- Enhanced the `UserIndicator` class to include an optional `timeframe` attribute for custom indicator timeframes.
- Updated the `get_indicator_data` method in `MarketDataIntegrator` to fetch and calculate indicators based on the specified timeframe, ensuring proper data alignment and handling.
- Modified the `ChartBuilder` to pass the correct DataFrame for plotting indicators with different timeframes.
- Added UI elements in the indicator modal for selecting timeframes, improving user experience.
- Updated relevant JSON templates to include the new `timeframe` field for all indicators.
- Refactored the `prepare_chart_data` function to ensure it returns a DataFrame with a `DatetimeIndex` for consistent calculations.
This commit enhances the flexibility and usability of the indicator system, allowing users to analyze data across various timeframes.
- Updated `ChartBuilder` to support dynamic indicator integration, allowing users to specify overlay and subplot indicators for enhanced chart analysis.
- Implemented a new `get_indicator_data` method in `MarketDataIntegrator` for fetching indicator data based on user configurations.
- Added `create_export_controls` in `chart_controls.py` to facilitate data export options (CSV/JSON) for user analysis.
- Enhanced error handling and logging throughout the chart and data analysis processes to improve reliability and user feedback.
- Updated documentation to reflect new features and usage guidelines for indicator management and data export functionalities.
- Introduced a comprehensive user indicator management system in `components/charts/indicator_manager.py`, allowing users to create, edit, and manage custom indicators with JSON persistence.
- Added new default indicators in `components/charts/indicator_defaults.py` to provide users with immediate options for technical analysis.
- Enhanced the chart rendering capabilities by implementing the `create_chart_with_indicators` function in `components/charts/builder.py`, supporting both overlay and subplot indicators.
- Updated the main application layout in `app.py` to include a modal for adding and editing indicators, improving user interaction.
- Enhanced documentation to cover the new indicator system, including a quick guide for adding new indicators and detailed usage examples.
- Added unit tests to ensure the reliability and functionality of the new indicator management features.
Implement modular chart layers and error handling for Crypto Trading Bot Dashboard
- Introduced a comprehensive chart layer system in `components/charts/layers/` to support various technical indicators and subplots.
- Added base layer components including `BaseLayer`, `CandlestickLayer`, and `VolumeLayer` for flexible chart rendering.
- Implemented overlay indicators such as `SMALayer`, `EMALayer`, and `BollingerBandsLayer` with robust error handling.
- Created subplot layers for indicators like `RSILayer` and `MACDLayer`, enhancing visualization capabilities.
- Developed a `MarketDataIntegrator` for seamless data fetching and validation, improving data quality assurance.
- Enhanced error handling utilities in `components/charts/error_handling.py` to manage insufficient data scenarios effectively.
- Updated documentation to reflect the new chart layer architecture and usage guidelines.
- Added unit tests for all chart layer components to ensure functionality and reliability.
- Suppressed SQLAlchemy logging in `app.py` and `main.py` to reduce console verbosity.
- Introduced a new modular chart system in `components/charts/` with a `ChartBuilder` class for flexible chart creation.
- Added utility functions for data processing and validation in `components/charts/utils.py`.
- Implemented indicator definitions and configurations in `components/charts/config/indicator_defs.py`.
- Created a comprehensive documentation structure for the new chart system, ensuring clarity and maintainability.
- Added unit tests for the `ChartBuilder` class to verify functionality and robustness.
- Updated existing components to integrate with the new chart system, enhancing overall architecture and user experience.
