python-clean-architecture

Python clean architecture separates domain logic from infrastructure by enforcing dependency rules where the domain layer imports nothing from infrastructure or API boundaries. This decouples business logic from specific frameworks, improving testability and maintainability across your project.

Structure your Python project using clean architecture by dividing it into domain, infrastructure, and API layers. Define domain models and repository interfaces in the inner layers, implement services, and wire them together with dependency injection for a runnable, testable application structure.

You need clean architecture for Python services when your projects require testable domain logic, framework-agnostic services, and maintainable code organization. It is applicable to software projects of varying sizes that need clear boundaries across repository, service, and API layers.

Dependency injection wiring in Python clean architecture connects repository interfaces to their concrete implementations at the infrastructure layer. This mechanism ensures your domain services remain framework-agnostic and testable by injecting dependencies rather than hardcoding them.

The best way to test domain models in Python is by using clean architecture to decouple them from persistence and web concerns. By defining repository interfaces and applying dependency rules, you can test domain logic independently without needing actual database or API connections.

Yes, Python clean architecture works for software projects of varying sizes. It provides a practical project structure with clear domain, infrastructure, and API boundaries, ensuring maintainable code organization and testable domain logic even as project scope scales.