Enforce a strict layered Django architecture with ULID keys and Pydantic DTOs.
npx skills add https://github.com/dvf/opinionated-django --skill dj-architecture
Please help me install this Agent Skill. Skill: dj-architecture Source: https://github.com/dvf/opinionated-django/tree/main/skills/dj-architecture Command: npx skills add https://github.com/dvf/opinionated-django --skill dj-architecture
Django projects often suffer from inconsistent architecture, ORM leakage across layers, and untestable business logic, leading to codebases that are hard to maintain and scale as the project grows.
Use the dj-architecture skill to implement a new order management feature with API endpoints, repository layer, and unit tests in your existing opinionated Django project.
High-intent search queries and answers about installing and using this skill.
To prevent Django ORM leakage, you can enforce a strict 5-layer architecture separating API, Service, DTO, Repository, and Model components. Using Pydantic DTOs at layer boundaries ensures type safety and stops ORM queries from leaking into business logic.
Structuring a new Django entity involves defining django-ninja API routes, repository layers, and Celery reliable signals for async side-effects. This strict separation ensures business logic remains decoupled from API routing and background task execution.
Yes, this layered Django architecture pattern supports dependency injection using the svcs library. Injecting dependencies through defined boundaries improves code testability and maintainability across your service and repository layers.
The best way to add type-safe DTOs to a Django project is using Pydantic models at layer boundaries. Defining Pydantic DTOs separates internal ORM models from external API contracts, eliminating data leakage and improving validation.
Prefixed ULID primary keys should be used in Django models to provide globally unique, time-sortable identifiers without exposing sequential database row counts. This opinionated convention enhances scalability and data integrity across distributed systems.
Comprehensive tests for layered Django business logic are written by targeting the Service and Repository layers independently using injected dependencies. Isolating layers through svcs dependency injection allows precise unit testing without hitting the database.
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