I am very surprised at any statement to not use Windows… that would be very unsubstantiated.
I am the lead developer of SciML and I almost exclusively use Windows. I have been doing that since I started in Julia in 2016 and that’s why you see the whole ecosystem works with Windows. I am a contributor to everything from Julia LinearAlgebra to Plots.jl and MATLAB.jl because for many years I was “the Windows guy” that made sure the open source ecosystem played nicely with Windows.
Now that we have a lot more industrial applications and commercial usage of Julia for engineering, Windows isn’t even uncommon and I haven’t been the only person looking out for Windows in the package ecosystem for a long time (since about 2020 or so many others have been helping out in this respect). And with the Yggdrasil artifacts system most of the Windows issues of pre-v1.0 Julia were largely eliminated.
So with what you’re saying
No, you don’t need to go to Linux. In fact, much of what you’ve described there was built and tested on Windows first, especially if you’re doing DiffEq + VS Code! And I develop all of SciML directly in Windows, no WSL. I would much rather run into every possible issue and fix it directly than use WSL, though I don’t think I can list a single Windows-specific issue that I’ve had to fix since… 2021?
At this point in time, I do not know of any Windows-specific issues related to SciML or its greater ecosystem other than the aforementioned Julia base issue with multithreaded image building. Also, the Windows file system is just naturally slower, but that’s just known. If you run into any issues with Windows just open an issue.
[Caveat: I did get a Mac laptop sometime last year, but I still mostly code on my desktop so… this at least means that I don’t use a Linux machine except with SSH. But this also means that SciML has similar Mac M-series support, which is why it uses AppleAccelerate linear algebra out of the box and will out benchmark other things which don’t. But I digress]