get_trade_dates

Instructions

    Fetch trading dates within a specified range.

    Args:
        start_date: Optional. Start date in 'YYYY-MM-DD' format. Defaults to 2015-01-01 if None.
        end_date: Optional. End date in 'YYYY-MM-DD' format. Defaults to the current date if None.

    Returns:
        Markdown table with 'is_trading_day' (1=trading, 0=non-trading).
    

Implementation Reference

• src/tools/market_overview.py:30-46 (handler)

  MCP tool handler implementation for 'get_trade_dates'. This is the function executed when the tool is called, handling parameters, logging, and delegating to the use case via run_tool_with_handling.

  @app.tool()
  def get_trade_dates(start_date: Optional[str] = None, end_date: Optional[str] = None, limit: int = 250, format: str = "markdown") -> str:
      """
      Fetch trading dates within a specified range.
  
      Args:
          start_date: Optional. Start date in 'YYYY-MM-DD' format. Defaults to 2015-01-01 if None.
          end_date: Optional. End date in 'YYYY-MM-DD' format. Defaults to the current date if None.
  
      Returns:
          Markdown table with 'is_trading_day' (1=trading, 0=non-trading).
      """
      logger.info(f"Tool 'get_trade_dates' called for range {start_date or 'default'} to {end_date or 'default'}")
      return run_tool_with_handling(
          lambda: fetch_trade_dates(active_data_source, start_date=start_date, end_date=end_date, limit=limit, format=format),
          context="get_trade_dates",
      )

• mcp_server.py:54-54 (registration)

  Registration of market overview tools, including 'get_trade_dates', by calling register_market_overview_tools during app setup.

  register_market_overview_tools(app, active_data_source)

• src/data_source_interface.py:88-91 (schema)

  Interface definition specifying the signature for get_trade_dates method in FinancialDataSource.

  @abstractmethod
  def get_trade_dates(self, start_date: Optional[str] = None, end_date: Optional[str] = None) -> pd.DataFrame:
      """Fetches trading dates information within a range."""
      pass

• src/use_cases/market_overview.py:9-13 (helper)

  Use case helper function that fetches trade dates from data source, applies validation and formatting.

  def fetch_trade_dates(data_source: FinancialDataSource, *, start_date: Optional[str], end_date: Optional[str], limit: int, format: str) -> str:
      validate_output_format(format)
      df = data_source.get_trade_dates(start_date=start_date, end_date=end_date)
      meta = {"start_date": start_date or "default", "end_date": end_date or "default"}
      return format_table_output(df, format=format, max_rows=limit, meta=meta)

• src/baostock_data_source.py:582-621 (helper)

  Concrete implementation in Baostock data source that queries the API for trade dates and returns a DataFrame.

  def get_trade_dates(self, start_date: Optional[str] = None, end_date: Optional[str] = None) -> pd.DataFrame:
      """Fetches trading dates using Baostock."""
      logger.info(
          f"Fetching trade dates from {start_date or 'default'} to {end_date or 'default'}")
      try:
          with baostock_login_context():  # Login might not be strictly needed for this, but keeping consistent
              rs = bs.query_trade_dates(
                  start_date=start_date, end_date=end_date)
  
              if rs.error_code != '0':
                  logger.error(
                      f"Baostock API error (Trade Dates): {rs.error_msg} (code: {rs.error_code})")
                  # Unlikely to have 'no record found' for dates, but handle API errors
                  raise DataSourceError(
                      f"Baostock API error fetching trade dates: {rs.error_msg} (code: {rs.error_code})")
  
              data_list = []
              while rs.next():
                  data_list.append(rs.get_row_data())
  
              if not data_list:
                  # This case should ideally not happen if the API returns a valid range
                  logger.warning(
                      f"No trade dates returned for range {start_date}-{end_date} (empty result set).")
                  raise NoDataFoundError(
                      f"No trade dates found for range {start_date}-{end_date} (empty result set).")
  
              result_df = pd.DataFrame(data_list, columns=rs.fields)
              logger.info(f"Retrieved {len(result_df)} trade date records.")
              return result_df
  
      except (LoginError, NoDataFoundError, DataSourceError, ValueError) as e:
          logger.warning(
              f"Caught known error fetching trade dates: {type(e).__name__}")
          raise e
      except Exception as e:
          logger.exception(f"Unexpected error fetching trade dates: {e}")
          raise DataSourceError(
              f"Unexpected error fetching trade dates: {e}")