Thread Rust vs Python performance benchmarks (CFFI + PyO3)

Benchmarking C-extensions in Python via CFFI and PyO3 for compute-heavy tasks — which approach offers better performance and maintainability? I've run several tests comparing pure Python, a C extension via CFFI with pre-compiled shared libraries, and a Rust module exposed through PyO3. For the tight loops and matrix operations that constitute our bottleneck, the Rust implementation consistently outperformed both approaches by 25x over pure Python and roughly 18% over CFFI. The key differentiator isn't raw execution speed but how each handles memory safety in unsafe code blocks — PyO3 uses a wrapper generation approach that prevents common ownership errors without manual reference counting overhead, while the CFFI solution required extensive boilerplate for error handling across the FFI boundary. Another factor is build system integration: Rust's cargo and pyo3-build handle dependencies more cleanly than