"""Panic event model."""

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

from app.core.database import Base


class PanicEvent(Base):
    """Panic event table model."""
    
    __tablename__ = "panic_events"
    
    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)
    
    # Event timing
    start_time = Column(DateTime(timezone=True), nullable=False, index=True)
    peak_time = Column(DateTime(timezone=True))
    end_time = Column(DateTime(timezone=True))
    
    # Price impact
    price_at_start = Column(Numeric(15, 4), nullable=False)
    price_at_peak_panic = Column(Numeric(15, 4))
    price_at_end = Column(Numeric(15, 4))
    max_drawdown_percent = Column(Numeric(8, 4), index=True)
    
    # Sentiment
    avg_sentiment_score = Column(Numeric(5, 2))
    min_sentiment_score = Column(Numeric(5, 2))
    news_volume = Column(Integer)
    
    # Recovery metrics
    recovery_time_days = Column(Integer)
    recovery_percent = Column(Numeric(8, 4))
    
    # Classification
    event_type = Column(String(100), index=True)  # earnings_miss, scandal, lawsuit, macro, etc.
    event_category = Column(String(50))  # company_specific, sector_wide, market_wide
    
    # Analysis
    is_complete = Column(Boolean, default=False)
    notes = Column(Text)
    
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    updated_at = Column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())