#!/usr/bin/env python3
"""stale_detector.py — 检查所有策略，标记价格偏离/过期的策略

读取 holding_strategies + 自选策略的DB双源数据。
可被 cron no_agent 模式调用：stdout 注入到后续 LLM 分析。

输出格式：
  [FLAG] [自选/持仓] 股票名(代码) 价XX | 买入A~B | 问题

用法：
  python3 stale_detector.py
"""
import json
import sys
import os
from datetime import datetime, timezone
sys.path.insert(0, '/home/hmo/MoFin')
from mo_data import read_portfolio, read_decisions, read_watchlist, get_price, get_prices_batch

# ── 消息通道统一路由(broadcast/xmpp by delivery) ──
try:
    from messenger import install_stdio_hook as _msh
    _msh()
except Exception:
    pass


def fetch_prices(codes):
    """统一价格源：优先 stock_quote.py，腾讯API降级为兜底"""
    if not codes:
        return {}
    # 尝试用 stock_quote.py 获取（脚本强制规范）
    try:
        import subprocess
        script = None
        for p in ["/home/hmo/MoFin/deploy/profile-scripts/stock_quote.py", "/home/hmo/MoFin/stock_quote.py"]:
            if os.path.exists(p):
                script = p
                break
        if script:
            result = subprocess.run(
                [sys.executable, script] + [str(c) for c in codes],
                capture_output=True, text=True, timeout=30
            )
            if result.returncode == 0 and result.stdout.strip():
                results = {}
                for line in result.stdout.strip().split("\n"):
                    if not line.strip():
                        continue
                    try:
                        item = json.loads(line)
                        code = str(item.get("code", ""))
                        price = item.get("price")
                        change = item.get("change_pct", 0)
                        if code and price is not None:
                            results[code] = (float(price), float(change))
                    except (json.JSONDecodeError, ValueError):
                        continue
                if results:
                    return results
    except Exception as e:
        print(f"[STALE] stock_quote.py 回退: {e}", file=sys.stderr)

    # 兜底：mo_data.get_prices_batch
    try:
        raw = get_prices_batch(codes)
        if raw:
            return {code: (p, chg) for code, (p, chg) in raw.items()}
    except Exception as e:
        print(f"FETCH_FAIL (fallback): {e}", file=sys.stderr)
    return {}


def main():
    decisions_list = read_decisions()
    if not isinstance(decisions_list, list):
        decisions_list = decisions_list.get("decisions", []) if isinstance(decisions_list, dict) else []

    # 只保留有买入区的条目，排除已关闭的（inactive/closed）
    EXCLUDED_STATUSES = ("closed",)
    to_check = [d for d in decisions_list if (d.get("entry_low") is not None or d.get("entry_high") is not None) and d.get("status") not in EXCLUDED_STATUSES]

    # ----- 补充自选（从 holding_strategies 读取，watchlist_stocks 已废弃） -----
    try:
        import sqlite3
        db = sqlite3.connect('/home/hmo/MoFin/data/mofin.db')
        db.row_factory = sqlite3.Row
        wl_rows = db.execute(
            "SELECT code, name, entry_low, entry_high, stop_loss, take_profit, rr_ratio, timing_signal, action "
            "FROM holding_strategies WHERE status='active' AND decision_type='自选策略' "
            "AND entry_low IS NOT NULL AND entry_high IS NOT NULL"
        ).fetchall()
        db.close()
        existing_codes = {d["code"] for d in to_check}
        for row in wl_rows:
            code = str(row["code"])
            if code in existing_codes:
                continue
            entry_low = row["entry_low"]
            entry_high = row["entry_high"]
            if not entry_low or not entry_high or entry_low <= 0:
                continue
            action = row["action"] or ""
            timing_signal = row["timing_signal"] or "买入"
            wl_entry = {
                "code": code,
                "name": row["name"] or code,
                "entry_low": entry_low,
                "entry_high": entry_high,
                "stop_loss": row["stop_loss"],
                "type": "自选策略",
                "action": action,
                "timing_signal": timing_signal,
            }
            to_check.append(wl_entry)
    except Exception as e:
        print(f"[WATCHLIST_MERGE FAIL] {e}", file=sys.stderr)

    if not to_check:
        print("[SILENT] 无需要检查的策略")
        return 0

    # ----- 自选股买入区偏离自动重评 (从 holding_strategies 读，watchlist_stocks 已废弃) -----
    try:
        import subprocess, sqlite3
        db = sqlite3.connect('/home/hmo/MoFin/data/mofin.db')
        db.row_factory = sqlite3.Row
        wl_stocks = db.execute(
            "SELECT code, name, entry_low, entry_high "
            "FROM holding_strategies WHERE status='active' AND decision_type='自选策略' "
            "AND entry_low IS NOT NULL AND entry_high IS NOT NULL AND entry_low > 0"
        ).fetchall()
        db.close()
        reassess_scripts = []
        for ws in wl_stocks:
            code, name, wl_el, wl_eh = ws
            if not wl_el or not wl_el or wl_el <= 0:
                continue
            center = (wl_el + wl_eh) / 2
            # 从 decisions 拿实时价
            price_map = fetch_prices([code])
            cur_price = price_map.get(code, (None, None))[0]
            if not cur_price or cur_price <= 0:
                continue
            drift = (cur_price / center - 1) * 100
            # 触发条件：价格偏离>15% 或 买入区明确错误（价格完全在区间外且偏离>50%）
            price_outside = cur_price < wl_el or cur_price > wl_eh
            if abs(drift) > 15 or (price_outside and abs(drift) > 50):
                reassess_scripts.append(code)
                print(f"[AUTO_REASSESS] {name}({code}) 价{cur_price:.2f}偏离买入区中心{center:.2f} {drift:+.0f}% → 触发重评")
        if reassess_scripts:
            # 调用 per_stock_reassess（每轮最多5只，防LLM慢导致整批超时；其余下轮继续）
            reassess_path = None
            for p in ['/home/hmo/MoFin/deploy/profile-scripts/per_stock_reassess.py',
                      '/home/hmo/.hermes/profiles/position-analyst/scripts/per_stock_reassess.py']:
                if os.path.exists(p):
                    reassess_path = p
                    break
            if reassess_path:
                MAX_PER_RUN = 5
                batch = reassess_scripts[:MAX_PER_RUN]
                if len(reassess_scripts) > MAX_PER_RUN:
                    print(f"[AUTO_REASSESS] 本轮限{MAX_PER_RUN}只，剩余{len(reassess_scripts)-MAX_PER_RUN}只下轮继续")
                for code in batch:
                    try:
                        # LLM 重评冷启动 20-100s，deepseek-v4-pro 更慢 → 480s
                        r = subprocess.run(['python3', reassess_path, code],
                                         capture_output=True, text=True, timeout=480)
                        out = r.stdout.strip()[:200] if r.stdout else ""
                        err = r.stderr.strip()[:200] if r.stderr else ""
                        print(f"  → {code}: exited={r.returncode} {out}")
                    except subprocess.TimeoutExpired:
                        print(f"  → {code}: 超时480s（LLM仍慢），下轮重试")
    except Exception as e:
        print(f"[AUTO_REASSESS FAIL] {e}")
    # ----- 结束 自选股重评 -----
    # 🔁 重评后重新从DB读取策略数据，刷新to_check
    try:
        decisions_list = read_decisions()
        if not isinstance(decisions_list, list):
            decisions_list = decisions_list.get("decisions", []) if isinstance(decisions_list, dict) else []
        to_check = [d for d in decisions_list if (d.get("entry_low") is not None or d.get("entry_high") is not None) and d.get("status") not in EXCLUDED_STATUSES]
        # 重新合并自选（从 holding_strategies 读）
        db2 = sqlite3.connect('/home/hmo/MoFin/data/mofin.db')
        db2.row_factory = sqlite3.Row
        wl_rows2 = db2.execute(
            "SELECT code, name, entry_low, entry_high, stop_loss, take_profit, rr_ratio, timing_signal, action "
            "FROM holding_strategies WHERE status='active' AND decision_type='自选策略' "
            "AND entry_low IS NOT NULL AND entry_high IS NOT NULL AND entry_low > 0"
        ).fetchall()
        db2.close()
        existing_codes2 = {d["code"] for d in to_check}
        for row in wl_rows2:
            code = str(row["code"])
            if code in existing_codes2:
                continue
            entry_low = row["entry_low"]
            entry_high = row["entry_high"]
            if not entry_low or not entry_high or entry_low <= 0:
                continue
            action = row["action"] or ""
            timing_signal = row["timing_signal"] or "买入"
            wl_entry = {
                "code": code,
                "name": row["name"] or code,
                "entry_low": entry_low,
                "entry_high": entry_high,
                "stop_loss": row["stop_loss"],
                "type": "自选策略",
                "action": action,
                "timing_signal": timing_signal,
            }
            to_check.append(wl_entry)
    except Exception as e:
        print(f"[RELOAD FAIL] {e}", file=sys.stderr)

    # ----- 组合级监测：读取总仓位 + 弱势比例 -----
    position_pct = 0
    cash = 0
    total_assets = 0
    try:
        pf = read_portfolio()
        position_pct = pf.get("position_pct", 0)
        cash = pf.get("cash", 0)
        total_assets = pf.get("total_assets", 0)
    except Exception:
        pass
    # 统计持仓策略中弱势/深套的比例
    weak_count = 0
    holding_count = 0
    for d in decisions_list:
        if d.get("type") == "持仓策略" and d.get("status") not in ("closed",):
            holding_count += 1
            cat = d.get("stock_category", "")
            if cat in ("弱势", "深套"):
                weak_count += 1
    weak_ratio = (weak_count / holding_count * 100) if holding_count > 0 else 0

    prices = fetch_prices([d["code"] for d in to_check])
    now = datetime.now(timezone.utc).astimezone()
    found = 0

    for d in to_check:
        code = d["code"]
        name = d.get("name", code)
        el = d.get("entry_low")
        eh = d.get("entry_high")
        sl = d.get("stop_loss")
        tp = d.get("take_profit")
        ts = d.get("created_at") or d.get("timestamp") or d.get("updated_at", "")
        is_wl = "自选" in (d.get("type", ""))

        pi = prices.get(code)
        if not pi:
            continue
        price, chg = pi
        if price <= 0:
            continue

        issues, flags = [], []
        tag = "[自选]" if is_wl else "[持仓]"

        # -- 偏离 --
        if is_wl and not issues and not flags:
            # 自选在买入区上沿与20%之间（零标记漏洞）：标记为小幅偏离
            if el and eh and price > eh:
                flags.append("[WL_DRIFT]")
                flags.append("[STRATEGY_STALE]")
                issues.append(f"[STRATEGY_STALE] 价{price:.2f}超买入区上沿+{((price/eh)-1)*100:.1f}%，买入区需重评")
        if is_wl and el and eh:
            # 读取 timing_signal 判断策略有效性（timing_signal 字段优先，fallback to action）
            current_str = d.get("current", "") or ""
            timing_signal = d.get("timing_signal", "") or current_str
            has_nonbuy_signal = any(kw in timing_signal for kw in [
                "等企稳再入", "等企稳", "弱势持有", "观望",
                "不建议买入", "谨慎买入",
            ])

            # 直接计算 R/R（不依赖文本匹配）
            rr_invalid = False
            if sl and sl > 0 and tp and tp > 0 and price > sl:
                rr = (tp - price) / (price - sl)
                if rr < 1.5:
                    rr_invalid = True
                # 也检查 tp 是否接近或低于成本（微盈/浮亏止盈）
                cost = d.get("cost", 0)
                if cost and cost > 0 and tp <= cost * 1.05:
                    rr_invalid = True

            strategy_deficient = has_nonbuy_signal or rr_invalid
            # 对自选无止盈位的也标记（策略不完整）
            if not tp or tp == 0:
                strategy_deficient = True

            if el <= price <= eh:
                flags.append("[WL_IN]")
                if strategy_deficient:
                    flags.append("[STRATEGY_STALE]")
                    issues.append(f"[STRATEGY_STALE] 价{price:.2f}在买入区{el}~{eh}但策略不完整（{'RR='+f'{rr:.2f}<1.5' if rr_invalid else '无止盈位' if not tp else '非买入信号'}），买入区需重评")
                else:
                    issues.append(f"[PUSH] 价{price:.2f}入买入区{el}~{eh}")
            elif price > eh * 1.35:
                flags.append("[WL_HIGH]")
                flags.append("[STRATEGY_STALE]")
                issues.append(f"[STRATEGY_STALE] 价{price:.2f}高出买入区+{((price/eh)-1)*100:.0f}%，买入区需重评")
            elif price > eh * 1.20:
                flags.append("[WL_DRIFT]")
                flags.append("[STRATEGY_STALE]")
                issues.append(f"[STRATEGY_STALE] 价{price:.2f}高出买入区+{((price/eh)-1)*100:.0f}%，买入区需重评")
            elif price > eh:
                flags.append("[WL_DRIFT]")
                flags.append("[STRATEGY_STALE]")
                issues.append(f"[STRATEGY_STALE] 价{price:.2f}超买入区上沿+{((price/eh)-1)*100:.1f}%，买入区需重评")
        elif not is_wl and eh:
            dp = (price / eh - 1) * 100
            if dp > 35:
                flags.append("[SEVERE]")
                issues.append(f"偏离买入区上沿+{dp:.0f}%")
            elif dp > 20:
                flags.append("[DRIFT]")
                issues.append(f"偏离买入区上沿+{dp:.0f}%")
            elif dp > 10:
                flags.append("[WARN]")
                issues.append(f"偏离买入区上沿+{dp:.0f}%")
            # 持仓在买入区内但 R/R 不达标
            if el and sl and sl > 0 and tp and tp > 0 and price > sl:
                if el <= price <= eh:
                    rr = (tp - price) / (price - sl)
                    if rr < 1.5:
                        flags.append("[RR_WARN]")
                        issues.append(f"买入区内RR仅{rr:.2f}<1.5，策略需重评")

        # -- 距止损/止盈（仅持仓） --
        if not is_wl:
            if sl and sl > 0:
                dsl = (price / sl - 1) * 100
                if dsl < 5:
                    # 成本基准校验：浮盈>5%时止损是利润保护，不是危险信号
                    # (mirrors NEAR_TP cost_check logic at line 195-198)
                    cost = d.get("cost")
                    if cost and cost > 0 and price > cost * 1.05:
                        flags.append("[PROFIT_PROTECT]")
                        pnl = (price / cost - 1) * 100
                        issues.append(f"距止损仅{dsl:.1f}%(利润保护,浮盈{pnl:.0f}%)")
                    else:
                        flags.append("[NEAR_SL]")
                        issues.append(f"距止损仅{dsl:.1f}%")
            if tp and tp > 0:
                dtp = (tp / price - 1) * 100
                if dtp < 5:
                    # 成本基准校验：止盈标记只有在盈利≥5%时才有效
                    cost_check = True
                    cost = d.get("cost")
                    if cost and cost > 0 and price < cost * 1.05:
                        cost_check = False
                    if cost_check:
                        flags.append("[NEAR_TP]")
                        issues.append(f"距止盈仅{dtp:.1f}%")

        # -- 过期 --
        stale_limit = 30 if is_wl else 14
        if ts:
            try:
                ud = datetime.fromisoformat(ts)
                if ud.tzinfo is None:
                    ud = ud.replace(tzinfo=timezone.utc)
                days = (now - ud).days
                if days > stale_limit:
                    flags.append("[STALE]")
                    issues.append(f"{days}天未更新(>{stale_limit})")
            except (ValueError, TypeError):
                pass

        if issues:
            # 仅输出有明确操作信号的行：[PUSH]=推荐买入, [STRATEGY_STALE]=需重评
            # 静默其他纯信息行（如仅"价XX高出/高于买入区"而无操作建议）
            if any("[PUSH]" in i or "[STRATEGY_STALE]" in i for i in issues):
                print(f"{' '.join(flags)} {tag} {name}({code}) 价{price:.2f}{chg} | 买入{el}~{eh} | {'; '.join(issues)}")
                found += 1

    if found == 0:
        print("[SILENT] 所有策略正常")

    # ----- 组合级警报 -----
    portfolio_alerts = 0
    if holding_count > 0:
        if weak_ratio > 40:
            print(f"\n[PORTFOLIO_WEAK] 组合弱势比例{weak_ratio:.0f}% ({weak_count}/{holding_count})！仓位{position_pct:.1f}% → 建议系统性减仓")
            portfolio_alerts += 1
        elif weak_ratio > 30:
            print(f"\n[PORTFOLIO_WEAK_MILD] 组合弱势比例{weak_ratio:.0f}% ({weak_count}/{holding_count})，仓位{position_pct:.1f}%，关注")
            portfolio_alerts += 1
    if position_pct > 80 and holding_count > 0:
        # 仓位过满提醒
        print(f"[PORTFOLIO_FULL] 总仓位{position_pct:.1f}% > 80%，现金{cash:.0f}({cash/total_assets*100:.1f}%)")
        portfolio_alerts += 1
    if portfolio_alerts > 0:
        found += portfolio_alerts

    return found


if __name__ == "__main__":
    main()