"""Pydantic 数据模型"""

from pydantic import BaseModel
from datetime import datetime


class StockQuote(BaseModel):
    ts_code: str
    name: str
    price: float
    pct_chg: float
    volume: float           # 成交量（手）
    amount: float           # 成交额（万元）
    turnover_rate: float    # 换手率 %
    pe: float | None = None
    pb: float | None = None
    circ_mv: float | None = None    # 流通市值（亿）
    total_mv: float | None = None   # 总市值（亿）
    volume_ratio: float | None = None   # 量比
    high: float | None = None
    low: float | None = None
    open: float | None = None
    pre_close: float | None = None
    limit_up: float | None = None
    limit_down: float | None = None
    amplitude: float | None = None  # 振幅 %


class CapitalFlow(BaseModel):
    ts_code: str
    trade_date: str
    buy_elg_amount: float = 0   # 特大单买入（万）
    sell_elg_amount: float = 0
    buy_lg_amount: float = 0    # 大单买入（万）
    sell_lg_amount: float = 0
    buy_md_amount: float = 0    # 中单买入（万）
    sell_md_amount: float = 0
    buy_sm_amount: float = 0    # 小单买入（万）
    sell_sm_amount: float = 0
    net_mf_amount: float = 0    # 主力净流入（万）

    @property
    def main_net_inflow(self) -> float:
        """主力净流入 = 特大单净买 + 大单净买"""
        return (self.buy_elg_amount - self.sell_elg_amount +
                self.buy_lg_amount - self.sell_lg_amount)

    @property
    def total_amount(self) -> float:
        return (self.buy_elg_amount + self.sell_elg_amount +
                self.buy_lg_amount + self.sell_lg_amount +
                self.buy_md_amount + self.sell_md_amount +
                self.buy_sm_amount + self.sell_sm_amount)


class SectorInfo(BaseModel):
    sector_code: str
    sector_name: str
    pct_change: float = 0       # 涨跌幅 %
    capital_inflow: float = 0   # 主力净流入（万）
    limit_up_count: int = 0     # 涨停数
    days_continuous: int = 0    # 连续资金流入天数
    heat_score: float = 0       # 热度综合评分
    stage: str = "mid"          # 板块阶段: early/mid/late/end


class MarketTemperature(BaseModel):
    trade_date: str
    up_count: int = 0           # 上涨家数
    down_count: int = 0         # 下跌家数
    limit_up_count: int = 0     # 涨停数（自然涨停）
    limit_down_count: int = 0   # 跌停数
    max_streak: int = 0         # 最高连板
    broken_rate: float = 0      # 炸板率 %
    index_above_ma20: bool = False  # 上证在 MA20 上方
    temperature: float = 0      # 综合温度 0-100


class TechnicalSignal(BaseModel):
    ts_code: str
    name: str = ""
    ma_bullish: bool = False        # 均线多头排列
    volume_breakout: bool = False   # 放量突破
    macd_golden: bool = False       # MACD金叉
    rsi_healthy: bool = False       # RSI健康区间
    pullback_support: bool = False  # 缩量回踩支撑
    big_yang: bool = False          # 底部放量长阳
    boll_support: bool = False      # 布林带下轨支撑
    score: float = 0                # 技术面总分
    signal_count: int = 0           # 满足的信号数量

    # 位置安全评估（防追高）
    rally_pct_5d: float = 0         # 近5日累计涨幅
    rally_pct_10d: float = 0        # 近10日累计涨幅
    distance_from_high: float = 0   # 距离60日高点 %（负=已回调）
    position_score: float = 50      # 位置安全得分 0-100

    # 价格参考
    support_price: float | None = None   # 支撑位
    resist_price: float | None = None    # 压力位
    stop_loss_price: float | None = None # 止损价


class Recommendation(BaseModel):
    ts_code: str
    name: str
    sector: str
    score: float                    # 综合评分
    market_temp_score: float
    sector_score: float
    capital_score: float
    technical_score: float
    position_score: float = 50      # 位置安全得分
    valuation_score: float = 50     # 估值安全得分
    signal: str                     # BUY / SELL / HOLD
    entry_price: float | None = None
    target_price: float | None = None
    stop_loss: float | None = None
    reasons: list[str] = []
    risk_note: str = ""
    level: str = ""                 # 强烈推荐/推荐/观望/回避
    llm_analysis: str = ""          # LLM 深度分析
    scan_session: str = ""
    created_at: datetime | None = None