How to use the pynpoint.core.attributes.get_attributes function in pynpoint

config_port : pynpoint.core.dataio.ConfigPort
        Configuration port.
    image_out_port : pynpoint.core.dataio.OutputPort
        Output port of the images to which the static attributes are stored.
    check : bool
        Print a warning if certain attributes from the configuration file are not present in
        the FITS header. If set to `False`, attributes are still written to the dataset but
        there will be no warning if a keyword is not found in the FITS header.

    Returns
    -------
    NoneType
        None
    """

    attributes = get_attributes()

    static = []
    for key, value in attributes.items():
        if value['config'] == 'header' and value['attribute'] == 'static':
            static.append(key)

    for attr in static:

        fitskey = config_port.get_attribute(attr)

        if isinstance(fitskey, np.bytes_):
            fitskey = str(fitskey.decode('utf-8'))

        if fitskey != 'None':
            if fitskey in header:
                status = image_out_port.check_static_attribute(attr, header[fitskey])

Returns
        -------
        None
        """

        super(FitsReadingModule, self).__init__(name_in, input_dir)

        self.m_image_out_port = self.add_output_port(image_tag)

        self.m_overwrite = overwrite
        self.m_check = check

        self.m_static = []
        self.m_non_static = []

        self.m_attributes = get_attributes()

        for key, value in six.iteritems(self.m_attributes):
            if value["config"] == "header" and value["attribute"] == "static":
                self.m_static.append(key)

        for key, value in six.iteritems(self.m_attributes):
            if value["attribute"] == "non-static":
                self.m_non_static.append(key)

        self.m_count = 0

Parameters
    ----------
    header : astropy.io.fits.header.Header
        Header information from the FITS file that is read.
    config_port : pynpoint.core.dataio.ConfigPort
        Configuration port.
    image_out_port : pynpoint.core.dataio.OutputPort
        Output port of the images to which the non-static attributes are stored.

    Returns
    -------
    NoneType
        None
    """

    attributes = get_attributes()

    nonstatic = []
    for key, value in attributes.items():
        if value['attribute'] == 'non-static':
            nonstatic.append(key)

    for attr in nonstatic:
        if attributes[attr]['config'] == 'header':
            fitskey = config_port.get_attribute(attr)

            # if type(fitskey) == np.bytes_:
            #     fitskey = str(fitskey.decode('utf-8'))

            if fitskey != 'None':
                if fitskey in header:
                    image_out_port.append_attribute_data(attr, header[fitskey])

self.m_image_out_port_1 = self.add_output_port(image_out_tag_1)
        self.m_image_out_port_2 = self.add_output_port(image_out_tag_2)
        self.m_image_out_port_3 = self.add_output_port(image_out_tag_3)
        self.m_image_out_port_4 = self.add_output_port(image_out_tag_4)

        # Parameters
        self.m_im_dir = image_in_dir
        self.m_check = check
        self.m_overwrite = overwrite
        self.m_scheme = scheme

        # Arguments
        self.m_static = []
        self.m_non_static = []

        self.m_attributes = get_attributes()

        for key, value in six.iteritems(self.m_attributes):
            if value["config"] == "header" and value["attribute"] == "static":
                self.m_static.append(key)

        for key, value in six.iteritems(self.m_attributes):
            if value["attribute"] == "non-static":
                self.m_non_static.append(key)

        self.m_count = 0

def run(self) -> None:
        """
        Run method of the module. Reads a list of values from a FITS or ASCII file and writes them
        as non-static attribute to a dataset.

        Returns
        -------
        NoneType
            None
        """

        print('Reading attribute data...', end='')

        attributes = get_attributes()

        if self.m_attribute not in attributes:
            raise ValueError(f'\'{self.m_attribute}\' is not a valid attribute.')

        if self.m_file_name.endswith('fits'):
            values = fits.getdata(os.path.join(self.m_input_location, self.m_file_name))
        else:
            values = np.loadtxt(os.path.join(self.m_input_location, self.m_file_name),
                                dtype=attributes[self.m_attribute]['type'])

        if values.ndim != 1:
            raise ValueError(f'The input file {self.m_file_name} should contain a 1D list with '
                             f'attributes.')

        status = self.m_data_port.check_non_static_attribute(self.m_attribute, values)

del hdf['config']

            config = hdf.create_group('config')

            for key in attributes.keys():
                if attributes[key]['value'] is not None:
                    config.attrs[key] = attributes[key]['value']

            config.attrs['WORKING_PLACE'] = self._m_working_place

            hdf.close()

        config_file = os.path.join(self._m_working_place, 'PynPoint_config.ini')
        print(f'Configuration: {config_file}\n')

        attributes = get_attributes()
        attributes['CPU']['value'] = multiprocessing.cpu_count()

        if not os.path.isfile(config_file):
            warnings.warn('Configuration file not found. Creating PynPoint_config.ini with '
                          'default values in the working place.')

            _create_config(config_file, attributes)

        attributes = _read_config(config_file, attributes)

        _write_config(attributes)

        n_cpu = attributes['CPU']['value']

        if 'OMP_NUM_THREADS' in os.environ:
            n_thread = os.environ['OMP_NUM_THREADS']