refactor: 提取数据同步逻辑为抽象基类

新增 base_sync.py 模块，提供三层抽象结构统一数据同步流程：
- BaseDataSync: 所有同步类型的基础抽象（客户端、股票代码获取、交易日历）
- StockBasedSync: 按股票同步抽象类（适用于 daily, pro_bar）
- DateBasedSync: 按日期同步抽象类（适用于 bak_basic）

src/data/sync.py

@@ -3,7 +3,8 @@
 该模块作为数据同步的调度中心，统一管理各类型数据的同步流程。
 具体的同步逻辑已迁移到对应的 api_xxx.py 文件中：
 - api_daily.py: 日线数据同步 (DailySync 类)
-- api_bak_basic.py: 历史股票列表同步
+- api_bak_basic.py: 历史股票列表同步 (BakBasicSync 类)
+- api_pro_bar.py: Pro Bar 数据同步 (ProBarSync 类)
 - api_stock_basic.py: 股票基本信息同步
 - api_trade_cal.py: 交易日历同步
 
@@ -30,6 +31,7 @@ import pandas as pd
 from src.data.api_wrappers import sync_all_stocks
 from src.data.api_wrappers.api_daily import sync_daily, preview_daily_sync
 from src.data.api_wrappers.api_pro_bar import sync_pro_bar
+from src.data.api_wrappers.api_bak_basic import sync_bak_basic
 
 
 def preview_sync(
@@ -135,30 +137,31 @@ def sync_all_data(
     dry_run: bool = False,
 ) -> Dict[str, pd.DataFrame]:
     """同步所有数据类型（每日同步）。
-        该函数按顺序同步所有可用的数据类型：
-        1. 交易日历 (sync_trade_cal_cache)
-        2. 股票基本信息 (sync_all_stocks)
-        3. 日线市场数据 (sync_all)
-        4. 历史股票列表 (sync_bak_basic)
 
-        注意：名称变更 (namechange) 不在自动同步中，如需同步请手动调用。
+    该函数按顺序同步所有可用的数据类型：
+    1. 交易日历 (sync_trade_cal_cache)
+    2. 股票基本信息 (sync_all_stocks)
+    3. Pro Bar 数据 (sync_pro_bar)
+    4. 历史股票列表 (sync_bak_basic)
 
-        Args:
-            force_full: 若为 True，强制所有数据类型完整重载
-            max_workers: 日线数据同步的工作线程数（默认: 10）
-            dry_run: 若为 True，仅显示将要同步的内容，不写入数据
+    注意：名称变更 (namechange) 不在自动同步中，如需同步请手动调用。
 
-        Returns:
-            映射数据类型到同步结果的字典
+    Args:
+        force_full: 若为 True，强制所有数据类型完整重载
+        max_workers: 日线数据同步的工作线程数（默认: 10）
+        dry_run: 若为 True，仅显示将要同步的内容，不写入数据
 
-        Example:
-            >>> result = sync_all_data()
-            >>>
-            >>> # 强制完整重载
-            >>> result = sync_all_data(force_full=True)
-            >>>
-            >>> # Dry run
-            >>> result = sync_all_data(dry_run=True)
+    Returns:
+        映射数据类型到同步结果的字典
+
+    Example:
+        >>> result = sync_all_data()
+        >>>
+        >>> # 强制完整重载
+        >>> result = sync_all_data(force_full=True)
+        >>>
+        >>> # Dry run
+        >>> result = sync_all_data(dry_run=True)
     """
     results: Dict[str, pd.DataFrame] = {}
 
@@ -167,47 +170,29 @@ def sync_all_data(
     print("=" * 60)
 
     # 1. Sync trade calendar (always needed first)
-    print("\n[1/6] Syncing trade calendar cache...")
+    print("\n[1/4] Syncing trade calendar cache...")
     try:
         from src.data.api_wrappers import sync_trade_cal_cache
 
         sync_trade_cal_cache()
         results["trade_cal"] = pd.DataFrame()
-        print("[1/6] Trade calendar: OK")
+        print("[1/4] Trade calendar: OK")
     except Exception as e:
-        print(f"[1/6] Trade calendar: FAILED - {e}")
+        print(f"[1/4] Trade calendar: FAILED - {e}")
         results["trade_cal"] = pd.DataFrame()
 
     # 2. Sync stock basic info
-    print("\n[2/6] Syncing stock basic info...")
+    print("\n[2/4] Syncing stock basic info...")
     try:
         sync_all_stocks()
         results["stock_basic"] = pd.DataFrame()
-        print("[2/6] Stock basic: OK")
+        print("[2/4] Stock basic: OK")
     except Exception as e:
-        print(f"[2/6] Stock basic: FAILED - {e}")
+        print(f"[2/4] Stock basic: FAILED - {e}")
         results["stock_basic"] = pd.DataFrame()
 
-    # # 3. Sync daily market data
-    # print("\n[3/6] Syncing daily market data...")
-    # try:
-    #     daily_result = sync_daily(
-    #         force_full=force_full,
-    #         max_workers=max_workers,
-    #         dry_run=dry_run,
-    #     )
-    #     results["daily"] = (
-    #         pd.concat(daily_result.values(), ignore_index=True)
-    #         if daily_result
-    #         else pd.DataFrame()
-    #     )
-    #     print("[3/6] Daily data: OK")
-    # except Exception as e:
-    #     print(f"[3/6] Daily data: FAILED - {e}")
-    #     results["daily"] = pd.DataFrame()
-
-    # 4. Sync Pro Bar data
-    print("\n[4/6] Syncing Pro Bar data (with adj, tor, vr)...")
+    # 3. Sync Pro Bar data
+    print("\n[3/4] Syncing Pro Bar data (with adj, tor, vr)...")
     try:
         pro_bar_result = sync_pro_bar(
             force_full=force_full,
@@ -219,87 +204,19 @@ def sync_all_data(
             if pro_bar_result
             else pd.DataFrame()
         )
-        print(f"[4/6] Pro Bar data: OK ({len(results['pro_bar'])} records)")
+        print(f"[3/4] Pro Bar data: OK ({len(results['pro_bar'])} records)")
     except Exception as e:
-        print(f"[4/6] Pro Bar data: FAILED - {e}")
+        print(f"[3/4] Pro Bar data: FAILED - {e}")
         results["pro_bar"] = pd.DataFrame()
 
-    # 5. Sync stock historical list (bak_basic)
-    print("\n[5/6] Syncing stock historical list (bak_basic)...")
-    try:
-        bak_basic_result = sync_bak_basic(force_full=force_full)
-        results["bak_basic"] = bak_basic_result
-        print(f"[5/6] Bak basic: OK ({len(bak_basic_result)} records)")
-    except Exception as e:
-        print(f"[5/6] Bak basic: FAILED - {e}")
-        results["bak_basic"] = pd.DataFrame()
-
-    # Summary
-    print("\n" + "=" * 60)
-    print("[sync_all_data] Sync Summary")
-    print("=" * 60)
-    for data_type, df in results.items():
-        print(f"  {data_type}: {len(df)} records")
-    print("=" * 60)
-    print("\nNote: namechange is NOT in auto-sync. To sync manually:")
-    print("  from src.data.api_wrappers import sync_namechange")
-    print("  sync_namechange(force=True)")
-
-    return results
-    results: Dict[str, pd.DataFrame] = {}
-
-    print("\n" + "=" * 60)
-    print("[sync_all_data] Starting full data synchronization...")
-    print("=" * 60)
-
-    # 1. Sync trade calendar (always needed first)
-    print("\n[1/5] Syncing trade calendar cache...")
-    try:
-        from src.data.api_wrappers import sync_trade_cal_cache
-
-        sync_trade_cal_cache()
-        results["trade_cal"] = pd.DataFrame()
-        print("[1/5] Trade calendar: OK")
-    except Exception as e:
-        print(f"[1/5] Trade calendar: FAILED - {e}")
-        results["trade_cal"] = pd.DataFrame()
-
-    # 2. Sync stock basic info
-    print("\n[2/5] Syncing stock basic info...")
-    try:
-        sync_all_stocks()
-        results["stock_basic"] = pd.DataFrame()
-        print("[2/5] Stock basic: OK")
-    except Exception as e:
-        print(f"[2/5] Stock basic: FAILED - {e}")
-        results["stock_basic"] = pd.DataFrame()
-
-    # 3. Sync daily market data
-    print("\n[3/5] Syncing daily market data...")
-    try:
-        daily_result = sync_daily(
-            force_full=force_full,
-            max_workers=max_workers,
-            dry_run=dry_run,
-        )
-        results["daily"] = (
-            pd.concat(daily_result.values(), ignore_index=True)
-            if daily_result
-            else pd.DataFrame()
-        )
-        print("[3/5] Daily data: OK")
-    except Exception as e:
-        print(f"[3/5] Daily data: FAILED - {e}")
-        results["daily"] = pd.DataFrame()
-
     # 4. Sync stock historical list (bak_basic)
-    print("\n[4/5] Syncing stock historical list (bak_basic)...")
+    print("\n[4/4] Syncing stock historical list (bak_basic)...")
     try:
         bak_basic_result = sync_bak_basic(force_full=force_full)
         results["bak_basic"] = bak_basic_result
-        print(f"[4/5] Bak basic: OK ({len(bak_basic_result)} records)")
+        print(f"[4/4] Bak basic: OK ({len(bak_basic_result)} records)")
     except Exception as e:
-        print(f"[4/5] Bak basic: FAILED - {e}")
+        print(f"[4/4] Bak basic: FAILED - {e}")
         results["bak_basic"] = pd.DataFrame()
 
     # Summary
@@ -316,10 +233,6 @@ def sync_all_data(
     return results
 
 
-# 保留向后兼容的导入
-from src.data.api_wrappers import sync_bak_basic
-
-
 if __name__ == "__main__":
     print("=" * 60)
     print("Data Sync Module")