> The ecosystem is still pretty barebones compared to Python
There's help: https://github.com/JuliaPy/PyCall.jl https://github.com/JuliaInterop/RCall.jl
Works like a charm.
There's help: https://github.com/JuliaPy/PyCall.jl https://github.com/JuliaInterop/RCall.jl
Works like a charm.
Additionally, I think you also have to think about things like Documentation and Tooling.
A lot of the "scientific" Python packages (NumPy, SciPy, etc.) actually just call out to C libraries for the majority of their computation. I imagine Julia can do that already, or it can call out to something similar in the stdlib, so it doesn't really need integration with these Python packages other than just API familiarity. But is that worth the cost in performance?
Julia at this point covers everything in NumPy, SciPy and much more. For optimization, bayesian stuff, scientific, and the convergence of the above with ML, it's far ahead- https://sciml.ai/
Even has relatively mature web frameworks (https://github.com/GenieFramework/Genie.jl)
I'm very certain that you can just import the underlying packages directly but this way is easiest, especially since I'm not familiar with R.