For compute-heavy code "100x slower than C++" is a good rule of thumb in my experience in python 3.10.
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.
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.