from datetime import date as date_type
from datetime import datetime

from sqlalchemy import Date, DateTime, Float, String, Text
from sqlalchemy.orm import Mapped, mapped_column

from app.database import Base


class RegimeFundamentalObservation(Base):
    """Point-in-time record of the sourced hyperscaler capex / earnings read.

    One row per ``effective_date`` (unique, upserted). Before this table the
    observation lived in a single ``SystemSetting`` slot, so every refresh
    overwrote the previous one and no history existed at all — which made the
    read impossible to replay, impossible to backtest, and meant a snapshot
    rebuild could only ever score historical sessions as if nothing had been
    observed.

    The read is a categorical channel reported beside State and Warning, never a
    term in either, so this series is not a scoring input. It is the record that
    makes the channel replayable at all -- and the only route to eventually
    testing whether it improves prediction conditional on Warning, which is the
    one thing that could justify combining the channels later.

    ``effective_date`` rather than ``fetched_at`` is the key: it is the session
    the observation becomes usable on (normally the next weekday), and the gate
    that stops a rebuild stamping today's reading onto historical rows.
    """

    __tablename__ = "regime_fundamental_observations"

    id: Mapped[int] = mapped_column(primary_key=True)
    effective_date: Mapped[date_type] = mapped_column(
        Date, nullable=False, unique=True, index=True
    )
    f1_score: Mapped[float | None] = mapped_column(Float, nullable=True)
    f3_score: Mapped[float | None] = mapped_column(Float, nullable=True)
    capex_json: Mapped[str] = mapped_column(Text, nullable=False)
    good_news_stock_down: Mapped[str] = mapped_column(String(10), nullable=False)
    reasoning: Mapped[str | None] = mapped_column(Text, nullable=True)
    source: Mapped[str] = mapped_column(String(30), nullable=False)
    fetched_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)