clean-architecture-python

Implement Clean Architecture in Python with layered design and domain-driven principles.

1|Updated Dec 30, 2025

Search Tags:#software design #python #ddd #clean architecture #solid #layered architecture

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npx skills add https://github.com/statick88/dotfiles --skill clean-architecture-python

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: clean-architecture-python
Source: https://github.com/statick88/dotfiles/tree/main/amp/.agents/skills/clean-architecture-python
Command: npx skills add https://github.com/statick88/dotfiles --skill clean-architecture-python

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a robust, maintainable, and scalable blueprint for building Python applications by enforcing a strict separation of concerns through Clean Architecture principles.

Core Features & Use Cases

Layered Design: Implements a 4-layer pattern (Presentation, Application, Domain, Infrastructure) ensuring dependencies point inwards.
Domain-Driven Development: Focuses on core business logic and entities, keeping them framework-agnostic.
Testability: Facilitates easy unit and integration testing by isolating business logic.
Use Case: Develop a new microservice for user management, ensuring the core user entity and business rules can be reused across different presentation layers (e.g., REST API, CLI) and infrastructure choices (e.g., PostgreSQL, MongoDB).

Quick Start

Implement a new user entity within the domain layer by defining its attributes and business rules.

Frequently Asked Questions about clean-architecture-python

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

FAQPage Schema

How do I structure a Python application using clean architecture and domain-driven design?▼

Structure your Python application into four layers: Presentation, Application, Domain, and Infrastructure, ensuring dependencies point inward toward the domain. This enforces a strict separation of concerns, keeping core business logic framework-agnostic and highly testable.

What is the best way to isolate business logic in Python for better testability?▼

Isolate business logic by defining domain entities and repository interfaces within the domain layer, keeping them independent of infrastructure choices. This approach facilitates easy unit and integration testing by decoupling core rules from database or framework implementations.

Can I reuse the same domain entities for both a REST API and a CLI in Python?▼

Yes, you can reuse the same domain entities across different presentation layers like a REST API or CLI. Clean architecture ensures core business rules are framework-agnostic, allowing infrastructure and presentation components to interact with the same domain layer.

How does a layered architecture handle switching between PostgreSQL and MongoDB in Python?▼

Layered architecture handles database switching by defining repository interfaces in the domain layer and implementing them separately in the infrastructure layer. This allows you to swap PostgreSQL or MongoDB implementations without altering the application use cases or domain entities.

When do I need clean architecture for my Python software design?▼

You need clean architecture when developing scalable microservices or applications requiring high maintainability, testability, and flexibility. It solves the problem of tightly coupled code by enforcing a strict separation of concerns through a layered design pattern.