在Bunch类型对象中设置和获取属性

为了简单解析/创建 JSON，机器学习应用程序通常使用Bunch对象，例如https://github.com/dsc/bunch/blob/master/bunch/__init__.py

获取时，有一个嵌套的 EAFP 习语，它检查dict.get()函数，然后尝试使用字典方括号语法访问它，即

class Bunch(dict):
    def __getattr___(self, k):
        try:
            return object.__getattribute__(self, k)
        except AttributeError:
            try: 
                 return self[k]
            except KeyError:
                 raise AttributeError

当试图设置一个属性时，

    def __setattr__(self, k, v):
        try:
            # Throws exception if not in prototype chain
            object.__getattribute__(self, k)
        except AttributeError:
            try:
                self[k] = v
            except:
                raise AttributeError(k)
        else:
            object.__setattr__(self, k, v)

似乎sklearn实现遵循相同的思路，但检查较少https://github.com/scikit-learn/scikit-learn/blob/2beed5584/sklearn/utils/__init__.py#L61

class Bunch(dict):
    def __init__(self, **kwargs):
        super().__init__(kwargs)

    def __setattr__(self, key, value):
        self[key] = value

    def __dir__(self):
        return self.keys()

    def __getattr__(self, key):
        try:
            return self[key]
        except KeyError:
            raise AttributeError(key)

    def __setstate__(self, state):
        # Bunch pickles generated with scikit-learn 0.16.* have an non
        # empty __dict__. This causes a surprising behaviour when
        # loading these pickles scikit-learn 0.17: reading bunch.key
        # uses __dict__ but assigning to bunch.key use __setattr__ and
        # only changes bunch['key']. More details can be found at:
        # https://github.com/scikit-learn/scikit-learn/issues/6196.
        # Overriding __setstate__ to be a noop has the effect of
        # ignoring the pickled __dict__
        pass

嵌套的 EAFP 似乎有点难以维护，我的问题是：

• 有没有更简单的方法来处理 Bunch 数据对象的 get 和 set 函数？
• 是否有其他类似 Dict 的对象允许属性和键之间的可变性？
• Bunch 对象的.update()函数应该如何工作，浅拷贝还是深拷贝？或者只是让默认dict.update()做它所做的？ 理解 dict.copy() - 浅还是深？