> AI/ML

The Machine-Learning world, especially "Google Brain" research team figured out that NumPy was an awesome piece of software for dealing with large arrays of numbers and matrix multiplication. They built "TensorFlow" on top of it around 2015 which became very popular. Facebook followed suit and released PyTorch in 2016.

IPython/Jupiter notebooks (for Julia, Python and R) from 2015 were another factor, also adopted by the AI/ML community.

The alternative data-science languages at the time were Mathematica, MATLAB, SAS, Fortran, Julia, R, etc, but Python probably won because it was general purpose and open source.

I suspect Python would not have survived the 2/3 split very well if it wasn't for AI/ML adopting Python as its main language.

> when the tooling was so inferior

Since 2012, Conda/Anaconda has been the go-to installer in the SciPy/NumPy world which also solves a lot of problems that uv solves.