refactor(factor): 完全重构因子计算框架 - 引入DSL表达式系统

- 删除旧因子框架：移除 base.py、composite.py、data_loader.py、data_spec.py
  及所有子模块（momentum、financial、quality、sentiment等）
- 新增DSL表达式系统：实现 factor DSL 编译器和翻译器
  - dsl.py: 领域特定语言定义
  - compiler.py: AST编译与优化
  - translator.py: Polars表达式翻译
  - api.py: 统一API接口
- 新增数据路由层：data_router.py 实现字段到表的动态路由
- 新增API封装：api_pro_bar.py 提供pro_bar数据接口
- 更新执行引擎：engine.py 适配新的DSL架构
- 重构测试体系：删除旧测试，新增 test_dsl_promotion.py、
  test_factor_integration.py、test_pro_bar.py
- 清理文档：删除8个过时文档（factor_design、db_sync_guide等）

src/data/sync.py

@@ -29,6 +29,7 @@ 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
 
 
 def preview_sync(
@@ -134,7 +135,6 @@ 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)
@@ -146,13 +146,12 @@ def sync_all_data(
         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    Returns:
-            映射数据类型，不写入数据
+            dry_run: 若为 True，仅显示将要同步的内容，不写入数据
 
-    到同步结果的字典
+        Returns:
+            映射数据类型到同步结果的字典
 
         Example:
-            >>> # 同步所有数据（增量）
             >>> result = sync_all_data()
             >>>
             >>> # 强制完整重载
@@ -167,6 +166,92 @@ def sync_all_data(
     print("[sync_all_data] Starting full data synchronization...")
     print("=" * 60)
 
+    # 1. Sync trade calendar (always needed first)
+    print("\n[1/6] 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")
+    except Exception as e:
+        print(f"[1/6] Trade calendar: FAILED - {e}")
+        results["trade_cal"] = pd.DataFrame()
+
+    # 2. Sync stock basic info
+    print("\n[2/6] Syncing stock basic info...")
+    try:
+        sync_all_stocks()
+        results["stock_basic"] = pd.DataFrame()
+        print("[2/6] Stock basic: OK")
+    except Exception as e:
+        print(f"[2/6] 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)...")
+    try:
+        pro_bar_result = sync_pro_bar(
+            force_full=force_full,
+            max_workers=max_workers,
+            dry_run=dry_run,
+        )
+        results["pro_bar"] = (
+            pd.concat(pro_bar_result.values(), ignore_index=True)
+            if pro_bar_result
+            else pd.DataFrame()
+        )
+        print(f"[4/6] Pro Bar data: OK ({len(results['pro_bar'])} records)")
+    except Exception as e:
+        print(f"[4/6] 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: