JSON to Pydantic model

How to use it

1. Enter json input and root type name.
2. The result appears straight away and updates as you edit.
3. Copy the result, or copy a link that keeps the same values to share it.

How it is calculated

str, int, float, bool, List[T] and Any, with a BaseModel per nested object. Field names are snake_case, and when one differs from the JSON key it gets Field(alias="key"). null makes the type a required Optional[T], and a key missing from some items defaults to None.

Example

Inputs: Root type name = Root. Result: Generated code: from typing import List, Optional from pydantic import BaseModel class Order(BaseModel): order_id: str total: float coupon: Optional[str] class Address(BaseModel): city: str postal_code: str class Root(BaseModel): id: int name: str email: str is_active: bool balance: float tags: List[str] address: Address orders: List[Order]; Types generated: 3; Fields: 13.

{
  "id": 1024,
  "name": "Sara Ahmed",
  "email": "sara@example.com",
  "is_active": true,
  "balance": 1520.75,
  "tags": ["vip", "riyadh"],
  "address": { "city": "Riyadh", "postal_code": "12211" },
  "orders": [
    { "order_id": "A-1", "total": 99.5, "coupon": "EID10" },
    { "order_id": "A-2", "total": 120, "coupon": null }
  ]
}

from typing import List, Optional

from pydantic import BaseModel


class Order(BaseModel):
    order_id: str
    total: float
    coupon: Optional[str]


class Address(BaseModel):
    city: str
    postal_code: str


class Root(BaseModel):
    id: int
    name: str
    email: str
    is_active: bool
    balance: float
    tags: List[str]
    address: Address
    orders: List[Order]

Limits and caveats

• The code targets Pydantic version 2.
• With an alias you pass data using the original JSON keys; to use the field names too, enable populate_by_name in model_config.