Python 中的适应性描述符

Question

我想在 class 上创建某种描述符 returns 代理对象。代理对象在索引时检索对象的成员并将索引应用于它们。然后它returns总和。

例如，

class NDArrayProxy:

    def __array__(self, dtype=None):
        retval = self[:]
        if dtype is not None:
            return retval.astype(dtype, copy=False)
        return retval


class ArraySumProxy(NDArrayProxy):

    def __init__(self, arrays):
        self.arrays = arrays

    @property
    def shape(self):
        return self.arrays[0].shape

    def __getitem__(self, indices):
        return np.sum([a[indices]
                       for a in self.arrays],
                      axis=0)

当我将实际数组作为成员变量时，此解决方案运行良好：

class CompartmentCluster(Cluster):

    """
    Base class for cluster that manages evidence.
    """

    def __init__(self, **kwargs):
        super().__init__(**kwargs)

        self.variable_evidence = ArraySumProxy([])

class BasicEvidenceTargetCluster(CompartmentCluster):

    # This class variable creates a Python object named basic_in on the
    # class, which implements the descriptor protocol.

    def __init__(self,
                 *,
                 **kwargs):
        super().__init__(**kwargs)

        self.basic_in = np.zeros(self.size)
        self.variable_evidence.arrays.append(self.basic_in)

class ExplanationTargetCluster(CompartmentCluster):

    """
    These clusters accept explanation evidence.
    """

    def __init__(self, **kwargs):
        super().__init__(**kwargs)

        self.explanation_in = np.zeros(self.size)
        self.variable_evidence.arrays.append(self.explanation_in)

class X(BasicEvidenceTargetCluster, ExplanationTargetCluster):
    pass

现在我已经将我的数组更改为 Python 描述符（cluster_signal 实现了返回 numpy 数组的描述符协议）：

class CompartmentCluster(Cluster):

    """
    Base class for cluster that manages evidence.
    """

    def __init__(self, **kwargs):
        super().__init__(**kwargs)

        self.variable_evidence = ArraySumProxy([])

class BasicEvidenceTargetCluster(CompartmentCluster):

    # This class variable creates a Python object named basic_in on the
    # class, which implements the descriptor protocol.

    basic_in = cluster_signal(text="Basic (in)",
                              color='bright orange')

    def __init__(self,
                 *,
                 **kwargs):
        super().__init__(**kwargs)

        self.variable_evidence.arrays.append(self.basic_in)

class ExplanationTargetCluster(CompartmentCluster):

    """
    These clusters accept explanation evidence.
    """

    explanation_in = cluster_signal(text="Explanation (in)",
                                    color='bright yellow')

    def __init__(self, **kwargs):
        super().__init__(**kwargs)

        self.variable_evidence.arrays.append(self.explanation_in)

class X(BasicEvidenceTargetCluster, ExplanationTargetCluster):
    pass

这不起作用，因为追加语句追加了描述符调用的结果。我需要的是附加一个绑定方法或类似的代理。修改我的解决方案的最佳方式是什么？简而言之：变量 basic_in 和 explanation_in 是 numpy 数组。他们现在是描述符。我想开发一些使用描述符而不是需要实际数组的 ArraySumProxy 版本。

Answer 1

当您访问一个描述符时，它会被求值，您只能得到值。由于您的描述符并不总是 return 相同的对象（我猜您无法避免它？），因此您不想在初始化代理时访问描述符。

避免访问它的最简单方法是只记住它的名称，而不是：

self.variable_evidence.arrays.append(self.basic_in)

你做到了：

self.variable_evidence.arrays.append((self, 'basic_in'))

然后，当然，variable_evidence 必须意识到这一点并执行 getattr(obj, name) 才能访问它。

另一种选择是使描述符 return 成为稍后评估的代理对象。我不知道你在做什么，但这可能是太多的代理人不合口味...

编辑

或者...您可以存储 getter:

self.variable_evidence.arrays.append(lambda: self.basic_in)

Python 中的适应性描述符

Adaptable descriptor in Python

python

python-3.x

numpy

python-descriptors