As package developers we need to optimize our packages for 1.9. It's quite a task but I am excited what's ahead in Julia. Matlab(is not open-source, R is slow and not really a general purpose language, Python is great but same issue 2-lang problem...why should I implement CUDA in C++ or Numpy in C. I want to be able to modify lower back-end code but with Python it's not possible. Julia fixes all of these problems and I am quite happy I invested my time in Julia. Present/Future is bright :)
I don’t understand how this wasn’t already implemented, it seems like such low hanging fruit
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Over the years I’ve kept coming back to Julia, like what I see, but ultimately end up with a deadline that has me reaching for R or Python. My latest foray has convinced me that the ecosystem is ready for me to double down and make it my language of first recourse for data science related tasks this year.
Precompilation sounds like it improves further on an annoyance (time-to-first-plot problem) that was already no longer much of an annoyance in Julia 1.8x.