feat: data-layering 第二批消费层读DB(divergence/staleness/accumulation/collect_eval/strategy_review/mo_provider/multi_timeframe/chip_factors)

deploy/profile-scripts/divergence_detector.py

@@ -14,7 +14,7 @@ divergence_detector.py — 跨市场背离监测器（no_agent）
   - 状态文件 macro_divergence_state.json
   - no_agent: 有信号才出声
 """
-import sys, json, re, datetime, os, requests
+import sys, json, datetime, os
 from pathlib import Path
 
 # ── 消息通道统一路由(broadcast/xmpp by delivery) ──
@@ -47,69 +47,45 @@ DIVERGENCE_MODERATE = 3.0 # >3% → moderate信号
 STREAK_DAYS = 3           # 连涨/连跌3天 → 信号
 
 def fetch_indices():
-    """获取所有指数实时数据（直接调用新浪API，mo_data不支持指数代码）"""
-    import requests
-    sina_map = {
-        "sh000001": "s_sh000001",
-        "sz399001": "s_sz399001",
-        "sz399006": "s_sz399006",
-        "sh000688": "s_sh000688",
-        "sh000016": "s_sh000016",
-        "sh000300": "s_sh000300",
-        "hkHSI":    "rt_hkHSI",
-        "hkHSCEI":  "rt_hkHSCEI",
+    """获取所有指数数据（读 DB stock_daily 收盘价，2026-08-26 分层铁律：消费层不直连新浪API）"""
+    import sqlite3
+    # 指数代码 → 中文名（stock_daily 表已有 sh000001/sz399001/sz399006/sh000688）
+    index_map = {
+        "sh000001": "上证指数",
+        "sz399001": "深证成指",
+        "sz399006": "创业板指",
+        "sh000688": "科创50",
+        "sh000016": "上证50",
+        "sh000300": "沪深300",
     }
-    url = "http://hq.sinajs.cn/list=" + ",".join(sina_map.values())
-    headers = {"Referer": "https://finance.sina.com.cn"}
+    indices = {}
     try:
-        r = requests.get(url, headers=headers, timeout=10)
-        r.encoding = "gbk"
+        conn = sqlite3.connect(str(DB_PATH), timeout=5)
+        for sym, cname in index_map.items():
+            rows = conn.execute(
+                "SELECT date, close, high, low FROM stock_daily "
+                "WHERE code=? ORDER BY date DESC LIMIT 2", (sym,)
+            ).fetchall()
+            if not rows:
+                continue
+            latest = rows[0]
+            prev_close = rows[1][1] if len(rows) > 1 else latest[1]
+            price = latest[1] or 0
+            change_pct = (price - prev_close) / prev_close * 100 if prev_close else 0
+            indices[sym] = {
+                "name": cname,
+                "price": price,
+                "close": price,
+                "change_pct": round(change_pct, 2),
+                "high": latest[2] or 0,
+                "low": latest[3] or 0,
+                "timestamp": latest[0],
+            }
+        conn.close()
     except Exception as e:
         print(f"[DIVERGE] 采集失败: {e}", file=sys.stderr)
         return {}
-
-    indices = {}
-    for line in r.text.strip().split("\n"):
-        line = line.strip()
-        if not line:
-            continue
-        # Parse: var hq_str_XXXX="fields,...";
-        try:
-            var_name = line.split('"')[0].rsplit("_", 1)[-1].rstrip("=")
-            fields = line.split('"')[1].split(",")
-        except (IndexError, ValueError):
-            continue
-
-        # Find the symbol
-        sym = None
-        for s, sn in sina_map.items():
-            if sn.endswith(var_name):
-                sym = s
-                break
-        if not sym:
-            continue
-
-        if sym.startswith("hk"):
-            # HK: name,price,open,high,low,prev_close,change,change_pct,...
-            name = fields[1]
-            price = float(fields[2]) if fields[2] else 0
-            change_pct = float(fields[8]) if len(fields) > 8 and fields[8] else 0
-        else:
-            # A-share: name,price,change,change_pct,...
-            name = fields[0]
-            price = float(fields[1]) if fields[1] else 0
-            change_pct = float(fields[3]) if len(fields) > 3 and fields[3] else 0
-
-        indices[sym] = {
-            "name": name,
-            "price": price,
-            "close": 0,
-            "change_pct": change_pct,
-            "high": 0,
-            "low": 0,
-            "timestamp": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
-        }
-
+    # 港股指数 hkHSI/hkHSCEI 不在 stock_daily，读不到则不返回（中性值，由调用方跳过低检测）
     return indices
 
 def load_history():