refactor: 重构 API 接口模块，整合为 api_wrappers 目录结构

- 将独立 API 模块 (daily, stock_basic, trade_cal) 整合至 api_wrappers/
- 重写 sync.py 使用新的 wrapper 结构，支持更多同步功能
- 更新测试文件适配新的模块结构
- 添加 pytest.ini 配置文件

src/data/storage.py

@@ -1,4 +1,5 @@
 """Simplified HDF5 storage for data persistence."""
+
 import os
 import pandas as pd
 from pathlib import Path
@@ -47,7 +48,9 @@ class Storage:
                     # Merge with existing data
                     existing = store[name]
                     combined = pd.concat([existing, data], ignore_index=True)
-                    combined = combined.drop_duplicates(subset=["ts_code", "trade_date"], keep="last")
+                    combined = combined.drop_duplicates(
+                        subset=["ts_code", "trade_date"], keep="last"
+                    )
                     store.put(name, combined, format="table")
 
             print(f"[Storage] Saved {len(data)} rows to {file_path}")
@@ -57,10 +60,13 @@ class Storage:
             print(f"[Storage] Error saving {name}: {e}")
             return {"status": "error", "error": str(e)}
 
-    def load(self, name: str,
-             start_date: Optional[str] = None,
-             end_date: Optional[str] = None,
-             ts_code: Optional[str] = None) -> pd.DataFrame:
+    def load(
+        self,
+        name: str,
+        start_date: Optional[str] = None,
+        end_date: Optional[str] = None,
+        ts_code: Optional[str] = None,
+    ) -> pd.DataFrame:
         """Load data from HDF5 file.
 
         Args:
@@ -80,14 +86,25 @@ class Storage:
 
         try:
             with pd.HDFStore(file_path, mode="r") as store:
-                if name not in store.keys():
+                keys = store.keys()
+                # Handle both '/daily' and 'daily' keys
+                actual_key = None
+                if name in keys:
+                    actual_key = name
+                elif f"/{name}" in keys:
+                    actual_key = f"/{name}"
+
+                if actual_key is None:
                     return pd.DataFrame()
 
-                data = store[name]
+                data = store[actual_key]
 
                 # Apply filters
                 if start_date and end_date and "trade_date" in data.columns:
-                    data = data[(data["trade_date"] >= start_date) & (data["trade_date"] <= end_date)]
+                    data = data[
+                        (data["trade_date"] >= start_date)
+                        & (data["trade_date"] <= end_date)
+                    ]
 
                 if ts_code and "ts_code" in data.columns:
                     data = data[data["ts_code"] == ts_code]