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python-project-structure

Organize Python projects with module boundaries and explicit __all__ interfaces.

3|1|Updated Feb 3, 2026
Search Tags:#python#project-structure#code-maintenance#public-api#package-design#module-architecture
One-click install
npx skills add https://github.com/duanbiao2000/obsidianDoc26 --skill python-project-structure-duanbiao2000
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: python-project-structure
Source: https://github.com/duanbiao2000/obsidianDoc26/tree/main/agents-main/plugins/python-development/skills/python-project-structure
Command: npx skills add https://github.com/duanbiao2000/obsidianDoc26 --skill python-project-structure-duanbiao2000

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Python project structure and module architecture guidelines to help you define clear boundaries, expose a clean public API via all, and plan scalable layouts that support maintainability and reuse.

Core Features & Use Cases

  • Define module cohesion with focused files and explicit public APIs using all.
  • Promote flat directory structures to reduce import complexity and navigation friction.
  • Plan packaging and testing layouts to improve maintainability and onboarding.

Quick Start

Create a new Python project layout with src/, tests/, and a minimal pyproject.toml, then document the public API with all.

Frequently Asked Questions about python-project-structure

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

FAQPage Schema
How do I define clear public APIs in a Python project?▼

Defining a clear Python public API involves using the __all__ variable to explicitly list exposed modules and functions, ensuring consumers only import intended interfaces while maintaining clean module boundaries.

What is the best way to organize Python project structure for maintainability?▼

Organizing Python project structure for maintainability requires adopting flat directory architectures to reduce import complexity, defining focused module files, and planning packaging layouts with src/ and tests/ directories.

How do I refactor an existing Python codebase to reduce import complexity?▼

Refactoring a Python codebase to reduce import complexity involves applying flat directory structures, enforcing consistent naming conventions, and setting explicit module boundaries with __all__ to expose clean APIs.

When should I use __all__ in Python module architecture?▼

You should use __all__ in Python module architecture when defining explicit public interfaces for libraries or refactors, ensuring controlled API exposure and improving testability by hiding internal implementation details.

Does a flat directory structure work for scalable Python packaging?▼

A flat directory structure supports scalable Python packaging by minimizing navigation friction and import complexity, allowing consistent naming conventions to maintainability as the project grows.

What layout do I need to start a new Python package with a clean API?▼

Starting a new Python package requires a layout with src/, tests/, and a minimal pyproject.toml, combined with explicit public API definitions using __all__ to ensure clean boundaries and testability.

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