feat(data): 数据源融合 P0 补全 + 每日增量脚本

采集层(多源各下):
- baostock: 日线全字段全量(baostock_daily_fullmarket) + 15min全市场 + 静态(基础/复权/分红/季频/三表) + 成份股
- akshare: 静态(估值/龙虎榜/大宗/融资融券/北向/指数成分/行业/股本/解禁/业绩预告)
- xtdata(miniQMT): build_daily_from_xtdata + daily_update_xtdata

数据补全 P0:
- ETF全市场: universe 扩展 沪深A股∪ETF∪基金(7414), dividend_type='front' 前复权
- 历史成份股(治幸存者偏差): index_const_hist_download 深证/国证 adjust_cni 4指数 + 中证1000/2000快照 + 新浪交叉校验
- 退市K线: baostock_delisted_download + import_delisted_to_db(实证 Day1 fetch_all_stocks 已含退市)

灌库:
- import_baostock_to_db: daily_baostock_full(5537股/1826万行,18字段)+ bs_index_constituent + bs_adjust_factor
- INSERT OR REPLACE 幂等, WAL+busy_timeout, dbbardata 不碰

每日增量 #7(用户决策A: VPS直跑):
- daily_update_static: login探针防黑名单graceful skip + LOOKBACK7 + query_stock_basic含退市 + INSERT OR REPLACE + QUERY_COUNT守48000/天

设计文档: spec(13节三层融合) + P0 plan + 数据gap设计

scripts/data_platform/probe_etf.py

@@ -0,0 +1,37 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""ETF universe + 前复权日线探针(P0 Task2.1)。
+VPS 跑: C:\\Python310\\python.exe -X utf8 probe_etf.py
+"""
+import sys
+from xtquant import xtdata as xd
+
+
+def main():
+    etf = xd.get_stock_list_in_sector("沪深ETF") or []
+    fund = xd.get_stock_list_in_sector("沪深基金") or []
+    a = xd.get_stock_list_in_sector("沪深A股") or []
+    u = list(set(a + etf + fund))
+    print(f"A={len(a)} ETF={len(etf)} fund={len(fund)} union={len(u)}")
+    print(f"sample ETF: {etf[:5]}")
+    print(f"sample fund: {fund[:5]}")
+
+    # 抽样: 510300.SH(沪深300ETF) / 513050.SH(中概互联网ETF) / 159919.SZ(300ETF)
+    samples = ["510300.SH", "513050.SH", "159919.SZ"]
+    r = xd.get_market_data_ex([], samples, period="1d",
+                              start_time="20240101", end_time="20260721",
+                              dividend_type="front")
+    for sym in samples:
+        df = r.get(sym) if r else None
+        bars = 0 if df is None else len(df)
+        tail_close = None if df is None or not len(df) else float(df["close"].iloc[-1])
+        head_date = None if df is None or not len(df) else str(df.index[0])[:8]
+        tail_date = None if df is None or not len(df) else str(df.index[-1])[:8]
+        nan_close = None if df is None else bool(df["close"].isnull().any())
+        print(f"{sym}: bars={bars} date=[{head_date}~{tail_date}] tail_close={tail_close} nan_close={nan_close}")
+
+    sys.stdout.flush()
+
+
+if __name__ == "__main__":
+    main()