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

2026-08-26 21:25:32 +08:00
parent bd1ef0c9a4
commit a819033175
8 changed files with 337 additions and 337 deletions
@@ -144,29 +144,32 @@ def evaluate_strategy(s, price):
    sl_recovery = False
    if tp > 0 or sl > 0:
        try:
-            prefix = "sh" if code.startswith(('60','68','51','56','50')) else "sz" if code.startswith(('00','30','15')) else "hk"
-            url = f"http://ifzq.gtimg.cn/appstock/app/fqkline/get?param={prefix}{code},day,,,60,qfq"
-            import subprocess as sp
-            r = sp.run(["curl", "-s", "--max-time", "3", url], capture_output=True, text=True, timeout=5)
-            if r.returncode == 0 and r.stdout:
-                data = json.loads(r.stdout)
-                day_key = 'qfqday' if prefix != 'hk' else 'day'
-                bars = data.get('data', {}).get(f'{prefix}{code}', {}).get(day_key, [])
-                if bars:
-                    prices = [(float(b[2]), float(b[3]), b[0]) for b in bars if len(b) > 3]  # (high, low, date)
-                    recent_high = max(p[0] for p in prices)
-                    recent_low = min(p[1] for p in prices)
-                    # 检查止损触发后的走势：是否后来反弹了？
-                    if sl > 0:
-                        # 找出价格低于SL的K线
-                        below_sl = [p for p in prices if p[1] <= sl]
-                        above_sl_later = [p for p in prices if p[1] > sl * 1.03]
-                        if below_sl and above_sl_later:
-                            # 曾跌破SL，但后来涨回去了 → 洗盘
-                            first_below = min(below_sl, key=lambda x: x[2])
-                            last_above = max(above_sl_later, key=lambda x: x[2])
-                            if last_above[2] > first_below[2]:
-                                sl_recovery = True
+            # 读 stock_daily 近60根日K（2026-08-26 分层铁律：消费层不直连腾讯API）
+            raw_code = str(code).split("_")[0]
+            if raw_code.lower().startswith("hk"):
+                raw_code = raw_code[2:]
+            _conn = sqlite3.connect(str(DB_PATH), timeout=5)
+            _bars = _conn.execute(
+                "SELECT date, high, low FROM stock_daily WHERE code=? "
+                "ORDER BY date DESC LIMIT 60", (raw_code,)
+            ).fetchall()
+            _conn.close()
+            if _bars:
+                # 转为升序（旧→新），与 qfqday 时序一致
+                prices = [(float(b[1]), float(b[2]), b[0]) for b in reversed(_bars) if b[1] and b[2]]  # (high, low, date)
+                recent_high = max(p[0] for p in prices)
+                recent_low = min(p[1] for p in prices)
+                # 检查止损触发后的走势：是否后来反弹了？
+                if sl > 0:
+                    # 找出价格低于SL的K线
+                    below_sl = [p for p in prices if p[1] <= sl]
+                    above_sl_later = [p for p in prices if p[1] > sl * 1.03]
+                    if below_sl and above_sl_later:
+                        # 曾跌破SL，但后来涨回去了 → 洗盘
+                        first_below = min(below_sl, key=lambda x: x[2])
+                        last_above = max(above_sl_later, key=lambda x: x[2])
+                        if last_above[2] > first_below[2]:
+                            sl_recovery = True
        except:
            pass