Add daily derived data pipeline

pipeline/alpha/compute.py

@@ -15,7 +15,11 @@ import pandas as pd
 
 from pipeline.alpha.registry import get_alpha
 from pipeline.common.schema import ALPHA_COLUMNS
-from pipeline.features.compute import FEATURE_KEY_COLUMNS, read_feature_frames, validate_feature_frame
+from pipeline.derived.compute import (
+    DERIVED_KEY_COLUMNS,
+    read_derived_frames,
+    validate_derived_frame,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -40,15 +44,15 @@ def join_feature_frames(
     data: pd.DataFrame,
     feature_frames: Iterable[pd.DataFrame],
 ) -> pd.DataFrame:
-    """Left-join validated daily feature frames onto long daily data."""
+    """Left-join validated daily derived/feature frames onto long daily data."""
     out = data.copy()
     out["date"] = pd.to_datetime(out["date"])
     existing = set(out.columns)
     joined_cols: list[str] = []
 
     for frame in feature_frames:
-        features = validate_feature_frame(frame)
-        feature_cols = [col for col in features.columns if col not in FEATURE_KEY_COLUMNS]
+        features = validate_derived_frame(frame)
+        feature_cols = [col for col in features.columns if col not in DERIVED_KEY_COLUMNS]
         overlap = sorted(existing.intersection(feature_cols))
         if overlap:
             raise ValueError(
@@ -56,7 +60,7 @@ def join_feature_frames(
             )
         out = out.merge(
             features,
-            on=FEATURE_KEY_COLUMNS,
+            on=DERIVED_KEY_COLUMNS,
             how="left",
             validate="many_to_one",
         )
@@ -171,7 +175,7 @@ def compute_alpha(
     """
     feature_inputs: list[pd.DataFrame] = []
     if feature_paths:
-        feature_inputs.extend(read_feature_frames(feature_paths))
+        feature_inputs.extend(read_derived_frames(feature_paths))
     if feature_frames:
         feature_inputs.extend(feature_frames)
     if feature_inputs: