def __init__(self, package, version):
        """Construct a new requirement.

        :param package: the package name.
        :param version: a semver compatible version specification.
        """
        self.package = package
        self.version = version
        if self.version and not re.match(r"[<=>~]", version[:2]):
            self.version = "=={}".format(self.version)
def _compare_metadata(netcdf_dataset, example_dict):
    """Compares metadata between existing NetCDF file and new batch of examples.

    This method contains a large number of `assert` statements.  If any of the
    `assert` statements fails, this method will error out.

    :param netcdf_dataset: Instance of `netCDF4.Dataset`.
    :param example_dict: See doc for `write_examples_with_3d_radar`.
    :raises: ValueError: if the two sets have different metadata.
    """

    include_soundings = SOUNDING_MATRIX_KEY in example_dict

    orig_example_dict = {
        TARGET_NAMES_KEY: [
            str(s) for s in
            netCDF4.chartostring(netcdf_dataset.variables[TARGET_NAMES_KEY][:])
        ],
        ROTATED_GRIDS_KEY: bool(getattr(netcdf_dataset, ROTATED_GRIDS_KEY)),
        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
        )
    }

    if example_dict[ROTATED_GRIDS_KEY]:
        orig_example_dict[ROTATED_GRID_SPACING_KEY] = int(
            getattr(netcdf_dataset, ROTATED_GRID_SPACING_KEY)
        )

    if include_soundings:
        orig_example_dict[SOUNDING_FIELDS_KEY] = [
            str(s) for s in netCDF4.chartostring(
                netcdf_dataset.variables[SOUNDING_FIELDS_KEY][:])
        ]
        orig_example_dict[SOUNDING_HEIGHTS_KEY] = numpy.array(
            netcdf_dataset.variables[SOUNDING_HEIGHTS_KEY][:], dtype=int
        )

    for this_key in orig_example_dict:
        if isinstance(example_dict[this_key], numpy.ndarray):
            if numpy.array_equal(example_dict[this_key],
                                 orig_example_dict[this_key]):
                continue
        else:
            if example_dict[this_key] == orig_example_dict[this_key]:
                continue

        error_string = (
            '\n"{0:s}" in existing NetCDF file:\n{1:s}\n\n"{0:s}" in new batch '
            'of examples:\n{2:s}\n\n'
        ).format(
            this_key, str(orig_example_dict[this_key]),
            str(example_dict[this_key])
        )

        raise ValueError(error_string)