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.
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.
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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.
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MarkusQ
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).
> 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
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.
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.
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.
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).
Current discussion, https://news.ycombinator.com/item?id=49651384
> 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