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- from datetime import datetime
- from sqlalchemy import DateTime, Float, ForeignKey, Index, Integer
- from sqlalchemy.orm import Mapped, mapped_column
- from backend.app.core.database import Base
- class SmartPlugEnergySnapshot(Base):
- """Hourly snapshot of a smart plug's lifetime energy counter.
- Powers date-range queries in "total consumption" energy mode. For a given
- range we sum `(last_snapshot_in_range - last_snapshot_before_range)` per plug.
- """
- __tablename__ = "smart_plug_energy_snapshots"
- __table_args__ = (Index("ix_plug_energy_snapshots_plug_time", "plug_id", "recorded_at"),)
- id: Mapped[int] = mapped_column(Integer, primary_key=True)
- plug_id: Mapped[int] = mapped_column(ForeignKey("smart_plugs.id", ondelete="CASCADE"), nullable=False)
- recorded_at: Mapped[datetime] = mapped_column(DateTime, nullable=False)
- lifetime_kwh: Mapped[float] = mapped_column(Float, nullable=False)
- # The electricity price when the snapshot was taken (#1251). The energy used
- # until the next snapshot is costed at it, so a price that changes during the
- # day is applied hour by hour instead of to all of history at once.
- price_per_kwh: Mapped[float | None] = mapped_column(Float, nullable=True)
- # Running totals of the energy counted and what it cost, up to this row
- # (#1251). The cost of any span is the difference of two rows, so the
- # Statistics never have to walk the whole history.
- kwh_to_date: Mapped[float | None] = mapped_column(Float, nullable=True)
- cost_to_date: Mapped[float | None] = mapped_column(Float, nullable=True)
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