JSON to Pydantic — FastAPI Model Generator

JSON to Pydantic — Generate FastAPI Models from Sample JSON

Paste a real API response and get production-ready Pydantic v2 models with type hints, optional fields, and nested class definitions. Ideal when bootstrapping FastAPI endpoints, writing typed SDK clients, or converting legacy JSON configs into validated Python objects — without hand-writing every field.

Input → Output Example

Given this JSON order payload:

{
  "order_id": "ORD-1042",
  "customer": { "name": "Alice", "tier": "premium" },
  "items": [{ "sku": "A100", "qty": 2, "price": 9.99 }],
  "shipped": null
}

The generator produces nested models with correct optional typing:

class Customer(BaseModel):
    name: str
    tier: str

class Item(BaseModel):
    sku: str
    qty: int
    price: float

class GeneratedModel(BaseModel):
    order_id: str
    customer: Customer
    items: list[Item]
    shipped: Optional[str] = None

Working with Nested API Responses

Real-world payloads often mix arrays, nullable fields, and nested objects — webhook events, CRM exports, or OpenAI structured outputs. Paste the full JSON (not a truncated snippet) so the generator can infer list types, optional fields, and inner models. For Zod or JSON Schema equivalents, use our JSON to Zod or JSON Schema Generator tools on the same sample data to keep your Python, TypeScript, and API docs aligned.

Why Pydantic?

Pydantic is the most widely used data validation library for Python. It provides runtime type checking, data parsing, and serialization — all with standard Python type hints.

Common Use Cases

• FastAPI — Request/response models with automatic validation
• Config Management — Environment variables and settings
• Data Pipelines — ETL job data structures
• API Clients — Typed SDKs for external APIs

JSON to Pydantic FAQ