feat: enrich daily bar schema with valuation/status fields + VWAP

Batch download now pulls baostock's preclose, turn, pctChg, tradestatus,
isST, and peTTM/pbMRQ/psTTM/pcfNcfTTM on top of OHLCV+amount, plus a
derived daily VWAP (amount/volume). VWAP is raw-price scale and not
comparable with adjusted OHLC under qfq/hfq — documented in the schema.

Richer fields live only in the batch path (download_daily_batch ->
download_universe); single-symbol download_daily keeps the legacy
8-column schema that test_downloader.py pins. Also flags intraday/L1-L2
microstructure data as a future phase in the README roadmap.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

data/downloader.py

@@ -9,8 +9,27 @@ logger = logging.getLogger(__name__)
 
 # Map the adjust argument to baostock's adjustflag codes.
 _BAOSTOCK_ADJUST = {"qfq": "2", "hfq": "1", "": "3", "none": "3"}
-_BAOSTOCK_FIELDS = "date,open,high,low,close,volume,amount"
-_OHLCV = ["open", "high", "low", "close", "volume", "amount"]
+
+# Richer field set requested by the batch downloader. On top of OHLCV+amount we
+# pull baostock's preclose, turnover rate, daily % change, trade/ST status, and
+# the four valuation ratios, then derive a daily VWAP (amount / volume).
+_BATCH_FIELDS = (
+    "date,open,high,low,close,preclose,volume,amount,turn,pctChg,"
+    "tradestatus,isST,peTTM,pbMRQ,psTTM,pcfNcfTTM"
+)
+# Every batch field except ``date`` is numeric (flags included: 0/1 strings).
+_BATCH_NUMERIC = [
+    "open", "high", "low", "close", "preclose", "volume", "amount",
+    "turn", "pctChg", "tradestatus", "isST",
+    "peTTM", "pbMRQ", "psTTM", "pcfNcfTTM",
+]
+# Output column order; ``vwap`` is derived (inserted right after ``amount``).
+_BATCH_COLUMNS = [
+    "symbol", "date",
+    "open", "high", "low", "close", "preclose", "volume", "amount", "vwap",
+    "turn", "pctChg", "tradestatus", "isST",
+    "peTTM", "pbMRQ", "psTTM", "pcfNcfTTM",
+]
 
 
 class _SessionLost(Exception):
@@ -163,7 +182,7 @@ def download_daily_batch(
         """One baostock query; returns df, or None (no data), or raises _SessionLost."""
         code = f"{symbol[:2]}.{symbol[2:]}"
         rs = bs.query_history_k_data_plus(
-            code=code, fields=_BAOSTOCK_FIELDS,
+            code=code, fields=_BATCH_FIELDS,
             start_date=start, end_date=end, frequency="d", adjustflag=flag,
         )
         if rs.error_code != "0":
@@ -176,12 +195,14 @@ def download_daily_batch(
             rows.append(rs.get_row_data())
         if not rows:
             return None
-        df = pd.DataFrame(rows, columns=["date", *_OHLCV])
+        df = pd.DataFrame(rows, columns=["date", *_BATCH_NUMERIC])
         # Suspended-trading days come back as empty strings; coerce to NaN
         # rather than crashing the whole symbol.
-        df[_OHLCV] = df[_OHLCV].apply(pd.to_numeric, errors="coerce")
+        df[_BATCH_NUMERIC] = df[_BATCH_NUMERIC].apply(pd.to_numeric, errors="coerce")
+        # Daily VWAP = turnover (yuan) / shares; NaN when no volume (suspended).
+        df["vwap"] = (df["amount"] / df["volume"]).where(df["volume"] > 0)
         df["symbol"] = symbol
-        return df[["symbol", "date", *_OHLCV]]
+        return df[_BATCH_COLUMNS]
 
     bs.login()
     try: