JSON to Language Struct / Class Generator
About JSON → Python Dataclass
The JSON to Python Dataclass & Pydantic Model Generator converts JSON objects into Python 3.10+ `@dataclass` structures, Pydantic v2 `BaseModel` classes, and TypedDict schemas with type hinting and field aliasing.
How to Use JSON → Python Dataclass
Step 1
Paste your JSON payload into the input editor.
Step 2
Select model format (Pydantic v2, Dataclass, or TypedDict).
Step 3
Name your root class (e.g. `UserSchema`).
Step 4
Click "Copy Python Code".
Practical Use Cases for JSON → Python Dataclass
FastAPI Request / Response Model Generation
Convert JSON payloads into Pydantic `BaseModel` classes with `Field(alias="...")` for FastAPI endpoints.
Python Data Pipeline & ETL Type Annotations
Generate standard library `@dataclass` definitions with `Optional[T]`, `List[T]`, and `Dict[str, Any]` type hints.
Input & Output Examples
Converting JSON to Pydantic v2 Model
`{ "user_id": 42, "email": "user@example.com", "is_admin": false }``from pydantic import BaseModel, Field\n\nclass User(BaseModel):\n user_id: int = Field(alias="user_id")\n email: str\n is_admin: bool`
Key Features & Performance
- ✓Outputs: Pydantic v2 `BaseModel`, Python standard `@dataclass`, `TypedDict`, or attrs class.
- ✓Type inference: `int`, `float`, `str`, `bool`, `list`, `dict`, and `Optional[T]`.
- ✓Option to generate `from_dict()` and `to_dict()` helper methods.
- ✓100% Client-Side memory execution.
- ✓1-Click Copy Python code.
Key Terminology & Definitions
Pydantic `BaseModel`
The primary data validation and settings management class in Python, parsing and validating incoming data against type annotations.
Python Dataclass
A decorator and module in the Python standard library (`dataclasses`) that automatically adds generated special methods like `__init__()` and `__repr__()`.