def __hash__(self):
        return hash(self.package)
def _read_metadata_from_example_file(netcdf_file_name, include_soundings):
    """Reads metadata from file with input examples.

    :param netcdf_file_name: Path to input file.
    :param include_soundings: Boolean flag.  If True and file contains
        soundings, this method will return keys "sounding_field_names" and
        "sounding_heights_m_agl".  Otherwise, will not return said keys.

    :return: example_dict: Dictionary with the following keys (explained in doc
        to `write_example_file`).
    example_dict['full_id_strings']
    example_dict['storm_times_unix_sec']
    example_dict['radar_field_names']
    example_dict['radar_heights_m_agl']
    example_dict['rotated_grids']
    example_dict['rotated_grid_spacing_metres']
    example_dict['target_names']
    example_dict['sounding_field_names']
    example_dict['sounding_heights_m_agl']

    :return: netcdf_dataset: Instance of `netCDF4.Dataset`, which can be used to
        keep reading file.
    """

    netcdf_dataset = netCDF4.Dataset(netcdf_file_name)
    include_soundings = (
        include_soundings and
        SOUNDING_FIELDS_KEY in netcdf_dataset.variables
    )

    example_dict = {
        ROTATED_GRIDS_KEY: bool(getattr(netcdf_dataset, ROTATED_GRIDS_KEY)),
        TARGET_NAMES_KEY: [
            str(s) for s in
            netCDF4.chartostring(netcdf_dataset.variables[TARGET_NAMES_KEY][:])
        ],
        FULL_IDS_KEY: [
            str(s) for s in
            netCDF4.chartostring(netcdf_dataset.variables[FULL_IDS_KEY][:])
        ],
        STORM_TIMES_KEY: numpy.array(
            netcdf_dataset.variables[STORM_TIMES_KEY][:], dtype=int
        ),
        RADAR_FIELDS_KEY: [
            str(s) for s in
            netCDF4.chartostring(netcdf_dataset.variables[RADAR_FIELDS_KEY][:])
        ],
        RADAR_HEIGHTS_KEY: numpy.array(
            netcdf_dataset.variables[RADAR_HEIGHTS_KEY][:], dtype=int
        )
    }

    # TODO(thunderhoser): This is a HACK to deal with bad files.
    example_dict[TARGET_NAMES_KEY] = [
        n for n in example_dict[TARGET_NAMES_KEY] if n != ''
    ]

    if example_dict[ROTATED_GRIDS_KEY]:
        example_dict[ROTATED_GRID_SPACING_KEY] = getattr(
            netcdf_dataset, ROTATED_GRID_SPACING_KEY)
    else:
        example_dict[ROTATED_GRID_SPACING_KEY] = None

    if not include_soundings:
        return example_dict, netcdf_dataset

    example_dict.update({
        SOUNDING_FIELDS_KEY: [
            str(s) for s in netCDF4.chartostring(
                netcdf_dataset.variables[SOUNDING_FIELDS_KEY][:])
        ],
        SOUNDING_HEIGHTS_KEY:
            numpy.array(netcdf_dataset.variables[SOUNDING_HEIGHTS_KEY][:],
                        dtype=int)
    })

    return example_dict, netcdf_dataset