AI Python Class Generator

Use dataclasses for simple data containers without validation needs. Choose Pydantic BaseModel when you need runtime validation, serialization to JSON, and settings management — ideal for API request and response models. Use SQLAlchemy models for database-backed entities with ORM relationships. Our generator produces idiomatic code for whichever approach fits your use case.

Yes, all generated classes use modern Python type hints including Optional for nullable fields, Union for fields accepting multiple types, Literal for fixed-value fields, and generic types for collections. The type hints are compatible with mypy and pyright for static type checking, helping catch errors before runtime.

For Pydantic models, the generator adds field validators for email format, URL format, numeric ranges, string length limits, regex patterns, and custom business rules. For dataclasses, it adds __post_init__ validation. Each validator includes clear error messages that help API consumers understand what went wrong.

The Standard and Full feature levels include serialization support. Pydantic models get model_dump and model_dump_json methods configured with appropriate exclusions. Dataclasses get asdict and custom to_json methods. SQLAlchemy models get a to_dict method that handles relationship serialization and datetime formatting.

The Full feature level includes a factory method or companion factory class that creates instances with realistic default values for testing. This follows the factory pattern commonly used with pytest — each field gets a sensible default that can be overridden, making it easy to create test instances without specifying every field.