from sqlalchemy import Column, Integer, String, Float, DateTime, ForeignKey, Enum
from sqlalchemy.orm import relationship
from sqlalchemy.sql import func
import enum
from app.db.database import Base


class TradeAction(str, enum.Enum):
    BUY = "BUY"
    SELL = "SELL"


class Simulation(Base):
    __tablename__ = "simulations"

    id = Column(Integer, primary_key=True, index=True)
    user_id = Column(String, nullable=True)  # For future multi-user support
    symbol = Column(String, default="XAU/USD")
    initial_capital = Column(Float, default=100000.0)
    current_capital = Column(Float, default=100000.0)
    total_pnl = Column(Float, default=0.0)
    total_pnl_percent = Column(Float, default=0.0)
    created_at = Column(DateTime(timezone=True), server_default=func.now())
    updated_at = Column(DateTime(timezone=True), onupdate=func.now())

    trades = relationship("Trade", back_populates="simulation", cascade="all, delete-orphan")
    positions = relationship("Position", back_populates="simulation", cascade="all, delete-orphan")


class Trade(Base):
    __tablename__ = "trades"

    id = Column(Integer, primary_key=True, index=True)
    simulation_id = Column(Integer, ForeignKey("simulations.id"))
    action = Column(Enum(TradeAction))
    quantity = Column(Float)
    price = Column(Float)
    total = Column(Float)
    pnl = Column(Float, nullable=True)
    timestamp = Column(DateTime(timezone=True), server_default=func.now())

    simulation = relationship("Simulation", back_populates="trades")


class Position(Base):
    __tablename__ = "positions"

    id = Column(Integer, primary_key=True, index=True)
    simulation_id = Column(Integer, ForeignKey("simulations.id"))
    symbol = Column(String, default="XAU/USD")
    quantity = Column(Float)
    avg_price = Column(Float)
    current_price = Column(Float)
    unrealized_pnl = Column(Float)
    unrealized_pnl_percent = Column(Float)
    updated_at = Column(DateTime(timezone=True), onupdate=func.now())

    simulation = relationship("Simulation", back_populates="positions")


class AIAnalysisLog(Base):
    __tablename__ = "ai_analysis_logs"

    id = Column(Integer, primary_key=True, index=True)
    simulation_id = Column(Integer, nullable=True)
    recommendation = Column(String)
    confidence = Column(Float)
    reasoning = Column(String)
    risk_level = Column(String)
    support_levels = Column(String)  # JSON string
    resistance_levels = Column(String)  # JSON string
    created_at = Column(DateTime(timezone=True), server_default=func.now())