JSON to Pydantic Model Converter

Transform any JSON object into a Pydantic BaseModel class with proper Python type annotations. Boolean values become bool, null values become Optional[T] = None, arrays become List[T], and nested objects become nested Pydantic model classes.

How to use

1. Paste your JSON data into the left editor
2. Toggle Pydantic BaseModel in the options (enabled by default)
3. Click Generate
4. Copy the generated Pydantic model code

What you get

• BaseModel classes — each JSON object becomes a Pydantic model
• Type annotations — str, int, float, bool, List[T], Optional[T]
• Nested models — deeply nested JSON produces nested Pydantic classes
• Required vs optional — fields present in all objects are required; optional fields use Optional[T] = None
• Enum support — string enums from JSON enum values

Example

Input:

{
  "name": "LangStop",
  "active": true,
  "score": 42,
  "tags": ["dev", "tools"],
  "config": {
    "theme": "dark",
    "timeout": null
  }
}

Output:

from pydantic import BaseModel
from typing import List, Optional
 
 
class Config(BaseModel):
    theme: str
    timeout: Optional[str] = None
 
 
class Root(BaseModel):
    name: str
    active: bool
    score: int
    tags: List[str]
    config: Config

Why Pydantic?

Pydantic is the most popular data validation library for Python — it validates data at runtime using Python type annotations. It is the foundation of FastAPI, widely used in data pipelines, ML systems, and configuration management.

Toggle the Pydantic BaseModel option to switch between plain Python dataclasses and full Pydantic models with BaseModel inheritance.

Related tools

• JSON to Python — Generate Python dataclasses from JSON
• JSON Schema GUI Builder — Visually design JSON Schema
• JSON to JSON Schema — Infer JSON Schema from sample data
• JSON to TypeScript Zod — Generate Zod schemas from JSON