1i LSrSSKJr SSKJr SSKJr SSKJr "SS5r g) zFeature engineering for ML model inputs. Extracts structured feature vectors from raw racing data to feed into ensemble or standalone ML models for win/place prediction. ) annotations)date)Any)Sessionc^\rSrSrSrS SjrS SjrS SjrS SSjjrSSjr Sr g )FeatureEngineeringzFeature extraction and dataset construction for racing ML models. Features are built from Elo ratings, form metrics, race conditions, and historical performance statistics. cXlg)z[Initialize with a database session. Args: session: Database session for loading data. N_session)selfsessions 9/root/tipsharks/tipsharks-elo-api/packages/ml/features.py__init__FeatureEngineering.__init__s  c[e)atExtract feature vector for a single horse. Features include: - Current Elo rating and RD - Recent form (avg placing, win rate, place rate) - Distance performance stats - Barrier/handicap statistics - Course/venue familiarity - Days since last start - Driver/trainer combination stats Args: horse_id: The horse entity ID. Returns: Dict of feature name -> value. NotImplementedError)r horse_ids rextract_horse_features)FeatureEngineering.extract_horse_featuress $"!rc[e)aExtract aggregate features for a race. Features include: - Race distance, start type, gait - Track condition, weather - Field size - Aggregate ratings of all starters - Race class / grade indicators Args: race_id: The race ID. Returns: Dict of feature name -> value. r)r race_ids rextract_race_features(FeatureEngineering.extract_race_features2s "!rc[e)aeBuild a complete training dataset for a date range. For each starter in completed races within the range, extract pre-race features and (optionally) the actual outcome as target. Args: date_from: Start date (inclusive). date_to: End date (inclusive). include_target: If True, include actual placing/probability targets in the returned data. Returns: Tuple of (features_list, targets_list_or_None). Each element in features_list is a dict of feature name -> value. Each element in targets_list is a dict with 'starter_id', 'placing', and optionally 'win_frac', 'place_frac'. r)r date_fromdate_toinclude_targets rbuild_training_dataset)FeatureEngineering.build_training_datasetDs ."!rc[e)znReturn ordered list of all feature names produced by this engine. Returns: List of feature name strings. r)r s r feature_names FeatureEngineering.feature_names]s "!rr N)rrreturnNone)rintr&dict[str, Any])rr(r&r))T)rrrrr boolr&z8tuple[list[dict[str, Any]], list[dict[str, Any]] | None])r&z list[str]) __name__ __module__ __qualname____firstlineno____doc__rrrr!r$__static_attributes__rrrrsL  "(", $ """ " B "2"rrN) r/ __future__rdatetimertypingrsqlalchemy.ormrrr1rrr6s$ #"T"T"r