get_sz50_stocks

Instructions

Implementation Reference

• src/tools/indices.py:33-39 (handler)

  Primary MCP tool handler for 'get_sz50_stocks'. Registered via @app.tool() decorator. Delegates execution to the use-cases layer via run_tool_with_handling.

  @app.tool()
  def get_sz50_stocks(date: Optional[str] = None, limit: int = 250, format: str = "markdown") -> str:
      """SZSE 50 constituents."""
      return run_tool_with_handling(
          lambda: fetch_index_constituents(active_data_source, index="sz50", date=date, limit=limit, format=format),
          context="get_sz50_stocks",
      )

• mcp_server.py:51-58 (registration)

  Registration block in main server file where register_index_tools is called to register the index tools including get_sz50_stocks.

  register_stock_market_tools(app, active_data_source)
  register_financial_report_tools(app, active_data_source)
  register_index_tools(app, active_data_source)
  register_market_overview_tools(app, active_data_source)
  register_macroeconomic_tools(app, active_data_source)
  register_date_utils_tools(app, active_data_source)
  register_analysis_tools(app, active_data_source)
  register_helpers_tools(app)

• src/use_cases/indices.py:25-35 (helper)

  Use case helper function invoked by the tool handler. Routes 'sz50' requests to data_source.get_sz50_stocks() and formats the output.

  def fetch_index_constituents(data_source: FinancialDataSource, *, index: str, date: Optional[str], limit: int, format: str) -> str:
      validate_output_format(format)
      key = validate_index_key(index, INDEX_MAP)
      if key == "hs300":
          df = data_source.get_hs300_stocks(date=date)
      elif key == "sz50":
          df = data_source.get_sz50_stocks(date=date)
      else:
          df = data_source.get_zz500_stocks(date=date)
      meta = {"index": key, "as_of": date or "latest"}
      return format_table_output(df, format=format, max_rows=limit, meta=meta)

• src/baostock_data_source.py:570-572 (helper)

  Concrete data source implementation for fetching SZSE 50 stocks using Baostock API via helper function.

  def get_sz50_stocks(self, date: Optional[str] = None) -> pd.DataFrame:
      """Fetches SZSE 50 index constituents using Baostock."""
      return _fetch_index_constituent_data(bs.query_sz50_stocks, "SZSE 50", date)

• src/baostock_data_source.py:78-123 (helper)

  Shared helper function in BaostockDataSource used by get_sz50_stocks to query and process Baostock API response.

  def _fetch_index_constituent_data(
      bs_query_func,
      index_name: str,
      date: Optional[str] = None
  ) -> pd.DataFrame:
      logger.info(
          f"Fetching {index_name} constituents for date={date or 'latest'}")
      try:
          with baostock_login_context():
              # date is optional, defaults to latest
              rs = bs_query_func(date=date)
  
              if rs.error_code != '0':
                  logger.error(
                      f"Baostock API error ({index_name} Constituents) for date {date}: {rs.error_msg} (code: {rs.error_code})")
                  if "no record found" in rs.error_msg.lower() or rs.error_code == '10002':
                      raise NoDataFoundError(
                          f"No {index_name} constituent data found for date {date}. Baostock msg: {rs.error_msg}")
                  else:
                      raise DataSourceError(
                          f"Baostock API error fetching {index_name} constituents: {rs.error_msg} (code: {rs.error_code})")
  
              data_list = []
              while rs.next():
                  data_list.append(rs.get_row_data())
  
              if not data_list:
                  logger.warning(
                      f"No {index_name} constituent data found for date {date} (empty result set).")
                  raise NoDataFoundError(
                      f"No {index_name} constituent data found for date {date} (empty result set).")
  
              result_df = pd.DataFrame(data_list, columns=rs.fields)
              logger.info(
                  f"Retrieved {len(result_df)} {index_name} constituents for date {date or 'latest'}.")
              return result_df
  
      except (LoginError, NoDataFoundError, DataSourceError, ValueError) as e:
          logger.warning(
              f"Caught known error fetching {index_name} constituents for date {date}: {type(e).__name__}")
          raise e
      except Exception as e:
          logger.exception(
              f"Unexpected error fetching {index_name} constituents for date {date}: {e}")
          raise DataSourceError(
              f"Unexpected error fetching {index_name} constituents for date {date}: {e}")