All notable changes to the USDA FDC Python Client will be documented in this file.
- Added comprehensive examples documentation in docs/user/examples.rst
- Added meal planning example (09_meal_planning.py) for creating and analyzing meal plans
- Added visualization example (10_visualization.py) for creating interactive charts
- Added breakfast_dri_chart.json sample data for visualization examples
- Added examples/data directory for sample data files
- Renamed example scripts for better organization:
- 06_meal_planning.py → 09_meal_planning.py
- 07_visualization.py → 10_visualization.py
- Updated examples/README.md with descriptions of all example scripts
- Fixed attribute reference in nutrient analysis example (display_name → name)
- Improved error handling in visualization module
- Fixed example script errors in nutrient analysis examples
- Fixed DRI chart visualization to properly scale percentage values
- Corrected attribute reference from display_name to name in Nutrient class usage
- Improved error handling in visualization module
- Added breakfast_dri_chart.json for sample visualization data
- Implemented comprehensive recipe analysis functionality
- Added ingredient parsing and nutritional calculation for recipes
- Created visualization tools for nutrient data with HTML reports
- Added RELEASE.md with release process instructions
- Updated documentation with new features and examples
- Renamed command-line tool from fdc-analyze to fdc-nat (Nutrient Analysis Tool)
- Updated package configuration in both setup.py and pyproject.toml
- Fixed version update script to properly handle all version references
- Fixed dotenv loading in client module
- Added comprehensive CHANGELOG.md file
- Added more detailed examples documentation
- Improved error handling in recipe analysis
- Fixed version_update.py script to properly update all version references
- Fixed Python version handling in pyproject.toml
- Updated documentation links and references
- Added 8 comprehensive example scripts demonstrating library functionality
- Created basic examples for searching and retrieving food data
- Added nutrient analysis examples for foods and recipes
- Implemented advanced examples for meal planning and visualization
- Added analyze_version.py example for CLI usage
- Updated documentation with detailed example explanations
- Fixed version_update.py to prevent modifying Python version in pyproject.toml
- Updated README with example information
- Implemented comprehensive nutrient analysis module
- Added dietary reference intake (DRI) data and comparisons
- Created recipe analysis with ingredient parsing
- Added visualization tools for nutrient data
- Implemented command-line interface for nutrient analysis (fdc-analyze)
- Added documentation for nutrient analysis features
- Completed Django integration with admin interface
- Implemented Django admin views for food data
- Added custom filters and search functionality
- Created background tasks for cache warming/refreshing
- Implemented migration scripts for database setup
- Added views and URLs for food data display
- Updated documentation with Django integration details
- Created comprehensive test suite
- Implemented unit tests for all components
- Added integration tests for API interactions
- Created Django-specific tests for models and cache
- Added detailed test fixtures and utilities
- Enhanced documentation with testing instructions
- Added VS Code configuration for development and testing
- Fixed documentation for correct GitHub URL
- Implemented command-line interface (CLI)
- Added comprehensive documentation
- Created user guide and API reference
- Added examples and tutorials
- Implemented error handling and logging
- Initial implementation of USDA FDC Python library
- Created base client class with authentication handling
- Implemented rate limiting and error handling
- Added support for all FDC API endpoints
- Created data models for all FDC data types
- Implemented search functionality with filtering
- Added batch operations for efficient API usage