The Python typing specification has evolved from PEP 484's initial implementation to a formal standard with a conformance test suite. Early type checkers like mypy defined the de facto rules, but as tools like Pyright, Pytype, and Pyre emerged, inconsistencies grew. The typing community consolidated rules into a single specification to address this fragmentation.

A conformance test suite now contains roughly a hundred test files covering generics, overloads, and type aliases. Each test marks expected errors, allowing type checkers to be measured for false positives (incorrectly flagging valid code) and false negatives (missing expected errors). For example, TypedDict with extra_items=bool should accept additional boolean keys but reject non-boolean values.

Current results show Pyright leading at 97.8% pass rate, while mypy only achieves 57.3% despite being the industry standard. Pyrefly already supports all major type system features and expects to close remaining gaps. Conformance matters because non-conformant checkers force developers to restructure code or add workarounds when using advanced typing features or third-party libraries.