Changelog
=========

All notable changes to binlearn will be documented in this file.

The format is based on `Keep a Changelog <https://keepachangelog.com/en/1.0.0/>`_,
and this project adheres to `Semantic Versioning <https://semver.org/spec/v2.0.0.html>`_.

[Unreleased]
------------

Added
~~~~~
- Comprehensive ReadTheDocs documentation with tutorials and examples
- Complete API reference documentation
- User guide with best practices and performance tips

Changed
~~~~~~~
- Improved documentation structure and organization

[1.0.0] - 2024-XX-XX
---------------------

Added
~~~~~

**New Binning Methods:**
- ``SingletonBinning`` - Creates one bin per unique numeric value
- ``SupervisedBinning`` - Decision tree-based supervised binning
- ``EqualFrequencyBinning`` - Quantile-based equal-frequency binning
- ``KMeansBinning`` - K-means clustering-based discretization
- ``EqualWidthMinimumWeightBinning`` - Weight-constrained equal-width binning
- ``ManualIntervalBinning`` - Custom interval boundary specification
- ``ManualFlexibleBinning`` - Mixed interval and singleton bin definitions

**Framework Integration:**
- Full scikit-learn compatibility with transformer interface
- Native pandas DataFrame support with column name preservation
- Polars DataFrame support (optional dependency)
- NumPy array processing with optimized performance

**Advanced Features:**
- Global configuration system for consistent behavior
- Comprehensive error handling with helpful messages
- Type safety with 100% mypy compliance
- Flexible binning with guidance columns support
- Custom bin representatives and edge specifications

**Development Quality:**
- 100% test coverage with 841+ comprehensive tests
- 100% ruff compliance for code quality
- Complete type annotations for better IDE support
- Extensive documentation with examples

**Tools and Utilities:**
- ``BinningFeatureSelector`` for feature selection integration
- ``BinningPipeline`` for streamlined ML workflows
- ``make_binning_scorer`` for custom scoring functions
- Integration utilities for ML workflows

Security
~~~~~~~~
- Input validation to prevent malicious data processing
- Robust error handling to prevent crashes
- Memory-safe operations for large datasets

[0.9.0] - 2024-XX-XX
---------------------

Added
~~~~~
- Initial beta release
- Basic equal-width binning functionality
- Sklearn compatibility layer
- Pandas DataFrame support

Changed
~~~~~~~
- Refactored codebase for better modularity
- Improved error messages

Fixed
~~~~~
- Memory leaks in large dataset processing
- Edge cases with single-value datasets

[0.8.0] - 2024-XX-XX
---------------------

Added
~~~~~
- Prototype supervised binning implementation
- Basic configuration management
- Initial test suite

[0.7.0] - 2024-XX-XX
---------------------

Added
~~~~~
- Core binning infrastructure
- Base classes for extensibility
- Initial equal-width implementation

[0.6.0] - 2024-XX-XX
---------------------

Added
~~~~~
- Project initialization
- Basic package structure
- Development environment setup