Repository: microsoft/qlib
File: qlib/backtest/__init__.py (Python)

Code before:
    benchmark: str = "SH000300",
    account: Union[float, int, dict] = 1e9,
    exchange_kwargs: dict = {},
    pos_type: str = "Position",
) -> Tuple[PortfolioMetrics, Indicator]:
    """initialize the strategy and executor, then backtest function for the interaction of the outermost strategy and
    executor in the nested decision execution

    Parameters
    ----------
    start_time : Union[pd.Timestamp, str]
        closed start time for backtest
        **NOTE**: This will be applied to the outmost executor's calendar.
    end_time : Union[pd.Timestamp, str]
        closed end time for backtest
        **NOTE**: This will be applied to the outmost executor's calendar.
        E.g. Executor[day](Executor[1min]),   setting `end_time == 20XX0301` will include all the minutes on 20XX0301
    strategy : Union[str, dict, object, Path]
        for initializing outermost portfolio strategy. Please refer to the docs of init_instance_by_config for more
        information.
    executor : Union[str, dict, object, Path]
        for initializing the outermost executor.
    benchmark: str
        the benchmark for reporting.
    account : Union[float, int, Position]
        information for describing how to creat the account
        For `float` or `int`:
            Using Account with only initial cash
        For `Position`:
            Using Account with a Position
    exchange_kwargs : dict
        the kwargs for initializing Exchange
    pos_type : str
        the type of Position.

    Returns
    -------
    portfolio_metrics_dict: Dict[PortfolioMetrics]
        it records the trading portfolio_metrics information
    indicator_dict: Dict[Indicator]
        it computes the trading indicator
        It is organized in a dict format

    """
    trade_strategy, trade_executor = get_strategy_executor(
        start_time,
        end_time,
        strategy,
        executor,
        benchmark,
        account,

Review comment (suggestion):
```suggestion
        information for describing how to create the account
```

Code after:
    benchmark: str = "SH000300",
    account: Union[float, int, dict] = 1e9,
    exchange_kwargs: dict = {},
    pos_type: str = "Position",
) -> Tuple[PortfolioMetrics, Indicator]:
    """initialize the strategy and executor, then backtest function for the interaction of the outermost strategy and
    executor in the nested decision execution

    Parameters
    ----------
    start_time : Union[pd.Timestamp, str]
        closed start time for backtest
        **NOTE**: This will be applied to the outmost executor's calendar.
    end_time : Union[pd.Timestamp, str]
        closed end time for backtest
        **NOTE**: This will be applied to the outmost executor's calendar.
        E.g. Executor[day](Executor[1min]),   setting `end_time == 20XX0301` will include all the minutes on 20XX0301
    strategy : Union[str, dict, object, Path]
        for initializing outermost portfolio strategy. Please refer to the docs of init_instance_by_config for more
        information.
    executor : Union[str, dict, object, Path]
        for initializing the outermost executor.
    benchmark: str
        the benchmark for reporting.
    account : Union[float, int, Position]
        information for describing how to create the account
        For `float` or `int`:
            Using Account with only initial cash
        For `Position`:
            Using Account with a Position
    exchange_kwargs : dict
        the kwargs for initializing Exchange
    pos_type : str
        the type of Position.

    Returns
    -------
    portfolio_metrics_dict: Dict[PortfolioMetrics]
        it records the trading portfolio_metrics information
    indicator_dict: Dict[Indicator]
        it computes the trading indicator
        It is organized in a dict format

    """
    trade_strategy, trade_executor = get_strategy_executor(
        start_time,
        end_time,
        strategy,
        executor,
        benchmark,
        account,