Python predates Julia by 3 decades. In many ways Julia is a response to Python's shortcomings. Julia could've never taken off "instead of" python but it clearly hopes to become the mature and more performant alternative eventually
> We want a language that's open source, with a liberal license. We want the speed of C with the dynamism of Ruby. We want a language that's homoiconic, with true macros like Lisp, but with obvious, familiar mathematical notation like Matlab. We want something as usable for general programming as Python, as easy for statistics as R, as natural for string processing as Perl, as powerful for linear algebra as Matlab, as good at gluing programs together as the shell. Something that is dirt simple to learn, yet keeps the most serious hackers happy. We want it interactive and we want it compiled. (Did we mention it should be as fast as C?). While we're being demanding, we want something that provides the distributed power of Hadoop — without the kilobytes of boilerplate Java and XML
> We are power Matlab users. Some of us are Lisp hackers. Some are Pythonistas, others Rubyists, still others Perl hackers. There are those of us who used Mathematica before we could grow facial hair. There are those who still can't grow facial hair. We've generated more R plots than any sane person should. C is our desert island programming language.
When I first heard about Julia I understood it to be a faster alternative to Python. As I started to learn it I realised that's really not what it's about, it's trying hard to compete simultaneously with Matlab and R and Fortran and C++ (and the template metaprogramming language hiding in C++) and APL and Lisp and maybe OCaml just as much as Python (but not Rust or Java or Agda), and I can't even speak to the other languages mentioned.
At the time we were part of the wave I suppose that was trying to convince people that open source Python was a better prospect than MATLAB which was where many people in physics/engineering were on interpreted languages. At least in my view, it wasn’t until much more recently that Julia became a workable alternative to those, regardless of the performance benefits (which were largely workable in Python and MATLAB anyway - and for us at least we were happy developing extension modules in C for the flexibility that the Python interface gave us over the top).
They still have to this day.