python-project-structure

Structure Python projects by adopting flat directory hierarchies, reliable absolute imports, and consistent test placement. This approach clarifies module boundaries and keeps codebases understandable as they scale, preventing circular dependencies and import errors.

Define a public API in a Python package by using explicit interfaces with __all__ and careful package initialization. This restricts exposed modules, hides internal implementation details, and provides a stable, predictable interface for downstream consumers.

Organize Python code by layer for simpler applications and switch to domain-driven architecture as project complexity grows. Structuring by domain groups related business logic together, making large repositories easier to navigate and maintain.

Refactor an existing Python repository by flattening directory layouts, standardizing absolute imports, and enforcing explicit module boundaries. This process reorganizes tests and public interfaces to achieve a cleaner, more maintainable package structure.

Yes, flat directory hierarchies work for large codebases when combined with coherent module boundaries and domain-driven organization. This layout prevents deeply nested packages, keeping Python project structures understandable and imports reliable.

Standardizing test placement in your Python project layout ensures tests are discoverable and separated from production code. Consistent test organization maintains architectural integrity and simplifies continuous integration across teams.