python project folder structure. the project packs multiple folders with libraries shared with other projects

When organizing a Python project involving multiple folders with shared libraries, it's important to adhere to best practices to enhance collaboration, maintainability, and scalability. Below, we explore an optimal folder structure along with essential best practices for Python projects that share libraries across different applications.

Importance of a Well-Structured Project

A well-defined project structure increases code readability, encourages reuse, and optimizes collaboration among team members. By following these guidelines, you create a robust framework for your project, making it easier to integrate and share libraries effectively with other projects.

Recommended Project Folder Structure

The following structure serves as a guideline for organizing your Python project that includes shared libraries:

project_root/
│
├── shared_libs/                     # Directory for shared libraries
│   ├── __init__.py                  # Initializes the package
│   ├── library_one/                 
│   │   ├── __init__.py
│   │   └── module_a.py
│   └── library_two/
│       ├── __init__.py
│       └── module_b.py
│
├── services/                        # Directory for different service modules
│   ├── service_one/
│   │   ├── __init__.py
│   │   └── main.py
│   └── service_two/
│       ├── __init__.py
│       └── main.py
│
├── tests/                           # Directory for test cases
│   ├── test_library_one.py
│   ├── test_library_two.py
│   ├── test_service_one.py
│   └── test_service_two.py
│
├── scripts/                         # Optional: shells or automation scripts
│   └── deploy.py
│
├── requirements.txt                # Project dependencies
├── setup.py                        # Package installation
└── README.md                       # Project documentation

Key Directories Explained

1. shared_libs/

This folder contains libraries that are intended to be used across multiple services or applications. Each library can be structured further into its own subdirectory, allowing for modular development.

2. services/

Each service folder encapsulates code that implements specific functionalities or business logic. This organization allows developers to work independently on different services without creating conflicts or dependencies between them.

3. tests/

A dedicated testing directory ensures that all code is verified and validated. Each module should have corresponding test files to ensure functionality and reliability. Utilizing frameworks like pytest or unittest is common practice in this directory.

4. scripts/

This optional folder can contain utility scripts for deployment, data migration, or configuration tasks. Keeping these scripts separate from application logic promotes clarity and organization.

5. requirements.txt

A text file listing all dependencies required for the project allows for consistent environment setup across different development machines or production environments.

6. setup.py

This file defines the package's metadata and dependencies which facilitates installation and distribution, making it easier to share your libraries with other projects or teams.

Best Practices for Shared Libraries

1. Modular Code: Keep each library modular to enhance reusability. Use clear and consistent naming conventions for modules and functions within each library.

2. Dependency Management: Utilize virtual environments and tools like pip to manage dependencies effectively. Ensure that the requirements.txt file is always up to date with the current dependencies for smooth setups.

3. Documentation: Maintaining a README.md file with clear instructions on how to set up and use the libraries will significantly benefit new developers or external teams looking to integrate with your project.

4. Version Control: Store the project in a version-controlled system like Git. This practice allows tracking changes, collaboration, and branching for feature development or bug fixes.

5. Consistent Testing: Incorporate continuous integration practices that run tests automatically when changes are made to the codebase. This approach ensures that your project remains stable as it evolves.

Conclusion

A well-organized Python project with a structured folder layout for shared libraries not only facilitates better collaboration but also promotes good software engineering practices. Following the guidelines provided here can help you establish a foundation that supports both current needs and future growth. Leveraging shared libraries effectively will also lead to a more efficient codebase and streamline overall development processes.

By adhering to these best practices for Python project organization, you can ensure your projects are manageable, scalable, and conducive to teamwork. For more details on these practices, consider exploring resources from Dagster and Medium.