Hey folks! There was a pretty good critical article written about Julia recently called “Why I no longer recommend Julia” by Yuri Vishnevsky There is an ongoing discussion about the article that has largely been constructive on Slack. Hoping to capture some of these thoughts here to provide actio…

Well, but it is so much more fun to write Julia packages than Python packages, so this ratio is changing…

As it turns out julia is a Lisp after all, and so it suffers from it’s curse, that curse is also a blessing because I don’t know of another language where one can be so expressive and also write performant code at the same time. On python there is a massive barrier between users and developers whil…

I don’t think Julia is more dangerous than the early-stage JavaScript… JavaScript has its advantage, then people who wants better software call for TypeScript. Julia has its advantage, we might have something.

So is the picture that is emerging is that in Julia the SciML ecosystem will be the “equivalent” to Python’s Scipy? (i.e. the go to package for numerical computing, which includes most common problems) If so, I see two fields which are still missing: eigenproblem, ffts. Are there plans to add those…

Yes, here’s the unified documentation (which is still in-progress, so don’t post it as something that’s complete, we’ll do a release announcement when it is): https://docs.sciml.ai/dev/ Indeed you can see it’s meant to be the “go-to” for numerical computing. Indeed FFTs are missing, but that’s bec…

I added FFTW just directly to the docs since it’s just the repo. That shold make it more searchable. DataInterpolations too (not Interpolations.jl because of course that is rough to use). Eigenvalue problems will take a bit more to do properly.

I don’t have much to add to this excellent discussion. I just want to say that it is great that Yuri and others opened all those issues listed in the blog post. Issues are actionable, and at least give developers the opportunity to address them, even if it occasionally takes a long time because of u…

I think that having a “one-stop-shop” for most common tasks in numerical computing is really import in order to advance the adoption of Julia. Having a unified SciML ecosystem will greatly improve this! So thank you for your efforts @ChrisRackauckas ! I have been facing a problem when trying to con…

I agree 100%. I wrote something similar in this post , and we discussed the package ecosystem a bit over in that thread. To summarize: I think the solution is that we, as instructors using Julia, select a few packages for the purpose of teaching undergraduates and standardize on those for education. …

I agree, I think some standardisation in the teaching tools is very important. But I also think that is import to suggest packages that are not just good enough for education, but can also be used for research (just like numpy+scipy). Otherwise, we end up with a kind of “two packages problem”. That…

Discussion on "Why I no longer recommend Julia" by Yuri Vishnevsky

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Discussion on "Why I no longer recommend Julia" by Yuri Vishnevsky

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