Fix shadow observer lifecycle, learning and prediction correctness

custom_components/heating_mpc/weather_sources.py

@@ -44,6 +44,8 @@ def normalize(metric: str, raw: object, unit: str | None = None) -> float | None
         return None
     if not isfinite(value):
         return None
+    if unit is not None and not isinstance(unit, str):
+        return None
     unit = (unit or "").strip().lower().replace(" ", "")
     if metric in ("temperature", "feels_like"):
         if unit in ("°f", "f", "fahrenheit"):