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

[Bruno_Amorim]

@martin.d.maas

As for Julia vs Numba, you can check out my blog post . Not only there is a performance penalty in numba, you also lose a good deal of the high-level features available in Python. Finally, there is no numba-specific package system, so if you need somewhat efficient code you need to write it yourself. As a side note, I don’t think that Numba has been very actively developed for the last few years.

Thank you for sharing this post. It very clearly illustrates de limitations of Numba. However, by lloking at its github, it seems that numba is seeing active development

@martin.d.maas

I agree that there is some dispersion here, or lack of a clear winner package. In my case, I have started to consider “Plots.jl” as the standard, as it provides a common API for a good number of existing backends.

My problem with Plots.jl is that the promise of one interface to multiple backends is a bit unfulfilled. If you want more advanced options, you always have to deal with the fact that not all backends support the same features and you might have to use backend specific options via extra_kwargs. I would rather use one of the backends directly. For me that is PyPlot, but I might move to Makie in the future.