JSON to Python
Generate Python dataclasses from any JSON sample.
Three steps, no reading required.
Paste your input
Drop text, code, or data into the input pane — from an API response, a file, anywhere.
See it process
The result updates instantly as you type.
Copy the result
Grab the output with Copy or Download, or fix the error shown if the input is invalid.
Try it with a sample.
{"id":1,"name":"Ada","active":true,"roles":["admin","user"],"address":{"city":"London"}}Untyped dicts
- Gives you dict access, not typed models
- Treats optional fields as required
- Uploads your sample
Typed dataclasses
- Dataclasses with type hints, one per nested object
- Missing keys become Optional; null becomes Optional[Any]
- Changes to a Pydantic model by swapping the base class
Questions worth answering upfront.
No. Code is generated entirely in your browser. Your JSON is never uploaded, stored, or logged.
Python dataclasses with type hints. Each nested object becomes its own dataclass, and lists are typed with the typing module (List, Optional, Union).
When you convert an array of objects, a key missing from some elements is typed as Optional. A field whose value is null is typed Optional[Any] because its real type can't be inferred.
The output is standard dataclasses. Switching to a Pydantic BaseModel is usually just changing the base class and decorator, since the field type hints carry over.
Yes. Every tool on DevUtilsNow is free to use with no account required.
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Guides that pair with this tool
How to Generate Python Dataclasses from JSON
Turn a JSON sample into typed Python dataclasses — how nested objects, optional fields, and null values are handled, and how to adapt for Pydantic.
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