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A comprehensive example of a well-structured Python project that demonstrates best practices for organization, packaging, and library management.

my_project/
│
├── pyproject.toml
├── README.md
├── LICENSE
│
├── src/
│   └── my_project/
│       ├── __init__.py
│       ├── core/
│       │   ├── __init__.py
│       │   ├── data_processor.py
│       │   └── helpers.py
│       │
│       ├── models/
│       │   ├── __init__.py
│       │   ├── user_model.py
│       │   └── analytics_model.py
│       │
│       └── utils/
│           ├── __init__.py
│           ├── logging.py
│           └── config.py
│
├── tests/
│   ├── __init__.py
│   ├── test_data_processor.py
│   ├── test_user_model.py
│   └── test_analytics.py
│
├── scripts/
│   ├── run_analysis.py
│   └── data_migration.py
│
├── notebooks/
│   └── data_exploration.ipynb
│
├── docs/
│   ├── index.md
│   └── usage.md
│
├── requirements.txt
└── setup.py

Key components of this project structure:

  1. Project Root
  • pyproject.toml: Modern Python project configuration (used with tools like Poetry)
  • README.md: Project documentation and setup instructions
  • LICENSE: Project licensing information
  • requirements.txt: Project dependencies
  • setup.py: Package installation and distribution configuration
  1. src/ Directory
  • Contains the main project package
  • Prevents naming conflicts and improves import structure
  • Follows the "src layout" recommended by Python packaging experts
  1. Project Modules
  • core/: Core functionality and business logic
  • models/: Data models and core objects
  • utils/: Utility functions, configuration, logging
  1. Additional Directories
  • tests/: Unit and integration tests
  • scripts/: Standalone scripts for specific tasks
  • notebooks/: Jupyter notebooks for data exploration
  • docs/: Project documentation

Some example content to illustrate the structure:

[build-system]
requires = ["setuptools>=61.0", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "my_project"
version = "0.1.0"
description = "A sample Python project demonstrating best practices"
authors = [
    {name = "Your Name", email = "[email protected]"}
]
dependencies = [
    "pandas>=2.0.0",
    "numpy>=1.22.0",
    "requests>=2.28.0"
]

[project.optional-dependencies]
dev = [
    "pytest>=7.0.0",
    "mypy>=1.0.0",
    "black>=23.0.0"
]

[tool.pytest.ini_options]
testpaths = ["tests"]



Best Practices Highlighted:
1. Modular design with clear separation of concerns
2. Type hints for better code readability
3. Docstrings for method documentation
4. Use of modern Python packaging tools
5. Separate test and source directories
6. Optional development dependencies
7. Configurable project setup

Recommended Tools:
- Poetry (dependency management)
- Black (code formatting)
- Pytest (testing)
- Mypy (type checking)

Recommendations for Managing the Project:
- Use virtual environments
- Implement continuous integration
- Regularly update dependencies
- Write comprehensive tests
- Maintain clear documentation

Would you like me to elaborate on any part of the project structure or explain any specific aspects in more detail?