refactoring logs
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@ -16,6 +16,13 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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### Changed
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### Changed
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- Refactored data processing to be more modular and extensible.
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- Refactored data processing to be more modular and extensible.
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- Refactored dashboard into a modular structure with separated layouts, callbacks, and components.
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- Refactored dashboard into a modular structure with separated layouts, callbacks, and components.
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- Refactored common package for better organization:
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- Split aggregation.py into dedicated sub-package
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- Split indicators.py into dedicated sub-package
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- Improved validation.py modularity
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- Added safety limits to transformation package
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- Verified and documented data_types.py structure
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### Removed
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### Removed
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- Monolithic `app.py` in favor of a modular dashboard structure.
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- Monolithic `app.py` in favor of a modular dashboard structure.
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- Original monolithic common package files in favor of modular structure
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124
docs/decisions/ADR-002-common-package-refactor.md
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124
docs/decisions/ADR-002-common-package-refactor.md
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# ADR-002: Common Package Refactoring
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## Status
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Accepted and Implemented
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## Context
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The common package contained several large, monolithic files that were becoming difficult to maintain and extend. The files included:
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- aggregation.py
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- indicators.py
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- validation.py
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- transformation.py
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- data_types.py
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These files handled critical functionality but were growing in complexity and responsibility, making it harder to:
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- Understand and maintain individual components
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- Test specific functionality
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- Add new features without affecting existing code
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- Ensure proper separation of concerns
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## Decision
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We decided to refactor the common package into a more modular structure by:
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1. **Splitting Large Files into Sub-packages:**
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- Created `aggregation/` package with specialized modules
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- Created `indicators/` package with focused components
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- Maintained core data types in a single, well-structured file
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2. **Improving Validation:**
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- Enhanced modularity of validation system
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- Added clearer validation rules and messages
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- Maintained backward compatibility
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3. **Enhancing Transformation:**
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- Added safety limits system
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- Improved error handling
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- Better separation of transformation concerns
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4. **Preserving Data Types:**
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- Reviewed and verified data_types.py structure
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- Maintained as single file due to good organization
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- Documented existing patterns
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## Consequences
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### Positive
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- Better code organization and maintainability
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- Clearer separation of concerns
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- Easier to test individual components
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- More focused and cohesive modules
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- Better safety with new limits system
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- Improved documentation and examples
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- Easier to extend with new features
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### Negative
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- Slightly more complex import paths
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- Need to update existing documentation
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- Initial learning curve for new structure
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### Neutral
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- Need to maintain more files
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- More granular version control
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- Different organization pattern from original
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## Alternatives Considered
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### Keep Monolithic Structure
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Rejected because:
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- Growing complexity
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- Difficult maintenance
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- Hard to test
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- Poor separation of concerns
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### Complete Microservices Split
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Rejected because:
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- Too complex for current needs
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- Would introduce unnecessary overhead
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- Not justified by current scale
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### Hybrid Approach (Selected)
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Selected because:
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- Balances modularity and simplicity
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- Maintains good performance
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- Easy to understand and maintain
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- Allows for future growth
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## Implementation Notes
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### Phase 1: Aggregation and Indicators
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- Split into focused sub-packages
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- Added proper interfaces
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- Maintained backward compatibility
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- Added comprehensive tests
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### Phase 2: Validation and Transformation
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- Enhanced validation system
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- Added safety limits
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- Improved error handling
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- Updated documentation
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### Phase 3: Verification
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- Reviewed data types
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- Ran comprehensive tests
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- Updated documentation
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- Verified no regressions
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## Migration Guide
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### For Developers
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1. Update imports to use new package structure
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2. Review new safety limits in transformation
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3. Check validation error handling
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4. Update any custom extensions
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### For Maintainers
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1. Familiarize with new package structure
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2. Review new testing patterns
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3. Understand safety limit system
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4. Follow modular development pattern
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## References
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- Original task list: tasks/refactor-common-package.md
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- Documentation standards: docs/documentation.mdc
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- Test coverage reports
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- Code review feedback
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@ -53,14 +53,14 @@
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- [x] 4.6 Add documentation for the transformation module.
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- [x] 4.6 Add documentation for the transformation module.
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- [x] 4.7 Delete redundant transformation.py file.
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- [x] 4.7 Delete redundant transformation.py file.
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- [ ] 5.0 Update `data_types.py` with new types.
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- [x] 5.0 Update `data_types.py` with new types.
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- [ ] 5.1 Review and document all data types.
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- [x] 5.1 Review and document all data types.
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- [ ] 5.2 Add any missing type hints.
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- [x] 5.2 Add any missing type hints.
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- [ ] 5.3 Add validation for data types.
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- [x] 5.3 Add validation for data types.
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- [ ] 5.4 Run tests to verify data types still work as expected.
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- [x] 5.4 Run tests to verify data types still work as expected.
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- [ ] 6.0 Final verification and cleanup.
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- [ ] 6.0 Final verification and cleanup.
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- [x] 6.1 Run all tests to ensure no regressions.
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- [x] 6.1 Run all tests to ensure no regressions.
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- [x] 6.2 Update documentation to reflect new structure.
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- [x] 6.2 Update documentation to reflect new structure.
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- [ ] 6.3 Review and clean up any remaining TODOs.
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- [x] 6.3 Review and clean up any remaining TODOs.
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- [ ] 6.4 Create PR with changes.
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- [ ] 6.4 Create PR with changes.
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