Json to python dataclass generator online

The JSON → Python Dataclass generator inspects sample JSON and produces Python classes decorated with @dataclass and annotated using typing. It is a productive helper for Python 3.7+ projects, and the generated classes can be used directly in FastAPI, Pydantic (with light tweaks), SQLAlchemy DTOs and data-analysis scripts, moving code from dynamic dictionaries to strongly-typed object models.

Step 1 — paste sample JSON on the left, or click "Sample" to load an example quickly. Step 2 — specify the root class name (default RootObject). Step 3 — the right panel produces the corresponding @dataclass code live; nested objects become separate classes and are declared in dependency order. Step 4 — copy the code to your project or download it as a .py file. The generated code automatically imports from dataclasses import dataclass and from typing import List, Optional when needed.

Quickly generate request / response models when building a FastAPI service (migrate to Pydantic later); data analysts use dataclasses to improve readability when handling deeply nested JSON logs; batch-generate type definitions when integrating with ML services; Python client SDK developers build models directly from API documentation; migrate an untyped legacy codebase to typed code by generating skeletons.

Strings map to str, integers to int, floats to float, booleans to bool, arrays to List[T], and null maps to Optional[Any]. Class names are PascalCased while field names keep their original JSON spelling (switch to snake_case manually if needed). Default indentation is 4 spaces, matching PEP 8. The dataclass output does not include __post_init__ or JSON serialisation helpers; combine with dataclasses-json or marshmallow if you need those.

Type inference runs entirely in your browser, so no JSON data is uploaded. You can safely process sample payloads that contain personal information or API-key placeholders.