[nerdponx]

You are mixing up "how things are implemented" with "stuff that data scientists interact with."

Arrow is a low-level implementation detail, like BLAS. "Using" Arrow in data science in Python would mean implementing an Arrow-backed Pandas (or Pandas-like) DataFrame.

Your rank-and-file data scientist doesn't even know that Arrow exists, let alone that you can theoretically implement arrays, matrices, and data frames backed by it.

If you want to break the hegemony of Numpy, you will have to reimplement Numpy using CFFI instead of the CPython C API. There is no other way, unless you get everyone to switch to Julia.