>Sadly Julia is pain too if you don't do REPL/notebook (which you shouldn't)
Can you be more precise on this? In my case, I do a lot work around visual outputs (such as images). So notebook based development (such as Pluto.jl) feels perfectly fine.
Can you be more precise on this? In my case, I do a lot work around visual outputs (such as images). So notebook based development (such as Pluto.jl) feels perfectly fine.
Usage where you don't keep the Julia process running. E.g. "$ julia stuff.jl" form a shell.
Do standalone binaries here include shared libraries (with a C ABI)? That would be a dream.
Unfortunately, the core devs are not too chatty about standalone binaries, because of how Julia's internals are set there are going to be a lot of unforeseen challenges, so they are not trying to promise how things will be rather let's wait and see how things will turnout. Since packagecompiler.jl already has C ABI and one goal discussed about binaries being easily callable from other languages and vice versa, I would bet that it will have shared libraries.
The discussion seems to be too deep in Julia internals for me to follow. Is this about startup time or defining an entry point (or both?). I haven't had problems with Julia entrypoints (yet at least).
With the nightly `./julia-f7618602d4/bin/julia -e "using DynamicalSystems"` still takes over 5 seconds. Can I somehow define a main to make this faster or precompile more efficiently?
> Since packagecompiler.jl already has C ABI and one goal discussed about binaries being easily callable from other languages and vice versa, I would bet that it will have shared libraries.
Sounds promising. Shared libraries are not a musthave for me, but could allow Julia save us from C++ in more cases.
DynamicalSystems looks like a heavy project. I don't think you can do much more on your own. There have been recent features in 1.10 that lets you just use the portion you need (just a weak dependency), and there is precompiletools.jl but these are on your side.
You can also look into https://github.com/dmolina/DaemonMode.jl for running a Julia process in the background and do your stuff in the shell without startup time until the standalone binaries are there.
Compiler latency ("time to first plot") used to be miserable but after a few releases with incremental improvements it feels mostly solved to me.
Just now on Friday at JuliaCon Local in Eindhoven one of the keynotes was about similar ongoing work on stand-alone binaries (including shared libraries to call like C/Fortran.)
https://julialang.github.io/PackageCompiler.jl/stable/libs.h...