Repository: microsoft/qlib
File: examples/run_all_model.py (Python)

Code before:
        qlib_uri: str = "git+https://github.com/microsoft/qlib#egg=pyqlib",
        exp_folder_name: str = "run_all_model_records",
        wait_before_rm_env: bool = False,
        wait_when_err: bool = False,
    ):
        """
        Please be aware that this function can only work under Linux. MacOS and Windows will be supported in the future.
        Any PR to enhance this method is highly welcomed. Besides, this script doesn't support parallel running the same model
        for multiple times, and this will be fixed in the future development.

        Parameters:
        -----------
        times : int
            determines how many times the model should be running.
        models : str or list
            determines the specific model or list of models to run or exclude.
        exclude : boolean
            determines whether the model being used is excluded or included.
        dataset : str
            determines the dataset to be used for each model.
        universe  : str
            the stock universe of the dataset.
            default "" indicates that
        qlib_uri : str
            the uri to install qlib with pip
            it could be url on the git or local path (NOTE: the local path must be an absolute path)
        exp_folder_name: str
            the name of the experiment folder
        wait_before_rm_env : bool
            wait before remove environment.
        wait_when_err : bool
            wait when errors raised when executing commands

        Usage:
        -------
        Here are some use cases of the function in the bash:

        The run_all_models  will decide which config to run based no `models` `dataset`  `universe`
        Example 1):

            models="lightgbm", dataset="Alpha158", universe="" will result in running the following config
            examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158.yaml

            models="lightgbm", dataset="Alpha158", universe="csi500" will result in running the following config
            examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158_csi500.yaml

        .. code-block:: bash

            # Case 1 - run all models multiple times
            python run_all_model.py run 3


Review comment (suggestion):
```suggestion
            it could be url on the remote or local path (NOTE: the local path must be an absolute path)
```

Code after:
        qlib_uri: str = "git+https://github.com/microsoft/qlib#egg=pyqlib",
        exp_folder_name: str = "run_all_model_records",
        wait_before_rm_env: bool = False,
        wait_when_err: bool = False,
    ):
        """
        Please be aware that this function can only work under Linux. MacOS and Windows will be supported in the future.
        Any PR to enhance this method is highly welcomed. Besides, this script doesn't support parallel running the same model
        for multiple times, and this will be fixed in the future development.

        Parameters:
        -----------
        times : int
            determines how many times the model should be running.
        models : str or list
            determines the specific model or list of models to run or exclude.
        exclude : boolean
            determines whether the model being used is excluded or included.
        dataset : str
            determines the dataset to be used for each model.
        universe  : str
            the stock universe of the dataset.
            default "" indicates that
        qlib_uri : str
            the uri to install qlib with pip
            it could be URI on the remote or local path (NOTE: the local path must be an absolute path)
        exp_folder_name: str
            the name of the experiment folder
        wait_before_rm_env : bool
            wait before remove environment.
        wait_when_err : bool
            wait when errors raised when executing commands

        Usage:
        -------
        Here are some use cases of the function in the bash:

        The run_all_models  will decide which config to run based no `models` `dataset`  `universe`
        Example 1):

            models="lightgbm", dataset="Alpha158", universe="" will result in running the following config
            examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158.yaml

            models="lightgbm", dataset="Alpha158", universe="csi500" will result in running the following config
            examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158_csi500.yaml

        .. code-block:: bash

            # Case 1 - run all models multiple times
            python run_all_model.py run 3