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litestar-dataclasses

Create Python dataclass transport models for Litestar endpoints with strict typing.

7|1|Updated Mar 2, 2026
Search Tags:#dto#dataclasses#typing#api-design#litestar#transport-models
One-click install
npx skills add https://github.com/alti3/litestar-skills --skill litestar-dataclasses
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: litestar-dataclasses
Source: https://github.com/alti3/litestar-skills/tree/main/plugins/litestar/skills/litestar-dataclasses
Command: npx skills add https://github.com/alti3/litestar-skills --skill litestar-dataclasses

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables developers to model Litestar request and response payloads using Python dataclasses, providing explicit typing, clear defaults, and lightweight DTO interoperability without relying on heavier model ecosystems.

Core Features & Use Cases

  • Explicit, typed dataclasses for API boundaries
  • DTO-friendly integration with Litestar routes
  • Clear separation between transport models and domain/persistence

Quick Start

Create a simple Litestar endpoint that accepts a dataclass payload and returns a confirmation.

Frequently Asked Questions about litestar-dataclasses

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I use Python dataclasses for Litestar request payloads instead of Pydantic?▼

Python dataclasses define Litestar request payloads by enforcing explicit field types and predictable serialization, providing a lightweight, DTO-driven contract without heavier ORM or Pydantic layers.

What is the best way to enforce strict typing for API transport models in Litestar?▼

The best way to enforce strict typing in Litestar is using dataclass-based transport models, which provide explicit field types, clear defaults, and lightweight DTO interoperability for API boundaries.

Can I separate transport models from domain logic using dataclasses in Litestar?▼

Yes, you can separate transport models from domain logic by creating explicit, typed dataclasses for API boundaries, ensuring clear separation between transport models and persistence layers.

Do I need Pydantic to handle DTO serialization and binding in Litestar?▼

No, you do not need Pydantic for DTO serialization in Litestar; dataclass-based transport models enforce explicit field types and handle serialization and binding between layers independently.

How do I create a lightweight DTO contract for Litestar endpoints?▼

Create a lightweight DTO contract for Litestar endpoints by modeling request and response payloads with Python dataclasses, enforcing explicit typing, clear defaults, and predictable serialization.

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