Maybe when you are reinventing the wheel instead of using e.g. numpy, Jax, PyTorch. Python is an ecosystem some of which is tooling built in C/C++. There’s no reason to ignore those libraries just because C devs like to roll their own everything.

There's an Amdahl-like effect, where "100x slower" means that anything nontrivial in pure python ends up being fat in your flamegraphs, even if your "heavy lifting" core algorithmic stuff uses some nice fast libraries.