"that statement is so fundamentally detached from reality that I don't even know how to start."
It is the statistical average for Android, but again it depends on the use-case situation. Apps are a saturated long-tail business that fragmented decades ago.
Python sits on top of layers of C++ wrappers for most ML libraries, and doesn't do the majority of the heavy computation in Python itself (that would be silly). Anyone dealing with the CUDA SDK for Pytorch installs can tell you how bad it is to setup due to versioning. That is why most projects simply give up to use a docker image to keep the poor design dependencies operational on a per project basis.
"then I think I'm wasting my time"
Than just let the community handle the hard part, and avoid having to figure it out yourself:
https://github.com/dambergn/ai-stack
I think you are confusing ML work with end users playing with other peoples algorithms.
Best of luck =3