Dataclasses

Execution Workflow

1. Define dataclasses for transport boundaries with explicit field types.
2. Use defaults and optionality intentionally to avoid ambiguous schemas.
3. Combine with DTO configuration when write/read shapes diverge.
4. Keep domain entities and transport dataclasses separate when needed.

Implementation Rules

• Favor immutable or clearly controlled mutation patterns.
• Avoid embedding persistence/session behavior in dataclasses.
• Keep field names/schema stable for clients.
• Validate nested dataclass behavior in serialization paths.

Example Pattern

from dataclasses import dataclass
from litestar import post

@dataclass
class CreateUser:
    name: str
    email: str

@post("/users")
async def create_user(data: CreateUser) -> dict[str, str]:
    return {"email": data.email}

Validation Checklist

• Confirm request binding maps correctly into dataclass fields.
• Confirm response serialization matches expected JSON schema.
• Confirm DTO include/exclude behavior remains predictable.

Cross-Skill Handoffs

• Use litestar-dto for advanced shaping and nested field policy.
• Use litestar-plugins when switching to different model ecosystems.

Litestar References

• https://docs.litestar.dev/latest/usage/dto/index.html