> Use Python + Numba, Python + C, Swift, Cython, Go, Lua-Jit, Rust, D - surprise us! I'm familiar with Python scientific ecosystems and currently learning Juli

> Use Python + Numba, Python + C, Swift, Cython, Go, Lua-Jit, Rust, D - surprise us! I'm familiar with Python scientific ecosystems and currently learning Julia and Rust. As far as I see it, these languages likely do not compete well with Julia on all three categories --- "developer effort, performance and extensibility" for the problem you picked, because none of them was designed for native array arithmetic with broadcasting in the first place (except Numba maybe). The current dominance of Python in scientific computing is rather a beneficent coincidence, because most people were pretty fed up with C++ and legacy Fortran back then, and efforts to improve tools of the trade tended to converge on Python. Fast forward 18 years after Python was born, Julia came to light and it was designed to do numerical tasks fast and elegantly and to avoid some pitfalls of "scripting languages". Does the success of Julia in these tasks signify the incompetence of Python? I don't think so. It served well what it was designed for. And if you tell me Julia is the right track of the history, you'd have to wait for it to happen. (Don't get me wrong, I like the Julia language and use it for a side project. I just don't see bashing other languages to prove that Julia is the one language to rule them all would be fruitful.) On the other hand, I'd say you forget to count in Fortran 2008! For broadcasting with multithreading, Fortran + OpenMP works pretty well.