- Introduced `indicators.py` containing implementations for SMA, EMA, RSI, MACD, and Bollinger Bands, optimized for handling sparse OHLCV data.
- Added `IndicatorResult` dataclass to encapsulate results of indicator calculations.
- Implemented methods for calculating multiple indicators efficiently with JSON configuration support and validation.
- Updated `__init__.py` to include new indicators in the module's exports.
- Enhanced documentation to cover the new technical indicators module, including usage examples and integration details.
- Added comprehensive unit tests to ensure accuracy and robustness of the indicators module.
- Introduced a modular architecture for data processing, including common utilities for validation, transformation, and aggregation.
- Implemented `StandardizedTrade`, `OHLCVCandle`, and `TimeframeBucket` classes for unified data handling across exchanges.
- Developed `OKXDataProcessor` for OKX-specific data validation and processing, leveraging the new common framework.
- Enhanced `OKXCollector` to utilize the common data processing utilities, improving modularity and maintainability.
- Updated documentation to reflect the new architecture and provide guidance on the data processing framework.
- Created comprehensive tests for the new data processing components to ensure reliability and functionality.
