from datetime import date, datetime

from sqlalchemy import Date, String, DateTime
from sqlalchemy.orm import Mapped, mapped_column, relationship

from app.database import Base


class Ticker(Base):
    __tablename__ = "tickers"

    id: Mapped[int] = mapped_column(primary_key=True)
    symbol: Mapped[str] = mapped_column(String(10), unique=True, nullable=False)
    # Company name (e.g. "Biogen Inc."); backfilled from Alpaca, nullable for
    # symbols Alpaca doesn't know.
    name: Mapped[str | None] = mapped_column(String(120), nullable=True)
    # SEC issuer identity, refreshed by the SEC fundamentals import from
    # company_tickers.json / submissions. The only ticker<->issuer join point;
    # multi-class tickers (GOOG/GOOGL) share these values. Nullable: not every
    # symbol resolves to a CIK (e.g. ADRs, foreign issuers not in SEC data).
    cik: Mapped[str | None] = mapped_column(String(10), nullable=True)
    sic: Mapped[str | None] = mapped_column(String(4), nullable=True)
    sic_description: Mapped[str | None] = mapped_column(String(160), nullable=True)
    # Delisting is recorded, never deleted: the rows carry the price history that
    # makes a backtest less survivorship-biased, and a delete cascades it away.
    # NULL == actively traded. The live signal path filters on this (see
    # ticker_service.active_only); list/admin views keep the row and show it.
    delisted_on: Mapped[date | None] = mapped_column(Date, nullable=True, index=True)
    # How we learned: "form_25" (SEC confirmed), "manual" (operator).
    delisted_reason: Mapped[str | None] = mapped_column(String(32), nullable=True)
    # The sibling of delisted_on, and the distinction matters: delisted means the
    # security stopped trading; untracked means it still trades and a prune took
    # it out of the scanner. Both retain every row — the delete this replaced
    # cascaded away exactly the history a survivorship-honest backtest needs.
    #
    # This records *exclusion by pruning*, NOT current index membership. The
    # scheduled sync runs prune_missing=False, so a symbol can have left the
    # index and still be scanned; the two states legitimately differ. Membership
    # itself lives in universe_memberships.
    #
    # active_only filters on it; the backtest's universe query deliberately does
    # not, so today's scanner state cannot erase yesterday's candidates.
    untracked_on: Mapped[date | None] = mapped_column(Date, nullable=True, index=True)
    # The operator's own "stop scanning this", kept apart from the prune flag on
    # purpose. If one column served both, a prune -> re-entry cycle would clear
    # an explicit operator "off", because re-entry cannot tell which writer set
    # it. Only set_tracked writes this; no bootstrap ever clears it.
    scan_disabled_on: Mapped[date | None] = mapped_column(Date, nullable=True, index=True)
    # Who owns this row's tracking: "index" (created by a universe bootstrap) or
    # "manual" (an operator added it). Pruning only ever touches index-owned
    # rows. Ownership is sticky towards manual — a bootstrap must never convert
    # manual to index, or a hand-added symbol that happens to join the index
    # would lose its protection when it later leaves.
    tracking_source: Mapped[str] = mapped_column(
        String(16), nullable=False, server_default="manual", default="manual"
    )
    created_at: Mapped[datetime] = mapped_column(
        DateTime(timezone=True), default=datetime.utcnow, nullable=False
    )

    # Relationships (cascade deletes)
    ohlcv_records = relationship("OHLCVRecord", back_populates="ticker", cascade="all, delete-orphan")
    sentiment_scores = relationship("SentimentScore", back_populates="ticker", cascade="all, delete-orphan")
    fundamental_data = relationship("FundamentalData", back_populates="ticker", cascade="all, delete-orphan")
    sr_levels = relationship("SRLevel", back_populates="ticker", cascade="all, delete-orphan")
    dimension_scores = relationship("DimensionScore", back_populates="ticker", cascade="all, delete-orphan")
    composite_scores = relationship("CompositeScore", back_populates="ticker", cascade="all, delete-orphan")
    trade_setups = relationship("TradeSetup", back_populates="ticker", cascade="all, delete-orphan")
    watchlist_entries = relationship("WatchlistEntry", back_populates="ticker", cascade="all, delete-orphan")
    ingestion_progress = relationship("IngestionProgress", back_populates="ticker", cascade="all, delete-orphan", uselist=False)
    earnings_events = relationship("EarningsEvent", back_populates="ticker", cascade="all, delete-orphan")
    universe_memberships = relationship("UniverseMembership", back_populates="ticker", cascade="all, delete-orphan")