julia when their PI thinks a new programming language will help differentiate their next NSF proposal among vast funding requests.
adgjlsfhk1 19 minutes ago [-]
> Both R and Julia have their core functions written in C++. Absolutely nothing new.
imo this isn't really a good summary. Julia is one of the 3 languages to have done an exascale HPC run https://arxiv.org/pdf/2309.10292v1 (Fortran and C are the other 2). Some parts of the compiler are written in c++ (the llvm interface), but doing codegen with llvm is much more similar to C/Rust/Fortran than R/Matlab
Alien1Being 33 minutes ago [-]
Thought that it would be about Lisp....
manwe150 21 minutes ago [-]
It was about lisp ;)
Secret mode: ./julia —-lisp
xuchenyi 13 minutes ago [-]
[flagged]
Rendered at 04:09:55 GMT+0000 (Coordinated Universal Time) with Vercel.
(I last tried Julia a few years ago; perhaps this has been improved since?)
From my experience, grad students use Julia when their PI thinks a new programming language will help differentiate their next NSF proposal among vast funding requests.
imo this isn't really a good summary. Julia is one of the 3 languages to have done an exascale HPC run https://arxiv.org/pdf/2309.10292v1 (Fortran and C are the other 2). Some parts of the compiler are written in c++ (the llvm interface), but doing codegen with llvm is much more similar to C/Rust/Fortran than R/Matlab
Secret mode: ./julia —-lisp