Hi HN,

I’ve been exploring whether pandas can be used as a computation description, rather than a runtime.

The idea is to write data logic in pandas / NumPy, then freeze that logic into a static compute graph and execute it in pure C++, without embedding Python.

This is not about reimplementing pandas or speeding up Python. It’s about situations where pandas-style logic is useful, but Python itself becomes a liability (latency, embedding, deployment).

The project is still small and experimental, but it already works for a restricted subset of pandas-like operations and runs deterministically in C++.

Repo: https://github.com/CVPaul/xpandas

I’d love feedback on whether this direction makes sense, and where people think it would break down.