flext-strict-typing

To enforce strict Python type safety, apply rules that prevent Any and dict usage in annotations, mandate explicit return types for functions, and require modern type-hinting standards across the codebase.

Enforcing Pydantic v2 best practices involves ensuring models use ConfigDict and modern validator decorators, preventing unexpected data structures in API payloads and improving runtime safety.

Using Mapping instead of dict for Python type annotations enforces a mapping-first contract policy, promoting better interface design and improving code maintainability within your ecosystem.

To mandate modern Python typing syntax, apply strict typing rules that require features like X | None and list[X] for all type annotations, ensuring clarity and conciseness across your Python codebase.

Yes, strict typing prevents runtime errors in API payloads by ensuring all request and response structures are strictly typed, avoiding failures due to unexpected data structures.