How to use the hickle.helpers.get_type_and_data function in hickle

def load_astropy_table(h_node):
    py_type, data = get_type_and_data(h_node)
    metadata = dict(h_node.attrs.items())
    metadata.pop('type')
    metadata.pop('colnames')

    if six.PY3:
        colnames = [cn.decode('ascii') for cn in h_node.attrs["colnames"]]
    else:
        colnames = h_node.attrs["colnames"]

    t = Table(data, names=colnames, meta=metadata)
    return t

def load_astropy_quantity_dataset(h_node):
    py_type, data = get_type_and_data(h_node)
    unit = h_node.attrs["unit"][0]
    q = Quantity(data, unit)
    return q

def load_astropy_time_dataset(h_node):
    py_type, data = get_type_and_data(h_node)
    if six.PY3:
        fmt = h_node.attrs["format"][0].decode('ascii')
        scale = h_node.attrs["scale"][0].decode('ascii')
    else:
        fmt = h_node.attrs["format"][0]
        scale = h_node.attrs["scale"][0]
    q = Time(data, format=fmt, scale=scale)
    return q

def load_python_dtype_dataset(h_node):
    py_type, data = get_type_and_data(h_node)
    subtype = h_node.attrs["python_subdtype"]
    type_dict = {
        b"": int,
        b"": float,
        b"": bool,
        b"": complex
    }

    tcast = type_dict.get(subtype)
    return tcast(data)

def load_ndarray_dataset(h_node):
    py_type, data = get_type_and_data(h_node)
    return np.array(data, copy=False)

def load_list_dataset(h_node):
    py_type, data = get_type_and_data(h_node)
    py3_str_type = get_py3_string_type(h_node)

    if py3_str_type == b"":
        # Yuck. Convert numpy._bytes -> str -> bytes
        return [bytes(str(item, 'utf8'), 'utf8') for item in data]
    if py3_str_type == b"":
        return [str(item, 'utf8') for item in data]
    else:
        return list(data)

def load_astropy_constant_dataset(h_node):
    py_type, data = get_type_and_data(h_node)
    unit   = h_node.attrs["unit"][0]
    abbrev = h_node.attrs["abbrev"][0]
    name   = h_node.attrs["name"][0]
    ref    = h_node.attrs["reference"][0]
    unc    = h_node.attrs["uncertainty"][0]

    system = None
    if "system" in h_node.attrs.keys():
        system = h_node.attrs["system"][0]

    c = Constant(abbrev, name, data, unit, unc, ref, system)
    return c

def load_ndarray_masked_dataset(h_node):
    py_type, data = get_type_and_data(h_node)
    try:
        mask_path = h_node.name + "_mask"
        h_root = h_node.parent
        mask = h_root.get(mask_path)[:]
    except IndexError:
        mask = h_root.get(mask_path)
    except ValueError:
        mask = h_root.get(mask_path)
    data = np.ma.array(data, mask=mask)
    return data

def load_string_dataset(h_node):
    py_type, data = get_type_and_data(h_node)
    return str(data[0])

def load_string_dataset(h_node):
    py_type, data = get_type_and_data(h_node)
    return str(data[0])