24b6a3feed
- 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.
65 lines
1.3 KiB
Python
65 lines
1.3 KiB
Python
"""
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Common data processing utilities for all exchanges.
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This package contains shared components for data validation, transformation,
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and aggregation that can be used across different exchange implementations.
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"""
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from .data_types import (
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StandardizedTrade,
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OHLCVCandle,
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MarketDataPoint,
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DataValidationResult
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)
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from .aggregation import (
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TimeframeBucket,
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RealTimeCandleProcessor,
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CandleProcessingConfig
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)
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from .transformation import (
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BaseDataTransformer,
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UnifiedDataTransformer,
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create_standardized_trade
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)
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from .validation import (
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BaseDataValidator,
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ValidationResult
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)
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from .indicators import (
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TechnicalIndicators,
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IndicatorResult,
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create_default_indicators_config,
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validate_indicator_config
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)
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__all__ = [
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# Data types
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'StandardizedTrade',
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'OHLCVCandle',
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'MarketDataPoint',
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'DataValidationResult',
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# Aggregation
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'TimeframeBucket',
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'RealTimeCandleProcessor',
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'CandleProcessingConfig',
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# Transformation
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'BaseDataTransformer',
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'UnifiedDataTransformer',
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'create_standardized_trade',
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# Validation
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'BaseDataValidator',
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'ValidationResult',
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# Technical Indicators
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'TechnicalIndicators',
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'IndicatorResult',
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'create_default_indicators_config',
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'validate_indicator_config'
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] |