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102 lines
4.8 KiB
102 lines
4.8 KiB
"""
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期货智析数据模型
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"""
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from datetime import datetime
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from sqlalchemy import Column, String, Integer, Float, Text, DateTime, Boolean, Index, UniqueConstraint, JSON
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from app.analysis_db import AnalysisBase
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class FuturesAnalysis(AnalysisBase):
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"""期货分析报告表"""
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__tablename__ = "futures_analysis"
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id = Column(Integer, primary_key=True, autoincrement=True)
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symbol = Column(String(32), nullable=False, index=True, comment="品种合约代码")
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analysis_time = Column(DateTime, nullable=False, default=datetime.now, index=True, comment="分析时间")
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period = Column(String(16), nullable=False, default="15min", comment="分析周期")
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# 分析结果
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suggestion = Column(String(32), nullable=True, comment="交易建议: 逢低做多/逢高做空/观望等待")
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suggestion_type = Column(String(16), nullable=True, comment="建议类型: up/down/neutral")
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entry_price = Column(Float, nullable=True, comment="建议入场价")
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target_price = Column(Float, nullable=True, comment="目标价位")
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stop_loss = Column(Float, nullable=True, comment="止损价位")
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risk_level = Column(String(16), nullable=True, comment="风险等级: 低/中/高")
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# 技术指标
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macd_signal = Column(String(16), nullable=True, comment="MACD信号")
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rsi_value = Column(Float, nullable=True, comment="RSI值")
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boll_signal = Column(String(16), nullable=True, comment="布林带信号")
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kdj_signal = Column(String(16), nullable=True, comment="KDJ信号")
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# 趋势评分
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trend_score = Column(Integer, nullable=True, comment="趋势评分 0-100")
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success_rate = Column(Float, nullable=True, comment="交易成功率")
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# 关键点位
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resistance_levels = Column(JSON, nullable=True, comment="压力位列表")
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support_levels = Column(JSON, nullable=True, comment="支撑位列表")
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# 多周期趋势
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period_trends = Column(JSON, nullable=True, comment="各周期趋势")
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def __repr__(self):
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return f"<FuturesAnalysis {self.symbol} {self.analysis_time}>"
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class WatchedSymbol(AnalysisBase):
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"""用户关注品种表"""
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__tablename__ = "watched_symbols"
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id = Column(Integer, primary_key=True, autoincrement=True)
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symbol = Column(String(32), nullable=False, unique=True, comment="品种合约代码")
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name = Column(String(64), nullable=True, comment="品种名称")
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note = Column(Text, nullable=True, comment="备注")
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created_at = Column(DateTime, nullable=False, default=datetime.now)
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updated_at = Column(DateTime, nullable=False, default=datetime.now, onupdate=datetime.now)
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def __repr__(self):
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return f"<WatchedSymbol {self.symbol}>"
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class AIModelConfig(AnalysisBase):
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"""AI模型配置表"""
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__tablename__ = "ai_model_configs"
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id = Column(Integer, primary_key=True, autoincrement=True)
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provider = Column(String(32), nullable=False, comment="AI提供商: openai/anthropic/google等")
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model_name = Column(String(64), nullable=False, comment="模型名称")
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api_key = Column(String(256), nullable=False, comment="API密钥")
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api_base = Column(String(256), nullable=True, comment="API基础URL")
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model_id = Column(String(64), nullable=True, comment="模型ID")
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temperature = Column(Float, nullable=True, default=0.7, comment="温度参数")
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max_tokens = Column(Integer, nullable=True, default=2000, comment="最大输出token")
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enabled = Column(Boolean, nullable=False, default=True, comment="是否启用")
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is_active = Column(Boolean, nullable=False, default=False, comment="是否为当前活跃模型")
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created_at = Column(DateTime, nullable=False, default=datetime.now)
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updated_at = Column(DateTime, nullable=False, default=datetime.now, onupdate=datetime.now)
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def __repr__(self):
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return f"<AIModelConfig {self.provider} {self.model_name}>"
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class AnalysisSettings(AnalysisBase):
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"""分析设置表（单例配置）"""
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__tablename__ = "analysis_settings"
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id = Column(Integer, primary_key=True, autoincrement=True)
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key = Column(String(64), nullable=False, unique=True, comment="配置键")
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value = Column(JSON, nullable=False, comment="配置值")
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updated_at = Column(DateTime, nullable=False, default=datetime.now, onupdate=datetime.now)
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def __repr__(self):
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return f"<AnalysisSettings {self.key}>"
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class AIAnalysisCache(AnalysisBase):
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"""AI分析缓存表"""
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__tablename__ = "ai_analysis_cache"
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id = Column(Integer, primary_key=True, autoincrement=True)
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symbol = Column(String(32), nullable=False, index=True, comment="品种合约代码")
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analysis_data = Column(JSON, nullable=False, comment="AI分析结果数据")
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created_at = Column(DateTime, nullable=False, default=datetime.now, index=True, comment="分析时间")
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def __repr__(self):
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return f"<AIAnalysisCache {self.symbol} {self.created_at}>"
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