python-project-structure

Organize Python project structures with module boundaries and explicit __all__ public APIs.

1|Updated Apr 14, 2026

Search Tags:#python #organize #project-structure #skeleton #public-api #module-architecture

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npx skills add https://github.com/Sumeet138/qwen-code-agents --skill python-project-structure-sumeet138

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: python-project-structure
Source: https://github.com/Sumeet138/qwen-code-agents/tree/main/plugins/python-development/skills/python-project-structure
Command: npx skills add https://github.com/Sumeet138/qwen-code-agents --skill python-project-structure-sumeet138

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Python projects often become tangled as they grow, making imports brittle and collaboration painful.

Core Features & Use Cases

Module boundaries and explicit interfaces using all to define public APIs.
Flat, scalable directory structures and a recommended src layout for packaging.
Use cases include starting new projects, refactoring for clarity, and creating reusable library skeletons.

Quick Start

Create a new project skeleton with a src/ directory, tests/ directory, and a clearly documented public API.

Frequently Asked Questions about python-project-structure

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

FAQPage Schema

How do I organize a Python project structure to prevent imports from becoming tangled?▼

Organize your Python project structure by defining clear module boundaries and using a flat, scalable directory layout. This approach prevents tangled imports by enforcing explicit public APIs through the __all__ attribute, ensuring codebase scalability and smoother collaboration.

What is the best way to define a public API in a Python module?▼

The best way to define a public API in a Python module is by explicitly listing exposed interfaces using the __all__ attribute. This establishes clear module boundaries, preventing internal implementation details from leaking and keeping your Python project structure maintainable.

How do I set up a new Python project skeleton for library development?▼

Set up a new Python project skeleton by creating a src/ directory for your library code and a separate tests/ directory. This src layout enforces clean packaging boundaries and pairs with an explicitly documented public API for scalable library development.

Can I refactor an existing Python codebase to use a src layout and explicit module boundaries?▼

Yes, you can refactor existing Python codebases by migrating to a flat src layout and defining explicit module boundaries. Applying explicit public interfaces with __all__ during the refactoring process clarifies dependencies and restores architectural clarity to tangled projects.

Does this Python project structure approach work for both small and large codebases?▼

Yes, this Python project structure approach applies across small to large codebases. Enforcing explicit public interfaces and a flat directory layout ensures that your module architecture remains scalable and clear whether you are starting small or expanding an existing library.

When should I not use a flat directory layout for my Python project?▼

You should avoid a flat directory layout if your Python project does not require strict module boundaries or explicit public APIs. Projects with highly nested, domain-specific architectures might find enforcing a flat src layout and __all__ interfaces unnecessarily rigid.