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')}

这里给出的答案没有返回正确的对象类型，因此我在下面创建了这些方法。如果你试图向给定JSON中不存在的类中添加更多字段，它们也会失败:

def dict_to_class(class_name: Any, dictionary: dict) -> Any:
    instance = class_name()
    for key in dictionary.keys():
        setattr(instance, key, dictionary[key])
    return instance


def json_to_class(class_name: Any, json_string: str) -> Any:
    dict_object = json.loads(json_string)
    return dict_to_class(class_name, dict_object)

你可以试试这个:

class User(object):
    def __init__(self, name, username):
        self.name = name
        self.username = username

import json
j = json.loads(your_json)
u = User(**j)

只需创建一个新对象，并将参数作为映射传递。

你也可以有一个带有对象的JSON:

import json
class Address(object):
    def __init__(self, street, number):
        self.street = street
        self.number = number

    def __str__(self):
        return "{0} {1}".format(self.street, self.number)

class User(object):
    def __init__(self, name, address):
        self.name = name
        self.address = Address(**address)

    def __str__(self):
        return "{0} ,{1}".format(self.name, self.address)

if __name__ == '__main__':
    js = '''{"name":"Cristian", "address":{"street":"Sesame","number":122}}'''
    j = json.loads(js)
    print(j)
    u = User(**j)
    print(u)

这似乎是一个XY问题(问A实际问题在哪里B)。

问题的根源是:如何有效地引用/修改深嵌套的JSON结构，而不必做obj['foo']['bar'][42]['quux']，这带来了键入挑战，代码膨胀问题，可读性问题和错误捕获问题?

使用抢

from glom import glom

# Basic deep get

data = {'a': {'b': {'c': 'd'}}}

print(glom(data, 'a.b.c'))

它还将处理列表项:

我已经对一个简单的实现进行了基准测试:

def extract(J, levels):
    # Twice as fast as using glom
    for level in levels.split('.'):
        J = J[int(level) if level.isnumeric() else level]
    return J

．.． 并且在复杂的JSON对象上返回0.14ms，而朴素的impl则返回0.06ms。

它还可以处理复杂的查询，例如取出所有foo.bar.记录，其中.name == 'Joe Bloggs'

编辑:

另一种性能方法是递归地使用覆盖__getitem__和__getattr__的类:

class Ob:
    def __init__(self, J):
        self.J = J

    def __getitem__(self, index):
        return Ob(self.J[index])

    def __getattr__(self, attr):
        value = self.J.get(attr, None)
        return Ob(value) if type(value) in (list, dict) else value

现在你可以做:

ob = Ob(J)

# if you're fetching a final raw value (not list/dict
ob.foo.bar[42].quux.leaf

# for intermediate values
ob.foo.bar[42].quux.J

这一基准测试也出奇地好。与我之前的天真冲动相当。如果有人能找到一种方法来整理非叶查询的访问，请留下评论!

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。

使用python 3.7，我发现下面的代码非常简单有效。在本例中，将JSON从文件加载到字典中:

class Characteristic:
    def __init__(self, characteristicName, characteristicUUID):
        self.characteristicName = characteristicName
        self.characteristicUUID = characteristicUUID


class Service:
    def __init__(self, serviceName, serviceUUID, characteristics):
        self.serviceName = serviceName
        self.serviceUUID = serviceUUID
        self.characteristics = characteristics

class Definitions:
    def __init__(self, services):
        self.services = []
        for service in services:
            self.services.append(Service(**service))


def main():
    parser = argparse.ArgumentParser(
        prog="BLEStructureGenerator",
        description="Taking in a JSON input file which lists all of the services, "
                    "characteristics and encoded properties. The encoding takes in "
                    "another optional template services and/or characteristics "
                    "file where the JSON file contents are applied to the templates.",
        epilog="Copyright Brown & Watson International"
    )

    parser.add_argument('definitionfile',
                        type=argparse.FileType('r', encoding='UTF-8'),
                        help="JSON file which contains the list of characteristics and "
                             "services in the required format")
    parser.add_argument('-s', '--services',
                        type=argparse.FileType('r', encoding='UTF-8'),
                        help="Services template file to be used for each service in the "
                             "JSON file list")
    parser.add_argument('-c', '--characteristics',
                        type=argparse.FileType('r', encoding='UTF-8'),
                        help="Characteristics template file to be used for each service in the "
                             "JSON file list")

    args = parser.parse_args()
    definition_dict = json.load(args.definitionfile)
    definitions = Definitions(**definition_dict)