138 lines
4.8 KiB
Python
138 lines
4.8 KiB
Python
"""
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数据库模型 - SQLAlchemy
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"""
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from sqlalchemy import create_engine, Column, Integer, Float, String, DateTime, Text, JSON
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from sqlalchemy.ext.declarative import declarative_base
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from sqlalchemy.orm import sessionmaker
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from datetime import datetime
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import os
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# 数据库路径
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DB_PATH = os.path.join(os.path.dirname(__file__), '..', 'data', 'stocks.db')
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os.makedirs(os.path.dirname(DB_PATH), exist_ok=True)
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SQLALCHEMY_DATABASE_URL = f"sqlite:///{DB_PATH}"
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engine = create_engine(
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SQLALCHEMY_DATABASE_URL,
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connect_args={"check_same_thread": False}
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)
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SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
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Base = declarative_base()
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# ═════════════════════════════════════════════════════════════════════
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# 数据表模型
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# ═════════════════════════════════════════════════════════════════════
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class Position(Base):
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"""持仓表"""
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__tablename__ = "positions"
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id = Column(Integer, primary_key=True, index=True)
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stock_name = Column(String(50), nullable=False)
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ticker = Column(String(20), nullable=False, index=True)
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shares = Column(Integer, nullable=False)
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cost_price = Column(Float, nullable=False)
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current_price = Column(Float, default=0)
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market_value = Column(Float, default=0)
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pnl = Column(Float, default=0) # 盈亏金额
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pnl_percent = Column(Float, default=0) # 盈亏百分比
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# 策略参数
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strategy = Column(String(10), default="C") # A/B/C
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stop_loss = Column(Float, default=0.08) # 止损比例
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# 元数据
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created_at = Column(DateTime, default=datetime.now)
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updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now)
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notes = Column(Text, nullable=True)
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class StockData(Base):
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"""股票数据缓存表"""
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__tablename__ = "stock_data"
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id = Column(Integer, primary_key=True)
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ticker = Column(String(20), nullable=False, index=True)
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date = Column(String(10), nullable=False)
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open_price = Column(Float)
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high_price = Column(Float)
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low_price = Column(Float)
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close_price = Column(Float)
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volume = Column(Float)
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ma5 = Column(Float)
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ma20 = Column(Float)
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ma60 = Column(Float)
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rsi = Column(Float)
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atr = Column(Float)
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updated_at = Column(DateTime, default=datetime.now)
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class SentimentData(Base):
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"""舆情数据表"""
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__tablename__ = "sentiment_data"
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id = Column(Integer, primary_key=True)
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ticker = Column(String(20), nullable=False, index=True)
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date = Column(String(10), nullable=False)
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score = Column(Integer) # -5 ~ +5
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label = Column(String(20)) # 极度悲观/悲观/中性/乐观/极度乐观
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factors = Column(JSON) # 影响因素列表
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outlook = Column(String(50))
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source = Column(String(20), default="llm") # llm / manual / system
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created_at = Column(DateTime, default=datetime.now)
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class AnalysisResult(Base):
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"""分析结果表"""
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__tablename__ = "analysis_results"
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id = Column(Integer, primary_key=True)
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ticker = Column(String(20), nullable=False, index=True)
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date = Column(String(10), nullable=False)
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# 信号
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action = Column(String(20)) # BUY / SELL / HOLD
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score = Column(Float) # 综合评分
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confidence = Column(String(10)) # HIGH / MEDIUM / LOW
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# 详情
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tech_score = Column(Float)
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fund_score = Column(Float)
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sent_score = Column(Float)
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# 止损建议
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suggested_stop = Column(Float)
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position_ratio = Column(Float)
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# 完整数据（JSON）
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full_data = Column(JSON)
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created_at = Column(DateTime, default=datetime.now)
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class TradeLog(Base):
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"""交易日志表"""
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__tablename__ = "trade_logs"
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id = Column(Integer, primary_key=True)
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ticker = Column(String(20), nullable=False)
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action = Column(String(10), nullable=False) # BUY / SELL
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shares = Column(Integer)
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price = Column(Float)
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reason = Column(Text)
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pnl = Column(Float, nullable=True)
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created_at = Column(DateTime, default=datetime.now)
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# ═════════════════════════════════════════════════════════════════════
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# 初始化数据库
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# ═════════════════════════════════════════════════════════════════════
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def init_db():
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Base.metadata.create_all(bind=engine)
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print(f"✅ 数据库初始化完成: {DB_PATH}")
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if __name__ == "__main__":
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init_db()
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