I think a really good example of how Julian tools are composable and work with the whole of the language, while that is not the case with Pythonic tools, is aut

I think a really good example of how Julian tools are composable and work with the whole of the language, while that is not the case with Pythonic tools, is autodifferentiation. The many different julian autodiff libraries have little trouble performing the autodiff through special functions, weird data structures, and 3rd party libraries. In python, none of the autodiff tools play nice with scipy or with mpmath or with sympy (or qutip, which is something I need). This is not about commercial competitors either - all of the libraries I mentioned are non-commercial. Julia provides the interoperability between such libraries, including custom datatypes, frequently with fast zero-cost abstractions.