如果你想访问dict键作为一个对象(或作为一个dict难键)，做递归，也能够更新原来的dict，你可以这样做:

class Dictate(object):
    """Object view of a dict, updating the passed in dict when values are set
    or deleted. "Dictate" the contents of a dict...: """

    def __init__(self, d):
        # since __setattr__ is overridden, self.__dict = d doesn't work
        object.__setattr__(self, '_Dictate__dict', d)

    # Dictionary-like access / updates
    def __getitem__(self, name):
        value = self.__dict[name]
        if isinstance(value, dict):  # recursively view sub-dicts as objects
            value = Dictate(value)
        return value

    def __setitem__(self, name, value):
        self.__dict[name] = value
    def __delitem__(self, name):
        del self.__dict[name]

    # Object-like access / updates
    def __getattr__(self, name):
        return self[name]

    def __setattr__(self, name, value):
        self[name] = value
    def __delattr__(self, name):
        del self[name]

    def __repr__(self):
        return "%s(%r)" % (type(self).__name__, self.__dict)
    def __str__(self):
        return str(self.__dict)

使用示例:

d = {'a': 'b', 1: 2}
dd = Dictate(d)
assert dd.a == 'b'  # Access like an object
assert dd[1] == 2  # Access like a dict
# Updates affect d
dd.c = 'd'
assert d['c'] == 'd'
del dd.a
del dd[1]
# Inner dicts are mapped
dd.e = {}
dd.e.f = 'g'
assert dd['e'].f == 'g'
assert d == {'c': 'd', 'e': {'f': 'g'}}

构建我对“python:如何动态地向类添加属性?”：

class data(object):
    def __init__(self,*args,**argd):
        self.__dict__.update(dict(*args,**argd))

def makedata(d):
    d2 = {}
    for n in d:
        d2[n] = trydata(d[n])
    return data(d2)

def trydata(o):
    if isinstance(o,dict):
        return makedata(o)
    elif isinstance(o,list):
        return [trydata(i) for i in o]
    else:
        return o

在要转换的字典上调用makedata，或者根据期望的输入调用trydata，它将输出一个数据对象。

注:

如果需要更多功能，可以向trydata添加elif。 显然，如果你想要x.a ={}或类似的东西，这是行不通的。 如果您想要一个只读版本，请使用原始答案中的类数据。

x = type('new_dict', (object,), d)

然后再加上递归，就完成了。

编辑这是我如何实现它:

>>> d
{'a': 1, 'b': {'c': 2}, 'd': ['hi', {'foo': 'bar'}]}
>>> def obj_dic(d):
    top = type('new', (object,), d)
    seqs = tuple, list, set, frozenset
    for i, j in d.items():
        if isinstance(j, dict):
            setattr(top, i, obj_dic(j))
        elif isinstance(j, seqs):
            setattr(top, i, 
                type(j)(obj_dic(sj) if isinstance(sj, dict) else sj for sj in j))
        else:
            setattr(top, i, j)
    return top

>>> x = obj_dic(d)
>>> x.a
1
>>> x.b.c
2
>>> x.d[1].foo
'bar'

class obj(object):
    def __init__(self, d):
        for k, v in d.items():
            if isinstance(k, (list, tuple)):
                setattr(self, k, [obj(x) if isinstance(x, dict) else x for x in v])
            else:
                setattr(self, k, obj(v) if isinstance(v, dict) else v)

>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> x = obj(d)
>>> x.b.c
2
>>> x.d[1].foo
'bar'

from mock import Mock
d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
my_data = Mock(**d)

# We got
# my_data.a == 1

令人惊讶的是，没有人提到邦奇。这个库专门用于提供对dict对象的属性样式访问，并完全符合OP的要求。一个示范:

>>> from bunch import bunchify
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> x = bunchify(d)
>>> x.a
1
>>> x.b.c
2
>>> x.d[1].foo
'bar'

Python 3的库可以在https://github.com/Infinidat/munch上获得-来源是codyzu

>>> from munch import DefaultMunch
>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> obj = DefaultMunch.fromDict(d)
>>> obj.b.c
2
>>> obj.a
1
>>> obj.d[1].foo
'bar'