新增列数据

limit_up.py

@@ -39,6 +39,7 @@ def init_db(engine):
         `status` TINYINT NOT NULL COMMENT '状态：1-涨停，2-炸板',
         `limit_price` DECIMAL(16, 4) COMMENT '计算出的理论涨停价',
         `close` DECIMAL(16, 4) COMMENT '实际收盘价',
+        `vol` BIGINT COMMENT '成交量',
         `market` VARCHAR(20) COMMENT '所属板块',
         `ak_code` VARCHAR(10) COMMENT 'AKShare-代码',
         `ak_name` VARCHAR(50) COMMENT 'AKShare-名称',
@@ -60,9 +61,24 @@ def init_db(engine):
     """
     with engine.begin() as conn:
         conn.execute(text(create_table_sql))
+        ensure_base_columns(conn)
         ensure_ak_columns(conn)
 
 
+def ensure_base_columns(conn):
+    existing_columns = {
+        row[0]
+        for row in conn.execute(text("SHOW COLUMNS FROM `stock_limit_data`")).fetchall()
+    }
+    base_columns = {
+        "vol": "BIGINT COMMENT '成交量'",
+    }
+
+    for column_name, column_def in base_columns.items():
+        if column_name not in existing_columns:
+            conn.execute(text(f"ALTER TABLE `stock_limit_data` ADD COLUMN `{column_name}` {column_def}"))
+
+
 def ensure_ak_columns(conn):
     existing_columns = {
         row[0]
@@ -233,7 +249,7 @@ def merge_ak_limit_pool(final_df, ak_df):
         print(f"⚠️ 有 {int(name_mismatch.sum())} 条记录代码一致但名称不一致，已按代码合并 AKShare 字段。")
 
     return merged_df[[
-        "trade_date", "symbol", "ts_code", "name", "status", "limit_price", "close", "market",
+        "trade_date", "symbol", "ts_code", "name", "status", "limit_price", "close", "vol", "market",
         *ak_columns,
     ]]
 
@@ -251,7 +267,7 @@ def analyze_and_save_limits(start_date, end_date):
     query = text("""
     SELECT 
         d.trade_date, d.symbol, d.ts_code, b.name, 
-        d.high, d.close, d.pre_close, b.market
+        d.high, d.close, d.pre_close, d.vol, b.market
     FROM stock_daily d
     JOIN stock_basic b ON d.ts_code = b.ts_code
     WHERE d.trade_date > :start_date
@@ -307,7 +323,7 @@ def analyze_and_save_limits(start_date, end_date):
             if not save_df.empty:
                 final_df = save_df[[
                     'trade_date', 'symbol', 'ts_code', 'name',
-                    'status', 'limit_price', 'close', 'market'
+                    'status', 'limit_price', 'close', 'vol', 'market'
                 ]].copy()
                 final_df["trade_date"] = pd.to_datetime(final_df["trade_date"]).dt.date
                 final_df["symbol"] = final_df["symbol"].astype(str).str.zfill(6)
@@ -333,8 +349,8 @@ def analyze_and_save_limits(start_date, end_date):
 # ============================================================
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="计算并保存涨停/炸板数据")
-    parser.add_argument("--start-date", default="2026-03-31", help="开始日期，格式 YYYY-MM-DD，实际查询为大于该日期")
-    parser.add_argument("--end-date", default="2026-04-29", help="结束日期，格式 YYYY-MM-DD")
+    parser.add_argument("--start-date", default="2026-04-29", help="开始日期，格式 YYYY-MM-DD，实际查询为大于该日期")
+    parser.add_argument("--end-date", default="2026-04-30", help="结束日期，格式 YYYY-MM-DD")
     args = parser.parse_args()
 
     # 开始日期：计算从该日期的下一个交易日开始