The interoperability of Julia and Python is really good (Julia calling Python and vice-versa). There is also the possibility to call R functions (but I do not u

The interoperability of Julia and Python is really good (Julia calling Python and vice-versa). There is also the possibility to call R functions (but I do not use it personally). To some degree, one can leverage python's ecosystem in Julia. Our group switched from matlab to Julia are we are quite happy with the move. For teaching, I think that Julia indexing (for example: vector[2:end-1]) is easier to explain than numpy (vector[1:-1]). On the other hand, I like python's plain English operators and/or versus && / || in Julia. Also loops tends to be more readable than vertorised code in some circumstances (e.g. computing the Laplacian by finite difference). In Julia, loop and vectorized code are both quite efficient, while in python and R, one has to vectorize the code.