Julia 1.13 cuts startup time by 20% and precompilation by 30%
Julia 1.13 Highlights
Julia 1.13 brings major performance wins: roughly 30% faster precompilation and 20% faster startup than 1.12, plus a revamped REPL with syntax highlighting and fzf-style history search. The release also introduces the @__FUNCTION__ macro, a new RapidhashNano hashing algorithm, and a garbage collector that skips image objects during marking, making full collections up to 17x faster. Scheduler fixes restore reliable Ctrl-C interrupts.
The effect is that the cost of a full collection now scales with the size of the heap that your program actually created, not with the amount of code that has been loaded.
- zuluonezero
Over the last three years I have been doing a focussed investigation of a lot of different programming languages and styles (about 38 last count). I was reflecting over the weekend which one I really liked best. Not really for features or functionality or toolset just which one felt 'right'. Julia came out on top as the one language I wanted to play with more and I wish could give a reasoned well justified argument for it but it's really just a feeling. The right mix of intelligent design, power, absence of evangelical idiocy, and a pleasing interface. So nice to get that feeling validated from the random workings of the world and see this release message this morning. Thanks Julia team.
- eigenspace
Due to how the release cycle turned out, most new major features got pushed to v1.14, and this one is a rather iterative release focused on making various things faster, quashing bugs, and general polish.
Still though, faster GC, lower startup latency, better interrupt handling, new REPL features, and faster package mangement are all great things. I'm especially happy that the `[sources]` section of a package is now applied recursively when you `add` a non-registered package.
- notthemessiah
I love Julia, but I feel two annoyances right now with the ecosystem.
Interactive programming seems to be having a schism between Pluto, a reactive notebook like Observable, and Bonito, a more imperative notebook like Jupyter from the creator of plotting library Makie.
The other annoyance is that the packaging ecosystem is tied very closely to Github and Gitlab as the only alternative, in an era where Microsoft is killing Github reliability, and many new projects are moving to Tangled (on the AT Protocol network) and Forgejo (with Codeberg as the flagship), which has no packaging support from JuliaHub.
- vitorsr
All I ever wanted from Julia was great a development experience, but it appears to have never quite gotten there.
As a language it has gotten there a long while ago (1.6 LTS series comes to mind).
The landscape has changed substantially since then, and now "ergonomics" has unfortunately taken lower priority due to agent-driven development.
Nevertheless I think everyone should take a page from Go's book, really, language design now should include the default development workflow.
- jan_m_savage
Julia would have seen more adoption with:
--> proper learning resources for beginners, but also for intermediate and advanced users. As of now resources are relatively sparse, compared to what you would find in the Python world.
--> a dedicated IDE. Python has several.
Otherwise it's a great clean language, faster and more elegant than Python. It's a shame it got stuck in Python's shadow.