INPUT - JSON
OUTPUT - Pydantic
Output will appear here
100% client-side
Output will appear here
Generate Python Pydantic v2 models from JSON instantly with our free JSON to Pydantic converter. The tool infers field types, creates nested BaseModel classes, and handles Optional and List annotations automatically. Ideal for FastAPI developers who need validated request and response schemas from sample API payloads.
Try Convert All - paste JSON once, see TypeScript, Go, YAML, and 15 more formats instantly.
Enter a JSON object in the left editor. Nested objects, arrays, and mixed-type fields are fully supported.
The output pane displays Python Pydantic v2 BaseModel classes with properly typed fields, including List, Optional, and nested model references.
Copy the models to your clipboard or download as a Python file. Drop them into your FastAPI, Django, or Flask project and start validating data immediately.
The converter targets Pydantic v2 by default, using the modern BaseModel API and Field() descriptors. The output is compatible with Pydantic 2.x and FastAPI 0.100+.
Each nested object generates its own BaseModel subclass. The parent model references it by class name, so Pydantic validates the entire tree recursively when you call model_validate().
Yes. The output models are standard Pydantic BaseModel classes that FastAPI accepts as request body types, query parameter models, and response models without modification.
They are treated as two different facts. A key that is missing from some objects in an array is optional, so it is emitted as Optional[type] = None. A key that is present but null is nullable, so it is emitted as Optional[type] with no default. A key that is null in every sample carries no type information at all and is emitted as Optional[Any] rather than being guessed.
Yes. camelCase and PascalCase JSON keys are converted to Python snake_case field names. A model_config with populate_by_name is included so the model still accepts the original JSON key names.