"""Buy signal model."""

from sqlalchemy import Column, String, DateTime, Numeric, Integer, ForeignKey
from sqlalchemy.dialects.postgresql import UUID
from sqlalchemy.sql import func
import uuid

from app.core.database import Base


class BuySignal(Base):
    """Buy signal table model."""
    
    __tablename__ = "buy_signals"
    
    id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
    stock_id = Column(UUID(as_uuid=True), ForeignKey("stocks.id", ondelete="CASCADE"), nullable=False, index=True)
    panic_event_id = Column(UUID(as_uuid=True), ForeignKey("panic_events.id", ondelete="SET NULL"))
    
    # Signal details
    signal_time = Column(DateTime(timezone=True), nullable=False, server_default=func.now(), index=True)
    signal_price = Column(Numeric(15, 4), nullable=False)
    
    # Confidence scoring
    confidence_score = Column(Numeric(5, 4), nullable=False, index=True)  # 0 to 1
    
    # Based on pattern
    pattern_id = Column(UUID(as_uuid=True), ForeignKey("historical_patterns.id", ondelete="SET NULL"))
    expected_recovery_percent = Column(Numeric(8, 4))
    expected_recovery_days = Column(Integer)
    
    # Current metrics
    current_drawdown_percent = Column(Numeric(8, 4))
    current_sentiment_score = Column(Numeric(5, 2))
    
    # Signal status
    status = Column(String(20), default="active", index=True)  # active, triggered, expired, cancelled
    triggered_at = Column(DateTime(timezone=True))
    
    # Outcome tracking
    outcome_price = Column(Numeric(15, 4))
    outcome_percent = Column(Numeric(8, 4))
    outcome_days = Column(Integer)
    
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    updated_at = Column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())