"""
交易信号数据库模型
"""
from datetime import datetime
from sqlalchemy import Column, Integer, String, Text, DateTime, JSON, Float, Boolean
from sqlalchemy.orm import relationship

from app.models.database import Base


class TradingSignal(Base):
    """交易信号表"""
    __tablename__ = "trading_signals"

    id = Column(Integer, primary_key=True, index=True)

    # 信号基本信息
    signal_type = Column(String(20), nullable=False, index=True)  # 'crypto' or 'stock'
    symbol = Column(String(50), nullable=False, index=True)  # 交易对或股票代码

    # 信号方向和评级
    action = Column(String(10), nullable=False)  # 'buy', 'sell', 'hold'
    grade = Column(String(5), nullable=False)  # 'A', 'B', 'C', 'D'
    confidence = Column(Float, nullable=False)  # 置信度 0-100

    # 价格信息
    entry_price = Column(Float, nullable=True)
    entry_zone = Column(Float, nullable=True)  # 挂单价格
    stop_loss = Column(Float, nullable=True)
    take_profit = Column(Float, nullable=True)
    current_price = Column(Float, nullable=True)  # 信号生成时的当前价格

    # 信号详情
    signal_type_detail = Column(String(20), nullable=True)  # 'short_term', 'medium_term', 'long_term'
    entry_type = Column(String(10), nullable=True)  # 'market', 'limit'
    position_size = Column(String(20), nullable=True)  # 'light', 'medium', 'heavy'

    # 分析信息
    reason = Column(Text, nullable=True)  # 信号理由
    risk_warning = Column(Text, nullable=True)  # 风险提示
    analysis_summary = Column(Text, nullable=True)  # 分析摘要
    news_sentiment = Column(String(20), nullable=True)  # 新闻情绪
    news_impact = Column(String(100), nullable=True)  # 消息影响

    # 关键价位
    key_levels = Column(JSON, nullable=True)  # 支撑位和阻力位

    # 技术指标（JSON 格式存储）
    indicators = Column(JSON, nullable=True)

    # 状态
    is_active = Column(Boolean, default=True)  # 信号是否有效
    notified = Column(Boolean, default=False)  # 是否已发送通知
    notification_sent_at = Column(DateTime, nullable=True)

    # 时间戳
    created_at = Column(DateTime, default=datetime.utcnow, index=True)
    updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)

    def __repr__(self):
        return f"<TradingSignal({self.signal_type} {self.symbol} {self.action} {self.grade} {self.confidence}%)>"

    def to_dict(self):
        """转换为字典"""
        return {
            'id': self.id,
            'signal_type': self.signal_type,
            'symbol': self.symbol,
            'action': self.action,
            'grade': self.grade,
            'confidence': self.confidence,
            'entry_price': self.entry_price,
            'entry_zone': self.entry_zone,
            'stop_loss': self.stop_loss,
            'take_profit': self.take_profit,
            'current_price': self.current_price,
            'signal_type_detail': self.signal_type_detail,
            'entry_type': self.entry_type,
            'position_size': self.position_size,
            'reason': self.reason,
            'risk_warning': self.risk_warning,
            'analysis_summary': self.analysis_summary,
            'news_sentiment': self.news_sentiment,
            'news_impact': self.news_impact,
            'key_levels': self.key_levels,
            'indicators': self.indicators,
            'is_active': self.is_active,
            'notified': self.notified,
            'notification_sent_at': self.notification_sent_at.isoformat() if self.notification_sent_at else None,
            'created_at': self.created_at.isoformat() if self.created_at else None,
            'updated_at': self.updated_at.isoformat() if self.updated_at else None,
            'timestamp': self.created_at.isoformat() if self.created_at else None
        }