JSON to Python Class Converter

How to use the json to python class converter

1. Paste your JSON object into the text area. It must begin with an opening brace {.
2. Set the Root class name to a PascalCase identifier like User or ApiResponse.
3. The converter immediately generates Python dataclass definitions with correct type hints below.
4. Copy the output and paste it into your Python file. Add from __future__ import annotations at the top if you need forward references.

How the json to python class conversion works

The tool parses your input using the built-in JSON.parse function and walks the resulting tree to determine Python types. Each JSON object becomes its own @dataclass. Keys are converted to valid Python identifiers by replacing hyphens and spaces with underscores and stripping other invalid characters.

Type mapping follows straightforward rules. A JSON string maps to str, an integer to int, a decimal number to float, a boolean to bool and null to Optional[Any]. Arrays become List[T] where T is inferred from every element, so objects with different keys are merged into one class and keys missing from some objects become Optional. Nested objects trigger generation of a child class whose name is derived from the parent key.

Type mapping reference

This table shows how each JSON type translates into a Python type hint in the generated dataclass.

When an array contains mixed types, the converter falls back to List[Any]. Empty arrays produce List[Any] because there is no element to inspect.

Handling nested objects and arrays

Nested structures are flattened into separate class definitions. If your root object has a field called address that is itself an object, the converter creates an Address dataclass and uses it as the type hint in the parent. This keeps every class small and focused.

Arrays of objects work the same way. A field like "items": [{"id": 1}] produces an Item class and types the field as List[Item]. The order of class definitions is bottom-up so that child classes appear before they are referenced, avoiding the need for string-based forward references in most cases.

Key sanitization rules

JSON keys can contain any Unicode character, but Python identifiers have strict rules. The converter applies these transformations in order:

• Hyphens, spaces and dots are replaced with underscores.
• Characters that are not ASCII letters, digits or underscores are removed.
• If the result starts with a digit, an underscore is prepended.
• If the result matches a Python reserved keyword such as class or return, a trailing underscore is appended.
• An empty result after filtering becomes _field.

The original JSON key name is preserved in a comment next to the field so you can map it back when serializing.

Using the generated classes

The output relies on the dataclasses module introduced in Python 3.7. Import it at the top of your file along with typing for List, Optional and Any:

from dataclasses import dataclass
from typing import List, Optional, Any

To populate these classes from a JSON string, parse the string with the standard json library and unpack the dictionary into the constructor: User(**json.loads(text)). For deeply nested payloads consider a library like dacite or marshmallow which handles recursive instantiation automatically.

If you need to convert your data to other formats, tools like json to xml or json to sql handle those transformations. For typed languages, sibling converters exist for Java, C#, Go and Kotlin.

Worked examples