你可以用我的方法来处理。

somedict= {"person": {"name": "daniel"}}

class convertor:
    def __init__(self, dic: dict) -> object:
        self.dict = dic

        def recursive_check(obj):
            for key, value in dic.items():
                if isinstance(value, dict):
                    value= convertor(value)
                setattr(obj, key, value)
        recursive_check(self)
my_object= convertor(somedict)

print(my_object.person.name)

下面的代码来自这里，适用于嵌套字典和ide，如VS code能够提示现有的属性:

class Struct:
    def __init__(self, **kwargs):
        for key, value in kwargs.items():
            if isinstance(value, dict):
                self.__dict__[key] = Struct(**value)
            else:
                self.__dict__[key] = value


my_dict = {
    'name': 'bobbyhadz',
    'address': {
        'country': 'Country A',
        'city': 'City A',
        'codes': [1, 2, 3]
    },
}

obj = Struct(**my_dict)

如果您想了解如何加载YAML文件并将其转换为Python对象，请参阅以下要点。

class Struct(dict):
    def __getattr__(self, name):
        try:
            return self[name]
        except KeyError:
            raise AttributeError(name)

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

    def copy(self):
        return Struct(dict.copy(self))

用法:

points = Struct(x=1, y=2)
# Changing
points['x'] = 2
points.y = 1
# Accessing
points['x'], points.x, points.get('x') # 2 2 2
points['y'], points.y, points.get('y') # 1 1 1
# Accessing inexistent keys/attrs 
points['z'] # KeyError: z
points.z # AttributeError: z
# Copying
points_copy = points.copy()
points.x = 2
points_copy.x # 1

为dict寻找一个简单的包装器类，支持属性样式的键访问/赋值(点表示法)，我对现有选项不满意，原因如下。

数据类、pydantic等都很棒，但需要对内容进行静态定义。此外，它们不能在依赖dict的代码中替换dict，因为它们不共享相同的方法，并且不支持__getitem__()语法。

因此，我开发了MetaDict。它的行为完全类似于dict，但支持点表示法和IDE自动补全(如果对象被加载到RAM中)，而没有其他解决方案的缺点和潜在的名称空间冲突。所有功能和使用示例都可以在GitHub上找到(见上面的链接)。

完全披露:我是MetaDict的作者。

我在尝试其他解决方案时遇到的缺点/限制:

Addict No key autocompletion in IDE Nested key assignment cannot be turned off Newly assigned dict objects are not converted to support attribute-style key access Shadows inbuilt type Dict Prodict No key autocompletion in IDE without defining a static schema (similar to dataclass) No recursive conversion of dict objects when embedded in list or other inbuilt iterables AttrDict No key autocompletion in IDE Converts list objects to tuple behind the scenes Munch Inbuilt methods like items(), update(), etc. can be overwritten with obj.items = [1, 2, 3] No recursive conversion of dict objects when embedded in list or other inbuilt iterables EasyDict Only strings are valid keys, but dict accepts all hashable objects as keys Inbuilt methods like items(), update(), etc. can be overwritten with obj.items = [1, 2, 3] Inbuilt methods don't behave as expected: obj.pop('unknown_key', None) raises an AttributeError

注意:我在这个stackoverflow中写了一个类似的答案，这是相关的。

下面是执行SilentGhost最初建议的另一种方法:

def dict2obj(d):
  if isinstance(d, dict):
    n = {}
    for item in d:
      if isinstance(d[item], dict):
        n[item] = dict2obj(d[item])
      elif isinstance(d[item], (list, tuple)):
        n[item] = [dict2obj(elem) for elem in d[item]]
      else:
        n[item] = d[item]
    return type('obj_from_dict', (object,), n)
  else:
    return d

下面是一个使用namedtuple的嵌套就绪版本:

from collections import namedtuple

class Struct(object):
    def __new__(cls, data):
        if isinstance(data, dict):
            return namedtuple(
                'Struct', data.iterkeys()
            )(
                *(Struct(val) for val in data.values())
            )
        elif isinstance(data, (tuple, list, set, frozenset)):
            return type(data)(Struct(_) for _ in data)
        else:
            return data

=>

>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
>>> s = Struct(d)
>>> s.d
['hi', Struct(foo='bar')]
>>> s.d[0]
'hi'
>>> s.d[1].foo
'bar'