pyalloq-features
pyalloq-features provides feature engineering transformers, TA-Lib indicator integration, scaling utilities, and feature pipeline orchestration for PyAlloq.
Key Modules
BaseFeatureTransformer: Abstract base class for all feature transformation modules operating onMarketData.TechnicalIndicator: Applies TA-Lib technical indicators (e.g.,SMA,RSI,MACD,ATR,BBANDS) across asset columns of a 2D DataFrame and appends resulting features toMarketData.features.FeaturePipeline: Sequential feature pipeline builder for chaining feature transformers.scalers: Cross-sectional and time-series feature normalization and standardization utilities.
Quick Example
from pyalloq_features.transformers.technical import TechnicalIndicator
from pyalloq_features.core.pipeline import FeaturePipeline
# Define feature engineering pipeline
pipeline = FeaturePipeline()
pipeline.add(TechnicalIndicator(indicator="RSI", timeperiod=14))
pipeline.add(TechnicalIndicator(indicator="SMA", timeperiod=50))
# Apply transformations directly to MarketData
# updated_data = pipeline.run(market_data)
1 maintainer
Metadata
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Release files for pyalloq-features 0.1.22
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