buffer_platform/app/analysis_models.py

"""
期货智析数据模型
"""
from datetime import datetime
from sqlalchemy import Column, String, Integer, Float, Text, DateTime, Boolean, Index, UniqueConstraint, JSON
from app.analysis_db import AnalysisBase


class FuturesAnalysis(AnalysisBase):
    """期货分析报告表"""
    __tablename__ = "futures_analysis"

    id = Column(Integer, primary_key=True, autoincrement=True)
    symbol = Column(String(32), nullable=False, index=True, comment="品种合约代码")
    analysis_time = Column(DateTime, nullable=False, default=datetime.now, index=True, comment="分析时间")
    period = Column(String(16), nullable=False, default="15min", comment="分析周期")
    # 分析结果
    suggestion = Column(String(32), nullable=True, comment="交易建议: 逢低做多/逢高做空/观望等待")
    suggestion_type = Column(String(16), nullable=True, comment="建议类型: up/down/neutral")
    entry_price = Column(Float, nullable=True, comment="建议入场价")
    target_price = Column(Float, nullable=True, comment="目标价位")
    stop_loss = Column(Float, nullable=True, comment="止损价位")
    risk_level = Column(String(16), nullable=True, comment="风险等级: 低/中/高")
    # 技术指标
    macd_signal = Column(String(16), nullable=True, comment="MACD信号")
    rsi_value = Column(Float, nullable=True, comment="RSI值")
    boll_signal = Column(String(16), nullable=True, comment="布林带信号")
    kdj_signal = Column(String(16), nullable=True, comment="KDJ信号")
    # 趋势评分
    trend_score = Column(Integer, nullable=True, comment="趋势评分 0-100")
    success_rate = Column(Float, nullable=True, comment="交易成功率")
    # 关键点位
    resistance_levels = Column(JSON, nullable=True, comment="压力位列表")
    support_levels = Column(JSON, nullable=True, comment="支撑位列表")
    # 多周期趋势
    period_trends = Column(JSON, nullable=True, comment="各周期趋势")

    def __repr__(self):
        return f"<FuturesAnalysis {self.symbol} {self.analysis_time}>"


class WatchedSymbol(AnalysisBase):
    """用户关注品种表"""
    __tablename__ = "watched_symbols"

    id = Column(Integer, primary_key=True, autoincrement=True)
    symbol = Column(String(32), nullable=False, unique=True, comment="品种合约代码")
    name = Column(String(64), nullable=True, comment="品种名称")
    note = Column(Text, nullable=True, comment="备注")
    created_at = Column(DateTime, nullable=False, default=datetime.now)
    updated_at = Column(DateTime, nullable=False, default=datetime.now, onupdate=datetime.now)

    def __repr__(self):
        return f"<WatchedSymbol {self.symbol}>"


class AIModelConfig(AnalysisBase):
    """AI模型配置表"""
    __tablename__ = "ai_model_configs"

    id = Column(Integer, primary_key=True, autoincrement=True)
    provider = Column(String(32), nullable=False, comment="AI提供商: openai/anthropic/google等")
    model_name = Column(String(64), nullable=False, comment="模型名称")
    api_key = Column(String(256), nullable=False, comment="API密钥")
    api_base = Column(String(256), nullable=True, comment="API基础URL")
    model_id = Column(String(64), nullable=True, comment="模型ID")
    temperature = Column(Float, nullable=True, default=0.7, comment="温度参数")
    max_tokens = Column(Integer, nullable=True, default=2000, comment="最大输出token")
    enabled = Column(Boolean, nullable=False, default=True, comment="是否启用")
    is_active = Column(Boolean, nullable=False, default=False, comment="是否为当前活跃模型")
    created_at = Column(DateTime, nullable=False, default=datetime.now)
    updated_at = Column(DateTime, nullable=False, default=datetime.now, onupdate=datetime.now)

    def __repr__(self):
        return f"<AIModelConfig {self.provider} {self.model_name}>"


class AnalysisSettings(AnalysisBase):
    """分析设置表（单例配置）"""
    __tablename__ = "analysis_settings"

    id = Column(Integer, primary_key=True, autoincrement=True)
    key = Column(String(64), nullable=False, unique=True, comment="配置键")
    value = Column(JSON, nullable=False, comment="配置值")
    updated_at = Column(DateTime, nullable=False, default=datetime.now, onupdate=datetime.now)

    def __repr__(self):
        return f"<AnalysisSettings {self.key}>"


class AIAnalysisCache(AnalysisBase):
    """AI分析缓存表"""
    __tablename__ = "ai_analysis_cache"

    id = Column(Integer, primary_key=True, autoincrement=True)
    symbol = Column(String(32), nullable=False, index=True, comment="品种合约代码")
    analysis_data = Column(JSON, nullable=False, comment="AI分析结果数据")
    kline_timestamp = Column(DateTime, nullable=True, comment="分析时K线数据的时间戳")
    created_at = Column(DateTime, nullable=False, default=datetime.now, index=True, comment="分析时间")

    def __repr__(self):
        return f"<AIAnalysisCache {self.symbol} {self.created_at}>"


class ReviewDate(AnalysisBase):
    """复盘日期表"""
    __tablename__ = "review_dates"

    id = Column(Integer, primary_key=True, autoincrement=True)
    review_date = Column(String(16), nullable=False, unique=True, index=True, comment="复盘日期 YYYY-MM-DD")
    week_day = Column(String(8), nullable=True, comment="星期")
    created_at = Column(DateTime, nullable=False, default=datetime.now)

    def __repr__(self):
        return f"<ReviewDate {self.review_date}>"


class SymbolRanking(AnalysisBase):
    """品种排名表"""
    __tablename__ = "symbol_rankings"

    id = Column(Integer, primary_key=True, autoincrement=True)
    review_date_id = Column(Integer, nullable=False, index=True, comment="关联复盘日期ID")
    symbol = Column(String(32), nullable=False, comment="品种合约代码")
    name = Column(String(64), nullable=True, comment="品种名称")
    rank_type = Column(String(32), nullable=False, comment="排名类型: volume/amplitude/change/open_interest")
    rank = Column(Integer, nullable=False, comment="排名")
    value = Column(String(64), nullable=True, comment="数值(如成交量、振幅等)")
    price = Column(String(32), nullable=True, comment="价格")
    change_pct = Column(String(16), nullable=True, comment="涨跌幅")

    def __repr__(self):
        return f"<SymbolRanking {self.symbol} {self.rank_type} rank={self.rank}>"


class TradingPlan(AnalysisBase):
    """交易计划表"""
    __tablename__ = "trading_plans"

    id = Column(Integer, primary_key=True, autoincrement=True)
    review_date_id = Column(Integer, nullable=False, index=True, comment="关联复盘日期ID")
    symbol = Column(String(32), nullable=False, comment="品种合约代码")
    name = Column(String(64), nullable=True, comment="品种名称")
    plan_type = Column(String(16), nullable=False, comment="计划类型: long/short")
    score = Column(Integer, nullable=False, comment="评分 0-100")
    logic = Column(Text, nullable=True, comment="多空逻辑")
    reason = Column(Text, nullable=True, comment="入选理由")
    entry_price = Column(String(64), nullable=True, comment="入场价位")
    stop_loss = Column(String(32), nullable=True, comment="止损价位")
    take_profit = Column(String(64), nullable=True, comment="止盈价位")
    confidence = Column(String(16), nullable=True, comment="置信度: 高/中高/中/低")
    position_suggestion = Column(String(32), nullable=True, comment="仓位建议")
    created_at = Column(DateTime, nullable=False, default=datetime.now)

    def __repr__(self):
        return f"<TradingPlan {self.symbol} {self.plan_type} score={self.score}>"


# ==================== V2 复盘计划模型 ====================

class SymbolScoreV2(AnalysisBase):
    """V2 品种多维度评分表"""
    __tablename__ = "symbol_scores_v2"

    id = Column(Integer, primary_key=True, autoincrement=True)
    review_date_id = Column(Integer, nullable=False, index=True, comment="关联复盘日期ID")
    symbol = Column(String(32), nullable=False, comment="品种合约代码")
    name = Column(String(64), nullable=True, comment="品种名称")
    close_price = Column(Float, nullable=True, comment="收盘价")
    prev_close = Column(Float, nullable=True, comment="昨收价")
    high_price = Column(Float, nullable=True, comment="当日最高")
    low_price = Column(Float, nullable=True, comment="当日最低")
    volume = Column(Float, nullable=True, comment="当日成交量")
    avg_volume_5 = Column(Float, nullable=True, comment="近5日均量")
    # 5维度评分
    amplitude_score = Column(Float, nullable=True, comment="振幅得分 0-100")
    volume_score = Column(Float, nullable=True, comment="量能得分 0-100")
    change_score = Column(Float, nullable=True, comment="涨跌幅得分 0-100")
    trend_score = Column(Float, nullable=True, comment="趋势得分 -100~100")
    activity_score = Column(Float, nullable=True, comment="活跃度得分 0-100")
    # 综合
    composite_score = Column(Float, nullable=True, comment="综合评分 0-100")
    # 原始数据
    amplitude_pct = Column(Float, nullable=True, comment="振幅百分比")
    change_pct = Column(Float, nullable=True, comment="涨跌幅百分比")
    volume_ratio = Column(Float, nullable=True, comment="量比")
    # 趋势明细
    trend_60m = Column(Float, nullable=True, comment="60分钟趋势分")
    trend_15m = Column(Float, nullable=True, comment="15分钟趋势分")
    trend_5m = Column(Float, nullable=True, comment="5分钟趋势分")
    # 方向标签
    direction = Column(String(32), nullable=True, comment="方向标签: 多头共振/空头共振/偏多震荡/偏空震荡/多空交织")
    direction_tag = Column(String(16), nullable=True, comment="方向标签简写: 强多/偏多/震荡/偏空/强空")
    category = Column(String(16), nullable=True, comment="分类: green(交易机会)/yellow(重点关注)/red(规避)")
    # 关键点位
    pivot = Column(Float, nullable=True, comment="枢轴点")
    r1 = Column(Float, nullable=True, comment="阻力位1")
    r2 = Column(Float, nullable=True, comment="阻力位2")
    s1 = Column(Float, nullable=True, comment="支撑位1")
    s2 = Column(Float, nullable=True, comment="支撑位2")
    # 排名
    rank = Column(Integer, nullable=True, comment="综合排名")
    # 实际数据日期
    data_date = Column(String(16), nullable=True, comment="实际数据日期 YYYY-MM-DD（日线最后一根K线的日期）")

    def __repr__(self):
        return f"<SymbolScoreV2 {self.symbol} score={self.composite_score}>"


class TradingPlanV2(AnalysisBase):
    """V2 交易计划表"""
    __tablename__ = "trading_plans_v2"

    id = Column(Integer, primary_key=True, autoincrement=True)
    review_date_id = Column(Integer, nullable=False, index=True, comment="关联复盘日期ID")
    symbol = Column(String(32), nullable=False, comment="品种合约代码")
    name = Column(String(64), nullable=True, comment="品种名称")
    direction = Column(String(16), nullable=False, comment="方向: long/short")
    composite_score = Column(Float, nullable=True, comment="综合评分")
    # 交易计划
    entry_low = Column(Float, nullable=True, comment="入场区间下限")
    entry_high = Column(Float, nullable=True, comment="入场区间上限")
    stop_loss = Column(Float, nullable=True, comment="止损位")
    target1 = Column(Float, nullable=True, comment="目标位1")
    target2 = Column(Float, nullable=True, comment="目标位2")
    trigger = Column(String(128), nullable=True, comment="触发条件")
    # 评分明细
    amplitude_score = Column(Float, nullable=True, comment="振幅得分")
    volume_score = Column(Float, nullable=True, comment="量能得分")
    trend_score = Column(Float, nullable=True, comment="趋势得分")
    activity_score = Column(Float, nullable=True, comment="活跃度得分")
    # 分类
    category = Column(String(16), nullable=True, comment="分类: green/yellow/red")

    def __repr__(self):
        return f"<TradingPlanV2 {self.symbol} {self.direction} score={self.composite_score}>"


class SectorHeat(AnalysisBase):
    """板块热度表"""
    __tablename__ = "sector_heat"

    id = Column(Integer, primary_key=True, autoincrement=True)
    review_date_id = Column(Integer, nullable=False, index=True, comment="关联复盘日期ID")
    sector_name = Column(String(32), nullable=False, comment="板块名称")
    avg_score = Column(Float, nullable=True, comment="板块均分")
    avg_trend = Column(Float, nullable=True, comment="平均趋势分")
    direction = Column(String(16), nullable=True, comment="方向: 多头/空头/震荡")
    heat_level = Column(Integer, nullable=True, comment="热度等级 0-3")
    leader_symbol = Column(String(32), nullable=True, comment="龙头品种代码")
    leader_score = Column(Float, nullable=True, comment="龙头品种评分")
    members = Column(JSON, nullable=True, comment="板块成员 [{symbol, name, score}]")

    def __repr__(self):
        return f"<SectorHeat {self.sector_name} avg={self.avg_score}>"


class ReviewPlanV2(AnalysisBase):
    """V2 复盘计划总表 - 存储每次生成的完整报告元数据"""
    __tablename__ = "review_plans_v2"

    id = Column(Integer, primary_key=True, autoincrement=True)
    review_date = Column(String(16), nullable=False, unique=True, index=True, comment="复盘日期 YYYY-MM-DD")
    week_day = Column(String(8), nullable=True, comment="星期")
    data_basis = Column(String(128), nullable=True, comment="数据基准说明")
    core_conclusion = Column(String(128), nullable=True, comment="核心结论")
    bull_count = Column(Integer, nullable=True, comment="多头品种数")
    bear_count = Column(Integer, nullable=True, comment="空头品种数")
    neutral_count = Column(Integer, nullable=True, comment="震荡品种数")
    opportunity_count = Column(Integer, nullable=True, comment="交易机会数")
    risk_warnings = Column(JSON, nullable=True, comment="风险提示列表")
    actual_data_date = Column(String(16), nullable=True, comment="实际数据日期 YYYY-MM-DD")
    data_date_matches = Column(Integer, nullable=True, comment="数据日期是否与复盘日期一致 1=是 0=否")
    created_at = Column(DateTime, nullable=False, default=datetime.now)

    def __repr__(self):
        return f"<ReviewPlanV2 {self.review_date}>"


# ==================== 交易复盘模型 ====================

class TradeRecord(AnalysisBase):
    """交易记录表 - 从期货结算单导入的逐笔交易明细"""
    __tablename__ = "trade_records"

    id = Column(Integer, primary_key=True, autoincrement=True)
    trade_type = Column(String(8), nullable=False, comment="类型: 期货/期权")
    symbol = Column(String(32), nullable=False, index=True, comment="合约代码 AG2606")
    variety = Column(String(16), nullable=False, index=True, comment="品种代码 AG")
    symbol_name = Column(String(64), nullable=True, comment="品种名称 沪银")
    direction = Column(String(8), nullable=False, comment="买卖方向: 买/卖")
    offset = Column(String(8), nullable=True, comment="开平标志: 开/平")
    price = Column(Float, nullable=True, comment="成交价/权利金单价")
    volume = Column(Float, nullable=True, comment="手数/成交量")
    amount = Column(Float, nullable=True, comment="成交额/权利金")
    close_pnl = Column(Float, nullable=True, default=0.0, comment="平仓盈亏")
    commission = Column(Float, nullable=True, default=0.0, comment="手续费")
    trade_date = Column(String(16), nullable=True, index=True, comment="成交日期 YYYY-MM-DD")
    trade_time = Column(String(32), nullable=True, comment="成交时间 HH:MM:SS")
    import_batch = Column(String(64), nullable=False, index=True, comment="导入批次号 UUID")
    source_file = Column(String(128), nullable=True, comment="来源文件名")
    created_at = Column(DateTime, nullable=False, default=datetime.now)

    __table_args__ = (
        Index('ix_trade_records_date_variety', 'trade_date', 'variety'),
    )

    def __repr__(self):
        return f"<TradeRecord {self.symbol} {self.direction} {self.offset} {self.trade_date}>"


class TradeImportBatch(AnalysisBase):
    """交易导入批次表 - 记录每次导入的元信息"""
    __tablename__ = "trade_import_batches"

    id = Column(Integer, primary_key=True, autoincrement=True)
    batch_id = Column(String(64), nullable=False, unique=True, index=True, comment="批次号 UUID")
    source_file = Column(String(128), nullable=False, comment="来源文件名")
    futures_count = Column(Integer, nullable=False, default=0, comment="期货交易记录数")
    options_count = Column(Integer, nullable=False, default=0, comment="期权交易记录数")
    trade_dates = Column(String(256), nullable=True, comment="涉及交易日期范围")
    created_at = Column(DateTime, nullable=False, default=datetime.now)

    def __repr__(self):
        return f"<TradeImportBatch {self.batch_id} {self.source_file}>"