- Added `realtime_execution.py` for real-time strategy execution, enabling live signal generation and integration with the dashboard's chart refresh cycle.
- Introduced `data_integration.py` to manage market data orchestration, caching, and technical indicator calculations for strategy signal generation.
- Implemented `validation.py` for comprehensive validation and quality assessment of strategy-generated signals, ensuring reliability and consistency.
- Developed `batch_processing.py` to facilitate efficient backtesting of multiple strategies across large datasets with memory management and performance optimization.
- Updated `__init__.py` files to include new modules and ensure proper exports, enhancing modularity and maintainability.
- Enhanced unit tests for the new features, ensuring robust functionality and adherence to project standards.
These changes establish a solid foundation for real-time strategy execution and data integration, aligning with project goals for modularity, performance, and maintainability.
- Introduced `config_utils.py` for loading and managing strategy configurations, including functions for loading templates, generating dropdown options, and retrieving parameter schemas and default values.
- Added JSON templates for EMA Crossover, MACD, and RSI strategies, defining their parameters and validation rules to enhance modularity and maintainability.
- Implemented `StrategyManager` in `manager.py` for managing user-defined strategies with file-based storage, supporting easy sharing and portability.
- Updated `__init__.py` to include new components and ensure proper module exports.
- Enhanced error handling and logging practices across the new modules for improved reliability.
These changes establish a robust foundation for strategy management and configuration, aligning with project goals for modularity, performance, and maintainability.
- Introduced a new `strategies` package containing the core structure for trading strategies, including `BaseStrategy`, `StrategyFactory`, and various strategy implementations (EMA, RSI, MACD).
- Added utility functions for signal detection and validation in `strategies/utils.py`, enhancing modularity and maintainability.
- Updated `pyproject.toml` to include the new `strategies` package in the build configuration.
- Implemented comprehensive unit tests for the strategy foundation components, ensuring reliability and adherence to project standards.
These changes establish a solid foundation for the strategy engine, aligning with project goals for modularity, performance, and maintainability.
