How to use the jsonpickle.util.is_type function in jsonpickle

# We handle tuples and sets by encoding them in a "(tuple|set)dict"
        if util.is_tuple(obj):
            if not self.unpicklable:
                return list_recurse
            return lambda obj: {tags.TUPLE: [self._flatten(v) for v in obj]}

        if util.is_set(obj):
            if not self.unpicklable:
                return list_recurse
            return lambda obj: {tags.SET: [self._flatten(v) for v in obj]}

        if util.is_dictionary(obj):
            return self._flatten_dict_obj

        if util.is_type(obj):
            return _mktyperef

        if util.is_object(obj):
            return self._ref_obj_instance

        if util.is_module_function(obj):
            return self._flatten_function

        # instance methods, lambdas, old style classes...
        self._pickle_warning(obj)
        return None

# We handle tuples and sets by encoding them in a "(tuple|set)dict"
        if util.is_tuple(obj):
            if not self.unpicklable:
                return list_recurse
            return lambda obj: {tags.TUPLE: [self._flatten(v) for v in obj]}

        if util.is_set(obj):
            if not self.unpicklable:
                return list_recurse
            return lambda obj: {tags.SET: [self._flatten(v) for v in obj]}

        if util.is_dictionary(obj):
            return self._flatten_dict_obj

        if util.is_type(obj):
            return _mktyperef

        if util.is_object(obj):
            return self._ref_obj_instance

        if util.is_module_function(obj):
            return self._flatten_function

        # instance methods, lambdas, old style classes...
        self._pickle_warning(obj)
        return None

def _flatten_dict_obj(self, obj, data=None):
        """Recursively call flatten() and return json-friendly dict
        """
        if data is None:
            data = obj.__class__()

        flatten = self._flatten_key_value_pair
        for k, v in sorted(obj.items(), key=util.itemgetter):
            flatten(k, v, data)

        # the collections.defaultdict protocol
        if hasattr(obj, 'default_factory') and callable(obj.default_factory):
            factory = obj.default_factory
            if util.is_type(factory):
                # Reference the class/type
                value = _mktyperef(factory)
            else:
                # The factory is not a type and could reference e.g. functions
                # or even the object instance itself, which creates a cycle.
                if self._mkref(factory):
                    # We've never seen this object before so pickle it in-place.
                    # Create an instance from the factory and assume that the
                    # resulting instance is a suitable examplar.
                    value = self._flatten_obj_instance(handlers.CloneFactory(factory()))
                else:
                    # We've seen this object before.
                    # Break the cycle by emitting a reference.
                    value = self._getref(factory)
            data['default_factory'] = value

def get(self, cls_or_name, default=None):
        """
        :param cls_or_name: the type or its fully qualified name
        :param default: default value, if a matching handler is not found

        Looks up a handler by type reference or its fully
        qualified name. If a direct match
        is not found, the search is performed over all
        handlers registered with base=True.
        """
        handler = self._handlers.get(cls_or_name)
        # attempt to find a base class
        if handler is None and util.is_type(cls_or_name):
            for cls, base_handler in self._base_handlers.items():
                if issubclass(cls_or_name, cls):
                    return base_handler
        return default if handler is None else handler

:param cls: The custom object class to handle
        :param handler: The custom handler class (if None, a decorator wrapper is returned)
        :param base: Indicates whether the handler should be registered for all subclasses

        This function can be also used as a decorator by omitting the `handler` argument:

        @jsonpickle.handlers.register(Foo, base=True)
        class FooHandler(jsonpickle.handlers.BaseHandler):
            pass
        """
        if handler is None:
            def _register(handler_cls):
                self.register(cls, handler=handler_cls, base=base)
                return handler_cls
            return _register
        if not util.is_type(cls):
            raise TypeError('{0!r} is not a class/type'.format(cls))
        # store both the name and the actual type for the ugly cases like
        # _sre.SRE_Pattern that cannot be loaded back directly
        self._handlers[util.importable_name(cls)] = self._handlers[cls] = handler
        if base:
            # only store the actual type for subclass checking
            self._base_handlers[cls] = handler

def _flatten_dict_obj(self, obj, data=None):
        """Recursively call flatten() and return json-friendly dict
        """
        if data is None:
            data = obj.__class__()

        flatten = self._flatten_key_value_pair
        for k, v in sorted(obj.items(), key=util.itemgetter):
            flatten(k, v, data)

        # the collections.defaultdict protocol
        if hasattr(obj, 'default_factory') and callable(obj.default_factory):
            factory = obj.default_factory
            if util.is_type(factory):
                # Reference the class/type
                value = _mktyperef(factory)
            else:
                # The factory is not a type and could reference e.g. functions
                # or even the object instance itself, which creates a cycle.
                if self._mkref(factory):
                    # We've never seen this object before so pickle it in-place.
                    # Create an instance from the factory and assume that the
                    # resulting instance is a suitable examplar.
                    value = self._flatten(handlers.CloneFactory(factory()))
                else:
                    # We've seen this object before.
                    # Break the cycle by emitting a reference.
                    value = self._getref(factory)
            data['default_factory'] = value

def _flatten_dict_obj(self, obj, data=None):
        """Recursively call flatten() and return json-friendly dict
        """
        if data is None:
            data = obj.__class__()

        flatten = self._flatten_key_value_pair
        for k, v in sorted(obj.items(), key=util.itemgetter):
            flatten(k, v, data)

        # the collections.defaultdict protocol
        if hasattr(obj, 'default_factory') and callable(obj.default_factory):
            factory = obj.default_factory
            if util.is_type(factory):
                # Reference the type
                value = _mktyperef(factory)
            else:
                # Create an instance from the factory and assume that the
                # resulting instance is a suitable examplar.
                value = self._flatten(handlers.CloneFactory(factory()))
            data['default_factory'] = value

        return data

return self._pop(obj)

        if util.is_list(obj):
            return self._pop([ self.flatten(v) for v in obj ])

        # We handle tuples and sets by encoding them in a "(tuple|set)dict"
        if util.is_tuple(obj):
            return self._pop({tags.TUPLE: [ self.flatten(v) for v in obj ]})

        if util.is_set(obj):
            return self._pop({tags.SET: [ self.flatten(v) for v in obj ]})

        if util.is_dictionary(obj):
            return self._pop(self._flatten_dict_obj(obj, obj.__class__()))

        if util.is_type(obj):
            return self._pop(_mktyperef(obj))

        if util.is_object(obj):
            if self._mkref(obj):
                # We've never seen this object so return its
                # json representation.
                return self._pop(self._flatten_obj_instance(obj))
            else:
                # We've seen this object before so place an object
                # reference tag in the data. This avoids infinite recursion
                # when processing cyclical objects.
                return self._pop(self._getref(obj))

            return self._pop(data)
        # else, what else? (methods, functions, old style classes...)

# We handle tuples and sets by encoding them in a "(tuple|set)dict"
        if util.is_tuple(obj):
            if not self.unpicklable:
                return list_recurse
            return lambda obj: {tags.TUPLE: [self._flatten(v) for v in obj]}

        if util.is_set(obj):
            if not self.unpicklable:
                return list_recurse
            return lambda obj: {tags.SET: [self._flatten(v) for v in obj]}

        if util.is_dictionary(obj):
            return self._flatten_dict_obj

        if util.is_type(obj):
            return _mktyperef

        if util.is_object(obj):
            return self._ref_obj_instance

        if util.is_module_function(obj):
            return self._flatten_function

        # instance methods, lambdas, old style classes...
        self._pickle_warning(obj)
        return None