python - 与新模型中多种类型(多态性)的关系

Question

自 2014 年以来，存在与多个对象类型的关系不可用的问题: https://github.com/robinedwards/neomodel/issues/126

现在是 2016 年，我仍然不知道关于这个关键问题的任何解决方案。

用法示例:

class AnimalNode(StructuredNode):
    tail_size = IntegerProperty()
    age = IntegerProperty()
    name = StringProperty()

class DogNode(AnimalNode):
    smell_level = IntegerProperty()

class CatNode(AnimalNode):
    vision_level = IntegerProperty()

class Owner(StructuredNode):
    animals_owned = RelationshipTo("AnimalNode", "OWNED_ANIMAL")

dog_node1 = DogNode(name="Doggy", tail_size=3, age=2, smell_level=8).save()
cat_node1 = CatNode(name="Catty", tail_size=3, age=2, vision_level=8).save()

owner = Owner().save()
owner.animals_owned.connect(dog_node1)
owner.animals_owned.connect(cat_node1)

如果我尝试访问 owner 的 animals_owned 关系，如您所料，它只会检索 AnimalNode 基类而不是其子类(DogNode或 CatNode)，所以我无法访问属性:smell_level 或 vision_level

我希望在 neomodel 中允许这样的事情:

class Owner(StructuredNode):
        animals_owned = RelationshipTo(["DogNode", "CatNode"], "OWNED_ANIMAL")

然后当我访问 owner 的 animals_owned 关系时，它将检索 DogNode 和 CatNode 类型的对象> 这样我就可以根据需要访问子类属性。

但是 connect 方法会产生以下错误:

TypeError: isinstance() arg 2 must be a type or tuple of types 

有什么方法可以优雅地在 neomodel 中实现这一点？

谢谢!

Answer 1

为了实现具有继承性的元数据模型，我最近做了类似的事情。相关代码在这里:https://github.com/diging/cidoc-crm-neo4j/blob/master/crm/models.py

基本上，我采用的方法是使用普通的多重继承来构建模型，neomodel 可以方便地将其转换为节点上相应的多个标签。这些模型都是基于 neomodel 的 StructuredNode 的抽象子类；我使用 labels() 和 inherited_labels() 实例方法添加了在类层次结构的各个级别重新实例化节点的方法。例如，此方法会将节点重新实例化为其最派生类或其层次结构中的特定类:

class HeritableStructuredNode(neomodel.StructuredNode):
    def downcast(self, target_class=None):
        """
        Re-instantiate this node as an instance its most derived derived class.
        """
        # TODO: there is probably a far more robust way to do this.
        _get_class = lambda cname: getattr(sys.modules[__name__], cname)

        # inherited_labels() only returns the labels for the current class and
        #  any super-classes, whereas labels() will return all labels on the
        #  node.
        classes = list(set(self.labels()) - set(self.inherited_labels()))

        if len(classes) == 0:
            return self     # The most derivative class is already instantiated.
        cls = None

        if target_class is None:    # Caller has not specified the target.
            if len(classes) == 1:    # Only one option, so this must be it.
                target_class = classes[0]
            else:    # Infer the most derivative class by looking for the one
                     #  with the longest method resolution order.
                class_objs = map(_get_class, classes)
                _, cls = sorted(zip(map(lambda cls: len(cls.mro()),
                                        class_objs),
                                    class_objs),
                                key=lambda (size, cls): size)[-1]
        else:    # Caller has specified a target class.
            if not isinstance(target_class, basestring):
                # In the spirit of neomodel, we might as well support both
                #  class (type) objects and class names as targets.
                target_class = target_class.__name__

            if target_class not in classes:
                raise ValueError('%s is not a sub-class of %s'\
                                 % (target_class, self.__class__.__name__))
        if cls is None:
            cls = getattr(sys.modules[__name__], target_class)
        instance = cls.inflate(self.id)

        # TODO: Can we re-instatiate without hitting the database again?
        instance.refresh()
        return instance

请注意，这之所以有效，部分原因是所有模型都在同一个命名空间中定义；如果不是这样，这可能会变得棘手。这里还有一些问题需要解决，但它可以完成工作。

使用这种方法，您可以定义与上级类的关系，然后连接节点与下级/更多派生类实例化。然后在检索时，将它们“向下转换”到它们的原始类(或层次结构中的某个类)。例如:

>>> for target in event.P11_had_participant.all():
...     original_target = target.downcast()
...     print original_target, type(original_target)
{'id': 39, 'value': u'Joe Bloggs'} <class 'neomodel.core.E21Person'>

参见 this README用于使用示例。