我不满意那些被标记和点赞的答案，所以这里有一个简单而通用的解决方案，用于将json风格的嵌套数据结构(由字典和列表组成)转换为普通对象的层次结构:

# tested in: Python 3.8
from collections import abc
from typings import Any, Iterable, Mapping, Union

class DataObject:
    def __repr__(self):
        return str({k: v for k, v in vars(self).items()})

def data_to_object(data: Union[Mapping[str, Any], Iterable]) -> object:
    """
    Example
    -------
    >>> data = {
    ...     "name": "Bob Howard",
    ...     "positions": [{"department": "ER", "manager_id": 13}],
    ... }
    ... data_to_object(data).positions[0].manager_id
    13
    """
    if isinstance(data, abc.Mapping):
        r = DataObject()
        for k, v in data.items():
            if type(v) is dict or type(v) is list:
                setattr(r, k, data_to_object(v))
            else:
                setattr(r, k, v)
        return r
    elif isinstance(data, abc.Iterable):
        return [data_to_object(e) for e in data]
    else:
        return data

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'

X.__dict__.update (d)应该没问题。

这可以让你开始:

class dict2obj(object):
    def __init__(self, d):
        self.__dict__['d'] = d

    def __getattr__(self, key):
        value = self.__dict__['d'][key]
        if type(value) == type({}):
            return dict2obj(value)

        return value

d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}

x = dict2obj(d)
print x.a
print x.b.c
print x.d[1].foo

它还不适用于列表。你必须将列表包装在UserList中，并重载__getitem__来包装字典。

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'

# Applies to Python-3 Standard Library
class Struct(object):
    def __init__(self, data):
        for name, value in data.items():
            setattr(self, name, self._wrap(value))

    def _wrap(self, value):
        if isinstance(value, (tuple, list, set, frozenset)): 
            return type(value)([self._wrap(v) for v in value])
        else:
            return Struct(value) if isinstance(value, dict) else value


# Applies to Python-2 Standard Library
class Struct(object):
    def __init__(self, data):
        for name, value in data.iteritems():
            setattr(self, name, self._wrap(value))

    def _wrap(self, value):
        if isinstance(value, (tuple, list, set, frozenset)): 
            return type(value)([self._wrap(v) for v in value])
        else:
            return Struct(value) if isinstance(value, dict) else value

可以用于任何深度的任何序列/字典/值结构。