The error messages you mentioned in here have been completely overhauled. In fact, most things in SciML are now caught and throw very high level error messages. We also revamped the whole documentation and added docstrings everywhere. See https://sciml.ai/news/2022/10/08/error_messages/ . We're also in the middle of rolling out a new documentation (https://docs.sciml.ai/Overview/stable/) that has a lot more of a split between tutorials and references. It's not complete, but the core push of this should be completed in about 2 weeks. As for loading times, we've transformed those as documented in https://sciml.ai/news/2022/09/21/compile_time/ (taking a core case from 30 seconds to 0.1 seconds), and Julia v1.9 is releasing a feature where package precompilation can store LLVM-compiled binaries.
So I think most of the blog post has already been addressed?
The one thing we haven't done is improved type printing. I am with you on that one, and actually opened a Base Julia issue about it way before your blog post: https://github.com/JuliaLang/julia/issues/36517 . It requires a Base Julia fix though, so that's a bit out of my hands. Also, I think it would be good for Base Julia to do a bit of the error message interpreting that SciML has done, specifically for broadcast (https://github.com/JuliaLang/julia/issues/45086). So there are some more improvements to be done, but I don't think the blog post is up-to-date given the overhauls that were done in the summer of 2022 (thanks to your feedback).
It would be nice to hear updated thoughts when you have a chance to try all of these improvements (especially when v1.9 comes out with the cached binaries)!
> It would be nice to hear updated thoughts when you have a chance to try all of these improvements (especially when v1.9 comes out with the cached binaries)!
I finished my Master in physics. Now, I'm working in IT, and even tough physics will always have a special place in my heart, I probably will not return to physics.
If I will find myself doing Numerics, I might give Julia a second try, but I don't think I will find myself doing numerics anytime soon.
Maybe if I buy a SDR and have some fun with it, I might use Julia.
So I think most of the blog post has already been addressed?
The one thing we haven't done is improved type printing. I am with you on that one, and actually opened a Base Julia issue about it way before your blog post: https://github.com/JuliaLang/julia/issues/36517 . It requires a Base Julia fix though, so that's a bit out of my hands. Also, I think it would be good for Base Julia to do a bit of the error message interpreting that SciML has done, specifically for broadcast (https://github.com/JuliaLang/julia/issues/45086). So there are some more improvements to be done, but I don't think the blog post is up-to-date given the overhauls that were done in the summer of 2022 (thanks to your feedback).
It would be nice to hear updated thoughts when you have a chance to try all of these improvements (especially when v1.9 comes out with the cached binaries)!