from datetime import datetime

from sqlalchemy import DateTime, Integer, String, Text
from sqlalchemy.orm import Mapped, mapped_column

from app.database import Base


class JobRunState(Base):
    """How each scheduled job last finished. One row per job, overwritten.

    The scheduler's ``_job_runtime`` dict is the live view and is deliberately
    in-memory, but it is also wiped by every process restart -- so after a deploy
    Admin → Jobs could only say "Active" with no indication of whether a job had
    ever run. This is the durable half.

    Deliberately not history: ``system_events`` already grows without a reaper,
    and a second append-only operational table would repeat that. Rows are
    upserted on ``job_name``; adding history later is purely additive.
    """

    __tablename__ = "job_run_state"

    id: Mapped[int] = mapped_column(primary_key=True)
    job_name: Mapped[str] = mapped_column(String(64), unique=True, nullable=False)
    # Scheduler vocabulary: completed | skipped | error | rate_limited | deferred.
    # Distinct from data_import_runs' statuses, which is one reason this is its
    # own table rather than a widened column there.
    status: Mapped[str] = mapped_column(String(32), nullable=False)
    started_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
    finished_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
    processed: Mapped[int | None] = mapped_column(Integer, nullable=True)
    total: Mapped[int | None] = mapped_column(Integer, nullable=True)
    message: Mapped[str | None] = mapped_column(Text, nullable=True)
    updated_at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True), default=datetime.utcnow, onupdate=datetime.utcnow, nullable=False
    )