remove unused func

Author: Omswastik-11

openml/runs/functions.py

@@ -1092,125 +1092,6 @@ def list_runs(  # noqa: PLR0913
     return pd.concat(batches)
 
 
-def _list_runs(  # noqa: PLR0913, C901
-    limit: int,
-    offset: int,
-    *,
-    id: list | None = None,  # noqa: A002
-    task: list | None = None,
-    setup: list | None = None,
-    flow: list | None = None,
-    uploader: list | None = None,
-    study: int | None = None,
-    tag: str | None = None,
-    display_errors: bool = False,
-    task_type: TaskType | int | None = None,
-) -> pd.DataFrame:
-    """
-    Perform API call `/run/list/{filters}'
-    <https://www.openml.org/api_docs/#!/run/get_run_list_filters>`
-
-    Parameters
-    ----------
-    The arguments that are lists are separated from the single value
-    ones which are put into the kwargs.
-    display_errors is also separated from the kwargs since it has a
-    default value.
-
-    id : list, optional
-
-    task : list, optional
-
-    setup: list, optional
-
-    flow : list, optional
-
-    tag: str, optional
-
-    uploader : list, optional
-
-    study : int, optional
-
-    display_errors : bool, optional (default=None)
-        Whether to list runs which have an error (for example a missing
-        prediction file).
-
-    task_type : str, optional
-
-    Returns
-    -------
-    dict, or dataframe
-        List of found runs.
-    """
-    api_call = "run/list"
-    if limit is not None:
-        api_call += f"/limit/{limit}"
-    if offset is not None:
-        api_call += f"/offset/{offset}"
-    if id is not None:
-        api_call += f"/run/{','.join([str(int(i)) for i in id])}"
-    if task is not None:
-        api_call += f"/task/{','.join([str(int(i)) for i in task])}"
-    if setup is not None:
-        api_call += f"/setup/{','.join([str(int(i)) for i in setup])}"
-    if flow is not None:
-        api_call += f"/flow/{','.join([str(int(i)) for i in flow])}"
-    if uploader is not None:
-        api_call += f"/uploader/{','.join([str(int(i)) for i in uploader])}"
-    if study is not None:
-        api_call += f"/study/{study}"
-    if display_errors:
-        api_call += "/show_errors/true"
-    if tag is not None:
-        api_call += f"/tag/{tag}"
-    if task_type is not None:
-        tvalue = task_type.value if isinstance(task_type, TaskType) else task_type
-        api_call += f"/task_type/{tvalue}"
-    return __list_runs(api_call=api_call)
-
-
-def __list_runs(api_call: str) -> pd.DataFrame:
-    """Helper function to parse API calls which are lists of runs"""
-    xml_string = openml._api_calls._perform_api_call(api_call, "get")
-    runs_dict = xmltodict.parse(xml_string, force_list=("oml:run",))
-    # Minimalistic check if the XML is useful
-    if "oml:runs" not in runs_dict:
-        raise ValueError(f'Error in return XML, does not contain "oml:runs": {runs_dict}')
-
-    if "@xmlns:oml" not in runs_dict["oml:runs"]:
-        raise ValueError(
-            f'Error in return XML, does not contain "oml:runs"/@xmlns:oml: {runs_dict}'
-        )
-
-    if runs_dict["oml:runs"]["@xmlns:oml"] != "http://openml.org/openml":
-        raise ValueError(
-            "Error in return XML, value of  "
-            '"oml:runs"/@xmlns:oml is not '
-            f'"http://openml.org/openml": {runs_dict}',
-        )
-
-    if not isinstance(runs_dict["oml:runs"]["oml:run"], list):
-        raise TypeError(
-            f"Expected runs_dict['oml:runs']['oml:run'] to be a list, "
-            f"got {type(runs_dict['oml:runs']['oml:run']).__name__}"
-        )
-
-    runs = {
-        int(r["oml:run_id"]): {
-            "run_id": int(r["oml:run_id"]),
-            "task_id": int(r["oml:task_id"]),
-            "setup_id": int(r["oml:setup_id"]),
-            "flow_id": int(r["oml:flow_id"]),
-            "uploader": int(r["oml:uploader"]),
-            "task_type": TaskType(int(r["oml:task_type_id"])),
-            "upload_time": str(r["oml:upload_time"]),
-            "error_message": str((r["oml:error_message"]) or ""),
-        }
-        for r in runs_dict["oml:runs"]["oml:run"]
-    }
-    return pd.DataFrame.from_dict(runs, orient="index")
-
-
 def format_prediction(  # noqa: PLR0913
     task: OpenMLSupervisedTask,
     repeat: int,