Skip to content

Latest commit

 

History

History
76 lines (59 loc) · 11.1 KB

README.md

File metadata and controls

76 lines (59 loc) · 11.1 KB

Litestar Logo - Light Litestar Logo - Dark

Project Status
CI/CD Latest Release ci Documentation Building
Quality Coverage Quality Gate Status Maintainability Rating Reliability Rating Security Rating
Package PyPI - Version PyPI - Support Python Versions DTOs PyPI - Downloads
Community Reddit Discord Matrix Medium Twitter Blog
Meta Litestar Project types - Mypy License - MIT Litestar Sponsors linting - Ruff code style - Ruff

Model your domain at the edge.

Warning

Pre-Release Alpha Stage

Please note that DTOS is currently in a pre-release alpha stage of development. This means the library is still under active development, and its API is subject to change. We encourage developers to experiment with DTOS and provide feedback, but we recommend against using it in production environments until a stable release is available.`

About

The dtos library bridges the gap between complex domain models and their practical usage across network boundaries. It is designed for Python developers seeking to streamline the process of configuring different representations of domain models, such as dataclasses and SQLAlchemy models, for network edge parsing and validation. Whether you're looking to accept a subset, superset, or a completely customized set of fields defined on your model at the network edge, dtos offers a flexible and powerful solution.

Purpose

dtos is built with the vision of enhancing domain modeling at the network edge, offering developers unparalleled control over their data's shape and structure during transfer. The library facilitates:

  • Customizable Data Representations: Tailor your data to meet the exact needs of your network interactions, enabling a more efficient and precise data exchange.
  • Edge Parsing and Validation: Ensure your data integrity by defining explicit parsing and validation rules that match your application's requirements.
  • Seamless Integration: Designed to work effortlessly with popular Python data modeling and ORM tools, dtos integrates into your existing workflow with minimal overhead.

Contributing

All Litestar Organization projects will always be a community-centered, available for contributions of any size.

Before contributing, please review the contribution guide.

If you have any questions, reach out to us on Discord, our org-wide GitHub discussions page, or the project-specific GitHub discussions page.


Litestar Logo - Light
An official Litestar Organization Project