I think you're regarding Mathematica from a purely "theory/analytics" point of view, however I think you're missing the fact for a lot of scientific computing y

I think you're regarding Mathematica from a purely "theory/analytics" point of view, however I think you're missing the fact for a lot of scientific computing you want to interact with other things apart from numerics/analytics etc.. I believe that is really where Python shines and why it's also eating Matlab's lunch (more so than Mathematica's). It's incredibly easy to write a gui to interface with e.g. a scientific instrument do some reasonably fast analytics with numpy and possibly even produce publication ready plots. This is not really possible with Mathematica and while you can do this in Matlab, you need several toolboxes which are expensive, but more over are of extremely varying quality (let's not even talk about the horror of writing GUIs in Matlab). With Python, you have all of that for free, with a single tool (remember most scientists don't want to learn lots of programming languages).