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.<p>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.
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 :)