python-project-structure

To organize a Python project with clean module boundaries, enforce explicit public interfaces using __all__ and maintain flat directory structures. This approach ensures modules remain cohesive and scalable by clearly separating internal implementations from exposed APIs.

The best way to design a public API in a Python package is by explicitly defining __all__ in your modules. This exposes specific functions and classes while hiding internal logic, keeping your interfaces clean and maintainable across src and packaging layouts.

The __all__ mechanism works by listing the explicit public interface names a module exposes. It controls imports so that wildcard imports only pull defined names, enforcing strict module boundaries and preventing internal code from leaking into the public API.

Yes, you can use this approach to reorganize an existing Python codebase. It applies structure by introducing clear modular boundaries, consistent naming conventions, and explicit __all__ exposure to refactor tangled code into a maintainable, scalable architecture.

The recommended testing layout for a scalable Python project involves a flat directory structure that mirrors your src layout. This ensures consistent naming conventions and clear modular boundaries, keeping tests aligned with your explicit public API.

You should reconsider a flat directory structure for Python projects when your codebase lacks clear modular boundaries. If your modules are highly interdependent without a separable public API, enforcing strict __all__ exposure and flat layouts may overcomplicate the architecture.