#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""leader_scanner.py — MoFin 龙头识别策略（bull_trend 适用，2026-08-13 落地）

核心逻辑（12维方法论 + 龙头识别低波动优化版理念）：
- 适用状态：bull_trend（above_ma20 + rsi>55 + adx>20）
- 入场：龙头股回调到 MA20 附近（趋势中的健康回调，不追高）
- 12维条件（复用 stock_indicators 已有字段，无拍脑袋）：
  1. 个股 close > MA20（趋势向上）
  2. dist_ma20 ∈ [-3%, +2%]（回调到 MA20 附近，不追高）
  3. 行业强势（sector_above_ma20=1 或 sector_ret20>0，需 sector 数据）
  4. 市值/流动性过滤（mcap_q > 0.3，龙头非小盘）
  5. RSI ∈ [45, 65]（强势但未超买）
  6. 量能配合（vol_ratio > 0.8，非极度缩量）
- 出场：跌破 MA20 或达到上方压力位
- RR：压力位（前高/筹码阻力）/ 支撑位（MA20）计算

注意：这是初版框架，需 MoFin 引擎验证达标（年化≥13.2%）才正式上线
"""
import sqlite3
import json
from datetime import datetime
from pathlib import Path

DB = "/home/hmo/MoFin/data/mofin.db"
OUT = Path("/home/hmo/MoFin/data/leader_signals.json")

def load_market_state():
    p = Path("/home/hmo/MoFin/data/market_state.json")
    if p.exists():
        return json.loads(p.read_text(encoding="utf-8"))
    return {"state": "neutral"}

def scan_leaders():
    """扫描龙头股回调买点（bull_trend 状态）"""
    ms = load_market_state()
    state = ms.get("state", "neutral")
    if state != "bull_trend":
        print(f"当前状态 {state}，非 bull_trend，不扫描龙头（避免追高）")
        return []

    c = sqlite3.connect(DB)
    # 最新交易日
    row = c.execute("SELECT MAX(date) FROM stock_indicators").fetchone()
    if not row or not row[0]:
        c.close()
        return []
    latest = row[0]
    print(f"扫描日期: {latest}")

    # 龙头条件（12维）
    rows = c.execute(
        """SELECT code, ma20, rsi, dist_ma20, mcap_q, pe_q, vol_ratio, trend_aligned
           FROM stock_indicators
           WHERE date=? AND ma20 IS NOT NULL AND rsi IS NOT NULL""",
        (latest,)
    ).fetchall()
    c.close()

    signals = []
    for r in rows:
        code, ma20, rsi, dist_ma20, mcap_q, pe_q, vol_ratio, trend_aligned = r
        # 条件1: 趋势向上（close > MA20 → dist_ma20 > 0，或接近）
        if dist_ma20 is None or dist_ma20 < -3 or dist_ma20 > 2:
            continue
        # 条件2: RSI 强势未超买
        if rsi < 45 or rsi > 65:
            continue
        # 条件3: 市值/流动性（龙头非小盘，mcap_q > 0.3）
        if mcap_q is not None and mcap_q < 0.3:
            continue
        # 条件4: 量能配合
        if vol_ratio is not None and vol_ratio < 0.8:
            continue
        # 条件5: 趋势共振（trend_aligned=1）
        if trend_aligned != 1:
            continue
        signals.append({
            "code": code, "ma20": ma20, "rsi": rsi,
            "dist_ma20": dist_ma20, "mcap_q": mcap_q, "pe_q": pe_q,
            "vol_ratio": vol_ratio, "entry_reason": "龙头回调MA20",
        })

    # 按 dist_ma20 排序（最接近 MA20 的优先）
    signals.sort(key=lambda x: abs(x["dist_ma20"]))
    print(f"龙头信号: {len(signals)} 只")
    for s in signals[:5]:
        print(f"  {s['code']}: dist_ma20={s['dist_ma20']:.1f}% rsi={s['rsi']:.1f} mcap_q={s['mcap_q']}")
    return signals

def main():
    signals = scan_leaders()
    out = {
        "state": load_market_state().get("state", "neutral"),
        "signals": signals,
        "count": len(signals),
        "updated_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
    }
    OUT.write_text(json.dumps(out, ensure_ascii=False, indent=1), encoding="utf-8")
    print(f"leader_signals.json 写入")

if __name__ == "__main__":
    main()