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Discussion Sentiment

80% Positive

Analyzed from 225 words in the discussion.

Trending Topics

#julia#lisp#written#system#far#cache#jit#run#experience#matlab

Discussion (7 Comments)Read Original on HackerNews

ashton314•3 minutes ago
[delayed]
maxall4•about 1 hour ago
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•about 1 hour ago
a between session cache had been merged for 1.14 (release expected within 6-12 months).
JanisErdmanis•3 minutes ago
What is this magic, how does it differ from PkgImages Julia already has?
Alien1Being•about 1 hour ago
Thought that it would be about Lisp....
manwe150•44 minutes ago
It was about lisp ;)

Secret mode: ./julia —-lisp

muragekibicho•about 1 hour 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•41 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