更新

在Python3中，你可以使用SimpleNamespace和object_hook在一行中完成:

import json
from types import SimpleNamespace

data = '{"name": "John Smith", "hometown": {"name": "New York", "id": 123}}'

# Parse JSON into an object with attributes corresponding to dict keys.
x = json.loads(data, object_hook=lambda d: SimpleNamespace(**d))
print(x.name, x.hometown.name, x.hometown.id)

旧答案(Python2)

在Python2中，你可以使用namedtuple和object_hook在一行中完成(但对于嵌套对象非常慢):

import json
from collections import namedtuple

data = '{"name": "John Smith", "hometown": {"name": "New York", "id": 123}}'

# Parse JSON into an object with attributes corresponding to dict keys.
x = json.loads(data, object_hook=lambda d: namedtuple('X', d.keys())(*d.values()))
print x.name, x.hometown.name, x.hometown.id

或者，为了便于重用:

def _json_object_hook(d): return namedtuple('X', d.keys())(*d.values())
def json2obj(data): return json.loads(data, object_hook=_json_object_hook)

x = json2obj(data)

如果希望它处理不是很好的属性名称的键，请检查namedtuple的rename参数。

这是我的办法。

特性

支持类型提示 如果缺少键则引发错误。 跳过数据中的额外值

import typing

class User:
    name: str
    age: int

    def __init__(self, data: dict):
        for k, _ in typing.get_type_hints(self).items():
            setattr(self, k, data[k])

data = {
    "name": "Susan",
    "age": 18
}

user = User(data)
print(user.name, user.age)

# Output: Susan 18

因此，我正在寻找一种不需要大量自定义反序列化代码就能解组任意类型(想想数据类的字典，或者数据类数组的字典的字典)的方法。

这是我的方法:

import json
from dataclasses import dataclass, make_dataclass

from dataclasses_json import DataClassJsonMixin, dataclass_json


@dataclass_json
@dataclass
class Person:
    name: str


def unmarshal_json(data, t):
    Unmarhsal = make_dataclass('Unmarhsal', [('res', t)],
                               bases=(DataClassJsonMixin,))
    d = json.loads(data)
    out = Unmarhsal.from_dict({"res": d})
    return out.res


unmarshalled = unmarshal_json('{"1": {"name": "john"} }', dict[str, Person])
print(unmarshalled)

打印:{'1':Person(name='john')}

对于复杂的对象，可以使用JSON Pickle

Python库，用于将任意对象图序列化为JSON。 它几乎可以接受任何Python对象并将对象转换为JSON。 此外，它还可以将对象重新构造回Python。

你可以使用

x = Map(json.loads(response))
x.__class__ = MyClass

在哪里

class Map(dict):
    def __init__(self, *args, **kwargs):
        super(Map, self).__init__(*args, **kwargs)
        for arg in args:
            if isinstance(arg, dict):
                for k, v in arg.iteritems():
                    self[k] = v
                    if isinstance(v, dict):
                        self[k] = Map(v)

        if kwargs:
            # for python 3 use kwargs.items()
            for k, v in kwargs.iteritems():
                self[k] = v
                if isinstance(v, dict):
                    self[k] = Map(v)

    def __getattr__(self, attr):
        return self.get(attr)

    def __setattr__(self, key, value):
        self.__setitem__(key, value)

    def __setitem__(self, key, value):
        super(Map, self).__setitem__(key, value)
        self.__dict__.update({key: value})

    def __delattr__(self, item):
        self.__delitem__(item)

    def __delitem__(self, key):
        super(Map, self).__delitem__(key)
        del self.__dict__[key]

对于通用的、经得起未来考验的解决方案。

我正在寻找一个与recordclass一起工作的解决方案。RecordClass，支持嵌套对象，可用于json序列化和json反序列化。

扩展DS的答案，扩展BeneStr的解决方案，我想出了以下似乎有效的方法:

代码:

import json
import recordclass

class NestedRec(recordclass.RecordClass):
    a : int = 0
    b : int = 0

class ExampleRec(recordclass.RecordClass):
    x : int       = None
    y : int       = None
    nested : NestedRec = NestedRec()

class JsonSerializer:
    @staticmethod
    def dumps(obj, ensure_ascii=True, indent=None, sort_keys=False):
        return json.dumps(obj, default=JsonSerializer.__obj_to_dict, ensure_ascii=ensure_ascii, indent=indent, sort_keys=sort_keys)

    @staticmethod
    def loads(s, klass):
        return JsonSerializer.__dict_to_obj(klass, json.loads(s))

    @staticmethod
    def __obj_to_dict(obj):
        if hasattr(obj, "_asdict"):
            return obj._asdict()
        else:
            return json.JSONEncoder().default(obj)

    @staticmethod
    def __dict_to_obj(klass, s_dict):
        kwargs = {
            key : JsonSerializer.__dict_to_obj(cls, s_dict[key]) if hasattr(cls,'_asdict') else s_dict[key] \
                for key,cls in klass.__annotations__.items() \
                    if s_dict is not None and key in s_dict
        }
        return klass(**kwargs)

用法:

example_0 = ExampleRec(x = 10, y = 20, nested = NestedRec( a = 30, b = 40 ) )

#Serialize to JSON

json_str = JsonSerializer.dumps(example_0)
print(json_str)
#{
#  "x": 10,
#  "y": 20,
#  "nested": {
#    "a": 30,
#    "b": 40
#  }
#}

# Deserialize from JSON
example_1 = JsonSerializer.loads(json_str, ExampleRec)
example_1.x += 1
example_1.y += 1
example_1.nested.a += 1
example_1.nested.b += 1

json_str = JsonSerializer.dumps(example_1)
print(json_str)
#{
#  "x": 11,
#  "y": 21,
#  "nested": {
#    "a": 31,
#    "b": 41
#  }
#}