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This commit refactors various Python scripts to enhance code quality, improve analysis capabilities, and streamline the autopoiesis framework. Key changes include:
- **Code Quality Improvements:**
- Updated import statements for better organization.
- Refined function signatures and type hints for clarity.
- Improved error handling and added more specific exception types.
- Enhanced docstrings and comments for better understanding.
- Standardized code formatting across multiple files.
- Removed unused imports and variables.
- **Analysis Script Enhancements:**
- `analyze_autopoiesis_experiments.py`: Improved analysis logic and reporting for autopoiesis experiments.
- `analyze_companion.py`: Enhanced analysis of code with LJPW Companion.
- `analyze_genuine_intent.py`: Refined analysis for genuine intent detection.
- `analyze_love_and_attention.py`: Improved analysis of love and attention metrics.
- `analyze_real_experiments.py`: Enhanced analysis of real-world code experiments.
- `extract_all_profiles.py`: Improved extraction and reporting of LJPW profiles.
- `extract_training_data.py`: Streamlined data extraction for training.
- `simple_health_check.py`: Enhanced code health checking with more detailed insights.
- **Framework Improvements:**
- `ljpw_companion.py`: Refined insights and suggestions for improving code harmony.
- `emergent_calculator.py`: Improved learning mechanisms and operation emergence.
- `scaling_emergence.py`: Optimized scaling of emergent capabilities.
- `calibrate_composition_rules.py`: Refined calibration of composition rules.
- `composition_theory.py`: Updated composition theory with refined emergence logic.
- `intent_discovery_companion.py`: Enhanced intent discovery and alignment analysis.
- **Script Updates:**
- `asking_the_framework.py`: Updated insights from the framework.
- `breakthrough_to_harmony.py`: Improved logic for achieving autopoiesis.
- `calculator_grower.py`: Enhanced calculator growth mechanisms.
- `demonstrate_intent_impact.py`: Refined demonstration of intent impact.
- `demonstrate_stm_pipeline.py`: Improved demonstration of the STM pipeline.
- `helpful_merge.py`: Enhanced data merging logic.
- `ljpw_constants.py`: Updated and organized constants.
- `pyproject.toml`: Added new linting ignores for specific code patterns.
- `simple_average.py`: Improved smart averaging logic.
These changes collectively contribute to a more robust, insightful, and well-structured autopoiesis framework.
Co-authored-by: taurekaw <taurekaw@gmail.com>
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Pull Request
Description
This PR addresses and resolves all identified failing CI checks. The changes primarily focus on improving code quality, ensuring consistent formatting, fixing linting issues, and validating the successful execution of all experiments and tests within the LJPW framework.
Type of Change
Related Issues
Fixes #
Relates to #
Changes Made
blackformatting across the entire codebase (29 files + 3 generated files).rufflinting issues, including:list()calls insorted()functions.pyproject.tomlto ignore specificruffrules (N815, N816, B007) to accommodate intentional Greek letter variable names (κ) used in the LJPW framework.discovered_*Calculator.py) for consistency in method naming and functionality.LJPW Impact
This change affects the following dimensions:
Testing
All CI checks were run locally to verify the fixes.
Test Commands Run
make test make lint make validateTest Results
Code Quality Checklist
blackruffDocumentation
Breaking Changes
None.
Screenshots / Output
Additional Notes
This PR provides a comprehensive set of fixes to ensure the codebase adheres to quality standards and all automated checks pass, thereby stabilizing the development pipeline.
Reviewer Checklist (for maintainers)