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