Best Practices for Managing Python File and Folder Structure

A well-organized file and folder structure is crucial for Python projects of any size. It improves readability, maintainability, and helps new contributors quickly understand your codebase. Let's explore some best practices for structuring Python projects.

Follow the Standard Project Structure

Most Python projects benefit from following a standardized structure:

project_root/
├── README.md
├── LICENSE
├── setup.py
├── requirements.txt
├── .gitignore
├── project_name/
│   ├── __init__.py
│   ├── core.py
│   ├── helpers.py
│   └── subpackage/
│       ├── __init__.py
│       └── submodule.py
├── tests/
│   ├── __init__.py
│   ├── test_core.py
│   └── test_helpers.py
└── docs/
    ├── conf.py
    └── index.rst

Use Clear, Descriptive Names

• Use lowercase letters and underscores for Python files and packages (snake_case)
• Avoid generic names like utils.py or helpers.py without context
• Make file names clearly indicate their purpose

Separate Code by Functionality

Group related functionality together. Consider organizing your code into these common directories:

• core/: Essential functionality
• models/: Data structures and database models
• views/: UI/presentation logic
• controllers/ or services/: Business logic
• utils/ or common/: Shared utility functions

Keep the Root Clean

The project root should contain only high-level files like:

• README, LICENSE, setup files
• Configuration files
• Entry points

Move all implementation code into your main package directory.

Use __init__.py Files Effectively

These files serve multiple purposes:

• Mark directories as Python packages
• Import and expose classes/functions to simplify imports
• Initialize package-level variables

# project_name/__init__.py
from .core import main_function, CoreClass
from .helpers import helper_function

__all__ = ['main_function', 'CoreClass', 'helper_function']

Group Tests Logically

Tests should mirror your project structure:

• One test file per module
• Same directory hierarchy as your main package
• Clear naming convention (e.g., test_filename.py)

Separate Application Code from Scripts

• Put your main application logic in importable modules
• Create separate entry point scripts that import and use your modules
• Use a scripts/ or bin/ directory for command-line tools

Configuration Management

Store configurations properly:

• Use a dedicated config/ directory for complex projects
• Keep simple settings in a single config.py file
• Use environment variables for sensitive information

Managing Dependencies

• requirements.txt: Direct dependencies for users
• requirements-dev.txt: Development dependencies (linters, test tools)
• setup.py: For installable packages

Use a src Layout for Packages

For packages meant to be distributed, consider the src layout:

project_root/
├── src/
│   └── package_name/
│       └── ...
├── tests/
└── ...

This prevents accidental imports from the development version of your package.

Documentation

Maintain documentation separately from code:

• Use a docs/ directory
• Consider using Sphinx for comprehensive documentation
• Include examples in a separate examples/ directory

Final Thoughts

A well-structured Python project saves time and headaches as your codebase grows. While these guidelines provide a solid foundation, adapt them to your specific needs. What matters most is consistency and clarity - choose a structure that makes sense for your project and stick with it.

Remember: Good structure is invisible when it's working well. You'll know you've succeeded when new team members can navigate your codebase without confusion.