python project folder structure. the project packs multiple folders with libraries shared with other projects. also it has some bash scripts that will be shared with other projects as well as some bash scripts of it's own, not shared.

Creating a well-structured Python project is crucial for maintainability, scalability, and ease of collaboration, especially when your project involves shared libraries and bash scripts. Below is a detailed guide to organizing a Python project folder structure that accommodates your requirements.

Overview of a Python Project Structure

A Python project typically consists of several directories and files that help organize modules, libraries, and scripts effectively. Given your specific needs for shared libraries and bash scripts, the following structure is a recommended approach.

Recommended Folder Structure

my_project/
├── shared_libs/                # Shared libraries with other projects
│   ├── __init__.py
│   ├── library1/
│   │   ├── __init__.py
│   │   └── module1.py
│   └── library2/
│       ├── __init__.py
│       └── module1.py
├── own_libs/                   # Project-specific libraries
│   ├── __init__.py
│   └── custom_module.py
├── scripts/                    # Folder for bash scripts
│   ├── shared/                 # Bash scripts shared with other projects
│   │   ├── shared_script1.sh
│   │   └── shared_script2.sh
│   └── own/                    # Bash scripts specific to this project
│       ├── own_script1.sh
│       └── own_script2.sh
├── tests/                      # Unit tests for your project
│   ├── test_module1.py
│   └── test_custom_module.py
├── requirements.txt            # Project dependencies
├── README.md                   # Project documentation
└── setup.py                    # Setup script for package installation

Breakdown of the Structure

Shared Libraries (shared_libs)

• Purpose: This directory holds libraries that can be shared across multiple projects.
• Subdirectories: Each library can have its own subdirectory containing related modules; include an __init__.py file to make the folder a package.

Own Libraries (own_libs)

• Purpose: This folder is for libraries and modules specific to this project, helping to isolate project-specific code.
• Contents: Typically contains one or more Python modules.

Bash Scripts (scripts)

• Shared Scripts: Place any bash scripts that will be shared with other projects in the shared subdirectory. This helps maintain clarity and accessibility.
• Project-specific Scripts: The own subdirectory is for scripts that serve specific purposes within this project.

Tests (tests)

• Purpose: It’s essential to include a separate directory for unit tests. This helps in maintaining code quality as you develop new features.
• Naming: Use a consistent naming convention (e.g., test_*.py) for your test files to facilitate running tests automatically.

Metadata and Configuration Files

• requirements.txt: Lists external libraries required by your project. Using a file for dependencies makes it easier for others (or yourself in the future) to set up the environment.
• README.md: Provides documentation about the project, including installation instructions, usage, and examples.
• setup.py: This is used for packaging and installing the project as a Python package.

Additional Tips for Implementation

• Version Control: Use a version control system like Git to manage changes and collaborate with others. Include a .gitignore file to exclude unnecessary files and directories (e.g., __pycache__, virtual environments).
• Testing Framework: Consider using a testing framework like unittest or pytest to structure your tests effectively.
• Documentation: Aside from the README.md, consider using tools like Sphinx for generating documentation from docstrings in your code.

Conclusion

Organizing your Python project with clarity and modular structure enhances code readability and maintainability. By following the outlined folder structure, you ensure that your shared libraries and bash scripts are easy to manage and utilize across various projects. Proper organization not only aids in current development but also streamlines future collaboration and integration efforts.

For comprehensive guidelines on structuring Python projects, you may refer to articles and resources from Medium and Hitchhiker's Guide to Python.