python-design-patterns

To untangle responsibilities, analyze Python design decisions to enforce explicit design principles. This separates domain logic from infrastructure, improves module boundaries, and enables safer refactors in a growing codebase.

Use value objects, services, adapters, and factories when you need to structure Python code with clean boundaries. Apply these patterns during architecture reviews to promote maintainability and avoid over-engineering.

The best way to assess a Python module for refactoring is to analyze its current design decisions. This process identifies tangled responsibilities and proposes a fitting design pattern to simplify maintenance and testing.

Safely refactor Python code by applying explicit design principles that separate domain logic from infrastructure. This approach provides safe refactor guidance, preventing over-engineering and promoting clean architectural boundaries.

Applying design patterns to Python projects does not lead to over-engineering when guided by explicit design principles. The focus is on reviewing design choices to promote clean boundaries, ensuring patterns fit the project scale.