- Introduced dynamic generation of parameter fields and callback handling for indicators, enhancing modularity and maintainability.
- Updated `config_utils.py` with new utility functions to load indicator templates and generate dynamic outputs and states for parameter fields.
- Refactored `indicators.py` to utilize these utilities, streamlining the callback logic and improving user experience by reducing hardcoded elements.
- Modified `indicator_modal.py` to create parameter fields dynamically based on JSON templates, eliminating the need for manual updates when adding new indicators.
- Added documentation outlining the new data-driven architecture for indicators, improving clarity and guidance for future development.
These changes significantly enhance the flexibility and scalability of the indicator system, aligning with project goals for maintainability and performance.
- Introduced `config_utils.py` to provide utility functions for loading and managing indicator templates, enhancing modularity and maintainability.
- Implemented functions to load templates, generate dropdown options, and retrieve parameter schemas, default parameters, and styling for various indicators.
- Updated the indicator modal to dynamically create parameter fields based on the loaded configurations, improving user experience and reducing redundancy.
- Refactored existing parameter field creation logic to utilize the new utility functions, streamlining the codebase and adhering to project standards for clarity and maintainability.
These changes significantly enhance the configuration management for indicators, aligning with project goals for modularity and performance.
