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Contributing to Databricks Calendar Dimension

Thank you for your interest in contributing to this project! This document provides guidelines and information for contributors.

How to Contribute

Reporting Bugs

Before creating a bug report, please check existing issues to avoid duplicates. When creating a bug report, include:

  • A clear, descriptive title
  • Steps to reproduce the issue
  • Expected behavior vs actual behavior
  • Your environment (Python version, Databricks runtime version, etc.)
  • Any relevant logs or error messages

Suggesting Enhancements

Enhancement suggestions are welcome! Please include:

  • A clear description of the enhancement
  • The motivation and use case
  • Any potential implementation approaches

Pull Requests

  1. Fork the repository and create your branch from main
  2. Install dependencies: 
    pip install -r requirements.txt
  3. Make your changes following the coding standards below
  4. Add tests for any new functionality
  5. Run the test suite: 
    pytest tests/ -v
  6. Format your code: 
    black src/ tests/
flake8 src/ tests/
  7. Commit your changes with a clear commit message
  8. Push to your fork and submit a pull request

Coding Standards

Python Style

  • Follow PEP 8 style guidelines
  • Use Black for code formatting
  • Use type hints where appropriate
  • Maximum line length: 88 characters (Black default)

Code Quality

  • Write clear, self-documenting code
  • Add docstrings to functions and classes
  • Keep functions focused and concise
  • Handle errors gracefully

Testing

  • Write tests for new functionality
  • Maintain or improve code coverage
  • Tests should be deterministic and not depend on external services
  • Use descriptive test names

Commit Messages

  • Use clear, descriptive commit messages
  • Start with a verb in present tense (e.g., "Add", "Fix", "Update")
  • Reference issues when applicable (e.g., "Fix #123")

Development Setup

  1. Clone your fork:

    git clone https://github.com/YOUR_USERNAME/Calendar-API.git
cd Calendar-API

  2. Create a virtual environment:

    python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

  3. Install dependencies:

    pip install -r requirements.txt

  4. Run tests to verify setup:

    pytest tests/ -v

Project Structure

Calendar-API/
├── src/                    # Source code
│   ├── generate_dim_calendar.py  # Main calendar generation
│   └── utils/              # Utility functions
├── tests/                  # Test suite
├── sql/                    # SQL scripts
├── notebooks/              # Databricks notebooks
├── docs/                   # Documentation
└── config/                 # Configuration files

Questions?

If you have questions about contributing, feel free to open an issue for discussion.

License

By contributing, you agree that your contributions will be licensed under the MIT License.