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.
mulderc 48 minutes ago [-]
Same, Julia really does just feel right to me. Which makes sense since I mostly program in R.
shevy-java 40 minutes ago [-]
To me it seems as if scripting languages have it hard right now, aside from Python.
AI seems to have changed how people find and use new languages. The influx of new people kind of ... died down for many older languages here.
throwaway894345 20 minutes ago [-]
Even before AI the trend was moving toward increasingly static languages (JS->TS and even a lot more typed Python). Once you accept the static typing benefits, you start to wonder if you could leverage the constraints to drive performance improvements.
rtpg 7 minutes ago [-]
> Faster GC by skipping image objects during marking
This one in particular I feel like we are inching towards in Python land. I had some really interesting convos from people who really want forking to "just work" and get actual memory savings, because a lot of code is really going to be in memory forever and if we can opt out of refcount work that'd be great
eigenspace 3 days ago [-]
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.
pjmlp 3 hours ago [-]
In Java, C# and C++ land, there are equally features that take several years to finally land.
I think it is perfectly fine that Julia folks take their time as well.
MarkusQ 2 hours ago [-]
I really like Julia, but I wind up not using it as much as I might otherwise because the startup time kills it for many use cases (though of course it's easily amortized in others).
postflopclarity 2 hours ago [-]
I think there's a very bright future in this regard :)
1.13 is, to-date, the release with the fastest startup times. and AOT compilation continues to be a serious priority for upcoming releases
AI seems to have changed how people find and use new languages. The influx of new people kind of ... died down for many older languages here.
This one in particular I feel like we are inching towards in Python land. I had some really interesting convos from people who really want forking to "just work" and get actual memory savings, because a lot of code is really going to be in memory forever and if we can opt out of refcount work that'd be great
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.
I think it is perfectly fine that Julia folks take their time as well.
1.13 is, to-date, the release with the fastest startup times. and AOT compilation continues to be a serious priority for upcoming releases