udpate

app/sources/xueqiu.py

@@ -178,6 +178,83 @@ class XueqiuSource(DataSource):
             logger.exception("[kline %s] 雪球 kline 异常: %s", code6, e)
             return pd.DataFrame()
 
+    def fetch_kline_5min(self, code6: str, start: str, end: str) -> pd.DataFrame:
+        """5 分钟 K 线（雪球 period=5m）。返回标准列：bar_time, open, high, low, close, volume, amount。"""
+        if not self._read_token():
+            return pd.DataFrame()
+        try:
+            ball = self._import_ball()
+            self._set_token_once()
+            self._wait_rps()
+
+            symbol = code6_to_xueqiu(code6)
+            start_dt = datetime.strptime(start, "%Y-%m-%d")
+            end_dt = datetime.strptime(end, "%Y-%m-%d")
+            days_needed = max((end_dt - start_dt).days + 2, 1)
+            count = min(days_needed * 48, 5000)
+
+            result = None
+            for attempt in range(3):
+                result = call_with_timeout(
+                    ball.kline, symbol, period="5m", count=count,
+                    timeout=20.0, on_timeout=None,
+                    description=f"xueqiu.kline.5m {symbol}",
+                )
+                if result and result.get("error_code") == 0:
+                    break
+                if result is None and attempt < 2:
+                    time.sleep(0.3 * (attempt + 1))
+                    continue
+                if result and result.get("error_code") != 0:
+                    time.sleep(0.3 * (attempt + 1))
+            if not result or result.get("error_code") != 0:
+                logger.warning(
+                    "[kline5m %s] 雪球 5m 失败: error_code=%s desc=%s",
+                    code6,
+                    result.get("error_code") if result else "None",
+                    result.get("error_description") if result else "None",
+                )
+                return pd.DataFrame()
+            data = result.get("data", {})
+            columns = data.get("column", [])
+            items = data.get("item", [])
+            if not columns or not items:
+                return pd.DataFrame()
+            idx = {c: i for i, c in enumerate(columns)}
+            needed = {"timestamp": idx.get("timestamp"), "volume": idx.get("volume"),
+                      "open": idx.get("open"), "high": idx.get("high"),
+                      "low": idx.get("low"), "close": idx.get("close")}
+            if any(v is None for v in needed.values()):
+                return pd.DataFrame()
+            records = []
+            for row in items:
+                try:
+                    ts = row[needed["timestamp"]] / 1000
+                    records.append({
+                        "bar_time": datetime.fromtimestamp(ts).strftime("%Y-%m-%d %H:%M:%S"),
+                        "open": float(row[needed["open"]]),
+                        "high": float(row[needed["high"]]),
+                        "low": float(row[needed["low"]]),
+                        "close": float(row[needed["close"]]),
+                        "volume": float(row[needed["volume"]]),
+                        "amount": 0.0,
+                    })
+                except (IndexError, ValueError, TypeError, OSError):
+                    continue
+            if not records:
+                return pd.DataFrame()
+            df = pd.DataFrame(records)
+            df["bar_time"] = pd.to_datetime(df["bar_time"], errors="coerce")
+            df = df.dropna(subset=["bar_time"]).sort_values("bar_time").reset_index(drop=True)
+            if start:
+                df = df[df["bar_time"] >= pd.Timestamp(start)]
+            if end:
+                df = df[df["bar_time"] < pd.Timestamp(end) + pd.Timedelta(days=1)]
+            return df
+        except Exception as e:
+            logger.exception("[kline5m %s] 雪球 5m 异常: %s", code6, e)
+            return pd.DataFrame()
+
     def fetch_share_snapshot(self, code6: str) -> Optional[dict[str, Any]]:
         """单只股票的最新股本快照。
 

app/tasks/task_kline_5min.py

@@ -40,7 +40,7 @@ INCREMENT_OVERLAP_DAYS = 2
 # 2026-07-08 教训: 数据源层有 20s timeout,task 层再硬兜底,
 # 防 SDK 升级 / 网络层 bug 让单只股票卡住(7月7日 4.4只/秒 后突然 0 持续 24h)
 # 7月9日 mairui/雪球 间歇性 "服务器连接失败" + Broken pipe,拉慢。给 120s 容忍。
-FETCH_HARD_TIMEOUT = 120.0  # 5min K 一只拉多年,单只允许更久
+FETCH_HARD_TIMEOUT = 600.0  # 5min K 全市场 5200+ 只,按 RPS 预估约 17min,给 10min 硬超时
 
 
 class SyncKline5Min(SyncTask):