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| Feature | Pydantic Handles? | mypy Handles? | Example/Note |
|-------------------------------|-------------------|---------------|-------------------------------------------------------------------------------|
| Type coercion | Yes | No | `"123"` → `123` for int fields (Pydantic). mypy only checks declared types. |
| Nested models | Yes | Limited | Pydantic validates recursively. mypy ensures type annotations are consistent. |
| Complex types (List, Dict) | Yes | Yes | Both validate/ensure typing; Pydantic does runtime parsing. |
| Custom validation | Yes | No | Pydantic: `@validator`. mypy can’t enforce custom logic. |
| Error reporting | Yes | No | Pydantic gives structured runtime errors. mypy stops at type errors only. |
| Serialization | Yes | No | Pydantic: `.dict()`, `.json()`. mypy doesn’t handle serialization. |
| Environment variable parsing | Yes | No | Pydantic: `BaseSettings`. mypy has no runtime features. |
| Strict types | Yes | Limited | Pydantic: `StrictInt`, etc. mypy flags type mismatches statically. |
| Arbitrary types | Yes | Yes (Limited) | Pydantic: `arbitrary_types_allowed=True`. mypy can allow with `Any`. |
| Default values | Yes | Yes | Both support defaults via type hints + field definitions. |
| Optional / Union types | Yes | Yes | Both support `Optional`/`Union`, but Pydantic also parses/validates runtime. |
| Literal types | Yes | Yes | Both handle `Literal`, but Pydantic enforces at runtime. |
| Generics | Partial | Yes | Pydantic has limited support; mypy supports generic type parameters fully. |
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