Python django.utils.functional.cached_property() Examples

def __reduce__(self):
        """
        Pickling should return the model._meta.fields instance of the field,
        not a new copy of that field. So, use the app registry to load the
        model and then the field back.
        """
        if not hasattr(self, 'model'):
            # Fields are sometimes used without attaching them to models (for
            # example in aggregation). In this case give back a plain field
            # instance. The code below will create a new empty instance of
            # class self.__class__, then update its dict with self.__dict__
            # values - so, this is very close to normal pickle.
            state = self.__dict__.copy()
            # The _get_default cached_property can't be pickled due to lambda
            # usage.
            state.pop('_get_default', None)
            return _empty, (self.__class__,), state
        return _load_field, (self.model._meta.app_label, self.model._meta.object_name,
                             self.name) 

def __reduce__(self):
        """
        Pickling should return the model._meta.fields instance of the field,
        not a new copy of that field. So, use the app registry to load the
        model and then the field back.
        """
        if not hasattr(self, 'model'):
            # Fields are sometimes used without attaching them to models (for
            # example in aggregation). In this case give back a plain field
            # instance. The code below will create a new empty instance of
            # class self.__class__, then update its dict with self.__dict__
            # values - so, this is very close to normal pickle.
            state = self.__dict__.copy()
            # The _get_default cached_property can't be pickled due to lambda
            # usage.
            state.pop('_get_default', None)
            return _empty, (self.__class__,), state
        return _load_field, (self.model._meta.app_label, self.model._meta.object_name,
                             self.name) 

def test_cached_property_reuse_different_names(self):
        """Disallow this case because the decorated function wouldn't be cached."""
        with self.assertRaises(RuntimeError) as ctx:
            class ReusedCachedProperty:
                @cached_property
                def a(self):
                    pass

                b = a

        self.assertEqual(
            str(ctx.exception.__context__),
            str(TypeError(
                "Cannot assign the same cached_property to two different "
                "names ('a' and 'b')."
            ))
        ) 

def test_cached_property(self):
        """cached_property caches its value and behaves like a property."""
        class Class:
            @cached_property
            def value(self):
                """Here is the docstring..."""
                return 1, object()

            @cached_property
            def __foo__(self):
                """Here is the docstring..."""
                return 1, object()

            def other_value(self):
                """Here is the docstring..."""
                return 1, object()

            other = cached_property(other_value, name='other')

        attrs = ['value', 'other', '__foo__']
        for attr in attrs:
            self.assertCachedPropertyWorks(attr, Class) 

def __reduce__(self):
        """
        Pickling should return the model._meta.fields instance of the field,
        not a new copy of that field. So, we use the app registry to load the
        model and then the field back.
        """
        if not hasattr(self, 'model'):
            # Fields are sometimes used without attaching them to models (for
            # example in aggregation). In this case give back a plain field
            # instance. The code below will create a new empty instance of
            # class self.__class__, then update its dict with self.__dict__
            # values - so, this is very close to normal pickle.
            state = self.__dict__.copy()
            # The _get_default cached_property can't be pickled due to lambda
            # usage.
            state.pop('_get_default', None)
            return _empty, (self.__class__,), state
        return _load_field, (self.model._meta.app_label, self.model._meta.object_name,
                             self.name) 

def _get_model_property_names(instance) -> List[str]:
    """
        Gather up properties and cached_properties which may be methods
        that were decorated. Need to inspect class versions b/c doing
        getattr on them could cause unwanted side effects.
    """
    property_names = []

    for name in dir(instance):
        try:
            attr = getattr(type(instance), name)

            if isinstance(attr, property) or isinstance(attr, cached_property):
                property_names.append(name)

        except AttributeError:
            pass

    return property_names 

def test_config(self):
        self.assertTrue(issubclass(self.ext_class, Extension))
        self.assertEqual(self.ext_class.key, self.ext_class_key)
        self.assertEqual(self.ext_class.name, self.ext_class_name)

        # Test some basic properties (just to be sure)
        self.assertIsInstance(self.ext_class.oid, ObjectIdentifier)
        self.assertIsInstance(self.ext_class.key, str)
        self.assertGreater(len(self.ext_class.key), 0)
        self.assertIsInstance(self.ext_class.name, str)
        self.assertGreater(len(self.ext_class.name), 0)

        # Test mapping dicts
        self.assertEqual(KEY_TO_EXTENSION[self.ext_class.key], self.ext_class)
        self.assertEqual(OID_TO_EXTENSION[self.ext_class.oid], self.ext_class)

        # test that the model matches
        self.assertTrue(hasattr(X509CertMixin, self.ext_class.key))
        self.assertIsInstance(getattr(X509CertMixin, self.ext_class.key), cached_property) 

def __reduce__(self):
        """
        Pickling should return the model._meta.fields instance of the field,
        not a new copy of that field. So, we use the app registry to load the
        model and then the field back.
        """
        if not hasattr(self, 'model'):
            # Fields are sometimes used without attaching them to models (for
            # example in aggregation). In this case give back a plain field
            # instance. The code below will create a new empty instance of
            # class self.__class__, then update its dict with self.__dict__
            # values - so, this is very close to normal pickle.
            state = self.__dict__.copy()
            # The _get_default cached_property can't be pickled due to lambda
            # usage.
            state.pop('_get_default', None)
            return _empty, (self.__class__,), state
        return _load_field, (self.model._meta.app_label, self.model._meta.object_name,
                             self.name) 

def __new__(mcs, name, bases, attrs):
        # We can't use it on __init__ because
        # cached_property fires on property's __get__
        for attr in mcs.CACHED_ATTRS:
            if attr in attrs:
                attrs[attr] = cached_property(attrs[attr])
        return super(WidgetMeta, mcs).__new__(mcs, name, bases, attrs) 

def _populate_directed_relation_graph(self):
        """
        This method is used by each model to find its reverse objects. As this
        method is very expensive and is accessed frequently (it looks up every
        field in a model, in every app), it is computed on first access and then
        is set as a property on every model.
        """
        related_objects_graph = defaultdict(list)

        all_models = self.apps.get_models(include_auto_created=True)
        for model in all_models:
            # Abstract model's fields are copied to child models, hence we will
            # see the fields from the child models.
            if model._meta.abstract:
                continue
            fields_with_relations = (
                f for f in model._meta._get_fields(reverse=False, include_parents=False)
                if f.is_relation and f.related_model is not None
            )
            for f in fields_with_relations:
                if not isinstance(f.rel.to, six.string_types):
                    related_objects_graph[f.rel.to._meta].append(f)

        for model in all_models:
            # Set the relation_tree using the internal __dict__. In this way
            # we avoid calling the cached property. In attribute lookup,
            # __dict__ takes precedence over a data descriptor (such as
            # @cached_property). This means that the _meta._relation_tree is
            # only called if related_objects is not in __dict__.
            related_objects = related_objects_graph[model._meta]
            model._meta.__dict__['_relation_tree'] = related_objects
        # It seems it is possible that self is not in all_models, so guard
        # against that with default for get().
        return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE) 

def test_cached_property_name_validation(self):
        msg = "%s can't be used as the name of a cached_property."
        with self.assertRaisesMessage(ValueError, msg % "'<lambda>'"):
            cached_property(lambda x: None)
        with self.assertRaisesMessage(ValueError, msg % 42):
            cached_property(str, name=42) 

def test_cached_property_mangled_error(self):
        msg = (
            'cached_property does not work with mangled methods on '
            'Python < 3.6 without the appropriate `name` argument.'
        )
        with self.assertRaisesMessage(ValueError, msg):
            @cached_property
            def __value(self):
                pass
        with self.assertRaisesMessage(ValueError, msg):
            def func(self):
                pass
            cached_property(func, name='__value') 

def test_cached_property_set_name_not_called(self):
        cp = cached_property(lambda s: None)

        class Foo:
            pass

        Foo.cp = cp
        msg = 'Cannot use cached_property instance without calling __set_name__() on it.'
        with self.assertRaisesMessage(TypeError, msg):
            Foo().cp 

def test_cached_property_auto_name(self):
        """
        cached_property caches its value and behaves like a property
        on mangled methods or when the name kwarg isn't set.
        """
        class Class:
            @cached_property
            def __value(self):
                """Here is the docstring..."""
                return 1, object()

            def other_value(self):
                """Here is the docstring..."""
                return 1, object()

            other = cached_property(other_value)
            other2 = cached_property(other_value, name='different_name')

        attrs = ['_Class__value', 'other']
        for attr in attrs:
            self.assertCachedPropertyWorks(attr, Class)

        # An explicit name is ignored.
        obj = Class()
        obj.other2
        self.assertFalse(hasattr(obj, 'different_name')) 

def assertCachedPropertyWorks(self, attr, Class):
        with self.subTest(attr=attr):
            def get(source):
                return getattr(source, attr)

            obj = Class()

            class SubClass(Class):
                pass

            subobj = SubClass()
            # Docstring is preserved.
            self.assertEqual(get(Class).__doc__, 'Here is the docstring...')
            self.assertEqual(get(SubClass).__doc__, 'Here is the docstring...')
            # It's cached.
            self.assertEqual(get(obj), get(obj))
            self.assertEqual(get(subobj), get(subobj))
            # The correct value is returned.
            self.assertEqual(get(obj)[0], 1)
            self.assertEqual(get(subobj)[0], 1)
            # State isn't shared between instances.
            obj2 = Class()
            subobj2 = SubClass()
            self.assertNotEqual(get(obj), get(obj2))
            self.assertNotEqual(get(subobj), get(subobj2))
            # It behaves like a property when there's no instance.
            self.assertIsInstance(get(Class), cached_property)
            self.assertIsInstance(get(SubClass), cached_property)
            # 'other_value' doesn't become a property.
            self.assertTrue(callable(obj.other_value))
            self.assertTrue(callable(subobj.other_value)) 

def test_cached_property(self):
        """
        cached_property caches its value and that it behaves like a property
        """
        class A:

            @cached_property
            def value(self):
                """Here is the docstring..."""
                return 1, object()

            def other_value(self):
                return 1

            other = cached_property(other_value, name='other')

        # docstring should be preserved
        self.assertEqual(A.value.__doc__, "Here is the docstring...")

        a = A()

        # check that it is cached
        self.assertEqual(a.value, a.value)

        # check that it returns the right thing
        self.assertEqual(a.value[0], 1)

        # check that state isn't shared between instances
        a2 = A()
        self.assertNotEqual(a.value, a2.value)

        # check that it behaves like a property when there's no instance
        self.assertIsInstance(A.value, cached_property)

        # check that overriding name works
        self.assertEqual(a.other, 1)
        self.assertTrue(callable(a.other_value)) 

def _populate_directed_relation_graph(self):
        """
        This method is used by each model to find its reverse objects. As this
        method is very expensive and is accessed frequently (it looks up every
        field in a model, in every app), it is computed on first access and then
        is set as a property on every model.
        """
        related_objects_graph = defaultdict(list)

        all_models = self.apps.get_models(include_auto_created=True)
        for model in all_models:
            opts = model._meta
            # Abstract model's fields are copied to child models, hence we will
            # see the fields from the child models.
            if opts.abstract:
                continue
            fields_with_relations = (
                f for f in opts._get_fields(reverse=False, include_parents=False)
                if f.is_relation and f.related_model is not None
            )
            for f in fields_with_relations:
                if not isinstance(f.remote_field.model, six.string_types):
                    related_objects_graph[f.remote_field.model._meta.concrete_model._meta].append(f)

        for model in all_models:
            # Set the relation_tree using the internal __dict__. In this way
            # we avoid calling the cached property. In attribute lookup,
            # __dict__ takes precedence over a data descriptor (such as
            # @cached_property). This means that the _meta._relation_tree is
            # only called if related_objects is not in __dict__.
            related_objects = related_objects_graph[model._meta.concrete_model._meta]
            model._meta.__dict__['_relation_tree'] = related_objects
        # It seems it is possible that self is not in all_models, so guard
        # against that with default for get().
        return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE) 

def test_config(self):
        self.assertTrue(issubclass(self.ext_class, Extension))
        self.assertEqual(self.ext_class.key, self.ext_class_key)
        self.assertEqual(self.ext_class.name, self.ext_class_name)

        # Test mapping dicts
        self.assertEqual(KEY_TO_EXTENSION[self.ext_class.key], self.ext_class)
        self.assertEqual(OID_TO_EXTENSION[self.ext_class.oid], self.ext_class)

        # test that the model matches
        self.assertTrue(hasattr(X509CertMixin, self.ext_class.key))
        self.assertIsInstance(getattr(X509CertMixin, self.ext_class.key), cached_property) 

def _populate_directed_relation_graph(self):
        """
        This method is used by each model to find its reverse objects. As this
        method is very expensive and is accessed frequently (it looks up every
        field in a model, in every app), it is computed on first access and then
        is set as a property on every model.
        """
        related_objects_graph = defaultdict(list)

        all_models = self.apps.get_models(include_auto_created=True)
        for model in all_models:
            # Abstract model's fields are copied to child models, hence we will
            # see the fields from the child models.
            if model._meta.abstract:
                continue
            fields_with_relations = (
                f for f in model._meta._get_fields(reverse=False, include_parents=False)
                if f.is_relation and f.related_model is not None
            )
            for f in fields_with_relations:
                if not isinstance(f.remote_field.model, six.string_types):
                    related_objects_graph[f.remote_field.model._meta].append(f)

        for model in all_models:
            # Set the relation_tree using the internal __dict__. In this way
            # we avoid calling the cached property. In attribute lookup,
            # __dict__ takes precedence over a data descriptor (such as
            # @cached_property). This means that the _meta._relation_tree is
            # only called if related_objects is not in __dict__.
            related_objects = related_objects_graph[model._meta]
            model._meta.__dict__['_relation_tree'] = related_objects
        # It seems it is possible that self is not in all_models, so guard
        # against that with default for get().
        return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE) 

def _populate_directed_relation_graph(self):
        """
        This method is used by each model to find its reverse objects. As this
        method is very expensive and is accessed frequently (it looks up every
        field in a model, in every app), it is computed on first access and then
        is set as a property on every model.
        """
        related_objects_graph = defaultdict(list)

        all_models = self.apps.get_models(include_auto_created=True)
        for model in all_models:
            opts = model._meta
            # Abstract model's fields are copied to child models, hence we will
            # see the fields from the child models.
            if opts.abstract:
                continue
            fields_with_relations = (
                f for f in opts._get_fields(reverse=False, include_parents=False)
                if f.is_relation and f.related_model is not None
            )
            for f in fields_with_relations:
                if not isinstance(f.remote_field.model, six.string_types):
                    related_objects_graph[f.remote_field.model._meta.concrete_model._meta].append(f)

        for model in all_models:
            # Set the relation_tree using the internal __dict__. In this way
            # we avoid calling the cached property. In attribute lookup,
            # __dict__ takes precedence over a data descriptor (such as
            # @cached_property). This means that the _meta._relation_tree is
            # only called if related_objects is not in __dict__.
            related_objects = related_objects_graph[model._meta.concrete_model._meta]
            model._meta.__dict__['_relation_tree'] = related_objects
        # It seems it is possible that self is not in all_models, so guard
        # against that with default for get().
        return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE) 

def access_token(self):
        """
        Returns the access token for this service.

        We don't use a cached_property decorator because we aren't sure how to
        set custom expiration dates for those.

        Returns:
            str: JWT access token
        """
        key = 'oauth2_access_token'
        access_token = cache.get(key)

        if not access_token:
            url = '{root}/access_token'.format(root=self.oauth2_provider_url)
            access_token, expiration_datetime = EdxRestApiClient.get_oauth_access_token(
                url,
                self.oauth2_client_id,
                self.oauth2_client_secret,
                token_type='jwt'
            )

            expires = (expiration_datetime - datetime.datetime.utcnow()).seconds
            cache.set(key, access_token, expires)

        return access_token 

def _populate_directed_relation_graph(self):
        """
        This method is used by each model to find its reverse objects. As this
        method is very expensive and is accessed frequently (it looks up every
        field in a model, in every app), it is computed on first access and then
        is set as a property on every model.
        """
        related_objects_graph = defaultdict(list)

        all_models = self.apps.get_models(include_auto_created=True)
        for model in all_models:
            opts = model._meta
            # Abstract model's fields are copied to child models, hence we will
            # see the fields from the child models.
            if opts.abstract:
                continue
            fields_with_relations = (
                f for f in opts._get_fields(reverse=False, include_parents=False)
                if f.is_relation and f.related_model is not None
            )
            for f in fields_with_relations:
                if not isinstance(f.remote_field.model, str):
                    related_objects_graph[f.remote_field.model._meta.concrete_model._meta].append(f)

        for model in all_models:
            # Set the relation_tree using the internal __dict__. In this way
            # we avoid calling the cached property. In attribute lookup,
            # __dict__ takes precedence over a data descriptor (such as
            # @cached_property). This means that the _meta._relation_tree is
            # only called if related_objects is not in __dict__.
            related_objects = related_objects_graph[model._meta.concrete_model._meta]
            model._meta.__dict__['_relation_tree'] = related_objects
        # It seems it is possible that self is not in all_models, so guard
        # against that with default for get().
        return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE) 

def _populate_directed_relation_graph(self):
        """
        This method is used by each model to find its reverse objects. As this
        method is very expensive and is accessed frequently (it looks up every
        field in a model, in every app), it is computed on first access and then
        is set as a property on every model.
        """
        related_objects_graph = defaultdict(list)

        all_models = self.apps.get_models(include_auto_created=True)
        for model in all_models:
            opts = model._meta
            # Abstract model's fields are copied to child models, hence we will
            # see the fields from the child models.
            if opts.abstract:
                continue
            fields_with_relations = (
                f for f in opts._get_fields(reverse=False, include_parents=False)
                if f.is_relation and f.related_model is not None
            )
            for f in fields_with_relations:
                if not isinstance(f.remote_field.model, str):
                    related_objects_graph[f.remote_field.model._meta.concrete_model._meta].append(f)

        for model in all_models:
            # Set the relation_tree using the internal __dict__. In this way
            # we avoid calling the cached property. In attribute lookup,
            # __dict__ takes precedence over a data descriptor (such as
            # @cached_property). This means that the _meta._relation_tree is
            # only called if related_objects is not in __dict__.
            related_objects = related_objects_graph[model._meta.concrete_model._meta]
            model._meta.__dict__['_relation_tree'] = related_objects
        # It seems it is possible that self is not in all_models, so guard
        # against that with default for get().
        return self.__dict__.get('_relation_tree', EMPTY_RELATION_TREE) 

def get_prefetcher(instance, through_attr, to_attr):
    """
    For the attribute 'through_attr' on the given instance, finds
    an object that has a get_prefetch_queryset().
    Returns a 4 tuple containing:
    (the object with get_prefetch_queryset (or None),
     the descriptor object representing this relationship (or None),
     a boolean that is False if the attribute was not found at all,
     a boolean that is True if the attribute has already been fetched)
    """
    prefetcher = None
    is_fetched = False

    # For singly related objects, we have to avoid getting the attribute
    # from the object, as this will trigger the query. So we first try
    # on the class, in order to get the descriptor object.
    rel_obj_descriptor = getattr(instance.__class__, through_attr, None)
    if rel_obj_descriptor is None:
        attr_found = hasattr(instance, through_attr)
    else:
        attr_found = True
        if rel_obj_descriptor:
            # singly related object, descriptor object has the
            # get_prefetch_queryset() method.
            if hasattr(rel_obj_descriptor, 'get_prefetch_queryset'):
                prefetcher = rel_obj_descriptor
                if rel_obj_descriptor.is_cached(instance):
                    is_fetched = True
            else:
                # descriptor doesn't support prefetching, so we go ahead and get
                # the attribute on the instance rather than the class to
                # support many related managers
                rel_obj = getattr(instance, through_attr)
                if hasattr(rel_obj, 'get_prefetch_queryset'):
                    prefetcher = rel_obj
                if through_attr != to_attr:
                    # Special case cached_property instances because hasattr
                    # triggers attribute computation and assignment.
                    if isinstance(getattr(instance.__class__, to_attr, None), cached_property):
                        is_fetched = to_attr in instance.__dict__
                    else:
                        is_fetched = hasattr(instance, to_attr)
                else:
                    is_fetched = through_attr in instance._prefetched_objects_cache
    return prefetcher, rel_obj_descriptor, attr_found, is_fetched 

def get_prefetcher(instance, through_attr, to_attr):
    """
    For the attribute 'through_attr' on the given instance, finds
    an object that has a get_prefetch_queryset().
    Returns a 4 tuple containing:
    (the object with get_prefetch_queryset (or None),
     the descriptor object representing this relationship (or None),
     a boolean that is False if the attribute was not found at all,
     a boolean that is True if the attribute has already been fetched)
    """
    prefetcher = None
    is_fetched = False

    # For singly related objects, we have to avoid getting the attribute
    # from the object, as this will trigger the query. So we first try
    # on the class, in order to get the descriptor object.
    rel_obj_descriptor = getattr(instance.__class__, through_attr, None)
    if rel_obj_descriptor is None:
        attr_found = hasattr(instance, through_attr)
    else:
        attr_found = True
        if rel_obj_descriptor:
            # singly related object, descriptor object has the
            # get_prefetch_queryset() method.
            if hasattr(rel_obj_descriptor, 'get_prefetch_queryset'):
                prefetcher = rel_obj_descriptor
                if rel_obj_descriptor.is_cached(instance):
                    is_fetched = True
            else:
                # descriptor doesn't support prefetching, so we go ahead and get
                # the attribute on the instance rather than the class to
                # support many related managers
                rel_obj = getattr(instance, through_attr)
                if hasattr(rel_obj, 'get_prefetch_queryset'):
                    prefetcher = rel_obj
                if through_attr != to_attr:
                    # Special case cached_property instances because hasattr
                    # triggers attribute computation and assignment.
                    if isinstance(getattr(instance.__class__, to_attr, None), cached_property):
                        is_fetched = to_attr in instance.__dict__
                    else:
                        is_fetched = hasattr(instance, to_attr)
                else:
                    is_fetched = through_attr in instance._prefetched_objects_cache
    return prefetcher, rel_obj_descriptor, attr_found, is_fetched 

def get_prefetcher(instance, through_attr, to_attr):
    """
    For the attribute 'through_attr' on the given instance, find
    an object that has a get_prefetch_queryset().
    Return a 4 tuple containing:
    (the object with get_prefetch_queryset (or None),
     the descriptor object representing this relationship (or None),
     a boolean that is False if the attribute was not found at all,
     a boolean that is True if the attribute has already been fetched)
    """
    prefetcher = None
    is_fetched = False

    # For singly related objects, we have to avoid getting the attribute
    # from the object, as this will trigger the query. So we first try
    # on the class, in order to get the descriptor object.
    rel_obj_descriptor = getattr(instance.__class__, through_attr, None)
    if rel_obj_descriptor is None:
        attr_found = hasattr(instance, through_attr)
    else:
        attr_found = True
        if rel_obj_descriptor:
            # singly related object, descriptor object has the
            # get_prefetch_queryset() method.
            if hasattr(rel_obj_descriptor, 'get_prefetch_queryset'):
                prefetcher = rel_obj_descriptor
                if rel_obj_descriptor.is_cached(instance):
                    is_fetched = True
            else:
                # descriptor doesn't support prefetching, so we go ahead and get
                # the attribute on the instance rather than the class to
                # support many related managers
                rel_obj = getattr(instance, through_attr)
                if hasattr(rel_obj, 'get_prefetch_queryset'):
                    prefetcher = rel_obj
                if through_attr != to_attr:
                    # Special case cached_property instances because hasattr
                    # triggers attribute computation and assignment.
                    if isinstance(getattr(instance.__class__, to_attr, None), cached_property):
                        is_fetched = to_attr in instance.__dict__
                    else:
                        is_fetched = hasattr(instance, to_attr)
                else:
                    is_fetched = through_attr in instance._prefetched_objects_cache
    return prefetcher, rel_obj_descriptor, attr_found, is_fetched 

def get_prefetcher(instance, through_attr, to_attr):
    """
    For the attribute 'through_attr' on the given instance, find
    an object that has a get_prefetch_queryset().
    Return a 4 tuple containing:
    (the object with get_prefetch_queryset (or None),
     the descriptor object representing this relationship (or None),
     a boolean that is False if the attribute was not found at all,
     a boolean that is True if the attribute has already been fetched)
    """
    prefetcher = None
    is_fetched = False

    # For singly related objects, we have to avoid getting the attribute
    # from the object, as this will trigger the query. So we first try
    # on the class, in order to get the descriptor object.
    rel_obj_descriptor = getattr(instance.__class__, through_attr, None)
    if rel_obj_descriptor is None:
        attr_found = hasattr(instance, through_attr)
    else:
        attr_found = True
        if rel_obj_descriptor:
            # singly related object, descriptor object has the
            # get_prefetch_queryset() method.
            if hasattr(rel_obj_descriptor, 'get_prefetch_queryset'):
                prefetcher = rel_obj_descriptor
                if rel_obj_descriptor.is_cached(instance):
                    is_fetched = True
            else:
                # descriptor doesn't support prefetching, so we go ahead and get
                # the attribute on the instance rather than the class to
                # support many related managers
                rel_obj = getattr(instance, through_attr)
                if hasattr(rel_obj, 'get_prefetch_queryset'):
                    prefetcher = rel_obj
                if through_attr != to_attr:
                    # Special case cached_property instances because hasattr
                    # triggers attribute computation and assignment.
                    if isinstance(getattr(instance.__class__, to_attr, None), cached_property):
                        is_fetched = to_attr in instance.__dict__
                    else:
                        is_fetched = hasattr(instance, to_attr)
                else:
                    is_fetched = through_attr in instance._prefetched_objects_cache
    return prefetcher, rel_obj_descriptor, attr_found, is_fetched