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JSON to Python Dataclass
Generate Python dataclasses with type hints from a sample JSON document.
Keys are converted to snake_case for PEP 8, fields with defaults are ordered last so the dataclass compiles, and the typing imports at the top match exactly what the hints below use.
Quick Tool Overview
The JSON to Python Dataclass converter generates dataclasses with full type hints, snake_case field names, Optional wrappers with None defaults, and exactly the typing imports the output uses.
- What it does
- Generates Python dataclasses from a JSON sample
- You give it
- A JSON payload, ideally an array of records
- You get back
- Typed dataclasses that import and run as written
- Best for
- Typing API responses in Python services and scripts
About the JSON to Python Dataclass
Paste a JSON sample and get dataclasses for it: one per nested object, with type hints on every field, List[...] for arrays and Optional[...] with a None default for anything that is not always present.
The details that make generated Python actually run are handled. Field names are converted to snake_case, the typing imports at the top list exactly what the output uses, and fields with defaults are ordered after those without — the rule a dataclass refuses to compile if you break. Nested classes are declared before the classes that reference them, so the module executes top to bottom without forward references.
Key features of the JSON to Python Dataclass
Output that actually compiles
Fields with defaults are ordered after those without, which is the rule a dataclass raises a TypeError over if you break it.
PEP 8 names
Keys are converted to snake_case, so the generated code reads like Python rather than like the JSON it came from.
Exact imports
The typing line at the top lists only what the hints below actually use — no unused imports for a linter to flag.
Declaration order is correct
Nested classes are declared before the classes that reference them, so the module executes top to bottom with no forward references.
Optional means optional
A key that is missing from some records becomes Optional[...] with a None default rather than being asserted as required.
How to use the JSON to Python Dataclass
-
1
Paste the JSON
An array of records gives the best optional-field detection.
-
2
Name the root class
Nested classes take their names from the keys that hold them.
-
3
Review the imports
The typing imports at the top match exactly what the generated hints use.
-
4
Copy into your project
Paste into a .py file and start using the classes.
Frequently asked questions
No, they are plain type definitions. Construct them with **data for flat shapes, or use a library such as pydantic or dacite when the nesting is deep.
Because a dataclass raises a TypeError at import time if a field without a default follows one with a default. Reordering is the only way the output compiles.
Yes, to snake_case, since that is PEP 8. If your JSON keys are camelCase you will need an alias when parsing — pydantic calls it an alias, dacite calls it a key mapping.
Dataclasses when you only need structure and type hints; pydantic when you also want the values validated and coerced at runtime. The field declarations look almost identical either way.
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