JSON to Pydantic Model

JSON → Pydantic v2 BaseModel classes. Nested models are declared before the model that uses them, so the file imports without forward references.

JSON{
  "id": 42,
  "email": "ada@example.com",
  "is_active": true,
  "balance": 120.5,
  "profile": {
    "display_name": "Ada Lovelace",
    "bio": null
  },
  "tags": ["math", "compiler"],
  "orders": [
    { "order_id": "A-1001", "total": 89.9 }
  ]
}

Pythonfrom typing import Optional
from pydantic import BaseModel


class Profile(BaseModel):
    display_name: str
    bio: Optional[str] = None


class Order(BaseModel):
    order_id: str
    total: float


class Root(BaseModel):
    id: int
    email: str
    is_active: bool
    balance: float
    profile: Profile
    tags: list[str]
    orders: list[Order]

# Validate with: Root.model_validate(data)

JSON to Pydantic Model — Free Online Tool

Generates Pydantic v2 BaseModel classes from a JSON sample, mapping types to int, float, bool, str, list and nested models, adding Field(alias=...) with populate_by_name when a key is not a valid Python identifier or is not snake_case, using Optional with a None default for nulls, and emitting classes in dependency order so the file imports cleanly.

How to use the JSON to Pydantic Model

Open the tool above — it runs entirely in your browser, so your input never leaves this page.
Paste or type your input into the field, then press the relevant button (e.g. Encode / Decode, Generate, or Convert).
Copy the result from the output area with the copy button orCtrl/Cmd + C.
No signup, no upload, and no tracking — repeat as often as you need.

Frequently asked questions

Which Pydantic version does the output target?

Pydantic v2. That is why it emits model_config = ConfigDict(populate_by_name=True) rather than the v1 class Config, and uses list[T] instead of typing.List[T].

When is a Field(alias=...) added?

Only when the JSON key cannot be used as the Python attribute name — a camelCase key, a key with a dash or space, or a key that collides with a Python keyword. populate_by_name then lets you construct the model with either the attribute name or the wire key.

Why are the nested models declared first?

Python evaluates annotations at class-definition time unless you enable postponed evaluation, so a model referenced by another must already exist. Emitting leaf models first means the file imports without forward references or model_rebuild() calls.

Free & private — why use this JSON to Pydantic Model

The JSON to Pydantic Model runs 100% client-side in your browser. Your data is never uploaded to a server, no account is required, and the tool is completely free. It works offline once the page has loaded and is part of a growing collection of privacy-first developer utilities.

More json tools

JSON Formatter JSON Minifier JSON Diff JSON Path Finder JSON Pointer Extractor (RFC 6901)JSON Schema Validator View all 29 JSON Tools →