JSON to Pydantic
Generate Python Pydantic v2 models from JSON. Creates type-safe Python data models with automatic field type inference.
# Pydantic models will appear here...Frequently Asked Questions
What is Pydantic and why should I use it?
Pydantic is Python's most popular data validation library, used by FastAPI, LangChain, and thousands of production applications. It validates data using Python type hints, generates JSON Schema automatically, and provides excellent error messages when validation fails.
Does the converter generate Pydantic v1 or v2?
The converter generates Pydantic v2 (BaseModel) code, which is the current stable version. Pydantic v2 is significantly faster than v1 and uses a Rust-based validation core.
How are field names converted?
JSON camelCase keys are automatically converted to Python snake_case field names following PEP 8 conventions. For example, 'firstName' becomes 'first_name'. The original JSON key is preserved using Field(alias=...) if needed.
What Python types are inferred?
Strings map to str, numbers to int or float (based on the actual value), booleans to bool, null to None with Optional typing. ISO datetime strings are detected and typed as datetime. Nested objects generate separate BaseModel classes.
Can I use the generated models with FastAPI?
Yes. The generated Pydantic models work directly with FastAPI for request/response validation, with automatic OpenAPI documentation generation and JSON Schema support.
How are nested objects and arrays handled?
Nested objects generate separate BaseModel classes. Arrays are typed as list[Type]. Arrays of objects generate a model for the object type and use list[ModelName] as the field type.