Half or more of the scientific research community live and breathe Python. Granted, it's Python 3.12, as 3.13 broke most of the C API, and everything COBOL and Fortran just about ground to a halt. But new projects are spun up constantly.
I guess these kinds of priorities are exactly why Python is not my favorite programming language and why you have tens of Python versions installed on any machine. Not to talk about the Python 2 -> 3 drama that was also about fetishising syntax and pureness over pragmatism, installed base, and respect for existing code.
Thanks, what madness. CPython wasn't abandoned in favor of PyPy at the 2 to 3 transition precisely because they wanted to keep the C extensions working. So what do they do next? Break the C extensions. Genius!
I forget who said it, but Python isn't the best at anything but it's decent to good at nearly everything, and that's why it's become so popular.
I do a lot of what I need symbolically in SymPy for dynamics analysis. Past that, I can't speak for it. At University I used Mathematica, but I just don't need all it can do at this point, so once again Python has proven to be "good enough." Matlab will be a similar story (e.g., I've never seen a good alternative to Simulink in Python).
But for everything else outside very specific domain tasks? Mathematica and Matlab are terrible for a lot of reasons. So I'll go out of my way to stay within the Python ecosystem, though I'm not afraid to pull out the specialty tools when I just can't make Python do the task near as well and/or nearly as quickly.
