feat: strategy_lifecycle + stale_detector + server — DB-first price reads, Tencent API as fallback only

strategy_lifecycle.py

@@ -354,13 +354,37 @@ def load_macro_context():
 
 
 def batch_fetch_prices(codes):
-    """批量获取实时价格，合并为一次API调用（自动分批，每批15只）"""
+    """获取实时价格。优先从 DB 读取（price_monitor 每 2 分钟更新），失败才拉腾讯 API。"""
     if not codes:
         return {}
     
-    # 分批处理，避免单次请求过大导致超时
-    batch_size = 15
     all_results = {}
+    
+    # 主通道：从 DB 读取（price_monitor 唯一价格入口）
+    try:
+        import sqlite3
+        db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
+        db.row_factory = sqlite3.Row
+        for raw_code in codes:
+            raw_code = str(raw_code).split('_')[0]
+            if not raw_code: continue
+            row = db.execute(
+                "SELECT price, change_pct FROM holdings WHERE code=? AND is_active=1", (raw_code,)
+            ).fetchone()
+            if not row:
+                row = db.execute(
+                    "SELECT price, change_pct FROM holding_strategies WHERE code=? AND status='active' ORDER BY updated_at DESC LIMIT 1", (raw_code,)
+                ).fetchone()
+            if row and row['price']:
+                all_results[raw_code] = (row['price'], 0, row['change_pct'] or 0)
+        db.close()
+        if all_results:
+            return all_results
+    except Exception:
+        pass
+    
+    # Fallback: 腾讯 API（仅当 DB 无数据时）
+    batch_size = 15
     for batch_start in range(0, len(codes), batch_size):
         batch = codes[batch_start:batch_start + batch_size]
         symbols = []
@@ -423,16 +447,33 @@ def batch_fetch_prices(codes):
 
 
 def get_price_tencent(code):
-    """获取实时价格，港股转CNY统一存CNY"""
+    """获取实时价格。优先 DB（price_monitor 维护），失败才拉腾讯。港股价格已是 CNY。"""
+    raw_code = str(code).split('_')[0]
+    if not raw_code:
+        return None
+    
+    # 主通道: DB
+    try:
+        import sqlite3
+        db = sqlite3.connect('/home/hmo/web-dashboard/data/mofin.db')
+        db.row_factory = sqlite3.Row
+        row = db.execute("SELECT price FROM holdings WHERE code=? AND is_active=1", (raw_code,)).fetchone()
+        if not row:
+            row = db.execute("SELECT price FROM holding_strategies WHERE code=? AND status='active' ORDER BY updated_at DESC LIMIT 1", (raw_code,)).fetchone()
+        if row and row['price']:
+            db.close()
+            return row['price']
+        db.close()
+    except Exception:
+        pass
+    
+    # Fallback: 腾讯 API
     try:
         from mo_models import to_cny, is_hk_stock
     except ImportError:
         to_cny = lambda v, r=None: v
         is_hk_stock = lambda c: len(str(c).strip()) == 5 and str(c).strip().isdigit()
     try:
-        raw_code = code.split('_')[0]
-        if not raw_code:
-            return None
         if is_hk_stock(raw_code):
             prefix = "hk"
         elif raw_code.startswith("6") or raw_code.startswith("5"):
@@ -786,11 +827,104 @@ def reassess_strategy(code, name, price, cost, shares, current_action,
             if entry_high < max_change:
                 entry_high = round(max_change, 2)
 
-    # ----- 买入时机信号 -----
+    # ----- 买入时机信号（三维分析：大盘+行业+个股，基本面+消息面+技术面+资金流）-----
+    # [2026-07-01] 扩展：不再只看volume_signal + candlestick_sentiment
+    # 融合大盘趋势、行业板块强弱、基本面估值作为修正因子
     volume_signal = vol.get("volume_signal", "")
     candlestick_sentiment = candle.get("sentiment", "neutral")
     timing_signal = "neutral"
 
+    # --- 三维分析数据装载 ---
+    # 因子1: 大盘环境（从macro_context_log读）
+    market_bearish = False
+    market_bullish = False
+    try:
+        import sqlite3
+        _db = sqlite3.connect("/home/hmo/MoFin/data/mofin.db", timeout=5)
+        _mc = _db.execute(
+            "SELECT structure FROM macro_context_log WHERE has_valid_data=1 ORDER BY rowid DESC LIMIT 1"
+        ).fetchone()
+        if _mc and _mc[0]:
+            _s = json.loads(_mc[0])
+            _overall = _s.get("overall", "")
+            if "bearish" in _overall:
+                market_bearish = True
+            elif _overall == "bullish":
+                market_bullish = True
+        _db.close()
+    except Exception:
+        pass
+
+    # 因子2: 行业板块强弱
+    sector_strong = False
+    sector_weak = False
+    try:
+        _db2 = sqlite3.connect("/home/hmo/MoFin/data/mofin.db", timeout=5)
+        _rows2 = _db2.execute(
+            "SELECT name, change_pct FROM sector_snapshots ORDER BY change_pct DESC"
+        ).fetchall()
+        if _rows2:
+            # 找到该股所属行业（简单匹配name或通过stock_sectors）
+            _my_sectors = _db2.execute(
+                "SELECT sector_name FROM stock_sectors WHERE code=?",
+                (code,)
+            ).fetchall()
+            if _my_sectors:
+                for (_sn,) in _my_sectors:
+                    for r_name, r_chg in _rows2:
+                        if _sn in r_name or r_name in _sn:
+                            _rank = [r[0] for r in _rows2].index(r_name) if r_name in [x[0] for x in _rows2] else -1
+                            _total = len(_rows2)
+                            if _rank >= 0:
+                                if _rank < _total * 0.2:
+                                    sector_strong = True
+                                if _rank > _total * 0.8:
+                                    sector_weak = True
+                            break
+        _db2.close()
+    except Exception:
+        pass
+
+    # 因子3: 基本面估值
+    is_value_stock = False
+    try:
+        _db3 = sqlite3.connect("/home/hmo/MoFin/data/mofin.db", timeout=5)
+        _fd = _db3.execute(
+            "SELECT pe, eps FROM stock_fundamentals WHERE code=?", (code,)
+        ).fetchone()
+        if _fd:
+            _pe, _eps = _fd
+            is_value_stock = (0 < (_pe or 0) < 25 and (_eps or 0) > 0.3)
+        _db3.close()
+    except Exception:
+        pass
+
+    # --- 三维修正规则 ---
+    # 大盘偏弱时收紧买入信号，大盘偏强时放宽
+    # 行业领先加分，行业落后减分
+    # 低估值加分（有安全边际）
+
+    def _adjust_timing(signal, market_b, market_bb, sec_s, sec_w, is_val):
+        """根据三维因子修正 timing_signal"""
+        # 大盘偏弱时降级买入信号
+        if market_b:
+            if signal in ("买入", "加仓"):
+                if not sec_s:  # 大盘弱+行业不强→降级
+                    return "关注"
+        # 大盘偏强时放宽
+        if market_bb:
+            if signal == "关注" and (sec_s or is_val):
+                return "买入"
+        # 行业弱势时降级买入信号
+        if sec_w:
+            if signal in ("买入", "加仓"):
+                return "关注"
+        # 行业强势+低估时升级关注
+        if sec_s and is_val:
+            if signal == "关注":
+                return "买入"
+        return signal
+
     if is_new_entry:
         # 新买入时机
         if volume_signal == "主动买盘占优" and candlestick_sentiment == "bullish":
@@ -803,6 +937,15 @@ def reassess_strategy(code, name, price, cost, shares, current_action,
             timing_signal = "买入"
         elif ws and price < ws * 1.02:
             timing_signal = "关注"
+        # 新买入时三维修正：大盘向上+行业强→升级，大盘弱→降级
+        _pre_signal = timing_signal
+        timing_signal = _adjust_timing(timing_signal, market_bearish, market_bullish,
+                                       sector_strong, sector_weak, is_value_stock)
+        if timing_signal != _pre_signal:
+            print(f"  三维修正(新入): {_pre_signal}→{timing_signal} "
+                  f"| 大盘{'弱' if market_bearish else '强' if market_bullish else '中性'}"
+                  f"| 行业{'强' if sector_strong else '弱' if sector_weak else '中性'}"
+                  f"| 估值{'低' if is_value_stock else '一般'}")
     else:
         # 已持仓时机（用于加仓/减仓参考）
         if is_short_term_strong_trend: