Coding Quality
################

This page describes the coding quality standards and practices used in the thompson package.

Quality Assurance
==================

We value software quality as it leads to:
- Fewer defects and bugs
- Better security
- Improved performance
- Happier users
- More effective development

According to McConnell (2004), different testing methods find different percentages of defects:
- Unit testing: ~25% of defects
- Function testing: ~35% of defects
- Integration testing: ~45% of defects
- Code review: ~55-60% of defects

This demonstrates that a combination of these methods is essential for high-quality software development.

Development Practices
=======================

The thompson package is developed using several quality assurance techniques:

1. **Code Style**
   - PEP-8 compliance
   - Consistent formatting
   - Clear naming conventions
   - Comprehensive docstrings

2. **Code Complexity**
   - Low technical debt
   - Modular design
   - Clear function boundaries
   - Maintainable structure

3. **Documentation**
   - Detailed docstrings
   - API documentation
   - Usage examples
   - Tutorials and guides

4. **Testing**
   - Unit tests
   - Integration tests
   - Code coverage
   - Continuous integration

5. **Code Review**
   - Peer review process
   - Automated checks
   - Style enforcement
   - Quality metrics

Project Structure
===================

The package follows a standard Python project structure:

.. code-block:: bash

    thompson/
    ├── .editorconfig          # Editor configuration
    ├── .gitignore            # Git ignore rules
    ├── .pre-commit-config.yml # Pre-commit hooks
    ├── .prospector.yml       # Code quality checks
    ├── CHANGELOG.rst         # Version history
    ├── docs/                 # Documentation
    │   ├── conf.py          # Sphinx configuration
    │   ├── index.rst        # Main documentation
    │   └── ...              # Other docs
    ├── LICENSE              # License file
    ├── MANIFEST.in          # Package files
    ├── NOTICE              # Legal notices
    ├── thompson/           # Source code
    │   ├── __init__.py    # Package initialization
    │   ├── __version__.py # Version information
    │   └── thompson.py    # Main implementation
    ├── README.md          # Project overview
    ├── requirements.txt   # Dependencies
    ├── setup.cfg         # Package configuration
    ├── setup.py          # Installation script
    └── tests/            # Test suite
        ├── __init__.py  # Test initialization
        └── test_thompson.py # Unit tests

Code Style
==========

The package follows PEP-8 standards for Python code style:
- Maximum line length: 79 characters
- Indentation: 4 spaces
- Naming conventions

Each public function includes a comprehensive docstring following numpy standards:
- Description
- Parameters
- Returns
- Examples
- Notes

Complexity Management
======================

We maintain low technical debt through:
- Modular code organization
- Clear function responsibilities
- Comprehensive documentation
- Regular code reviews
- Automated quality checks

Benefits of this approach:
- Higher code quality
- Easier maintenance
- Fewer bugs
- Better security
- Faster development

Unit Testing
=============

The package includes comprehensive unit tests that verify:
- Input validation
- Output correctness
- Parameter handling
- Edge cases
- Performance characteristics

Tests are implemented using Python's unittest framework and cover:
- Thompson Sampling algorithm
- UCB algorithm
- Randomized sampling
- Plotting functionality
- Data loading and processing

Continuous Integration
=======================

The package uses continuous integration to ensure quality:
- Automated testing
- Code coverage reporting
- Style checking
- Documentation building
- Dependency management

This helps maintain consistent quality across all development.

.. include:: add_bottom.add