fastapi-validation

Validate API requests by defining Pydantic BaseModel classes with Field constraints and using them as FastAPI endpoint parameters. FastAPI automatically enforces type safety, generates OpenAPI schemas, and returns validation errors for malformed input across request bodies, query parameters, and path parameters.

Yes, Pydantic supports nested structures and lists through model composition. Define models containing other models or List types, and FastAPI validates the entire hierarchy automatically, including deeply nested objects and bulk operations.

Pydantic Field constraints enable min/max values, string patterns, length limits, and enum constraints. Custom validators add business logic validation. These constraints are enforced on request bodies, query parameters, and path parameters, with violations returned as structured validation errors.

Define Pydantic models for both requests and responses, then use them as FastAPI endpoint annotations. Pydantic enforces type checking on input and output, preventing type mismatches and generating accurate OpenAPI documentation for both directions.

Yes, Pydantic v2 custom validators enable complex rule implementation. Combine Field constraints, model_config settings, and validator functions to enforce business logic, cross-field dependencies, and conditional validation rules beyond basic type checking.

FastAPI returns structured validation error responses with field names, error types, and messages. Validation failures on request bodies, query parameters, or path parameters are caught automatically and returned as HTTP 422 Unprocessable Entity with detailed error metadata.