How do I generate a Pydantic model from JSON?

Paste your JSON into the input box, set a root model name, and the tool generates the Pydantic BaseModel classes instantly. Click Copy Python Code to use them in your project.

What happens to camelCase JSON keys?

They are converted to snake_case field names with an alias that keeps the original key, for example user_id: int = Field(..., alias="userId"). Keys that are already snake_case are left unchanged.

How are nested objects and lists handled?

Each nested object becomes its own BaseModel class named after its key. Lists are typed from their first element, such as list[str], and an empty list becomes list[Any].

Which Python version does the generated code need?

The output uses built-in generics like list[str], which need Python 3.9 or newer. On older versions, replace them with List[str] from the typing module.

Is my JSON data kept private?

Yes. The JSON is parsed and converted in your browser and is never sent to a server.

JSON to Python Pydantic Model Generator

Convert sample JSON payloads into clean, typed Python 3.10+ Pydantic v2 BaseModel classes.

100% free
Private in browser
No signup
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Root Model Name

Input JSON

Pydantic v2 Models (2)

from pydantic import BaseModel, Field
from typing import Optional, Any


class Metadata(BaseModel):
    last_ip: str


class UserAccount(BaseModel):
    user_id: int
    email: str
    is_staff: bool
    metadata: Metadata

About JSON to Python Pydantic Model Generator

The JSON to Pydantic Model Generator converts a sample JSON payload into Python Pydantic BaseModel classes. Paste an API response, name the root model, and the tool writes typed fields using str, int, float, bool, and list[...] annotations, plus the import lines you need. Nested objects become separate models, and keys that are not snake_case get a snake_case field with a Field alias that keeps the original name. The conversion runs in your browser, so your JSON never leaves your device.

How to use JSON to Python Pydantic Model Generator

Enter a root model name, such as UserAccount.
Paste your sample JSON object or array into the input box.
Review the generated BaseModel classes and field types.
Click Copy Python Code and paste it into your Python module.

Key features

Generates Pydantic BaseModel classes with the required import lines
Infers str, int, float, bool, and list[...] types from sample values
Creates a separate model for every nested object
Converts camelCase keys to snake_case fields with a Field alias
Shows the JSON parse error when the input is invalid
Runs in your browser — your JSON is never uploaded

Frequently asked questions

How do I generate a Pydantic model from JSON?: Paste your JSON into the input box, set a root model name, and the tool generates the Pydantic BaseModel classes instantly. Click Copy Python Code to use them in your project.
What happens to camelCase JSON keys?: They are converted to snake_case field names with an alias that keeps the original key, for example user_id: int = Field(..., alias="userId"). Keys that are already snake_case are left unchanged.
How are nested objects and lists handled?: Each nested object becomes its own BaseModel class named after its key. Lists are typed from their first element, such as list[str], and an empty list becomes list[Any].
Which Python version does the generated code need?: The output uses built-in generics like list[str], which need Python 3.9 or newer. On older versions, replace them with List[str] from the typing module.
Is my JSON data kept private?: Yes. The JSON is parsed and converted in your browser and is never sent to a server.

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