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JSON to Python Dataclass

Convert JSON into Python dataclasses with type hints. Nested objects become nested classes, lists get element types, and nulls become Optional.

JSON input

Paste JSON, optionally name the root type, then generate.

Your Python dataclass code will appear here.
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From JSON to typed models

Paste a JSON payload and the tool builds a dataclass per object level. Primitives map to str, int, float, and bool, arrays map to List, and uncertain fields become Optional. The result is a faithful, type hinted model of your data.

Why dataclasses for API data

Dataclasses give you readable constructors, equality, and repr for free, which makes debugging API integrations far easier than juggling raw dicts. Pair them with a JSON loader to turn responses into real objects in one line.

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JSON to Py Dataclass FAQs

What is a Python dataclass?
A dataclass is a concise way to define classes that mainly hold data. The @dataclass decorator auto generates __init__, __repr__, and __eq__, so you write fields once with type hints.
How are nested objects represented?
Each nested JSON object becomes its own @dataclass, declared above the parent, so an address object becomes an Address class referenced by a typed field.
What does Optional mean here?
Fields whose sample value is null, or that are missing from some array items, become Optional[X], signaling the value may be None in real data.
How are JSON arrays typed?
Arrays become List[X] from the typing module, with X inferred from the elements. Arrays of objects reference the generated nested class.
Which Python version does the output need?
Dataclasses require Python 3.7 or newer, and the typing imports used here work on all supported Python 3 versions.
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