def _read_feather_columns(path, columns, num_splits):  # pragma: no cover
    """Use a Ray task to read columns from Feather into a Pandas DataFrame.

    Note: Ray functions are not detected by codecov (thus pragma: no cover)

    Args:
        path: The path of the Feather file.
        columns: The list of column names to read.
        num_splits: The number of partitions to split the column into.

    Returns:
         A list containing the split Pandas DataFrames and the Index as the last
            element. If there is not `index_col` set, then we just return the length.
            This is used to determine the total length of the DataFrame to build a
            default Index.
    """
    from pyarrow import feather

    df = feather.read_feather(path, columns=columns)
    # Append the length of the index here to build it externally
    return _split_result_for_readers(0, num_splits, df) + [len(df.index)]
Use a Ray task to read columns from Feather into a Pandas DataFrame.

    Note: Ray functions are not detected by codecov (thus pragma: no cover)

    Args:
        path: The path of the Feather file.
        columns: The list of column names to read.
        num_splits: The number of partitions to split the column into.

    Returns:
         A list containing the split Pandas DataFrames and the Index as the last
            element. If there is not `index_col` set, then we just return the length.
            This is used to determine the total length of the DataFrame to build a
            default Index.