feat: macro_context/market数据全部DB优先，JSON回退

- 建 macro_context_log 表，macro_context_collector.py 双写
- strategy_lifecycle.py load_macro_context() 优先DB
- strategy_tree.py detect_scenario() 优先DB
- stale_push_wlin.py load_macro_line() 优先DB
- xiaoguo_signal_consumer.py 大盘判断优先DB
- stock_profile.py load_macro() 优先DB
- system_audit.py 管道审计改查DB market_snapshots
- JSON保留作fallback，确保过渡期不中断

strategy_lifecycle.py

@@ -286,22 +286,39 @@ def compute_sector_adjustment(code, market_ctx, stock_sector_map):
 
 
 def load_macro_context():
-    """读取宏观上下文，返回 (bias, desc)，bias 取 0.8/1.0/1.1 分别对应 bearish/neutral/bullish"""
+    """读取宏观上下文，返回 (bias, desc)，优先 DB，回退 JSON"""
     try:
-        with open(MACRO_CONTEXT_PATH) as f:
-            ctx = json.load(f)
-        overall = ctx.get("structure", {}).get("overall", "neutral")
-        desc = ctx.get("structure", {}).get("description", "")
-        if "bearish" in overall:
-            return 0.8, f"宏观{desc}"
-        elif overall == "bullish":
-            return 1.05, f"宏观{desc}"
-        elif overall == "strong_bullish":
-            return 1.1, f"宏观{desc}"
+        import sqlite3
+        from pathlib import Path
+        conn = sqlite3.connect(str(Path(__file__).parent.parent / "data" / "mofin.db"))
+        row = conn.execute(
+            "SELECT indices, structure FROM macro_context_log "
+            "WHERE has_valid_data=1 ORDER BY created_at DESC LIMIT 1"
+        ).fetchone()
+        conn.close()
+        if row:
+            indices = json.loads(row[0]) if row[0] else {}
+            structure = json.loads(row[1]) if row[1] else {}
+            overall = structure.get("overall", "neutral")
+            desc = structure.get("description", "")
         else:
-            return 1.0, f"宏观{desc}"
+            raise ValueError("no db data")
     except Exception:
-        return 1.0, "宏观未加载"
+        try:
+            with open(MACRO_CONTEXT_PATH) as f:
+                ctx = json.load(f)
+            overall = ctx.get("structure", {}).get("overall", "neutral")
+            desc = ctx.get("structure", {}).get("description", "")
+        except Exception:
+            return 1.0, "宏观未加载"
+    if "bearish" in overall:
+        return 0.8, f"宏观{desc}"
+    elif overall == "bullish":
+        return 1.05, f"宏观{desc}"
+    elif overall == "strong_bullish":
+        return 1.1, f"宏观{desc}"
+    else:
+        return 1.0, f"宏观{desc}"
 
 
 def batch_fetch_prices(codes):