Why Dataclasses Over Dicts?

Python dataclasses provide type safety, IDE autocompletion, and self-documenting code compared to raw dictionaries. They also support default values, comparison, and hashing out of the box. This generator creates ready-to-use dataclasses from your JSON.

// JSON input
// { "name": "Alice", "age": 30, "tags": ["admin", "editor"] }

# Generated Python dataclass
from dataclasses import dataclass, field
from typing import List

@dataclass
class User:
    name: str
    age: int
    tags: List[str] = field(default_factory=list)

# Usage
user = User(name="Alice", age=30, tags=["admin"])
print(user.name)  # "Alice"

Type Hint Inference

The generator maps JSON types to Python types: strings to str, booleans to bool, integers to int, floats to float, nulls to Optional[Any], and arrays to list[T]. Nested objects become separate dataclass definitions.

Snake Case Naming

Python convention uses snake_case for variable names. The generator automatically converts camelCase JSON keys to snake_case field names, following PEP 8 naming conventions.