增加了moneyflow表格导入模块。

quantitative_data/importer.py

@@ -766,6 +766,179 @@ def import_daily_basic_by_date(
     logger.info("  每日指标导入完成")
 
 
+# ============================================================
+# 4.1 导入资金流向 (moneyflow)
+# ============================================================
+
+def import_moneyflow(
+    ts_code: Optional[str] = None,
+    trade_date: Optional[str] = None,
+    start_date: Optional[str] = None,
+    end_date: Optional[str] = None,
+    conn=None,
+) -> int:
+    """
+    导入个股资金流向 (moneyflow)
+    Tushare: moneyflow
+
+    调用方式 (互斥，按优先级生效):
+    1. 按单日全市场导入 (推荐，一次拉取全市场):
+         import_moneyflow(trade_date="2026-08-14")
+         对应示例: pro.moneyflow(trade_date='20260814')
+    2. 按单只股票导入:
+         import_moneyflow(ts_code="000001.SZ", start_date="2026-01-01", end_date="2026-08-14")
+         对应示例: pro.moneyflow(ts_code='000001.SZ', start_date='20260101', end_date='20260814')
+    3. 按交易日批量全市场导入请配合 import_moneyflow_by_date 使用
+
+    返回: 导入的记录数
+    """
+    pro = get_ts_pro()
+    own_conn = conn is None
+    if own_conn:
+        conn = get_pg_connection()
+
+    log_desc = ""
+    try:
+        # ---- 构建 moneyflow 请求参数 ----
+        kwargs = {}
+        if trade_date:
+            # 按单日 (全市场)
+            kwargs["trade_date"] = str(trade_date).replace("-", "")
+            log_desc = f"交易日 {kwargs['trade_date']}"
+        elif ts_code:
+            # 按单只股票 (日期范围)
+            if start_date is None:
+                start_date = START_DATE
+            if end_date is None:
+                end_date = END_DATE
+            kwargs["ts_code"] = ts_code
+            kwargs["start_date"] = start_date.replace("-", "")
+            kwargs["end_date"] = end_date.replace("-", "")
+            log_desc = f"{ts_code} ({start_date} ~ {end_date})"
+        else:
+            logger.warning(
+                "  moneyflow: 请指定 trade_date (交易日, 如 '2026-08-14') 或 ts_code (股票代码)"
+            )
+            return 0
+
+        logger.info("=" * 60)
+        logger.info(f"[4.1] 导入资金流向 (moneyflow): {log_desc}")
+
+        def fetch():
+            return pro.moneyflow(**kwargs)
+
+        df = fetch_with_retry(fetch, max_retries=3)
+        if df is None or df.empty:
+            logger.warning(f"  moneyflow ({log_desc}): 未获取到数据")
+            return 0
+
+        df = normalize_columns(df)
+
+        # 转换日期列 (YYYYMMDD -> DATE)
+        if "trade_date" in df.columns:
+            df["trade_date"] = pd.to_datetime(df["trade_date"], format="%Y%m%d", errors="coerce")
+
+        # 数值列安全转换 (NaN -> None)
+        numeric_cols = [
+            "buy_sm_vol", "buy_sm_amount", "sell_sm_vol", "sell_sm_amount",
+            "buy_md_vol", "buy_md_amount", "sell_md_vol", "sell_md_amount",
+            "buy_lg_vol", "buy_lg_amount", "sell_lg_vol", "sell_lg_amount",
+            "buy_elg_vol", "buy_elg_amount", "sell_elg_vol", "sell_elg_amount",
+            "net_mf_vol", "net_mf_amount",
+        ]
+        for col in numeric_cols:
+            if col in df.columns:
+                df[col] = pd.to_numeric(df[col], errors="coerce")
+
+        conflict_cols = ["ts_code", "trade_date"]
+        return batch_insert("moneyflow", df, conn, conflict_cols)
+
+    finally:
+        if own_conn:
+            conn.close()
+
+
+def import_moneyflow_by_date(
+    start_date: Optional[str] = None,
+    end_date: Optional[str] = None,
+    sleep_interval: float = 0.3,
+):
+    """
+    按交易日批量导入资金流向 (全市场)
+    Tushare moneyflow 接口可按交易日获取全市场数据，比较高效
+
+    用法:
+        import_moneyflow_by_date(start_date="2010-01-01", end_date="2025-12-31")
+
+    返回: 失败的交易日列表
+    """
+    if start_date is None:
+        start_date = START_DATE
+    if end_date is None:
+        end_date = END_DATE
+
+    logger.info("=" * 60)
+    logger.info(f"[4.1] 导入资金流向 (moneyflow): {start_date} ~ {end_date}")
+
+    # 获取交易日列表
+    conn = get_pg_connection()
+    try:
+        cursor = conn.cursor()
+        cursor.execute(
+            """
+            SELECT DISTINCT cal_date FROM trade_cal
+            WHERE is_open = 1
+              AND cal_date >= %s AND cal_date <= %s
+            ORDER BY cal_date
+            """,
+            (start_date, end_date),
+        )
+        trade_dates = [row[0].strftime("%Y%m%d") for row in cursor.fetchall()]
+        cursor.close()
+    finally:
+        conn.close()
+
+    total = len(trade_dates)
+    if total == 0:
+        logger.warning(f"  日期范围 {start_date} ~ {end_date} 内无交易日")
+        return []
+
+    logger.info(f"  共 {total} 个交易日")
+
+    conn = get_pg_connection()
+    success_count = 0
+    fail_list = []
+    for i, td in enumerate(trade_dates, 1):
+        try:
+            pro = get_ts_pro()
+
+            def fetch_moneyflow():
+                return pro.moneyflow(trade_date=td)
+
+            df = fetch_with_retry(fetch_moneyflow, max_retries=3)
+            if df is not None and not df.empty:
+                df = normalize_columns(df)
+                if "trade_date" in df.columns:
+                    df["trade_date"] = pd.to_datetime(df["trade_date"], format="%Y%m%d", errors="coerce")
+                conflict_cols = ["ts_code", "trade_date"]
+                batch_insert("moneyflow", df, conn, conflict_cols)
+                success_count += 1
+        except Exception as e:
+            logger.warning(f"  [{td}] 导入失败: {e}")
+            fail_list.append(td)
+            conn.rollback()
+
+        if i % 20 == 0 or i == total:
+            logger.info(f"  进度: {i}/{total} 成功={success_count} 失败={len(fail_list)}")
+        time.sleep(sleep_interval)
+
+    conn.close()
+    logger.info(f"  资金流向导入完成: 成功 {success_count}/{total}")
+    if fail_list:
+        logger.warning(f"  失败日期({len(fail_list)}): {fail_list[:20]}...")
+    return fail_list
+
+
 # ============================================================
 # 5. 导入复权因子
 # ============================================================
@@ -1385,9 +1558,10 @@ def full_import(
     3. 交易日历
     4. 日线行情
     5. 每日指标(估值)
-    6. 复权因子
+    6. 资金流向 (moneyflow)
-    7. 财务数据 (可选)
+    7. 复权因子
-    8. 指数日线行情
+    8. 财务数据 (可选)
+    9. 指数日线行情
 
     参数:
     - start_date, end_date: 数据范围
@@ -1430,6 +1604,9 @@ def full_import(
     # Step 4: 每日指标 (按日期导入)
     import_daily_basic_by_date(start_date, end_date)
 
+    # Step 4.1: 资金流向 (按交易日导入)
+    import_moneyflow_by_date(start_date, end_date)
+
     # Step 5: 复权因子
     import_adj_factor_batch(stock_codes, start_date, end_date)
 
@@ -1500,6 +1677,7 @@ def check_table_summary(conn=None):
             ("trade_cal", (("trade_cal", "cal_date"),)),
             ("daily", (("daily", "trade_date"),)),
             ("daily_basic", (("daily_basic", "trade_date"),)),
+            ("moneyflow", (("moneyflow", "trade_date"),)),
             ("adj_factor", (("adj_factor", "trade_date"),)),
             ("income", (("income", "end_date"),)),
             ("balancesheet", (("balancesheet", "end_date"),)),

quantitative_data/incremental_import.py

@@ -18,7 +18,6 @@
     - 行情类表按 MAX(trade_date)+1 天 → 昨天 增量拉取
     - daily / daily_basic 走按交易日全市场模式（快）；adj_factor 走按股票批量
     - 财务表按 MAX(end_date) 往前推 400 天 → 昨天（覆盖新公告的季度报告，UPSERT 幂等）
-    - moneyflow 表暂未纳入（新版 importer 无对应导入函数，后续需要再补）
 """
 import argparse
 import logging
@@ -32,6 +31,7 @@ from importer import (
     import_stock_basic,
     import_daily_by_date,
     import_daily_basic_by_date,
+    import_moneyflow_by_date,
     import_adj_factor_batch,
     import_index_daily,
     import_financial_statements,
@@ -49,6 +49,7 @@ logger.setLevel(logging.INFO)
 TABLE_SPECS = {
     "daily": ("trade_date", ["ts_code", "trade_date"]),
     "daily_basic": ("trade_date", ["ts_code", "trade_date"]),
+    "moneyflow": ("trade_date", ["ts_code", "trade_date"]),
     "adj_factor": ("trade_date", ["ts_code", "trade_date"]),
     "index_daily": ("trade_date", ["ts_code", "trade_date"]),
     "income": ("end_date", ["ts_code", "end_date", "report_type"]),
@@ -105,6 +106,7 @@ def run_daily(end_date, dry_run, limit):
     for table, date_col in [
         ("daily", "trade_date"),
         ("daily_basic", "trade_date"),
+        ("moneyflow", "trade_date"),
         ("adj_factor", "trade_date"),
         ("index_daily", "trade_date"),
     ]:
@@ -129,6 +131,8 @@ def run_daily(end_date, dry_run, limit):
                 import_daily_by_date(start, end_date)
             elif table == "daily_basic":
                 import_daily_basic_by_date(start, end_date)
+            elif table == "moneyflow":
+                import_moneyflow_by_date(start, end_date)
             elif table == "adj_factor":
                 import_adj_factor_batch(codes, start, end_date)
             elif table == "index_daily":