.pyi vs beartype vs typeguard: 43% Runtime Overhead

Why This Benchmark Exists

Python's type system splits into two worlds: static analysis (mypy, pyright reading .pyi stubs) and runtime validation (beartype, typeguard injecting checks into your running code). Most teams pick one without measuring the tradeoff. That's a mistake.

I ran the same codebase through all three approaches—type stubs alone, beartype's O(1) sampling, and typeguard's full validation—on a realistic data pipeline processing 100K records. The runtime overhead gap was 43% between the fastest and slowest. But speed isn't the only axis that matters.

Here's what actually breaks in production, and when you'd deliberately choose the slower tool.

Photo by Christina Morillo on Pexels

The Three Approaches Tested

Type stubs (.pyi files): Zero runtime cost. Mypy or pyright reads the stubs during CI, catches type errors before deployment. Your production code runs unmodified. The catch? If your types lie, you find out when users hit the exception.

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