refactor: class-based alpha factory + month-partitioned data pipeline

Replace the old signal/strategy/backtest modules with a decoupled
data → alpha → combo pipeline (parquet between phases, .pq extension).

Alphas:
- BaseAlpha + @register_alpha factory/plugin registry; one file per
  built-in (reversal, reversal_vol, momentum); external alphas via
  --alpha-module. Alphas are z-scored position weights, not predictors.

Data:
- baostock primary / akshare fallback, treated consistently.
- New --universe all (~5000 A-shares via query_all_stock, filtered).
- login-once batch downloader; empty-string OHLCV coerced to NaN.
- Month-partitioned dataset {output_dir}/{universe}/month=YYYY-MM/*.pq
  with chunked durability flushes; --data-path is the dataset dir.

CLI logs at INFO by default (--log-level) so progress is visible.
Docs (README, CLAUDE.md) updated incl. pipeline diagram and roadmap
TODOs for portfolio construction / backtest / paper trading.

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

data/universe.py

@@ -1,36 +1,16 @@
-"""CSI 300 (HS300) and CSI 500 (ZZ500) universe helpers."""
+"""CSI 300 (HS300), CSI 500 (ZZ500), and full A-share universe helpers."""
 import logging
+from datetime import date, timedelta
 
 import baostock as bs
 import pandas as pd
 
 logger = logging.getLogger(__name__)
 
-# First 30 HS300 constituents (large caps) in 'shXXXXXX' / 'szXXXXXX' format.
-# Hardcoded for fast, deterministic smoke tests. Use get_hs300_stocks() for the
-# live, full list — downloading daily bars for all ~300 takes roughly 10 minutes.
-SYMBOLS = [
-    "sh600000", "sh600009", "sh600010", "sh600028", "sh600030",
-    "sh600036", "sh600048", "sh600050", "sh600104", "sh600276",
-    "sh600309", "sh600519", "sh600585", "sh600887", "sh600900",
-    "sh601012", "sh601166", "sh601288", "sh601318", "sh601398",
-    "sh601628", "sh601668", "sh601857", "sh601888", "sh601988",
-    "sz000001", "sz000002", "sz000333", "sz000651", "sz000858",
-]
-
-
-# First 30 CSI 500 (ZZ500) constituents (mid/small caps) in 'shXXXXXX' /
-# 'szXXXXXX' format. Hardcoded for fast, deterministic smoke tests. Use
-# get_zz500_stocks() for the live, full list. Mean reversion tends to be
-# stronger in these smaller caps than in the HS300 large caps.
-CSI500_SYMBOLS = [
-    "sh600006", "sh600008", "sh600017", "sh600020", "sh600021",
-    "sh600026", "sh600037", "sh600039", "sh600053", "sh600056",
-    "sh600060", "sh600061", "sh600062", "sh600073", "sh600089",
-    "sh600095", "sh600118", "sh600125", "sh600126", "sh600143",
-    "sh600153", "sh600160", "sh600169", "sh600176", "sh600183",
-    "sz000009", "sz000012", "sz000021", "sz000025", "sz000027",
-]
+# A-share code patterns (baostock dotted form): SH main/STAR (sh.6xxxxx),
+# SZ main/SME (sz.0xxxxx), ChiNext (sz.3xxxxx). Excludes indices and B-shares.
+_ASHARE_RE = r"^sh\.6\d{5}$|^sz\.[03]\d{5}$"
+_SZ_INDEX_RE = r"^sz\.399"
 
 
 def get_hs300_stocks() -> pd.DataFrame:
@@ -69,3 +49,44 @@ def get_zz500_stocks() -> pd.DataFrame:
     df = pd.DataFrame(stocks, columns=["code", "name", "date"])
     df["code"] = df["code"].str.replace(".", "", regex=False)
     return df
+
+
+def get_all_stocks(day: str = "") -> pd.DataFrame:
+    """Fetch every listed A-share from baostock's all-stock snapshot.
+
+    Queries ``query_all_stock`` for a single trading day and keeps only A-shares
+    (SH main/STAR, SZ main/SME/ChiNext), dropping indices and B-shares. If the
+    given day is a non-trading day baostock returns nothing, so we walk back up
+    to 10 days to land on the most recent trading day.
+
+    Args:
+        day: ``YYYY-MM-DD`` snapshot day; defaults to today (walks back to the
+            last trading day).
+
+    Returns:
+        DataFrame with columns ``code`` (e.g. ``sh600000``), ``name``.
+    """
+    start = date.fromisoformat(day) if day else date.today()
+    bs.login()
+    try:
+        rows: list = []
+        fields: list = []
+        for back in range(11):
+            probe = (start - timedelta(days=back)).isoformat()
+            rs = bs.query_all_stock(day=probe)
+            fields = rs.fields
+            while rs.next():
+                rows.append(rs.get_row_data())
+            if rows:
+                logger.info("query_all_stock: %d rows on %s", len(rows), probe)
+                break
+    finally:
+        bs.logout()
+
+    df = pd.DataFrame(rows, columns=fields)
+    code = df["code"]
+    keep = code.str.match(_ASHARE_RE) & ~code.str.match(_SZ_INDEX_RE)
+    df = df[keep].copy()
+    df["code"] = df["code"].str.replace(".", "", regex=False)
+    df = df.rename(columns={"code_name": "name"})
+    return df[["code", "name"]].reset_index(drop=True)