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August 27, 2025 10:34
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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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