When developing a Python project as the codebase gets bigger you may need some organization on the file hierarchy. A well-structured project not only makes your codebase more maintainable but also helps in scalability and collaboration. Whether you’re working solo or as part of a team, adopting a clear and logical project structure will add to the project’s success.

In this blog post, I’ll explore best practices for organizing Python project hierarchies backed by examples.

1. The Importance of a Well-Organized Project Structure

A clean project structure makes it easier to:

  • Understand the codebase: A logical layout allows you and your team to quickly find and navigate through files and modules.
  • Maintain and scale the project: As your project grows, a well-structured hierarchy helps manage complexity and prevents it from becoming overwhelming.
  • Encourage collaboration: Contributors can quickly get up to speed when the project is organized consistently.
  • Separate concerns: Organizing code into distinct modules and packages helps isolate functionality, making the code easier to test and reuse.

2. Basic Layout of a Python Project

A typical Python project layout might look like this:

project_name/
│
├── src/
│   ├── package_name/
│   │   ├── __init__.py
│   │   ├── module1.py
│   │   └── module2.py
│   └── __main__.py
│
├── tests/
│   ├── __init__.py
│   ├── test_module1.py
│   └── test_module2.py
│
├── docs/
│   └── index.md
│
├── .gitignore
├── requirements.txt
├── setup.py
└── README.md

Key Components of the Structure

  • src/ Directory:
    • Contains the main application code.
    • The package_name/ subdirectory is the main package, and __init__.py is used to initialize it as a package.
    • __main__.py is a special file in a package that Python will execute when you run the package as a script.
    • When you use the command python -m package_name, Python will search for the __main__.py file inside the package_name directory and execute it. This allows you to run the entire package or its entry point (defined by __main__.py) without needing to specify a particular script.
    • In summary, __main__.py is how you allow a Python package to act like a script, and the command python -m package_name will trigger it.
  • tests/ Directory:
    • Contains all test cases.
    • It mirrors the structure of the src/ directory to keep tests organized and related to the code they’re testing.
  • docs/ Directory:
    • Includes documentation for the project.
    • Can be expanded with subdirectories and files as needed.
  • setup.py:
    • A script for setting up the package. It defines dependencies and other metadata required for packaging and distribution.
  • .gitignore:
    • Specifies files and directories that Git should ignore, such as temporary files, build directories, or virtual environments.
  • requirements.txt:
    • Lists all the dependencies required for the project. This file is crucial for setting up the environment.
  • README.md:
    • Provides an overview of the project, including how to install, use, and contribute.

3. Structuring Your Code with Packages and Modules

In Python, a module is a single file containing Python definitions and statements, while a package is a collection of modules in directories that provide a hierarchy. Organizing your code into packages and modules helps keep your codebase modular and easier to navigate.

Example Structure

Suppose you’re building an API client for multiple exchanges like Alpaca, Binance, and BingX. Your src/ directory might look like this:

src/
│
├── api/
│   ├── __init__.py
│   ├── alpaca_api.py
│   ├── binance_api.py
│   └── bingx_api.py
│
└── utils/
    ├── __init__.py
    ├── logger.py
    └── helpers.py

__init__.py and Its Role

Each directory in the hierarchy that you want to use as a package must contain an __init__.py file. This file can be empty, but it’s often used to initialize the package and control what is imported when the package is accessed.

Example:

# src/api_/__init__.py
from alpaca_api import AlpacaApi
from binance_api import BinanceApi
from bingx_api import BingXApi

__all__ = ['AlpacaApi', 'BinanceApi', 'BingXApi']

This __init__.py file allows you to import all API clients using a single import statement:

from api import AlpacaApi, BinanceApi, BingXApi

4. Organizing Tests

Organizing tests in a structure that mirrors your source code makes it easier to manage and run.

Example Test Structure:

tests/
│
├── __init__.py
├── test_api/
│   ├── __init__.py
│   ├── test_alpaca_api.py
│   ├── test_binance_api.py
│   └── test_bingx_api.py
│
└── test_utils/
    ├── __init__.py
    └── test_logger.py

This structure ensures that your tests are logically grouped, making it easier to maintain as the project grows.

6. Conclusion

Organizing your Python project hierarchy thoughtfully is essential for maintainability, scalability, and collaboration. By following these best practices and conventions, you can create a structure that is logical, easy to navigate, and “Pythonic.” A well-organized project is the foundation for efficient development and a successful codebase.