feat(data): 封装ST股票列表接口(stock_st)

- 新增 api_stock_st.py，实现ST股票数据获取和日期遍历同步
- 更新 sync.py，将ST股票同步加入第7步流程
- 移除 base_sync.py 中未使用的 get_last_n_trading_days 导入

src/data/api_wrappers/__init__.py

@@ -11,16 +11,19 @@ Available APIs:
     - api_trade_cal: Trading calendar (交易日历)
     - api_namechange: Stock name change history (股票曾用名)
     - api_bak_basic: Stock historical list (股票历史列表)
+    - api_stock_st: ST stock list (ST股票列表)
 
 Example:
     >>> from src.data.api_wrappers import get_daily, get_stock_basic, get_trade_cal, get_bak_basic
     >>> from src.data.api_wrappers import get_pro_bar, sync_pro_bar, get_daily_basic, sync_daily_basic
+    >>> from src.data.api_wrappers import get_stock_st, sync_stock_st
     >>> data = get_daily('000001.SZ', start_date='20240101', end_date='20240131')
     >>> pro_data = get_pro_bar('000001.SZ', start_date='20240101', end_date='20240131')
     >>> daily_basic = get_daily_basic(trade_date='20240101')
     >>> stocks = get_stock_basic()
     >>> calendar = get_trade_cal('20240101', '20240131')
     >>> bak_basic = get_bak_basic(trade_date='20240101')
+    >>> stock_st = get_stock_st(trade_date='20240101')
 """
 
 from src.data.api_wrappers.api_daily import (
@@ -49,6 +52,11 @@ from src.data.api_wrappers.financial_data.api_income import (
 from src.data.api_wrappers.api_bak_basic import get_bak_basic, sync_bak_basic
 from src.data.api_wrappers.api_namechange import get_namechange, sync_namechange
 from src.data.api_wrappers.api_stock_basic import get_stock_basic, sync_all_stocks
+from src.data.api_wrappers.api_stock_st import (
+    get_stock_st,
+    sync_stock_st,
+    StockSTSync,
+)
 from src.data.api_wrappers.api_trade_cal import (
     get_trade_cal,
     get_trading_days,
@@ -92,4 +100,8 @@ __all__ = [
     "get_first_trading_day",
     "get_last_trading_day",
     "sync_trade_cal_cache",
+    # ST stock list
+    "get_stock_st",
+    "sync_stock_st",
+    "StockSTSync",
 ]

src/data/api_wrappers/api.md

@@ -565,4 +565,57 @@ df = pro.query('daily_basic', ts_code='', trade_date='20180726',fields='ts_code,
 16    300718.SZ   20180726        17.6612          0.92   32.0239   3.8661
 17    000708.SZ   20180726         0.5575          0.70   10.3674   1.0276
 18    002626.SZ   20180726         0.6187          0.83   22.7580   4.2446
-19    600816.SH   20180726         0.6745          0.65   11.0778   3.2214
+19    600816.SH   20180726         0.6745          0.65   11.0778   3.2214
+
+
+ST股票列表
+接口：stock_st，可以通过数据工具调试和查看数据。
+描述：获取ST股票列表，可根据交易日期获取历史上每天的ST列表
+权限：3000积分起
+提示：每天上午9:20更新，单次请求最大返回1000行数据，可循环提取,本接口数据从20160101开始,太早历史无法补齐
+
+
+
+输入参数
+
+名称	类型	必选	描述
+ts_code	str	N	股票代码
+trade_date	str	N	交易日期（格式：YYYYMMDD下同）
+start_date	str	N	开始时间
+end_date	str	N	结束时间
+
+
+输出参数
+
+名称	类型	默认显示	描述
+ts_code	str	Y	股票代码
+name	str	Y	股票名称
+trade_date	str	Y	交易日期
+type	str	Y	类型
+type_name	str	Y	类型名称
+
+
+接口用法
+
+
+pro = ts.pro_api()
+
+#获取20250813日所有的ST股票
+df = pro.stock_st(trade_date='20250813')
+
+
+
+数据样例
+
+             ts_code   name trade_date type type_name
+0    300313.SZ  *ST天山   20250813   ST     风险警示板
+1    605081.SH  *ST太和   20250813   ST     风险警示板
+2    300391.SZ  *ST长药   20250813   ST     风险警示板
+3    300343.SZ   ST联创   20250813   ST     风险警示板
+4    300044.SZ   ST赛为   20250813   ST     风险警示板
+..         ...    ...        ...  ...       ...
+170  300175.SZ   ST朗源   20250813   ST     风险警示板
+171  603721.SH  *ST天择   20250813   ST     风险警示板
+172  600289.SH   ST信通   20250813   ST     风险警示板
+173  000929.SZ  *ST兰黄   20250813   ST     风险警示板
+174  000638.SZ  *ST万方   20250813   ST     风险警示板

src/data/api_wrappers/api_stock_st.py

@@ -0,0 +1,147 @@
+"""ST股票列表接口。
+
+获取ST股票列表数据，可根据交易日期获取历史上每天的ST列表。
+数据从20160101开始可用，每天上午9:20更新。
+"""
+
+import pandas as pd
+from typing import Optional
+
+from src.data.client import TushareClient
+from src.data.api_wrappers.base_sync import DateBasedSync
+
+
+def get_stock_st(
+    trade_date: Optional[str] = None,
+    start_date: Optional[str] = None,
+    end_date: Optional[str] = None,
+    ts_code: Optional[str] = None,
+) -> pd.DataFrame:
+    """Fetch ST stock list from Tushare.
+
+    This interface retrieves the daily ST stock list including stock codes,
+    names, and ST type information. Data is available from 20160101 onwards.
+    Updates at 9:20 AM daily.
+
+    Args:
+        trade_date: Specific trade date in YYYYMMDD format
+        start_date: Start date for date range query (YYYYMMDD format)
+        end_date: End date for date range query (YYYYMMDD format)
+        ts_code: Stock code filter (optional, e.g., '000001.SZ')
+
+    Returns:
+        pd.DataFrame with columns:
+        - ts_code: Stock code
+        - name: Stock name
+        - trade_date: Trade date (YYYYMMDD)
+        - type: Type code
+        - type_name: Type name (风险警示板)
+
+    Example:
+        >>> # Get all ST stocks for a single date
+        >>> data = get_stock_st(trade_date='20240101')
+        >>>
+        >>> # Get date range data
+        >>> data = get_stock_st(start_date='20240101', end_date='20240131')
+        >>>
+        >>> # Get specific stock ST history
+        >>> data = get_stock_st(ts_code='000001.SZ')
+    """
+    client = TushareClient()
+
+    # Build parameters
+    params = {}
+    if trade_date:
+        params["trade_date"] = trade_date
+    if start_date:
+        params["start_date"] = start_date
+    if end_date:
+        params["end_date"] = end_date
+    if ts_code:
+        params["ts_code"] = ts_code
+
+    # Fetch data
+    data = client.query("stock_st", **params)
+
+    return data
+
+
+class StockSTSync(DateBasedSync):
+    """ST股票列表批量同步管理器，支持全量/增量同步。
+
+    继承自 DateBasedSync，按日期顺序获取数据。
+    数据从 2016 年开始可用，单次请求最大返回1000行数据。
+
+    Example:
+        >>> sync = StockSTSync()
+        >>> results = sync.sync_all()  # 增量同步
+        >>> results = sync.sync_all(force_full=True)  # 全量同步
+        >>> preview = sync.preview_sync()  # 预览
+    """
+
+    table_name = "stock_st"
+    default_start_date = "20160101"
+
+    # 表结构定义
+    TABLE_SCHEMA = {
+        "ts_code": "VARCHAR(16) NOT NULL",
+        "name": "VARCHAR(50)",
+        "trade_date": "DATE NOT NULL",
+        "type": "VARCHAR(10)",
+        "type_name": "VARCHAR(50)",
+    }
+
+    # 索引定义
+    TABLE_INDEXES = [
+        ("idx_stock_st_date_code", ["trade_date", "ts_code"]),
+    ]
+
+    # 主键定义
+    PRIMARY_KEY = ("trade_date", "ts_code")
+
+    def fetch_single_date(self, trade_date: str) -> pd.DataFrame:
+        """获取单日的ST股票列表数据。
+
+        Args:
+            trade_date: 交易日期（YYYYMMDD）
+
+        Returns:
+            包含当日ST股票列表的 DataFrame
+        """
+        return get_stock_st(trade_date=trade_date)
+
+
+def sync_stock_st(
+    start_date: Optional[str] = None,
+    end_date: Optional[str] = None,
+    force_full: bool = False,
+) -> pd.DataFrame:
+    """Sync ST stock list to DuckDB with intelligent incremental sync.
+
+    Logic:
+    - If table doesn't exist: create table + composite index (trade_date, ts_code) + full sync
+    - If table exists: incremental sync from last_date + 1
+
+    Args:
+        start_date: Start date for sync (YYYYMMDD format, default: 20160101 for full, last_date+1 for incremental)
+        end_date: End date for sync (YYYYMMDD format, default: today)
+        force_full: If True, force full reload from 20160101
+
+    Returns:
+        pd.DataFrame with synced data
+    """
+    sync_manager = StockSTSync()
+    return sync_manager.sync_all(
+        start_date=start_date,
+        end_date=end_date,
+        force_full=force_full,
+    )
+
+
+if __name__ == "__main__":
+    # Test sync
+    result = sync_stock_st(end_date="20240102")
+    print(f"Synced {len(result)} records")
+    if not result.empty:
+        print("\nSample data:")
+        print(result.head())

src/data/api_wrappers/api_trade_cal.py

@@ -14,7 +14,6 @@ from src.config.settings import get_settings
 _cache_synced = False
 
 
-
 # Trading calendar cache file path
 def _get_cache_path() -> Path:
     """Get the cache file path for trade calendar."""

src/data/api_wrappers/base_sync.py

@@ -63,15 +63,15 @@ class BaseDataSync(ABC):
     table_name: str = ""  # 子类必须覆盖
     DEFAULT_START_DATE = "20180101"
     DEFAULT_MAX_WORKERS = get_settings().threads
-    
+
     # 表结构定义（子类可覆盖）
     # 格式: {"column_name": "SQL_TYPE", ...}
     TABLE_SCHEMA: Dict[str, str] = {}
-    
+
     # 索引定义（子类可覆盖）
     # 格式: [("index_name", ["col1", "col2"]), ...]
     TABLE_INDEXES: List[tuple] = []
-    
+
     # 主键定义（子类可覆盖）
     # 格式: ("col1", "col2")
     PRIMARY_KEY: tuple = ()
@@ -325,7 +325,9 @@ class BaseDataSync(ABC):
 
         try:
             print(f"[{class_name}] Probe: {probe_description}")
-            print(f"[{class_name}] Probe: Inserting {len(probe_data)} sample records...")
+            print(
+                f"[{class_name}] Probe: Inserting {len(probe_data)} sample records..."
+            )
 
             # 插入样本数据
             storage.save(self.table_name, probe_data, mode="append")
@@ -344,18 +346,20 @@ class BaseDataSync(ABC):
             # 清空表（truncate）
             print(f"[{class_name}] Probe: Cleaning up sample data...")
             storage._connection.execute(f'DELETE FROM "{self.table_name}"')
-            
+
             # 验证表已清空
             count_result = storage._connection.execute(
                 f'SELECT COUNT(*) FROM "{self.table_name}"'
             ).fetchone()
             remaining = count_result[0] if count_result else -1
-            
+
             if remaining == 0:
                 print(f"[{class_name}] Probe: SUCCESS - Table verified and cleaned")
                 return True
             else:
-                print(f"[{class_name}] Probe: WARNING - {remaining} rows remaining after cleanup")
+                print(
+                    f"[{class_name}] Probe: WARNING - {remaining} rows remaining after cleanup"
+                )
                 return True  # 仍然继续，因为主要目的是验证结构
 
         except Exception as e:
@@ -395,44 +399,50 @@ class BaseDataSync(ABC):
         子类可以覆盖此方法以自定义建表逻辑。
         """
         storage = Storage()
-        
+
         if storage.exists(self.table_name):
             return
-        
+
         if not self.TABLE_SCHEMA:
-            print(f"[{self.__class__.__name__}] TABLE_SCHEMA not defined, skipping table creation")
+            print(
+                f"[{self.__class__.__name__}] TABLE_SCHEMA not defined, skipping table creation"
+            )
             return
-        
+
         # 构建列定义
         columns_def = []
         for col_name, col_type in self.TABLE_SCHEMA.items():
             columns_def.append(f'"{col_name}" {col_type}')
-        
+
         # 添加主键约束
         if self.PRIMARY_KEY:
-            pk_cols = ', '.join(f'"{col}"' for col in self.PRIMARY_KEY)
+            pk_cols = ", ".join(f'"{col}"' for col in self.PRIMARY_KEY)
             columns_def.append(f"PRIMARY KEY ({pk_cols})")
-        
+
         columns_sql = ", ".join(columns_def)
         create_sql = f'CREATE TABLE IF NOT EXISTS "{self.table_name}" ({columns_sql})'
-        
+
         try:
             storage._connection.execute(create_sql)
             print(f"[{self.__class__.__name__}] Created table '{self.table_name}'")
         except Exception as e:
             print(f"[{self.__class__.__name__}] Error creating table: {e}")
             raise
-        
+
         # 创建索引
         for idx_name, idx_cols in self.TABLE_INDEXES:
             try:
-                idx_cols_sql = ', '.join(f'"{col}"' for col in idx_cols)
+                idx_cols_sql = ", ".join(f'"{col}"' for col in idx_cols)
                 storage._connection.execute(
                     f'CREATE INDEX IF NOT EXISTS "{idx_name}" ON "{self.table_name}"({idx_cols_sql})'
                 )
-                print(f"[{self.__class__.__name__}] Created index '{idx_name}' on {idx_cols}")
+                print(
+                    f"[{self.__class__.__name__}] Created index '{idx_name}' on {idx_cols}"
+                )
             except Exception as e:
-                print(f"[{self.__class__.__name__}] Error creating index {idx_name}: {e}")
+                print(
+                    f"[{self.__class__.__name__}] Error creating index {idx_name}: {e}"
+                )
 
     @abstractmethod
     def preview_sync(
@@ -863,28 +873,30 @@ class StockBasedSync(BaseDataSync):
 
         # 首次同步探测：验证表结构是否正常
         if self._should_probe_table():
-            print(f"[{class_name}] Table '{self.table_name}' is empty or doesn't exist, probing...")
+            print(
+                f"[{class_name}] Table '{self.table_name}' is empty or doesn't exist, probing..."
+            )
             # 使用第一只股票的完整日期范围数据进行探测
             probe_stock = stock_codes[0]
-            probe_data = self.fetch_single_stock(
+            probe_data = self.fetch_single_stock(probe_stock, sync_start_date, end_date)
-                probe_stock, sync_start_date, end_date
-            )
             probe_desc = f"stock={probe_stock}, range={sync_start_date} to {end_date}"
             probe_success = self._probe_table_and_cleanup(probe_data, probe_desc)
-            
+
             if not probe_success:
-                print(f"[{class_name}] Probe failed! Stopping sync to prevent data corruption.")
+                print(
+                    f"[{class_name}] Probe failed! Stopping sync to prevent data corruption."
+                )
                 raise RuntimeError(
                     f"Table '{self.table_name}' probe failed. "
                     "Please check database schema and column mappings."
                 )
         if self._should_probe_table():
-            print(f"[{class_name}] Table '{self.table_name}' is empty or doesn't exist, probing...")
+            print(
+                f"[{class_name}] Table '{self.table_name}' is empty or doesn't exist, probing..."
+            )
             # 使用第一只股票的完整日期范围数据进行探测
             probe_stock = stock_codes[0]
-            probe_data = self.fetch_single_stock(
+            probe_data = self.fetch_single_stock(probe_stock, sync_start_date, end_date)
-                probe_stock, sync_start_date, end_date
-            )
             probe_desc = f"stock={probe_stock}, range={sync_start_date} to {end_date}"
             self._probe_table_and_cleanup(probe_data, probe_desc)
 
@@ -1301,7 +1313,7 @@ class DateBasedSync(BaseDataSync):
             else:
                 print(f"[{class_name}] Cannot create table: no sample data available")
                 return pd.DataFrame()
-        
+
         # 首次同步探测：验证表结构是否正常
         if self._should_probe_table():
             print(f"[{class_name}] Table '{self.table_name}' is empty, probing...")
@@ -1335,10 +1347,8 @@ class DateBasedSync(BaseDataSync):
         if self._should_probe_table():
             print(f"[{class_name}] Table '{self.table_name}' is empty, probing...")
             # 使用最近一个交易日的完整数据进行探测
-            from src.data.api_wrappers.api_trade_cal import get_last_n_trading_days
+            probe_date = get_last_trading_day(sync_start, sync_end)
-            last_days = get_last_n_trading_days(1, sync_end)
+            if probe_date:
-            if last_days:
-                probe_date = last_days[0]
                 probe_data = self.fetch_single_date(probe_date)
                 probe_desc = f"date={probe_date}, all stocks"
                 self._probe_table_and_cleanup(probe_data, probe_desc)

src/data/sync.py

@@ -46,6 +46,7 @@ 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
 from src.data.api_wrappers.api_daily_basic import sync_daily_basic
+from src.data.api_wrappers.api_stock_st import sync_stock_st
 
 
 def preview_sync(
@@ -161,6 +162,7 @@ def sync_all_data(
     4. Pro Bar 数据 (sync_pro_bar)
     5. 每日指标数据 (sync_daily_basic)
     6. 历史股票列表 (sync_bak_basic)
+    7. ST股票列表 (sync_stock_st)
 
     【不包含的同步（需单独调用）】
     - 财务数据: 利润表、资产负债表、现金流量表（季度更新）
@@ -195,53 +197,53 @@ def sync_all_data(
     print("=" * 60)
 
     # 1. Sync trade calendar (always needed first)
-    print("\n[1/5] Syncing trade calendar cache...")
+    print("\n[1/7] 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")
+        print("[1/7] Trade calendar: OK")
     except Exception as e:
-        print(f"[1/5] Trade calendar: FAILED - {e}")
+        print(f"[1/7] Trade calendar: FAILED - {e}")
         results["trade_cal"] = pd.DataFrame()
 
     # 2. Sync stock basic info
-    print("\n[2/5] Syncing stock basic info...")
+    print("\n[2/7] Syncing stock basic info...")
     try:
         sync_all_stocks()
         results["stock_basic"] = pd.DataFrame()
-        print("[2/5] Stock basic: OK")
+        print("[2/7] Stock basic: OK")
     except Exception as e:
-        print(f"[2/5] Stock basic: FAILED - {e}")
+        print(f"[2/7] Stock basic: FAILED - {e}")
         results["stock_basic"] = pd.DataFrame()
 
     # 3. Sync daily market data
-    print("\n[3/5] Syncing daily market data...")
+    # print("\n[3/7] Syncing daily market data...")
-    try:
+    # try:
-        # 确保表存在
+    #     # 确保表存在
-        from src.data.api_wrappers.api_daily import DailySync
+    #     from src.data.api_wrappers.api_daily import DailySync
-
+    #
-        DailySync().ensure_table_exists()
+    #     DailySync().ensure_table_exists()
-
+    #
-        daily_result = sync_daily(
+    #     daily_result = sync_daily(
-            force_full=force_full,
+    #         force_full=force_full,
-            max_workers=max_workers,
+    #         max_workers=max_workers,
-            dry_run=dry_run,
+    #         dry_run=dry_run,
-        )
+    #     )
-        results["daily"] = daily_result
+    #     results["daily"] = daily_result
-        total_daily_records = (
+    #     total_daily_records = (
-            sum(len(df) for df in daily_result.values()) if daily_result else 0
+    #         sum(len(df) for df in daily_result.values()) if daily_result else 0
-        )
+    #     )
-        print(
+    #     print(
-            f"[3/5] Daily data: OK ({total_daily_records} records from {len(daily_result)} stocks)"
+    #         f"[3/7] Daily data: OK ({total_daily_records} records from {len(daily_result)} stocks)"
-        )
+    #     )
-    except Exception as e:
+    # except Exception as e:
-        print(f"[3/5] Daily data: FAILED - {e}")
+    #     print(f"[3/7] Daily data: FAILED - {e}")
-        results["daily"] = pd.DataFrame()
+    #     results["daily"] = pd.DataFrame()
 
     # 4. Sync Pro Bar data
-    print("\n[4/6] Syncing Pro Bar data (with adj, tor, vr)...")
+    print("\n[4/7] Syncing Pro Bar data (with adj, tor, vr)...")
     try:
         # 确保表存在
         from src.data.api_wrappers.api_pro_bar import ProBarSync
@@ -258,15 +260,15 @@ def sync_all_data(
             sum(len(df) for df in pro_bar_result.values()) if pro_bar_result else 0
         )
         print(
-            f"[4/6] Pro Bar data: OK ({total_pro_bar_records} records from {len(pro_bar_result)} stocks)"
+            f"[4/7] Pro Bar data: OK ({total_pro_bar_records} records from {len(pro_bar_result)} stocks)"
         )
     except Exception as e:
-        print(f"[4/6] Pro Bar data: FAILED - {e}")
+        print(f"[4/7] Pro Bar data: FAILED - {e}")
         results["pro_bar"] = pd.DataFrame()
 
     # 5. Sync daily basic indicators
     print(
-        "\n[5/6] Syncing daily basic indicators (PE, PB, turnover rate, market value)..."
+        "\n[5/7] Syncing daily basic indicators (PE, PB, turnover rate, market value)..."
     )
     try:
         # 确保表存在
@@ -276,13 +278,13 @@ def sync_all_data(
 
         daily_basic_result = sync_daily_basic(force_full=force_full, dry_run=dry_run)
         results["daily_basic"] = daily_basic_result
-        print(f"[5/6] Daily basic: OK ({len(daily_basic_result)} records)")
+        print(f"[5/7] Daily basic: OK ({len(daily_basic_result)} records)")
     except Exception as e:
-        print(f"[5/6] Daily basic: FAILED - {e}")
+        print(f"[5/7] Daily basic: FAILED - {e}")
         results["daily_basic"] = pd.DataFrame()
 
     # 6. Sync stock historical list (bak_basic)
-    print("\n[6/6] Syncing stock historical list (bak_basic)...")
+    print("\n[6/7] Syncing stock historical list (bak_basic)...")
     try:
         # 确保表存在
         from src.data.api_wrappers.api_bak_basic import BakBasicSync
@@ -291,11 +293,26 @@ def sync_all_data(
 
         bak_basic_result = sync_bak_basic(force_full=force_full)
         results["bak_basic"] = bak_basic_result
-        print(f"[6/6] Bak basic: OK ({len(bak_basic_result)} records)")
+        print(f"[6/7] Bak basic: OK ({len(bak_basic_result)} records)")
     except Exception as e:
-        print(f"[6/6] Bak basic: FAILED - {e}")
+        print(f"[6/7] Bak basic: FAILED - {e}")
         results["bak_basic"] = pd.DataFrame()
 
+    # 7. Sync ST stock list
+    print("\n[7/7] Syncing ST stock list...")
+    try:
+        # 确保表存在
+        from src.data.api_wrappers.api_stock_st import StockSTSync
+
+        StockSTSync().ensure_table_exists()
+
+        stock_st_result = sync_stock_st(force_full=force_full)
+        results["stock_st"] = stock_st_result
+        print(f"[7/7] ST stock list: OK ({len(stock_st_result)} records)")
+    except Exception as e:
+        print(f"[7/7] ST stock list: FAILED - {e}")
+        results["stock_st"] = pd.DataFrame()
+
     # Summary
     print("\n" + "=" * 60)
     print("[sync_all_data] Sync Summary")

tests/test_stock_st.py

@@ -0,0 +1,143 @@
+"""Test suite for stock_st API wrapper."""
+
+import pytest
+import pandas as pd
+from unittest.mock import patch, MagicMock
+
+from src.data.api_wrappers.api_stock_st import get_stock_st, sync_stock_st, StockSTSync
+
+
+class TestStockST:
+    """Test suite for stock_st API wrapper."""
+
+    @patch("src.data.api_wrappers.api_stock_st.TushareClient")
+    def test_get_by_date(self, mock_client_class):
+        """Test fetching ST stock list by date."""
+        # Setup mock
+        mock_client = MagicMock()
+        mock_client_class.return_value = mock_client
+        mock_client.query.return_value = pd.DataFrame(
+            {
+                "ts_code": ["300313.SZ", "605081.SH", "300391.SZ"],
+                "name": ["*ST天山", "*ST太和", "*ST长药"],
+                "trade_date": ["20240101", "20240101", "20240101"],
+                "type": ["ST", "ST", "ST"],
+                "type_name": ["风险警示板", "风险警示板", "风险警示板"],
+            }
+        )
+
+        # Test
+        result = get_stock_st(trade_date="20240101")
+
+        # Assert
+        assert not result.empty
+        assert len(result) == 3
+        assert "ts_code" in result.columns
+        assert "name" in result.columns
+        assert "trade_date" in result.columns
+        assert "type" in result.columns
+        assert "type_name" in result.columns
+        mock_client.query.assert_called_once()
+
+    @patch("src.data.api_wrappers.api_stock_st.TushareClient")
+    def test_get_by_stock(self, mock_client_class):
+        """Test fetching ST history by stock code."""
+        # Setup mock
+        mock_client = MagicMock()
+        mock_client_class.return_value = mock_client
+        mock_client.query.return_value = pd.DataFrame(
+            {
+                "ts_code": ["300313.SZ", "300313.SZ"],
+                "name": ["*ST天山", "*ST天山"],
+                "trade_date": ["20240101", "20240102"],
+                "type": ["ST", "ST"],
+                "type_name": ["风险警示板", "风险警示板"],
+            }
+        )
+
+        # Test
+        result = get_stock_st(
+            ts_code="300313.SZ", start_date="20240101", end_date="20240102"
+        )
+
+        # Assert
+        assert not result.empty
+        assert len(result) == 2
+        mock_client.query.assert_called_once()
+
+    @patch("src.data.api_wrappers.api_stock_st.TushareClient")
+    def test_empty_response(self, mock_client_class):
+        """Test handling empty response."""
+        mock_client = MagicMock()
+        mock_client_class.return_value = mock_client
+        mock_client.query.return_value = pd.DataFrame()
+
+        result = get_stock_st(trade_date="20240101")
+        assert result.empty
+
+    @patch("src.data.api_wrappers.api_stock_st.TushareClient")
+    def test_get_by_date_range(self, mock_client_class):
+        """Test fetching ST stock list by date range."""
+        # Setup mock
+        mock_client = MagicMock()
+        mock_client_class.return_value = mock_client
+        mock_client.query.return_value = pd.DataFrame(
+            {
+                "ts_code": ["300313.SZ"],
+                "name": ["*ST天山"],
+                "trade_date": ["20240101"],
+                "type": ["ST"],
+                "type_name": ["风险警示板"],
+            }
+        )
+
+        # Test
+        result = get_stock_st(start_date="20240101", end_date="20240131")
+
+        # Assert
+        assert not result.empty
+        mock_client.query.assert_called_once()
+
+
+class TestStockSTSync:
+    """Test suite for StockSTSync class."""
+
+    def test_sync_class_attributes(self):
+        """Test that sync class has correct attributes."""
+        sync = StockSTSync()
+        assert sync.table_name == "stock_st"
+        assert sync.default_start_date == "20160101"
+        assert "ts_code" in sync.TABLE_SCHEMA
+        assert "trade_date" in sync.TABLE_SCHEMA
+        assert "name" in sync.TABLE_SCHEMA
+        assert "type" in sync.TABLE_SCHEMA
+        assert "type_name" in sync.TABLE_SCHEMA
+        assert sync.PRIMARY_KEY == ("trade_date", "ts_code")
+
+    @patch("src.data.api_wrappers.api_stock_st.TushareClient")
+    def test_fetch_single_date(self, mock_client_class):
+        """Test fetching single date data."""
+        # Setup mock
+        mock_client = MagicMock()
+        mock_client_class.return_value = mock_client
+        mock_client.query.return_value = pd.DataFrame(
+            {
+                "ts_code": ["300313.SZ"],
+                "name": ["*ST天山"],
+                "trade_date": ["20240101"],
+                "type": ["ST"],
+                "type_name": ["风险警示板"],
+            }
+        )
+
+        # Test
+        sync = StockSTSync()
+        result = sync.fetch_single_date("20240101")
+
+        # Assert
+        assert not result.empty
+        assert len(result) == 1
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])