first_commit

2026-04-25 20:35:25 +02:00
commit 9d15860f0b
22 changed files with 2254 additions and 0 deletions
@@ -0,0 +1,63 @@
+from __future__ import annotations
+
+from datetime import datetime, timezone
+
+from gibil.classes.models import Observation, ObservationQuality, Snapshot
+
+
+class SnapshotBuilder:
+    """Builds Gibil's decision input from the latest observations."""
+
+    def build(self, observations: list[Observation]) -> Snapshot:
+        latest = self._latest_by_metric(observations)
+
+        return Snapshot(
+            created_at=datetime.now(timezone.utc),
+            solar_power_w=self._number(latest, "solar_power_w"),
+            home_power_w=self._number(latest, "home_power_w"),
+            battery_soc_pct=self._number(latest, "battery_soc_pct"),
+            grid_import_w=self._number(latest, "grid_import_w"),
+            grid_export_w=self._number(latest, "grid_export_w"),
+            cheap_window_active=self._boolean(latest, "cheap_window_active"),
+            input_quality={
+                metric: observation.quality for metric, observation in latest.items()
+            },
+        )
+
+    def _latest_by_metric(
+        self, observations: list[Observation]
+    ) -> dict[str, Observation]:
+        latest: dict[str, Observation] = {}
+
+        for observation in observations:
+            existing = latest.get(observation.metric)
+            if existing is None or observation.observed_at > existing.observed_at:
+                latest[observation.metric] = observation
+
+        return latest
+
+    def _number(
+        self, observations: dict[str, Observation], metric: str
+    ) -> float | None:
+        observation = observations.get(metric)
+        if observation is None or observation.quality != ObservationQuality.OK:
+            return None
+
+        if isinstance(observation.value, bool):
+            return None
+
+        if isinstance(observation.value, int | float):
+            return float(observation.value)
+
+        return None
+
+    def _boolean(self, observations: dict[str, Observation], metric: str) -> bool:
+        observation = observations.get(metric)
+        if observation is None or observation.quality != ObservationQuality.OK:
+            return False
+
+        if isinstance(observation.value, bool):
+            return observation.value
+
+        return False
+