JSON to Python.

Pandia turns a JSON document into Python @dataclass definitions with type hints. Field names use snake_case, optional fields are inferred, and nested structures become their own dataclasses.

Example

Input JSON:

{
  "id": 42,
  "name": "Ada",
  "active": true,
  "tags": ["admin", "early"]
}

Python output:

from dataclasses import dataclass

@dataclass
class Root:
    id: int
    name: str
    active: bool
    tags: list[str]

What you get

• Typed @dataclass output with standard-library type hints.
• Optional fields inferred; nested objects become nested dataclasses.
• Idiomatic snake_case field names.
• No dependencies required — plain dataclasses.

It’s the same engine behind Pandia’s type generation — opinionated, deterministic, and built to run on files far too large for an online converter.

Frequently asked questions

How do I generate Python types from JSON?

Open the Types panel in Pandia, choose Python, and copy the @dataclass definitions into your code.

Does it use Pydantic or dataclasses?

Pandia generates standard-library dataclasses with type hints, so there are no extra dependencies.

Does it work offline and on large files?

Yes — everything runs locally with no upload, and Pandia opens multi-gigabyte JSON without lag.

More converters: JSON to TypeScript · JSON to Go · JSON to Rust · JSON to Zod · JSON to YAML · all tools · download.