chore: 重构前基线 — 9 个 sync task 全部 ok + akshare 移除 + mairui 资金流接入

状态： - 9 个 sync task（stock_basic / kline_daily / kline_index / kline_5min / moneyflow / industry_sector / sector_features / share_snapshot / market_regime） - 数据源：baostock + mairui + 雪球(pysnowball) + 新浪（4 个） - 项目级约束：永远不用 akshare（已落实） - kline_5min 改用 DB 快照统一全量/增量逻辑 - 零后端 Chrome 扩展 xueqiu_sync（独立项目）
2026-06-15 15:36:09 +08:00
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+"""Baostock 数据源。
+
+提供：
+  - 全市场股票基础信息（query_stock_basic）
+  - 日 K 线（query_history_k_data_plus，免费，但 QPS 限制需要信号量）
+  - 股票-行业映射（query_stock_industry）
+
+免费、无 token，但需 bs.login() / bs.logout() 维护会话。
+"""
+from __future__ import annotations
+
+import threading
+from typing import Any, Optional
+
+import pandas as pd
+
+from app.core.datasource.base import DataSource
+from app.core.datasource.utils import (
+    code6_to_baostock,
+    normalize_kline,
+)
+
+
+class BaostockSource(DataSource):
+    key = "datasource_baostock"
+    name = "Baostock"
+    provides = ["kline_daily", "stock_basic", "industry"]
+    requires_credential = False
+
+    # 进程内只 login 一次
+    _login_lock = threading.Lock()
+    _logged_in = False
+    _semaphore = threading.BoundedSemaphore(3)  # QPS 限流
+
+    def _ensure_login(self) -> None:
+        if self._logged_in:
+            return
+        with self._login_lock:
+            if self._logged_in:
+                return
+            import baostock as bs
+            bs.login()
+            self._logged_in = True
+
+    def is_available(self) -> tuple[bool, str]:
+        try:
+            self._ensure_login()
+            return True, "ok"
+        except Exception as e:
+            return False, f"Baostock 登录失败: {e}"
+
+    def health_check(self) -> dict[str, Any]:
+        """连通性测试：复用 _ensure_login 避免重复 login 阻塞。"""
+        try:
+            self._ensure_login()
+            import baostock as bs
+            rs = bs.query_stock_basic(code="sh.600036")
+            if rs.error_code != "0":
+                return {"success": False, "message": f"Baostock 查询失败: {rs.error_msg}"}
+            rows = []
+            while rs.next():
+                rows.append(rs.get_row_data())
+            return {"success": True, "message": f"连接成功，查询到 {len(rows)} 条股票信息"}
+        except Exception as e:
+            return {"success": False, "message": f"Baostock 连接失败: {e}"}
+
+    def fetch_stock_basic(self) -> list[dict[str, Any]]:
+        """全市场 A 股基础信息。
+
+        baostock query_stock_basic 返回字段（按当前接口）：
+          code, code_name, ipoDate, outDate, type, status
+        按字段名索引，防止 Baostock 改顺序。
+        """
+        import baostock as bs
+        self._ensure_login()
+        try:
+            rs = bs.query_stock_basic()
+            if rs.error_code != "0":
+                raise RuntimeError(f"Baostock query_stock_basic 失败: {rs.error_msg}")
+            fields = list(rs.fields)
+            idx = {name: i for i, name in enumerate(fields)}
+            rows = []
+            while rs.next():
+                row = rs.get_row_data()
+                bs_code = row[idx["code"]]
+                name = row[idx["code_name"]]
+                stype = row[idx["type"]]
+                status = row[idx["status"]]
+                ipo = row[idx.get("ipoDate", -1)] if "ipoDate" in idx else ""
+                if stype != "1" or status != "1":
+                    continue
+                exchange = bs_code.split(".")[0].upper()
+                if exchange not in ("SH", "SZ", "BJ"):
+                    continue
+                code6 = bs_code.split(".")[-1]
+                rows.append({
+                    "code": f"{exchange}{code6}",
+                    "name": name,
+                    "exchange": exchange,
+                    "list_date": ipo,
+                    "listing_status": "st" if (name.startswith("ST") or name.startswith("*ST")) else "normal",
+                })
+            return rows
+        except Exception:
+            return []
+
+    def fetch_kline_daily(self, code6: str, start: str, end: str) -> pd.DataFrame:
+        import baostock as bs
+        self._ensure_login()
+        bs_code = code6_to_baostock(code6)
+        with self._semaphore:
+            try:
+                rs = bs.query_history_k_data_plus(
+                    bs_code,
+                    "date,open,high,low,close,volume",
+                    start_date=start, end_date=end,
+                    frequency="d", adjustflag="2",  # 前复权
+                )
+                if rs.error_code != "0":
+                    return pd.DataFrame()
+                rows = []
+                while rs.next():
+                    rows.append(rs.get_row_data())
+                if not rows:
+                    return pd.DataFrame()
+                df = pd.DataFrame(rows, columns=["trade_date", "open", "high", "low", "close", "volume"])
+                return normalize_kline(df)
+            except Exception:
+                return pd.DataFrame()
+
+    def fetch_industry_map(self) -> list[dict[str, Any]]:
+        """全市场股票-行业映射。"""
+        import baostock as bs
+        self._ensure_login()
+        try:
+            rs = bs.query_stock_industry(code="", date="")
+            if rs.error_code != "0":
+                raise RuntimeError(f"query_stock_industry 失败: {rs.error_msg}")
+            fields = list(rs.fields)  # 实际字段顺序：['updateDate', 'code', 'code_name', 'industry', 'industryClassification']
+            idx = {name: i for i, name in enumerate(fields)}
+            rows = []
+            while rs.next():
+                row = rs.get_row_data()
+                industry = row[idx.get("industry", 3)] if "industry" in idx else ""
+                if not industry:
+                    continue
+                bs_code = row[idx.get("code", 1)] if "code" in idx else ""
+                code6 = bs_code.split(".")[-1]
+                classification = row[idx.get("industryClassification", 4)] if "industryClassification" in idx else ""
+                update = row[idx.get("updateDate", 0)] if "updateDate" in idx else ""
+                rows.append({
+                    "code": code6,
+                    "industry_name": industry.strip(),
+                    "industry_classification": (classification or "").strip(),
+                    "update_date": update or "",
+                })
+            return rows
+        except Exception:
+            return []